CRANIAL VARIATION OF CONTEMPORARY EAST ASIANS IN A GLOBAL CONTEXT

H. GREEN

A thesis submitted in fulfillment of the requirements for the degree of Doctor of Philosophy

Department of Anatomy School of Medical Sciences University of New South Wales August 2007

i ORIGINALITY STATEMENT

I hereby declare that this submission is my own work and to the best of my knowledge it contains no materials previously published or written by another person, or substantial proportions of material which have been accepted for the award of any other degree or diploma at UNSW or any other educational institution, except where due acknowledgment is made in the thesis. Any contribution made to the research by others, with whom I have worked at UNSW or elsewhere, is explicitly acknowledged in the thesis. I also declare that the intellectual content of this thesis is the product of my own work, except to the extent that assistance from others in the project’s design and conception or in style, presentation and linguistic expression is acknowledged.

Signed ......

Date ......

ii Abstract

The current study examines cranial variation of contemporary East Asians with an aim to comprehensively describe and define the morphology of people in this region. In doing so, a better understanding of the causes of variation within East Asia and compared to other geographic populations is sought. The study encompasses a broad range of samples from Northeast Asia to island Southeast Asia. Traditional linear and angular data and analytical methods (e.g Box and Whisker, Principal Components Analysis) were used to assess cranial variation. Thus the results may be compared to published studies using traditional craniometric approaches. Innovative geometric morphometric data collection and analysis techniques are also used here for the first time. Results show East Asians are distinguishable from non-Asians on the basis of their tall, round, vault, shorter cranial length, tall faces that are flattened in the upper- and mid-facial regions, short malars (anteroposterior length), narrow interorbital breadth and orthognathism. A north-south East Asian cline was also detected, with the northern samples exhibiting tall, orthognathic faces, and a long low vault. This long, low vault shape is in contradiction to the purported shape of cold-climate adapted populations. Southern East Asians possess a tall, rounded vault and a short, projecting (prognathic) face. Island Southeast Asians inhabiting the Andaman and Nicobar Islands exhibit a ‘mixed’ morphology, possessing the southern East Asian facial form, but the long, low vault seen in northern East Asian samples. The long, low vault also characterises non- Asian samples from Australia, Africa and Melanesia. Shape differences were significantly associated with latitude, explaining most of the variation. The identification of ancestral East Asian features in recent samples suggests phylogenetics may also be contributing to variation in part. The study concludes that there is clear evidence for geographical variation among modern East Asians, some if it being continuous (clinal) and some discontinuous. Importantly, much of the variation reflects adaptation to climate, with a phylogenetic component also recognised. The study contributes to our understanding of human evolution in a region that today constitutes around half of the world’s population.

iii Acknowledgments

Firstly, I would like to thank my supervisor, Dr Darren Curnoe, for your guidance, advice, patience and financial support. I have learned and experienced so much, and been given so many great opportunities throughout the course of this PhD, and for that, I thank you. I look forward to the next big project (and all the not-so-big ones in between). To Professor Ken Ashwell and staff in the Department of Anatomy UNSW, for all your support. Also, to Dr Alan Thorne, for your role in getting the project off the ground, and your financial support.

To Associate Professor Nick Milne of the University of Western Australia for all your help with the three-dimensional statistics and providing me with additional software.

To the curators and assistants in the many museums around the world from which I gathered my data. In no particular order: Phillipe Mennecier of Musée de l’Homme, Paris; Rob Kruszynski of the Natural History Museum, London; Maggie Bellatti of the Duckworth Museum, Cambridge; Dr Ian Tattersall, Gary Sawyer and Will Harcourt- Smith of the American Museum of Natural History, New York.

This study was funded by the Australian Research Council. I also wish to thank The School of Medical Sciences, UNSW for funding several conference trips.

To my friends at UNSW: Erica Danielsen, Julien Louys and Andy Herries, for your words of ‘wisdom’, your company and your friendship. To Jack (Andy) Coate: your friendship and your constant presence made all the difference.

To my family, for their love, support and unwavering belief in me throughout the course of this thesis. Likewise to my closest friends, who have endured this long journey with me (you know who you are).

And lastly, to Tim Newman: my EXCEL King, my sanity, my best friend, for your support, your patience, your faith and your love. I dedicate this to you.

iv Table of Contents Volume 1

List of Figures ...... x List of Tables ...... xviii

Chapter 1: Introduction 1.1 Origins and affinities of East Asians...... 1 1.1.1 The Fossils ...... 1 1.1.2 Neolithic-Recent East Asia sensu lato ...... 3 1.1.3 East Asia sensu stricto ...... 5 1.1.4 Southeast Asia...... 7 1.1.5 Northeast Asia...... 9 1.2 Trends and Clines in East Asia ...... 10 1.3 East Asian Cranial Morphology...... 11 1.3.1 Fossil East Asian Morphology...... 11 1.3.2 Contemporary East Asian Morphology ...... 13 1.4 Advances in Data Collection...... 15 1.5 Aims of the Study ...... 17

Chapter 2: Materials and Methods 2.1 Materials...... 18 2.1.1 East Asia sensu stricto ...... 18 2.1.2 Northeast Asia...... 20 2.1.3 Mainland Southeast Asia...... 20 2.1.4 Island Southeast Asia ...... 20 2.1.5 Comparative populations ...... 21 2.2 Methods...... 21 2.2.1 Landmark Choice...... 21 2.2.2 Data Collection ...... 30 2.2.3 Linear Measurements...... 30 2.2.4 Indices ...... 34 2.2.5 Angles ...... 37

v 2.2.5.1 Standard and modified-standard angles ...... 38 2.2.5.2 Non-standard angles...... 43 2.2.6 Statistical Analysis – Linear/Angular/Index Data ...... 45 2.2.6.1 Univariate Methods...... 45 2.2.6.2 Multivariate Methods...... 46 2.2.7 Geometric Morphometrics ...... 47 2.2.7.1 General Procrustes Analysis ...... 48 2.2.7.2 Registration ...... 49 2.2.8 Statistical Analysis – Three-Dimensional data ...... 49 2.2.9 Visualisation...... 50 2.2.10 Implementation of morphometric methods in the current study...... 51 2.2.11 Error studies ...... 52 2.2.11.1 Intra-observer error ...... 52 2.2.11.2 Measurement error ...... 53

Chapter 3: Sex Determination of Unsexed Crania 3.1 Introduction ...... 54 3.2 Results...... 56 3.2.1 East Asia sensu lato ...... 56 3.2.1.1 Mainland Southeast Asia ...... 56 3.2.1.2 Island Southeast Asia ...... 59 3.2.1.3 Andaman and Nicobar Islands ...... 60 3.2.1.4 South China...... 62 3.2.1.5 Northeast Asia...... 63 3.2.1.6 Native America ...... 65 3.2.2 Caucasians...... 66 3.2.3 Australia, Melanesia and Micronesia...... 69 3.2.4 Africa ...... 71 3.3 Summary and Conclusions...... 73

Chapter 4: Univariate Results - Linear Variables 4.1 Introduction...... 75 4.2 Results...... 77 4.2.1 Breadth variables...... 77

vi 4.2.1.1 Facial Breadths...... 77 4.2.1.2 Cranial Breadths...... 85 4.2.2 Length Variable...... 97 4.2.2.1 Facial Lengths ...... 97 4.2.2.2 Cranial Lengths ...... 101 4.2.2.3 Lengths of the Inferior Cranium ...... 106 4.2.3 Height Variables...... 108 4.2.3.1 Facial Heights...... 108 4.3 Summary and Conclusions...... 117 4.3.1 East Asian versus non-Asian...... 117 4.3.2 Northern versus Southern East Asia ...... 118

Chapter 5: Univariate Results – Angles 5.1 Introduction...... 119 5.2 Results...... 120 5.2.1 Facial Flatness Angles ...... 120 5.2.1.1 Upper Facial Flatness...... 120 5.2.1.2 Mid Facial Flatness ...... 128 5.2.1.3 Lower Facial Flatness ...... 135 5.2.2 Other Facial Angles ...... 137 5.2.3 Frontal Angles...... 139 5.2.4 Parietal Angles ...... 144 5.3 Summary and Conclusions...... 147 5.3.1 East Asian versus non-Asian...... 147 5.3.2 Northern versus Southern East Asia ...... 147

Chapter 6: Univariate Results – Indices 6.1 Introduction...... 149 6.2 Results...... 150 6.2.1 Cranial Vault Indices ...... 150 6.2.1.1 Breadth/Length...... 150 6.2.1.2 Height/Length ...... 155 6.2.1.3 Breadth/Height ...... 157

vii 6.2.1.4 Cranial Breadth Proportions...... 161 6.2.1.5 Frontal Length Proportion...... 164 6.2.2 Facial Indices ...... 166 6.2.2.1 Upper Facial...... 166 6.2.2.2 Nasal...... 170 6.2.3 Inferior Cranial Base Indices ...... 172 6.2.3.1 Palate ...... 172 6.2.4 Facial Flatness Indices ...... 175 6.2.4.1 Glabellar...... 175 6.2.4.2 Gnathic ...... 175 6.3 Summary and Conclusions...... 179 6.3.1 East Asian versus non-Asian...... 179 6.3.2 Northern versus Southern...... 180

Chapter 7: Multivariate Results – Linear and Angular Data 7.1 Introduction ...... 181 7.2 Results ...... 181 7.2.1 Linear Variables...... 181 7.2.1.1 Pooled Sex ...... 181 7.2.1.2 Male-Only ...... 186 7.2.1.3 Female-Only...... 192 7.2.1.4 Associations of Latitude with Observed Variation ...... 201 7.2.2 Angles ...... 202 7.2.2.1 Pooled Sex ...... 202 7.2.2.2 Male-Only ...... 207 7.2.2.3 Female-Only...... 211 7.2.2.4 Associations of Latitude with Observed Variation ...... 215 7.3 Summary and Conclusions...... 217 7.3.1 East Asian versus non-Asian...... 217 7.3.2 Northern versus Southern East Asia ...... 219

Chapter 8: Three-Dimensional Analysis – East Asia versus Comparative Populations 8.1 Introduction...... 221

viii 8.2 Results ...... 221 8.2.1 Pooled Sex...... 221 8.2.1.1 Sample Dispersion ...... 221 8.2.1.2 Latitude ...... 226 8.2.1.3 Centroid Size...... 226 8.2.2 Male-Only ...... 236 8.2.2.1 Sample Dispersion ...... 236 8.2.2.2 Latitude ...... 239 8.2.2.3 Centroid Size...... 242 8.2.3 Female-Only...... 246 8.2.3.1 Sample Dispersion ...... 246 8.2.3.2 Latitude ...... 249 8.2.3.3 Centroid Size...... 251 8.3 Summary and Conclusions...... 254 8.3.1 East Asian versus non-Asian...... 254 8.3.2 Northern versus Southern East Asia ...... 254

Chapter 9: Three-Dimensional Analysis – East Asia sensu lato 9.1 Introduction...... 256 9.2 Results ...... 256 9.2.1 Pooled Sex...... 256 9.2.1.1 Sample Dispersion ...... 256 9.2.1.2 Latitude ...... 259 9.2.1.3 Centroid Size...... 261 9.2.2 Male-Only ...... 266 9.2.2.1 Sample Dispersion ...... 266 9.2.2.2 Latitude ...... 268 9.2.2.3 Centroid Size...... 270 9.2.3 Female-Only...... 272 9.2.3.1 Sample Dispersion ...... 272 9.2.3.2 Latitude ...... 273 9.2.3.3 Centroid Size...... 276 9.3 Summary and Conclusions...... 278

ix Chapter 10: Discussion 10.1 Summary ...... 280 10.2 Discussion ...... 284 10.2.1 Current versus Previous Research...... 284 10.2.2 Defining East Asian Cranial Form...... 285 10.2.2.1 Vault Shape ...... 286 10.2.2.2 Facial Flatness...... 286 10.2.2.3 The Malar (Zygomatic)...... 288 10.2.3 Geometric Morphometrics ...... 288

Chapter 11: Conclusions 11.1 Conclusions...... 290 11.2 Areas of Future Research...... 291

References...... 293

Volume 2

Appendix ...... 314

List of Figures

Chapter 2 Figure 2.1 Map of East Asia ...... 22 Figure 2.2 Diagram of landmarks:anterior aspect...... 27 Figure 2.3 Diagram of landmarks:lateral aspect...... 28 Figure 2.4 Diagram of landmarks:inferior aspect...... 29 Figure 2.5 Diagram of angles: NAA, BAA, PRA...... 38 Figure 2.6 Diagram of angles: NBA, BBA...... 39 Figure 2.7 Diagram of angle: mSSA...... 40 Figure 2.8 Diagram of angle: mFRA ...... 40 Figure 2.9 Diagram of angle: mNFA...... 41

x Figure 2.10 Diagram of angles: mPAA1, mPAA2 ...... 42 Figure 2.11 Diagram of angle: mOCA ...... 42 Figure 2.12 Diagram of angles: NS, PR ...... 43 Figure 2.13 Diagram of angle: mf-n-zyo ...... 44 Figure 2.14 Diagram of angles: ns-n-zyo, n-ns-zyo ...... 44 Figure 2.15 Diagram of angles: ns-n-ba, n-ns-ba ...... 45 Figure 2.16 PCA plot of intra-observer error test...... 52

Chapter 4 Figure 4.1 Interorbital breadth: Pooled sex...... 77 Figure 4.2 Interorbital breadth: Male-only ...... 78 Figure 4.3 Interorbital breadth: Female-only...... 78 Figure 4.4 Upper facial breadth (fmo-fmo): Pooled sex...... 80 Figure 4.5 Upper facial breadth (fmt-fmt): Pooled sex ...... 80 Figure 4.6 Upper facial breadth (fmo-fmo): Male-only...... 81 Figure 4.7 Upper facial breadth (fmo-fmo):: Female-only...... 81 Figure 4.8 Mid-facial breadth: Pooled sex ...... 82 Figure 4.9 Mid-facial breadth: Male-only ...... 83 Figure 4.10 Mid-facial breadth: Female-only ...... 83 Figure 4.11 Zygomatic breadth: Pooled sex ...... 84 Figure 4.12 Zygomatic breadth: Male-only...... 85 Figure 4.13 Nasal breadth: Pooled sex ...... 86 Figure 4.14 Nasal breadth: Male-only ...... 86 Figure 4.15 Nasal breadth: Female-only...... 87 Figure 4.16 Anterior cranial breadth (STB): Pooled sex ...... 88 Figure 4.17 Anterior cranial breadth (STB):: Male-only...... 88 Figure 4.18 Anterior cranial breadth (STB):: Female-only ...... 89 Figure 4.19 Anterior cranial breadth (Bipterion): Pooled sex ...... 90 Figure 4.20 Anterior cranial breadth (Bipterion): Male-only ...... 90 Figure 4.21 Anterior cranial breadth (Bipterion): Female-only...... 91 Figure 4.22 Posterior cranial breadth (AUB): Pooled sex ...... 92 Figure 4.23 (Biporion): Pooled sex...... 92 Figure 4.24 Posterior cranial breadth (AUB): Male-only...... 93 xi Figure 4.25 (Biporion): Male-only ...... 93 Figure 4.26 Posterior cranial breadth (AUB): Female-only ...... 94 Figure 4.27 (Biporion): Female-only...... 94 Figure 4.28 Posterior cranial breadth (Bimastoid): Pooled sex ...... 95 Figure 4.29 Posterior cranial breadth (Bimastoid): Male-only...... 96 Figure 4.30 Posterior cranial breadth (Bimastoid): Female-only ...... 96 Figure 4.31 Facial Length: Pooled sex ...... 98 Figure 4.32 Facial Length: Male-only ...... 98 Figure 4.33 Facial Length: Female-only...... 99 Figure 4.34 Inferior Malar length: Pooled sex...... 99 Figure 4.35 Inferior Malar length: Male-only...... 100 Figure 4.36 Inferior Malar length: Female-only...... 100 Figure 4.37 Cranial length (n-l): Pooled sex...... 102 Figure 4.38 (g-l): Pooled sex ...... 102 Figure 4.39 Cranial length (n-l): Male-only ...... 103 Figure 4.40 (g-l): Male-only ...... 103 Figure 4.41 Cranial length (n-l): Female-only...... 104 Figure 4.42 (g-l): Female-only...... 104 Figure 4.43 Parietal length: Male-only ...... 105 Figure 4.44 Parietal length: Female-only...... 106 Figure 4.45 Palate length: Pooled sex...... 107 Figure 4.46 Palate length: Male-only...... 107 Figure 4.47 Palate length: Female-only...... 108 Figure 4.48 Foramen magnum length: Pooled sex ...... 109 Figure 4.49 Foramen magnum length: Male-only ...... 109 Figure 4.50 Alveolar height: Pooled sex...... 110 Figure 4.51 Alveolar height: Male-only ...... 111 Figure 4.52 Alveolar height: Female-only...... 111 Figure 4.53 Upper facial height (NPH): Pooled sex...... 112 Figure 4.54 Upper facial height (NPH): Male-only...... 113 Figure 4.55 Upper facial height (NPH): Female-only ...... 113 Figure 4.56 Upper facial height (pr-g): Pooled sex ...... 114 Figure 4.57 Upper facial height (pr-g): Male-only ...... 115 xii Figure 4.58 Upper facial height (pr-g): Female-only...... 115 Figure 4.59 Nasal height: Pooled sex ...... 116 Figure 4.60 Nasal height: Male-only ...... 117

Chapter 5 Figure 5.1 Angle NAA: Pooled sex ...... 121 Figure 5.2 Angle NAA: Male-only...... 122 Figure 5.3 Angle NAA: Female-only ...... 122 Figure 5.4 Angle mNFA: Pooled sex...... 123 Figure 5.5 Angle mNFA: Male-only ...... 124 Figure 5.6 Angle mNFA: Female-only...... 124 Figure 5.7 Angle mf-n-zyo: Pooled sex...... 125 Figure 5.8 Angle mf-n-zyo: Female-only ...... 126 Figure 5.9 Angle ns-n-zyo: Pooled sex...... 127 Figure 5.10 Angle ns-n-zyo: Male-only...... 127 Figure 5.11 Angle ns-n-zyo: Female-only...... 128 Figure 5.12 Angle mSSA: Pooled sex ...... 129 Figure 5.13 Angle mSSA: Male-only ...... 130 Figure 5.14 Angle mSSA: Female-only...... 130 Figure 5.15 Angle ns-n-ba: Pooled sex...... 131 Figure 5.16 Angle ns-n-ba: Male-only...... 132 Figure 5.17 Angle ns-n-ba: Female-only...... 132 Figure 5.18 Angle n-ns-zyo: Pooled sex...... 133 Figure 5.19 Angle n-ns-zyo: Male-only...... 134 Figure 5.20 Angle n-ns-zyo: Female-only...... 134 Figure 5.21 Angle NS: Pooled sex...... 136 Figure 5.22 Angle NS: Male-only ...... 136 Figure 5.23 Angle NS: Female-only...... 137 Figure 5.24 Angle BAA: Pooled sex ...... 138 Figure 5.25 Angle BAA: Male-only ...... 138 Figure 5.26 Angle BAA: Female-only...... 139 Figure 5.27 Angle NBA: Pooled sex ...... 140 Figure 5.28 Angle NBA: Male-only ...... 140 xiii Figure 5.29 Angle NBA: Female-only...... 141 Figure 5.30 Angle BBA: Pooled sex...... 142 Figure 5.31 Angle BBA: Male-only ...... 143 Figure 5.32 Angle BBA: Female-only...... 143 Figure 5.33 Angle mPAA1: Pooled sex...... 145 Figure 5.34 mPAA2: Pooled Sex...... 145 Figure 5.35 Angle mPAA1: Male-only ...... 146 Figure 5.36 Angle mPAA1: Female-only...... 146

Chapter 6 Figure 6.1 Length vs anterior Breadth: Pooled sex...... 151 Figure 6.2 Length vs anterior Breadth: Male-only ...... 152 Figure 6.3 Length vs anterior Breadth: Female-only...... 152 Figure 6.4 Length vs posterior Breadth: Pooled sex...... 153 Figure 6.5 Length vs posterior Breadth: Male-only...... 154 Figure 6.6 Length vs posterior Breadth: Female-only...... 154 Figure 6.7 Length vs Height: Pooled sex...... 155 Figure 6.8 Length vs Height: Male-only...... 156 Figure 6.9 Length vs Height: Female-only...... 156 Figure 6.10 Height vs anterior Breadth: Pooled sex...... 157 Figure 6.11 Height vs anterior Breadth: Male-only...... 158 Figure 6.12 Height vs anterior Breadth: Female-only ...... 158 Figure 6.13 Height vs posterior Breadth: Pooled sex ...... 159 Figure 6.14 Height vs posterior Breadth: Male-only...... 160 Figure 6.15 Height vs posterior Breadth: Female-only ...... 160 Figure 6.16 Anterior Cranial Breadth index: Pooled sex...... 161 Figure 6.17 Anterior Cranial Breadth index: Male-only ...... 162 Figure 6.18 Posterior Cranial Breadth index: Pooled sex...... 163 Figure 6.19 Anterior Cranial Breadth index: Male-only ...... 163 Figure 6.20 Anterior Cranial Breadth index: Female-only...... 164 Figure 6.21 Frontal Length proportion: Pooled sex...... 165 Figure 6.22 Frontal Length proportion: Male-only...... 165 Figure 6.23 Frontal Length proportion: Female-only...... 166 xiv Figure 6.24 Upper facial index1: Pooled sex...... 167 Figure 6.25 Upper facial index1: Male-only...... 168 Figure 6.26 Upper facial index1: Female-only...... 168 Figure 6.27 Upper facial index2: Pooled sex...... 169 Figure 6.28 Upper facial index2: Male-only...... 169 Figure 6.29 Upper facial index2: Female-only...... 170 Figure 6.30 Nasal index: Pooled sex...... 171 Figure 6.31 Nasal index: Male-only ...... 171 Figure 6.32 Nasal index: Female-only...... 172 Figure 6.33 Palate index: Pooled sex...... 173 Figure 6.34 Palate index: Male-only...... 174 Figure 6.35 Palate index: Female-only ...... 174 Figure 6.36 Glabellar index: Pooled sex...... 176 Figure 6.37 Glabellar index: Male-only...... 176 Figure 6.38 Glabellar index: Female-only...... 177 Figure 6.39 Gnathic index: Pooled sex...... 178 Figure 6.40 Gnathic index: Male-only...... 178 Figure 6.41 Gnathic index: Female-only ...... 179

Chapter 7 Figure 7.1 Pooled sex (Linear): PC 1 vs PC 2 (Ln-transformed)...... 184 Figure 7.2 Pooled sex (Linear): PC 1 vs PC 2 (Mosimann shape) ...... 184 Figure 7.3 Pooled sex (Linear): PC 3 vs PC 4 (Mosimann shape) ...... 185 Figure 7.4 Male-only (Linear): PC 1 vs PC 2 (Ln-transformed) ...... 189 Figure 7.5 Male-only (Linear): PC 1 vs PC 2 (Mosimann shape) ...... 189 Figure 7.6 Male-only (Linear): PC 3 vs PC 4 (Mosimann shape) ...... 191 Figure 7.7 Male-only (Linear): PC 5 vs PC 6 (Mosimann shape) ...... 191 Figure 7.8 Female-only (Linear): PC 3 vs PC 4 (Ln-transformed) ...... 194 Figure 7.9 Female-only (Linear): PC 3 vs PC 4 (Mosimann shape) ...... 195 Figure 7.10 Female-only (Linear): PC 5 vs PC 6 (Mosimann shape) ...... 195 Figure 7.11 Female-only (Linear): PC 1 vs PC 2 (Ln-transformed; excluding samples of n < 5) ...... 198 Figure 7.12 Female-only (Linear): PC 1 vs PC 2 (Mosimann shape; excluding xv samples of n < 5) ...... 198 Figure 7.13 Female-only (Linear): PC 3 vs PC 4 (Ln-transformed; excluding samples of n < 5) ...... 199 Figure 7.14 Female-only (Linear): PC 3 vs PC 4 (Mosimann shape; excluding samples of n < 5) ...... 199 Figure 7.15 Female-only (Linear): PC 5 vs PC 6 (Mosimann shape; excluding samples of n < 5) ...... 200 Figure 7.16 Pooled sex (Angles): PC 1 vs PC 2 (raw data) ...... 204 Figure 7.17 Pooled sex (Angles): PC 1 vs PC 2 (Ln-transformed) ...... 204 Figure 7.18 Pooled sex (Angles): PC 3 vs PC 4 (Ln-transformed; excluding samples of n < 5) ...... 206 Figure 7.19 Male-only (Angles): PC 1 vs PC 2 (Ln-transformed) ...... 208 Figure 7.20 Male-only (Angles): PC 1 vs PC 2 (raw data; excluding samples of n < 5) ...... 210 Figure 7.21 Male-only (Angles): PC 3 vs PC 4 (Ln-transformed; excluding samples of n < 5) ...... 210 Figure 7.22 Female-only (Angles): PC 1 vs PC 2 (raw data) ...... 212 Figure 7.23 Female-only (Angles): PC 3 vs PC 4 (Ln-transformed) ...... 213 Figure 7.24 Female-only (Angles): PC 3 vs PC 4 (Ln-transformed; excluding samples of n < 5) ...... 215

Chapter 8 Figure 8.1 Pooled sex: PC 1 vs PC 2 ...... 224 Figure 8.2 Pooled sex: PC 3 vs PC 4 ...... 225 Figure 8.3 Pooled sex: PC 1 vs Latitude...... 227 Figure 8.4 Pooled sex: PC 2 vs Latitude...... 228 Figure 8.5 Pooled sex: PC 2 vs Centroid size...... 230 Figure 8.6 Pooled sex: PC 3 vs Centroid size...... 231 Figure 8.7 Pooled sex: PC 5 vs Centroid size...... 232 Figure 8.8 Pooled sex: PC 3 vs Centroid size (excluding cranially small samples)...... 234 Figure 8.9 Pooled sex: PC 4 vs Centroid size (excluding cranially small samples) ...... 235 xvi Figure 8.10 Male-only: PC 1 vs PC 2...... 237 Figure 8.11 Male-only: PC 5 vs PC 6...... 238 Figure 8.12 Male-only: PC 1 vs Latitude...... 240 Figure 8.13 Male-only: PC 2 vs Latitude...... 241 Figure 8.14 Male-only: PC 3 vs Centroid size...... 244 Figure 8.15 Male-only: PC 5 vs Centroid size...... 245 Figure 8.16 Female-only: PC 1 vs PC 2 ...... 247 Figure 8.17 Female-only: PC 3 vs PC 4 ...... 248 Figure 8.18 Female-only: PC 1 vs Latitude...... 250 Figure 8.19 Female-only: PC 7 vs Centroid size ...... 252 Figure 8.20 Female-only: PC 6 vs Centroid size (excluding cranially small samples) ...... 253

Chapter 9 Figure 9.1 Pooled sex: PC 1 vs PC 2 ...... 258 Figure 9.2 Pooled sex: PC 1 vs Latitude...... 260 Figure 9.3 Pooled sex: PC 1 vs Centroid size...... 262 Figure 9.4 Pooled sex: PC 2 vs Centroid size...... 263 Figure 9.5 Pooled sex: PC 3 vs Centroid size...... 265 Figure 9.6 Male-only: PC 1 vs PC 2...... 267 Figure 9.7 Male-only: PC 1 vs Latitude...... 269 Figure 9.8 Male-only: PC 2 vs Centroid size...... 271 Figure 9.9 Female-only: PC 1 vs PC 2 ...... 274 Figure 9.10 Female-only: PC 1 vs Latitude...... 275 Figure 9.11 Female-only: PC 1 vs Centroid size ...... 277

List of Tables

Chapter 2 Table 2.1 Samples numbers for East Asian and comparative populations; pooled sex...... 19

xvii Table 2.2 Cranial Landmarks ...... 24 Table 2.3 T-test results and significance values for bilateral linear measurements .. 31 Table 2.4 Linear Measurements ...... 31 Table 2.5 Indices ...... 35

Chapter 3 Table 3.1 Sample numbers of known sex and unsexed crania from each sample..... 55 Table 3.2 Summary statistics and significance values for sexually dimorphic variables: Southeast Asia ...... 57 Table 3.3 Correlation coefficients from DFA: Mainland Southeast Asia...... 58 Table 3.4 Classification Results: Mainland Southeast Asia...... 58 Table 3.5 Correlation coefficients from DFA: Island Southeast Asia ...... 59 Table 3.6 Classification Results: Island Southeast Asia ...... 60 Table 3.7 Correlation coefficients from DFA: Andaman and Nicobar Islands...... 61 Table 3.8 Classification Results: Andaman and Nicobar Islands ...... 61 Table 3.9 Correlation coefficients from DFA: South China ...... 62 Table 3.10 Classification Results: South China ...... 63 Table 3.11 Correlation coefficients from DFA: Northeast Asia ...... 64 Table 3.12 Classification Results: Northeast Asia ...... 64 Table 3.13 Correlation coefficients from DFA: Native America...... 65 Table 3.14 Classification Results: Native America...... 66 Table 3.15 Summary statistics and significance values for sexually dimorphic variables: Caucasians ...... 67 Table 3.16 Correlation coefficients from DFA: Caucasians ...... 68 Table 3.17 Classification Results: Caucasians...... 68 Table 3.18 Summary statistics and significance values for sexually dimorphic variables: Australia, Melanesia and Micronesia ...... 69 Table 3.19 Correlation coefficients from DFA: Australia, Melanesia and 70 Micronesia...... 70 Table 3.20 Classification Results: Australia, Melanesia and Micronesia ...... 71 Table 3.21 Summary statistics and significance values for sexually dimorphic variables: Africa ...... 72 Table 3.22 Correlation coefficients from DFA: Africa...... 72 xviii Table 3.23 Classification Results: Africa...... 73

Chapter 7 Table 7.1 Pooled sex (Linear): Percentage variance explained by PCs 1-6 for Log-transformed and Mosimann data ...... 182 Table 7.2 Male-Only (Linear): Percentage variance explained by PCs 1-6 for Log-transformed and Mosimann data ...... 187 Table 7.3 Female-Only (Linear): Percentage variance explained by PCs 1-6 for Log-transformed and Mosimann data...... 195 Table 7.4 Female-Only (Linear): Summary of highest variable loadings on PCs 1-6 after exclusion of small samples (n<5) ...... 196 Table 7.5 Correlation between PCs 1-6 and Latitude (Linear log-transformed and Mosimann data) ...... 202 Table 7.6 Pooled sex (Angles): Percentage variance explained by PCs 1-6 for Log-transformed and Mosimann data ...... 203 Table 7.7 Pooled Sex (Angles): Summary of highest variable loadings on PCs 1-6 after exclusion of small samples (n<5) ...... 206 Table 7.8 Male-Only (Angles): Percentage variance explained by PCs 1-6 for Log-transformed and Mosimann data ...... 207 Table 7.9 Male-Only (Angles): Summary of highest variable loadings on PCs 1-6 after exclusion of small samples (n<5) ...... 209 Table 7.10 Female-Only (Angles): Percentage variance explained by PCs 1-6 for Log-transformed and Mosimann data ...... 211 Table 7.11 Female-Only (Angles): Summary of highest variable loadings on PCs 1-6 after exclusion of small samples (n<5) ...... 214 Table 7.12 Correlation between PCs 1-6 and Latitude (Angular raw and log- transformed data) ...... 216

Chapter 8 Table 8.1 Sample numbers for East Asian and non-Asian populations in 3D analysis...... 222

xix Chapter 9 Table 9.1 Samples numbers for East Asians populations in 3D analysis...... 257 Table 9.2 Pooled sex: Procrustes distances between means and significance values...... 259 Table 9.3 Male-Only: Procrustes distances between means and significance values ...... 269 Table 9.4 Female-Only: Procrustes distances between means and significance values...... 273

Appendix Appendix 1 Summary Statistics: Linear Variables...... 315 Appendix 2 Significant p-values for non-parametric post-hoc group comparisons (Kruskal-Wallis): Linear Variables...... 360 Appendix 3 Summary Statistics: Angles ...... 420 Appendix 4 Significant p-values for non-parametric post-hoc group comparisons (Kruskal-Wallis): Angles...... 438 Appendix 5 Summary Statistics: Indices...... 473 Appendix 6 Significant p-values for non-parametric post-hoc group comparisons (Kruskal-Wallis): Indices...... 496 Appendix 7 PCA variable loadings for log-transformed and Mosimann Linear Variables (all samples): Pooled sex ...... 537 Appendix 8 PCA variable loadings for log-transformed and Mosimann Linear Variables (excluding samples n < 5): Pooled sex ...... 541 Appendix 9 PCA variable loadings for log-transformed and Mosimann Linear Variables (all samples): Male-Only...... 545 Appendix 10 PCA variable loadings for log-transformed and Mosimann Linear Variables (excluding samples n < 5): Male-Only ...... 549 Appendix 11 PCA variable loadings for log-transformed and Mosimann Linear Variables (all samples): Female-Only...... 553 Appendix 12 PCA variable loadings for log-transformed and Mosimann Linear Variables (excluding samples n < 5): Female-Only...... 557 Appendix 13 PCA variable loadings for raw and log-transformed Angular Variables (all samples): Pooled sex ...... 561 xx Appendix 14 PCA variable loadings for raw and log-transformed Angular Variables (excluding samples n < 5): Pooled sex ...... 566 Appendix 15 PCA variable loadings for raw and log-transformed Angular Variables (all samples): Male-Only ...... 568 Appendix 16 PCA variable loadings for raw and log-transformed Angular Variables (excluding samples n < 5): Male-Only ...... 570 Appendix 17 PCA variable loadings for raw and log-transformed Angular Variables (all samples): Female-Only...... 572 Appendix 18 PCA variable loadings for raw and log-transformed and Angular Variables (excluding samples n < 5): Female-Only ...... 574

xxi Chapter 1 Introduction

1.1 Origins and affinities of East Asians: A Brief Background

1.1.1 The Fossils The origins and affinities of living East Asians are far from obvious, despite the fact that numerous craniometric (eg Brace and Tracer, 1992; T. Hanihara, 1994, 1997; Ishida and Kondo, 1998; Pietrusewsky and Chang, 2003; Brown and Maeda, 2004), dental (eg. Turner, 1987; Irish 1998; Matsumura and Hudson, 2005), linguistic (eg Bellwood 1991, 1996) and genetic (eg. Ballinger et al 1992; Chu et al 1998; Ding et al, 2000; Oota et al, 2001) studies have been made in this region. Previous studies have focused on China, Japan and island Southeast Asia, presumably because most of the fossil evidence in East Asia has surfaced in these areas. Most researchers agree that Homo erectus (or Homo sapiens erectus: Curnoe, 2006) colonised East Asia by 1.5 million years ago (Mya) from Africa. In China, the study of human evolution began in 1923 at Zhoukoudian, with the discovery of a worn and fossilised hominid molar tooth, and later (1927-1933) hominid fossils and associated cultural remains (Wu and Wu, 1997; Brown, 2001). The fossils, then named Sinanthropus pekinensis, are the largest Homo erectus sample from a single locality in the world, and were described by Weidenreich (eg 1935, 1936, 1943). Various dating methods suggest the fossils to be between 550,000 and 250,000 years old (Liu et al 1985; Pei 1985; Zhao et al, 1985; Huang et al, 1991; Grün et al, 1997). Cranial features of one reconstructed cranium, Skull 5, include a long, low vault shape with receding forehead, projecting supraorbital torus and a well developed occipital torus. According to Weidenreich (1946), ancestors of modern East Asians, particularly in northern China, could be identified among the Sinanthropus remains from Zhoukoudian due to the persistence of regional patterns in skeletal morphology through time. This theory of relationship between Middle Pleistocene and modern Chinese is supported by authors such as Wolpoff et al (1984), Wu (1990) and Wu and Poirier (1995), forming the basis of the Multiregional Model for the origins of modern humans (Weidenreich, 1939; Wolpoff et al, 1994).

1 Over the last 20 years there have been significant additions to the East Asian hominid fossil record in China, including other representatives of Homo erectus from Yunxian, Yuanmou, Gongwangling, and Hexian. Following these, were early ‘archaic’ Homo sapiens, represented by Dali, Jinniushan, and Maba, which are cranially more modern when compared to H. erectus (Etler, 1996). Their affinities to the older Chinese human fossils are still unclear. Some researchers believe ‘archaic’ Chinese specimens to be descended from H. erectus predecessors in China (Etler, 1996), while others regard them as eastern representatives of Homo heidelbergensis (Lahr, 1996; Rightmire 1998; Stringer, 2002). ‘Anatomically modern’ H. sapiens (e.g Liujiang, Salawusu and Upper Cave 101, 102 and 103) appear in China around 12-30 thousand years ago (kya) or as far back as about 70 kya - 153 kya, if U-series dates for Liujiang (Shen et al, 2002) are correct (Brown, 1992, 2001; Shen et al, 2002). Etler (1996) believes that these anatomically modern Late Pleistocene Chinese crania retain a set of primitive features that closely resemble Chinese H. erectus, thus concluding that Chinese fossils display a mosaic of transitional features from H. erectus to modern H. sapiens, uninterrupted by any major replacement of archaic by more modern people. Other studies (eg. Weidenreich, 1939) concluded that the anatomically modern Upper Cave crania were not morphologically similar to modern Chinese, leading researchers to suggest that recent Chinese, or East Asian morphology was a Holocene development (Kamminga and Wright, 1988; Brown, 1992). East Asian fossils and ‘anatomically modern humans’ are not just confined to China. In Indonesia, several H. erectus fossils have been dated to >1.5-1.8 Mya including Sangiran, Mojokerto and Ngandong fossils (Anton and Swisher, 2004). The timing of the arrival of ‘anatomically modern’ humans in Indonesia (eg. Wajak, Java and Niah Cave, Sarawak) is still uncertain, but based on fossil evidence from Australia, it must lie before 60 kya (Stringer, 2002). From Okinawa Japan, the Minatogawa 1 cranium (16.6-18.25 kya; Kobayashi et al, 1974) was recovered (Suzuki and Hanihara. 1982), which is morphologically similar to Liujiang from China and Niah Cave from Sarawak (Wu, 1992). Like Liujiang and Upper Cave, Minatogawa is morphologically and statistically distinct from modern and Neolithic East Asians (Weidenreich, 1939; Kaminga and Wright, 1988; Howells, 1989; Wu, 1992). This suggests that modern East Asian cranial morphology, as seen during the Holocene and present day, may have a very recent origin that does not appear to extend into the Late Pleistocene (Brown, 1992, 2001; Hanihara, 1992).

2 A poor Late Pleistocene fossil record in East Asia has become problematic in attempting to document the arrival and evolution of modern East Asians (Brown, 2001). In particular, China has a significant gap between late ‘archaic’ (~100kya) and modern human fossils (~30 kya), which is presumably the time period during which modern humans may have arrived, or evolved, in East Asia (Brown, 2001; Bräuer, 1992). Thus it is likely that the many questions concerning the origins of East Asians will only be answered once a late Pleistocene record is recovered in this region (Stringer, 2002).

1.1.2 Neolithic-Recent East Asia sensu lato The use of craniometric data for reconstructing biological relationships between and within populations, both past and present, has a long history in biological anthropology (eg Howells 1973, 1989; Van Vark and Howells, 1984; Hanihara, 1994; Ishida and Dodo, 1997; Ishida and Kondo, 1998; Pietrusewsky, 2000). Despite these numerous studies, and the introduction of genetic evidence, a definitive population history for East Asia sensu lato (Northeast, East sensu stricto and mainland and island Southeast Asia) is yet to be agreed upon.

Cranio-dental Evidence Many hypotheses have been put forward about the origins of East Asians on the basis of craniometric data. A number of Chinese anthropologists believe China is the original homeland of all Asian derived peoples (Wu and Zhang, 1985; Wu, 1990, 1992; Li et al, 1991; Liu et al 1991). Their evidence is based on archaeological and anthropological findings that suggest the present Chinese morphology arose during the Late Pleistocene. Macintosh and Larnach (1976) also believed China to be the geographic homeland of modern East Asians. However, it is widely perceived that modern populations of East Asia (as well as Australia, Melanesia, Polynesia and Micronesia) originated in Southeast Asia during the late Pleistocene to early Holocene (eg. Bowler, 1976; Howells, 1990; Bellwood, 1975, 1985; Turner, 1987; Pietrusewsky 1990). The studies of Turner (1987, 1989, 1990, 1992) found two significant patterns of nonmetric dental traits, which serve to divide East Asians into two groups: Northeast Asians, Native Americans and northern Chinese displaying ‘Sinodonty’, and southern China, Southeast Asia, Japan and Ainu, showing ‘Sundadonty’. Turner (1987, 1989, 1990, 1992) concluded that the Sinodont complex evolved from a Sundadont source.

3 However, Higa et al (2003) cautions that the sundodont-sindodont boundary is unclear, because all morphological traits exhibit clinal variation. The Sundadont pattern is a dental morphological complex that characterises prehistoric and recent Southeast Asian populations. It is recognised as low frequencies of incisor shovelling, double shovelling, lower first molar cusp 6, lower second molar cusp 5 and 3-rooted first molars (Lahr, 1995). It is proposed that Sundadonty is chronologically earlier and a less specialised morphologically than the Sinodont pattern of northern populations. This assumption is based on observed similarities between Sundadont East Asians and a small sample of Cro-Magnon teeth (Turner, 1987). The Sinodont pattern is characterised by intensification and increased complexity, such as a high frequency of incisor shovelling, double shovelling, lower first molar cusp 6 and 3-rooted first molars (Lahr, 1995). This pattern is believed to represent a more specialised or derived morphology, and thus it is considered unlikely that the dental morphology of the northern East Asians (Sinodonty) is the ancestral condition to the generalised morphology (Sundadonty) of the southern East Asians (Lahr, 1996). Thus, evidence indicating that the Sinodont condition is the derived form, and the existence of Sundadont relics within the range of Sinodont populations, suggests that the original inhabitants of East Asia sensu lato were part of a wide ranging Sundadont group, over which Sinodonts later expanded, most likely during the Neolithic (Lahr, 1995, 1996).

Genetic Evidence A genetic study by Cavalli-Sforza et al (1988) on population blood-groups posited that East Asians shared common ancestors with Europeans, possibly from the Middle East (Cavalli-Sforza et al, 1994). However, the general consensus of the genetic data indicates an Asian origin for modern East Asians. Several early studies of mitochondrial DNA (mtDNA) in a limited number of populations indicated that all East Asians may have descended from a common ancestor (Yu et al, 1988; Ballinger et al, 1992), and are consistent with dental studies (Turner, 1987) that suggest a common southern origin. In 1998, Chu et al used autosomal-microsatellite markers to determine the origins of East Asians. The results strongly supported a common African ancestor for East Asia, with a south to north migration that originated in Southeast Asia. This theory

4 of a Southeast Asian origin for all of East Asia is supported by Y-chromosome studies (Su et al, 1999; Ji and Su, 2000), which attributed the increased genetic diversity of Southeast Asians to the fact that mainland Southeast Asia may have been the first settlement of modern humans in East Asia. A Y-chromosome study by Capelli et al (2001) also supports a southern origin for East Asia, but from insular Southeast Asia and Melanesia, rather than from the mainland. Conversely, an alternative model supported by genetic studies (Nei and Roychoudry, 1993; Karafet et al, 2001) is a multi directional route to East Asia, with one migration through Central Asia and a second through Southeast Asia. Ding et al (2000) concluded that Southeast Asia is not the original homeland of Northeast Asian populations, stressing the importance of further investigation for potential gene flow from Central Asia into Northeast Asia. In addition, a recent genetic study on the genotype and phenotype of ear wax suggested an origin in Northeast Asia that spread south towards Southeast Asia (Yoshiura et al, 2006). This is based on the presence of allele-A occurring in dry ear wax, believed to be a cold-climate adaptation, that is present in high frequencies in northern Han Chinese (100%) and Mongolian populations. The dry type earwax is uncommon (0-3%) in populations of European and African origins (Yoshiura et al, 2006).

1.1.3 East Asia sensu stricto Cranio-dental evidence A craniometric study by T. Hanihara (1994) concluded that a few Neolithic Chinese samples from North China tended to show a craniofacial morphology similar to that of the recent Chinese samples, however, most of the Neolithic craniofacial morphologies were less evident in the majority of recent Chinese populations, particularly in southern China. Based on this evidence, Hanihara (1994) suggested that the population history of China shows similarities to the ‘dual structure’ population model of Japan (see below), and is more complex than that proposed by Brace and Tracer (1992) and Howells (1984). He also concludes that recent Chinese morphology may be derived from migrants out of northern East Asia within the last 3000-5000 years. The population history of Japan, including the Ainu and Ryukuan people may be explained under a single hypothesis known as the ‘dual-structure’ model, initially proposed by Hanihara (1991). This model posits that the first occupants of the Japanese

5 Archipelago came from Southeast Asia during the Upper Palaeolithic (~ 40,000 yrs ago), and gave rise to the Jomon people during the Neolithic (~10,000 years ago). A second migration from Northeast Asia took place after the Aeneolithic Yayoi age (~ 4,000 years age. In his craniometric study of East Asians from the Holocene, Hanihara (1994) found that recent Japanese show a cranial morphology intermediate between the Jomon and Yayoi, concluding that the physical features of recent Japanese are the result of admixture between Southeast and Northeast Asians. Hanihara (1994) attributes the southern expansion of the Northeast Asians (Yayoi) to rapid population growth and weather deterioration approximately 3000-5000 years ago. As discussed above, previous dental studies (Turner, 1987, 1989, 1990, 1992) have identified a north-south East Asian dichotomy on the basis of dental traits. Sundadonty, the earliest most generalised dental condition (Lahr, 1995) is evident in South China and Japan. Based on these results, Turner (1987) concluded that recent Japanese are much more like peoples from mainland Asia, particularly southern China, than the prehistoric Jomonese, clearly indicating that a major post-Jomon immigration event occurred, with interbreeding. North China tends to exhibit the northern Sinodont morphology, a condition that is evident during the Neolithic, with the Dawenkou population (6300-4500 BP) possibly representing the oldest Sinodont population (Manabe et al, 2003). Thus, the dental evidence alone is indicative of a complex population history for East Asia sensu stricto.

Genetic Evidence As discussed previously, ‘East Asia’ and ‘China’ are often synonymous in craniometric and genetic studies. Thus, discussion on genetic evidence for the population history of East Asia sensu stricto, which includes China, is predominantly repeated from that of East Asia sensu lato above. Chinese populations are underrepresented in genetic studies (Chu et al, 1998). However, studies that have been conducted generally concur that modern Chinese populations are derived from a Southeast Asian source (Chu et al, 1998; Su et al, 1999; Ji and Su, 2000; Capelli et al, 2001). However, studies using ancient mtDNA from Linzi, China over three time periods (2,500 ka, 2,000 ka and present day) showed that the genetic backgrounds of these three populations are very distinct from each other, with the oldest of these remains, from 2,500 yrs ago, genetically similar to present day

6 Europeans (Wang et al, 2000). These relationships indicate the occurrence of drastic changes in the genetic structure of the Chinese over the last 2,500 yrs. An ancient mtDNA study on 2,000 yr old Japanese (Yayoi) remains also indicated genetic similarities between modern Japanese, the Jomon and Yayoi people and Europeans (Oota et al, 1995). This genetic relationship between populations of Japan and the Eurasian continent have been the subject of many studies (Oota et al, 1999). A more recent mtDNA study (Tanaka et al, 2004) declared that the actual population history of Japan is complex, from which previously proposed theories only emphasise partial aspects. For example, Nei (1995) suggested a northeastern Asian influence on Palaeolithic Japanese, which is consistent with the results of Tanaka et al (2004). In an earlier study, Matsumoto (1988) used serum gammaglobulin polymorphisms to conclude that the homeland of all Japanese could have been Siberia, which correlates with the similarities found between Siberians and mainland Japanese in the Tanaka et al (2004) study. Omoto and Saitou (1997) and Horai et al (1996) demonstrated close affinities between Koreans and Japanese, which was also found by Tanaka et al (2004). A southern Asian signal has also been identified in Japanese mtDNA studies, thus leading Tanaka et al (2004) to conclude that Japan could have received several northern and southern Asian maternal inputs since the Palaeolithic, with more recent (Neolithic) input from northern Asia via Korea.

1.1.4 Southeast Asia Cranio-dental evidence The population history of Southeast Asia has been widely interpreted in terms of an original ‘Australo-Melanesian’ occupation followed by admixture with ‘Mongoloid’ peoples who expanded from the north with the spread of agriculture during the Neolithic on (Matsumura and Hudson, 2005; Hanihara, 1994). This hypothesis was initially proposed by Jacob (1967) and has been supported by genetic (e.g. Omoto and Saitou, 1997), cranial (e.g Hanihara 1992, 1993, 1994), linguistic (e.g. Ballinger et al, 1992) and archaeological data (e.g. Bellwood, 1997). Prehistoric remains recovered from both mainland and island Southeast Asia, particularly Indonesia and Malaysia, display morphological features similar to those of Australian Aboriginals or Melanesians (Duckworth, 1934; Trevor and Brothwell, 1962; Jacob, 1967). Thus it has been argued that Southeast Asia was occupied by indigenous

7 Australo-Melanesians before East Asian populations began dispersing into the region (Brace, 1976; Bellwood, 1987, 1997; Brace et al 1991). More recent prehistoric discoveries, such as at Niah cave in Borneo, Tabon in the Philippines and Hoabinhian in Vietnam provided further support for an Australo-Melanesian lineage in early Southeast Asia (Matsumura and Hudson, 2005). Conversely, large scale analyses of craniometric data from Southeast Asia conducted by Pietrusewsky et al (1992) and Hanihara (1992, 1993, 1994) demonstrate close affinities between modern East and Southeast Asians, with distinct dissimilarity to Australo-Melanesians (Matsumura and Hudson, 2005). Another example (Brace et al, 1991) found a Neolithic Thai cluster with modern Southeast Asians, as well as East Asian populations which include Neolithic Chinese and Yayoi. Dental and cranial studies have also provided an alternative interpretation of Southeast Asian population history known as ‘regional continuity’ or ‘local evolution’. As noted above, Turner (1987, 1989, 1990, 1992) discovered two significant patterns of nonmetric dental features among East and Southeast Asians, a ‘Sinodont’ pattern among East and Northeast populations and a ‘Sundodont’ pattern in Southeast Asians. Thus, Turner (1987, 1989, 1990, 1992) concluded that the dental patterns displayed among recent Southeast Asians are the product of continuity over time, uninterrupted by significant interbreeding with East Asians until recently. This theory is supported by craniometric data (Hanihara, 1992, 1993, 1994) that concludes that recent Southeast Asians are descended from a prehistoric indigenous population (lineage,) lacking significant admixture with East Asians until recently. Hanihara (1992) continues, suggesting that the predominant phenotype of modern Southeast Asians has also been acquired recently, and is a result of migration of Chinese populations that replaced or assimilated the aborigines of Southeast Asia. Hanihara (1992) names them the ‘Proto- Malay’, a population he claims to be morphologically similar to modern Dayaks and ‘Negritos’, as the indigenous source of modern Southeast Asians.

Genetic Evidence Genetic markers have many biological similarities between Chinese and Southeast Asians (Cavalli-Sforza et al, 1994; Omoto and Saitou, 1997). One study by Tan (2001) concluded that some Southeast Asian populations such as the Malay, Vietnamese and Dayak, are likely to be descended from an ancestral southern Chinese population. A mtDNA study (Ballinger et al, 1992) also supports the genetic influence of southern

8 China on Southeast Asian populations. According to Ballinger et al (1992) analysis of mtDNA variation among Southeast Asians indicates that all recent populations were derived from a common ancestral population that included most of the variation. In this study, it appeared that most mtDNA variation was shared between Southeast Asian populations and predates the geographical subdivision of the present-day. Vietnam had the greatest intrapopulational genetic divergence, suggesting it is the oldest population. Therefore, since Vietnam was colonised from southeast China, it implies a southern Chinese origin for the rest of Southeast Asia, approximately 59,000 to 118,000 years BP (Ballinger et al, 1992).

1.1.5 Northeast Asia Cranio-dental Evidence The cranial and dental morphology of modern Northeast Asians has been the subject of numerous studies, resulting in various hypotheses about the origins and affinities of these populations. Dental and facial characteristics of Northeast Asians have suggested affinities with the Ainu or with the Jomon, the ancestors of the Ainu (Turner, 1986; Brace and Tracer, 1992). According to Hanihara (1994), the Neolithic Northeast Asians in his study shared more similar craniofacial features to subsequent Northeast Asian populations than to any modern East or Southeast Asian group. This indicated that the basic Northeast Asian craniofacial form may have been established by at least the Neolithic. Hanihara (1994) also suggests that Northeast Asian morphology could be the result of biological influence from the western part of the Old World. As previously mentioned above, dental studies (eg., Manabe et al, 2003; Turner, 1987) point to Northeast Asians deriving from Sundadonty (ie. Southeast Asians) in northern China, Mongolia or Southeast Siberia. According to Manabe et al (2003) the regional continuity or discontinuity of the Sinodont pattern from the Upper Cave period to modern populations in North China is essential to understanding the origin of ‘Northern Mongoloid’ populations. Continuity of Sinodonty after the Shang period has been confirmed (Turner, 1990), however, no studies have examined the distribution of Sinodonty and Sundadonty in populations from the period between Upper Cave and Shang periods (Manabe et al, 2003).

9 Genetic Evidence Genetics tend to refute Northeast Asians as having a southern origin and instead link them with Europeans via Eurasia (Cavalli-Sforza et al, 1988). Studies mtDNA polymorphisms, short tandem repeat loci and Y-chromosome data (Ding et al, 2000; Karafet et al, 2001) also found no support for a southern origin for Northeast Asian populations, with Karafet et al (2001) reporting a closer genetic affinity between Northeast Asians and Central Asians than with Southeast Asians. A virological study (Zheng et al, 2004) claims both arguments may have validity, suggesting South China partially contributed to the formation of North China, and a European-related ethnic group probably contributed to Northeast Japanese and South Koreans.

1.2 Trends and Clines in East Asia

Northern and southern divisions have been recognised among East Asian populations using craniometric, dental and genetic evidence. Craniometric studies have long provided evidence of a north-south East Asian division. Research has established a clear but gradual cline between on the basis of craniofacial features that are believed to have developed in response to genetic and climatic factors (eg. Coon et al, 1950; Coon, 1962; Yamaguchi, 1992; Hanihara, 1994, 1996). These north-south features include short versus long vault; ‘low’ versus ‘high’ vault; ‘high’ versus ‘low’ facial skeleton; and narrow versus wide piriform aperture. Yongyi et al (1991) found that C-scores of craniofacial measurements divided their mainland Asian group into a northern component, consisting of the Chinese (Hong Kong to Hebei in the north and Yunnan in the west, to Shanghai in the east), Taiwan, Korea and Japan (excluding Ainu) and a southern group, which encompasses Southeast Asia from Vietnam to Indonesia, including Borneo and the Philippines. Brace and Tracer (1992) also found an East Asian northern and southern division, consisting of North, South, East and West China, Japan, Taiwan and Korea in the northern group, and Thailand, Burma, Borneo and the Philippines in the southern group. Pietrusewsky and Chang (2003) again found a clear distinction between the populations of East/North Asia and Southeast Asia, suggesting the division is due to long term ‘in-situ evolution’ in their respective regions.

10 According to Manabe et al (2003), north-south divisions observed using a range of evidence sources (craniometric, dental and genetic) roughly correspond to the divisions proposed by the Sinodont/Sundadont dental theory (Turner, 1985, 1987, 1992) and may therefore be equivalent to that of the origin of the two dental groups. As discussed above, Turner (1987, 1992) proposed that based on non-metric dental traits, East Asian groups could be separated into two distinct groups: a northern, specialised ‘Sinodont’ group consisting of East and Northeast Asians and a southern, generalised division known as the ‘Sundadont’ group, involving Southeast Asians and Jomonese. These studies cited higher frequencies of incisor shovelling and double shovelling in the northern group compared to the southern group as evidence of this specialisation. Also, northern populations exhibit additional traits not known before in earlier fossil hominids, which include three-rooted lower first molars, while the southern groups retain the older dental traits of high frequencies of two-rooted upper second premolars. Another dental study by Irish (1998) also supports a division between Southeast Asia and Northeast Asia on the basis of the frequency of derived dental traits compared to Sub-Saharan Africans, with Northeast Asians displaying the more recent and derived dentition. This study thus supports the work of Turner. While some dental traits appear to display a north-south cline, Turner (1987) suggests that all patterns can be attributed to protohistoric and historic gene flow. However, he adds that the assessment of a north to south cline will only be possible with the discovery of early Holocene East Asian samples. There is contradictory evidence within genetic studies on the presence of a north-south division. Chu et al (1998) used autosomal microsatellites to reconstruct East Asian phylogenies and alluded to a northern and southern distinction on the basis of the presence of a paraphyletic northern group, and a nearly monophyletic southern group. Karafet et al (2001) found a clear distinction between Northeast and Southeast Asia on the basis of Y-chromosome data, a division which is also apparent in virological markers (Zheng et al, 2004). Yoshiura et al (2005) found a north-south downward gradient from northern China toward Japan and Southeast Asia based on the genotype of dry earwax, as well as an east-west gradient from Siberia to Europe. Chu et al (1998) also found a clear distinction between northern and southern Chinese populations, a finding that is supported by studies using genetic markers (Zhao et al, 1989), craniometry (e.g Hanihara, 1994) and non-metric cranial features (Etler,

11 1992). According to Chu et al (1998), most authors attribute this distinction to the presence of geographic barriers and isolation. Ding et al (2000) found no support for a strong regional distinction in East Asian populations, including the Chinese. Instead, they believe that the existence of a genetic distinction between northern and southern populations is not well supported, claiming that while northern and southern populations fall into different regions of principal components maps, the clusters are not distinct, appearing to blend across a cline. Ding et al (2000) concludes that patterns of variation throughout East Asia can best be explained by a simple model of isolation by distance, and a possible over- sampling along a north/south axis, which results in a segregating of principal components maps into groups delineated by latitude that appears to blend across a cline, rather than clearly distinguished groups.

1.3 East Asian Cranial Morphology

While there have been extensive studies on the population histories of living and past East Asians, studies of the distinguishing morphological features of contemporary East Asians are not as thorough, somewhat ambiguous, and rarely described metrically.

1.3.1 Fossil East Asian Morphology Many studies defining Asian cranial features use ‘China’ and ‘East Asia’ interchangeably, presumably because China has yielded a considerable fossil record. Thus, both fossil and modern populations of China are featured in comparative morphological studies of the region, particularly studies of continuity of human evolution. As a result, fossil Chinese features are featured widely, with fleeting mention of current modern cranial morphology and its variation across East Asia. Wu (2004) lists shovel shaped upper incisors, a ‘horizontal curve’ of the sutures between the frontal bone above and nasal and maxillary bones below, a ‘low’ and ‘flat’ ‘upper face’, large nasomalar angle, flat nasal ‘saddle’ and quadrangular orbits as just some of the common features among Chinese fossils. Wolpoff et al (1984) also found shovel shaped incisors, ‘flatness of the upper and middle face (particularly the nasal saddle)’, and an anteriorly facing frontosphenoidal process of the zygomatic as defining features of fossil human Chinese.

12 In his review of craniofacial features in China, Pope (1992) found specific features concentrated in the midfacial region that also included the anterior orientation of the frontospenoidal process. Other features include: a broad interorbital distance, rectangularly shaped orbits, a ‘low nasal saddle’ and an absence of alveolar prognathism. Comparative studies of the East Asian fossil Liujiang and modern southern Chinese males found similar mean alveolar (54 mm vs 53.2 mm respectively), tooth size, nasal breadth (25 mm vs 26.1 mm) and vault thickness (7 mm vs 7.6 mm) dimensions (Brown, 1992), and ‘Mongoloid characteristics’ of shovel shaped central incisors, ‘shallow pre-nasal fossa’ and an anterior orientation of the anterolateral surface of the frontal process of the zygomatic were present in the two (Wu and Zhang, 1985).

1.3.2 Contemporary East Asian Morphology Blumenbach (1865) defines ‘Mongoloid’ morphology as being characterised by a ‘square head’, broad facial skeleton but ‘flat and depressed’, flat glabella, ‘small’ nose and ’outwardly prominent cheeks’. In his monograph on the skull of Sinanthropus Pekinensis (Peking Man), Weidenreich (1943) suggested at least 12 morphological features he believed to represent continuity in East Asians, based on comparisons of Peking Man remains and modern ‘Mongoloids’. These features include a sagittal “crest”; presence of an Inca bone (Os Incae) on the occipital bone; broad nasal bones, with small differences between upper and middle breadth; angle of the nasal roof profile of approximately 90°; pronounced anterior orientation of the malar region (zygomatic bone) and frontosphenoidal process of the zygomatic (on the orbital surface of the zygomatic; attachment of the lateral palpebral raphe of the eye); rounded inferior margin of the orbit that is level with the floor of the orbit; and shovel shaped upper lateral incisors. Hanihara (1994) describes the characteristic modern Asian, or ‘classic Mongoloid’ features as a rounded cranial vault, ‘wide’ and ‘high’ facial skeleton and marked facial flatness, originally developed in Northeast Asia as a response to the intense cold climate of the last glacial maximum. Brown (1992), states that ‘great’ cranial, cheek and orbit heights are characteristically ‘Mongoloid’. Bass (1995) outlines Mongoloid characteristics to be anteriorly projecting zygomatics that ‘dip below lower edge of maxilla’ and projection of the nasal bones, both superiorly and inferiorly, beyond the maxilla at the level of the alveolar bone.

13 According to Ishida and Dodo (1997), one of the major characteristics of populations originating in Asia is facial flatness, although compared to the Siberians, other ‘Mongoloid’ populations have greater variation in facial flatness (Ishida, 1992). Ishida and Kondo (1998) found that Siberian and northern Chinese populations both had high upper facial index values (bizygomatic breadth/upper facial height), indicating ‘high and broad’ facial skeletons. However, the populations were separated based on other variables used in the study that included variable cranial breadth/length index (cephalic index) values for Siberians that saw the samples range from mesocephalic to hyperbrachicephalic versus the mesocephalic and ‘relatively small skulls’ of the northern Chinese. It was also found that the nasal index (nasal height/nasal breadth) displayed northern Chinese as having a ‘relatively narrow and high’ nasal region. Ishida and Kondo (1998) found no difference between Siberian samples and the northern Chinese in the sagittal parieto-occipital index (parietal arc/occipital arc) but reported on results of a study by Benevolenskaya (1980) that found Northeast Asians could be separated from Southeast Asians using this index, with high values of the index seen in Northeast Asians and low values displayed in Southeast Asians. Lahr (1995) believes that ‘Mongoloid’ features described in the literature are not diagnostic, although some features have high incidences among some groups, such as facial flatness and incisor shovelling among Northeast Asian groups. However, based on the presence of ‘specialised’ features such as those mentioned above, Northeast and Southeast Asians can be separated morphologically, with Northeast populations classified as ‘typical Mongoloids’ and populations of the Southeast referred to as ‘Southern’ or ‘generalised Mongoloids’(Lahr, 1995). Generalised Southeast Asians are characterised by broad and flat facial skeletons, a broad cranial base and vault, ‘high’ cheeks and ‘tall noses’. They are also characterised by a gracile skeleton and Sundadonty. Northeast Asians, or ‘typical Mongoloids’, are characterised by a ‘more specialised’ morphological pattern that also includes facial flatness, broad vault and ‘high’ cheekbones, but also ‘tall’ orbits and facial skeletons, and ‘narrow noses’ when compared to Southeast Asians and a Sinodont dental pattern (Lahr, 1995). Peripheral East Asian populations, such as the Andaman Islanders, display intensification or absence of certain morphological traits compared to ‘southern’ and ‘typical Mongoloids’, such as absence of robusticity, due to limited gene flow from neighbouring populations (Lahr, 1995).

14 In sum, based on the literature, contemporary East Asian populations can be characterised non-metrically with the presence of a sagittal ‘crest’ or ‘ridge’ (Brown, 1992), an Inca bone on the occipital bone and dental morphologies (trait combinations) such as Sinodonty vs Sundadonty features and shovel shaped incisors. Metric studies have identified the anterior orientation of the zygomatic bones (both superior and inferior) or ‘outwardly prominent cheeks’ (Blumenbach, 1865), a broad ‘high’ facial skeleton, little glabella projection, mid and lower facial flatness and a round, ‘high’ cranial vault as characterising East Asians. With the exception of Weidenreich (1943), most authors agree on a narrow nasal region as a characteristic ‘Mongoloid’ characteristic.

1.4 Advances in Data Collection

The use of craniometric data for reconstructing biological relationships between and within populations, for the past and present, has a long history in biological anthropology (eg. Van Vark and Howells, 1984; Pietrusewsky, 2000; Pietrusewsky and Chang, 2003), and has led to the view that primary geographical areas can be distinguished by aspects of cranial form (Hanihara, 1994). In the past, research into the craniometric morphology of East Asians has focused on particular regions, specifically China, Japan and Taiwan (eg. K. Hanihara, 1985, 1991; Liu et al, 1991; Pietrusewsky, 1999; Brown and Maeda, 2004). Previous studies have collected standard linear measurements such as those used by Howells (1973) and Martin and Saller (1957), using standard osteometric instruments (callipers) to record dimensions of the cranial vault and facial skeleton (eg., Brace and Tracer, 1992; Yongi et al, 1991; Hanihara, 1994, 1997; Ishida and Kondo, 1998; Pietrusewsky and Chang, 2003; Brown and Maeda, 2004). Coon (1962) and Coon et al (1950) introduced six cranial indices (length/width; length/height; width/height; facial index; orbital index; nasal index) obtained from nine cranial measurements (Martin and Saller, 1957; Hanihara, 1985a,b) that claim to express the division of Northeast and Southeast Asians, while Brown (1992) used three facial angles (basion-nasion, nasion-prosthion and prosthion-basion) to asses facial prognathism. There is now a considerable collection of linear cranial measurements in the literature for many different human populations, collected by means of standard

15 anthropometric instruments. Recently, however, a relatively new method has been introduced in the form of three-dimensional (3D) or geometric morphometric analysis. Previous studies (eg. O’Higgins and Jones, 1998; Havarti, 2001a,b, 2003; Hennessy and Stringer, 2002; Pan et al, 2003; O’Higgins and Pan, 2004; Franklin et al, 2005a,b; Franklin et al, 2006) used the technique to acquire 3D landmark co-ordinates, using generalised Procrustes and principal components analysis to analyse the data in terms of ‘shape’ variation. Franklin et al (2005a) took this technique further and converted the 3D co-ordinates into linear data, to make them comparable to traditional linear dimension studies. This method of data collection and statistical analysis is considered to be advantageous relative to traditional methods because the physical integrity of the object being studied is preserved, rather than collapsing the object into a series of linear and angular measures in which some aspect of ‘shape’ is generally lost (Harvati, 2003; Franklin et al, 2006). The techniques are non-invasive, and allow for the capture, modification and analysis of a greater volume of data that would otherwise be impossible (Nasab, 2006). Perhaps the greatest advantage is the ability to visualise shape differences (Pan et al, 2003), thus providing a means of quantifying these shape differences that traditional methods can only deal with qualitatively (Harvati, 2003; Nasab, 2006).The method also allows for measurements between craniometric points that previously could not be measured due to the inaccessibility between points with traditional callipers (Hennessy and Stringer, 2002). Jolly (2003) believes that the extensive technical, statistical and computational power of 3D analysis applied to the data collection and analysis is significantly advanced compared to traditional methods due to the degree of reproducibility that can be achieved. Jolly (2003) continues, stating that once the digitised points have been chosen, the rest of the process is standardised, making representation and measurement of features less dependent on mere observation, and thus more ‘scientific’. Geometric morphometrics will be employed in this study for the first time to comprehensively survey contemporary East Asian populations.

16 1.5 Aims of the Study

The primary aims of the current study are several fold. Firstly, the study aims to undertake a comprehensive metric assessment of the morphology of the cranium of contemporary East Asian populations, with a view to understand variation within this region and between East Asia and other regions. This will be achieved by examining variation within and between East Asian populations, and comparing these populations to comparative Native American, African, Australo-Melanesian and Caucasian samples. An attempt to identify possible causes for any variation or similarities seen will also be made. Secondly, the study aims to broaden the geographical sample of East Asian groups beyond that of previous studies, by encompassing populations from Siberia to Island Southeast Asia, and extending beyond populations of present day China and Japan. In doing so, the study hopes to more comprehensively describe and define the cranial morphology of contemporary ‘East Asia’ by either refuting characteristic cranial features discussed above, or adding to the previously established list. An better understanding of the causes of variation are also sought. Clinal trends within East Asia based on their cranial morphology have been suggested in previous studies (see above). As such, the thesis aims to assess the presence of these proposed trends, particularly claims of an East Asian north-south division. Finally, the project aims to continue the successful use of 3D morphometric analysis in biological anthropology, assessing potential benefits to the discipline. In using this method, traditional measurements will be retained so as to remain comparable with previous studies, while providing an opportunity for the creation of new and repeatable linear measurements, indices and angles that may aid in defining East Asian morphology.

17 Chapter 2 Materials and Methods

2.1 Materials

According to Brues (1977), the term ‘Mongoloid’ refers to all native East Asian populations from the Burmese in the west, Japanese in the east, Chuckchi in the north, Malays in the south (including island Southeast Asians) and all indigenous groups in between. As such, the populations in the current study, which originate from Northeast Asia, China, Japan, Korea and the Ainu, and mainland and island Southeast Asia (including Andaman and Nicobar Islands) will be broadly termed East Asia sensu lato. The crania from aforementioned China, Japan, which are often synonymous with ‘East Asia’ in the literature, as well as Korea and the Ainu population, will be grouped under the heading ‘East Asia sensu stricto’. Native American, Caucasian, African, Australian Aboriginal, Melanesian and Micronesian samples are used for comparative purposes. Table 2.1 is a summary of the 530 crania from 23 countries used in the study and the region from which they originate. Details of the museum in which the material was housed is also given. Descriptions of the provinces represented within in each group are provided below. Figure 2.1 is a map detailing the regions from which the East Asian samples originate. The crania were selected on the basis of preservation and age, with those that were well preserved with a majority of osteological landmarks selected. Adult crania only were considered, with age assessed on the basis of maxillary and/or mandibular M3 eruption. Edentulous individuals were also excluded from analysis due to the possibility of the bone resorption having modified facial features. The crania in each population are of mixed sex, but due to the lack of information on the sex of individuals in the museum records, many crania were unsexed. This issue is addressed further in Chapter 3, where discriminant analysis is used to assign individuals to a sex in order to aid further analysis.

2.1.1 East Asia sensu stricto In the present study, countries China, Japan, Korea and the Ainu population define East Asia sensu stricto. China can be divided into a northern group, consisting of individuals

18 from Tientsin and Tungku, and a southern group, with representatives from Canton and the Yunnan Province. The majority of the Japanese crania are from Tokyo, with the exception of two crania from Nagasaki, and three individuals whose regional information was not provided. Two Ainu crania are from Saghalin Island, the remaining one from Yelo. The origin of the Korean crania is unknown.

Table 2.1 Summary table samples used in the study.

Population N Location East Asia Southern China 6 American Museum of Natural History Northern China 16 American Museum of Natural History Japan 13 American Museum of Natural History Korea 4 American Museum of Natural History Ainu 3 American Museum of Natural History

Northeast Asia Musée de l'Homme; The Natural History Siberia 27 Museum, London Mongolia 24 Musée de l'Homme

Southeast Asia (Mainland) University of Cambridge; The Natural Burma 39 History Museum, London Musée de l'Homme; The Natural History Cambodia 13 Museum, London Laos 24 Musée de l'Homme Thailand 23 Musée de l'Homme Vietnam 23 Musée de l'Homme

Southeast Asia (Island) Andaman Islands 36 University of Cambridge; The Natural History Museum, London Borneo 38 University of Cambridge; The Natural History Museum, London Indonesia 27 The Natural History Museum, London University of Cambridge; The Natural Nicobar Islands 20 History Museum, London Musée de l'Homme; The Natural History Philippines 31 Museum, London (continued)

19 Table 2.1 continued Population N Location Native America 33 American Museum of Natural History Aboriginal Australia Musée de l'Homme; The Natural History 27 (including Tasmania) Museum, London Africa Kenya (East Africa) 20 University of Cambridge Nigeria 9 The Natural History Museum, London

Pacific Melanesia 30 American Museum of Natural History Micronesia 15 American Museum of Natural History

Caucasian United Kingdom 29 University of Cambridge; The Natural History Museum London Total 530

2.1.2 Northeast Asia Siberian and Mongolian crania represent this region in the current study. The Siberian crania range across the Tchoukotka, Kalmouk, Evenk, Mordve, Troianov Gorogok, Tobolsk, Iakoute, Khnaty, Nivkh, Ouliassoutai, Tungusic, Ostyak and Samoyede tribes. The individuals from Mongolia represent the Gobi Desert, Kobdo, Ourga, Toqquoz- Sarai, Khan-Kin and Oerdaklik.

2.1.3 Mainland Southeast Asia The mainland group comprises crania from Burma (Myanmar), Cambodia, Laos, Thailand and Vietnam. The Cambodian crania are from Compong-Soi, Phnom Penh, Kampot and Neal Pring, while no regional information was provided for the Burmese. The majority of crania from Laos are from Kha, with one from Louang-Prabang and eight have unknown specific origins. Individuals from Thailand originated from Bangkok and Siam, and the Vietnamese crania Tonkin and Saigon, with some unprovenanced specimens.

2.1.4 Island Southeast Asia The Andaman and Nicobar Islands, Philippines, Borneo and Indonesian samples define Island Southeast Asia in the present study. No information on the origins or provinces for the crania from the Andaman and Nicobar Islands were provided by museums.

20 Crania from the Philippines originated from Panay, ile Cagraray, Samar and Manila. Six crania were found in battlefield remains. The Borneo crania range across a number of regions, including Leppu-Patong, Padas River, Peolau Petak, Murut and the Kapuas River. The Indonesian crania include some native Javanese, as well as crania from Timor, Bali, Malay and Java-Malay.

2.1.5 Comparative Populations The comparative samples comprise crania from Africa, Melanesia, Micronesia and the United Kingdom, as well as a Native American and an Australian Aboriginal groups. The African group can be divided into an eastern sample from Kenya, and a western Nigerian sample. The Melanesian crania range from across the Solomon and Torres Strait Islands and the Bismark Archipelago. The latter region comprises Duke of York, Gerrit Dennys Island, Fead Island, New Ireland and New Hanover. The Micronesian crania are spread across Yap in the Caroline Islands, Palau and Mortlock Island. The European, or Caucasian, crania originate from the Poundbury and Brandon collections from the United Kingdom. The Native American sample used in the present study comprises members of an unprovenanced tribe from Grand Gulch, Utah. It was studied with the permission of the American Museum of Natural History. The Australian Aboriginal sample includes crania from New South Wales, Queensland and the Northern Territory, as well as four crania from Tasmania. Nine Australian crania have unknown origin.

2.2 Methods

2.2.1 Landmark choice The current study involves the use of digitised craniofacial landmarks (figures 2.1-2.3), which were chosen to accurately reflect overall shape of the cranial vault and face, as well as provide accurate linear measurements between landmarks. A number of standard osteological landmarks (Howells, 1973; White, 2000) are included for purposes of comparison with earlier studies whose results and analyses have used standard caliper measurements. The remaining landmarks have been chosen to help facilitate the aforementioned shape analysis, as well as to demonstrate the flexibility of this innovative technology and thus the advantages of using digitised data points (ie specific

21

Siberia

Japan Mongolia Korea

China

Philippines Mainland Southeast Asia (Burma, Laos, Vietnam, Thailand,Cambodia) Andaman Islands

Nicobar Islands

Borneo

Indonesia

Figure 2.1. Map of the regions from which the East Asian samples in the current study (table 2.1) originated. Figure adapted from Hanihara, 1994.

22 landmarks for specific questions) as opposed to traditional morphometric methods. Table 2.2 presents the landmarks chosen and their descriptions. Selection of landmarks should be made using the principal of equivalence. Equivalence refers to developmental or evolutionary ‘homology’, it may be functional, or it may refer to constraints of the equipment e.g. the positioning of the end of the lever arm of the digitiser (Harcourt-Smith, 2002). In the present study, the landmarks chosen can be reasonably considered homologous in the evolutionary-developmental sense, based on knowledge of comparative anatomy and developmental biology. Previous studies (Bookstein, 1991; Marcus et al, 1996; O’Higgins, 2000) have developed a system of classifying the homology of anatomical landmarks:

Type I Landmarks These are landmarks whose equivalence or homology from specimen to specimen is supported by strong local evidence, such as the meeting of two or more structures or unusual local histology. An example of this type of landmark is bregma, the meeting point of the coronal and sagittal sutures.

Type II Landmarks Homology is supported case to case by geometric evidence rather than local or histological, such as the tip of a process or other bony projection. An example of a type II landmark would be endomalare, the most medial point on the inner surface of the alveolar ridge of the second upper molar.

Type III Landmarks Homology is supported by a relative position on a feature, rather than a specific location. An example of this type of landmark would be mastoidale, the most inferior point on the mastoid process. Based on the criteria above, the most confidence can therefore be placed in results generated from type I landmarks and the least in type III. Variation observed when interpreting results will more likely be due to error in data based on type III landmarks is included in table 2.2.

23 Table 2.2 Summary table of the cranial landmarks collected in the study. Landmark type is also included.

Landmark Type Description Prosthion (pr)1 III The most anteriorly prominent point in the median plane, above the septum between the incisors

Nasospinale (ns)2 II The point where the line tangent to the inferiormost points of the two curves of the inferior nasal aperture margin crosses the midline

Rhinion (rhi)2 II The midline point at the inferior end of the internasal suture

Nasion (na)1 II The intersection of the fronto-nasal suture and the median plane

Glabella (g)2 III The most anterior point on the frontal bone in the median sagittal plane, usually above the frontonasal suture Bregma (br)1 I The meeting point of the coronal and sagittal sutures in the median plane Obelion (ob)2 II A point in the median sagittal plane where a line connecting the parietal foramina (when present) intersects the sagittal suture

Lambda (la)1 I The apex of the occipital bone at its junction with the parietals, where sagittal and lambdoid sutures intersect

Jugale (ju)2* II The point in the depth of the notch between the temporal and frontal processes of the zygomatic

Maxillofrontale (mf)2* I The point where the anterior lacrimal crest of the maxilla meets the frontolacrimal suture

Zygoorbitale (zyo)1* I The intersection of the orbital margin and the zygomaticomaxillary suture

Frontomalare orbitale (fmo)2* I The point where the frontozygomatic suture crosses the inner orbital rim

Frontomalare temporale (fmt)2* I The point where the frontozygomatic suture crosses the temporal lie (or outer orbital rim)

Stephanion (st)1* I The intersection of the coronal suture and the inferior temporal line

Pterion (pt)2* I The region where the frontal, temporal, parietal and sphenoid meet on the side of the vault. In the current study, the landmark was taken at the anterior intersection of the frontal, sphenoid and parietal sutures

(continued)

24 Table 2.2 continued

Landmark Type Description Porion (po)2* III The uppermost point on the margin of the external acoustic meatus

Auriculare (au)2* II A point vertically above the center of the external acoustic meatus at the root of the zygomatic process

Asterion (as)1* I The meeting point of the temporal, parietal and occipital bones on either side

Mid-frontal3 II Mid-point of the bregma-glabella arc, in the median sagittal plane of the frontal bone

Alare*^ II A point on the inferior margin of the nasal aperture when projected vertically from the alveolar process between the second incisor and the canine on both sides

Mid-parietal3 II Mid-point of the bregma-asterion arc

Supraorbital notch/foramen3* I Located on the supero-medial border of the orbital rim bilaterally

Infraorbital foramen3* I The foramen of the maxilla located inferiorly to the inferior margin of the orbit. Point taken on the infero-lateral part

Superior zygotemporal suture3* I The most superior point on the suture that joins the zygomatic bone to the zygomatic process of the temporal bone

Inion (i)2 II A point at the base of the external occipital protuberance in the median plane. Normally defined as the point where the superior nuchal line merges in the external occipital protuberance

Opisthion (os)1 II The inferior edge of the posterior border of the foramen magnum, in the median plane

Basion (ba)1 II The anterior border of the foramen magnum, in the midline Sphenobasion (sphba)2 II The point where the median sagittal plane intersects the sphenooccipital suture

Hormion (ho)2 III The most posterior median point on the vomer

Alveolon (alv)2 II The point on the interpalatal suture where a line drawn between the deepest part of the alveolar ridges crosses the median sagittal plane

Staphylion (sta)2 II The point on the interpalatal suture where a line drawn between the deepest parts of the notches at the rear of the palate crosses the median sagittal plane

(continued)

25 Table 2.2 continued

Landmark Type Description

Orale (ol)2 II The point on the hard palate where a line drawn tangent to the posterior margins of the central incisor alveoli crosses the median sagittal plane

Zygomaxillare (zm)2* III The most inferior point on the zygomaticomaxillary suture

Mastoidale (ms)2* III The most inferior point on the tip of the mastoid process

Endomalare (enm)2* II The most medial point on the inner surface of the alveolar margin opposite the midpoint of the M2 crown

Inferior zygotemporal suture3* I The most inferior point on the suture that joins the zygomatic bone to the zygomatic process of the temporal bone

* Denotes bilateral landmark. 1 Landmark described by Howells (1973). 2 Landmark described by White (2000). 3 Landmark created specifically for the current study. ^ Standard landmark adapted from standard and modified for current study.

26 • Mid-frontal

Supraorbital foramen/notch G • • • N FMO MF• •MF •FMO

RHI• ZYO• • ZYO

NS• • ZM• ZM AL• • AL Infraorbital foramen

P•R

Figure 2.2. Landmarks in the current study located on the anterior skull. See table 2.2 for landmark key (adapted from White, 2000).

27

B •

ST O•B Mid-frontal • • Mid-parietal •

L • PT G • •

AST JU AU • • Superior Zygotemporal • • suture PO • Inferior• Zygotemporal I suture • NS •

PR MS • •

Figure 2.3. Landmarks in the current study located on the lateral skull. See table 2.2 for landmark key (adapted from White, 2000).

28

OL•

ZM ZM • • •ENM ENM• STA• •ALV

•HO SPHBA•

BA• MS•• PC 1

•O

•I

Figure 2.4. Landmarks in the current study located on the inferior skull. See table 2.2 for landmark key (adapted from White, 2000).

29 2.2.2 Data Collection The 3-dimensional landmarks described in table 2.2 are illustrated in figures 2.2-2.4. These landmarks were collected using a Microscribe 3DX digitiser (Immersion Corporation, 801 Fox Lane, California 95131, USA). The Microscribe is a digitising joint with five separate rotating joints, each containing a digital optical sensor. Unlike earlier models, these optical sensors are not affected by external environmental factors such as magnetic fields (Harcourt-Smith, 2002). Each skull was placed on a cushioned board to prevent displacement of the bone during the digitising process. The Microscribe was attached to a foot pedal and a laptop via a serial cable. The Microscribe and the skull were then calibrated using the software program Rhinoceros 3.0 (Robert McNeel and Associates, 1993-2002), a process that first involves calibration of the digitiser and the skull to a point in space, and second to the software program itself, so as to allow correct orientation of landmarks in Rhinoceros 3.0 (Rhino). Once calibrated, the point of the digitising arm of the Microscribe was placed gently on the landmark and the foot pedal depressed. The digitised landmark is instantly viewed on the screen. This means that as each landmark is digitised, the observer can see the skull/bone shape forming in real-time. If during the digitising process the skull is displaced or needs to be re-orientated, for example, to reach landmarks on the inferior surface, the skull must be recalibrated using the same method above. Each time a landmark is digitised, its x, y, z coordinate is stored in Rhino. Later, those co-ordinates can be imported into a program such as EXCEL (© Microsoft corporation) for conversion into linear measurements. Alternatively, both linear measurements and angles can be calculated directly in the Rhino program. If using the import option, one must ensure that each landmark is entered in the same order from case to case.

2.2.3 Linear Measurements Initially, 55 variables were measured for this study and included 10 bilateral measurements. T-tests were performed on these 10 bilateral variables in the statistical program PAST (Hammer et al, 2001) using the male-only sample from the standard Southeast Asian group used in sex determination (see chapter 3) to identify significant differences between left and right measurements. A significant result was returned for only one bilateral measurement, fmo-mf (t = 2.17, p = 0.03), thus this measurement was subsequently used in analysis in its separate forms of Left and Right fmo-mf (table 2.3).

30 The average values of each of the remaining bilateral measurements were used in place of the original left and right values, resulting in a total of 45 linear variables in this study.

Table 2.3 Results of t-tests on the 10 bilateral variables initially measured in the study. Significant results are in bold and subsequently treated as separate measurements.

Variable Result n-al t = 0.05 p = 0.96 ju-au t = 1.30 p = 0.20 ms-ob t = 1.70 p = 0.09 zm-inferior zygomatic t = 0.72 p= 0.47 zm-fmo t = 1.04 p = 0.30 zm-au t = 1.59 p = 0.11 ms-po t = 0.30 p = 0.76 zm-fmt t = 0.81 p = 0.42 zyo-superior zygomatic t = 1.66 p = 0.10 fmo-mf t = 2.17 p = 0.03*

Of the 45 measurements, 13 are standard anthropometric variables (Howells, 1989), 4 are adapted from the standards of Howells (1989) and the remainder have been created for the purposes of the current study. The measurements selected for the current study are presented in table 2.4.

Table 2.4 Summary table presenting the linear measurements taken for the current study.

Measurement (abbrev) Description Prosthion-nasospinale (pr-ns) Chord distance between prosthion and nasospinale Prosthion-nasion (NPH)1 Upper facial height from nasion to prosthion as defined Prosthion-glabella (pr-g) Chord distance from prosthion to glabella Prosthion-bregma (pr-b) Chord distance from prosthion to glabella Nasion-alare (n-al)* Distance from nasion to alare. In the current study, both left and right were taken, and the average of the two measurements used

(continued)

31 Table 2.4 continued Measurement (abbrev) Description Left frontomalare orbitale- Orbital breadth, taken as the direct distance from maxillofrontale (Lfmo-mf)^ frontomalare orbitale to maxillofrontale on the left side

Bijugal breadth (JUB)1 The external cranial breadth across the malars at the point jugale

Bimaxillofrontale (mf-mf)^ Interorbital breadth taken between the maxillofrontale landmark on both sides

Bifrontomalare orbitale (fmo-fmo)^ Minimum biorbital breadth taken between left and right points

Bifrontomalare temporale (fmt-fmt) Maximum biorbital breadth taken between left and right points

Bizygomaxillare (ZMB)1 Breadth across the maxillae between left and right zygomaxillare

Bialare (al-al)^ Breadth of the nasal aperture taken as the direct distance between this landmark on both sides

Bregma-basion (BBH)1 Distance from basion to bregma, as defined Bregma-lambda (PAC)1 The external parietal chord, or direct distance from bregma to lambda, taken in the median plane and at the external surface

Nasion-nasospinale (n-ns) Direct distance between nasion and nasospinale, as defined

Nasion-bregma (FRC)1 The frontal chord, or direct distance from nasion to bregma, taken in the median plane and at the external surface

Nasion-lambda (n-l) Chord distance between nasion and lambda, as defined Nasion-opisthion (n-o) Chord distance between nasion and opisthion, as defined Nasion-basion (BNL)1 Direct length between basion and nasion Basion-prosthion (BPL)1 The facial length from basion to prosthion, as defined Lambda-opisthion (OCC)1 The external occipital chord, or direct distance from lambda to opisthion, taken in the median plane and at the external surface

Bistephanic breadth (STB)1 Breadth between the stephanion points, on either side Bipterionic breadth Breadth between pterion on each side. See table 2.2 for definition of pterion in the current study

Biauricular breadth (AUB)1 The exterior breadth across the bilateral auricular points Biporionic breadth The exterior breadth between left and right porion Biasterionic breadth (ASB)1 Direct measurement from one asterion to the other

(continued)

32 Table 2.2 continued Measurement (abbrev) Description Jugale-auriculare (ju-au)* Direct measurement from jugale to auriculare, bilaterally

Zygomaxillare-auriculare (zm-au)* Chord measurement from zygomaxillare to auriculare, on both sides

Biparietal breadth Chord measurement between the mid-parietal points (parietal bosses), as defined in table 2.2

Bi-superior zygomatic breadth Chord measurement between left and right superior zygotemporal sutures (most superior point)

Bi-inferior zygomatic breadth Chord measurement between left and right inferior zygotemporal sutures (most inferior point)

Bimastoidale Direct measurement from one mastoidale to the other Mastoidale-obelion (ms-ob)* Direct measurement from mastoidale to obelion. Bilateral Mastoidale-porion (ms-po)* Chord distance from mastoidale to porion. Bilateral Zygomaxillare-inferior zygomatic Chord length from zygomaxillare to the inferior (zm-infzyg)* zygotemporal suture (most inferior point), bilaterally

Zygomaxillare-frontomalare orbitale Direct measurement from zygomaxillare to frontomalare (zm-fmo)* orbitale, on both sides Zygomaxillare-frontomalare temporale Direct measurement from zygomaxillare to frontomalare (zm-fmt)* temporale, on both sides Zygoorbitale-superior zygomatic (zyo- Chord distance between zygoorbitale and the superior supzyg)* zygomaticotemporal suture (most superior point), bilaterally

Basion-opisthion (FOL)1 The length from basion to opisthion, as defined Basion-sphenobasion (ba-sphba) The length from basion to sphenobasion Sphenobasion-staphylion (sphba-sta) Chord distance between sphenobasion and staphylion Staphylion-orale (sta-ol) The length from staphylion to orale Biendomalare (enm-enm) The measurement from one endomalare to the other Glabella-lambda (g-l) Direct measurement from glabella to lambda, as defined

* Denotes bilateral measurement. In the current study, the average value of the variable is used. 1Described by Howells (1989). ^ Measurement modified from Howells (1989) for the purposes of the current study.

33 Due to the large number of crania used in the study, the preferred method of calculating the linear measurements was to use the import option from Rhino to EXCEL. This method was also deemed more time efficient, as it was found that taking linear measurements directly from Rhino was time consuming and not appropriate for the time constraints and size of the data set of the study. Thus, measuring directly from Rhino is better suited to small samples and datasets. The three-dimensional x, y, z coordinates produced in Rhino were converted to linear distances in EXCEL using a Pythagorean formula:

2 2 2 (x1-x2) + (y1-y2) + (z1-z2) (1)

where x1-x2 is the x coordinate difference between any two landmarks, and x, y and z are the three-dimensional coordinates. In a three dimensional study of modern southern African populations, Franklin et al (2005a) examined the comparability of linear measurements generated from three- dimensional landmark coordinates to those measurements by traditional anthropometric methods. It was concluded that landmark coordinate data can be successfully transformed for use in traditional linear studies, and thus comparable with the large collection of traditional studies available in the literature.

2.2.4 Indices The use of craniofacial indices has previously been considered vital information, as craniofacial shape can be assessed directly via this method, allowing morphological differences or similarities among populations to be expressed in a more tangible way than in the case of individual linear measurements (Hanihara, 1994). Shape indices thus make relative statement about cranial morphology, e.g a cranium is broad for its length. To assess shape differences between samples in the present study, 23 indices were derived from the linear measurements. These indices give information on overall cranial vault shape and facial proportions (including facial projection), as well as specific bone shape such as in the zygomatic and frontal bones. Table 2.5 is a summary of the indices calculated in the present study.

34 Table 2.5 A table of indices, and the linear measurements from which they are derived. Abbreviations from table 2.4 have been used.

Index Description Measurements involved Cranial vault anterior breadth/length Expresses the length- STB/g-l breadth ratio of the anterior cranium posterior breadth/length** Cranial index: length- ASB/g-l breadth ratio of the posterior cranium height/length** Expresses the length- BBH/g-l height ratio of the cranium anterior breadth/height Expresses the height- STB/BBH breadth ratio of the anterior cranium posterior breadth/height** Expresses the height- ASB/BBH breadth ratio of the posterior cranium posterior cranial breadth The proportion of superior biparietal breadth / ASB proportion (superior vs to inferior breadth of the inferior) posterior cranial vault anterior cranial breadth The proportion of superior STB / bipterionic breadth proportion (superior vs to inferior breadth of the inferior) anterior cranial vault frontal index The length-breadth ratio of STB/FRC the frontal bone frontal bone length proportion Proportion of frontal bone FRC / g-l length to total cranial vault length parietal bone length proportion Proportion of parietal bone PAC / g-l length to total cranial vault length

Facial skeleton upper facial index 1 ** The height-breadth ratio of NPH / ZMB the face without the maxillary teeth upper facial index 2 The height-breadth ratio of NPH / JUB the face without the maxillary teeth

(continued)

35 Table 2.5 continued

Index Description Measurements involved upper facial index 3 The height-breadth ratio of zm-fmt/fmo-fmo the upper face above the maxilla

Interorbital index Proportion of interorbital mf-mf / fmo-fmo breadth to biorbital breadth nasal index** Describes ratio of breadth al-al / n-ns to height in the nasal aperture

Zygomatic zygomatic index Expresses the length- zyo-supzyg / zm-fmo height ratio of the zygomatic bone superior zygomatic projection Describes projection of the bi-superior zygomatic / JUB index 1 superior zygomatic process when compared to the breadth of the face superior zygomatic projection Describes projection of the bi-superior zygomatic / zm-zm index 2 superior zygomatic process when compared to the breadth of the face inferior zygomatic projection Describes projection of the bi-inferior zygomatic / JUB index 1 inferior zygomatic process when compared to the breadth of the face inferior zygomatic projection Describes projection of the bi-inferior zygomatic / zm-zm index 2 inferior zygomatic process when compared to the breadth of the face

Palate palate index Expresses the length- enm-enm / sta-ol breadth ratio of the palate

Facial projection glabellar projection* Evaluates the projection of g-l / n-l glabella compared to nasion gnathic index* Evaluates the degree of BPL / BNL projection of the lower face (prognathism)

* Adapted from Hanihara (2000). ** Adapted from Hanihara (1994).

36 A number of linear measurements used in the calculation of the indices in the current study have been modified from the standards of Howells (1989), and thus the indices are also modified. For example, maximum cranial breadth (or width) is generally defined as the maximum breadth perpendicular to the median sagittal plane, above the supramastoid crests (Howells, 1989). However, in the current study, the posterior cranial breadth used in the calculation of the cranial vault indices is biasterionic breadth (ASB). An anterior breadth variable, bistephanic breadth (STB), is also used in the same calculations. This anterior breadth measurement is involved in the indices of the frontal bone, and in the current study, is a substitute for the standard maximum frontal breadth measurement, defined as the maximum breadth at the coronal suture perpendicular to the median plane (Howells, 1989). Maximum vault length in the present study is defined as the distance between glabella and lambda, as the standard landmark opithsocranion, has not been taken, and has resulted in all vault indices involving length, and the glabellar projection index being modified from the standards. As seen in table 2.2, the landmark alare has been modified in the present study, and thus the nasal index is not strictly standard. Indices not marked as being adapted from a previous study, have been created by the author for the purposes of the present study. The indices have been calculated in EXCEL using the linear measurements in table 2.4. The indices are multiplied by 100, and presented as a percentage.

2.2.5 Angles Angles of the face and cranial vault can also be used to assess shape changes or similarities between samples. Examples of features described by angles include degree of prognathism (projection of the lower face), flatness of the frontal bone and nasal projection. More examples include angulation of individual bones of the cranial vault, such as the parietal and occipital bones. The angles selected for the current study are calculated in EXCEL, but it is also possible to determine the angles in Rhino. However, as has been previously discussed above, calculation of variables of large samples in Rhino has been deemed cumbersome by the author, and thus is better suited to small data sets for this particular group of measurements. All angles were calculated using the formula fo the Cosine rule:

37 Cos = b2 + c2- a2 (2) 2bc where b and c represent the measurements, or sides of the triangle adjacent to the unknown angle (), and a is the measurement opposite . Selected angles represent a combination of standard measurements, as defined by Howells (1973), and where standard variables were not available, similar measurements collected in the present study have been substituted, resulting in modified but repeatable angles. Angles to be calculated are as follows:

2.2.5.1 Standard and modified-standard Angles o Facial angles- Nasion angle (NAA), Basion angle (BAA) and Prosthion angle (PRA): These three angles, made up of their respective landmarks; nasion (N), basion (Ba) and prosthion (Pr), constitute the facial triangle, which can be used as an assessment of facial projection or prognathism. Each angle has been calculated individually in EXCEL using formula (2) above.

N

NPH

BNL PRA Pr

BAA Ba BPL

Figure 2.5 Nasion (NAA) Basion (BAA) Prosthion (PRA) angles. BNL: basion-nasion length, NPH: nasion-prosthion height, BPL: basion-prosthion length, as defined in table 2.4.

o Frontal angles- Nasion angle (NBA) and Basion angle (BBA): This set of angles has previously been defined by Howells (1973) and derives from the Bregma Nasion Basion triangle. The angles are assessed separately using the following cell references:

38 For NBA: This angle is a measure of the slope of the frontal bone, and the flexion of the cranial base. For BBA: This is a measure of the slope and the length of the frontal bone.

B

FRC

BBH NBA N

BNL BBA

Ba Figure 2.6 Nasion (NBA) and Basion (BBA) angles. BBH: basion-bregma height; FRC: basion-nasion chord length, BNL: basion-nasion length, as defined in table 2.4.

o Modified zygomaxilary angle (mSSA): The zygomaxillary angle is a measure of relative facial flatness. For the purposes of the current study, nasospinale (Ns) has replaced subspinale, the landmark defined by Howells (1973) in the standard calculation of this angle. The landmark zygomaxillare (ZM), as defined by White (2000) in the current study, is used in place of Howells’ zygomaxillare anterior. The values for b and c in the Cosine triangle formula were not previously calculated in the study, and so had to be specifically calculated as described above, using the Pythagorean formula in EXCEL (1). Only then could the Cosine rule be applied to determine the angle mSSA.

39 ZM ZM

mSSA

Ns

Figure 2.7 Modified Zygomaxillary angle (mSSA).

o Modified frontal angle (mFRA): This angle is a measure of the slope of the frontal bone between the points of bregma (B) and nasion (N). The angle has been modified from Howells’ standard angle by replacing the maximum subtense on the frontal bone, with the midfrontal landmark taken in the present study. As seen previously, the measurements N-midfrontal and B- midfrontal required specific calculation before the angle could be determined. The former calculation required equation (1) above, which then allowed the angle mFRA to be calculated using equation (2).

B

Midfrontal mFRA

FRC

N

Figure 2.8 Modified frontal angle (mFRA). FRC: bregma-nasion chord length as defined in table 2.4.

40 o Modified nasio-frontal angle (mNFA): The nasio-frontal angle is a measure of transverse frontal flatness. This angle has been modified from the standard defined by Howells (1973). For the purposes of the current study, frontomalare anterior is replaced by frontomalare orbitale. The linear measurements required for the b and c values in equation (2), which are not part of table 2.4, were calculated in EXCEL using the Pythagorean formula above (1).

FMO-FMO FMO FMO

mNFA

N Figure 2.9 Modified Nasio-frontal angle (mNFA). FMO-FMO: Bifrontomalare orbitale length, as defined in table 2.4.

o Modified parietal angle (mPAA): The parietal angle is a measure of the curvature and length of the parietal bone. This angle is defined by Howells (1973) as the angle between bregma, the parietal bone and lambda. In the present study, two parietal angles were calculated, differing slightly from the angle describe above. In the first angle, mPAA 1, the parietal bone landmark used in the present study was mid-parietal, as defined in table 2.2, with bregma (B) and lambda (L) continued as the remaining points of the triangle. The second angle calculated, mPAA 2, also used the mid-parietal landmark, but lambda was replaced by asterion (AST). As seen in the cases above, the modification of landmarks in the calculation of the angles also required the linear measurements between the new landmarks to be determined in order to complete the calculation. For mPAA 1, the new measurements are between bregma and mid-parietal, and lambda and mid-parietal. For mPAA 2, the measurements are bregma to asterion, asterion to mid-parietal and the bregma to mi-parietal measurement previously calculated for mPAA 1. All linear measurements were calculated in EXCEL using formula (1) of the present chapter.

41 BB PAC

L

mPAA11 mPAA2 Midparietal

Midparietal AST

Figure 2.10 Modified Parietal angles (mPAA 1 , mPAA 2). PAC: bregma-lambda chord length as defined in table 2.4.

o Modified occipital angle (mOCA): The occipital angle is a measure of the curvature of the occipital bone at its maximum height. The standard angle is defined as involving a triangle between lambda, the occipital bone and opisthion. In the current study, inion (I) was used as the landmark on the occipital bone, which has been defined in table 2.2, while lambda (L) and opisthion (O) remained as the remaining two corners of the triangle. The linear measurement between lambda and inion, and opisthion and inion were calculated in EXCEL using equation (1) of this chapter.

L

OCC mOCA I

O

Figure 2.11 Modified Occipital angle (mOCA). OCC: lambda-opisthion chord length as defined in table 2.4.

42 2.2.5.2 Non-standard Angles Seven angles were created specifically for the current study to examine to projection of the upper face at nasion, and the lower face at the level of nasospinale and prosthion. The angles were determined as follows: o Nasospinale (NS) and Prosthion (PR) angles: These two angles were created to examine the projection of the lower face with respect to the inferior cranium, or basion. Both angles, NS and PR are part of the same triangle, and essentially describe the same feature: projection of the alveolar region (prognathism). These angles were determined using the Cosine rule (equation 2). The linear distance between basion (Ba) and Nasospinale (Ns) was calculated using equation (1) above.

Ns

NS pr-ns PR Pr

Ba BPL

Figure 2.12 Nasospinale (NS) and Prosthion (PR) angles to assess lower facial projection. BPL: basion- prosthion length, pr-ns: prosthion-nasospinale length as defined in table 2.4.

o Upper and Lower Nasal projection angles: The five angles below quantify the projection of the upper and lower nasal region, with three in relation to the orbit and the remaining two with respect to the cranial base. In the case of bilateral landmarks, eg. zygoorbitale and maxillofrontale, measurements of the left side were used. The descriptions of these angles are below: mf-n-zyo : This angle (n) quantifies the relationship of nasion (N) to the orbit, using orbital margin landmarks maxillofrontale (MF) and zygoorbitale (ZYO). All linear measurements comprising the sides of the triangle were calculated specifically for the determination of this angle using the Pythagorean formula (1) above.

43

MF N n

ZYO Figure 2.13 The mf-n-zyo angle (n). An assessment of the projection of the upper nasal region with respect to the orbit. Landmarks are taken from the left side of the face.

ns-n-zyo (a) and n-ns-zyo (b): The two angles measured here examine the degree of projection of the upper and mid-face in the mid-sagittal plane. The former angle (ns-n- zyo), quantifies the projection of nasion with respect to the inferior orbital margin. The latter angle (n-ns-zyo) is a measure of the degree of projection of nasospinale with reference to nasion. Measurements required for the sides of the triangle not previously calculated were determined as described above, using equation (1). The angles a, describing upper nasal projection, and b, projection of the lower nasal bones, were then determined separately using the Cosine rule (2).

N

a

n-ns ZYO

b Ns Figure 2.14 Angles ns-n-zyo (a) and n-ns-zyo (b). An assessment of the projection of the upper (a) and lower (b) nasal region with respect to the mid-face and nasal height. Landmarks are taken from the left side of the face. N-ns: nasion-nasospinale length as defined in table 2.4.

ns-n-ba (c) and n-ns-ba (d): These two angles are essentially a measure of the same feature: mid-facial flatness. The former of the two (ns-n-ba), also takes into

44 consideration the degree of cranial base flexure. Both angles were calculated using the Cosine rule above (equation 2).

N c

BNL n-ns

d NS Ba

Figure 2.15 Angles ns-n-ba (c) and n-ns-ba (d). An assessment of the projection of the upper (c) and lower (d) nasal region with respect to the inferior cranium (ba). N-ns: nasion-nasospinale length, BNL: as defined in table 2.4.

2.2.6 Statistical Analysis: Linear Data 2.2.6.1 Univariate Methods A number of univariate methods were employed to describe variation between samples: Quantitative variables (linear measurements, indices and angles) are described in tables (see Appendix) giving the median, mean, standard deviation (SD) and coefficient of variation (CV) for each sample in the pooled sex, male-only and female-only groups. The median has been included due to the small sample sizes (n < 5) of a number of populations once separated into sex-specific groups. Minimum (min) and maximum (max) values are also given. To test for skewness in the data, as well as distribution and variation, Box and Whisker plots for each individual measurement in all three groups (pooled sex, male- only and female-only) were created in statistical program SPSS. The samples were ranked in order of increasing median to better visualise any patterns due to latitude, or separation of East Asian populations from each other and the comparative groups. Only those variables perceived as exhibiting interesting groupings or separations in the box and whisker plots are discussed (see Chapter 4). Apparent significant median differences between samples in the box and whisker plots were analysed using the Kruskal-Wallis method. This test is a non-

45 parametric one-way analysis of variance (ANOVA), which tests the hypothesis that two or more sample medians are equal. As it is a non-parametric test, it makes no assumptions as to the distribution of the data that would otherwise be assumed for ANOVA (e.g. distribution).

2.2.6.2 Multivariate Methods A number of other multivariate techniques were employed to the linear data and angles to visually explore relationships within and between the East Asian samples, as well as between the East Asians and the comparative groups. Indices were not explored using multivariate statistics, as shape is analysed separately and in greater depth during the three-dimensional analyses (see below). The linear and angular data were subjected to two sets of analyses for each of the pooled sex, male-only and female-only groups. Median data were used, so as to encompass all the East Asian samples that would otherwise be omitted from mean studies due to small sample sizes, and to better visualise the distribution of the samples. The first set of analyses on the linear measurements transformed the data to natural logarithms, placing all data points onto a common (log-normal) scale, thus minimising scaling effects. The second set involved converting the data to Mosimann shape variables to correct for size. This process saw each datum divided by the geometric mean of all variables for each individual cranium (Darroch and Mosimann, 1985; Jungers et al, 1995). Regarding the angular data, analysis was undertaken on a raw median data set, while a second analysis used log-transformed median data, as described above. The multivariate techniques undertaken in the current study are described below.

Principal Components Analysis (PCA): Principal components analysis (PCA) is a popular statistical method which attempts to summarise patterns of correlations among observed variables by reducing a large number of variables to a small number of uncorrelated components or factors that account for most of the variance in a dataset (Tabachnick and Fidell, 2001; Hubert et al, 2005). This method has been applied widely and successfully in past anthropological studies (e.g. Andrews and Williams, 1973; Howells, 1989; Hanihara, 1997; Pan et al, 2004; Curnoe, 2006) and was thus considered a useful tool in the current study.

46 The first component, or axis, usually accounts for the largest amount of variance between samples, the second axis the next largest amount and so on. The benefit of this statistical technique is that the majority of information about the samples can usually be summarised by the first few components. These components can be interpreted numerically with regard to the original variables in the form of factor loadings, which rank the original variables on the basis of those contributing most to the new component. The separation of the samples along the new components can be presented visually with bivariate plots. Limitations of this particular analysis are its sensitivity to small sample sizes and outliers, which may give false results, and an assumption of multivariate linearity (Tabachnick and Fidell, 2001). All analyses using PCA were performed in PAST (Hammer et al, 2001), a statistical program specifically created for palaeontological studies. However, due to labelling restrictions in PAST, the graphical outputs were recreated in EXCEL.

Discriminant Analysis: Due to limitations of museum records, a number of the crania in the study were of unknown sex. To rectify this, discriminant analysis (DA) was employed to classify these unsexed crania (see Chapter 3: Sex determination of unsexed crania). DA was chosen for this process because of its function of predicting group membership from a set of predictors (Tabachnik and Fidell, 2001). The method assumes multivariate normality, but is robust to departures of normality if the violation is due to unbalanced or skewed sample, rather than outliers. DA is sensitive to outliers, which may provide false results and missing data, which prevents analysis of the complete datset.

2.2.7 Geometric Morphometrics Geometric morphometrics was used in the present study to examine cranial shape changes both between contemporary East Asian populations, and between East Asia and non-Asians. The shape of each face is described by 3D coordinates that reasonably be considered developmentally homologous. Landmark configurations are used to calculate a measure of overall scale, or centroid size (O’Higgins and Jones, 1998). Centroid size is defined here as the square root of the sum of squared Euclidean distances from each landmark to the centroid (O’Higgins and Pan, 2004). The

47 configurations are then scaled, translated and rotated to ‘best-fit’ each other using Generalised Procrustes Analysis (GPA) and can then be used to estimate a mean configuration or mean shape (O’Higgins and Jones, 1998). Following GPA, landmark configurations are represented in a shape space that is well understood statistically (O’Higgins et al, 2001), known as Kendall’s shape space (Kendall, 1984), which is described below. Statistical analysis, specifically PCA, can now be applied to the landmark configurations to visualise shape variation within and between samples.

2.2.7.1 Generalised Procrustes Analysis (GPA )- How its works As briefly described above, GPA registers series of forms (size and shape), first removing size, followed by the removal of rotational and translational differences. Size is eliminated by calculating centroid size (defined above). Squaring and then square rooting eliminates any negative values. The x, y and z values for each coordinate are then each divided separately by centroid size. A new set of x,y and z values are thus created where size has been removed, and each shape is at unit size (ie centroid size = 1). The following equation summarises the process described above:

S(X) is centroid size. X is a matrix of k x m Cartesian coordinates, with k landmarks and m real dimensions and i,jth elements Xij . X is an m x 1 matrix of mean coordinates representing the centroid, and has the jth element Xj. Centroids for all the shapes are then superimposed onto that of the first specimen. Each configuration of landmarks then undergoes repeated least squares fitting of shapes to estimates of the mean until the fit can no longer be improved, minimising the distances between them. This results in the removal of translational and rotational differences. The new distance between each minimised landmark is known as the Procrustes chord distance (d2). This distance is calculated using the following equation:

d2 =

48 where n is the number of individuals, each represented by a k x m matrix (k = number of landmarks, m = number of real dimensions) of landmark coordinates, Xi ( i = 1,…,n). X i represents registered specimens.

2.2.7.2 GPA registered landmarks Registered landmark configurations can then be represented as points in shape space, known as Kendall’s shape space (Kendall, 1984), which is of a reduced dimensionality due to the aforementioned removal of translational (m), rotational (m(m- 1)/2) and scaling (1 dimension) differences. Kendall’s shape space is non-Euclidean (non-linear), however, statistical analysis can still be applied. This is because isotropic distributions of landmarks about the mean lead to isotropic distribution of points representing specimens in shape space (O’Higgins and Jones, 1998). However, great care is needed due to the non-linearity of the space. One approach, which is used because it naturally allows the study of allometry, is to carry out PCA in the tangent space to Kendall’s shape space (Dryden and Mardia, 1993). It is this method that is used in the current study, and discussed further below.

2.2.8 Statistical Analysis: Three-Dimensional Data Principal Components Analysis (PCA): PCA and its conventional application to linear data has been discussed above. In a conventional PCA, individual dispersion is represented by dots in a scatter plot that contain the information from the linear measurements, and involves variations in both size and shape. When PCA is applied to the Procrustes registered data, none of the resulting axes are size related (Pan et al, 2003). This results in the PCA becoming more sensitive to subtle shape differences (Franklin et al, 2006). Thus, variation illustrated on each PC axis is purely a shape profile, with each dot indicative of the individual’s geometric profile, as well as indicating the location for each individual (Pan et al, 2003). To determine which PCs contributed most to observed variation, multivariate analysis of variance (MANOVA) was applied to selected axes.

Procrustes distances: Procrustes distances between samples were used to compare the mean shape of one sample with the mean shape of another in some instances (eg. to lend statistical support the separation of East Asia sensu lato into four separate groups: Northeast Asia,

49 East Asia sensu stricto, mainland Southeast Asia and island Southeast Asia). Each group is separately Procrustes registered in Morphologika, and the registered data from each group combined into a single data file and Procrustes registered again. Software provided by Associate Professor Nick Milne (UWA) takes the mean of the Procrustes registered data from the combined file and creates a matrix of Procrustes chord distances. A permutation test can then be applied to the Procrustes distances to determine the presence of significant group separations. This technique can be used to calculate the Procrustes chord distance between any two group means.

Permutation tests: Software provided by Associate Professor Nick Milne (UWA) allowed for permutation tests to calculate the significance of a Procrustes chord distance (described above). The real Procrustes distance between the means of the two samples is calculated, and then individuals are randomly allocated to each group and a new mean calculated. The original mean difference is then compared to the distribution of permuted differences to assess whether it might be considered significant (Harcourt- Smith, 2002). If it fell outside of the 95% range of variation, it was considered significantly different. The technique does not assume a normal distribution, but creates its own distribution from which p values are then calculated. The tests were performed 1000 times, as defined by the software.

2.2.9 Visualisation An advantage of geometric morphometric methods is that it is possible to visualise variations in shape represented by PCA results (O’Higgins and Pan, 2004). To begin, GPA preserves the landmark geometry of a shape, allowing a mean shape to be constructed (ie. the shape at the centroid), which corresponds the zero point on the x and y principal component (PC) axis. A hypothetical shape at any point along the PC axis can be constructed using the equation:

Xh = Xmean + c

Where Xh is the hypothetical shape, Xmean is the mean shape, c is the PC score of the hypothetical shape in question and is the eigenvector of the PC of interest (O’Higgins and Jones, 1998).

50 Visualisation of the mean shape along a PC is then achieved by ‘warping’ or ‘morphing’ the mean shape along the axis. Visualisation is aided by the construction of triangular polygons between sets of landmarks to create a wireframe or fully rendered model of the landmark configuration. Deformations (ie stretching and contractions) of the mean shape can be explored in greater detail using Cartesian transformation grids calculated from thin-plate splines, which indicate how the space surrounding a reference shape might be deformed into the space surrounding a target shape (O’Higgins and Pan, 2004). The ability to view how the shape of the wireframe or rendered model deforms along the PC axis is important in understanding how shape change between specimens occurs.

2.2.10 Implementation of morphometric methods in the current study The analyses described above were undertaken using software created by O’Higgins and Jones (1998) Morphologika ©, a program that has been successfully applied in a number of peer reviewed studies (e.g. O’Higgins and Jones, 1998; Lockwood et al, 2002; Pan et al, 2003; O’Higgins and Pan, 2004; Merino et al, 2005).The program allows raw 2D or 3D Cartesian coordinates to be rotated, translated and scaled through GPA, and then carries out PCA in the tangent plane. The output appears in a number of linked windows which allow interactive exploration of shape variability. A descriptive table that presents information such as specimen name and variables such as sex, latitude, centroid size etc are displayed in one window, while a graphical plot offering pairs of PC’s or any one PC and an independent variable such as latitude is displayed in a second window. A further window is a 3D viewer that allows visualisation of the mean landmark configurations at any point along a PC axis in the form of a series of points, a wireframe model or a surface rendered model. A control window allows the user to investigate shape variability along a PC axis by ‘sliding’ or ‘walking’ up and down the axis, while simultaneously viewing any ‘warping’ or ‘morphing’ of the mean configuration in the viewer window. Alternatively, the computer mouse can be used to click on any point on the PC graph, and its representative shape can be viewed in the 3D viewer window. The control window also enables regression tests between multiple PC’s, or PC’s and independent variables. Numerical results of GPA and PCA are presented in another window.

51 2.2.11 Error Studies 2.2.11.1 Intra-observer Error To assess the degree of intra-observer error in the acquisition of landmarks, one cranium, randomly selected from the teaching collection of the Department of Anatomy, The University of New South Wales was digitised ten times. To assess variations due to errors of precision in relation to variability of the sample, the co-ordinate data from the test cranium was subjected to GPA and PCA with a sample of 10 East Asians. The 10 sets of co-ordinates from the test cranium clustered closely on PCs 1-4, indicating errors of precision are small with respect to sample variability, and are unlikely to influence results (Franklin et al, 2006). An example of this close clustering of the 10 sets of data from the test cranium after PCA is given in figure 2.14.

0040.04

0.03

0.02

0.01

0 -0.05 -0.03 -0.01 0.01 0.03 0.05 0.07 -0.01

-0.02

-0.03

-0.04

Figure 2.16 Dispersion of 10 repeats of the test cranium and a random samples of East Asians along PC 1 and PC 2 for the purposes of testing intra-observer error and errors of precision in relation to variability of a sample. Some of the 10 repeats are virtually identical hence only 8 tests are visible. Open squares, Test cranium; Closed triangles, East Asia.

52 2.2.11.2 Measurement Error Franklin et al (2005b) have previously demonstrated success in the conversion of 3D co-ordinates to linear variables. Thus, the co-ordinate data obtained from ten digitisation sessions on the test cranium were converted to linear variables (as outlined above), and a measurement error calculated using the method of White (2000). Based on this method the measurement error for all variables generally ranged between 0.1-1.5%. Exceptions to this were measurements of alveolar height (pr-ns; 3.56%), mastoid process height (ms-po; 3.64%) and nasal aperture breadth (al-al; 3.48%). These inflated measurement errors may reflect sexual dimorphism, such as the case with height of the mastoid process, or variation may due to large environmental influences during epigenesis (Carson, 2006; see Chapter 4 for further discussion).

53 Chapter 3 Sex Determination of Unsexed Crania

3.1 Introduction

As is commonly a problem when studying human material housed in a Museum environment, many crania examined in the current study had no record of sex (table 3.1). This proves to be an obstacle when applying statistics to the collected data, particularly when using samples which might be skewed by sexual composition. To address this issue, discriminant function analysis (DFA) was applied, using cranial samples of known sex to classify individuals of unknown sex. Previous studies (e.g. Hooton, 1946; Keen, 1950; Giles and Elliot, 1963; Franklin et al, 2005a) have demonstrated the successful use of DFA in sex determination. These studies were largely based on a selection of standard craniofacial variables that were determined by Hooton (1946) as being strong sexually dimorphic characters on modern European crania. As geographic variation in modern populations has been well documented, it seems reasonable to assume that sexually discriminating variables would also vary between geographic regions. Therefore, in the present study, a geographically specific method was applied to determine sex rather than the methods of the studies mentioned above. As well as having a large number of unsexed crania, the numbers of crania of known sex in most of the populations were small in the present study (table 3.1) which may make statistical analysis questionable. Within East Asia sensu lato, most individual samples demonstrated small numbers of known sex individuals (table 3.1). So as all East Asian populations had the opportunity to be classified as accurately as possible, individual populations were grouped into larger nearest-neighbour groups: mainland Southeast Asia, island Southeast Asia and Northeast Asia. Due to its relatively large combined sample size, the mainland Southeast Asian group was then nominated as a ‘standard’ sample from which the sexually dimorphic variables for all of East Asia sensu lato could be determined.

54 Table 3.1. Summary table of known sex versus unsexed individuals within each population.

Population Total Males Females Unknown Cambodia 13 4 6 3

Burma 39 14 3 22

Laos 24 1 4 19

Thailand 23 8 1 14

Vietnam 23 3 8 12

Borneo 38 19 3 16

Indonesia 27 11 6 10

Philippines 31 21 5 5

Andaman Islands 36 8 5 23

Nicobar Islands 20 8 1 11

Siberia 27 5 7 15

Mongolia 24 7 6 11

Korea 4 1 - 3

Ainu 3 1 - 2

Japan 13 7 2 4

North China 16 8 2 6

South China 6 3 - 3

Native American 33 10 13 10

Caucasian 29 12 10 7

Australia 27 8 2 17

Melanesia 30 11 4 15

Micronesia 15 3 6 6

Africa 29 9 2 18

55 All 45 linear variables for the ‘standard’ East Asian and comparative samples were assessed for their ability to discriminate between the sexes using t-tests on the samples of known sex. The results are provided in tables. Variables demonstrating significant male/female differences were then used in the DFA. As expected, sexual dimorphic variables differed between most of the samples, thus requiring each group to be analysed separately. The results of the DFA are provided and discussed below.

3.2 Results

3.2.1 East Asia sensu lato 3.2.1.1 Mainland Southeast Asia As previously mentioned, Southeast Asia was divided into mainland and island groups. This was done due to suggestions of an East Asian north to south cline. The mainland sample grouped crania from Cambodia, Laos, Burma, Thailand and Vietnam, which was considered plausible because of geographic and reported genetic relationships (e.g Wang et al, 1986; Liu et al, 1991; Turner, 1992; Chu et al, 1998). Due to its large combined sample size (n = 52 crania of known sex), the mainland group was then assigned as the ‘standard’ group for the purposes of determining sexual dimorphic features of East Asians. A total of 45 linear measurements from the 52 crania of known sex were subjected to t-tests to determine those that differed significantly between the sexes. The results of t-tests are presented below in table 3.2. These variables were then used in DFA to classify the unsexed crania from mainland Southeast Asia (n = 70), which was performed in SPSS. As the analysis involves only two categories (male and female), there will only be one discriminant function. A limitation of the DFA method in SPSS is the inability of the program to recognise crania with missing variables. As such, crania not classified in the analysis were re-analysed after the removal of variables with missing data. This process continued until all crania were assigned a sex. Therefore, structure matrix tables herein represent the results generated from the first majority analysis of each dataset. Table 3.3 is a structure matrix table ranking the dimorphic variables in order of absolute size of correlation within the function (function 1), as defined by the DFA. The structure coefficients reported by the structure matrix table are interpretable as a variable’s

56 contribution to the function independent to that variable’s relationship to the other variables (DiBennardo and Taylor, 1983). These structure coefficients are used here instead of the commonly employed standardised discriminant function coefficients, as the latter can at times produce a misleading impression of a variable’s power of discrimination (Klecka, 1980). Thus, the variables are ranked in order of contribution to the discrimination of the sexes. In this first analysis, discrimination between the sexes is most likely due to size differences, as indicated by the positive coefficient scores (DiBennardo and Taylor, 1983). Separation of the sexes on the basis of size differences is reflected in the sexually dimorphic variables, where male means are consistently larger than female means (table 3.2). Height of the mastoid process (ms-po), and prosthion-bregma height (pr-b) were the strongest sexual discriminators of male and female mainland Southeast Asians. Following these variables was a moderately strong contribution from facial breadth (fmo-fmo, fmt-fmt, JUB).

Table 3.2. Summary statistics of sexually dimorphic variables for the ‘standard’ Southeast Asian group. Variables to be used in DFA for all East Asian groups in order to classify individuals of unknown sex.

Variable Male (n=30) Female (n=22) Mean S.D Mean S.D p-value prosthion-bregma (pr-b) 173.04 6.64 163.68 6.13 <0.001 bijugal breadth (JUB) 116.29 4.73 110.41 3.72 <0.001 bi-frontomalare orbitale (fmo-fmo) 98.25 3.87 93.28 3.48 <0.001 bi-frontomalare temporale (fmt-fmt) 103.96 3.86 98.60 3.55 <0.001 basion-bregma (BBH) 136.80 5.05 130.47 5.05 <0.001 nasion-bregma (FRC) 112.11 4.38 106.86 4.41 <0.001 basion-prosthion (BPL) 95.04 5.71 91.04 3.76 <0.01 bi-inferior zygomatic breadth 123.03 5.25 116.93 4.97 <0.001 bimastoidale (ms-ms) 105.17 5.22 99.86 4.55 <0.001 mastoidale-porion (ms-po) 33.49 2.95 28.86 3.08 <0.000 glabella-lambda (g-l) 167.99 6.22 160.50 8.30 <0.001

57 According to the DFA, approximately 90% of the crania of known sex in this analysis were deemed correctly classified (table 3.4). Thus, confidence can be placed in both the classification results (table 3.4), and the variables identified above as being the strongest contributors to that classification.

Table 3.3. Structure matrix table reporting structure coefficients for function 1 for mainland Southeast Asia. Variables in order of absolute size of correlation.

Variable Function 1 Mastoidale-porion (ms-po) 0.62 Prosthion-bregma (pr-b) 0.61 Bi-frontomalare temporale (fmt-fmt) 0.57 Bi-frontomalare orbitale (fmo-fmo) 0.55 Bijugal breadth (JUB) 0.52 Basion-bregma (BBH) 0.50 Bi-inferior zygomatic breadth 0.47 Glabella-lambda (g-l) 0.46 Nasion-bregma (FRC) 0.46 Bimastoidale (ms-ms) 0.40 Basion-prosthion (BPL) 0.30

Table 3.4. Sexing accuracy and classification results for the mainland Southeast Asian group as determined by discriminant function analysis.

Actual Group Membership Predicted Group Membership Sex N Male Female Male 30 27 3 Female 22 2 20 Ungrouped cases 68 40 28 Percentage of cases Male 100 90.0 10.0 Female 100 9.1 90.9 Ungrouped cases 100 58.8 41.2 * 90.5% of original cases correctly classified

58 3.2.1.2 Island Southeast Asia Sixty five crania of known sex (51 male, 14 female) from the Philippines, Indonesia and Borneo were combined to form a combined island Southeast Asian group. The clustering of these samples was to facilitate the sexing of a total 27 unsexed crania from the populations above. Variables to be used for classification were those previously determined by the ‘standard’ group above (table 3.2). The structure matrix table (table 3.5), indicates facial breadth (fmo-fmo, fmt- fmt) as the strongest classifying craniofacial feature. This was followed by a moderate influence from mastoid process height (ms-po) and bimastoid breadth (ms-ms). The positive result for all coefficient scores implies that size differences of these variables between the sexes is influencing classification. Results of the DFA indicated that approximately 90% of the original crania of known sex from island Southeast Asia were correctly classified (table 3.6). Thus, the allocation 17 of the 27 unsexed individuals as male and 10 as female, can be considered an acceptable result.

Table 3.5. Structure matrix table reporting structure coefficients for function 1 for island Southeast Asia. Variables in order of absolute size of correlation.

Variable Function 1 Bi-frontomalare orbitale (fmo-fmo) 0.72 Bi-frontomalare temporale (fmt-fmt) 0.66 Mastoidale-porion (ms-po) 0.59 Bimastoidale (ms-ms) 0.51 Basion-bregma (BBH) 0.44 Nasion-bregma (FRC) 0.44 Glabella-lambda (g-l) 0.43 Bijugal breadth (JUB) 0.18 Basion-prosthion (BPL) 0.09 Bi-inferior zygomatic breadth 0.07 Prosthion-bregma (pr-b) 0.04

59 Table 3.6. Sexing accuracy and classification results for the island Southeast Asian group as determined by discriminant function analysis.

Actual Group Membership Predicted Group Membership Sex N Male Female Male 51 44 7 Female 14 1 13 Ungrouped cases 27 17 10 Percentage of cases Male 100 86.3 13.7 Female 100 7.1 92.9 Ungrouped cases 100 63.0 37.0 * 89.6% of original cases correctly classified

3.2.1.3 Andaman and Nicobar Islands Although these two samples are described as island Southeast Asian populations throughout the current study, for the purposes of sexing, it was deemed appropriate to separate these two groups from the populations above. This separation was due to the Andaman and Nicobar crania exhibiting noticeably smaller cranial size in comparison to all other samples, particularly the Andaman sample. Results so far in this chapter have suggested that discrimination between the sexes has been largely due to size differences, and thus the inclusion of small crania in a size dependant analysis may result in false classification results. The variables used to classify 34 crania of unknown sex from 22 crania of known sex from the Andaman and Nicobar Islands (table 3.1) have been previously determined by the ‘standard’ Southeast Asian group above (table 3.2). As observed above in the island Southeast Asian group, facial breadth (fmt-fmt) is the most influential variable in the determination of sex, followed by cranial length (g-l), height (BBH) and bimastoid breadth (ms-ms). The aforementioned variables exhibit a similar level of contribution (table 3.7), and all but one variable (bi-inferior zygomatic breadth) display a positive loading, thus indicating that classification is mostly size dependant. Approximately 86% of the original group of known sex crania from the Andaman and Nicobar Islands were correctly classified (table 3.8). Thus the results of the classification of the unsexed crania, which are based on these individuals, are considered satisfactory.

60 Table 3.7. Structure matrix table reporting structure coefficients for function 1 for the Andaman and Nicobar Islands. Variables in order of absolute size of correlation.

Variable Function 1 Bi-frontomalare temporale (fmt-fmt) 0.69 Glabella-lambda (g-l) 0.65 Basion-bregma (BBH) 0.63 Bimastoidale (ms-ms) 0.62 Bi-frontomalare orbitale (fmo-fmo) 0.60 Prosthion-bregma (pr-b) 0.57 Nasion-bregma (FRC) 0.51 Mastoidale-porion (ms-po) 0.50 Basion-prosthion (BPL) 0.11 Bi-inferior zygomatic breadth -0.01 Bijugal breadth (JUB) 0.00

Table 3.8. Sexing accuracy and classification results for the Andaman and Nicobar Islands group as determined by discriminant function analysis.

Actual Group Membership Predicted Group Membership Sex N Male Female Male 15 13 2 Female 7 1 6 Ungrouped cases 34 20 14 Percentage of cases Male 100 86.7 13.3 Female 100 14.3 85.7 Ungrouped cases 100 58.8 41.2 * 86.2 % of original cases correctly classified

61 3.2.1.4 South China The two Chinese samples, North and South China, were analysed separately due to suggestions of a north-south cline within China (e.g. Yamaguchi, 1992; Hanihara 1994, 1996; Chu et al, 1998). Due to the small sample size from South China (table 3.1), the crania of known sex were combined with the ‘standard’ mainland Southeast Asian sample so as to increase the sample size to achieve a more accurate classification of the unsexed crania. This grouping was considered acceptable because of a close geographic relationship between South China and mainland Southeast Asia, and reported genetic relationships between the two regions (e.g Cavalli-Sforza et al, 1994; Omoto and Saitou, 1997). North China is discussed further below. The variables determined above (table 3.2) during analysis of the mainland Southeast Asian group were used in the classification of the South Chinese crania. Not surprisingly, results were identical to those of the ‘standard’ group (table 3.9). Height of the mastoid process (ms-po), and facial height (pr-b) and breadth (fmo-fmo, fmt-fmt) were the strongest contributors to the classification, with the size the most likely discriminating factor, as indicated by the positive scores.

Table 3.9. Structure matrix table reporting structure coefficients for function 1 for South China. Variables in order of absolute size of correlation.

Variable Function 1 Mastoidale-porion (ms-po) 0.62 Prosthion-bregma (pr-b) 0.61 Bi-frontomalare temporale (fmt-fmt) 0.57 Bi-frontomalare orbitale (fmo-fmo) 0.55 Bijugal breadth (JUB) 0.52 Basion-bregma (BBH) 0.50 Bi-inferior zygomatic breadth 0.47 Glabella-lambda (g-l) 0.46 Nasion-bregma (FRC) 0.46 Bimastoidale (ms-ms) 0.40 Basion-prosthion (BPL) 0.30

Table 3.10. Sexing accuracy and classification results for the South China group as determined by discriminant function analysis.

62 Actual Group Membership Predicted Group Membership SEX N Male Female Male 33 30 3 Female 22 2 20 Ungrouped cases 3 0 3 Percentage of cases Male 100 90.1 9.9 Female 100 9.1 90.9 Ungrouped cases 100 0 100.0 *90.5% of original cases classified correctly

The unsexed crania were all placed in the female category according to the DFA, an acceptable result due to 90% of the original sample being correctly classified (table 3.10).

3.2.1.5 Northeast Asia Due to a low number of individuals of known sex in the Northeast Asian sample (table 3.1), the unsexed crania from this group were classified using the variables determined by the ‘standard’ East Asian sample above (table 3.2). Small samples from Korea, Japan, North China and the Ainu were also grouped with Northeast Asia, as on their own their sample size were insufficient to produce a satisfactory result, and all samples share a reasonable geographic relationship. In total, data from the crania of 30 males and 17 females were used to classify 40 unsexed individuals. Cranial length (g-l) and mastoid process height (ms-po) proved the strongest influence to classification with moderate contributions (table 3.11), followed by facial breadth (JUB) and cranial height (BBH). The results were for the most part positive, indicating that size differences were the major separating factor. Of the 40 unsexed crania, 30 were assigned to male and 10 to female (table 3.12). This result is considered satisfactory, as over 93% of the original crania of known sex were considered correctly classified.

63 Table 3.11. Structure matrix table reporting structure coefficients for function 1 for Northeast Asia. Variables in order of absolute size of correlation.

Variable Function 1 Glabella-lambda (g-l) 0.56 Mastoidale-porion (ms-po) 0.54 Bijugal breadth (JUB) 0.45 Basion-bregma (BBH) 0.40 Prosthion-bregma (BPL) 0.38 Bi-frontomalare orbitale (fmo-fmo) 0.30 Bi-frontomalare temporale (fmt-fmt) 0.23 Nasion-bregma (FRC) 0.21 Basion-prosthion (BPL) 0.16 Bimastoidale (ms-ms) 0.11 Bi-inferior zygomatic breadth -0.01

Table 3.12. Sexing accuracy and classification results for the Northeast Asia group as determined by discriminant function analysis.

Actual Group Membership Predicted Group Membership Sex N Male Female Male 30 26 4 Female 17 0 17 Ungrouped cases 40 30 10 Percentage of cases Male 100 86.7 13.3 Female 100 0 100.0 Ungrouped cases 100 75.0 25.0 * 93.4 % of original cases correctly classified

64 3.2.1.6 Native America The East Asian sexually dimorphic variables determined above were used to classify the unsexed crania in the Native American sample (n = 10) Despite no reported genetic relationship between Southeast Asia and Native Americans, this method was considered reasonable (though not totally satisfactory) due to evidence of a genetic relationship between Native Americans and Northeast Asians (e.g. Tokunaga et al, 2001). The structure matrix table generated for this sample revealed facial length/prognathism (BPL), cranial height (BBH) and facial height (pr-b) as the greatest contributors to sexual discrimination, although with moderate loadings (table 3.13). As table 3.14 shows, the 10 unsexed crania were classified as female on the basis of an original sample of 10 males and 13 females, all of which were 100% correctly classified. Thus, the classification results may be accepted with a high degree of confidence.

Table 3.13. Structure matrix table reporting structure coefficients for function 1 for Native America. Variables in order of absolute size of correlation.

Variable Function 1 Basion-prosthion (BPL) 0.41 Basion-bregma (BBH) 0.38 Prosthion-bregma (pr-b) 0.37 Bi-frontomalare orbitale (fmo-fmo) 0.24 Nasion-bregma (FRC) 0.23 Mastoidale-porion (ms-po) 0.23 Glabella-lambda (g-l) 0.23 Bijugal breadth (JUB) -0.12 Bi-frontomalare temporale (fmt-fmt) 0.11 Bimastoidale (ms-ms) 0.08 Bi-inferior zygomatic breadth 0.03

65 Table 3.14. Sexing accuracy and classification results for the Native American group as determined by discriminant function analysis.

Actual Group Membership Predicted Group Membership Sex N Male Female Male 10 10 0 Female 13 0 13 Ungrouped cases 10 0 10 Percentage of cases Male 100 100 0 Female 100 0 100 Ungrouped cases 100 0 100 * 100 % of original cases correctly classified

3.2.2 Caucasians

The Caucasian sample consisted of 12 males, 10 females and 7 crania of unknown sex. In order to assign a sex to the unsexed crania, variables discriminating the sexes needed to be ascertained. As above for the East Asian sensu lato group, the complete dataset of 45 variables underwent t-tests to determine those variables demonstrating significant male-female differences. The results are presented below (table 3.15), where it is observed that male means are significantly greater than female means. These variables were the used in a DFA in order to classify the unsexed Caucasian crania. Table 3.16 is the structure matrix table generated from the analysis, ranking the sexually dimorphic variables in order of their discriminating strength. Possibly due to the larger number of variables in the analysis in and/or a comparatively lower sample size comparison to the East Asians above, low loadings from all the variables are observed. The variables most strongly influencing the classification, albeit with low loadings, were cranial breadth (ASB, biporionic breadth), length (n-o) and facial height (BNL). As 100% of the crania of known sex were determined to be correctly classified, the resulting appointment of 7 unsexed crania to 3 males and 4 as females can be confidently accepted (table 3.17).

66 Table 3.15. Summary statistics of sexually dimorphic variables for the Caucasian group.

Variable Male (n=12) Female (n=10) Mean S.D Mean S.D p-value bijugal breadth (JUB) 114.11 4.80 107.57 4.70 <0.001 bi-frontomalare temporale (fmt-fmt) 103.46 5.25 98.66 5.37 <0.05 bi-alare (al-al) 14.93 1.48 13.17 1.89 <0.05 basion-bregma (BBH) 131.54 6.28 124.06 4.45 <0.01 nasion-nasospinale (n-ns) 48.70 3.38 45.75 2.10 <0.05 nasion-opisthion (n-o) 134.51 4.33 126.11 3.71 <0.001 nasion-basion (BNL) 99.18 4.13 92.19 3.28 <0.001 basion-prosthion (BPL) 90.79 5.24 85.82 4.39 <0.05 bipterionic breadth 118.48 7.49 112.16 5.15 <0.05 biauricular breadth (AUB) 122.16 6.40 115.26 4.30 <0.01 biporionic breadth 117.03 5.06 108.71 4.56 <0.001 biasterionic breadth (ASB) 111.76 3.97 102.83 4.23 <0.001 zygomaxillare-auriculare (zm-au) 70.42 3.18 65.81 2.89 <0.01 Bimastoidale (ms-ms) 104.75 5.33 96.65 7.48 <0.01 mastoidale-porion (ms-po) 30.83 2.80 28.07 3.26 <0.05 zygomaxillare-inferior zygomatic (IML) 32.99 2.38 30.39 2.35 <0.05 basion-opisthion (FOL) 37.47 1.99 35.44 2.17 <0.05 basion-sphenobasion (ba-sphba) 26.29 2.83 23.33 1.89 <0.01 staphylion-orale (sta-ol) 46.25 2.93 43.43 2.33 <0.05 glabella-lambda (g-l) 179.11 7.25 172.04 7.95 <0.05

67 Table 3.16. Structure matrix table reporting structure coefficients for function 1 for the Caucasians. Variables in order of absolute size of correlation.

Variable Function 1 Biasterionic breadth (ASB) 0.23 Nasion-opisthion 0.19 Nasion-basion (BNL) 0.17 Biporionic breadth 0.16 Zygomaxillare-auriculare 0.14 Bijugale (JUB) 0.13 Basion-bregma (BBH) 0.13 Bimastoidale 0.12 Biauriculare (AUB) 0.11 Bipterionic breadth 0.09 Basion-prosthion (BPL) 0.09 Alare-alare 0.09 Nasion-nasospinale 0.09 Basion-opisthion (FOL) 0.09 Mastoidale-porion 0.08 Bi-frontomalare temporale 0.08

Table 3.17. Sexing accuracy and classification results for the Caucasian group as determined by discriminant function analysis.

Actual Group Membership Predicted Group Membership Sex N Male Female Male 12 12 0 Female 10 0 10 Ungrouped cases 7 3 4 Percentage of cases Male 100 100 0 Female 100 0 100 Ungrouped cases 100 42.9 47.1 * 100 % of original cases correctly classified

68 3.2.3 Australia, Melanesia and Micronesia Melanesian, Micronesian and Australian samples were grouped together due to their geographic proximity and because of documented physical similarities of Melanesians with Australians and Micronesians (e.g. Howells, 1973). Grouping these samples also resulted in an increased sample size, so as to improve the reliability of the discriminant analysis T-tests were performed on 45 measurements to determine the variables that significantly distinguish the sexes. The results of t-tests are presented in table 3.18, where it is also observed that males are larger than females (means) for all sexually dimorphic variables. Once identified, the variables were used for DFA of the Australian, Melanesian and Micronesia crania of known sex in order to assign a sex to the 38 unsexed crania. Facial breadth variables (fmt-fmt, fmo-fmo, JUB), exhibiting moderate loadings, were identified as the strongest contributors to male-female discrimination (table 3.19). Remaining variables exhibit low contributions to the analysis. Observed low loadings could possibly be due to the relatively large number of significant sexually dimorphic variables.

Table 3.18. Summary statistics of sexually dimorphic variables for Australia, Melanesia and Micronesia.

Variable Male (n=23) Female (n=11) Mean S.D Mean S.D p-value bijugal breadth (JUB) 116.33 4.46 109.24 4.54 <0.001 bi-frontomalare orbitale 100.79 3.59 94.69 4.03 <0.001 bi-frontomalare temporale 107.06 4.14 100.33 3.90 <0.001 nasion-opisthion 135.49 4.86 128.97 5.47 <0.001 nasion-basion (BNL) 100.85 4.27 95.59 3.78 <0.001 basion-prosthion (BPL) 101.96 4.85 97.17 4.62 <0.01 biasterionic breadth (ASB) 108.48 4.66 102.45 4.79 <0.001 bimastoidale 102.17 3.85 97.76 3.87 <0.01 bi-inferior zygomatic breadth 122.84 6.24 116.09 4.29 <0.01 mastoidale-porion 34.25 3.59 28.18 4.40 <0.001 zygomaxillare-frontomalare temporale 44.04 2.89 40.65 3.20 <0.01 zygomaxillare-inferior zygomatic (IML) 37.70 3.61 32.30 3.06 <0.001 biauricular breadth (AUB) 120.29 5.62 113.15 4.41 <0.001 glabella-lambda 177.33 5.48 170.36 5.53 <0.001

69 All variables display positive loading, which implies that classification was based on the size differences of these variables. According the DFA results, 100% of the 23 male and 11 female crania from the combined Australia, Melanesia and Micronesia sample were classified correctly (table 3.20). Therefore, the classification of the 38 unsexed crania into 22 male and 16 female individuals is considered acceptable for this study.

Table 3.19. Structure matrix table reporting structure coefficients for function 1 for Australia, Melanesia and Micronesia. Variables in order of absolute size of correlation.

Variable Function 1 Bi-frontomalare temporale 0.44 Bifrontomalare orbitale 0.43 Bijugale (JUB) 0.39 Nasion-basion (BNL) 0.37 Zygomaxillare-inferior zygomatic (IML) 0.36 Mastoidale-porion 0.36 Nasion-opisthion 0.33 Glabella-lambda 0.32 Biauriculare (AUB) 0.32 Biasterionic breadth (ASB) 0.28 Zygomaxillare-frontomalare orbitale 0.28 Bi-inferior zygomatic breadth 0.27 Bimastoidale 0.25 Basion-prosthion (BPL) 0.20

70 Table 3.20. Sexing accuracy and classification results for Australia, Melanesia and Micronesia, as determined by discriminant function analysis.

Actual Group Membership Predicted Group Membership Sex N Male Female Male 23 23 0 Female 11 0 11 Ungrouped cases 38 22 16 Percentage of cases Male 100 100 0 Female 100 0 100 Ungrouped cases 100 57.9 42.1 * 100 % of original cases correctly classified

3.2.4 Africa As table 3.1 shows, the known number of male and female crania in the Africa sample is small (n = 2), and therefore, it is most unlikely that this sample could generate accurate classifications for the unsexed crania. In order to increase both male and female sample sizes, data drawn from Howells’ global population study (Howells, 1989) were included. Due to the inclusion of these external data, only variables common to both studies could be used. A total of 13 of Howells’ ‘standard’ linear measurements (Howells, 1989) were adopted in the current study, and it was these measurements that were subjected to t-tests to determine their discriminating power. Nine out of the 13 measurements were found to significantly discriminate the sexes in the Africa sample, the results of which are presented in table 3.21. As observed in all other analyses above, male means are significantly larger than female means for all variables presented (table 3.21). The structure matrix table generated from the DFA (table 3.22) reveals posterior cranial breadth (ASB) as the strongest discriminating variable, closely followed by facial length (BNL). All remaining values exhibit similarly low loadings. Results of the DFA indicate a classification accuracy of approximately 90% in regards to the sample of African crania of known sex (table 3.23), thus making the classification of 9 males and 9 males from 18 unsexed crania a satisfactory result.

71 Table 3.21. Summary statistics of sexually dimorphic variables for Africa1.

Variable Male (n=9) Female (n=12) Mean S.D Mean S.D p-value prosthion-nasion (NPH) 65.27 4.29 61.01 4.29 <0.001 bijugal breadth (JUB) 116.84 3.60 112.59 4.59 <0.01 zygomaxillary breadth (ZMB) 98.17 4.49 94.39 4.93 <0.05 basion-bregma (BBH) 131.41 5.24 128.36 4.20 <0.05 nasion-bregma (FRC) 110.77 5.58 105.42 5.29 <0.01 nasion-basion (BNL) 101.04 4.98 95.49 3.66 <0.001 basion-prosthion (BPL) 101.59 5.71 96.19 5.89 <0.01 bistephanic breadth (STB) 95.51 5.48 90.95 5.10 <0.01 biauricular breadth (AUB) 117.18 3.64 113.24 4.58 <0.01 biasterionic breadth (ASB) 106.68 3.94 101.83 3.20 <0.001 1Sample numbers represent the number of African individuals in the current study

Table 3.22. Structure matrix table reporting structure coefficients for function 1 for Africa. Variables in order of absolute size of correlation.

Variable Function 1 Biasterionic breadth (ASB) 0.59 Nasion-basion (BNL) 0.54 Nasion-prosthion (NPH) 0.45 Bijugale (JUB) 0.42 Nasion-bregma (FRC) 0.40 Biauriculare (AUB) 0.39 Basion-prosthion (BPL) 0.35 Zygomaxillary breadth (ZMB) 0.30 Basion-bregma (BBH) 0.25

72 Table 3.23. Sexing accuracy and classification results for the African group as determined by discriminant function analysis1.

Actual Group Membership Predicted Group Membership Sex N Male Female Male 19 16 3 Female 22 1 21 Ungrouped cases 18 9 9 Percentage of cases Male 100 84.2 15.8 Female 100 4.5 95.5 Ungrouped cases 100 50.0 50.0

* 89.9 % of original cases correctly classified 1 Sample numbers are inclusive of a random African sample from Howells (1989)

3.3 Summary and Conclusions

In sum, while sexually discriminating variables are not constant between all samples, height of the mastoid process (ms-po) and facial breadth (fmo-fmo, fmt-fmt, JUB) commonly dominated as the strongest sexually dimorphic features for all of East Asia sensu lato. Size of the mastoid process, assessed both non-metrically and metrically, has long been recognised as a sexual indicator in humans (e.g. Keen, 1950; Giles and Elliot, 1963; Buikstra and Ubelaker, 1994; Bass, 1995; Patil and Mody, 2005; Franklin et al, 2006; Williams and Rogers, 2006), with males usually exhibiting larger processes. The sexually dimorphic differences in the mastoid process have in part been attributed to the development of the process in response to differences in size and force of the associated musculature, ie. sternocleidomastoid (Keen, 1950; Franklin et al, 2006). Facial breadth, or strictly biorbital breadth (fmt-fmt, fmo-fmo), is not commonly assessed for its sex- discriminating strength in the literature. However, its presence in the present study as one of the stronger sexually dimorphic variables in East Asia sensu lato may be attributed to a possible relationship between upper face robusticity and masticatory muscle force (Lahr and Wright, 1996). Cranial length, breadth and facial length and height appear as the strongest sexual discriminators in the majority of the comparative samples. All of these variables feature prominently in many of the previous sexual dimorphism studies listed above.

73 Finally, there appears to be disagreement in the literature as to whether classifying the sex of individuals should be performed on a population specific basis. For example, in their 1963 study, Giles and Elliot stated that a classification accuracy of 82-89%, calculated from Caucasian and African American crania, was upheld when their technique was applied to Native Americans and chimpanzees. Kajanoja (1966) tested this theory on Finnish crania, and found that with a maximum accuracy of 65%, the theory of Giles and Elliot (1963) was questionable. This was later supported by Uytterschaut (1986), who found the construction of a race-independent sex function difficult, noting that his results should not be generalised to any given population. The current chapter, while primarily aimed at classifying unsexed crania, has highlighted that variables demonstrating sexual discriminating strength does appear to vary between geographic regions. This study however, was possibly affected by small sample sizes and variables that have not been studied in this context previously, but clearly this is a subject that warrants further investigation.

74 Chapter 4 Results Univariate Analysis Part A: Linear Measurements

4.1 Introduction

Summary statistics (median, range, standard deviation and coefficient of variation values) for 45 linear variables for pooled sex samples are presented in Appendix 1. Overall, sample dispersions and variability are virtually indistinguishable, exhibiting similar standard deviation (SD) and coefficient of variation (CV) values for all variables. These results suggest that the degree of relative within-group variation (CV) is globally uniform for these variables. Exceptions to this are samples exhibiting small sample sizes (n 5), which despite being corrected for low sample size (after Sokal and Braumann, 1980), tend to exhibit inflated CVs. A number of variables exhibit CVs that are uniformly inflated in comparison to the majority of variables. The variables concerned are alveolar height (pr-ns), nasal breadth al-al), interorbital breadth (mf-mf) and mastoid height (ms-po). The high variation for alveolar height, nasal breadth and interorbital breadth may be explained by their low heritability, suggesting variation may be due to large environmental influences during epigenesis (Carson, 2006). The high degree of variation in the height of the mastoid process is indicative of sexual dimorphism, as this feature is used routinely for sexual discriminaton (see Chapter 3). Variation in alveolar height may be due to individual variation in developmental plasticity due to environmental effects. Measurements involving prosthion exhibit moderate heritabilities which are significantly different to zero (Carson, 2006. NB: pr-ns used in the present study lacks published heritability values). It is difficult therefore, to attribute high variation to environmental influences alone. It may be that this feature (pr-ns) is characterised by high inter-individual variation associated with genetic polymorphism. To correct for any effects of sexual dimorphism on variation, pooled sex samples were disaggregated into sex specific samples (Appendix 1). Once separated, SD and CV remain relatively similar to pooled sex samples, although female-only samples tend to exhibit CVs that are marginally inflated in comparison to pooled sex

75 and male-only samples. This inflation may be attributed to the smaller sample sizes of the female-only samples, or may be a reflection of complex sex-specific population histories of East Asia (Perez et al, 2007). While SD and CVs between samples are virtually indistinguishable, sample medians exhibit considerable variation. Pooled sex and male-only samples exhibit similar values, possibly indicating that the pooled sex sample is heavily influenced by the male-only samples, as the male-only samples are predominantly greater in sample size compared to female-only samples. Only variables exhibiting apparent significant median differences between samples (ie. Asian versus non-Asian and/or divisions within East Asia sensu lato) were visually assessed with Box and Whisker plots (presented below), a heuristic device in which non-overlapping boxes are indicative of a significant difference at the < 1% level. Apparent significant median differences were confirmed statistically with a non- parametric ANOVA method, Kruskal-Wallis. Overall results of the Kruskal-Wallis tests are summarised below, while p-values of the non-parametric post-hoc tests, based on Bonferroni-corrected pairwise Mann-Whitney (Hammer et al, 2001) are presented in Appendix 2. Box and whisker (B&W) plots were created in the statistical program SPSS version 11.0, reporting median, interquartile range (box) and minimum and maximum values (whiskers) of each sample. This method of analysis using median values was selected so as to enable the inclusion of populations whose sample numbers were n < 5, and whose sample means may be statistically unreliable. Populations with low sample numbers are herein marked accordingly (*) and should be regarded with caution, as they may not accurately represent the actual population value of central tendency. Overall, B&W plots reveal that most samples are approximately normally distributed, with the exception of a few. Samples exhibiting skewed medians are mostly those with a sample size of n < 5. Whisker lengths demonstrate large ranges for a number of samples, while most remain relatively moderate in comparison. Samples are arranged within in each plot in order of increasing median.

76 4.2 Results

4.2.1 Breadth variables 4.2.1.1 Facial Breadths Facial breadth variables most useful for discriminating samples were interorbital breadth (mf-mf), upper facial breadth (fmo-fmo, fmt-fmt), mid-facial breadth (ZMB), zygomatic breadth (bi-inferior zygomatic breadth) and nasal breadth (al-al). All but one of them indicates separation of East Asian sensu lato from comparative samples, the specific details of which are discussed below. A distinction between East Asian and non-Asian samples, in particular Australia, Africa, Native America and the Caucasians, is observed for interorbital breadth (mf- mf). This separation is most distinct in pooled sex and male-only plots (fig 4.1-4.2) and is also suggested in the female-only plot (fig 4.3). The comparative samples tend to possess the broadest interorbital breadth, with East Asians (with the exception of South China) exhibiting moderate to narrow interorbital breadths. Highly significant median differences

Population Key 28.00 NA - Native America Sib - Siberia Mon - Mongolia Ain - Ainu 24.00 Kor - Korea Jap - Japan

) S.Chi - South China

m N.Chi - North China m ( 20.00 Bur - Burma

f * Lao - Laos

m - f * Viet - Vietnam

m Thai - Thailand Cam - Cambodia 16.00 Phi - Philippines And - Andaman Is. Nic - Nicobar Is. Bor - Borneo 12.00 Indo - Indonesia Mel - Melanesia

J Mo B K N T A L Me N Mi S I P A B V A N C C S A

n

a a h Mic - Micronesia u o i i . i h n o i u A a a . f

d

c n b e C

C

p o c

a

r r i d r s

m u

n l o

t

i h h Aus - Australia

c

i i Af - Africa Cauc - Caucasian Population Figure 4.1. Box and whisker plot of interorbital breadth (mf-mf) for pooled sex data. Populations are in

order of increasing median. * denotes sample size n < 5.

77 Population Key 28.00 NA - Native America Sib - Siberia * Mon - Mongolia * Ain - Ainu 24.00 Kor - Korea Jap - Japan

) S.Chi - South China m N.Chi - North China

(m Bur - Burma

f 20.00 Lao - Laos m

- * Viet - Vietnam f

m Thai - Thailand * Cam - Cambodia Phi - Philippines 16.00 And - Andaman Is. Nic - Nicobar Is. Bor - Borneo Indo - Indonesia Mel - Melanesia

J Mo N K B T A Mi I L N A P S N C Me B V C S A A

n

a a h Mic - Micronesia i o u i A n h i . a o i a . u f

d

c n b e C

C

p c

a o

r r d i r s

m u

n o l

t

i h h Aus - Australia

c

i i Af - Africa Cauc - Caucasian Population Figure 4.2. Box and whisker plot of interorbital breadth (mf-mf) for male-only data. Populations are in order of increasing median. * denotes sample size n < 5.

Population Key

NA - Native America Sib - Siberia 24.00 Mon - Mongolia Ain - Ainu * Kor - Korea Jap - Japan ) * S.Chi - South China m 20.00 * N.Chi - North China (m Bur - Burma f Lao - Laos

m * - f * * Viet - Vietnam

m Thai - Thailand 16.00 Cam - Cambodia Phi - Philippines And - Andaman Is. Nic - Nicobar Is. Bor - Borneo 12.00 Indo - Indonesia Mel - Melanesia

S J B K B I N Me L T V Mo A C A A P Mi C N N A S

n

a a

h i o o u . i i a u n h a A i f . Mic - Micronesia

d

b e n c C

C

p c

o a

r r r s d i

m u

o l n

t

h i h

c Aus - Australia

i i Af - Africa Cauc - Caucasian Population Figure 4.3. Box and whisker plot of interorbital breadth (mf-mf) for female-only data. Populations are in order of increasing median. * denotes sample size n < 5.

78 were detected in pooled sex (H: 86.6, p < 0.001), male-only (H: 64.69, p < 0.001) and female-only (H: 48.18, p < 0.001) plots using a Kruskal-Wallis test (see Appendix 2). Upper facial breadth variables fmo-fmo and fmt-fmt distinguish East Asia from comparative samples, albeit incompletely. The separation is observed for both variables in the pooled sex plot, while the male-only and female-only plots exhibit similar separation for variable fmo-fmo only. An East Asian versus non-Asian separation is implied in the male and female-only plots for the variable fmt-fmt, however, overlap between the samples is large (not shown). Separation is nearly complete for both variables (fmo-fmo, fmt-fmt) in the pooled sex plot (fig 4.4-4.5) and for variable fmo-fmo in male-only (fig 4.6), except for East Asian samples positioning with non-Asians in the pooled sex (Siberia and South China) and male-only plots (Siberia, South China and Cambodia). Despite a similar position in both pooled sex and male-only plots, the position of South China should be regarded with caution due to its relatively small sample sizes in both cases (n = 6, n = 5 respectively). The same applies to Cambodia in the male-only plot (n = 4). Australia and Africa display the broadest upper facial breadths, and are distinguished from Native America, Micronesia and Melanesia, which exhibit moderate medians. Aforementioned East Asian samples lie between them. The Caucasian sample does not plot with the comparative samples, exhibiting a moderate median for both variables (lying among East Asian samples). East Asian populations exhibit narrow to moderate median breadths, with the Andaman sample consistently the narrowest. Both variables (fmo- fmo, fmt-fmt) demonstrated significant differences in the pooled sex samples (H: 120.7, p < 0.001; H: 114.2, p < 0.001 respectively; refer to Appendix 2 for details). Significant differences were also found in the male-only sample (H: 95.96, p < 0.001; see Appendix 2). The female-only group clearly shows the Andaman sample as exhibiting one of the narrowest median upper facial breadths (fig 4.7), which is consistent for all three plots (pooled sex, male-only and female-only). Upper facial breadth (fmo-fmo) is narrow to moderate in East Asia, and broad in the comparative groups. A Kruskal- Wallis test identified highly significant differences (H: 75.16, p < 0.00; see Appendix 2).

79 Population Key 110.00 NA - Native America Sib - Siberia Mon - Mongolia Ain - Ainu Kor - Korea * Jap - Japan ) S.Chi - South China

m 100.00 N.Chi - North China (m Bur - Burma o *

Lao - Laos fm

- Viet - Vietnam o Thai - Thailand

fm Cam - Cambodia 90.00 Phi - Philippines And - Andaman Is. Nic - Nicobar Is. Bor - Borneo Indo - Indonesia Mel - Melanesia

A B J K B N C P T A V C Mo L I N Me N Mi S S A A

n Mic - Micronesia

a a

h

n o o u i a h i i a . A . i f u

d

c n e C b

C

p c

a o

d r r r i s

u m

n o l t Aus - Australia

i h h

c

i i Af - Africa Cauc - Caucasian Population Figure 4.4. Box and whisker plot of upper facial breadth (fmo-fmo) for pooled sex data. Populations are in order of increasing median. * denotes sample size n < 5.

Population Key

NA - Native America Sib - Siberia Mon - Mongolia 110.00 * Ain - Ainu Kor - Korea Jap - Japan

) S.Chi - South China

m m N.Chi - North China

( *

Bur - Burma t

m Lao - Laos

100.00 Viet - Vietnam t-f Thai - Thailand fm Cam - Cambodia Phi - Philippines And - Andaman Is. Nic - Nicobar Is. 90.00 Bor - Borneo Indo - Indonesia Mel - Melanesia

A A A C J T B C B K N Mo V A N P I L Me Mi N S S

n

a a Mic - Micronesia h

f n a o a u o i i i . h A i . u

d

c e n b C

C

p c

a o

d r r r i s

u m

n o l

t

i h h Aus - Australia

c

i i Af - Africa Cauc - Caucasian Population Figure 4.5. Box and whisker plot of upper facial breadth (fmt-fmt) for pooled sex data. Populations are in order of increasing median. * denotes sample size n < 5.

80 Population Key 110.00 NA - Native America * Sib - Siberia Mon - Mongolia * Ain - Ainu

* Kor - Korea ) Jap - Japan

m 100.00 S.Chi - South China

m N.Chi - North China

( Bur - Burma o

* Lao - Laos fm

- Viet - Vietnam o Thai - Thailand

fm Cam - Cambodia Phi - Philippines 90.00 And - Andaman Is. Nic - Nicobar Is. Bor - Borneo Indo - Indonesia Mel - Melanesia

N A S S C A A J A K N P T B V L Mo C B I N Mi Me

n

a a Mic - Micronesia h

A f i . a u n i o i h o i a u .

d

b C n c e

C

p c

a o

s d r i r r

u m

n o l

t

i h h Aus - Australia

c

i i Af - Africa Cauc - Caucasian Population Figure 4.6. Box and whisker plot of upper facial breadth (fmo-fmo) for male-only data. Populations are in order of increasing median. * denotes sample size n < 5.

Population Key

105.00 NA - Native America Sib - Siberia Mon - Mongolia Ain - Ainu 100.00 * Kor - Korea

Jap - Japan )

S.Chi - South China m

m * N.Chi - North China

( 95.00 **Bur - Burma o

* * Lao - Laos fm

- Viet - Vietnam o Thai - Thailand

fm 90.00 Cam - Cambodia Phi - Philippines And - Andaman Is. Nic - Nicobar Is. 85.00 Bor - Borneo Indo - Indonesia Mel - Melanesia

Mo C L N A A S S N A K A P B B N T J Mi Me I V C

n Mic - Micronesia a a

h

a i u i i . A f o n h u o . i a

d

e c n b C

C

p c

a o

s r d i r r

u m

l o n t Aus - Australia

h h i

c

i i Af - Africa Cauc - Caucasian Population Figure 4.7. Box and whisker plot of upper facial breadth (fmo-fmo) for female-only data. Populations are in order of increasing median. * denotes sample size n < 5.

81 Separations observed in upper facial breadth are reversed for the mid-facial breadth variable ZMB. East Asia is separated from Australian, Melanesian and Caucasian samples, which display the narrowest median breadths for pooled sex (fig 4.8), male- only (fig 4.9) and female-only plots (fig 4.10). Kruskal-Wallis tests indicate highly significant differences between samples in all three plots (H: 119.8, p < 0.001; H: 78.92, p < 0.001; H: 68.95, p < 0.001, respectively. Refer to Appendix 2 for more detail). The Andaman sample is located among this cluster for all three plots, displaying a median breadth similar to the Australians. There is considerable overlap between remaining East Asian populations across all three plots (pooled sex, male-only and female-only), exhibiting median breadths ranging from moderate to broad; although there does not appear to be a large median difference between the narrowest (Korea) and broadest (South China) East Asian population, and all display similar range values. Remaining comparative samples are indistinct from East Asians for this variable for all three plots, however, in the female-only group, African and Native American samples display the broadest median breadths, separating them from the East Asians.

Population Key

NA - Native America Sib - Siberia Mon - Mongolia 110.00 Ain - Ainu Kor - Korea * Jap - Japan ) * S.Chi - South China

m N.Chi - North China 100.00

m Bur - Burma (

B Lao - Laos Viet - Vietnam

ZM Thai - Thailand 90.00 Cam - Cambodia Phi - Philippines And - Andaman Is. Nic - Nicobar Is. Bor - Borneo 80.00 Indo - Indonesia Mel - Melanesia

C A A Me K P B N I S Mo B C N T L Mi N J A A V S

n

a a Mic - Micronesia h

a n u o h u i i o a . A f i i .

d

c b n e C

C

c p

a o

d s r i r r

u m

l o n

t

h i h Aus - Australia

c

i i Af - Africa Cauc - Caucasian Population

Figure 4.8. Box and whisker plot of mid-facial breadth (ZMB) for pooled-sex data. Populations are in order of increasing median. * denotes sample size n < 5.

82 Population Key

NA - Native America Sib - Siberia Mon - Mongolia Ain - Ainu 110.00 * Kor - Korea * Jap - Japan

) * S.Chi - South China

m * N.Chi - North China

m Bur - Burma ( 100.00 Lao - Laos B Viet - Vietnam

ZM Thai - Thailand Cam - Cambodia Phi - Philippines 90.00 And - Andaman Is. Nic - Nicobar Is. Bor - Borneo Indo - Indonesia Mel - Melanesia

C A A Me P N K C B A L B J I N Mo S N A T V Mi S

n Mic - Micronesia

a a

h

a n u h i o a u f o A i . i i .

d

c b n e C

C

p c

o a

d s i r r r

u m

l o n t Aus - Australia

h i h

c

i i Af - Africa Cauc - Caucasian Population Figure 4.9. Box and whisker plot of mid-facial breadth (ZMB) for male-only data. Populations are in order of increasing median. * denotes sample size n < 5.

Population Key 110.00 NA - Native America Sib - Siberia * Mon - Mongolia Ain - Ainu 100.00 * Kor - Korea * * * Jap - Japan ) S.Chi - South China

m N.Chi - North China m ( * Bur - Burma

B Lao - Laos 90.00 Viet - Vietnam

ZM Thai - Thailand Cam - Cambodia Phi - Philippines And - Andaman Is. Nic - Nicobar Is. 80.00 Bor - Borneo Indo - Indonesia Mel - Melanesia

L Mo S N A C A A Me N P B J S K T I B Mi V N C A

n

a a

h Mic - Micronesia

. A f a n u . h u i o o i i a i

d

b e c n C

C

p c

a o

d s i r r r

u m

l o n

t

h i h Aus - Australia

c

i i Af - Africa Cauc - Caucasian Population

Figure 4.10. Box and whisker plot of mid-facial breadth (ZMB) for female-only data. Populations are in order of increasing median. * denotes sample size n < 5.

83 Zygomatic breadth at the inferior zygotemporal suture, is the only facial breadth measurement that does not separate East Asian from non-Asian populations. In the current study, this variable serves to separate Northeast Asia from remaining East Asian and non-Asian samples in both pooled sex and male-only plots. No such observation is made in the female-only plot (not shown). Pooled sex and male-only plots both exhibit significant separations (H: 86.69, p < 0.001; H: 93.82, p < 0.001, respectively; see Appendix 2). Pooled sex (fig 4.11) and male-only (fig 4.12) plots display Northeast Asians (Siberia and Mongolia) as having the broadest median breadths across the most posterior point of the zygomatic. The male only plot contains South Chinese and Ainu samples in thisgrouping, but their sample sizes are small (n = 3, n = 1 respectively). The Andaman sample is clearly the population with the narrowest median breadth. Extensive overlap is observed between all remaining samples.

Population Key 140.00

) NA - Native America

m Sib - Siberia Mon - Mongolia

(m Ain - Ainu h

t * Kor - Korea d 130.00 *

a Jap - Japan e

r S.Chi - South China

cb N.Chi - North China i t Bur - Burma

a 120.00 Lao - Laos m

o Viet - Vietnam g

y Thai - Thailand

rz Cam - Cambodia o

i Phi - Philippines

r 110.00 And - Andaman Is. fe

n Nic - Nicobar Is.

i -

i Bor - Borneo b Indo - Indonesia Mel - Melanesia

A N Me C A B L B I C Mi N V P J T N A S A K Mo S

n

a a

h

n i a u u o a A i h . i . f o i Mic - Micronesia

d

c e n C b

C

c p

o a

d s r r i r

u m

l o n

t

i h h Aus - Australia c

i i Af - Africa Cauc - Caucasian Population

Figure 4.11. Box and whisker plot of zygomatic breadth (bi-inferior zygomatic breadth) for pooled sex data. Populations are in order of increasing median. * denotes sample size n < 5.

84 Population Key 140.00 NA - Native America

) Sib - Siberia m Mon - Mongolia

(m Ain - Ainu h t * * Kor - Korea d 130.00 *

a Jap - Japan e

r S.Chi - South China N.Chi - North China cb *

ti Bur - Burma

a Lao - Laos m

o 120.00 Viet - Vietnam g

y Thai - Thailand

Cam - Cambodia

r z o

i Phi - Philippines

r And - Andaman Is. fe

n Nic - Nicobar Is.

i 110.00 -

i Bor - Borneo

b Indo - Indonesia Mel - Melanesia

A N C Me L B N T C A B K J P I V N A Mi Mo S S A

n Mic - Micronesia a a

h

n i a u A a f o o h i . u i . i

d

c e b C n

C

p c

o a

d r r r i s

u m

l o n t Aus - Australia

i h h

c

i i Af - Africa Cauc - Caucasian Population Figure 4.12. Box and whisker plot of zygomatic breadth (bi-inferior zygomatic breadth) for male-only data. Populations are in order of increasing median. * denotes sample size n < 5.

Nasal breadth (al-al) distinguishes Native American and Pacific populations (Australia, Melanesia and Micronesia) and East Asia sensu stricto (North and South China, Japan, Korea and the Ainu) from all remaining populations. This trend is apparent in pooled sex (fig 4.13), male-only (fig 4.14) and female-only (fig 4.15) plots. The aformentioned populations display a broad to (high) moderate median nasal apertures for all three plots, with the remainder of the samples exhibiting a moderate morphology. Significant median differences (Appendix 2) were identified for all three plots: pooled sex (H: 184.9, p < 0.001), male-only (H: 96.55, p < 0.001) and female- only (H: 96.13, p < 0.001).

4.2.1.2 Cranial Breadths Cranial breadth variables to be discussed are the anterior breadth variables of bistephanic (STB) and bipterionic breadth and the posterior breadth variables of biauricular breadth (AUB), biporionic breadth and bimastoidale. Cranial breadth measurements separate samples based on both suggestions of a north-south cline, and of Asian-non Asian separations, the details of which are discussed below.

85 Population Key 20.00 NA - Native America Sib - Siberia Mon - Mongolia * Ain - Ainu 17.50 Kor - Korea Jap - Japan * S.Chi - South China

) N.Chi - North China m

Bur - Burma (m

l 15.00 Lao - Laos a

- Viet - Vietnam l

a Thai - Thailand Cam - Cambodia Phi - Philippines 12.50 And - Andaman Is. Nic - Nicobar Is. Bor - Borneo Indo - Indonesia 10.00 Mel - Melanesia

N A T C Mo B L B V S I C A A P S A N Mi J N K Me

n Mic - Micronesia

a a

h

i n a o u i i a i f h . u . A o

d

c e b n C

C

o c p

a

d r r i s r

m u

n o l

t Aus - Australia

i h h

c

i i Af - Africa Cauc - Caucasian Population Figure 4.13. Box and whisker plot of nasal breadth (al-al) for pooled sex data. Populations are in order of increasing median. * denotes sample size n < 5.

Population Key 20.00 NA - Native America Sib - Siberia * Mon - Mongolia 18.00 * Ain - Ainu Kor - Korea Jap - Japan

) * S.Chi - South China

m 16.00 N.Chi - North China

Bur - Burma (m

l Lao - Laos a *

- Viet - Vietnam l a 14.00 Thai - Thailand Cam - Cambodia Phi - Philippines And - Andaman Is. Nic - Nicobar Is. 12.00 Bor - Borneo Indo - Indonesia Mel - Melanesia

N T C L V B A B I S C Mo P A S A A Mi N J K Me N

n

a a Mic - Micronesia

h

i a i o n u i a h f . i u . o A

d

c e b C n

C

o c p

a

r d r i s r

m u

o n l t Aus - Australia i h h

c

i i Af - Africa Cauc - Caucasian Population

Figure 4.14. Box and whisker plot of nasal breadth (al-al) for male-only data. Populations are in order of increasing median. * denotes sample size n < 5.

86 Population Key

NA - Native America Sib - Siberia 18.00 * Mon - Mongolia * Ain - Ainu Kor - Korea Jap - Japan 16.00 S.Chi - South China ) * N.Chi - North China m * * Bur - Burma (m *

l Lao - Laos a

- Viet - Vietnam l 14.00

a Thai - Thailand Cam - Cambodia Phi - Philippines 12.00 And - Andaman Is. Nic - Nicobar Is. Bor - Borneo Indo - Indonesia 10.00 Mel - Melanesia

A N B C Mo T S I B C A L V P A N A S J Mi N K Me

n Mic - Micronesia

a a

h

n i o a i u a f i h i . u . A o

d

c b e n C

C

o p c

a

d r r i s r

m u

n o l

t Aus - Australia

i h h

c

i i Af - Africa Cauc - Caucasian Population Figure 4.15. Box and whisker plot of nasal breadth (al-al) for female-only data. Populations are in order of increasing median. * denotes sample size n < 5.

Anterior breadth variables separate within East Asia, and between East Asia and non-Asians. The most superior of the variables, bistephanic breadth (STB), shows moderate separation of Australia and Melanesia, and to an extent, the Native Americans, from East Asia in pooled sex (fig 4.16), male-only (fig 4.17) and female- only (fig 4.18) plots, with the comparative samples exhibiting narrow median values. Conversely, the Caucasians are separated from East Asia in pooled sex and male-only plots. East Asians display moderate to broad median breadths, with the Andaman and Nicobar samples tending to display the narrowest east Asian medians. The Caucasian sample clearly demonstrates the broadest median breadth across these landmarks for the pooled sex and male-only groups. Kruskal-Wallis tests indicate highly significant differences in pooled sex (H: 98.85, p < 0.001), male-only (H: 57.03, p < 0.001) and female-only (H: 58.46, p < 0.001) samples (see Appendix 2 for more details).

87 Population Key

NA - Native America Sib - Siberia 120.00 * Mon - Mongolia Ain - Ainu * Kor - Korea Jap - Japan S.Chi - South China ) 110.00

m N.Chi - North China

m Bur - Burma ( Lao - Laos

TB Viet - Vietnam

S 100.00 Thai - Thailand Cam - Cambodia Phi - Philippines And - Andaman Is. 90.00 Nic - Nicobar Is. Bor - Borneo Indo - Indonesia Mel - Melanesia

Me A A N N J N A A Mi B V P S B K C Mo L S T I C

n

a a Mic - Micronesia h

u n A i . i f o i h . u o a i a

d

c n e C b

C

p c

o a

s d r i r r

m u

l n o

t

h h i Aus - Australia

c

i i Af - Africa Cauc - Caucasian Population

Figure 4.16. Box and whisker plot of anterior cranial breadth (STB) for pooled sex data. Populations are in order of increasing median. * denotes sample size n < 5.

Population Key

NA - Native America * * Sib - Siberia 120.00 * Mon - Mongolia Ain - Ainu * Kor - Korea Jap - Japan

110.00 S.Chi - South China )

m N.Chi - North China

m Bur - Burma ( Lao - Laos

TB 100.00 Viet - Vietnam S Thai - Thailand Cam - Cambodia Phi - Philippines And - Andaman Is. 90.00 Nic - Nicobar Is. Bor - Borneo Indo - Indonesia Mel - Melanesia

Mi I C K C Me A N A N J S A B N Mo P B L A S V T

n

a a Mic - Micronesia h

a o a u i n A i f o . h u i . i

d

c b n C e

C

p c

o a

r s d r i r

m u

o l n

t

h h i Aus - Australia

c

i i Af - Africa Cauc - Caucasian Population Figure 4.17. Box and whisker plot of anterior cranial breadth (STB) for male-only data. Populations are in order of increasing median. * denotes sample size n < 5.

88 Population Key

NA - Native America Sib - Siberia 120.00 Mon - Mongolia Ain - Ainu Kor - Korea Jap - Japan * S.Chi - South China ) 110.00

m * N.Chi - North China

m * * * Bur - Burma ( * Lao - Laos

TB Viet - Vietnam

S 100.00 Thai - Thailand Cam - Cambodia Phi - Philippines And - Andaman Is. 90.00 Nic - Nicobar Is. Bor - Borneo Indo - Indonesia Mel - Melanesia

A Me J A N V Mi I N N B K A P C A B S T L C S Mo

n

a a Mic - Micronesia h

u n A i . i u o i h a f o . a i

d

e c n C b

C

p c

a o

s d r r i r

m u

l o n

t

h h i Aus - Australia

c

i i Af - Africa Cauc - Caucasian Population Figure 4.18. Box and whisker plot of anterior cranial breadth (STB) for female-only data. Populations are in order of increasing median. * denotes sample size n < 5.

The inferior anterior cranial breadth variable, bipterionic breadth, appears to distinguish Northeast Asia from the remaining East Asian populations, and suggests the presence of a north to south cline. Figures 4.19-4.21 show Siberia and Mongolia as having two of, if not the, broadest breadths at pterion for pooled sex, male-only and female-only plots respectively. They are distinct from the rest of the samples. Korea joins the Northeast Asians in all three groups, but its small sample size (n = 3) urges caution when regarding its position. The positioning of comparative samples Australia, Melanesia and Caucasian observed above for STB are similar for the current variable, but not as distinct. All three plots exhibit significant separations (H: 150.4, p < 0.001; H: 111.2, p < 0.001; H: 71.16, p < 0.001 for pooled sex, male-only and female-only plots respectively; see Appendix 2). The posterior cranial breadth variable of biauricular breadth (AUB) displays evidence of a north-south cline for pooled sex (fig 4.22) male-only (fig 4.24) and female-only (fig 4.26) plots with the northern East Asian populations, particularly Siberia and Mongolia, possessing among, if not the, broadest median. The remaining East Asians, with the exception of the Andaman and Nicobar samples, display moderate median values.

89 Population Key 130.00 * NA - Native America Sib - Siberia Mon - Mongolia ) Ain - Ainu

m 120.00 * Kor - Korea m

( Jap - Japan

th S.Chi - South China

d N.Chi - North China a

e 110.00 Bur - Burma r Lao - Laos

ic b Viet - Vietnam n

o Thai - Thailand i

r Cam - Cambodia

e 100.00

t Phi - Philippines p

i And - Andaman Is. b Nic - Nicobar Is. Bor - Borneo 90.00 Indo - Indonesia Mel - Melanesia

N A A Me C Mi S P B L B T A N J A N I V C Mo S K

n

a a Mic - Micronesia h

i n u a . h u o f A i . i a i o

d

c C n e b

C

c p

o a

d s i r r r

m u

l o n

t

h i h Aus - Australia

c

i i Af - Africa Cauc - Caucasian Population Figure 4.19. Box and whisker plot of anterior cranial breadth (bipterionic breadth) for pooled sex data. Populations are in order of increasing median. * denotes sample size n < 5.

Population Key 130.00 * NA - Native America Sib - Siberia Mon - Mongolia

) Ain - Ainu m 120.00 Kor - Korea m * ( * Jap - Japan

th * S.Chi - South China

d N.Chi - North China

a e

r Bur - Burma

110.00 Lao - Laos cb

i Viet - Vietnam n

o Thai - Thailand i

r Cam - Cambodia e

t Phi - Philippines p i And - Andaman Is. b 100.00 Nic - Nicobar Is. Bor - Borneo Indo - Indonesia Mel - Melanesia

N A Me A P C A N T Mi B N B I J V L A S S Mo C K

n

a a

h Mic - Micronesia

i u n h a f A o . u i i . i a o

d

c e n C b

C

c p

a o

s d i r r r

m u

l o n

t

i h h Aus - Australia

c

i i Af - Africa Cauc - Caucasian Population Figure 4.20. Box and whisker plot of anterior cranial breadth (bipterionic breadth) for male-only data. Populations are in order of increasing median. * denotes sample size n < 5.

90 Population Key

NA - Native America 120.00 Sib - Siberia * Mon - Mongolia

) Ain - Ainu

m * Kor - Korea m

( Jap - Japan * S.Chi - South China th 110.00 *

d N.Chi - North China a

e * Bur - Burma r * Lao - Laos

ic b Viet - Vietnam

n Thai - Thailand o

i 100.00

r Cam - Cambodia e

t Phi - Philippines p i And - Andaman Is. b Nic - Nicobar Is. Bor - Borneo 90.00 Indo - Indonesia Mel - Melanesia

A N N Me J V A Mi B T B C S L A P I A N C K Mo S

n Mic - Micronesia

a a

h

u . i i n u o a . f h i A a o i

d

c e C n b

C

p c

a o

s d r r i r

m u

l o n t Aus - Australia

h i h

c

i i Af - Africa Cauc - Caucasian Population Figure 4.21. Box and whisker plot of anterior cranial breadth (bipterionic breadth) for female-only data. Populations are in order of increasing median. * denotes sample size n < 5.

The comparative groups tend to display moderate median breadths at the narrow end of the scale, and are within the range of the East Asians. A similar north-south pattern is apparent in the analysis of biporionic breadth (figs 4.23, 4.25 and 4.27), which is not surprising due to its close physical proximity to AUB. The presence of small samples Korea (n = 3), Cambodia (n = 4) and South China (n = 3) reduces confidence in the accuracy of the north to south East Asian division in the female-only plot (fig 4.24). Kruskal-Wallis tests (Appendix 2) detected significant differences for both AUB and biporionic breadth in pooled sex (H: 185.4, p < 0.001; H: 167.3, p < 0.001), male- only (H: 146.0, p < 0.001; H: 135.2, p < 0.001) and female-only (H: 77.38, p < 0.001; H: 71.71, p < 0.001).

91 Population Key

NA - Native America 140.00 Sib - Siberia Mon - Mongolia Ain - Ainu Kor - Korea

130.00 **Jap - Japan ) S.Chi - South China

m N.Chi - North China

m Bur - Burma ( 120.00 Lao - Laos

UB Viet - Vietnam

A Thai - Thailand Cam - Cambodia 110.00 Phi - Philippines And - Andaman Is. Nic - Nicobar Is. Bor - Borneo 100.00 Indo - Indonesia Mel - Melanesia

A N A A Mi C Me A B B S P L J N C V T I N K S Mo

n Mic - Micronesia

a a

h

n i u f a i u o . h A a i . o i

d

c n C e b

C

c p

o a

d s r r i r

u m

l o n t Aus - Australia

h i h

c

i i Af - Africa Cauc - Caucasian Population Figure 4.22. Box and whisker plot of posterior cranial breadth (AUB) for pooled sex data. Populations are in order of increasing median. * denotes sample size n < 5.

Population Key

130.00 NA - Native America Sib - Siberia Mon - Mongolia

) Ain - Ainu

m * * Kor - Korea m

( 120.00 Jap - Japan h

t S.Chi - South China

d N.Chi - North China a

e Bur - Burma r Lao - Laos

cb 110.00

i Viet - Vietnam n

o Thai - Thailand i

r Cam - Cambodia o

p Phi - Philippines i

b And - Andaman Is. 100.00 Nic - Nicobar Is. Bor - Borneo Indo - Indonesia Mel - Melanesia

A N A Mi A Me A C B L B V P N J T I C S S N K Mo

n

a a

h n i u i f a o u i h A a . i . o Mic - Micronesia

d

c n e C b

C

c p

o a

d s r r i r

u m

l o n

t

i h h

c Aus - Australia

i i Af - Africa Cauc - Caucasian Population Figure 4.23. Box and whisker plot of posterior cranial breadth (biporionic breadth) for pooled sex data. Populations are in order of increasing median. * denotes sample size n < 5.

92 Population Key

NA - Native America 140.00 Sib - Siberia Mon - Mongolia Ain - Ainu Kor - Korea Jap - Japan 130.00

) S.Chi - South China

m N.Chi - North China m

( Bur - Burma Lao - Laos

UB 120.00 Viet - Vietnam A * Thai - Thailand * * Cam - Cambodia * Phi - Philippines And - Andaman Is. 110.00 Nic - Nicobar Is. Bor - Borneo Indo - Indonesia Mel - Melanesia

A N A A Me C B B P A L C J N V I T Mi K N S S Mo

n

a a

h Mic - Micronesia

n i f u a o u h i a A i o . . i

d

c n e C b

C

p c

o a

d s r r i r

u m

l o n

t

i h h Aus - Australia

c

i i Af - Africa Cauc - Caucasian Population Figure 4.24. Box and whisker plot of posterior cranial breadth (AUB) for male-only data. Populations are in order of increasing median. * denotes sample size n < 5.

Population Key

130.00 NA - Native America Sib - Siberia Mon - Mongolia ) * * Ain - Ainu m Kor - Korea

m * ( 120.00 * Jap - Japan

h S.Chi - South China t

d N.Chi - North China a

e Bur - Burma

r Lao - Laos

cb i Viet - Vietnam 110.00

n Thai - Thailand

o i

r Cam - Cambodia

o Phi - Philippines p

i And - Andaman Is. b Nic - Nicobar Is. 100.00 Bor - Borneo Indo - Indonesia Mel - Melanesia

A N A A Me B L A B C Mi J C P N T V N I K S S Mo

n Mic - Micronesia

a a

h

n i f u u i o a a h A i . o i .

d

c n e b C

C

c p

o a

d s r r i r

m u

l o n t Aus - Australia

i h h

c

i i Af - Africa Cauc - Caucasian Population Figure 4.25. Box and whisker plot of posterior cranial breadth (biporionic breadth) for male-only data. Populations are in order of increasing median. * denotes sample size n < 5.

93 Population Key 130.00 * NA - Native America * Sib - Siberia Mon - Mongolia * Ain - Ainu Kor - Korea Jap - Japan 120.00 * ) * * S.Chi - South China

m N.Chi - North China

m Bur - Burma ( Lao - Laos

UB Viet - Vietnam

A 110.00 Thai - Thailand Cam - Cambodia Phi - Philippines And - Andaman Is. Nic - Nicobar Is. Bor - Borneo 100.00 Indo - Indonesia Mel - Melanesia

A N A Mi N B Me I C A B J P A T S L V S K N C Mo

n Mic - Micronesia

a a

h

n i u . u a f o h i . i i o A a

d

c n C e b

C

c p

a o

d s r r i r

u m

l o n t Aus - Australia

h i h

c

i i Af - Africa Cauc - Caucasian Population Figure 4.26. Box and whisker plot of posterior cranial breadth (AUB) for female-only data. Populations are in order of increasing median. * denotes sample size n < 5.

Population Key

NA - Native America * * Sib - Siberia 120.00 Mon - Mongolia

) Ain - Ainu

m Kor - Korea

m Jap - Japan

( h S.Chi - South China t * N.Chi - North China d * a * Bur - Burma e 110.00 r * Lao - Laos

cb Viet - Vietnam i

n Thai - Thailand o

i Cam - Cambodia r

o Phi - Philippines p i And - Andaman Is.

b 100.00 Nic - Nicobar Is. Bor - Borneo Indo - Indonesia Mel - Melanesia

A N N Mi J A Me B C A I P B L A T V S S N C K Mo Mic - Micronesia

n

a a

h

n . i u o a i h u f i . i A a o

d

c n e C b

C

c p

o a

d s r i r r u m Aus - Australia l o n

t

h i h

c

i i Af - Africa Cauc - Caucasian Population Figure 4.27. Box and whisker plot of posterior cranial breadth (biporionic breadth) for female-only data. Populations are in order of increasing median. * denotes sample size n < 5.

94 Bimastoidale, the last of the posterior cranial breadth measurements to be discussed, separates Northeast Asia from the remaining East Asian populations in a similar pattern to variables AUB and biporionic breadth. Figures 4.28-4.30 show Siberia and Mongolia as being consistently broader than most remaining samples, exhibiting broad median breadths at the level of the mastoid processes for pooled sex, male-only and female only plots respectively. Korea is also consistently located with the Northeast Asians, but its sample size is small (n = 3). The Andaman Islanders clearly and consistently display the narrowest median breadth for all samples. Comparative populations display considerable overlap with East Asia. Highly significant differences were identified in all three plots (pooled sex, male-only and female-only) with Kruskal- Wallis tests (H: 145.2, p < 0.001; H: 101.6, p < 0.001, H: 65.64, p < 0.001, respectively; see Appendix 2).

Population Key 120.00 NA - Native America Sib - Siberia Mon - Mongolia Ain - Ainu 110.00 * ) Kor - Korea

m Jap - Japan m

( S.Chi - South China

e *

l N.Chi - North China

a Bur - Burma d

i 100.00

o Lao - Laos t

s Viet - Vietnam

a Thai - Thailand m i Cam - Cambodia b Phi - Philippines 90.00 And - Andaman Is. Nic - Nicobar Is. Bor - Borneo Indo - Indonesia Mel - Melanesia

Mi C N V S K Mo A N A Me A A P B T B S I L C J N

n

a a

h

a A i i o n i i u f h o u . a .

d

e b c n C Mic - Micronesia C

p c

a o

r d s i r r

u m

n l o

t

i h h c Aus - Australia

i i Af - Africa Cauc - Caucasian Population

Figure 4.28. Box and whisker plot of posterior cranial breadth (bimastoidale) for pooled sex data. Populations are in order of increasing median. * denotes sample size n < 5.

95 Population Key 120.00 NA - Native America Sib - Siberia * Mon - Mongolia Ain - Ainu Kor - Korea ) 110.00

m * Jap - Japan

m * S.Chi - South China

(

e N.Chi - North China l

a * Bur - Burma d

i Lao - Laos

to Viet - Vietnam s 100.00

a Thai - Thailand m

i Cam - Cambodia

b Phi - Philippines And - Andaman Is. Nic - Nicobar Is. 90.00 Bor - Borneo Indo - Indonesia Mel - Melanesia

V T N Mi K S Mo A N Me A A A P I S N J L C B B C

n

a a Mic - Micronesia h

i . o i n i i u f h . A a u o a

d

b c n C e

C

p c

o a

r d s i r r

m u

n l o

t

h i h Aus - Australia

c

i i Af - Africa Cauc - Caucasian Population

Figure 4.29. Box and whisker plot of posterior cranial breadth (bimastoidale) for male-only data. Populations are in order of increasing median. * denotes sample size n < 5.

Population Key

NA - Native America Sib - Siberia Mon - Mongolia 110.00 * * Ain - Ainu

Kor - Korea

) m Jap - Japan

m * S.Chi - South China ( N.Chi - North China

e * l

a 100.00 Bur - Burma d

i Lao - Laos

to * Viet - Vietnam s *

a Thai - Thailand m

i Cam - Cambodia

b Phi - Philippines 90.00 And - Andaman Is. Nic - Nicobar Is. Bor - Borneo Indo - Indonesia Mel - Melanesia

S L V S N Mo K A N A N A B B P I J A Mi Me C T C

n Mic - Micronesia a a

h

. i i A o n i i . u u o h f a a

d

e b c n C

C

p c

a o

r d s r r i

u m

o l n t Aus - Australia

h i h

c

i i Af - Africa Cauc - Caucasian Population

Figure 4.30. Box and whisker plot of posterior cranial breadth (bimastoidale) for female-only data. Populations are in order of increasing median. * denotes sample size n < 5.

96 4.2.2 Length variables 4.2.2.1 Facial Lengths Variables describing facial length discussed below are basion-prosthion (BPL) and malar (cheek) length (IML). Facial length variable BPL displays similar groupings and separations for pooled sex (fig 4.31), male-only (fig 4.32) and female-only (fig 4.33) plots. Similar separations are observed for malar length in all three plots (fig 4.34-4.36). Both facial length variables separate East Asia from the comparative samples, particularly Africa, Australia, Melanesia and the Caucasians. Significant differences were detected for both variables (BPL, IML) and all three samples; pooled sex (H: 142.5, p < 0.001; H: 92.83, p < 0.001), male-only (H: 89.71, p < 0.001; H: 80.71, p < 0.001) and female-only (H: 76.17, p < 0.001; H: 42.61, p < 0.001). Refer to Appendix 2 for further details. East Asian populations display moderate to short facial lengths in all three plots for variable BPL, flanked at both ends by comparative populations (figs 4.31-4.33). The Caucasian sample consistently exhibits the shortest median length. At the opposite end of the scale, a grouping consisting of Australia, Africa and Melanesia displays the longest median lengths, seen in all three plots (pooled sex male-only and female-only), but less distinct in the female-only plot (fig 4.33). This is due to the sample relationships observed between aforementioned comparative samples and East Asian samples Nicobar Islands and the Ainu. These two samples are however, small (n < 5) and thus these results should be viewed cautiously. Malar (cheek) length (IML) has been defined in the study as the distance between zygomaxillare and the inferior suture of the posterior edge of the zygomatic bone. Figures 4.34-4.36 display the results of the univariate analysis of this measurement for pooled sex, male-only and female-only respectively, and show separation of Asian and non-Asian populations across all three plots. Australia, Africa and Melanesia are moderately distinct from the remaining samples for all plots. This grouping includes Micronesia in the male-only and female-only plots. Members of this comparative grouping display the longest median cheek lengths, with Australia consistently the longest. Remaining samples exhibiting moderate to short medians. There is considerable overlap between the East Asian samples in all three plots.

97 Population Key

NA - Native America 110.00 Sib - Siberia Mon - Mongolia Ain - Ainu * Kor - Korea Jap - Japan

) S.Chi - South China 100.00

m N.Chi - North China

m Bur - Burma ( Lao - Laos L * Viet - Vietnam

BP Thai - Thailand 90.00 Cam - Cambodia Phi - Philippines And - Andaman Is. Nic - Nicobar Is. Bor - Borneo 80.00 Indo - Indonesia Mel - Melanesia

A A A Me C A K B S C B V Mo N P L J T N Mi N I S

n

a a Mic - Micronesia h

i f u a n o u . a o i . h A i i

d

C e c b n

C

p c

o a

s d r r r i

u m

n o l

t

h h i Aus - Australia

c

i i Af - Africa Cauc - Caucasian Population Figure 4.31. Box and whisker plot of facial length (BPL) for pooled sex data. Populations are in order of increasing median. * denotes sample size n < 5.

Population Key

NA - Native America Sib - Siberia 110.00 Mon - Mongolia Ain - Ainu ** Kor - Korea Jap - Japan S.Chi - South China

) *

100.00 N.Chi - North China m

Bur - Burma m ( Lao - Laos L Viet - Vietnam

BP * Thai - Thailand 90.00 Cam - Cambodia Phi - Philippines And - Andaman Is. Nic - Nicobar Is. Bor - Borneo Indo - Indonesia 80.00 Mel - Melanesia

I T J N S A C A Mi A Me C K A S B B V N N Mo L P

n Mic - Micronesia

a a

h

A i i a f u a o n . o u i . i h

d

b n C e c

C

p c

o a

s r d r r i

m u

n o l

t Aus - Australia

h h i

c

i i Af - Africa Cauc - Caucasian Population Figure 4.32. Box and whisker plot of facial length (BPL) for male-only data. Populations are in order of increasing median. * denotes sample size n < 5.

98 Population Key

110.00 NA - Native America Sib - Siberia Mon - Mongolia Ain - Ainu Kor - Korea * Jap - Japan

) 100.00 * * S.Chi - South China

m N.Chi - North China

m Bur - Burma ( * Lao - Laos L * Viet - Vietnam

BP * Thai - Thailand 90.00 Cam - Cambodia Phi - Philippines And - Andaman Is. Nic - Nicobar Is. Bor - Borneo Indo - Indonesia 80.00 Mel - Melanesia

P S N Mi L I Me A A N A C B S T A C V N K J B Mo

n

a a Mic - Micronesia h

h i A i u i f a u . n a i . o o

d

n c C e b

C

p c

o a

i s r d r r

u m

n o l

t

h i h Aus - Australia

c

i i Af - Africa Cauc - Caucasian Population

Figure 4.33. Box and whisker plot of facial length (BPL) for female-only data. Populations are in order of increasing median. * denotes sample size n < 5.

Population Key

NA - Native America 45.00 Sib - Siberia Mon - Mongolia Ain - Ainu 40.00 Kor - Korea Jap - Japan

S.Chi - South China

) m N.Chi - North China 35.00 Bur - Burma (m Lao - Laos

L * * Viet - Vietnam M I 30.00 Thai - Thailand Cam - Cambodia Phi - Philippines And - Andaman Is. 25.00 Nic - Nicobar Is. Bor - Borneo Indo - Indonesia Mel - Melanesia

K B P T A N C J I N B N Mo A L V C Mi S S Me A A

n Mic - Micronesia

a a

h

o u h i i a . o A n i a i . f u

d

n c e b C

C

p o c

a

r r i r d s

u m

o n l

t Aus - Australia

i h h

c

i i Af - Africa Cauc - Caucasian Population Figure 4.34. Box and whisker plot of malar length (IML) for pooled sex data. Populations are in order of increasing median. * denotes sample size n < 5.

99 Population Key

45.00 NA - Native America Sib - Siberia * Mon - Mongolia Ain - Ainu 40.00 Kor - Korea Jap - Japan * ) S.Chi - South China

m N.Chi - North China Bur - Burma

(m 35.00 Lao - Laos L * Viet - Vietnam

M *

I Thai - Thailand 30.00 Cam - Cambodia Phi - Philippines And - Andaman Is. Nic - Nicobar Is. 25.00 Bor - Borneo Indo - Indonesia Mel - Melanesia

K J B N P A B C N A I N L T Mo V S C A S Mi Me A

n

a a Mic - Micronesia

h

o u i h i o a . n A i i a f . u

d

c n e b C

C

p o c

a

r r i r d s

u m

o n l t Aus - Australia h i h

c

i i Af - Africa Cauc - Caucasian Population

Figure 4.35. Box and whisker plot of malar length (IML) for male-only data. Populations are in order of increasing median. * denotes sample size n < 5.

Population Key

40.00 NA - Native America Sib - Siberia Mon - Mongolia * Ain - Ainu 35.00 * Kor - Korea * Jap - Japan S.Chi - South China ) *

m * N.Chi - North China 30.00 * Bur - Burma (m Lao - Laos

L Viet - Vietnam M I 25.00 Thai - Thailand Cam - Cambodia Phi - Philippines And - Andaman Is. 20.00 Nic - Nicobar Is. Bor - Borneo Indo - Indonesia Mel - Melanesia

N K A I B P Mo N T C J L V N B C S A Mi Me S A A

n Mic - Micronesia

a a

h

i o i u h . a i A o a i n . f u

d

c n e b C

C

p o c

a

r r i r d s

u m

o n l

t Aus - Australia

h i h

c

i i Af - Africa Cauc - Caucasian Population Figure 4.36. Box and whisker plot of malar length (IML) for female-only data. Populations are in order of increasing median. * denotes sample size n < 5.

100 4.2.2.2 Cranial Lengths Measurements of cranial length exhibiting reasonably clear separation of samples are nasion-lambda (n-l) and glabella-lambda (g-l). The fact that both variables are included here is not unexpected, as landmarks nasion and glabella are located in a similar region on the cranium, and thus, both variables are quite similar. Length of the parietal bone (PAC) is also included in this section. Cranial length variables (n-l, g-l) distinguish East Asians from non-Asian populations for all three plots, with the distinction appearing stronger for the variable g-l. Parietal length displays a similar pattern of separation, but in the male and female plots only. The results are described in more detail below. Cranial length separates most comparative samples from East Asians, albeit incompletely, in the pooled sex plot (figs 4.37-4.38), with the non-Asian populations displaying longer median lengths. The Ainu sample is grouped amongst the long headed comparative samples for both variables, although its small sample number (n = 3) makes the accuracy of this result questionable. Two non-Asian populations not amongst this group, Micronesia and the Native Americans, are placed with the Northeast Asians, displaying (high) moderate median lengths (both variables). There is a suggestion from both n-l and g-l of a north to south cline among the East Asians, with Siberia and North China positioned at the long end of the moderate scale, and Southeast Asian populations displaying moderate to short lengths. However, the distinction between northern and southern East Asian samples is incomplete due to some overlap between Northeast and Southeast Asians for both variables. Kruskal-Wallis tests (Appendix 2) detected highly significant separations for both n-l (H: 160.6, p < 0.001) and g-l (H: 173.8, p < 0.001). The pattern of separation of East Asian and non-Asian samples is consistent also for both cranial length variables (n-l, g-l) in the male-only (figs 4.39-4.40) and female- only (figs 4.41-4.42) plots, although as above, the separation is not complete. A north to south cline of decreasing cranial length is also apparent in the male-only plot, but no such pattern is discernible in the female-only plot. Significant differences were apparent for both male-only (H: 106.3, p < 0.001; H: 114.0, p < 0.001; n-l and g-l, respectively) and female-only plots (H: 75.28, p < 0.001; H: 78.26, p < 0.001, respectively) using a Kruskal-Wallis test (Appendix 2).

101 Population Key 190.00 * NA - Native America Sib - Siberia Mon - Mongolia Ain - Ainu 180.00 Kor - Korea Jap - Japan * S.Chi - South China

) N.Chi - North China m 170.00

Bur - Burma m

( Lao - Laos

-l Viet - Vietnam n Thai - Thailand 160.00 Cam - Cambodia Phi - Philippines And - Andaman Is. Nic - Nicobar Is. 150.00 Bor - Borneo Indo - Indonesia Mel - Melanesia

C A S T L I B P Mo V J K B Mi N S N N Me A C A A

n Mic - Micronesia

a a

h

a n . u h i o o A i . i u a i f

d

C e b c n

C

p c

a o

d r i r r s

m u

o n l t Aus - Australia

h i h

c

i i Af - Africa Cauc - Caucasian Population Figure 4.37. Box and whisker plot of cranial length (n-l) for pooled sex data. Populations are in order of increasing median. * denotes sample size n < 5.

Population Key * NA - Native America 190.00 Sib - Siberia Mon - Mongolia Ain - Ainu Kor - Korea 180.00 Jap - Japan S.Chi - South China

) * N.Chi - North China

m Bur - Burma m

( 170.00 Lao - Laos

-l Viet - Vietnam g Thai - Thailand Cam - Cambodia 160.00 Phi - Philippines And - Andaman Is. Nic - Nicobar Is. Bor - Borneo 150.00 Indo - Indonesia Mel - Melanesia

A A S C T L B P Mo I J V N S Mi N B K C N Me A A

n Mic - Micronesia

a a

h

i n . a u h i A i . o o a i u f

d

C e b c n

C

p c

a o

d r i r r s

m u

n o l t Aus - Australia

h i h

c

i i Af - Africa Cauc - Caucasian Population Figure 4.38. Box and whisker plot of cranial length (g-l) for pooled sex data. Populations are in order of increasing median. * denotes sample size n < 5.

102 Population Key 190.00 * NA - Native America Sib - Siberia * Mon - Mongolia Ain - Ainu 180.00 * Kor - Korea Jap - Japan * S.Chi - South China

) N.Chi - North China m 170.00 Bur - Burma

(m Lao - Laos

-l Viet - Vietnam n Thai - Thailand 160.00 Cam - Cambodia Phi - Philippines And - Andaman Is. Nic - Nicobar Is. 150.00 Bor - Borneo Indo - Indonesia Mel - Melanesia

K N Me S Mi A C A T C A L I A P B V Mo S B J N N

n Mic - Micronesia

a a

h

i u a f a n i h u i . o i A o .

d

b n e C c

C

p c

a o

s d i r r r

u m

l o n t Aus - Australia

h i h

c

i i Af - Africa Cauc - Caucasian Population Figure 4.39. Box and whisker plot of cranial length (n-l) for male-only data. Populations are in order of increasing median. * denotes sample size n < 5.

Population Key * NA - Native America 190.00 Sib - Siberia Mon - Mongolia Ain - Ainu Kor - Korea 180.00 * Jap - Japan S.Chi - South China ) * N.Chi - North China m * Bur - Burma

(m Lao - Laos 170.00 -l Viet - Vietnam g Thai - Thailand Cam - Cambodia Phi - Philippines 160.00 And - Andaman Is. Nic - Nicobar Is. Bor - Borneo Indo - Indonesia 150.00 Mel - Melanesia

N N Mi Me C A A A S A T C L P I B Mo V B J N K S

n Mic - Micronesia a a

h

A i a f u i . n a h u i o . o i

d

c n C e b

C

p c

a o

s d i r r r

m u

o n l t Aus - Australia

h i h

c

i i Af - Africa Cauc - Caucasian Population

Figure 4.40. Box and whisker plot of cranial length (g-l) for male-only data. Populations are in order of increasing median. * denotes sample size n < 5.

103 Population Key

NA - Native America Sib - Siberia 180.00 Mon - Mongolia Ain - Ainu * * Kor - Korea Jap - Japan * S.Chi - South China ) 170.00 N.Chi - North China m * * Bur - Burma (m Lao - Laos

-l * Viet - Vietnam n Thai - Thailand 160.00 Cam - Cambodia Phi - Philippines And - Andaman Is. Nic - Nicobar Is. Bor - Borneo 150.00 Indo - Indonesia Mel - Melanesia

B V A Mi Me N C N A A T A C L S K N P B I Mo J S

n Mic - Micronesia

a a

h

i u A a i i f n a . o . h u i o

d

C b e c n

C

p c

a o

s d r i r r

u m

o n l t Aus - Australia

i h h

c

i i Af - Africa Cauc - Caucasian Population Figure 4.41. Box and whisker plot of cranial length (n-l) for female-only data. Populations are in order of increasing median. * denotes sample size n < 5.

Population Key

NA - Native America 180.00 Sib - Siberia Mon - Mongolia * Ain - Ainu * Kor - Korea Jap - Japan * S.Chi - South China ) 170.00 N.Chi - North China m * Bur - Burma

(m Lao - Laos

-l * Viet - Vietnam g Thai - Thailand 160.00 Cam - Cambodia Phi - Philippines * And - Andaman Is. Nic - Nicobar Is. Bor - Borneo 150.00 Indo - Indonesia Mel - Melanesia

B V N Mi C Me A N A A K T A C L N P I B S S Mo J

n Mic - Micronesia a a

h

o i A a u i f i o n a . h u . i

d

C b e c n

C

p c

a o

r s r d i r

m u

o n l t Aus - Australia

i h h

c

i i Af - Africa Cauc - Caucasian Population

Figure 4.42. Box and whisker plot of cranial length (g-l) for female-only data. Populations are in order of increasing median. * denotes sample size n < 5.

104 Parietal length variable, PAC, implies a separation of East Asia from non-Asian populations for the male-only plot (fig 4.43), with this separation appearing stronger in the female-only plot (fig 4.44). Both plots exhibited significant differences using a Kruskal-Wallis test (H: 77.04, p < 0.001; H: 58.39, p < 0.001, respectively; see Appendix 2). Figures 4.43 and 4.44 show East Asians possessing moderate to short median lengths, with considerable overlap between northern and southern populations. Comparative groups, particularly Australians, African, Melanesian and Caucasian samples tend to exhibit longer median parietal lengths. This separation from East Asia is, however, incomplete, due to some overlap with East Asian samples for both plots (male-only and female-only). In most cases, the overlapping East Asian samples are those exhibiting small sample numbers, particularly in the female-only plot, and therefore their position in the plot should be regarded with caution.

Population Key

130.00 NA - Native America * Sib - Siberia * Mon - Mongolia 120.00 Ain - Ainu Kor - Korea **Jap - Japan

) S.Chi - South China 110.00

m N.Chi - North China

m Bur - Burma Lao - Laos

Viet - Vietnam AC ( 100.00

P Thai - Thailand Cam - Cambodia 90.00 Phi - Philippines And - Andaman Is. Nic - Nicobar Is. Bor - Borneo 80.00 Indo - Indonesia Mel - Melanesia

C J N B Me K A S A A T P L N A N C S Mo Mi I B V

n Mic - Micronesia a a

h

i o o f . u i h A n . a i u i a

d

n b e c C

C

c p

a o

r r s i d r

m u

n o l t Aus - Australia

h i h

c

i i Af - Africa Cauc - Caucasian Population

Figure 4.43. Box and whisker plot of parietal length (PAC) for male-only data. Populations are in order of increasing median. * denotes sample size n < 5.

105 Population Key

NA - Native America Sib - Siberia 120.00 Mon - Mongolia Ain - Ainu * Kor - Korea Jap - Japan

* S.Chi - South China )

m N.Chi - North China 110.00 * m ** Bur - Burma * Lao - Laos

Viet - Vietnam AC (

P Thai - Thailand 100.00 Cam - Cambodia Phi - Philippines And - Andaman Is. Nic - Nicobar Is. Bor - Borneo 90.00 Indo - Indonesia Mel - Melanesia

J N A A C B Me A Mi N T C K A S N I S L B Mo P V

n Mic - Micronesia

a a

h

A u f a o i i a o n i . . u h i

d

n c b C e

C

p c

a o

s r r d r i

u m

o n l t Aus - Australia

i h h

c

i i Af - Africa Cauc - Caucasian Population Figure 4.44. Box and whisker plot of parietal length (PAC) for female-only data. Populations are in order of increasing median. * denotes sample size n < 5.

4.2.2.3 Lengths of the Inferior Cranial Surface Measurements located on the cranial base that discriminated samples are palate length (sta-ol) and foramen magnum length (FOL). The former variable exhibits similar separations for pooled sex (fig 4.45), male-only (fig 4.46) and female-only (fig 4.47) plots, while the latter displays observable groupings for pooled sex and male-only plots only (figs 4.48-4.49). Palate length strongly separates East Asia from comparative populations Australia, Africa and Melanesia in the pooled sex and male-only plots, with the female- only plot showing separation from Australia and Africa only. All three plots exhibit highly significant differences between samples when subjected to a Kruskal-Wallis test (H: 109.4, p < 0.001; H: 75.21, p < 0.001; H: 56.38, p < 0.001, respectively; see Appendix 2). Micronesia joins the comparative sample cluster in the male-only plot (fig. 4.46). The aforementioned comparative samples exhibit the longest median palate lengths, while all remaining samples display moderate to short medians. There is considerable overlap between all East Asian populations in all three plots.

106 Population Key

NA - Native America 55.00 Sib - Siberia Mon - Mongolia Ain - Ainu Kor - Korea 50.00 Jap - Japan

) * S.Chi - South China

m N.Chi - North China

m Bur - Burma

( 45.00

l Lao - Laos

-o * Viet - Vietnam

a

t s Thai - Thailand 40.00 Cam - Cambodia Phi - Philippines And - Andaman Is. 35.00 Nic - Nicobar Is. Bor - Borneo Indo - Indonesia Mel - Melanesia

K C S Mo N A P C V T Mi B N B J L A N S I Me A A

n Mic - Micronesia

a a

h

o a . . n h a i o i u i A i f u

d

C e c n b

C

c p o

a

r d i r r s

m u

n o l

t Aus - Australia

h h i

c

i i Af - Africa Cauc - Caucasian Population Figure 4.45. Box and whisker plot of palate length (sta-ol) for pooled sex data. Populations are in order of increasing median. * denotes sample size n < 5.

Population Key

NA - Native America 55.00 Sib - Siberia Mon - Mongolia Ain - Ainu * * Kor - Korea 50.00 Jap - Japan

) S.Chi - South China

m N.Chi - North China

m *

( 45.00 Bur - Burma l Lao - Laos -o Viet - Vietnam

a * t

s Thai - Thailand 40.00 Cam - Cambodia Phi - Philippines And - Andaman Is. 35.00 Nic - Nicobar Is. Bor - Borneo Indo - Indonesia Mel - Melanesia

K A N N P A L B V Mo J B S I C T C S N A Me Mi A

n

a a Mic - Micronesia

h

o n i . h i o i u . a a i A f u

d

c n e C b

C

o p c

a

r d i r r s

u m

n o l t Aus - Australia h h i

c

i i Af - Africa Cauc - Caucasian Population

Figure 4.46. Box and whisker plot of palate length (sta-ol) for male-only data. Populations are in order of increasing median. * denotes sample size n < 5.

107 Population Key

NA - Native America 55.00 Sib - Siberia Mon - Mongolia Ain - Ainu * Kor - Korea 50.00 Jap - Japan

) S.Chi - South China

m * * N.Chi - North China

m Bur - Burma (

l Lao - Laos

-o 45.00 * Viet - Vietnam a

t * s Thai - Thailand * Cam - Cambodia Phi - Philippines 40.00 And - Andaman Is. Nic - Nicobar Is. Bor - Borneo Indo - Indonesia Mel - Melanesia

Me I A A N A C S J K T Mo N V P B C Mi A B N L S

n Mic - Micronesia

a a

h

i f i u a . o . i h u a n o A i

d

n c C e b

C

p c

a o

s r i r d r

m u

n l o t Aus - Australia

h i h

c

i i Af - Africa Cauc - Caucasian Population Figure 4.47. Box and whisker plot of palate length (sta-ol) for female-only data. Populations are in order of increasing median. * denotes sample size n < 5.

Foramen magnum length (FOL) shows a north to south pattern of decreasing median length for both pooled sex (4.48) and male-only (4.49) plots, although it is somewhat incomplete. The cline is not observed in the female-only plot (not shown). Siberia is clearly the population with the longest FOL for both plots, with the next East Asian samples being Mongolia and North China, which are positioned at the upper end of the moderate range. The Andaman Islands sample is consistently and clearly has the shortest foramen magnum. Comparative populations tend to be distributed between the northern and southern East Asian samples, exhibiting moderate lengths. Kruskal-Wallis tests identify significant differences between samples for both pooled sex (H: 74.44, p < 0.001) and male-only (H: 58.33, p < 0.001) plots.

4.2.3 Height Variables 4.2.3.1 Facial Heights Facial height variables to be discussed below are alveolar height (pr-ns) and upper facial height measurements nasion-prosthion (NPH) and prosthion-glabella (pr-g) height. Nasal height (n-ns) is also included here. All facial height variables indicate a

108 Population Key

NA - Native America 45.00 Sib - Siberia Mon - Mongolia Ain - Ainu Kor - Korea Jap - Japan 40.00 S.Chi - South China ) *

m * N.Chi - North China

m Bur - Burma ( Lao - Laos

L Viet - Vietnam O

F 35.00 Thai - Thailand Cam - Cambodia Phi - Philippines And - Andaman Is. Nic - Nicobar Is. 30.00 Bor - Borneo Indo - Indonesia Mel - Melanesia

A K N I J L P B N T A Me S Mi C V B C A Mo N A S

n Mic - Micronesia

a a

h

n o i h u A u . a i o a i . f i

d

c C e n b

C

p o c

a

d r i r s r

m u

o l n

t Aus - Australia

i h h

c

i i Af - Africa Cauc - Caucasian Population Figure 4.48. Box and whisker plot of foramen magnum length (FOL) for pooled sex data. Populations are in order of increasing median. * denotes sample size n < 5.

Population Key * NA - Native America 45.00 Sib - Siberia * Mon - Mongolia Ain - Ainu Kor - Korea Jap - Japan S.Chi - South China ) 40.00 * m * N.Chi - North China

Bur - Burma (m Lao - Laos

OL Viet - Vietnam F 35.00 Thai - Thailand Cam - Cambodia Phi - Philippines And - Andaman Is. Nic - Nicobar Is. Bor - Borneo 30.00 Indo - Indonesia Mel - Melanesia

A I N Me T J P B L K S A V A B C N C A Mo N Mi S

n

a a Mic - Micronesia

h

n i h u o . u i f o a A a i . i

d

c C e n b

C

p o c

a

d i r r s r

u m

o l n t Aus - Australia i h h

c

i i Af - Africa Cauc - Caucasian Population

Figure 4.49. Box and whisker plot of foramen magnum length (FOL) for male-only data. Populations are in order of increasing median. * denotes sample size n < 5.

109 separation of northern and southern East Asian populations, although at times imperfect. A separation of Northeast Asia and the most northern East Asia sensu stricto samples (Korea, Ainu, Japan and North China) from Southeast Asia is observed for alveolar height (pr-ns) in figures 4.50-4.52. The northern samples tend to exhibit the longest medians, although overlap between northern and southern East Asian samples is apparent in the pooled sex plot (fig 4.50). The Andaman and Cambodian samples are among, if not the smallest Southeast Asian populations for all three plots. Overlap between Asian and non-Asian samples are visible, with Caucasian and Native American samples clustering with Siberia, and remaining samples situated within the Southeast Asian range. Highly significant differences are apparent in pooled sex (H: 119.8, p < 0.001), male-only (H: 64.74, p < 0.001) and female-only plots (H: 65.49, p < 0.001) using Kruskal-Wallis tests (Appendix 2).

Population Key

30.00 NA - Native America Sib - Siberia Mon - Mongolia Ain - Ainu 25.00 Kor - Korea Jap - Japan * S.Chi - South China ) * N.Chi - North China m 20.00

m Bur - Burma

( Lao - Laos s

Viet - Vietnam -n

r Thai - Thailand p 15.00 Cam - Cambodia Phi - Philippines And - Andaman Is. Nic - Nicobar Is. 10.00 Bor - Borneo Indo - Indonesia Mel - Melanesia

A C Me Mi T N P J B B S V I A A K Mo L N C S A N Mic - Micronesia

n

a a

h

n a i h o u . i f u o . a i i A

d

c C e b n

C

c p o

a

d i r r s r Aus - Australia m u

l o n

t

i h h

c

i i Af - Africa Cauc - Caucasian Population Figure 4.50. Box and whisker plot of facial height (pr-ns) for pooled sex data. Populations are in order of increasing median. * denotes sample size n < 5.

110 Population Key

30.00 NA - Native America Sib - Siberia Mon - Mongolia Ain - Ainu 25.00 Kor - Korea * Jap - Japan

) * S.Chi - South China

m * N.Chi - North China 20.00

m * Bur - Burma (

s Lao - Laos

-n Viet - Vietnam r

p Thai - Thailand 15.00 Cam - Cambodia Phi - Philippines And - Andaman Is. 10.00 Nic - Nicobar Is. Bor - Borneo Indo - Indonesia Mel - Melanesia

C S N A Mi C T Me P N J L B I B A S V A A N K Mo

n Mic - Micronesia

a a

h

a i A n a h i o u f . i u i . o

d

c C e n b

C

c p

a o

d i r r s r

m u

l o n t Aus - Australia

i h h

c

i i Af - Africa Cauc - Caucasian Population Figure 4.51. Box and whisker plot of facial height (pr-ns) for male-only data. Populations are in order of increasing median. * denotes sample size n < 5.

Population Key

NA - Native America 25.00 Sib - Siberia * Mon - Mongolia * Ain - Ainu Kor - Korea Jap - Japan 20.00 *

) * * S.Chi - South China m N.Chi - North China

m * ( Bur - Burma

s Lao - Laos -n

r 15.00 Viet - Vietnam

p Thai - Thailand Cam - Cambodia Phi - Philippines And - Andaman Is. 10.00 Nic - Nicobar Is. Bor - Borneo Indo - Indonesia Mel - Melanesia

S N A C Me S A B Mi K T V N J B P A A Mo I L N C

n

a a

h

i A i a . n u o i i o h u f . a

d Mic - Micronesia

C e c b n

C

c p

a o

d r r r i s

m u

l n o

t

h i h c Aus - Australia

i i Af - Africa Cauc - Caucasian Population Figure 4.52. Box and whisker plot of facial height (pr-ns) for female-only data. Populations are in order of increasing median. * denotes sample size n < 5.

111 Upper facial height variable NPH appears to distinguish Northeast Asia and North China from the southern populations in all three plots; pooled sex, male-only and female only (figs 4.53-4.55 respectively). Northern populations display the longer median upper facial heights, while the southern samples exhibit moderate to short median heights. The Andaman Islanders clearly and consistently have the shortest facial height. The Native Americans are consistently positioned close, if not among, the Northeast Asians. The remaining comparative samples are within the range of Southeast Asia. Kruskal-Wallis tests (Appendix 2) detected highly significant differences in all three plots (H: 131.9, p < 0.001; H: 95.1, p < 0.001; H: 58.71, p < 0.001, respectively).

Population Key

NA - Native America 80.00 Sib - Siberia * Mon - Mongolia Ain - Ainu * Kor - Korea Jap - Japan ) 70.00 S.Chi - South China m N.Chi - North China

(m Bur - Burma

H Lao - Laos

P Viet - Vietnam N Thai - Thailand 60.00 Cam - Cambodia Phi - Philippines And - Andaman Is. Nic - Nicobar Is. Bor - Borneo 50.00 Indo - Indonesia Mel - Melanesia

A P N Mi C B A A B Me A C J T I V S L N Mo K N S

n

a a

h

n h i a o f u u i a i . A o . i

d Mic - Micronesia c n e C b

C

c p o

a

d i r s r r

m u

l o n

t

i h h c Aus - Australia

i i Af - Africa Cauc - Caucasian Population

Figure 4.53. Box and whisker plot of facial height (NPH) for pooled sex data. Populations are in order of increasing median. * denotes sample size n < 5.

112 Population Key

NA - Native America 80.00 Sib - Siberia Mon - Mongolia * Ain - Ainu Kor - Korea Jap - Japan S.Chi - South China ) * *

m 70.00 N.Chi - North China Bur - Burma (m * Lao - Laos

H Viet - Vietnam P

N Thai - Thailand Cam - Cambodia 60.00 Phi - Philippines And - Andaman Is. Nic - Nicobar Is. Bor - Borneo Indo - Indonesia Mel - Melanesia 50.00

A N P A A B Me Mi C C A T I J L S V B N Mo N K S

n Mic - Micronesia

a a

h

n i h f i o a a u . i u A . o i

d

c n C e b

C

c p o

a

d i r s r r

m u

l o n

t Aus - Australia

i h h

c

i i Af - Africa Cauc - Caucasian Population Figure 4.54. Box and whisker plot of facial height (NPH) for male-only data. Populations are in order of increasing median. * denotes sample size n < 5.

Population Key

* NA - Native America * Sib - Siberia * Mon - Mongolia Ain - Ainu Kor - Korea 70.00 * Jap - Japan

* S.Chi - South China )

N.Chi - North China m Bur - Burma

(m * Lao - Laos

H Viet - Vietnam P

N Thai - Thailand 60.00 Cam - Cambodia Phi - Philippines And - Andaman Is. Nic - Nicobar Is. Bor - Borneo Indo - Indonesia 50.00 Mel - Melanesia

A P T Me B A N C Mi S A B N I J C V K S N L Mo A Mic - Micronesia n

a a

h

n h o u i a . f u . a i o i A i

d

c C e b n

C

c p o

a

d i r s r r

m u

l o n Aus - Australia

t

i h h

c

i i Af - Africa Cauc - Caucasian Population Figure 4.55. Box and whisker plot of facial height (NPH) for female-only data. Populations are in order of increasing median. * denotes sample size n < 5.

113 A second measure of upper facial height, prosthion-glabella (pr-g), clearly displays Northeast Asia and North China as a distinct cluster separate from all remaining East Asian populations. These groupings are evident in the pooled sex and male-only plots (figs 4.56-4.57 respectively), with an imperfect grouping observed in the female-only plot (fig 4.58) due to overlap between northern and southern samples. All three plots (pooled sex, male-only and female-only) exhibit significant differences when subjected to Kruskal-Wallis tests (H: 143.00, p < 0.001; H: 101.8, p < 0.001; H: 58.98, p < 0.001, respectively; see Appendix 2). The Native Americans exhibit a high moderate median height for all three groups (pooled sex, male-only and female-only) positioning close to the Northeast Asians. Most East Asian samples exhibit moderate facial height medians, however, Mongolia is consistently the population with the longest median height, while the Andaman sample consistently displays the shortest face. There is no separation of Asian and non-Asian populations for this variable.

Population Key

NA - Native America 90.00 * Sib - Siberia Mon - Mongolia Ain - Ainu * Kor - Korea Jap - Japan S.Chi - South China

) 80.00 N.Chi - North China

m Bur - Burma m ( Lao - Laos

-g Viet - Vietnam r

p Thai - Thailand 70.00 Cam - Cambodia Phi - Philippines And - Andaman Is. Nic - Nicobar Is. Bor - Borneo 60.00 Indo - Indonesia Mel - Melanesia

S N Mo A N A Mi B P K A Me C I S J T C A B V N L

n Mic - Micronesia

a a

h

i . n i u o h o f a . a i u i A

d

c C n e b

C

c p o

a

d s r i r r

u m

l o n

t Aus - Australia

h i h

c

i i Af - Africa Cauc - Caucasian Population

Figure 4.56. Box and whisker plot of facial height (pr-g) for pooled sex data. Populations are in order of increasing median. * denotes sample size n < 5.

114 Population Key

NA - Native America Sib - Siberia 90.00 * Mon - Mongolia Ain - Ainu Kor - Korea Jap - Japan * S.Chi - South China ) N.Chi - North China

m 80.00 *

Bur - Burma m ( * Lao - Laos

-g Viet - Vietnam r

p Thai - Thailand Cam - Cambodia 70.00 Phi - Philippines And - Andaman Is. Nic - Nicobar Is. Bor - Borneo Indo - Indonesia Mel - Melanesia

V N S K S N Mo A N A P Me A B C I A Mi J L T C B

n Mic - Micronesia

a a

h

i A . o i . n i u h f o a i a u

d

C b c n e

C

c p o

a

r d s i r r

u m

n l o t Aus - Australia

i h h

c

i i Af - Africa Cauc - Caucasian Population Figure 4.57. Box and whisker plot of facial height (pr-g) for male-only data. Populations are in order of increasing median. * denotes sample size n < 5.

Population Key 90.00 * NA - Native America Sib - Siberia Mon - Mongolia * Ain - Ainu Kor - Korea 80.00 Jap - Japan S.Chi - South China ) N.Chi - North China

m *

* Bur - Burma m ( * Lao - Laos

-g Viet - Vietnam r

p 70.00 Thai - Thailand Cam - Cambodia * Phi - Philippines And - Andaman Is. Nic - Nicobar Is. Bor - Borneo 60.00 Indo - Indonesia Mel - Melanesia

A V B J S N Mo L A K A P Me Mi B A T S I N C N C

n Mic - Micronesia

a a

h

f i u i A i o n h o u . i a . a

d

C c e b n

C

o c p

a

r r d i r s

m u

n l o Aus - Australia t

i h h

c

i i Af - Africa Cauc - Caucasian Population Figure 4.58. Box and whisker plot of facial height (pr-g) for female-only data. Populations are in order of increasing median. * denotes sample size n < 5.

115 Figures 4.59 and 4.60 display separations based on nasal height (n-ns) for pooled sex and male-only samples (respectively). As discussed above, this height variable implies an East Asian north to south separation, with Northeast Asia exhibiting among the largest median nasal height (pooled sex: moderate to long; male-only: long). Separation between samples is not clear in the female-only plot (not shown). The remaining East Asian samples possess a moderate median nasal height, with the exception of Southeast Asian population. Andaman Islands, which is distinctly short in height for both plots. Both pooled sex and male-only plots exhibit highly significant differences between samples (H: 98.32, p < 0.001; H: 74.21, p < 0.001) when subjected to Kruskal-Wallis tests (Appendix 2).

Population Key 60.00 NA - Native America Sib - Siberia Mon - Mongolia * Ain - Ainu 55.00 Kor - Korea * Jap - Japan

) S.Chi - South China

m N.Chi - North China 50.00

m Bur - Burma (

s Lao - Laos

-n Viet - Vietnam n Thai - Thailand 45.00 Cam - Cambodia Phi - Philippines And - Andaman Is. Nic - Nicobar Is. 40.00 Bor - Borneo Indo - Indonesia Mel - Melanesia

Mi C T N S J Mo K A C A B A N N Me P A S L V B I

n

a a

h

a . i o n a u o f i A h i . i u Mic - Micronesia

d

c n C e b

C

o c p

a

r d s r i r

u m

l o n

t

h i h Aus - Australia c

i i Af - Africa Cauc - Caucasian Population Figure 4.59. Box and whisker plot of nasal height (n-ns) for pooled sex data. Populations are in order of increasing median. * denotes sample size n < 5.

116 Population Key 60.00 NA - Native America Sib - Siberia Mon - Mongolia * Ain - Ainu 55.00 Kor - Korea * Jap - Japan * S.Chi - South China

) N.Chi - North China m

m Bur - Burma ( 50.00 Lao - Laos

s *

Viet - Vietnam -n

n Thai - Thailand Cam - Cambodia Phi - Philippines 45.00 And - Andaman Is. Nic - Nicobar Is. Bor - Borneo Indo - Indonesia Mel - Melanesia 40.00

T J Mo Mi S K A A A N C B A P S Me N C L B V N I

n Mic - Micronesia

a a

h

i o n i f i a o u h . A a u i .

d

b n c C e

C

p c

o a

r d r s i r

u m

l o n t Aus - Australia

h h i

c

i i Af - Africa Cauc - Caucasian Population Figure 4.60. Box and whisker plot of nasal height (n-ns) for male-only data. Populations are in order of increasing median. * denotes sample size n < 5.

4.3 Summary and Conclusions

Considerable overlap between all populations is evident, however, separation of Asian and non-Asian samples, as well as northern versus southern East Asian is observable. All variables discussed above exhibited overall significant differences between samples when subjected to Kruskal-Wallis tests.

4.3.1 East Asian versus non-Asian Breadth and length variables of the face and vault discriminate East Asian and non- Asian samples. Specifically, the following breadth and length variables are supported statistically (Kruskal-Wallis and pairwise post-hoc Bonferroni-corrected p-values) as exhibiting significant differences:  Interorbital (mf-mf)  Bi-orbital (fmo-fmo and fmt-fmt)  Bimaxillary breadth (ZMB)  Nasal breadth (al-al)

117  Anterior cranial breadth (STB, bipterionic)  Posterior cranial breadth (AUB, biporionic)  Basion-prosthion length (BPL)  Inferior malar length (IML)  Vault length (n-l, g-l)  Parietal length (PAC)  Palate length (sta-ol)

4.3.2 Northern versus Southern East Asians Variables distinguishing northern from southern East Asians samples are those describing facial height (its component heights). The following variables are found to clearly separate the majority of Northeast Asia and northern East Asia sensu stricto from the majority of Southeast Asia:  Alveolar height (pr-ns)  Upper facial height (NPH)  Prosthion–glabella height (pr-g)  Nasal height (n-ns) North-south separations on the basis of these variables are supported statistically by Kruskal-Wallis tests. A number of variables isolated the Andaman Islanders as being unusually small in size in comparison to all remaining samples. These distinctions are statistically significant using Kruskal-Wallis tests. Variables isolating the Andaman Islanders are:  Facial Breadth (fmo-fmo, ZMB, bi-inferior zygomatic)  Facial length (BPL)  Facial height (pr-ns, pr-g, n-ns)  Cranial breadth (STB, AUB, biporionic, bimastoidale)  Cranial length (n-l. g-l)  Foramen Magnum length (FOL) The neighbouring Nicobar Islanders exhibit similar results for facial breadth (bi-inferior zygomatic breadth), posterior cranial breadth (AUB, biporionic, bimastoidale) and facial height (NPH).

118 Chapter 5 Results Univariate Analysis Part B: Angles

5.1 Introduction

A table of summary statistics (median, range, standard deviation and coefficient of variation values) for 18 angular pooled sex variables is presented in Appendix 3. Most variables exhibit indistinguishable sample dispersions and variability, which is not surprising, as the angles have been derived from the linear measurements described in Chapter 4. As for the linear variables, exceptions to this are samples exhibiting small sample sizes (n 5), which generally continue to exhibit inflated CVs despite being corrected for low sample size (after Sokal and Braumann, 1980). Angles quantifying prognathism (e.g. NS and PR) and those involving nasospinale (e.g n-ns-zyo) and maxillofrontale (e.g mf-n-zyo) also exhibit inflated CVs. As these angles are derived from the linear variables exhibiting high variability described in Chapter 4, it is not unexpected that these angles also exhibit inflated values. The reasons behind this inflation are outlined in Chapter 4. The pooled sex samples were disaggregated into male and female samples to assess if sexual dimorphism had an effect on variability (Appendix 3). Once separated, SD and CV remain relatively similar to pooled sex samples. Discrepancies between the three samples may be attributed to differences in sample sizes or may possibly be explained by complex sex-specific population histories (Perez et al, 2007). While dispersion and variability between samples is generally very similar, sample medians display substantial variation. As observed for linear variables (Chapter 4) pooled sex and male-only samples exhibit similar values, which may be attributed to an imbalance between male and female sample sizes, with males tending to exhibit the greater number of individuals. Thus, the pooled sex sample may be prejudiced by the male-only samples. Hence, it was deemed appropriate to analyse all three samples: pooled sex, male-only and female-only. The method of analysing apparent significant median differences between samples (ie. Asian versus non-Asian and/or divisions within East Asia sensu lato) is as

119 described previously in Chapter 4. Apparent significant differences were first were assessed with Box and Whisker plots (B&W; presented below), a heuristic device in which non-overlapping boxes are indicative of a significant difference at the < 1% level. Significant median differences were confirmed statistically with Kruskal-Wallis tests. The overall results of the Kruskal-Wallis tests are summarised below, while p-values of the non-parametric post-hoc tests, based on Bonferroni-corrected pairwise Mann- Whitney (Hammer et al, 2001) are presented in Appendix 4. Generally, B&W plots reveal that most samples are approximately normally distributed, with the exception of a few. Samples exhibiting skewed medians are mostly those with a sample size of n < 5. Populations with low sample numbers are herein marked accordingly (*) and should be regarded with caution, as they may not accurately represent the actual population value of central tendency. Samples are arranged within in each plot in order of increasing median.

5.2 Results

5.2.1 Facial Flatness variables 5.2.1.1 Upper Facial Flatness Upper facial angles that discriminate samples are a combination of standard, modified standard and original angles. Upper facial flatness angles are defined in the current study as those describing facial flatness in the superior orbital region, particularly at nasion. Angles NAA, mNFA, mf-n-zyo and ns-n-zyo are discussed below. Facial flatness angles of the upper face tend to distinguish East Asia from non- Asian populations, with some evidence of north to south East Asian clines. Nasion angle, NAA, is a part of the standard facial triangle (Howells, 1973) and a measure of facial flatness, where a low angle is indicative of a flat face. The angle displays a similar distribution of samples across all three plots: pooled sex (fig 5.1), male-only (fig 5.2) and female-only (fig 5.3). All three figures show separation, albeit imperfect, of comparative and East Asian populations. Australia, Melanesia and Africa tend to exhibit the highest angles, and thus a greater degree of upper facial projection. These samples are often accompanied by a number of island Southeast Asian populations. The Caucasian sample is consistently positioned close to the Korean sample, with both populations displaying the lowest angles, clearly separated from the

120 remaining samples. However, Korea exhibits a small sample number in all three plots. There is a possible suggestion of a north to south East Asian cline in all three groups, with northern populations tending to display the lower median angle. However, considerable overlap between north and south is readily observable. All remaining East Asian populations display a moderate NAA. Kruskal-Wallis tests (Appendix 4) detected highly significant median differences for all three plots: pooled sex (H: 163.9, p < 0.001), male-only (H:111.5, p < 0.001) and female-only (H: 70.07, p < 0.001). The second facial flatness angle, mNFA, is a modified version of the standard NFA (see Chapter 2- Materials and Methods). The angle is a measure of transverse facial flatness with respect to the angle of the frontal bone. A high angle results in reduced facial projection at nasion. Box and Whiskers plots (pooled sex, male-only and female-only) display similar sample groupings.

Population Key

NA - Native America Sib - Siberia 80.00 Mon - Mongolia Ain - Ainu Kor - Korea Jap - Japan 75.00 *

) S.Chi - South China .

g N.Chi - North China e Bur - Burma (d * 70.00 Lao - Laos

AA Viet - Vietnam

N Thai - Thailand 65.00 Cam - Cambodia Phi - Philippines And - Andaman Is. Nic - Nicobar Is. 60.00 Bor - Borneo Indo - Indonesia Mel - Melanesia

K C N B C Mo V S N A J P I T B L S Mi N A A A Me

n

a a Mic - Micronesia

h

o a . u a i i A i h o . i f n u

d

e b n C c

C

p c

a o

r r i r d s

u m

n o l t Aus - Australia h i h

c

i i Af - Africa Cauc - Caucasian Population Figure 5.1. Box and whisker plot of upper facial flatness angle (NAA) for pooled sex data. Populations are in order of increasing median. * denotes sample size n < 5.

121 Population Key 80.00 NA - Native America Sib - Siberia Mon - Mongolia 75.00 * * Ain - Ainu Kor - Korea Jap - Japan

) * S.Chi - South China .

g 70.00 N.Chi - North China e

d Bur - Burma ( Lao - Laos

Viet - Vietnam AA

N 65.00 Thai - Thailand Cam - Cambodia Phi - Philippines * And - Andaman Is. Nic - Nicobar Is. 60.00 Bor - Borneo Indo - Indonesia Mel - Melanesia

K C N Mo V B S J N L T I P B N A S C A Mi A A Me

n Mic - Micronesia a a

h

o a . i u i A h o i n . a f i u

d

e b c C n

C

p c

o a

r r i r d s

u m

n o l t Aus - Australia

h i h

c

i i Af - Africa Cauc - Caucasian Population Figure 5.2. Box and whisker plot of upper facial flatness angle (NAA) for male-only data. Populations are in order of increasing median. * denotes sample size n < 5.

Population Key

80.00 NA - Native America * Sib - Siberia Mon - Mongolia Ain - Ainu 75.00 Kor - Korea Jap - Japan

) S.Chi - South China .

g * N.Chi - North China e * * d 70.00 * Bur - Burma Lao - Laos

* Viet - Vietnam AA (

N Thai - Thailand 65.00 Cam - Cambodia Phi - Philippines And - Andaman Is. Nic - Nicobar Is. 60.00 Bor - Borneo Indo - Indonesia Mel - Melanesia

C K B C N P N A Mo B S S V Mi J L T A I A Me N A

n Mic - Micronesia

a a

h

a o u a . h A i o . i i n f i u

d

n C b e c

C

c p

o a

r r i r d s

u m

n o l t Aus - Australia

h h i

c

i i Af - Africa Cauc - Caucasian Population Figure 5.3. Box and whisker plot of upper facial flatness angle (NAA) for female-only data. Populations are in order of increasing median. * denotes sample size n < 5.

122 Figure 5.4 displays the pooled sex results for mNFA. As with NAA, the angle appears to distinguish Asian from non-Asian populations, only here, the majority of comparative populations exhibit the lowest median angles, indicating that these samples have a greater degree of transverse projection of the frontal bone (ie.nasion is more projecting). Exceptions to this are the Micronesian and Native American samples, which tend to exhibit moderate medians. East Asians exhibit moderate to high angles, with considerable overlap between all Asian samples. Highly significant median differences are apparent in pooled sex samples (H: 80.47, p < 0.001; see Appendix 4). Male-only and female-only analyses are presented in figures 5.5-5.6 respectively, and display similar groupings as observed in the pooled sex plot. However, the female- only group displays some differences: The Australian and Caucasian sample is still low, but overlap with East Asia is observable. The African sample no longer clusters at the low end of the scale, instead exhibiting a more moderate median angle. Remaining comparative samples are within the East Asian range, all of which exhibit moderate medians. Kruskal-Wallis tests (Appendix 4) identified significant differences in both male-only (H: 69.67, p < 0.001) and female-only (H: 29.17, p = 0.02) plots.

Population Key

NA - Native America Sib - Siberia * Mon - Mongolia * Ain - Ainu Kor - Korea

150.00 Jap - Japan )

. S.Chi - South China g

e N.Chi - North China d

( Bur - Burma

A Lao - Laos

F Viet - Vietnam N 140.00 Thai - Thailand m Cam - Cambodia Phi - Philippines And - Andaman Is. Nic - Nicobar Is. Bor - Borneo 130.00 Indo - Indonesia Mel - Melanesia

A C Me A A Mi C I N N B N S K A V B J P S L Mo T

n Mic - Micronesia

a a

h

f a u n a i A u . i o i i o h .

d

c b n e C

C

c p

o a

s d r r r i

u m

l o n t Aus - Australia

h h i

c

i i Af - Africa Cauc - Caucasian Population Figure 5.4. Box and whisker plot of upper facial flatness angle (mNFA) for pooled sex data. Populations are in order of increasing median. * denotes sample size n < 5.

123 Population Key

NA - Native America Sib - Siberia Mon - Mongolia * Ain - Ainu Kor - Korea 150.00 *

Jap - Japan

) .

g * S.Chi - South China e N.Chi - North China d * ( Bur - Burma

A Lao - Laos

F N Viet - Vietnam

m 140.00 Thai - Thailand Cam - Cambodia Phi - Philippines And - Andaman Is. Nic - Nicobar Is. Bor - Borneo 130.00 Indo - Indonesia Mel - Melanesia

A Me A C A C N Mi I B T V S K N B N J L S P A Mo

n

a a

h f u a n a A u i i o i o . . h i Mic - Micronesia d

e b c C n

C

c p

a o

s d r r r i

u m

l o n

t

i h h c Aus - Australia

i i Af - Africa Cauc - Caucasian Population

Figure 5.5. Box and whisker plot of upper facial flatness angle (mNFA) for male-only data. Populations are in order of increasing median. * denotes sample size n < 5.

Population Key

155.00 * NA - Native America * Sib - Siberia * Mon - Mongolia 150.00 Ain - Ainu Kor - Korea

Jap - Japan )

. S.Chi - South China

g *

e 145.00 * N.Chi - North China d

( Bur - Burma

A Lao - Laos

F * Viet - Vietnam N 140.00 Thai - Thailand m Cam - Cambodia Phi - Philippines And - Andaman Is. 135.00 Nic - Nicobar Is. Bor - Borneo Indo - Indonesia Mel - Melanesia

J C Mi A N N A P C A I L B A N S Me S B Mo V K T

n Mic - Micronesia

a a

h

a u i . n h a f u i A i . o i o

d

c n b C e

C

p c

o a

s d i r r r

u m

o l n t Aus - Australia

h h i

c

i i Af - Africa Cauc - Caucasian Population Figure 5.6. Box and whisker plot of upper facial flatness angle (mNFA) for female-only data. Populations are in order of increasing median. * denotes sample size n < 5.

124 The facial angle mf-n-zyo has been specifically created in this study to assess the relationship of nasion to the inferior margin of the orbit. Nasion is less projecting with respect to the orbit when the angle is low. A low interorbital breadth and tall upper face are also features of a low angle. Figures 5.7 and 5.8 display univariate results for this angle in pooled sex and female-only samples respectively, with the male-only sample excluded due to considerable overlap. As observed with the upper facial flatness angles above, an East Asian versus non-Asian separation is present. Figure 5.7 shows that pooled sex median values are relatively similar for the majority of populations. The Pacific populations- Australia, Melanesia and Micronesia display median values greater, or higher, than the remaining samples. The Andaman Islands sample exhibits the lowest median angle, with the majority of remaining populations displaying moderate angles. Significant differences between samples have been identified using a Kruskal-Wallis test (H: 61.17, p < 0.00; see Appendix 4).

Population Key

NA - Native America Sib - Siberia 30.00 Mon - Mongolia Ain - Ainu Kor - Korea

Jap - Japan )

. 25.00

g S.Chi - South China e

d * N.Chi - North China

( Bur - Burma o

y 20.00 * Lao - Laos z

- Viet - Vietnam

n -

f Thai - Thailand

m 15.00 Cam - Cambodia Phi - Philippines And - Andaman Is. Nic - Nicobar Is. 10.00 Bor - Borneo Indo - Indonesia Mel - Melanesia

A S K A P L Mo B B C S V C N J T I N A N Me Mi A

n Mic - Micronesia

a a

h

n . o f h o u a i i a i A i . u

d

C b e c n

C

o p c

a

d r i r r s

m u

n o l

t Aus - Australia

h i h

c

i i Af - Africa Cauc - Caucasian Population Figure 5.7. Box and whisker plot of upper facial flatness angle (mf-n-zyo) for pooled sex data. Populations are in order of increasing median. * denotes sample size n < 5.

125 Population Key

NA - Native America Sib - Siberia 30.00 Mon - Mongolia Ain - Ainu Kor - Korea

) Jap - Japan . 25.00 g S.Chi - South China e *

d * N.Chi - North China ( * *

o * Bur - Burma

y z 20.00 Lao - Laos

- *

n Viet - Vietnam -

f Thai - Thailand

m Cam - Cambodia 15.00 Phi - Philippines And - Andaman Is. Nic - Nicobar Is. 10.00 Bor - Borneo Indo - Indonesia Mel - Melanesia

A Mo A S K B N P C I N J S B L C N V A Mi A T Me

n

a a h Mic - Micronesia n f . o u i h a . i o a A i i u

d

C c b e n

C

p c

o a

d r r i r s

u m

n o l

t

h h i Aus - Australia

c

i i Af - Africa Cauc - Caucasian Population

Figure 5.8. Box and whisker plot of upper facial flatness angle (mf-n-zyo) for female-only data. Populations are in order of increasing median. * denotes sample size n < 5.

A similar yet incomplete distribution of samples is observed in the female-only plot (fig 5.8). The high comparative samples remain, but the cluster overlaps with Thailand and Ainu samples. The Ainu are represented by a single individual, and thus it is unlikely to be representative. All remaining populations exhibit a moderate to low medians, with the Andamanese sample consistently the lowest. Significant median differences are apparent in this plot (H: 39.68, p < 0.01). An observable East Asian versus non-Asian separation, and a north to south East Asian cline is observed in pooled sex (fig 5.9), male-only (fig 5.10) and female-only (fig 5.11) plots for upper facial flatness angle, ns-n-zyo. All three plots exhibit significant differences (H: 138.0, p < 0.001; H: 98.53, p < 0.001; H: 44.26, p < 0.001) when subjected to Kruskal-Wallis tests (Appendix 4). This angle represents upper nasal projection, with a high angle indicating increased projection of nasion with respect to the inferior margin of the orbit. A short facial height and high inferior interorbital breadth (zyo-zyo) are also characteristic of a high angle.

126 Population Key 60.00 NA - Native America Sib - Siberia Mon - Mongolia 55.00 Ain - Ainu Kor - Korea

Jap - Japan

) .

g S.Chi - South China e 50.00

d N.Chi - North China

( Bur - Burma o

y Lao - Laos

z * - Viet - Vietnam

-n 45.00

s Thai - Thailand

n * Cam - Cambodia Phi - Philippines And - Andaman Is. 40.00 Nic - Nicobar Is. Bor - Borneo Indo - Indonesia Mel - Melanesia

K N S Mo J C A V B I N C T N B L A P Me A Mi S A

n Mic - Micronesia

a a

h

o . i a i i u i a A o n h f . u

d

b n e c C

C

p o c

a

r r r d i s

u m

n o l t Aus - Australia

h i h

c

i i Af - Africa Cauc - Caucasian Population

Figure 5.9. Box and whisker plot of upper facial flatness angle (ns-n-zyo) for pooled sex data. Populations are in order of increasing median. * denotes sample size n < 5.

Population Key

NA - Native America 55.00 Sib - Siberia Mon - Mongolia * * Ain - Ainu Kor - Korea

Jap - Japan )

. 50.00

g S.Chi - South China

e N.Chi - North China d ( Bur - Burma

o *

y Lao - Laos z

- 45.00 Viet - Vietnam

-n Thai - Thailand s

n Cam - Cambodia * Phi - Philippines 40.00 And - Andaman Is. Nic - Nicobar Is. Bor - Borneo Indo - Indonesia Mel - Melanesia

K N C S Mo J V A I N N B T L B Me P A A C Mi A S

n Mic - Micronesia

a a

h

o . a i i i i A u o h n f a u .

d

b e n c C

C

p o c

a

r r r i d s

u m

n o l

t Aus - Australia

h i h

c

i i Af - Africa Cauc - Caucasian Population Figure 5.10. Box and whisker plot of upper facial flatness angle (ns-n-zyo) for male-only data. Populations are in order of increasing median. * denotes sample size n < 5.

127 Population Key

NA - Native America 60.00 Sib - Siberia Mon - Mongolia Ain - Ainu Kor - Korea Jap - Japan 55.00 S.Chi - South China

) N.Chi - North China

. *

g Bur - Burma

e Lao - Laos (d

o 50.00 * Viet - Vietnam

y * Thai - Thailand z - Cam - Cambodia

-n *

s Phi - Philippines n And - Andaman Is. 45.00 * Nic - Nicobar Is. * Bor - Borneo Indo - Indonesia Mel - Melanesia 40.00 Mic - Micronesia Aus - Australia

K A Mo N J S S B C I C B N A V L P T Me A A N Mi

n

a a

h

o i . i . u a a o A n i h f u i Af - Africa

d

n b C e c

C

p c

o a

r r r d i s

m u

n o l

t

h h i

c Cauc - Caucasian

i

i

Population Figure 5.11. Box and whisker plot of upper facial flatness angle (ns-n-zyo) for female-only data. Populations are in order of increasing median. * denotes sample size n < 5.

All three plots (pooled sex, male-only and female-only) show that comparative samples Australia, Melanesia, Micronesia and Africa have the highest medians, although in all cases, the cluster is flawed. South China is positioned among the comparative cluster for both the pooled sex and male-only plots, while Cambodian and Nicobar samples exhibit similar high medians in the male-only and female-only plots respectively. These three samples are, however, small samples (n < 5) in the male and female only groups, and thus results should be regarded with caution. A north to south distribution in East Asia is also observed in all three plots, with Northeast and East Asia sensu stricto tending to exhibit the lowest medians, positioning at the low end of the moderate cluster. Remaining East Asian populations display moderate angles.

5.2.1.2 Mid-Facial Flatness Mid-facial angles that separate or group variables are a combination of modified standards and original angles. Mid-facial angles are defined in the current study as those describing projection or flatness of the face in the region of the inferior malars (ZMB) and nasal aperture, particularly at nasospinale. Angles mSSA, ns-n-ba, and n-ns-zyo are

128 discussed below. Facial flatness angles of the mid-face tend to distinguish East Asian from non-Asian populations, with one angle displaying a north-south pattern. The zygomaxillary angle (mSSA), modified from the standard in the current study, distinguishes East Asian from non-Asian populations in pooled sex (fig 5.12), male-only (fig. 5.13) and female-only (fig. 5.14) plots. All three plots exhibit significant differences between samples (H: 161.6, p < 0.001; H: 111.5, p < 0.001: H: 62.86, p < 0.001; see Appendix 4 for specific details). Melanesia and Australia consistently exhibit the lowest medians across all three plots. The Caucasian sample exhibits a low or low to moderate angle, and consistently clusters with the Andmanese, thus marring the distinct separation of the comparative samples from East Asia. Africa exhibits a moderate median, similar to that of the East Asians. All East Asian populations exhibit moderate to high median angles, with no obvious groupings or separations.

Population Key

NA - Native America Sib - Siberia 150.00 Mon - Mongolia * Ain - Ainu Kor - Korea

* Jap - Japan )

. 140.00 S.Chi - South China g

e N.Chi - North China

(d Bur - Burma

Lao - Laos A

S Viet - Vietnam

S 130.00 Thai - Thailand m Cam - Cambodia Phi - Philippines 120.00 And - Andaman Is. Nic - Nicobar Is. Bor - Borneo Indo - Indonesia Mel - Melanesia

Me A A C Mi B A N J S P C T Mo K N I S B V L A N

n Mic - Micronesia

a a

h

u n a u f . i h a o A . o i i i

d

b C e n c

C

c p

a o

s d r i r r

u m

l n o t Aus - Australia

h i h

c

i i Af - Africa Cauc - Caucasian Population

Figure 5.12. Box and whisker plot of mid- facial flatness angle (mSSA) for pooled sex data. Populations are in order of increasing median. * denotes sample size n < 5.

129 Population Key

NA - Native America 150.00 Sib - Siberia Mon - Mongolia * * Ain - Ainu * Kor - Korea * Jap - Japan

) 140.00

. S.Chi - South China g

e N.Chi - North China d

( Bur - Burma

A Lao - Laos

S 130.00 Viet - Vietnam

S Thai - Thailand m Cam - Cambodia Phi - Philippines 120.00 And - Andaman Is. Nic - Nicobar Is. Bor - Borneo Indo - Indonesia Mel - Melanesia

Me A A C C B A J S Mi N T N I P B K Mo V L S N A

n Mic - Micronesia

a a

h

u n a a u f i A . h o o i . i i

d

b e C c n

C

p c

a o

s d r i r r

u m

l o n t Aus - Australia

i h h

c

i i Af - Africa Cauc - Caucasian Population

Figure 5.13. Box and whisker plot of mid-facial flatness angle (mSSA) for male-only data. Populations are in order of increasing median. * denotes sample size n < 5.

Population Key

NA - Native America Sib - Siberia 150.00 Mon - Mongolia Ain - Ainu Kor - Korea * Jap - Japan

S.Chi - South China ) . * N.Chi - North China g 140.00 * e Bur - Burma d * Lao - Laos A( * Viet - Vietnam S *

S Thai - Thailand

m 130.00 Cam - Cambodia Phi - Philippines And - Andaman Is. Nic - Nicobar Is. Bor - Borneo 120.00 Indo - Indonesia Mel - Melanesia Mic - Micronesia

A Me C A N N Mi B A K Mo A P S S C J I V N L T B

n

a a

h u a n . i u f o i h . i a i A o Aus - Australia

d

c n C b e

C

c p

o a

s d r r i r

u m

l n o

t

h h i

c Af - Africa

i i Cauc - Caucasian Population Figure 5.14. Box and whisker plot of mid-facial flatness angle (mSSA) for female-only data. Populations are in order of increasing median. * denotes sample size n < 5.

130 Groupings are observed for the angle ns-n-ba, a measure of mid-facial flatness with respect to the cranial base, in pooled sex, male-only and female-only plots (figs 5.15-5.17) with suggestions of a distinction between Asian and non-Asian populations. This angle describes the degree of nasospinale projection, with a high angle at nasion reflective of projection of nasospinale. The placement of the cranial base at basion also affects this angle, ie the longer the cranial base (posteriorly placed basion) the higher the angle. Australia, Melanesia and Africa consistently exhibit the highest median angle in pooled sex (fig 5.15), male-only (fig 5.16) and female-only (fig 5.17) plots. The non- Asians, particularly the African sample, exhibit similar median values to the Andaman Islands sample for all three plots. The remaining East Asian samples display extensive overlap, with Northeast Asia exhibiting medians in the upper moderate scale. The lowest medians tend to be exhibited by North China and Caucasian samples. Korea displays the lowest median angle, but its small sample size means it may not be representative. A Kruskal-Wallis test (Appendix 4) detected highly significant differences in all three plots: pooled sex (H: 148.3, p < 0.001), male-only (H: 97.55, p < 0.001) and female-only (H: 61.95, p < 0.001).

Population Key 80.00 NA - Native America Sib - Siberia Mon - Mongolia 75.00 Ain - Ainu Kor - Korea

Jap - Japan ) . 70.00 g S.Chi - South China e N.Chi - North China (d Bur - Burma a *

b 65.00 Lao - Laos

- * Viet - Vietnam -n s Thai - Thailand n 60.00 Cam - Cambodia Phi - Philippines And - Andaman Is. 55.00 Nic - Nicobar Is. Bor - Borneo Indo - Indonesia Mel - Melanesia

K N B C N V I L P N J A C B Mo S S T Mi A A A Me

n

a a

h o . u a A i h i i a o i . n f u Mic - Micronesia

d

e c n b C

C

p c

o a

r r i r d s

u m

o n l

t

h h i

c Aus - Australia

i i Af - Africa Cauc - Caucasian Population

Figure 5.15. Box and whisker plot of mid-facial flatness angle (ns-n-ba) for pooled sex data. Populations are in order of increasing median. * denotes sample size n < 5.

131 Population Key

NA - Native America Sib - Siberia Mon - Mongolia 75.00 Ain - Ainu Kor - Korea Jap - Japan S.Chi - South China

70.00 N.Chi - North China ) . Bur - Burma

g * e * * Lao - Laos

(d 65.00 Viet - Vietnam a

b Thai - Thailand

-

n Cam - Cambodia -

s Phi - Philippines n 60.00 And - Andaman Is. Nic - Nicobar Is. * Bor - Borneo 55.00 Indo - Indonesia Mel - Melanesia Mic - Micronesia Aus - Australia

K N C B V I L P N J T C N Mo B S A S Mi A A A Me

n Af - Africa a a

h

o . a u i h i a A o i i . n f u

d

e c b n C

C

p c

o a

r r i r d s

u m

o n l t Cauc - Caucasian h i h

c

i

i

Figure 5.16. Box and whisker plot of mid-faPopulationcial flatness angle (ns-n-ba) for male-only data. Populations are in order of increasing median. * denotes sample size n < 5.

Population Key

80.00 NA - Native America Sib - Siberia Mon - Mongolia Ain - Ainu Kor - Korea

Jap - Japan

) .

g 70.00 S.Chi - South China e * N.Chi - North China

(d * * Bur - Burma a

b Lao - Laos -

n * * Viet - Vietnam

- * s Thai - Thailand n Cam - Cambodia 60.00 Phi - Philippines And - Andaman Is. Nic - Nicobar Is. Bor - Borneo Indo - Indonesia Mel - Melanesia

K N B P C N S B A J L C I Mi V S N T Mo A A Me A

n

a a h Mic - Micronesia o . u h a A . o i a i i i f n u

d

C n e b c

C

p c

o a

r r i r d s

u m

o n l

t

h h i Aus - Australia

c

i i Af - Africa Cauc - Caucasian Population

Figure 5.17. Box and whisker plot of mid-facial flatness angle (ns-n-ba) for female-only data. Populations are in order of increasing median. * denotes sample size n < 5.

132 Figures 5.18-5.20 display the B&W plots for mid-facial flatness angle n-ns-zyo in pooled sex, male-only and female-only samples respectively. This angle describes the degree of projection of nasospinale, with a low angle occurring when nasospinale is flat and inline with nasion, resulting in a flat mid-face. A tall face and low inferior interorbital breadth (zyo-zyo) are also associated with a low angle. East Asian and non-Asian populations are separated consistently for all three plots. Non-Asian populations Australia, Melanesia and Africa exhibit the higher median angles in all three plots, and are joined by Micronesia in the male-only plot (fig. 5.22). Remaining comparative samples display moderate medians in all three groups A second observation is the position of the Andaman Islands sample, which exhibits a similar median to the African sample, and thus possesses a high median angle compared to remaining East Asian populations. This is observable across all three plots (pooled sex, male-only and female-only). Kruskal-Wallis tests (Appendix 4) identified significant differences in pooled sex (H: 114.5, p < 0.001), male-only (H: 65.73, p < 0.001) and female-only (H: 44.26, p < 0.001) samples.

Population Key

NA - Native America Sib - Siberia 60.00 Mon - Mongolia Ain - Ainu

) Kor - Korea .

g Jap - Japan e * d S.Chi - South China ( 50.00 *

o N.Chi - North China y

z Bur - Burma -

s Lao - Laos

-n Viet - Vietnam n Thai - Thailand 40.00 Cam - Cambodia Phi - Philippines And - Andaman Is. Nic - Nicobar Is. Bor - Borneo 30.00 Indo - Indonesia

J K N V Mo S T A S L P C Me N Mi B B A I N A C A

n

a a

h

o . i . i i h a i o u n A u a f Mel - Melanesia

d

e C n b c

C

p o c

a

r i r r d s

m u

n l o

t

h h i Mic - Micronesia c

i i Aus - Australia Af - Africa Population Cauc - Caucasian

Figure 5.18. Box and whisker plot of mid- facial flatness angle (n-ns-zyo) for pooled sex data. Populations are in order of increasing median. * denotes sample size n < 5.

133 Population Key

NA - Native America Sib - Siberia Mon - Mongolia 60.00 Ain - Ainu Kor - Korea

Jap - Japan

) .

g S.Chi - South China e * N.Chi - North China d * *

( 50.00 * Bur - Burma o

y Lao - Laos z

- Viet - Vietnam s

Thai - Thailand -n

n Cam - Cambodia 40.00 Phi - Philippines And - Andaman Is. Nic - Nicobar Is. Bor - Borneo Indo - Indonesia Mel - Melanesia 30.00

K J N S V S Mo T Mi L C N P B A Me N A C B I A A

n Mic - Micronesia

a a

h

o . i i . a i h o i A n a u u f

d

b e C c n

C

p c o

a

r i r d r s

m u

n l o t Aus - Australia

h h i

c

i i Af - Africa Cauc - Caucasian Population Figure 5.19. Box and whisker plot of mid-facial flatness angle (n-ns-zyo) for male-only data. Figure 7.3. Box and whisker plot of mid-facial flatness angle (n-ns-zyo) for male-only data. Populations are in order of increasing median. * denotes sample size n < 5. Populations are in order of increasing median. * denotes sample size n < 5.

Population Key

NA - Native America Sib - Siberia Mon - Mongolia Ain - Ainu 60.00 * Kor - Korea Jap - Japan

) S.Chi - South China .

g N.Chi - North China e

d Bur - Burma (

o Lao - Laos y

z * * Viet - Vietnam - 50.00 * * * s Thai - Thailand

-n Cam - Cambodia n Phi - Philippines And - Andaman Is. Nic - Nicobar Is. Bor - Borneo 40.00 Indo - Indonesia Mel - Melanesia Mic - Micronesia

S J V Mo K N Me T L A C S I B Mi B A A N P C N A

n

a a

h

. i o . i a i u o n u A h a i f Aus - Australia

d

C e n b c

C

p o c

a

r r r d s i

m u

n l o

t

h h i

c Af - Africa

i i Cauc - Caucasian Population Figure 5.20. Box and whisker plot of mid-facial flatness angle (n-ns-zyo) for female-only data. Populations are in order of increasing median. * denotes sample size n < 5.

134 5.2.1.3 Lower Facial Flatness Angles of lower facial flatness are defined in the study as angles that describe projection of the alveolar region (prognathism), specifically at prosthion. One lower facial flatness angle (NS) displayed apparent significant separations between populations. The angle NS, was specifically created for the current study, and involves the landmarks nasospinale, prosthion and basion. A high angle is indicative of projection of the lower face at prosthion with respect to nasospinale. This angle displays evidence of a north to south East Asian cline. An Asian versus non-Asian distinction is implied, particularly with Australian and Melanesian samples, but considerable overlap between Asian and non-Asian samples is apparent. Figures 5.21-23 display slight separation of Northeast Asia from the remaining East Asian populations in pooled sex, male-only and female-only plots respectively, with the northern cluster exhibiting the lower medians. This indicates that prosthion exhibits little projection with respect to nasospinale in these Northeast Asian samples. Cambodia displays a similar median to the Northeast Asians in the pooled sex (fig 5.21) and female-only (fig 5.23) plots. All remaining East Asian samples possess a moderate median, except in the female-only plot (fig 5.23), where a number of Southeast Asian populations exhibit dramatically higher medians compared to the main body of East Asian samples. Another observation that is consistent for all three groups (pooled sex, male-only and female-only) is a distinct isolation of the Caucasian sample from all remaining populations, with the Caucasians displaying the lowest median. Remaining comparative samples tend to display moderate medians, positioning among the East Asian populations. All three plots exhibit highly significant median differences between samples (H: 156.4, p < 0.001; H: 107.8, p < 0.001; H: 66.89, p < 0.001; for pooled sex, male and female plots, respectively) when subjected to Kruskal-Wallis tests (Appendix 4).

135 Population Key

140.00 NA - Native America Sib - Siberia Mon - Mongolia Ain - Ainu * Kor - Korea * Jap - Japan S.Chi - South China

) 120.00 .

g N.Chi - North China e

d Bur - Burma

( Lao - Laos

S N Viet - Vietnam Thai - Thailand 100.00 Cam - Cambodia Phi - Philippines And - Andaman Is. Nic - Nicobar Is. Bor - Borneo Indo - Indonesia 80.00 Mel - Melanesia

C S N Mo C N A J A K B V A B S L T Mi A P I Me N

n

a a

h a i . a A i f o u i n o . u h i Mic - Micronesia d

b n e C c

C

p c

o a

r r d r s i

u m

n o l

t

h h i

c Aus - Australia

i i Af - Africa Cauc - Caucasian Population

Figure 5.21. Box and whisker plot of lower facial flatness angle (NS) for pooled sex data. Populations are in order of increasing median. * denotes sample size n < 5.

Population Key

NA - Native America 140.00 Sib - Siberia Mon - Mongolia Ain - Ainu * Kor - Korea * Jap - Japan * S.Chi - South China

) 120.00

. N.Chi - North China g

e * Bur - Burma d

( Lao - Laos

S Viet - Vietnam N Thai - Thailand Cam - Cambodia 100.00 Phi - Philippines And - Andaman Is. Nic - Nicobar Is. Bor - Borneo Indo - Indonesia Mel - Melanesia 80.00

C A S N Mo A J V N B K L S B T A Mi I A P Me N C

n Mic - Micronesia

a a

h

a f i . n i A u o . o u i h i a

d

b e C n c

C

p c

o a

d r r r s i

u m

n o l t Aus - Australia

h h i

c

i i Af - Africa Cauc - Caucasian Population

Figure 5.22. Box and whisker plot of lower facial flatness angle (NS) for male-only data. Populations are in order of increasing median. * denotes sample size n < 5.

136 Population Key

NA - Native America * Sib - Siberia Mon - Mongolia 130.00 Ain - Ainu * Kor - Korea * Jap - Japan S.Chi - South China

) N.Chi - North China

. 120.00 *

g * Bur - Burma e

d Lao - Laos

( Viet - Vietnam S

N 110.00 * Thai - Thailand Cam - Cambodia Phi - Philippines And - Andaman Is. 100.00 Nic - Nicobar Is. Bor - Borneo Indo - Indonesia Mel - Melanesia Mic - Micronesia

C Mo S C N A N B S B V P J A Mi A K L A T Me N I

n

a a

h

a i a . i A u . o i h n f o u i

d b n C e c Aus - Australia C

p c

o a

r r i d r s

u m

n l o

t

h h i c Af - Africa

i i Cauc - Caucasian Population

Figure 5.23. Box and whisker plot of lower facial flatness angle (NS) for female-only data. Populations are in order of increasing median. * denotes sample size n < 5.

5.2.2 Other Facial Angles The angle BAA (basion angle) is used to assess facial height with respect to the cranial base, with a low angle indicative of a short facial height (NPH). This is a standard angle derived from Howells’ facial triangle (1973). In the present study, this angle implies divisions of both Asian from non-Asian samples and a north to south cline. Separation of comparative populations from East Asians is observable in pooled sex (fig. 5.24), male-only (fig. 5.25) and female-only (fig. 5.26) plots, while the north to south cline is most strongly observed in the former two plots. Comparative samples Africa, Australia and Melanesia consistently display the lowest medians for all three groups, with Micronesia present in the cluster for pooled sex and male plots only (figs 5.24-25 respectively). The separation is not complete however, with the presence of the Andaman Islanders within the comparative cluster in both the pooled sex and male-only plots, and the Nicobar Islanders in the female-only group. In the latter case, the Nicobarese display a small sample number (n = 3) and should thus be regarded with care.

137 Population Key

NA - Native America 50.00 Sib - Siberia Mon - Mongolia Ain - Ainu * Kor - Korea Jap - Japan

) 45.00 S.Chi - South China .

g * N.Chi - North China e

d Bur - Burma ( Lao - Laos Viet - Vietnam

BAA 40.00 Thai - Thailand Cam - Cambodia Phi - Philippines And - Andaman Is. 35.00 Nic - Nicobar Is. Bor - Borneo Indo - Indonesia Mel - Melanesia

Me A A A Mi N A P C B J I V N B C T L S N S Mo K

n Mic - Micronesia a a

h

u n f i i h a o i A u a . . i o

d

c n e C b

C

c p

a o

s d i r r r

m u

l o n t Aus - Australia

i h h

c

i i Af - Africa Cauc - Caucasian Population

Figure 5.24. Box and whisker plot of facial angle (BAA) for pooled sex data. Populations are in order of increasing median. * denotes sample size n < 5.

Population Key

NA - Native America 50.00 Sib - Siberia Mon - Mongolia Ain - Ainu * Kor - Korea Jap - Japan

) 45.00

. S.Chi - South China g

e * N.Chi - North China d

( * Bur - Burma Lao - Laos

AA Viet - Vietnam B 40.00 * Thai - Thailand Cam - Cambodia Phi - Philippines And - Andaman Is. 35.00 Nic - Nicobar Is. Bor - Borneo Indo - Indonesia Mel - Melanesia

Mi A Me A A A N P B C I C J B L V T N N S S K Mo

n

a a

h n u i f i h o a a u i A . i . o Mic - Micronesia

d

n c e b C

C

c p

o a

d s i r r r

m u

l o n

t

i h h

c Aus - Australia

i i Af - Africa Cauc - Caucasian Population Figure 5.25. Box and whisker plot of facial angle (BAA) for male-only data. Populations are in order of increasing median. * denotes sample size n < 5.

138 Population Key * NA - Native America 48.00 Sib - Siberia Mon - Mongolia * Ain - Ainu Kor - Korea 44.00 * Jap - Japan

) S.Chi - South China .

g N.Chi - North China e *

d Bur - Burma ( * Lao - Laos 40.00 Viet - Vietnam

BAA Thai - Thailand * Cam - Cambodia Phi - Philippines 36.00 And - Andaman Is. Nic - Nicobar Is. Bor - Borneo Indo - Indonesia Mel - Melanesia

Me A N A A P C Mi B S I V J K N B T Mo L N S C A

n

a a Mic - Micronesia

h

f i u n h a o . i o A u . i a i

d

c C e b n

C

c p

a o

s d i r r r

m u

l o n t Aus - Australia h i h

c

i i Af - Africa Cauc - Caucasian Population

Figure 5.26. Box and whisker plot of facial angle (BAA) for female-only data. Populations are in order of increasing median. * denotes sample size n < 5.

Considering that the Korea and South China samples may not be representative of their populations due to small sample size (see appendix 3), Northeast Asians and North China thus display the highest medians in the pooled sex (fig. 5.24) and male- only (fig. 5.25) plots. A decreasing median, possibly linked with a decrease in latitude, is observed in these two groups, as remaining East Asian samples exhibit moderate medians for BAA. This pattern is not clearly observed in the female-only plot (fig. 5.26). A Kruskal-Wallis test (Appendix 4) identified highly significant differences in pooled sex (H: 137.1, p < 0.001), male-only (H: 98.37, p < 0.001) and female-only (H: 46.77, p < 0.001) plots.

5.2.3 Frontal Angles The frontal angles discussed here have been previously described by Howells (1973) and are derived from the Bregma-Nasion-Basion triangle. The first of these angles, the nasion angle (NBA) measures the slope of the frontal bone and the flexion of the cranial base. The second, basion angle (BBA) measures the slope and length of the frontal bone. Both angles

139 Population Key

90.00 NA - Native America Sib - Siberia Mon - Mongolia Ain - Ainu 85.00 Kor - Korea * Jap - Japan

) S.Chi - South China .

g N.Chi - North China e 80.00 d Bur - Burma ( *

Lao - Laos A

B Viet - Vietnam

N Thai - Thailand 75.00 Cam - Cambodia Phi - Philippines And - Andaman Is. Nic - Nicobar Is. 70.00 Bor - Borneo Indo - Indonesia Mel - Melanesia

A S C Mo A N A P B N N J Me T B A L C I Mi S V K

n

a a Mic - Micronesia

h

f i a u A i h u . i o n a . i o

d

b n c C e

C

p c

a o

s i r r d r

u m

n l o t Aus - Australia h i h

c

i i Af - Africa Cauc - Caucasian Population Figure 5.27. Box and whisker plot of frontal angle (NBA) for pooled sex data. Populations are in order of increasing median. * denotes sample size n < 5.

Population Key

90.00 NA - Native America Sib - Siberia Mon - Mongolia * Ain - Ainu 85.00 Kor - Korea **Jap - Japan

) S.Chi - South China .

g N.Chi - North China e 80.00 * Bur - Burma

Lao - Laos A (d

B Viet - Vietnam

N Thai - Thailand 75.00 Cam - Cambodia Phi - Philippines And - Andaman Is. Nic - Nicobar Is. 70.00 Bor - Borneo Indo - Indonesia Mel - Melanesia

S A A Mo C A N P S C Me B N N T J Mi A B L I V K

n Mic - Micronesia

a a

h

i f i a u A h . a u . i n o i o

d

b n C c e

C

p c o

a

s i r d r r

u m

n l o t Aus - Australia

h h i

c

i i Af - Africa Cauc - Caucasian Population Figure 5.28. Box and whisker plot of frontal angle (NBA) for male-only data. Populations are in order of increasing median. * denotes sample size n < 5.

140 Population Key

NA - Native America Sib - Siberia 85.00 Mon - Mongolia * Ain - Ainu * Kor - Korea * Jap - Japan

) S.Chi - South China . *

g N.Chi - North China e 80.00 * Bur - Burma Lao - Laos A (d *

B Viet - Vietnam

N Thai - Thailand Cam - Cambodia 75.00 Phi - Philippines And - Andaman Is. Nic - Nicobar Is. Bor - Borneo Indo - Indonesia 70.00 Mel - Melanesia

A C S Mo A N N A J B T P N K A I Me B L C V Mi S

n Mic - Micronesia

a a

h

f a i u A i i u h . o n o a i .

d

b c n e C

C

p o c

a

s r i r d r

u m

n o l t Aus - Australia

i h h

c

i i Af - Africa Cauc - Caucasian Population Figure 5.29. Box and whisker plot of frontal angle (NBA) for female-only data. Populations are in order of increasing median. * denotes sample size n < 5.

are represented by pooled sex, male-only and female-only samples, and appear to distinguish north and south East Asia. Pooled sex (fig. 5.27), male-only (fig. 5.28) and female-only (fig. 5.29) plots all display Northeast Asia (Siberia and Mongolia) as possessing a distinctly low median angle compared to the remainder of East Asia, which is indicative of a flat frontal bone. The two samples are located amongst the comparative populations in all three groups, also demonstrating low medians, and thus low frontal angles. The remaining East Asian samples exhibit moderate medians, with no groupings or separations observed among them in any of the three plots. Highly significant differences were identifies for all three samples (H: 132.2, p < 0.001; H: 93.78, p < 0.001; H: 63.62, p < 0.001; for pooled sex, male and female samples, respectively) using a Kruskal-Wallis test (Appendix 4). The second frontal angle to be discussed is the basion angle (BBA) which displays evidence of a north to south East Asian distribution in pooled sex (fig. 5.30), male-only (fig. 5.31) and female-only (fig. 5.32) plots. A high angle may be indicative of a long

141 frontal length (BNL) and/or low angle (flat frontal bone). Pooled sex, male-only and female-only plots all exhibit significant median differences (Kruskal-Wallis: H: 76.12, p < 0.001; H: 42.65, p = 0.01; H: 36.85, p < 0.05, respectively. See Appendix 4 for specific details). Northeast Asia displays the highest median angle compared to the moderate medians of the remaining East Asians in all three plots, and thus a longer frontal length. South China also demonstrates a high median in the male-only plot (fig 5.31). However, the South Chinese sample is small in the male-only plot (n = 3), and therefore should be regarded with caution. Northeast Asians tend to overlap with Australian, African and Caucasian samples, suggesting that these comparative samples also exhibit long frontal bones and/or low frontal angles.

Population Key 65.00 NA - Native America Sib - Siberia Mon - Mongolia Ain - Ainu 60.00 Kor - Korea Jap - Japan

* S.Chi - South China

) .

g N.Chi - North China

e *

d Bur - Burma

( Lao - Laos A 55.00 Viet - Vietnam

BB Thai - Thailand Cam - Cambodia Phi - Philippines 50.00 And - Andaman Is. Nic - Nicobar Is. Bor - Borneo Indo - Indonesia Mel - Melanesia

J Mi I Me K V L T B N C P N A B N S A A S C A Mo

n Mic - Micronesia

a a

h

o i o i a h . n u A . i u i a f

d

e c C n b

C

p c

o a

r r i d r s

m u

o l n t Aus - Australia

i h h

c

i i Af - Africa Cauc - Caucasian Population

Figure 5.30. Box and whisker plot of frontal angle (BBA) for pooled sex data. Populations are in order of increasing median. * denotes sample size n < 5.

142 Population Key 65.00 NA - Native America Sib - Siberia Mon - Mongolia Ain - Ainu 60.00 * Kor - Korea * Jap - Japan

) S.Chi - South China .

g N.Chi - North China e Bur - Burma (d *

Lao - Laos A 55.00 * Viet - Vietnam

BB Thai - Thailand Cam - Cambodia Phi - Philippines 50.00 And - Andaman Is. Nic - Nicobar Is. Bor - Borneo Indo - Indonesia Mel - Melanesia

J Me Mi L K T N I V B A P C N B N A C S S A Mo A

n Mic - Micronesia

a a

h

o i i o n h a A u . u a i . f i

d

c e b C n

C

p c o

a

r r d i r s

m u

l o n t Aus - Australia

i h h

c

i i Af - Africa Cauc - Caucasian Population Figure 5.31. Box and whisker plot of frontal angle (BBA) for male-only data. Populations are in order of increasing median. * denotes sample size n < 5.

Population Key

NA - Native America Sib - Siberia Mon - Mongolia 60.00 Ain - Ainu Kor - Korea Jap - Japan

) S.Chi - South China

. *

g * * N.Chi - North China e 56.00 * * Bur - Burma Lao - Laos A (d * Viet - Vietnam

BB Thai - Thailand Cam - Cambodia 52.00 Phi - Philippines And - Andaman Is. Nic - Nicobar Is. Bor - Borneo Indo - Indonesia 48.00 Mel - Melanesia

I V J Mi C B Me S K A P N N A B L N A A T S Mo C

n Mic - Micronesia

a a

h

i a o . o i h . i n u A f u i a

d

e C n c b

C

p c o

a

r r i d r s

m u

o l n t Aus - Australia

h h i

c

i i Af - Africa Cauc - Caucasian Population Figure 5.32. Box and whisker plot of frontal angle (BBA) for female-only data. Populations are in order of increasing median. * denotes sample size n < 5.

143 5.2.4 Parietal Angles Two angles of the parietal bone were measured, both of which displayed a distinction of Asian versus non-Asian populations in the pooled sex plot (figs. 5.33-4). The first of these angles, mPAA 1, measures the angle of the parietal between bregma and lambda, with a high angle indicative of a long parietal length (PAC), or flat parietal angle. This angle also shows a weak north-south cline in the male-only (fig 5.35) and female-only (fig. 5.36) plots. The second parietal angle, measured between bregma and asterion (mPAA 2), exhibits a similar distribution of samples for the pooled sex plot (fig 5.34), but displays no evidence of the aforementioned cline in male and female-only plots (not shown). This angle reflects the degree of superior parietal projection, with a low angle indicative of lateral projection of the parietals. Cranial length may also contribute to this angle; the longer the length, the higher the angle. The pooled sex result for mPAA 1 (fig. 5.33) displays near perfect separation of Australian, Pacific, African and Native American samples from East Asia, although the latter two are separated from the former three by the Nicobarese. These aforementioned samples exhibit the highest medians, and thus flatter parietals, while the East Asians possess moderate medians, the lowest of which belongs to the Andmanese. A Kruskal- Wallis test (Appendix 4) identified significant median differences (H: 126.5, p < 0.001) Results for pooled sex mPAA 2 (fig. 5.34) display similar results to mPAA 1, with Australia, Native America, Africa and Melanesia possessing the highest median angles. All East Asian populations exhibit moderate medians in comparison. The Andaman Islands sample exhibits the lowest angle. Significant median differences (H:150.7, p < 0.001) were detected with a Kruskal-Wallis test (Appendix 4). A weak Asian versus non-Asian separation is observed in both male-only (fig. 5.35) and female-only (fig. 5.36) plots for mPAA 1. The male-only plot follows a similar distribution of comparative populations to the pooled sex group above (fig. 5.33) including the presence of the Nicobar Islands in the cluster. The Ainu sample is also present with the comparative samples, but its small sample size (n = 2) makes it problematic. East Asian populations display moderate medians, with no distinctive groupings, although the Northeast Asians exhibit some of the higher East

144 Population Key

95.00 NA - Native America Sib - Siberia Mon - Mongolia Ain - Ainu 90.00 * Kor - Korea

) Jap - Japan .

g * S.Chi - South China e N.Chi - North China (d 85.00

1 Bur - Burma

A Lao - Laos

A Viet - Vietnam

P 80.00 Thai - Thailand m Cam - Cambodia Phi - Philippines And - Andaman Is. 75.00 Nic - Nicobar Is. Bor - Borneo Indo - Indonesia Mel - Melanesia

A P T I Mo L B K N C S S C A B J V N A N Mi Me A

n

a a

h

n h u o . a . i a i o i A f i u

d

C b n e c Mic - Micronesia C

o p c

a

d i r r r s

m u

o n l

t

i h h c Aus - Australia

i i Af - Africa Cauc - Caucasian Population

Figure 5.33. Box and whisker plot of parietal angle (mPAA1) for pooled sex data. Populations are in order of increasing median. * denotes sample size n < 5.

Population Key

NA - Native America 125.00 Sib - Siberia Mon - Mongolia * Ain - Ainu 120.00 * Kor - Korea

Jap - Japan

) .

g S.Chi - South China

e d N.Chi - North China ( 115.00 Bur - Burma

A2 Lao - Laos

A Viet - Vietnam

P Thai - Thailand m 110.00 Cam - Cambodia Phi - Philippines And - Andaman Is. Nic - Nicobar Is. 105.00 Bor - Borneo Indo - Indonesia Mel - Melanesia

A K P T N I L Mi V S B J C A C N B S Mo Me A N A

n

a a Mic - Micronesia h

n o h . i . u a i a i o i f A u

d

e C n c b

C

c p

a o

d r i r r s

m u

o n l

t

i h h Aus - Australia

c

i i Af - Africa Cauc - Caucasian Population

Figure 5.34. Box and whisker plot of parietal angle (mPAA2) for pooled sex data. Populations are in order of increasing median. * denotes sample size n < 5.

145 Population Key

NA - Native America Sib - Siberia * Mon - Mongolia 90.00 * * Ain - Ainu Kor - Korea

* Jap - Japan )

. S.Chi - South China g

e N.Chi - North China

(d 80.00 Bur - Burma 1 Lao - Laos

A Viet - Vietnam A

P Thai - Thailand

m Cam - Cambodia Phi - Philippines 70.00 And - Andaman Is. Nic - Nicobar Is. Bor - Borneo Indo - Indonesia Mel - Melanesia

P T I A Mo K V N B L C S C N S J B A Mi A N Me A Mic - Micronesia

n

a a

h

h n o i . u a . a A i o f i i u

d

e C b n c

C

o p c

a

i d r r r s

m u Aus - Australia

o n l

t

i h h

c

i i Af - Africa Cauc - Caucasian Population

Figure 5.35. Box and whisker plot of parietal angle (mPAA1) for male-only data. Populations are in order of increasing median. * denotes sample size n < 5.

Population Key 95.00 NA - Native America Sib - Siberia * Mon - Mongolia Ain - Ainu 90.00 Kor - Korea

* Jap - Japan ) . S.Chi - South China g *

e * N.Chi - North China d ( 85.00 Bur - Burma

* Lao - Laos A1

A * Viet - Vietnam

P Thai - Thailand

m Cam - Cambodia 80.00 Phi - Philippines And - Andaman Is. Nic - Nicobar Is. Bor - Borneo 75.00 Indo - Indonesia Mel - Melanesia

T A N I K A C L B Mo S S C A B N J N P A Me V Mi

n

a a Mic - Micronesia

h

n . o i a u . i a u o i A h f i

d

n C b c e

C

p c

a o

d r r s r i

m u

o n l t Aus - Australia i h h

c

i i Af - Africa Cauc - Caucasian Population

Figure 5.36. Box and whisker plot of parietal angle (mPAA1) for female-only data. Populations are in order of increasing median. * denotes sample size n < 5.

146 Asian median angles. Significant differences were detected (H: 75.11, p < 0.001) with a Kruskal-Wallis test (Appendix 4). Micronesia, Melanesia and Africa exhibit the highest median in the female-only group (fig 5.36), but display some overlap with Vietnam. The remaining East Asian populations possess low to moderate medians, with no obvious groupings in their distribution. A Kruskal-Wallis test (Appendix 4) found highly significant differences between samples (H: 68.87, p < 0.001).

5.3 Summary and Conclusions

Although overlap between samples was evident, as demonstrated by overlapping boxes in the B&W plots, significant separations between East Asian and non-Asian samples and northern and southern East Asian samples was apparent.

5.3.1 East Asian versus non-Asian Angles quantifying facial, frontal and parietal flatness and facial height exhibited apparent significant differences between East Asian and non-Asian samples, which were supported by Kruskal-Wallis tests (Appendix 4). The following facial flatness angles distinguish East Asia from comparative samples:  Upper facial flatness (NAA, mNFA, mf-n-zyo, ns-n-zyo)  Mid-facial flatness (mSSA, ns-n-ba, n-ns-zyo)  Lower facial flatness (NS)  Frontal flatness Frontal angles exhibiting significant separations are NBA and BBA, while parietal angle mPAA 1 displayed significant Asian/non-Asian separations for all three plots. The second parietal angle, mPAA 2, was significant for pooled sex samples. The BAA angle, quantifying facial height with respect to the cranial base, also significantly separated East Asians from non-Asians.

5.3.2 Northern versus Southern East Asians A number of angles that separate East Asian samples from comparative samples also exhibit a distinct division of Northeast Asia from all remaining East Asians. This separation occurred with angles quantifying upper and lower facial flatness:

147  ns-n-zyo  NS frontal and parietal flatness:  NBA  BBA  mPAA 1 and facial height:  BAA North-south separations on the basis of these angles were supported statistically by Kruskal-Wallis tests (Appendix 4).

148 Chapter 6 Results Univariate Analysis Part C: Indices

6.1 Introduction

Summary statistics (median, range, standard deviation and coefficient of variation values) for 23 indices for pooled sex samples are presented in Appendix 5. As observed in Chapters 4 and 5, standard deviations (SD) and coefficients of variation (CV) are virtually indistinguishable between samples, with the exception of samples exhibiting small samples sizes (n 5). These small samples continually exhibit inflated SD and CV values, even after the relevant corrections have been made (after Sokal and Braumann, 1980). A number of indices exhibit CVs that are uniformly inflated in comparison to remaining variables. The indices concerned are those that involve cranial breadth variables STB and ASB and facial breadth variables ZMB, JUB and bi-orbital breadth to quantify cranial shape. These linear variables have been found to demonstrate low to moderate heritabilities which are not significantly different to zero (Carson, 2006) and thus, the high variability of the indices involving these variables may be attributed to environmental factors (Carson, 2006). A temporal change in diet has also been suggested as a possible explanation for observed variability (Carson, 2006), as diet type (ie hard or soft) has an effect on masticatory muscle development (Corrucini et al, 1992) and thus the muscle attachments (eg zygomatic region and temporal line, thus effecting facial breadth and anterior cranial breadth variables). Not surprisingly, interorbital and nasal indices, which involve landmarks maxillofrontale (mf) and nasal breadth (al-al) exhibit the highest variability, as observed previously in Chapters 4 and 5. The high variation for these indices may also be explained by low heritability, suggesting variation may be due to large environmental influences during epigenesis (Carson, 2006). Pooled sex samples were disaggregated into sex specific samples to correct for any effects of sexual dimorphism on variation (Appendix 5). Once separated, SD and CV remain relatively similar to pooled sex samples. Large discrepancies may be

149 attributed to the differences in sample sizes or may be a reflection of the complex population histories of East Asia (Perez et al, 2007). While SD and CVs between samples are virtually indistinguishable, sample medians exhibit considerable variation. Pooled sex and male-only samples exhibit similar values, possibly indicating that the pooled sex sample is heavily influenced by the male-only samples, as the male-only samples are predominantly greater in sample size compared to female-only samples. Variables exhibiting apparent significant median differences between samples (ie. Asian versus non-Asian and/or divisions within East Asia sensu lato) were visually assessed with Box and Whisker plots (presented below), a heuristic device in which non-overlapping boxes are indicative of a significant difference at the < 1% level. Kruskal-Wallis tests (non-parametric ANOVA method) were applied to the data exhibiting apparent significant differences for statistical confirmation. Overall results of the Kruskal-Wallis tests are summarised below, while p-values of the non-parametric post-hoc tests, based on Bonferroni-corrected pairwise Mann-Whitney (Hammer et al, 2001) are presented in Appendix 6. Overall, B&W plots reveal that most samples are approximately normally distributed, with the exception of a few. Samples exhibiting skewed medians are mostly those with a sample size of n < 5. Populations with low sample numbers are herein marked accordingly (*) and should be carefully regarded, as they may not be an accurate representation of the actual population median. Samples are arranged within in each plot in order of increasing median.

6.2 Results

6.2.1 Cranial Vault Indices 6.2.1.1 Breadth-Length Index Two indices measuring the relationship between breadth and length (B/L) of the cranial vault for each population are discussed below. The first index is anterior breadth versus length (ant.B/L), which uses maximum cranial length (g-l) and anterior cranial breadth (STB), and is an original variable created specifically for the current study. The second index, length/posterior breadth (post.B/L) is adapted from Hanihara (1994) and assesses the relationship between g-l and posterior cranial breadth variable ASB. Both indices

150 suggest evidence of a separation of Asian and non-Asian samples for pooled sex, male- only and female-only samples. Figures 6.1-3 display the box plots for pooled sex, male-only and female-only plots respectively for the ant.B/L index. All three plots show Australia and Africa to possess the lowest median, or long and narrow vault. These samples are accompanied by Micronesia in pooled sex (fig 6.1) and female-only (fig 6.3) plots. However, Nicobar Islanders is found among these non-Asian samples in all three plots. There does not appear to be any groupings or separations among East Asian samples, which exhibit moderate to high median values in comparison to the aforementioned non-Asian cluster. Thus, East Asians exhibit a broader and shorter vault. Pooled sex, male-only and female-only plots all exhibit significant median differences (H: 181.3, p < 0.001; H: 114.8, p < 0.001; H: 69.88, p < 0.001, respectively) when Kruskal-Wallis tests are performed (Appendix 6).

Population Key

80.00 NA - Native America Sib - Siberia Mon - Mongolia Ain - Ainu Kor - Korea * Jap - Japan 70.00 S.Chi - South China N.Chi - North China (%) * Bur - Burma L Lao - Laos

B/ Viet - Vietnam t.

n Thai - Thailand a Cam - Cambodia 60.00 Phi - Philippines And - Andaman Is. Nic - Nicobar Is. Bor - Borneo Indo - Indonesia Mel - Melanesia

Mi A N A A C Me V B A N S N J P I Mo L S T B C K Mic - Micronesia

n

a a

h

u i f i a i o n A i . h . u a o

d

c n e b C

C

c p o

a

s r d i r r Aus - Australia

u m

l o n

t

h h i

c

i i Af - Africa Cauc - Caucasian Population Figure 6.1. Box and whisker plot of the anterior cranial index (ant.B/L) for pooled sex data. Populations are in order of increasing median. * denotes sample size n < 5.

151 Population Key 80.00 NA - Native America Sib - Siberia Mon - Mongolia Ain - Ainu Kor - Korea Jap - Japan 70.00 S.Chi - South China

* N.Chi - North China (%)

* Bur - Burma L Lao - Laos

B/ * Viet - Vietnam t.

n Thai - Thailand a * Cam - Cambodia 60.00 Phi - Philippines And - Andaman Is. Nic - Nicobar Is. Bor - Borneo Indo - Indonesia Mel - Melanesia

A N A A V Mi A Me J B N S C I N P B L Mo S T C K

n Mic - Micronesia

a a

h

u i f i i n o . i a A h u . a o

d

c n e b C

C

c p

o a

s d r i r r

u m

l o n t Aus - Australia

h h i

c

i i Af - Africa Cauc - Caucasian Population Figure 6.2. Box and whisker plot of the anterior cranial index (ant.B/L) for male-only data. Populations are in order of increasing median. * denotes sample size n < 5.

Population Key

75.00 NA - Native America Sib - Siberia Mon - Mongolia * Ain - Ainu 70.00 Kor - Korea * Jap - Japan * * S.Chi - South China N.Chi - North China

(%) * Bur - Burma L 65.00 Lao - Laos

B/ Viet - Vietnam t.

n * Thai - Thailand a 60.00 Cam - Cambodia Phi - Philippines And - Andaman Is. Nic - Nicobar Is. 55.00 Bor - Borneo Indo - Indonesia Mel - Melanesia

Mi A A K N C Me N B A V P S Mo N S B C I L J T A Mic - Micronesia n

a a

h

f u o i a A o n i h i . . u a i

d

c e b C n

C

c p

o a

s r r d i r

u m

l n o Aus - Australia

t

h h i

c

i i Af - Africa Cauc - Caucasian Population Figure 6.3. Box and whisker plot of the anterior cranial index (ant.B/L) for female-only data. Populations are in order of increasing median. * denotes sample size n < 5.

152 Similar separations are observable in the second breadth-length index, post.B/L, although the degree of separation between Asian and non-Asian populations is not as distinct as observed above in ant.B/L, as some overlap of the comparatives samples with East Asian samples is evident. However, highly significant median differences are apparent for all three plots: pooled sex (H: 113.4, p < 0.001), male-only (H: 59.91, p < 0.001) and female-only (H: 57.11, p < 0.001) using a Kruskal-Wallis test (Appendix 6). A strong separation of Australia and Melanesia from all remaining samples is apparent in pooled sex (fig. 6.4), male-only (fig. 6.5) and female-only (fig. 6.6) plots, with the two comparative populations exhibiting the lowest median value. African and Native American samples display low medians, but in all plots (pooled sex, male-only and female- only), these samples are separated from Australia and Melanesia mostly by East Asian samples. No other distinctions are observable. As above in the ant.B/L index, East Asians exhibit a broader and shorter vault in comparison to non-Asians.

Population Key 80.00 NA - Native America * Sib - Siberia Mon - Mongolia Ain - Ainu Kor - Korea 70.00 * Jap - Japan

S.Chi - South China %)

( N.Chi - North China

L Bur - Burma

B/ Lao - Laos

t. Viet - Vietnam

s 60.00

o Thai - Thailand p Cam - Cambodia Phi - Philippines And - Andaman Is. Nic - Nicobar Is. 50.00 Bor - Borneo Indo - Indonesia Mel - Melanesia

A Me J A N N A Mi S N B Mo A B C V K P S L C I T

n Mic - Micronesia

a a

h

u f A i i i . o n u a i o h . a

d

c n b e C

C

p c o

a

s r d r r i

u m

l n o t Aus - Australia

h h i

c

i i Af - Africa Cauc - Caucasian Population

Figure 6.4. Box and whisker plot of the posterior cranial index (post.B/L) for pooled sex data. Populations are in order of increasing median. * denotes sample size n < 5.

153 Population Key 80.00 NA - Native America Sib - Siberia Mon - Mongolia * Ain - Ainu * Kor - Korea 70.00 * Jap - Japan

S.Chi - South China %)

( N.Chi - North China

L Bur - Burma

B/ * Lao - Laos

t. Viet - Vietnam

s 60.00

o Thai - Thailand

p Cam - Cambodia Phi - Philippines And - Andaman Is. Nic - Nicobar Is. 50.00 Bor - Borneo Indo - Indonesia Mel - Melanesia

A Me A J A N S N N B Mo C B A Mi V P L I T S C K

n Mic - Micronesia

a a

h

u f i A i i . o a u n i h . a o

d

n b c e C

C

p c o

a

s r r d i r

u m

l n o

t Aus - Australia

h i h

c

i i Af - Africa Cauc - Caucasian Population

Figure 6.5. Box and whisker plot of the posterior cranial index (post.B/L) for male-only data. Populations are in order of increasing median. * denotes sample size n < 5.

Population Key * NA - Native America * Sib - Siberia Mon - Mongolia Ain - Ainu 70.00 Kor - Korea * Jap - Japan

* S.Chi - South China %)

( * * N.Chi - North China L Bur - Burma

B/ Lao - Laos

t. Viet - Vietnam s

o 60.00 Thai - Thailand p Cam - Cambodia Phi - Philippines And - Andaman Is. Nic - Nicobar Is. Bor - Borneo Indo - Indonesia 50.00 Mel - Melanesia

A Me N N Mi K V A S B A B J C N P L C S Mo I T A

n

a a Mic - Micronesia

h

u i A o i f . o n u a . h a i i

d

c e C b n

C

c p o

a

s r r d r i

u m

l n o t Aus - Australia h h i

c

i i Af - Africa Cauc - Caucasian Population Figure 6.6. Box and whisker plot of the posterior cranial index (post.B/L) for female-only data. Populations are in order of increasing median. * denotes sample size n < 5.

154 6.2.1.2 Height-Length Index Figures 6.7-6.9 depict box plot results for the height-length (H/L) index in pooled sex, male-only and female-only plots respectively. All three plots clearly display a separation of at least half of the comparative populations from East Asia. In the pooled sex plot (fig. 6.7), Caucasian, African and Australian samples exhibit the lowest medians, indicating that cranial height is low in relation to length. This is found also in male-only and female-only plots (figs. 6.8-6.9, respectively). The Ainu sample plots with the aforementioned comparative groups for the pooled sex and male-only plots, but should be regarded with care due to its small sample size. A weak north to south East Asian cline is observable for this index (H/L), with Northeast Asia and East Asia sensu stricto tending to exhibit lower median values compared to Southeast Asia. This is apparent in pooled sex, male-only and female-only plots. A Kruskal-Wallis test (Appendix 6) indicates highly significant differences for all three plots (H: 21.6, p < 0.001; H: 127.7, p < 0.001; H: 73.98, p < 0.001; for pooled sex, male-only and female-only, respectively).

Population Key

90.00 NA - Native America Sib - Siberia * Mon - Mongolia Ain - Ainu Kor - Korea Jap - Japan S.Chi - South China

80.00 N.Chi - North China %)

( Bur - Burma Lao - Laos /L *

Viet - Vietnam H Thai - Thailand Cam - Cambodia 70.00 Phi - Philippines And - Andaman Is. Nic - Nicobar Is. Bor - Borneo Indo - Indonesia Mel - Melanesia

C A A A Me N Mo J S N B Mi P N A S B I L V C T K

n

a a

h Mic - Micronesia

a f i u i i A o h . n . u i a o

d

n c b C e

C

p c

o a

s r i d r r

u m

l n o

t

h h i Aus - Australia

c

i i Af - Africa Cauc - Caucasian Population

Figure 6.7. Box and whisker plot of the height-length cranial index (H/L) for pooled sex data. Populations are in order of increasing median. * denotes sample size n < 5.

155 Population Key

90.00 NA - Native America Sib - Siberia * Mon - Mongolia Ain - Ainu * * Kor - Korea Jap - Japan S.Chi - South China 80.00 N.Chi - North China

%) Bur - Burma ( Lao - Laos /L Viet - Vietnam H * Thai - Thailand Cam - Cambodia 70.00 Phi - Philippines And - Andaman Is. Nic - Nicobar Is. Bor - Borneo Indo - Indonesia Mel - Melanesia

A A C A S Me N Mo N J B Mi P A N B L C V I K T S

n Mic - Micronesia

a a

h

i f a u i A i o h n . u a i o .

d

n b c e C

C

p c o

a

s r i d r r

u m

l n o

t Aus - Australia

h i h

c

i i Af - Africa Cauc - Caucasian Population

Figure 6.8. Box and whisker plot of the height-length cranial index (H/L) for male-only data. Populations are in order of increasing median. * denotes sample size n < 5.

Population Key

NA - Native America 90.00 Sib - Siberia * Mon - Mongolia * Ain - Ainu 85.00 Kor - Korea * Jap - Japan S.Chi - South China N.Chi - North China

%) * Bur - Burma ( 80.00 Lao - Laos /L * Viet - Vietnam H * Thai - Thailand 75.00 Cam - Cambodia Phi - Philippines And - Andaman Is. Nic - Nicobar Is. 70.00 Bor - Borneo Indo - Indonesia Mel - Melanesia

C A A N A J Me Mo N B S N Mi S B A I V P L C T K

n Mic - Micronesia

a a

h

a f u i i A o i . . u n i h a o

d

c n b C e

C

p c o

a

s r r d i r

u m

l n o

t Aus - Australia

h h i

c

i i Af - Africa Cauc - Caucasian Population Figure 6.9. Box and whisker plot of the height-length cranial index (H/L) for female-only data. Populations are in order of increasing median. * denotes sample size n < 5.

156 6.2.1.3 Breadth-Height Index The relationship between cranial breadth and height (BBH) was examined using two indices, the first involving anterior breadth (STB), and the second, posterior breadth (ASB). The anterior index (ant.B/H) exhibits a northern versus southern East Asian separation, and the posterior index (post.B/H) displays suggestions of both a north-south cline and an Asian versus non-Asian division. Results for pooled sex, male-only and female-only samples for ant.B/H are displayed in figs. 6.10-6.12. Northeast Asia and the Ainu are distinct from the rest of East Asia in pooled sex (fig. 6.10) and male-only (fig. 6.11) plots, while the female-only group (fig. 6.12) exhibits a clear division of Siberian and Ainu samples. The Northeast Asian samples, together with the Caucasians, exhibit the highest median values for ant.B/H, which is indicative of a broad anterior cranial breadth relative to height. Remaining East Asian samples exhibit considerable overlap with comparative groups, and display moderate to low median values (ie. narrow anterior breadth relative to height). Highly significant median differences were detected in pooled sex (H: 96.81, p < 0.001), male-only (H: 46.44, p < 0.001) and female-only (H: 60.68, p < 0.001) using a Kruskal-Wallis test (see Appendix 6).

Population Key

NA - Native America Sib - Siberia 100.00 Mon - Mongolia Ain - Ainu Kor - Korea Jap - Japan S.Chi - South China %) 90.00 * N.Chi - North China

H( Bur - Burma

Lao - Laos B/

t. Viet - Vietnam

n * Thai - Thailand a 80.00 Cam - Cambodia Phi - Philippines And - Andaman Is. Nic - Nicobar Is. 70.00 Bor - Borneo Indo - Indonesia Mel - Melanesia

J C S A Mo V N N A Mi K T I P L B A C B N S A Me

n

a a

h Mic - Micronesia

a i i i i . n o h o u a u A . f

d

b n e c C

C

c p

a o

d r i r s r

m u

o l n

t

h i h Aus - Australia

c

i i Af - Africa Cauc - Caucasian Population Figure 6.10. Box and whisker plot of the anterior breadth-height cranial index (ant.B/H) for pooled sex

data Populations are in order of increasing median * denotes sample size n <5

157 Population Key

NA - Native America Sib - Siberia 100.00 Mon - Mongolia Ain - Ainu Kor - Korea Jap - Japan S.Chi - South China 90.00 * N.Chi - North China Bur - Burma H(%) * * Lao - Laos B/ Viet - Vietnam t. *

n Thai - Thailand a 80.00 Cam - Cambodia Phi - Philippines And - Andaman Is. Nic - Nicobar Is. 70.00 Bor - Borneo Indo - Indonesia Mel - Melanesia

Mo V N I N A T B Mi L P B A C N S K J A Me S A C

n Mic - Micronesia

a a

h

i i . n u h o u a A . o f i i a

d

e c C b n

C

c p

a o

d r i r s r

m u

o l n t Aus - Australia

h i h

c

i i Af - Africa Cauc - Caucasian Population

Figure 6.11. Box and whisker plot of the anterior breadth-height cranial index (ant.B/H) for male-only data. Populations are in order of increasing median. * denotes sample size n < 5.

Population Key

NA - Native America Sib - Siberia 90.00 Mon - Mongolia Ain - Ainu * Kor - Korea * Jap - Japan 85.00 * S.Chi - South China

(%) N.Chi - North China * Bur - Burma H * Lao - Laos B/ 80.00

Viet - Vietnam t.

n Thai - Thailand a * Cam - Cambodia 75.00 Phi - Philippines And - Andaman Is. Nic - Nicobar Is. Bor - Borneo 70.00 Indo - Indonesia Mel - Melanesia

B I C S A K B Mi V A P L J N T A C A N S Me Mo N

n Mic - Micronesia

a a

h

u a i i o o i n h i u a f A . .

d

b n e c C

C

c p

o a

r r r d i s

m u

l n o t Aus - Australia

i h h

c

i i Af - Africa Cauc - Caucasian Population

Figure 6.12. Box and whisker plot of the anterior breadth-height cranial index (ant.B/H) for female- only data. Populations are in order of increasing median. * denotes sample size n < 5.

158 In the case of the male-only group, the Caucasian sample is exceeded by the South Chinese sample, which in this group is of small sample size (n = 3), and therefore unlikely to be a representative sample. All remaining samples demonstrate moderate to low post.B/H median values. The pooled sex group, along with the female-only plot (fig. 6.15) also exhibit evidence of a north-south East Asian distinction, with Northeast Asian samples clearly possessing the highest Asian medians in both groups. This separation is not observable in the male-only plot. All three plots (pooled sex, male-only and female-only) exhibit significant median differences (H: 93.45, p < 0.001; H: 61.53, p < 0.001; H: 44.85, p < 0.001, respectively). Refer to Appendix 6 for specific details.

Population Key 100.00 NA - Native America Sib - Siberia Mon - Mongolia * 90.00 Ain - Ainu Kor - Korea Jap - Japan * S.Chi - South China

(%) N.Chi - North China

H 80.00 Bur - Burma

B/ Lao - Laos .

t Viet - Vietnam s

o Thai - Thailand p Cam - Cambodia 70.00 Phi - Philippines And - Andaman Is. Nic - Nicobar Is. Bor - Borneo 60.00 Indo - Indonesia Mel - Melanesia

Me A J Mi N N K N V B S B A L P C I A T S Mo A C

n

a a

h Mic - Micronesia

u i . o A i o . u n h a f i i a

d

c e C b n

C

p c

o a

s r r r d i

m u

l o n

t

h h i Aus - Australia

c

i i Af - Africa Cauc - Caucasian Population

Figure 6.13. Box and whisker plot of the posterior breadth-height cranial index (post.B/H) for pooled sex data. Populations are in order of increasing median. * denotes sample size n < 5.

159 Population Key 100.00 NA - Native America Sib - Siberia Mon - Mongolia 90.00 Ain - Ainu * Kor - Korea * * Jap - Japan * S.Chi - South China

(%) N.Chi - North China 80.00 Bur - Burma

B/H Lao - Laos

t. Viet - Vietnam s

o Thai - Thailand p Cam - Cambodia 70.00 Phi - Philippines And - Andaman Is. Nic - Nicobar Is. Bor - Borneo 60.00 Indo - Indonesia Mel - Melanesia

Me A N N J N B B S A V L A P K I Mi T C Mo A C S

n

a a Mic - Micronesia h

u i . A u o i f i n h o a i a .

d

c b e n C

C

p c

o a

s r r d i r

m u

l o n

t

h i h Aus - Australia

c

i i Af - Africa Cauc - Caucasian Population

Figure 6.14. Box and whisker plot of the posterior breadth-height cranial index (post.B/H) for male- only data. Populations are in order of increasing median. * denotes sample size n < 5.

Population Key 100.00 NA - Native America Sib - Siberia Mon - Mongolia Ain - Ainu * Kor - Korea 90.00 Jap - Japan

* S.Chi - South China %) ( * * N.Chi - North China * Bur - Burma

Lao - Laos B/H

. Viet - Vietnam t 80.00

s * Thai - Thailand o

p Cam - Cambodia Phi - Philippines And - Andaman Is. Nic - Nicobar Is. 70.00 Bor - Borneo Indo - Indonesia Mel - Melanesia

S V K Mi A Me J N N A B B L C P N T A I Mo S C A Mic - Micronesia

n

a a

h

. i o u A i n o u a h . f i a i

d

C e c b n

C

c p

o a

r s d r r i m u Aus - Australia l o n

t

h h i

c

i i Af - Africa Cauc - Caucasian Population Figure 6.15. Box and whisker plot of the posterior breadth-height cranial index (post.B/H) for female- only data. Populations are in order of increasing median. * denotes sample size n < 5.

160 6.2.1.4 Cranial Breadth Proportion Indices describing the ratio of superior to inferior breadth of the anterior and posterior cranium reveal a distinction of Northeast Asia from remaining East Asian populations. The anterior breadth ratio involves variables STB and bipterionic breadth (sup/inf ant.B), the posterior ratio involving biparietal breadth and ASB (sup/inf post.B). The anterior breadth ratio (sup/inf ant.B) displays the East Asian north-south separation in pooled sex and male-only plots only (figs. 6.16 and 6.17). Northeast Asia and East Asia sensu stricto exhibit the lowest medians for both plots, while Southeast Asia exhibits moderate medians at the upper end of the moderate range. Comparative populations Australia, Melanesia and the Caucasians divide north and south East Asian samples in pooled sex and male-only plots. A Kruskal-Wallis test (Appendix 6) identified significant median differences in both pooled sex (H: 75.72, p < 0.001) and male-only plots (H: 59.84, p < 0.001).

Population Key

NA - Native America 110.00 Sib - Siberia Mon - Mongolia Ain - Ainu Kor - Korea

100.00 Jap - Japan %)

( S.Chi - South China

B * N.Chi - North China . *

t Bur - Burma n

a Lao - Laos

f 90.00 Viet - Vietnam in

/ Thai - Thailand p

u Cam - Cambodia s Phi - Philippines 80.00 And - Andaman Is. Nic - Nicobar Is. Bor - Borneo Indo - Indonesia Mel - Melanesia

K Mo N S J N A A Me C I V L A B B T P A Mi S N C

n Mic - Micronesia a a

h

o A i . i u a i n u o h f . i a

d

b n e C c

C

p c

o a

r s d r r i

u m

n l o t Aus - Australia

h i h

c

i i Af - Africa Cauc - Caucasian Population Figure 6.16. Box and whisker plot of the anterior cranial breadth index (sup/inf ant.B) for pooled sex data. Populations are in order of increasing median. * denotes sample size n < 5.

161 Population Key

NA - Native America 110.00 Sib - Siberia * Mon - Mongolia Ain - Ainu * Kor - Korea Jap - Japan

(%) 100.00 S.Chi - South China

B N.Chi - North China

t. * Bur - Burma n

a Lao - Laos

f *

n Viet - Vietnam i

/ 90.00 Thai - Thailand p

u Cam - Cambodia s Phi - Philippines And - Andaman Is. Nic - Nicobar Is. 80.00 Bor - Borneo Indo - Indonesia Mel - Melanesia

A Mi S C Mo K S N J N A V Me A C B L I B P T A N

n

a a h Mic - Micronesia a o i A . i i u a u o h n f i .

d

b n e c C

C

p c

o a

r s r r i d

u m

n l o

t

h i h Aus - Australia

c

i i Af - Africa Cauc - Caucasian Population

Figure 6.17. Box and whisker plot of the anterior cranial breadth index (sup/inf ant.B) for male-only data. Populations are in order of increasing median. * denotes sample size n < 5.

A similar north-south East Asian division is also apparent for the posterior breadth index (sup/inf post.B) in pooled sex (fig. 6.18), male-only (fig. 6.19) and female-only (fig. 6.20) plots. Northeast Asia is distinct from East Asia sensu stricto and Southeast Asia, exhibiting low medians. There is overlap between Northeast Asia and non-Asian samples, particularly in the pooled sex and male-only plots (figs. 6.18 and 6.19). The Andaman Islands sample consistently possesses the highest median in all three plots. All medians are greater than 100%, which is indicates that posterior cranial breadth is widest superiorly (at biparietal breadth). Significant median differences were detected for all three plots using a Kruskal-Wallis test: pooled sex (H: 122.0, p < 0.001), male-only (H: 74.36, p < 0.001) and female-only (H: 65.1, p < 0.001). Refer to Appendix 6 for further details.

162 Population Key

NA - Native America Sib - Siberia 130.00 Mon - Mongolia Ain - Ainu Kor - Korea

* Jap - Japan %)

( 120.00 S.Chi - South China

B N.Chi - North China .

t * s Bur - Burma

o Lao - Laos p

f 110.00 Viet - Vietnam in

/ Thai - Thailand

p Cam - Cambodia u s Phi - Philippines 100.00 And - Andaman Is. Nic - Nicobar Is. Bor - Borneo Indo - Indonesia 90.00 Mel - Melanesia

K I N A A S Me N Mo A S L A Mi J C V B N P B C T

n Mic - Micronesia

a a

h

o . i n i A u . f a i o i h u a

d

n b C e c

C

c p

o a

s r i r r d

u m

o l n t Aus - Australia

h i h

c

i i Af - Africa Cauc - Caucasian Population

Figure 6.18. Box and whisker plot of the posterior cranial breadth index (sup/inf post.B) for pooled sex data. Populations are in order of increasing median. * denotes sample size n < 5.

Population Key

NA - Native America 130.00 Sib - Siberia Mon - Mongolia Ain - Ainu * Kor - Korea

Jap - Japan %) 120.00 ( * * S.Chi - South China B N.Chi - North China

. * t

s Bur - Burma

o Lao - Laos p 110.00

f Viet - Vietnam in

/ Thai - Thailand

p Cam - Cambodia u

s Phi - Philippines 100.00 And - Andaman Is. Nic - Nicobar Is. Bor - Borneo Indo - Indonesia 90.00 Mel - Melanesia

Me S N Mo A C A B Mi N L J C S V P K B T N I A A

n Mic - Micronesia

a a

h

i A u a f o . a . i h o u i i n

d

b C e c n

C

c p

o a

s r i r r d

m u

l n o t Aus - Australia

h h i

c

i i Af - Africa Cauc - Caucasian Population

Figure 6.19. Box and whisker plot of the posterior cranial breadth index (sup/inf post.B) for male-only data. Populations are in order of increasing median. * denotes sample size n < 5.

163 Population Key

NA - Native America Sib - Siberia 130.00 Mon - Mongolia Ain - Ainu Kor - Korea

Jap - Japan %) ( 120.00 * S.Chi - South China

B * N.Chi - North China .

t * * *

s Bur - Burma

o * Lao - Laos p

f 110.00 Viet - Vietnam

in Thai - Thailand /

p Cam - Cambodia u

s Phi - Philippines 100.00 And - Andaman Is. Nic - Nicobar Is. Bor - Borneo Indo - Indonesia 90.00 Mel - Melanesia

S N S Mo K L V B T A A P Me N C Mi C I J B A N A

n Mic - Micronesia

a a

h

i A . o i u u f h i a a o i . n

d

b C e c n

C

c p

o a

r r s i r d

u m

n l o t Aus - Australia

h i h

c

i i Af - Africa Cauc - Caucasian Population Figure 6.20. Box and whisker plot of the posterior cranial breadth index (sup/inf post.B) for female- only data. Populations are in order of increasing median. * denotes sample size n < 5.

6.2.1.5 Frontal Length Proportion The ratio of the length of the frontal bone (FRC) to maximum cranial length (g-l) was assessed, revealing some separation of non-Asian from Asian samples. This division is observable in pooled sex, male only and female only plots (figs. 6.21-23 respectively). Highly significant median differences are apparent in all three plots (H: 165.3, p < 0.001; H: 102.2, p < 0.001; H: 64.95, p < 0.001, respectively) using a Kruskal-Wallis test (see Appendix 6). The comparative populations, excluding the Native Americans, exhibit the lowest median values, indicating that these samples possess a long vault length with respect to frontal length. Based on medians, these populations are clearly separate from East Asia, with the exception of Japanese, Ainu and Nicobarese samples, which consistently overlap with the non-Asians in all three plots. East Asian populations display moderate to high median values (thus a shorter vault length or longer frontal length), with no apparent groupings.

164 Population Key

NA - Native America Sib - Siberia 70.00 Mon - Mongolia

* Ain - Ainu (%) Kor - Korea

n Jap - Japan o

i S.Chi - South China t

r N.Chi - North China o 65.00

p Bur - Burma o

r Lao - Laos

p * Viet - Vietnam

L

l Thai - Thailand a

t Cam - Cambodia

n 60.00 Phi - Philippines o

r And - Andaman Is. F Nic - Nicobar Is. Bor - Borneo Indo - Indonesia 55.00 Mel - Melanesia

Me J A A C A N Mi B S N N I A P V Mo B T L C S K

n Mic - Micronesia

a a

h

i u a f i o i A . n h i u a . o

d

n c b e C

C

p c

a o

s r d i r r

u m

l o n t Aus - Australia

h i h

c

i i Af - Africa Cauc - Caucasian Population

Figure 6.21. Box and whisker plot of the frontal bone length proportion for pooled sex data. Populations are in order of increasing median. * denotes sample size n < 5.

Population Key

NA - Native America Sib - Siberia 70.00 * Mon - Mongolia * Ain - Ainu (%) * Kor - Korea

n Jap - Japan o

i S.Chi - South China t

r N.Chi - North China o 65.00

p Bur - Burma o

r Lao - Laos p Viet - Vietnam L *

l Thai - Thailand a

t Cam - Cambodia n

o 60.00 Phi - Philippines r And - Andaman Is. F Nic - Nicobar Is. Bor - Borneo Indo - Indonesia 55.00 Mel - Melanesia

A Me J Mi A A C N B S N N A L P Mo K B I T V C S

n

a a Mic - Micronesia h

i u f a i o i A . n h o u i a .

d

n c b e C

C

p c

o a

s r d i r r

u m

l n o

t

h i h Aus - Australia

c

i i Af - Africa Cauc - Caucasian Population Figure 6.22. Box and whisker plot of the frontal bone length proportion for male-only data. Populations are in order of increasing median. * denotes sample size n < 5.

165 Population Key 72.00 NA - Native America Sib - Siberia Mon - Mongolia Ain - Ainu

(%) * Kor - Korea

n 68.00 Jap - Japan o

i * S.Chi - South China t *

r N.Chi - North China o

p Bur - Burma

o *

r Lao - Laos

p 64.00 Viet - Vietnam L

l * Thai - Thailand a

t * Cam - Cambodia

n Phi - Philippines o

r And - Andaman Is. F Nic - Nicobar Is. 60.00 Bor - Borneo Indo - Indonesia Mel - Melanesia

Me C A A A N J Mi B N N V I A P C S B Mo T S L K

n Mic - Micronesia

a a

h

a i f u i o A . i n h a . u i o

d

n c e C b

C

p c

a o

s r d i r r

u m

l o n t Aus - Australia

h h i

c

i i Af - Africa Cauc - Caucasian Population

Figure 6.23. Box and whisker plot of the frontal bone length proportion for female-only data. Populations are in order of increasing median. * denotes sample size n < 5.

6.2.2 Facial Indices 6.2.2.1 Upper Facial Index Two of the three upper facial indices assessed in the current study display evidence of groupings. The two indices described below are very similar, with first index, upper facial 1 examining the relationship between upper facial height and zygomaxillare breadth (NPH/ZMB), and upper facial 2 describing the facial height/bijugale breadth ratio (NPH/JUB). Unsurprisingly, both indices depict similar separations between northern and southern East Asians. Figures 6.24-6.26 depict pooled sex, male-only and female-only results (respectively) for the upper facial 1 index. North to south separation, or more specifically Northeast Asia and North China versus the remainder of East Asia, is apparent in pooled sex (fig. 6.24) and male-only (fig. 6.25) plots. It is also present but weak in the female-only plot (fig. 6.26). Northeast Asia and North China tend to display the higher median values, and are often clustering with the Australians and Caucasians. Remaining East Asian populations exhibit moderate to low medians. There is considerable overlap between Asian and non-Asian populations in all three plots. All sample medians are between 50-100%, indicating that facial height is less than facial

166 breadth. The larger medians of the Northeast Asians suggest that either facial height is increasing and/or facial breadth is decreasing. All upper facial 1 plots (pooled sex, male-only and female-only) exhibit significant median differences (H: 121.4, p < 0.001; H: 81.17, p < 0.001; H: 41.1, p < 0.01, respectively) using a Kruskal-Wallis test (Appendix 6). The north-south East Asian separation follows a similar pattern for the upper facial 2 index, with Northeast Asia and North China exhibiting the highest median values. The separation is evident in pooled sex (fig. 6.27), male-only (fig. 6.28) and female-only (fig. 6.29) plots. East Asia sensu stricto and mainland Southeast Asian populations tend to possess higher medians than their island counterparts, although overlap between all remaining samples is evident. The Andaman Islands sample consistently displays the lowest median value. Significant median differences in all plots were detected for this index using a Kruskal-Wallis test (Appendix 6): pooled sex (H: 104.1, p < 0.001), male-only (H: 61.67, p < 0.001) and female-only (H: 43.46, p < 0.001).

Population Key

NA - Native America Sib - Siberia 80.00 Mon - Mongolia * Ain - Ainu * Kor - Korea

(%) Jap - Japan 1

x S.Chi - South China e N.Chi - North China

d 70.00 n

i Bur - Burma

l Lao - Laos

a i

c Viet - Vietnam a Thai - Thailand

rf Cam - Cambodia e 60.00

p Phi - Philippines

p And - Andaman Is. U Nic - Nicobar Is. Bor - Borneo 50.00 Indo - Indonesia Mel - Melanesia

Mi A A A C S B N P V Me L J T I B N N A Mo S C K

n Mic - Micronesia

a a

h

n i f a . o i h i u A . u i a o

d

n C c e b

C

c o p

a

d r i r s r

m u

l o n

t Aus - Australia

h i h

c

i i Af - Africa Cauc - Caucasian Population

Figure 6.24. Box and whisker plot of the upper facial 1 index (NPH/ZMB) for pooled sex data. Populations are in order of increasing median. * denotes sample size n < 5.

167 Population Key

NA - Native America 80.00 Sib - Siberia Mon - Mongolia Ain - Ainu

(%) Kor - Korea

1 * Jap - Japan

x e S.Chi - South China

d * N.Chi - North China

n i 70.00

Bur - Burma l

a *

i Lao - Laos

c a Viet - Vietnam

* Thai - Thailand rf

e Cam - Cambodia p

p Phi - Philippines

U 60.00 And - Andaman Is. Nic - Nicobar Is. Bor - Borneo Indo - Indonesia Mel - Melanesia

A Mi A B C A P N S L B V I T N J Me N A Mo S K C

n

a a

h

n i o a f h i . u i A . u i o a

d Mic - Micronesia

n c C e b

C

c o p

a

d r i r s r

m u

o l n

t

h i h c Aus - Australia

i i Af - Africa Cauc - Caucasian Population

Figure 6.25. Box and whisker plot of the upper facial 1 index (NPH/ZMB) for male-only data. Populations are in order of increasing median. * denotes sample size n < 5.

Population Key

* NA - Native America Sib - Siberia 80.00 Mon - Mongolia * Ain - Ainu * Kor - Korea

(%) Jap - Japan 1

x S.Chi - South China e N.Chi - North China

d 70.00 * n

i * Bur - Burma

l * Lao - Laos

a i

c Viet - Vietnam a Thai - Thailand

r f Cam - Cambodia e 60.00

p Phi - Philippines

p And - Andaman Is. U Nic - Nicobar Is. Bor - Borneo 50.00 Indo - Indonesia Mel - Melanesia

A N T S C A Mi Me B V P J I N N K A B Mo L S C A

n Mic - Micronesia

a a

h

f i . a n o i h A . o u u i a i

d

c C e b n

C

c p o

a

d r i r s r

m u

l o n

t Aus - Australia

i h h

c

i i Af - Africa Cauc - Caucasian Population

Figure 6.26. Box and whisker plot of the facial 1 index (NPH/ZMB) for female-only data. Populations are in order of increasing median. * denotes sample size n < 5.

168 Population Key

70.00 NA - Native America Sib - Siberia * Mon - Mongolia Ain - Ainu Kor - Korea

(%) *

Jap - Japan 2

x S.Chi - South China e N.Chi - North China

d 60.00 n

i Bur - Burma

l Lao - Laos

a i

c Viet - Vietnam a Thai - Thailand

rf Cam - Cambodia e

p Phi - Philippines

p And - Andaman Is. U 50.00 Nic - Nicobar Is. Bor - Borneo Indo - Indonesia Mel - Melanesia

A A A P S A Me Mi C B N V I T B J L C N N S K Mo

n Mic - Micronesia

a a

h

n u f h . i a o i i u a A . i o

d

C n c e b

C

c p o

a

d s i r r r

m u

l o n

t Aus - Australia

h i h

c

i i Af - Africa Cauc - Caucasian Population

Figure 6.27. Box and whisker plot of the upper facial 2 index (NPH/JUB) for pooled sex data. Populations are in order of increasing median. * denotes sample size n < 5.

Population Key

70.00 NA - Native America Sib - Siberia Mon - Mongolia Ain - Ainu 65.00 Kor - Korea (%) *

2 Jap - Japan

x S.Chi - South China e *

d N.Chi - North China n

i 60.00 Bur - Burma l

a Lao - Laos i

c * Viet - Vietnam

a *

Thai - Thailand r f

e 55.00 Cam - Cambodia

p Phi - Philippines p

U And - Andaman Is. Nic - Nicobar Is. 50.00 Bor - Borneo Indo - Indonesia Mel - Melanesia

A A A A Mi S P C B N I Me B L V T C J N N S K Mo

n

a a Mic - Micronesia

h

n u i f . h a o i u i a A . i o

d

n C c e b

C

c o p

a

d s i r r r

m u

o l n t Aus - Australia h i h

c

i i Af - Africa Cauc - Caucasian Population

Figure 6.28. Box and whisker plot of the upper facial 2 index (NPH/JUB) for male-only data. Populations are in order of increasing median. * denotes sample size n < 5.

169 Population Key 70.00 NA - Native America Sib - Siberia Mon - Mongolia Ain - Ainu Kor - Korea

(%) Jap - Japan 2

x S.Chi - South China

e 60.00 N.Chi - North China

d n

i Bur - Burma

l Lao - Laos

a i

c Viet - Vietnam a Thai - Thailand

rf Cam - Cambodia e

p Phi - Philippines p And - Andaman Is. U 50.00 Nic - Nicobar Is. Bor - Borneo Indo - Indonesia Mel - Melanesia

A T A Me A S N V P C Mi B I K N J B L S C N Mo A

n Mic - Micronesia

a a

h

n u f . i i h a o o A u i a . i

d

C c e b n

C

c p o

a

d s i r r r

m u

l o n

t Aus - Australia

i h h

c

i i Af - Africa Cauc - Caucasian Population

Figure 6.29. Box and whisker plot of the facial 2 index (NPH/JUB) for female-only data. Populations are in order of increasing median. * denotes sample size n < 5.

6.2.2.2 Nasal Index Separation of samples is observed in the pooled sex, male-only and female-only plots (figs 6.30-6.32, respectively) on the basis of the nasal index (al-al/n-ns), separating samples Asian and non-Asian populations. All three plots exhibit highly significant differences between samples when subjected to a Kruskal-Wallis test (H: 166.5, p < 0.001; H: 90.53, p < 0.001; H: 83.71, p < 0.001, respectively). Pooled sex, male-only and female-only plots exhibit a similar sample distribution, with the majority of comparative populations displaying the higher median values. Melanesia and Native America consistently possess the highest median, followed by Micronesia and Australia. Africa and the Caucasians tend to display moderate medians, and display some overlap with East Asia. East Asians exhibit moderate to low medians. Despite exhibiting medians of less than 50%, samples displaying the higher medians are likely to exhibit taller nasal skeletons relative to width.

170 Population Key

NA - Native America Sib - Siberia Mon - Mongolia 40.00 Ain - Ainu * Kor - Korea Jap - Japan * S.Chi - South China

(%) N.Chi - North China x

e Bur - Burma d

n Lao - Laos i

l 30.00 Viet - Vietnam a

s Thai - Thailand a

N Cam - Cambodia Phi - Philippines And - Andaman Is. Nic - Nicobar Is. Bor - Borneo 20.00 Indo - Indonesia Mel - Melanesia

N S C Mo L V B T B N I S A A P A C K J A Mi N Me

n Mic - Micronesia

a a

h

i i a i o u . . n i h f a o u A

d

c b e C n

C

p c

o a

r r d i r s

m u

n o l t Aus - Australia

i h h

c

i i Af - Africa Cauc - Caucasian Population

Figure 6.30. Box and whisker plot of the nasal index (al-al/n-ns) for pooled sex data. Populations are in order of increasing median. * denotes sample size n < 5.

Population Key

NA - Native America Sib - Siberia Mon - Mongolia 40.00 Ain - Ainu Kor - Korea * Jap - Japan * S.Chi - South China 35.00

%) N.Chi - North China (

x Bur - Burma

e Lao - Laos

d * n

i Viet - Vietnam

l 30.00 Thai - Thailand

a * s Cam - Cambodia a Phi - Philippines N And - Andaman Is. 25.00 Nic - Nicobar Is. Bor - Borneo Indo - Indonesia Mel - Melanesia 20.00 Mic - Micronesia

T N S V L C Mo I B B N P C A S K A J A Mi A Me N

n Aus - Australia

a a

h

i i i a o u . h a f . o n u i A

d

c b e C n

C

o p c

a

r r i r d s

m u

n o l t Af - Africa

i h h

c

i i Cauc - Caucasian

Population

Figure 6.31. Box and whisker plot of the nasal index (al-al/n-ns) for male-only data. Populations are in order of increasing median. * denotes sample size n < 5.

171 Population Key 45.00 NA - Native America Sib - Siberia Mon - Mongolia 40.00 Ain - Ainu Kor - Korea * * * Jap - Japan

%) S.Chi - South China

( 35.00 N.Chi - North China x

e * Bur - Burma

d * Lao - Laos in

l Viet - Vietnam a

s 30.00 Thai - Thailand

a * Cam - Cambodia N Phi - Philippines And - Andaman Is. 25.00 Nic - Nicobar Is. Bor - Borneo Indo - Indonesia Mel - Melanesia

C N B S Mo A N L B S I A V A T C P J K A Mi N Me

n Mic - Micronesia

a a

h

a i o . i . u i n i f a h o u A

d

c C n b e

C

o p c

a

r r d i r s

m u

n o l

t Aus - Australia

h h i

c

i i Af - Africa Cauc - Caucasian Population

Figure 6.32. Box and whisker plot of nasal index (al-al/n-ns) for female-only data. Populations are in order of increasing median. * denotes sample size n < 5.

6.2.3 Inferior Cranial Indices 6.2.3.1 Palate Index Pooled sex, male-only and female-only results for the palate index (enm-enm/sta-ol) are displayed below in figures 6.33-6.35, respectively. All three plots are suggestive of a division of East Asian and non-Asian samples, although there is some overlap between them. Significant differences are apparent in all three plots when a Kruskal-Wallis test is applied (H: 96.89, p < 0.001; H: 56.28, p < 0.001; H: 44.42, p < 0.001, respectively; see Appendix 6 for details). Pooled sex (fig. 6.33) and male-only (fig. 6.34) plots clearly show Australia, Melanesia and Africa possessing the lowest medians, with Micronesia exhibiting low- moderate median values. Indonesia exhibits similar median values to Micronesia, while the Andaman Islands sample consistently exhibits a median very similar to the Africans in both plots. The above observations are less obvious in the female-only plot (fig. 6.35) compared to the former two plots due to the presence of additional Asian samples (Nicobar Islands and Ainu in the non-Asian cluster described above. These East Asian samples however are of small sample size, and should be regarded with caution.

172 Disregarding these small samples, the comparative populations display the lowest median values. East Asian populations consistently display moderate medians for the palate index. Cambodia features as one of the highest median populations in all three groups. There is also a suggestion of a north to south cline, with Northeast Asia featured at the higher end of the moderate scale. All samples exhibit index medians that indicate palate lengths are greater than breadths. Those sample discussed above as exhibiting the higher medians possess a shorter length and/or greater breadth, with the smaller medians indicative of the opposite palate shape.

Population Key

NA - Native America Sib - Siberia Mon - Mongolia 110.00 Ain - Ainu * Kor - Korea Jap - Japan

100.00 S.Chi - South China %)

( N.Chi - North China x

e Bur - Burma d

n 90.00 * Lao - Laos

Viet - Vietnam

ei

t

a Thai - Thailand l

a Cam - Cambodia P 80.00 Phi - Philippines And - Andaman Is. Nic - Nicobar Is. 70.00 Bor - Borneo Indo - Indonesia Mel - Melanesia

A Me A A A Mi I N B B J T N C L V S S N P Mo C K Mic - Micronesia

n

a a

h

u f n i i u o . a i . i A h a o

d

n c e C b

C

c p

a o Aus - Australia

s d r r i r

u m

l o n

t

i h h

c

i Af - Africa i Cauc - Caucasian Population Figure 6.33. Box and whisker plot of the palate index (enm-enm/sta-ol) for pooled sex data. Populations are in order of increasing median. * denotes sample size n < 5.

173 Population Key

NA - Native America Sib - Siberia 110.00 Mon - Mongolia Ain - Ainu * * Kor - Korea * Jap - Japan

%) 100.00 S.Chi - South China (

x N.Chi - North China

e Bur - Burma d

n Lao - Laos 90.00 *

ei Viet - Vietnam

t a

l Thai - Thailand a Cam - Cambodia P 80.00 Phi - Philippines And - Andaman Is. Nic - Nicobar Is. Bor - Borneo 70.00 Indo - Indonesia Mel - Melanesia

Me A A A Mi I V N N B B C S T J L A S P Mo N C K

n Mic - Micronesia

a a

h

u n f i A i u o a . i i h . a o

d

e c C n b

C

c p

a o

s d r r i r

u m

l o n t Aus - Australia

h i h

c

i i Af - Africa Cauc - Caucasian Population Figure 6.34. Box and whisker plot of the palate index (enm-enm/sta-ol) for male-only data. Populations are in order of increasing median. * denotes sample size n < 5.

Population Key

NA - Native America 110.00 Sib - Siberia Mon - Mongolia * Ain - Ainu 100.00 Kor - Korea Jap - Japan

%) S.Chi - South China (

x * N.Chi - North China e 90.00 Bur - Burma d *

n Lao - Laos

ei * Viet - Vietnam

t a

l Thai - Thailand

a 80.00 Cam - Cambodia P * * Phi - Philippines And - Andaman Is. 70.00 Nic - Nicobar Is. Bor - Borneo Indo - Indonesia Mel - Melanesia

A N A A A Me Mi I K L B B P T J N S Mo N V S C C

n Mic - Micronesia

a a

h

u i i f n o u o h . i A i . a a

d

c n b e C

C

c p

o a

s d r r r i

u m

l o n t Aus - Australia

i h h

c

i i Af - Africa Cauc - Caucasian Population

Figure 6.35. Box and whisker plot of palate index (enm-enm/sta-ol) for female-only data. Populations are in order of increasing median. * denotes sample size n < 5.

174 6.2.4 Facial Flatness Indices 6.2.4.1 Glabellar Index The glabellar index (g-l/n-l) in the current study has been modified from an index defined by Hanihara (2000). This index assesses the degree of projection of glabella in relation to nasion. In the current study, the index appears to distinguish a number of non-Asian populations from East Asian. Figures 6.36-6.38 show the pooled sex, male-only and female-only results respectively for the glabellar index. A strong separation of Australia and Melanesia together from all other samples is evident in all three plots, the pair of samples consistently displaying high, if not the highest median values, which are consistently greater than 100%. This result indicates that these samples have a longer g-l length compared to n-l and therefore, increased projection of glabella. Micronesia exhibits a high median value also, but is separated from the former two samples by the Nicobar Islanders in all three plots (pooled sex, male-only and female-only). Northeast Asia tends to exhibit the lowest median values (ie the least amount of glabellar projection) but considerable overlap between all East Asian samples is observed in the pooled sex (fig. 6.36), male-only (fig. 6.37) and female-only (fig. 6.38) plots. Kruskal-Wallis tests indicate highly significant median differences between samples in pooled sex (H: 161.5, p < 0.001), male-only (H: 95.75, p < 0.001) and female-only (H: 84.16, p < 0.001) plots.

6.2.4.2 Gnathic Index The gnathic index (BPL/BNL) assesses facial flatness by examining the ratio of the projection nasion to prosthion. A high index is indicative of a greater projection of prosthion relative to nasion, and thus, a greater degree of progntahism. The pooled sex, male-only and female-only results (figs 6.39-6.41 respectively) are similar to those described above for the glabellar index. The pooled sex group (fig. 6.39) clearly displays Melanesia and Australia as possessing the highest median values, consistent with the male-only plot (fig. 6.40). The medians of these two csamples exceed 100%, which is indicative of greater projection of prosthion in relation to nasion (ie, prognathic). The Caucasian sample is visibly the population with the lowest median in both pooled sex and male-only plots, to the exclusion

175 Population Key

104.00 NA - Native America Sib - Siberia Mon - Mongolia Ain - Ainu Kor - Korea

%) 102.00 Jap - Japan

( S.Chi - South China x

e ** N.Chi - North China d

n Bur - Burma

ri Lao - Laos

la Viet - Vietnam l 100.00

e Thai - Thailand

b Cam - Cambodia la

G Phi - Philippines And - Andaman Is. 98.00 Nic - Nicobar Is. Bor - Borneo Indo - Indonesia Mel - Melanesia

B A A P Mo S I N C N V C B S J A L T K Mi N Me A

n Mic - Micronesia

a a

h

u n f h i . a A i a o . i o i u

d

b e C n c

C

p c

o a

r d i r r s

u m

n o l t Aus - Australia

h h i

c

i i Af - Africa Cauc - Caucasian Population

Figure 6.33. Box and whisker plot of the glabellar index (g-l/n-l) for pooled sex data. Populations are in order of increasing median. * denotes sample size n < 5.

Population Key

NA - Native America 104.00 Sib - Siberia Mon - Mongolia Ain - Ainu Kor - Korea

%) * Jap - Japan

( S.Chi - South China x 102.00

e N.Chi - North China d *

n Bur - Burma

r i * Lao - Laos a

l * Viet - Vietnam l e 100.00 Thai - Thailand

b Cam - Cambodia la

G Phi - Philippines And - Andaman Is. Nic - Nicobar Is. 98.00 Bor - Borneo Indo - Indonesia Mel - Melanesia

B S P S Mo A N I A K C B V J N L T C Mi N A Me A

n Mic - Micronesia

a a

h

u . h i n . f o a o i A a i i u

d

C b e c n

C

p c

o a

r i d r r s

u m

n o l t Aus - Australia

h h i

c

i i Af - Africa Cauc - Caucasian Population Figure 6.37. Box and whisker plot of the glabellar index (g-l-n-l) for male-only data. Populations are in order of increasing median. * denotes sample size n < 5.

176 Population Key

NA - Native America 102.00 Sib - Siberia Mon - Mongolia Ain - Ainu * Kor - Korea

%) 101.00 * Jap - Japan (

x S.Chi - South China e * N.Chi - North China d * n * Bur - Burma

ri 100.00 Lao - Laos

a l

l Viet - Vietnam

e * b Thai - Thailand

la Cam - Cambodia 99.00 G Phi - Philippines And - Andaman Is. Nic - Nicobar Is. 98.00 Bor - Borneo Indo - Indonesia Mel - Melanesia

S A I A P A Mo B T C C N N V B J L S Mi N Me K A

n

a a

h Mic - Micronesia

i n f h i u a a . A i o . i o u

d

b n e C c

C

p c

a o

d i r r r s

u m

o n l

t

i h h Aus - Australia

c

i i Af - Africa Cauc - Caucasian Population Figure 6.38. Box and whisker plot of glabellar index (g-l/n-l) for female-only data. Populations are in order of increasing median. * denotes sample size n < 5.

of Korea, which is of small sample size and therefore unlikely to accurately represent the sample median. Caucasians thus exhibit little to no prognathism (orthognathism). Pooled sex and male-only East Asians exhibit moderate medians, with no separations or groupings observable. Both plots exhibit highly significant median differences (H: 122.2, p < 0.001; H: 61.02, p < 0.001, respectively) when subjected to a Kruskal-Wallis test (Appendix 6). The female-only plot (fig. 6.41) displays a weak Asian versus non-Asian division in comparison to the pooled sex and male-only plots. Australia clearly possesses the highest median value, but is separated from Melanesia and Africa by overlapping East Asian samples (Indonesia and Nicobar Islands). The position of the Caucasian sample is consistent with the pooled sex and male-only plots (ie, low median value, and therefore orthognathic). East Asian samples continue to display moderate medians, with considerable overlap between northern and southern populations. A Kruskal-Wallis test (Appendix 6) indicates significant median differences between female-only samples for this index (H: 64.7, p < 0.001).

177 Population Key

NA - Native America Sib - Siberia 110.00 Mon - Mongolia Ain - Ainu Kor - Korea Jap - Japan %) * ( S.Chi - South China

x * N.Chi - North China e d 100.00 Bur - Burma

Lao - Laos cin

i Viet - Vietnam h

t Thai - Thailand a

n Cam - Cambodia

G Phi - Philippines And - Andaman Is. 90.00 Nic - Nicobar Is. Bor - Borneo Indo - Indonesia Mel - Melanesia

K C N B C V Mo N J S B Mi I S A A P L T A N Me A

n Mic - Micronesia

a a

h

o a . u a i A i o . i f h n i u

d

e b C n c

C

p c

o a

r r r i d s

u m

n o l t Aus - Australia

h h i

c

i i Af - Africa Cauc - Caucasian Population

Figure 6.39. Box and whisker plot of the gnathic index (BPL/BNL) for pooled sex data. Populations are in order of increasing median. * denotes sample size n < 5.

Population Key

NA - Native America 110.00 Sib - Siberia Mon - Mongolia Ain - Ainu * Kor - Korea * Jap - Japan %) *

( S.Chi - South China x

e 100.00 N.Chi - North China d Bur - Burma

Lao - Laos cin

i Viet - Vietnam

h t

a Thai - Thailand

n Cam - Cambodia G * Phi - Philippines 90.00 And - Andaman Is. Nic - Nicobar Is. Bor - Borneo Indo - Indonesia Mel - Melanesia

K C N B V J Mo N I L S B A A Mi N P T A C A S Me

n

a a Mic - Micronesia h

o a . u i A i o f n i h i a u .

d

e b c n C

C

p c

o a

r r r d i s

u m

n o l

t

h i h Aus - Australia

c

i i Af - Africa Cauc - Caucasian Population

Figure 6.40. Box and whisker plot of the gnathic index (BPL/BNL) for male-only data. Populations are in order of increasing median. * denotes sample size n < 5.

178 Population Key

NA - Native America Sib - Siberia 110.00 Mon - Mongolia * Ain - Ainu Kor - Korea

Jap - Japan %)

( S.Chi - South China

x * N.Chi - North China e

d Bur - Burma 100.00 ** Lao - Laos cin * i Viet - Vietnam

h *

t Thai - Thailand a

n Cam - Cambodia

G Phi - Philippines And - Andaman Is. Nic - Nicobar Is. 90.00 Bor - Borneo Indo - Indonesia Mel - Melanesia

K C B C P N V Mo N B J Mi S S A T L A Me A I N A

n Mic - Micronesia

a a

h

o a u a h . i A o i . i f n i u

d

e b C n c

C

p c

a o

r r i r d s

u m

n l o t Aus - Australia

h h i

c

i i Af - Africa Cauc - Caucasian Population

Figure 6.41. Box and whisker plot of gnathic index (BPL/BNL) for female-only data. Populations are in order of increasing median. * denotes sample size n < 5.

6.3 Summary and Conclusion

In sum, there is considerable overlap between all populations, yet distinction and groupings of Asian versus non-Asians and within East Asia sensu lato are evident.

6.3.1 East Asian versus non-Asian Indices separating East Asians from non-Asians describe the former samples as exhibiting broader vault breadth, shorter vault length, taller vault height and flat faces. A shorter frontal length relative to vault length, broad and short nasal bones longer, narrower palates also discriminate Asians from non-Asians. Specifically, the indices that significantly distinguish East Asians from non-Asians, supported by Kruskal-Wallis tests, are:  ant.B/L  post.B/L  H/L  Glabellar Index

179  Gnathic Index  Frontal Length Proportion  Nasal Index  Palate Index

6.3.2 Northern versus Southern East Asians Northern and southern East Asian distinctions were apparent predominantly for cranial indices. Upper facial indices also exhibited north-south East Asian divisions. More specifically, the following indices distinguished northern from southern samples:  H/L  ant.B/H  post.B/H  superior vs inferior cranial breadth (anteriorly and posteriorly)  Upper Facial Index (1, 2) North-south divisions on the basis of these variables are statistically significant (Kruskal-Wallis; see Appendix 6).

180 Chapter 7 Results Multivariate Results: Principal Components Analysis

7.1 Introduction

To assess the relationships of contemporary East Asian and non-Asian (comparative) populations, and in an attempt to define the East Asian cranial morphology, 44 linear variables and 18 angles were subjected to Principal Components Analysis (PCA) and the object scores plotted so as to identify separations (ie Asian vs non-Asian; northern vs southern East Asia). Variable loadings were then examined to identify variables responsible for the observed separations. Linear and angular results were analysed separately, assessing relationships in pooled sex, male-only and female-only samples.

7.2 Results

7.2.1 Linear Variables 7.2.1.1 Pooled Sex Table 7.1 summarises the results of PCA of 44 variables and 23 objects for pooled sex. Results are for log-transformed and Mosimann shape (size corrected) sample medians. For the log-transformed data, 86% of total variation is explained by the first 6 PCs, with 100% of variation occurring around PC 22. Size corrected data also explains 100% of the variance by PC 22, with PCs 1-6 accounting for 83.5%. The two highest ranking variable loadings are also provided (a complete table of all variables loadings is provided in Appendix 7). Initially, all 45 linear variables in the study were to be subjected to multivariate analysis. However, the measurement mastoidale-obelion (ms-ob) was removed from the analysis due to a substantial number of individuals (crania) missing the landmark obelion. Object scores generated for the first 6 principal components for both log- transformed and Mosimann variables were used to generate scatter (bivariate) plots, in

181 Table 7.1. Eigenvalues, variance and the two highest variable loadings for the first 6 axes of principal components analysis of Ln-transformed and size-corrected pooled sex analyses (44 variables and 23 objects).

Eigenvalue % variance Cumulative % Variable 1 Variable 2 Ln-transformed PC 1 0.024 36.7 36.7 pr-ns: 0.534 NPH: 0.269 PC 2 0.011 17.3 54.1 IML: -0.382 sta-ol: -0.342 PC 3 0.008 11.7 65.8 pr-ns: 0.623 ms-po: -0.326 PC 4 0.007 10.2 76.01 al-al: -0.585 mf-mf: 0.441 PC5 0.004 5.8 81.8 al-al: -0.485 mf-mf: -0.466 PC6 0.003 7 86.0 mf-mf: -0.400 ms-po: 0.368

Size corrected PC 1 0.020 43.1 43.1 g-l: 0.489 PAC: 0.415 PC 2 0.007 15.8 58.9 Bipterion: -0.399 Biporion: -0.335 PC 3 0.005 10.9 69.9 Biporion: -0.429 BBH: -0.410 PC 4 0.003 6.5 76.4 STB: 0.538 BBH: -0.413 PC5 0.002 3.9 80.2 ZMB: 0.464 pr-g: 0.333 PC6 0.002 3.3 83.5 pr-g: 0.500 Bi-supzyg: -0.372

order to assess phenetic groupings or separations. The reason for using only the first 6 axes is that the majority of the variation is explained by these components: most publishes anthropological studies present only the first two or three axes (e.g Curnoe, 2006). A plot of object scores for PC 1 and PC 2 from the log-transformed analysis (figure 7.1) shows strong separation of the Andaman Islanders from the remaining samples along the main axis (PC 1) which accounts for about 37% of total variance. Scores along PC 1 are positive, which suggests that variation is determined mostly by size (Jolicoeur and Mossiman, 1960). There is a suggestion of an East Asian north-south cline, with Northeast Asia, Native America and the northern East Asian populations exhibiting the highest scores in the main axis, while Southeast Asians display moderate scores. The two highest variable loadings (table 7.1) are for the facial height variables NPH and pr-ns which exhibit moderate to low loadings (0.534 and 0.269 respectively). Separation between comparative and East Asian samples is observed along the orthogonal (PC 2) and accounts for approximately 17% of total variance in these data.

182 The lowest object score is displayed by the Australian sample, which along with the Melanesia and Africa, displays the greatest separation from the East Asians, possessing the highest object scores. Caucasians, Micronesians and the Native Americans are also distinct from the East Asians, displaying moderately low object scores. Variable loadings indicate that PC 2 is influenced most by inferior malar length (IML) and palate length (sta-ol), with low loadings (-0.382 and -0.342 respectively). T-tests of the mean difference between northern and southern East Asian object scores on PC 1, and East Asian and the non-Asian samples on PC 2 are highly significant (p < 0.01 and p < 0.001, respectively). Similar separations are seen when object scores for PC 1 and PC 2 from the Mosimann shape analysis are plotted (fig 7.2). Australian, African and Melanesian samples are again separate from the majority of the East Asian samples along PC 1 (43.1% total variance) and with the highest object scores. However, they overlap with the Ainu and Nicobar Island samples along this axis. The remaining comparative samples display moderate to high object scores, overlapping with island Southeast Asians. East Asian samples show substantial overlap, displaying the lowest object scores along PC 1. The variable loadings generated from this analysis indicate separation along PC 1 is determined mostly by cranial length with moderate influences from variables g-l (0.489) and PAC (0.415). The Australian sample is also separated from the main body of East Asians along PC 2, displaying the highest object score. The lowest object score is for the Caucasian sample, which has also “pulled away” from the East Asians (with the exception of the Korean sample). Variable loadings indicate cranial breadth as the strongest influence for PC 2, with moderate to low contributions from bipterionic and biparietal breadths (-0.399 and-0.335 respectively). Mean difference in object scores between East Asian and all non-Asian sample averages is significant on PC 1 (p < 0.05), and is only significant on PC 2 when the Caucasian sample is not included (p < 0.01), when object scores are tested using Student’s t-test. A plot of object scores for PC 3 and PC 4 for the log-transformed data shows considerable overlap both within East Asia, and between East Asians and the non-Asian samples. Thus, with no distinct groupings or separations observed, this plot is not included here.

183 -2.9 Population Key PC 2 Thai -2.95 NA - Native America Cam Mon Kor Sib - Siberia Mon - Mongolia -3 Bur Ain - Ainu Lao Kor - Korea -3.05 Phi Indo Jap - Japan Viet N.Chi Bor Jap S.Chi - South China S.Chi Sib -3.1 And Nic N.Chi - North China Cauc Bur - Burma -3.15 Lao - Laos Mic Viet - Vietnam Ain NA Thai - Thailand -3.2 Cam - Cambodia Phi - Philippines -3.25 Mel And - Andaman Is. Af Nic - Nicobar Is. -3.3 Bor - Borneo Indo - Indonesia Mel - Melanesia -3.35 Aus Mic - Micronesia PC 1 Aus - Australia -3.4 Af - Africa 21.8 21.9 22 22.1 22.2 22.3 22.4 22.5 22.6 22.7 Cauc - Caucasian

Figure 7.1. Scatterplot of object scores for PC1 and PC2 from principal components of 44 variables and 23 objects. Scores calculated from Ln-transformed pooled sex data. Closed triangles, East Asians; Open squares, comparative populations.

-3.45 Population Key PC 2 -3.5 Aus NA - Native America Sib - Siberia S.Chi Mon - Mongolia -3.55 Af Ain - Ainu Mel Kor - Korea -3.6 Sib NA Jap - Japan Cam S.Chi - South China N.Chi - North China Lao Mic -3.65 Bur - Burma Mon N.Chi Phi Lao - Laos Viet - Vietnam -3.7 Thai Indo Nic Viet Jap Thai - Thailand And Cam - Cambodia -3.75 Bur Bor Ain Phi - Philippines And - Andaman Is. -3.8 Nic - Nicobar Is. Bor - Borneo Kor Cauc Indo - Indonesia -3.85 Mel - Melanesia Mic - Micronesia PC 1 -3.9 Aus - Australia Af - Africa 1 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 Cauc - Caucasian

Figure 7.2. Scatterplot of object scores for PC1 and PC2 from principal components of 44 variables and 23 objects. Scores calculated from the pooled sex Mosimann shape variables. Closed triangles, East Asians; Open squares, comparative populations.

184 Figure 7.3 plots PC 3 (10.9%) and PC 4 (6.5%) for the size corrected data. The mean difference between object scores for northern and southern East Asians is highly significant (p < 0.001) on PC 3. Southeast Asians exhibit the most negative object scores. Comparative groups show substantial overlap with the East Asians on this axis. The two highest variable loadings for PC 3 are cranial breadth and the height variables biparietal breadth (-0.429) and BBH (-0.410). There is considerable (but incomplete) overlap between East Asia and the comparative samples on PC 4. Caucasian and African samples are distinct with high PC scores, while Melanesia displays the lowest score. Northeast Asia, along with the Andaman Islands and South China samples display slightly higher scores compared to the remaining East Asians, positioning between the latter group and the Africans. North China and Korea plot close to Melanesia, separate from the main cluster of East Asians. The largest variable loadings for PC 4 are again cranial height (BBH) and breadth (STB), but unlike PC 3, the breadth variable is anterior, and contrasts with the height variable: BBH (-0.410) and STB (0.538).

Population Key Cauc PC 4 NA - Native America Sib - Siberia 0.205 Af Mon - Mongolia Ain - Ainu And S.Chi Sib Kor - Korea Jap - Japan 0.155 S.Chi - South China N.Chi - North China Bur - Burma Mon Phi Lao - Laos Indo Lao Bor Ain Viet - Vietnam 0.105 Mic Thai - Thailand Bur Aus Viet Cam - Cambodia Thai Cam Phi - Philippines Jap NA And - Andaman Is. Nic Nic - Nicobar Is. 0.055 Bor - Borneo Indo - Indonesia N.Chi Mel - Melanesia Kor Mic - Micronesia Mel PC 3 Aus - Australia 0.005 Af - Africa -0.9 -0.85 -0.8 -0.75 -0.7 -0.65 -0.6 -0.55 Cauc - Caucasian

Figure 7.3. Scatterplot of object scores for PC3 and PC4 from principal components of 44 variables and 23 objects. Scores calculated from the pooled sex Mosimann shape variables. Closed triangles, East Asians; Open squares, comparative populations.

185 Scatter plots for PC 5 versus PC 6 for both log-transformed and size corrected data showed substantial overlap between all groups, with no distinct groupings or separations (not shown). Median values have been used to minimise skewness in the data due to small sample sizes, as the possibility that small samples may still affect the distribution of the populations during the analysis needed to be explored. Thus, populations of n < 5 were removed from analyses and PCA repeated. For the pooled sex dataset, this involved the removal of Korea and the Ainu. Complete results of newly calculated variable loadings are located in the appendices (Appendix 8). Removing the Korean and Ainu samples from the pooled sex log-transformed and Mosimann shape data had little to no impact on the distribution of the remaining populations for the plots of PCs 1-6 (not shown). Differences observed were mostly in the degree of separation between samples, but not in the sample relationships as previously described. There were also minor changes in the variable loading rankings, but even these results were largely unaltered (see Appendix 8). The relationship of the Andaman Islands sample to the remaining East Asians in the plot of log-transformed PC 1 versus PC 2 was also explored by removing the sample and repeating the PCA. The north-south cline, and the separation of East Asia and the comparative samples did not appear to be affected by the removal of this sample. The highest ranked variable loadings for each axis also did not change (not shown).

7.2.1.2 Male-Only A summary of the results of PCA of 44 variables and 23 male samples is provided in table 7.3. Results are given for the first six PCs for both log-transformed and size corrected data, which explain approximately 84% of total variance for both sets. Total variance (100%) for both log-transformed and size corrected data is explained in approximately 22 PCs. The two variables with the highest loadings for each test for PCs 1-6 are also provided, with complete variable loading tables given in the appendix (Appendix 9). A scatterplot of PC scores for log-transformed PC 1 versus 2 is shown below (fig 7.4). Scores on PC 1, which explain approximately 37% of total variation, are positive,

186 Table 7.2. Eigenvalues, variance and the two highest variable loadings for the first 6 axes of principal components analysis of Ln-transformed and size-corrected male-only analyses (44 variables and 23 objects). Eigenvalue % variance Cumulative % Variable 1 Variable 2 Ln-transformed PC 1 0.027 37.3 37.3 pr-ns: 0.513 NPH: 0.273 PC 2 0.014 18.6 55.8 IML: -0.505 mf-mf: -0.480 PC 3 0.008 10.6 66.5 pr-ns: 0.608 sphba-sta: -0.342 PC 4 0.006 8.5 75.0 al-al: -0.686 mf-mf: 0.264 PC5 0.004 5.1 80.1 mf-mf: -0.529 STB: -0.289 PC6 0.003 3.9 84.0 al-al: 0.381 g-l: -0.298

Size corrected PC 1 0.019 34.4 34.4 g-l: 0.557 n-l: 0.346 PC 2 0.011 19.8 57 Biparietal: -0.499 Bipterion: -0.346 PC 3 0.006 10.7 64.9 BBH: -0.359 g-l: 0.315 PC 4 0.004 7.8 72.7 PAC: 0.487 BBH: -0.384 PC5 0.003 6.3 79.0 n-l: -0.558 BPL: 0.335 PC6 0.002 4.6 83.6 STB: -0.380 pr-b : 0.362

suggesting size is most likely determining variation. There is a clear division of the Andaman Islands from the other East Asian populations and comparative samples on this main axis, with partial separation of the Nicobar Islands. As seen in the pooled sex analysis, there is a suggestion of a north-south cline, with the remaining East and Southeast Asian samples clustering together with moderate scores, and Northeast Asians and the Native Americans possessing the highest scores. The observed north to south pattern of the East Asians is significant when average differences of object scores are tested using t-tests (p < 0.01). This axis is influenced moderately by lower facial height (pr-ns), with a loading of 0.513, and to some extent by total facial height or NPH (0.273). Korea is isolated from the group on PC 2 (18.6%) with the highest object score, while non-Asian samples exhibit the lowest object scores. There is clear separation of Australia, Melanesia and Africa from East Asians, and minor separation of Micronesia. The Caucasian and Native American samples are within the ranges of the East Asians along PC 2. Average differences of object scores for Asian and non-Asian samples are highly significant (p < 0.001). Variable loadings

187 indicate that the two highest ranking variables influencing PC 2 are inferior malar length (IML) and interorbital breadth (mf-mf). Plots of object scores for log-transformed PCs 3-6 displayed substantial overlap between all samples, with no clear separations observed (not shown). Size corrected PC 1 versus PC 2 (fig 7.5) explains approximately 54% of total variance across both axes. Australia, Africa and Melanesia are located to the right of the main axis (PC 1), with the highest positive scores, however, Nicobar and the Ainu are within their range. The East Asian populations, which exhibit considerable overlap, are situated to the left of PC 1 with low to moderate object scores, while the remaining comparative groups are positioned between the aforementioned clusters. Mean difference in object scores between Asian and non-Asian samples is significant (p < 0.01). Cranial length variables g-l and n-l are the strongest contributors on this axis (0.557 and 0.346 respectively). Comparative populations, with the exception of the Caucasian sample, are separated from all East Asian populations along PC 2, except Northeast Asians, South China and Cambodia, with high PC scores. Nonetheless, a t-test shows the average difference to be significant (p < 0.01). The Caucasian sample has a low score and is within the Southeast Asian range. Siberia is isolated from the East Asian group with a high object score, while Korea, Ainu and the Andaman Islands clearly possess the lowest object scores. Anterior and posterior cranial breadth variables have the greatest influence on PC 2, scoring -0.346 and -0.499 respectively. Figure 7.6 plots size corrected PC 3 (10.7%) versus PC 4 (7.8%). A clear north-south distribution of the East Asian populations from right to left on PC 3 can be observed. Caucasians are located to the outside of the northern cluster with the highest object score, while the Native Americans are located within the cluster. Separating the north from the south are the remaining comparative groups. Cranial height and length variables are responsible for the observed groupings above, however, the loadings are low (-0.359 and 0.315 respectively). There is a large degree of overlap observed on PC 4 between all samples. Northeast Asia is marginally separated from the remaining East Asian populations. Parietal length (0.487), opposed by cranial height (-0.384), is the variable with the greatest influence on PC 4.

188 -5 Population Key PC 2 NA - Native America Kor -5.1 Sib - Siberia Mon - Mongolia Ain - Ainu Mon Kor - Korea -5.2 Bur Jap - Japan Nic Thai Jap S.Chi - South China N.Chi And Phi Lao N.Chi - North China -5.3 Bor Indo Ain Bur - Burma Cauc Viet Lao - Laos Cam NA Sib Viet - Vietnam Thai - Thailand -5.4 S.Chi Mic Cam - Cambodia Phi - Philippines -5.5 And - Andaman Is. Mel Nic - Nicobar Is. Af Bor - Borneo Indo - Indonesia -5.6 Aus Mel - Melanesia Mic - Micronesia PC 1 Aus - Australia -5.7 Af - Africa 21.6 21.7 21.8 21.9 22 22.1 22.2 22.3 22.4 22.5 22.6 Cauc - Caucasian

Figure 7.4. Scatterplot of object scores for PC1 and PC2 from principal components of 44 variables and 23 objects. Scores calculated from Ln-transformed male-only data. Closed triangles, East Asians; Open squares, comparative populations.

-2.75 Population Key PC 2

-2.8 Sib NA - Native America Aus Sib - Siberia Mel Mon - Mongolia -2.85 Ain - Ainu NA Kor - Korea Jap - Japan -2.9 S.Chi Cam Mic Af S.Chi - South China Mon N.Chi - North China -2.95 Bur - Burma Thai Lao Lao - Laos N.Chi Phi Viet - Vietnam -3 Indo Bur Jap Thai - Thailand Cam - Cambodia Viet Bor Nic -3.05 Phi - Philippines And - Andaman Is. Nic - Nicobar Is. -3.1 Bor - Borneo Cauc Indo - Indonesia -3.15 And Ain Mel - Melanesia Kor Mic - Micronesia PC 1 Aus - Australia -3.2 Af - Africa 1 1.05 1.1 1.15 1.2 1.25 1.3 1.35 1.4 1.45 1.5 Cauc - Caucasian

Figure 7.5. Scatterplot of object scores for PC1 and PC2 from principal components of 44 variables and 23 objects. Scores calculated from the male-only Mosimann shape variables. Closed triangles, East Asians; Open squares, comparative populations. 189 A plot of size corrected PC 5 versus PC 6 is provided below (fig 7.7) and provides reasonable separation of Asian and non-Asian populations, as well as separation of northern and southern Asian populations. There is a suggestion of a north-south East Asian cline on PC 5 (6.3%), with the northern samples tending to display the more positive object scores. Cranial length variable n-l shows a moderately strong contribution to observed variation on PC 5 (-0.558), and is opposed by inferior length variable BPL (0.335). Accounting for 4.6% of the total variance, PC 6 is seen to separate the Caucasian, Micronesian and African samples from the East Asians, possessing more negative scores. Variation observed on PC 6 is most strongly determined by cranial breadth and height, however, the loadings are low (-0.380 and 0.362 respectively). To assess the affect of small samples on phenetic relationships, populations with a sample size n < 5 were removed from the group and the PCA performed again. For the male-only dataset, this involved the removal of Korea, the Ainu, South China and Cambodia. The spread of all populations in the log-transformed PC 1 versus PC 2 plot (not shown) shows little change with the removal of small samples, the most notable difference being a slight increase in the distance between non-Asian and Asian samples. The two variables with the highest loadings for each are unchanged from the original analysis. New loading values are available in Appendix 10. Plots generated for log-transformed PCs 3-6 displayed substantial overlap between all samples, with no discernable groupings (not shown). The plot of object scores of PC 1 versus PC 2 for the Mosimann shape data also remains largely unchanged when small samples are excluded (not shown). Little change has occurred to the positioning of the each sample, the most notable difference being the movement of the African sample closer to the Nicobarese. All other associations described previously (fig 7.5) remain relatively unchanged. Variables influencing each PC remain unchanged, with the exception of PC 2, where one cranial breadth measurement, bipterionic breadth, has been replaced by another, STB (-0.436). The new loadings are given in Appendix 10.

190 0.9 Population Key PC 4 NA - Native America 0.85 S.Chi Sib - Siberia Mon - Mongolia Ain - Ainu 0.8 Ain Kor - Korea Jap - Japan S.Chi - South China 0.75 N.Chi - North China Bur - Burma 0.7 Lao - Laos Mon Viet - Vietnam Aus Sib Thai - Thailand 0.65 And Cam - Cambodia Bor Af Lao Viet Jap Phi - Philippines Cam Bur Mel Cauc And - Andaman Is. Nic 0.6 Indo Phi N.Chi Nic - Nicobar Is. Kor NA Bor - Borneo Thai Indo - Indonesia 0.55 Mic Mel - Melanesia Mic - Micronesia PC 3 Aus - Australia 0.5 Af - Africa -0.8 -0.75 -0.7 -0.65 -0.6 -0.55 -0.5 -0.45 Cauc - Caucasian

Figure 7.6. Scatterplot of object scores for PC3 and PC4 from principal components of 44 variables and 23 objects. Scores calculated from the male-only Mosimann shape variables. Closed triangles, East Asians; Open squares, comparative populations.

-1.75 Population Key PC 6 NA - Native America Sib - Siberia -1.8 Kor Mon - Mongolia Ain - Ainu Kor - Korea -1.85 Jap - Japan Aus N.Chi Cam Mel S.Chi - South China NA N.Chi - North China Nic Bur - Burma -1.9 Bur Lao - Laos S.Chi And Viet - Vietnam Viet Lao Ain Thai - Thailand Bor Sib Mon Cam - Cambodia Indo Thai -1.95 Jap Phi - Philippines Af And - Andaman Is. Phi Nic - Nicobar Is. Cauc Bor - Borneo -2 Indo - Indonesia Mic Mel - Melanesia Mic - Micronesia PC 5 Aus - Australia -2.05 Af - Africa -0.02 0.03 0.08 0.13 0.18 0.23 0.28 0.33 Cauc - Caucasian

Figure 7.7. Scatterplot of object scores for PC5 and PC6 from principal components of 44 variables and 23 objects. Scores calculated from the male-only Mosimann shape variables. Closed triangles, East Asians; Open squares, comparative populations.

191 Relationships between samples observed in the repeated analysis of size corrected PC 3 versus PC 4 remains similar to the original PCA (fig 7.6). Separation between northern and southern East Asian populations is still observable in the, although the distance between them has decreased. The clusters are no longer separated by comparative samples, which are now located within and around the East Asian clusters (not shown). Variables selecting for PC 3 are mostly unchanged, retaining cranial height (BBH), but changing cranial length (g-l) to an inferior length variable, BPL (-0.403). Variable loadings for PC 4 have changed, with the highest ranked variable now cranial height (pr-b) with a value of -0.421, followed by an opposing cranial breadth variable (STB, 0.364). The new variable loadings are provided in Appendix 10. There are no clear groupings or separations observed in the repeated analysis of size corrected PC 5 versus PC 6, either within East Asia, or between the Asian and non-Asian populations (not shown).

7.2.1.3 Female Only Table 7.5 summarises the results for the first 6 PCs from the PCA of 44 variables and 23 female-only medians (objects). Results are based on log-transformed and Mosimann median data. The two variables with the highest loadings for each PC are also provided. Approximately 80% of total variance for the female-only dataset is explained by the first 6 PCs, with 100% explained by approximately 22 PCs for both log-transformed and size corrected variables. A table of all the object scores for this analysis is provided in Appendix 11. Unlike the sample groupings and separations seen previously in the pooled sex and male-only datasets, plots of object scores for PCs 1 and 2 of both log-transformed and size- corrected female-only data show substantial overlap between all populations, with no distinctions observed (not shown). A plot of log-transformed PC 3 (12.8%) versus PC 4 (9.0%) however, displays clear separation of the East Asians from comparative populations on PC 3 (fig 7.8), where non- Asians, excluding the Caucasians, display the highest positive object scores on the main axis. The average difference is highly significant, based on a t-test (p < 0.001). The

192 Table 7.3. Eigenvalues, variance and the two highest variable loadings for the first 6 axes of principal components analysis of Ln-transformed and size-corrected female-only analyses (44 variables and 23 objects). Eigenvalue % variance Cumulative % Variable 1 Variable 2 Ln-transformed PC 1 0.028 27.8 27.8 pr-ns: 0.663 NPH: 0.274 PC 2 0.017 17.6 45.4 pr-ns: -0.426 ms-po: 0.344 PC 3 0.013 12.8 58.1 mf-mf: 0.383 al-al: 0.346 PC 4 0.009 9.0 67.2 al-al: 0.670 mf-mf: -0.509 PC5 0.006 6.1 73.3 ms-po: -0.441 mf-mf: -0.392 PC6 0.005 5.4 78.7 IML: 0.592 pr-ns: 0.306

Size corrected PC 1 0.027 38.2 38.2 g-l: 0.512 n-l: 0.421 PC 2 0.008 10.8 49.0 BBH: -0.515 pr-g: 0.414 PC 3 0.007 9.9 58.8 Biparietal: -0.599 STB: -0.425 PC 4 0.006 8.9 67.7 Bipterion: -0.428 NPH: -0.243 PC5 0.005 7.3 75.1 pr-b: -0.346 STB: 0.320 PC6 0.003 4.7 79.8 sta-ol: 0.398 BPL: 0.372

Caucasian sample is located among the Southeast Asian cluster. There is no obvious distinction between northern and southern East Asian populations, which display some overlap. Moderately low variable loadings for PC 3 indicate that interorbital breadth (0.383) and nasal breadth (0.346) are largely determining variation in this axis. There is considerable overlap between all samples on the orthogonal axis (PC4). Nasal breadth displays a high variable loading for PC 4 (0.670), followed by a moderately strong opposing influence from interorbital breadth (-0.509). Figure 7.9 is a plot of size corrected PC 3 versus PC 4 and explains 18.8% of the total variance. PC 3 (9.9%) displays the separation of Africa, Native America, Australia and Melanesia from the East Asians. The average difference between the aforementioned comparative samples and East Asia is statistically significant (p < 0.01). The Caucasian and Micronesians are located among the East Asians. There is considerable overlap among all East Asian samples along this axis. There is also no obvious separation of East Asian samples on PC 4 (8.9%). Substantial overlap is also observed between Asian and non-Asian

193 samples on this axis. Contributing the most to the variation along PC 3 are variables for posterior and anterior cranial breadth (biparietal breadth and STB respectively), which display moderate values of -0.599 and -0.425 respectively. PC 4 has moderate to low contributions from bipterionic breadth (-0.428) and facial height (NPH, -0.243). There are no apparent phenetic relationships on a plot of log-transformed PC 5 versus PC 6, with extensive overlap evident both among East Asians, and between Asian and non-Asian samples. A plot of size corrected PC 5 versus PC 6 (fig 7.10), accounting for approximately 11% of total variance, displays no groupings or separations among the East Asian populations on either axis. There is also no distinction of Asian and non-Asian populations on either axis, with the exception of the Caucasians. This sample is distinct from all other samples on the main axis (PC 5). The two highest variable loadings for PC 5 are pr-b (- 0.346) and STB (0.320), and for PC 6, sta-ol (0.398) and BPL (0.372). Due to extensive overlap, no figure is shown.

-4.1 Population Key PC 4 Kor -4.15 NA-Native America Sib-Siberia Mel Mon-Mongolia -4.2 Ain - Ainu Jap Kor - Korea -4.25 Jap - Japan S.Chi - South China Mic N.Chi - North China -4.3 N.Chi Bur - Burma Bur Phi NA Lao - Laos Indo Aus Viet - Vietnam -4.35 Ain Lao Viet Thai - Thailand Thai Sib Bor Cam - Cambodia -4.4 Cauc Phi - Philippines Mon And And - Andaman Is. Nic - Nicobar Is. -4.45 Bor - Borneo Cam S.Chi Indo - Indonesia -4.5 Af Mel - Melanesia Nic Mic - Micronesia PC 3 Aus - Australia -4.55 Af - Africa 9.29.259.39.359.49.459.59.559.69.659.7Cauc - Caucasian

A Figure 7.8. Scatterplot of object scores for PC3 and PC4 from principal components of 45 variables and 23 objects. Scores calculated from Ln-transformed female-only data. Closed triangles, East Asians; Open squares, comparative populations.

194 -2 Population Key PC 4 -2.05 NA-Native America Sib-Siberia S.Chi Mon-Mongolia -2.1 Ain - Ainu Kor - Korea -2.15 Jap - Japan N.Chi Aus S.Chi - South China Thai And -2.2 Cam Af N.Chi - North China Viet Bur - Burma Indo Lao - Laos -2.25 Jap Mel Viet - Vietnam Bur Lao Mic NA Thai - Thailand Bor -2.3 Nic Cam - Cambodia Sib Phi - Philippines -2.35 Ain Phi And - Andaman Is. Nic - Nicobar Is. Cauc Kor Bor - Borneo -2.4 Indo - Indonesia Mon Mel - Melanesia -2.45 Mic - Micronesia PC 3 Aus - Australia -2.5 Af - Africa -1.3 -1.25 -1.2 -1.15 -1.1 -1.05 -1 -0.95 -0.9 Cauc - Caucasian

Figure 7.9. Scatterplot of object scores for PC3 and PC4 from principal components of 45 variables and 23 objects. Scores calculated from the female-only Mosimann shape variables. Closed triangles, East Asians; Open squares, comparative populations.

2.25 Population Key PC 6 NA-Native America And Af Sib-Siberia Indo Mon-Mongolia 2.2 Ain - Ainu Nic Sib Lao Kor - Korea Aus Jap - Japan S.Chi - South China N.Chi - North China 2.15 Kor Phi Bur Bur - Burma NA Cam Lao - Laos Thai Bor Viet - Vietnam Mon Thai - Thailand Mel Cauc 2.1 S.Chi Cam - Cambodia Ain Phi - Philippines And - Andaman Is. Mic Nic - Nicobar Is. C 2.05 Bor - Borneo Viet Indo - Indonesia Mel - Melanesia N.Chi Jap Mic - Micronesia PC 5 Aus - Australia 2 Af - Africa 1.35 1.4 1.45 1.5 1.55 1.6 1.65 1.7 1.75 Cauc - Caucasian

Figure 7.10. Scatterplot of object scores for PC5 and PC6 from principal components of 45 variables and 23 objects. Scores calculated from the female-only Mosimann shape variables. Closed triangles, East Asians; Open squares, comparative populations.

195 Table 7.4. The two highest ranked variable loadings for Ln-transformed and Mosimann female-only samples after the exclusion of samples with n < 5. Italics represent a change of variable from the original analysis.

Variable 1 Variable 2 Ln-transformed PC 1 pr-ns: 0.533 NPH: 0.241 PC 2 pr-ns: -0.384 al-al: -0.391 PC 3 pr-ns: -0.627 al-al: 0.327 PC 4 al-al: 0.522 mf-mf: -0.600 PC5 IML: 0.336 mf-mf: -0.592 PC6 PAC: -0.388 l-o: -0.365

Size corrected PC 1 g-l: 0.496 n-l: 0.418 PC 2 OCC: -0.432 STB: -0.313 PC 3 Bipterion: 0.479 STB: 0.410 PC 4 BBH: -0.346 Biparietal: 0.396 PC5 pr-b: -0.397 BPL: -0.452 PC6 ZMB: 0.391 ASB: -0.438

Populations with a sample number n < 5 were again removed from the analysis to assess the effect of small samples on phenetic associations, and PCA performed for again. This resulted in all East Asia sensu stricto samples (North China, South China, Japan, Korea and the Ainu) and the Nicobar Islands being excluded from the repeat analysis. The removal of the small samples above resulted in a dramatic change in phenetic associations observed in the original analysis of PC 1 versus PC 2 of log-transformed data. As such, a summary of the new variable loadings are provided in table 7.4, with a table of all the new object scores available in Appendix 12. The plot of PC 1 versus PC 2 (fig 7.11) after re-analysis suggests a separation of Northeast Asia from Southeast Asia along PC 1, where the northern samples display the highest object scores. Separation is most likely due to size differences, as all object scores for this axis are positive. Average differences in object scores between Northeast and Southeast Asia are, however, not statistically significant. The Andaman Islands are clearly

196 distinct from the main body of Southeast Asians, a result observed above in both pooled sex and male-only PC 1 versus PC 2 log-transformed plots. Variables defining variation for PC 1 are unaltered from the original analysis. PC 2 clearly defines the Asian samples from all non-Asians, the mean difference being highly significant (p < 0.001) The variable pr-ns remains as one of the strongest contributors to PC 2 variance (-0.384), while height of the mastoid process has been replaced by nasal breadth (-0.391). The plot of object scores for size corrected PC 1 versus PC 2 (fig 7.12) after the removal of small samples shows clear separation of East Asians from all comparative samples along the diagonal, with the exception of the Caucasians. The average difference between the Asian and non-Asian samples is statistically significant on PC 1 only (p < 0.01). The Caucasian sample is positioned among the Southeast Asians on both axes. There is considerable overlap of northern and southern East Asian samples on both PC 1 and PC 2. Variables determining variation on PC 1 remain unchanged with the removal of the small samples, with moderate values for both (g-l, 0.496; n-l, 0.418). However, loadings for PC 2 indicate two new variables influencing variation, with moderate to low loadings from occipital length variable OCC (-0.432) and STB (-0.313). The clear distinction of Asian versus non-Asian samples in the initial female-only log-transformed plot of PC 3 versus PC 4 containing all samples (fig 7.8) is lost when populations with small sample sizes are removed and the PCA repeated (fig 7.13). The Caucasians are now isolated from East Asia and the remaining comparative samples on PC 3. Africa is also isolated from all other comparative populations and East Asia on PC 4, possessing the lowest object score. A significant average difference between East Asia and non-Asian samples (Australia, Melanesia and Micronesia) is found on PC 3 (p < 0.05). There are no groupings or separations within East Asia on either axis. Nasal breadth is retained as one of the two highest ranked variables defining PC 3 variation, albeit a small influence (0.327). Strongly opposing nasal breadth is lower facial height variable pr-ns (- 0.627). Variables that define the variance for PC 4 remain unchanged.

197 1.4 PC 2 Cam 1.3 Population Key NA-Native America Sib-Siberia 1.2 Mon-Mongolia Thai Bur - Burma Mon Lao - Laos Bur Viet Viet - Vietnam 1.1 Sib Thai - Thailand Indo Lao Cam - Cambodia Bor Phi - Philippines 1 And And - Andaman Is. Phi Bor - Borneo Mic Indo - Indonesia Cauc Af 0.9 Mel NA Mel - Melanesia Mic - Micronesia Aus - Australia 0.8 Aus Af - Africa Cauc - Caucasian

PC 1 0.7 22.2 22.3 22.4 22.5 22.6 22.7 22.8 22.9 23 23.1

Figure 7.11. Scatterplot of object scores for log-transformed PC1 and PC2 with the exclusion of East Asia sensu stricto and Nicobar Islands and a repeat analysis. Closed triangles, East Asians; Open squares, comparative populations.

-2.65 PC 2 NA Population Key -2.7 Af Lao NA-Native America Sib -2.75 Sib-Siberia Aus Mon-Mongolia Cam Bur - Burma -2.8 Lao - Laos Mon Phi Viet - Vietnam Indo Mel Viet Mic Thai - Thailand -2.85 Bur Cam - Cambodia Phi - Philippines And - Andaman Is. -2.9 Bor - Borneo Cauc Indo - Indonesia Bor Mel - Melanesia -2.95 And Mic - Micronesia Aus - Australia Af - Africa -3 Cauc - Caucasian Thai PC 1 -3.05 0.60.70.80.91 1.11.21.3

Figure 7.12. Scatterplot of object scores for size corrected PC1 and PC2, with the exclusion of East Asia sensu stricto and Nicobar Islands and a repeat analysis. Closed triangles, East Asians; Open squares, comparative populations.

198 -1.9 PC 4

-1.95 Mel Population Key

NA-Native America -2 Sib-Siberia Indo Mic Mon-Mongolia -2.05 Bur Bur - Burma Thai Sib Lao Phi Lao - Laos Mon NA Viet Viet - Vietnam -2.1 Thai - Thailand Bor Aus Cam - Cambodia Cauc Phi - Philippines -2.15 Cam And - Andaman Is. Bor - Borneo -2.2 And Indo - Indonesia Mel - Melanesia -2.25 Mic - Micronesia Aus - Australia Af Af - Africa -2.3 Cauc - Caucasian PC 3 -2.35 10.7 10.75 10.8 10.85 10.9 10.95 11 11.05 11.1 11.15 11.2

Figure 7.13. Scatterplot of object scores for log-transformed PC3 and PC4, with the exclusion of East Asia sensu stricto and Nicobar Islands and a repeat analysis. Closed triangles, East Asians; Open squares, comparative populations.

-0.6 PC 4 Population Key -0.65 And NA-Native America Indo Sib-Siberia Mon-Mongolia Aus Bur - Burma -0.7 Sib Lao - Laos Af Viet - Vietnam Lao Thai - Thailand Cauc Cam - Cambodia -0.75 Thai Phi - Philippines Bur And - Andaman Is. NA Bor - Borneo -0.8 Indo - Indonesia Bor Mel - Melanesia Mic - Micronesia Cam Mon Mel Aus - Australia -0.85 Af - Africa Viet Mic Phi Cauc - Caucasian

PC 3 -0.9 0.5 0.55 0.6 0.65 0.7 0.75 0.8 0.85 0.9 0.95

Figure 7.14. Scatterplot of object scores for size corrected PC3 and PC4 with the exclusion of East Asia sensu stricto and Nicobar Islands and a repeat analysis. Closed triangles, East Asians; Open squares, comparative populations.

199 Figure 7.14 is a plot of object scores for PC 3 versus PC 4 Mosimann shape data after the exclusion of small samples. There is a clear separation of Northeast Asia from Southeast Asia on PC 3 unobservable in the original (all object) analysis (fig 7.9). The average difference between Northeast and Southeast Asia is statistically significant (p < 0.01). The Caucasian sample is the only comparative sample distinct from East Asia, clearly separate from all other samples on PC 3, and exhibiting the highest PC 3 object score. PC 4 exhibits overlap of East Asians and comparative groups, with no separations observed. Moderate loadings indicate STB remains as an influence on PC 3 (0.479), while biparietal breadth has been replaced by bipterionic breadth (0.410). Cranial height (BBH) has a low contribution to variation on PC 4 (-0.346), and is opposed by a moderate to low loading from biparietal breadth (0.396). There are no distinct sample groupings or separation between any samples on the log-transformed PC 5 versus PC 6 plot with the exclusion of the small sampled populations (not shown).

0.4 PC 6 Population Key Af 0.35 NA-Native America Sib-Siberia Mon-Mongolia 0.3 Bur - Burma Bor Lao - Laos Viet - Vietnam Phi Cam And Thai - Thailand 0.25 Cam - Cambodia Mic Bur Phi - Philippines Indo And - Andaman Is. Cauc Sib Viet Bor - Borneo 0.2 Mon Indo - Indonesia NA Mel - Melanesia Lao Thai Mic - Micronesia Mel Aus - Australia 0.15 Af - Africa Aus Cauc - Caucasian PC 5 0.1 0.05 0.1 0.15 0.2 0.25 0.3 0.35

Figure 7.15. Scatterplot of object scores for size corrected PC5 and PC6, with the exclusion of East Asia in sensu stricto and Nicobar Islands and a repeat analysis. Filled triangles, East Asians; Open squares, comparative populations

200 Figure 7.15 shows the results of size corrected PC 5 versus PC 6 after the removal of samples with small sample sizes. There is considerable overlap observable of East Asian samples on both axes. PC 5 displays no separation of Asian and non-Asian populations. There is, however, some separation of East Asia from non-Asian samples on PC 6. The African sample, possessing the highest object score on the orthogonal axis, is clearly separated from all other populations. Melanesia and Australia are located at the opposite extreme, with the lowest PC 6 scores, and are reasonably separated from the East Asians, which display moderate scores. Cranial height variable pr-b is one of the strongest influences on the variation of PC 5, although its loading is low at -0.365. Length variable BPL is the strongest contributor to PC 5 variation, with a moderate loading of -0.452, replacing cranial breadth. Selecting for PC 6 are variables ASB (posterior cranial breadth) and facial breadth, with moderate loadings of -0.438 and 0.395 respectively.

7.2.1.4 Testing the Association of Latitude with Observed Variation Linear regression was applied to a dataset comprising the approximate latitude for each sample and their PC object scores for axes 1-6 (log-transformed and Mosimann). Table 7.5 is a summary of the significant results. Significant correlations for log-transformed PC 1 object scores in both pooled sex and male-only samples are apparent. Facial height variables (pr-ns, NPH; see table 7.1) are the strongest influencing variables in both plots, thus suggesting that alveolar height and upper facial height very with latitude. The fact that PC 1, which tends to reflect size differences, is exhibiting significant correlations with latitude, suggests that overall size differences among samples may be associated with proximity to the equator. It is well documented that among modern humans overall body size is distributed clinally, increasing in higher latitudes as part of an adaptive strategy to colder climates (e.g. Ruff, 2002). However, the majority of axes exhibiting significant correlations with latitude are those concerned predominantly with shape variation. Tables 7.1-7.3 display the variables most strongly influencing variation on the shape axes exhibiting significant correlations with latitude (table 7.5). Log-transformed shape axes (PC 2 and PC 3) are primarily influenced by interorbital breadth and inferior malar length, while the Mosimann shape

201 Table 7.5 Summary table of significant correlations of PC object scores with latitude PC 1 PC 2 PC 3 PC 4 PC 5 PC 6 Pooled Sex r :0.49 r :0.42 Ln-transformed n.s n.s n.s n.s p=0.02 p=0.05 r :0.44 r:0.57 Mosimann n.s n.s n.s n.s p=0.03 p<0.01 Male-Only r :0.46 r :0.57, Ln-transformed n.s n.s n.s n.s p=0.03 p=0.01 r :0.45 r :0.65 Mosimann n.s n.s n.s n.s p:0.03 p=0.001 Female-Only r :0.52 Ln-transformed n.s n.s n.s n.s n.s p=0.01 r : -0.49 Mosimann n.s n.s n.s n.s n.s p< 0.02

axes separate samples mostly on the basis of cranial vault shape (breadth, length and height) across all three samples (pooled sex, male-male-only and female-only).

7.2.2 Angles 7.2.2.1 Pooled sex Table 7.6 summarises the results of PCA of 18 angles and 23 sample medians (objects) of pooled sex. Results are for raw and log-transformed data. Raw angles range between 15- 150 degrees, so to account for possible scaling effects, a log-transformed dataset was created. Log-transformation of the angles puts them on the same scale, approximating a log-normal distribution and making sample variances approximately equal. For the raw data, approximately 82% of total variance is explained by the first 4 PCs, while 86.3% is explained by the same number of axes for the log-transformed data. Both sets of analyses display 100% of total variance in 18 PCs. The first 4 PCs are described below, as subsequent PCs each contribute less than 5% to the total variance of each analysis. A complete set of object scores is presented in Appendix 13.

202 Table 7.6. Eigenvalues, variance and the two highest variable loadings for the first 4 axes of principal components analysis of raw and Ln-transformed pooled sex data from (18 angles and 23 objects).

Eigenvalue % variance Cumulative % Variable 1 Variable 2 Raw PC 1 54.170 41.0 41.0 NS: -0.624 PR: 0.468 PC 2 31.035 23.5 64.6 mSSA: -0.578 ns-n-ba: 0.300 PC 3 15.012 11.4 75.9 mOCA: 0.673 mPAA2: -0.407 PC 4 8.291 6.3 82.2 n-ns-zyo: 0.387 mOCA: 0.317

Ln-transformed PC 1 0.013 40.6 40.6 mf-n-zyo: -0.565 PR: 0.375 PC 2 0.008 23.5 64.1 mf-n-zyo: -0.769 PR: -0.360 PC 3 0.005 16.4 80.6 n-ns-zyo: -0.530 PR: -500 PC 4 0.002 5.7 86.3 n-ns-zyo: -0.696 ns-n-ba: 0.359

Figures 7.16 and 7.17 illustrate the distribution of populations when PC 1 object scores are plotted against scores for PC 2 for raw and log-transformed data respectively. The East Asian populations are separated from the Caucasians along PC 1 (41%) of the raw data analysis (fig 7.16). There is also a north to south cline from high to low scores (right to left) for this PC. The average difference of this north-south division is highly significant (p < 0.001) using t-tests. Most separation occurs on PC 2 (23.5%), where East Asian populations, with the exception of the Andaman Islanders, are separated from the majority of the comparative samples. This Asian versus non-Asian division has a highly significant average difference (p < 0.001). Variable loadings for the two axes show the two highest ranked angles for PC 1 are those describing the degree of lower facial flatness and alveolar projection or prognathism (NS and PR, respectively), while mid-facial flatness angles (mSSA and ns-n-ba) are the strongest variables acting on PC 2.

203 -50 Population Key PC 2 NA-Native America Sib-Siberia -55 Mon-Mongolia Ain - Ainu Kor - Korea -60 Jap - Japan Cauc Aus S.Chi - South China N.Chi - North China Mel -65 Africa Bur - Burma And Lao - Laos Viet - Vietnam Sib -70 Thai - Thailand Cam Cam - Cambodia Mic NA Bur Mon N.Chi Phi - Philippines S.Chi Bor Jap Ain And - Andaman Is. -75 Nic - Nicobar Is. Indo Phi Viet Bor - Borneo Nic Thai Lao Indo - Indonesia -80 Mel - Melanesia Kor Mic - Micronesia PC 1 Aus - Australia -85 Af - Africa -95 -90 -85 -80 -75 -70 -65 -60 -55 Cauc - Caucasian

Figure 7.16 Scatterplot of object scores for PC1 and PC2 from principal components of 18 angles and 23 objects. Scores calculated from raw pooled sex data. Closed triangles, East Asians; Open squares, comparative populations.

-0.4 Population Key PC 2 NA - Native America -0.45 Sib - Siberia Mon - Mongolia -0.5 Ain - Ainu And Kor - Korea -0.55 Jap - Japan S.Chi - South China -0.6 S.Chi N.Chi - North China Bur - Burma Phi Lao - Laos -0.65 Nic Af Lao Kor Viet - Vietnam Bor Thai - Thailand -0.7 Indo Cam - Cambodia Mel Thai Phi - Philippines Viet Bur -0.75 Aus Cam And - Andaman Is. Mon Nic - Nicobar Is. Jap Bor - Borneo -0.8 Mic Ainu NA Sib Indo - Indonesia Mel - Melanesia N.Chi -0.85 Mic - Micronesia Cauc PC 1 Aus - Australia -0.9 Af - Africa -4.2 -4.1 -4 -3.9 -3.8 -3.7 -3.6 Cauc - Caucasian

Figure 7.17 Scatterplot of object scores for PC1 and PC2 from principal components of 18 angles and 23 objects. Scores calculated from Ln-transformed pooled sex data. Closed triangles, East Asians; Open squares, comparative populations.

204 The first two PCs for the log-transformed dataset account for approximately 64% of total variance. The plot of PC 1 versus PC 2 (fig 7.17) shows some separation of Melanesia, Australia and Micronesia from the East Asians on PC 1, with the average difference between the two groups statistically significant (p < 0.001) on both axes. Angles presenting the strongest contribution to this axis are alveolar projection angles PR (0.375) and nasion projection angle mf-n-zyo (-0.565). There is also a suggestion of a north-south cline from negative to positive scores on the orthogonal axis. Angles with the highest variable loading on PC 2 are the same as those on PC 1 (PR: -0.360; mf-n-zyo: -0.769). Scatter plots of raw and log-transformed PC scores for PC 3 versus PC 4 showed no discernable groupings within East Asia or between the East Asian and comparative populations (not shown). As above in the linear variable analysis, the effect of small sample sizes on the analysis was explored by removing populations with sample sizes n < 5 and repeating PCA. In the case of the pooled sex dataset, this meant the removal of the Korean and Ainu samples. Table 7.7 summarises changes to the variable loadings as a result of the repeated analysis, with a complete set of new variable loading presented in the Appendix (Appendix 14). There is no change to the plotting of populations in the PC 1 versus PC 2 plot after the removal of small samples (not shown) compared to those previously observed in the original PC 1 versus PC 2 plots for both raw and log-transformed data (figs 7.16-17). Previously no divisions or clusters were observed in plots of raw and log- transformed PC 3 versus PC 4. However, the removal of the two small samples has resulted in a distinct separation of East Asians from Australia, Africa and the Caucasians on PC 3, and a suggestion of a north-south pattern within East Asia, with the exception of the Andaman Islanders and South China, on PC 4 of the log-transformed data only (fig 7.18). Variables exhibiting the highest loadings for both axes are unchanged from those seen originally in table 7.5; raw: Occipital (PC 3, 4), parietal projection (PC 3) and mid-facial flatness (PC 4); log-transformed: mid-facial flatness (PC 3, 4) and prognathism (PC 3).

205 Table 7.7. The two highest ranked variable loadings for the repeated PCA of raw and Ln-transformed pooled sex data after the exclusion of samples with n < 5. Italics represent a change of variable from the original analysis. Variable 1 Variable 2 Raw PC 1 NS: -0.677 PR: 0.526 PC 2 mSSA: -0.670 mNFA: -0.367 PC 3 mOCA: -0.695 mPAA2: 0.394 PC 4 n-ns-zyo: -0.650 n-ns-ba: -0.350

Ln-transformed PC 1 mf-n-zyo: 0.449 PR: 0.523 PC 2 mf-n-zyo:- 0.863 ns-n-zyo: 0.221 PC 3 ns-n-zyo: -0.576 PR: -0.383 PC 4 n-ns-zyo: -0.576 ns-n-ba: 0.336

-2.94 PC 4 Population Key -2.96 Mel NA - Native America Mon Sib - Siberia Jap -2.98 Mon - Mongolia Sib Aus And Jap - Japan -3 N.Chi S.Chi - South China S.Chi N.Chi - North China -3.02 Bur - Burma Lao - Laos Viet - Vietnam -3.04 Af Viet Thai Cam Thai - Thailand Cam - Cambodia Cauc Mic -3.06 Phi - Philippines Nic Lao Bor And - Andaman Is. Phi -3.08 NA Nic - Nicobar Is. Bor - Borneo -3.1 Bur Indo - Indonesia Mel - Melanesia Mic - Micronesia Indo -3.12 Aus - Australia PC 3 Af - Africa -3.14 Cauc - Caucasian -2.9 -2.85 -2.8 -2.75 -2.7 -2.65 -2.6

Figure 7.18 Scatterplot of object scores for PC3 and PC4 from principal components of 18 angles and 21 objects after exclusion of Korean and Ainu samples and a repeat analysis. Scores calculated from Ln- transformed pooled sex data. Closed triangles, East Asians; Open squares, comparative populations.

206 7.2.2.2 Male-Only A summary of th e PCA results for the male-only dataset is provided in table 7.8 (a full set of variable loadings is available in Appendix 15). The highest two variable loadings are also provided. When compared to the pooled sex analysis, variables exhibiting the highest loadings are largely similar, with few dissimilarities. Prognathism and upper facial flatness variables, particularly at nasion, are still strongly present. The PCA was performed on both raw and log-transformed data. A plot of raw data object scores for PC 1 versus PC 2 shows no discernable distinctions within East Asia, and only minor separation between Asian and non-Asian samples (not shown). The log-transformed plot of PC 1 and PC 2 object scores (fig 7.19) also shows overlap within East Asia along both axes. However, there is some distinction of East Asia from Australia, Melanesia, Micronesia and the Native Americans on PC 1 and the Caucasians on PC 2. The highest variable loadings for PC 1 are for projection of nasion (upper facial flatness) with respect to the orbital and nasal bones (mf-n-zyo and ns-n-zyo), and for PC 2, prognathism and upper facial flatness (PR and mf-n-zyo).

Table 7.8. Eigenvalues, variance and variable loadings for the first 4 axes of principal components analysis of raw and Ln-transformed male-only data (18 angles and 23 objects).

Eigenvalue % variance Cumulative % Variable 1 Variable 2 Raw PC 1 75.058 43.5 43.5 NP S: -0701 R: 0.535 PC 2 39.300 22.8 66.2 mSSA: -0.577 mNFA: -0.323 PC 3 19.860 11.5 77.7 mOCA: 0.762 mPAA1: -0.310 PC 4 10.036 5.8 83.5 mSSA: 0.651 n-ns-zyo: 0.364

Ln-transf ormed PC 1 0.016 35.9 35.9 mn f-n-zyo: -0.864 s-n-zyo: -0.211 PC 2 0.013 30.4 66.3 PR: -0.554 mf-n-zyo: -0.427 PC 3 0.007 16.3 82.5 PR: -0.498 n-ns-zyo: -0.477 PC 4 0.002 5.1 87.6 n-ns-zyo: -0.491 PRA: -0.407

207 0.6 Population Key PC 2 NA - Native America Cam 0.5 Sib - Siberia Mon - Mongolia Ain - Ainu And Kor - Korea 0.4 Mel Ain S.Chi Mic Nic Jap - Japan Aus Phi Thai Bor Lao S.Chi - South China N.Chi - North China 0.3 Indo Bur - Burma Bur Af Kor Lao - Laos Viet Viet - Vietnam Jap 0.2 NA Mon Thai - Thailand Sib Cam - Cambodia Phi - Philippines N.Chi 0.1 And - Andaman Is. Nic - Nicobar Is. Bor - Borneo Indo - Indonesia 0 Cauc Mel - Melanesia Mic - Micronesia PC 1 Aus - Australia -0.1 Af - Africa -4.8 -4.7 -4.6 -4.5 -4.4 -4.3 -4.2 -4.1 Cauc - Caucasian

Figure 7.19 Scatterplot of object scores for PC1 and PC2 from principal components of 18 angles and 23 objects. Scores calculated from Ln-transformed male-only data. Closed triangles, East Asians; Open squares, comparative populations.

A plot of object scores for PC 3 and PC 4 for the raw and log-transformed data shows considerable overlap between all samples, and thereby no obvious divisions or clusters either within East Asia or between East Asia and the comparative groups are observed. The PCA for the male-only dataset was repeated upon the removal of samples with n < 5. This involved the exclusion of the aforementioned Korean and Ainu samples, as well as South China and Cambodia. Removal of these samples resulted in the appearance of sample groupings that were previously not observable. Table 7.9 summarises the two highest ranked variables after the repeated analysis, with a complete set of variable loadings available in Appendix 16. Figure 7.20 is a plot of raw object scores for PC1 and PC 2 after the removal of the small samples. Previously, where considerable overlap was observed between all samples, the current analysis shows a distinct separation of non-Asian samples from most East Asians along PC 2, with the exception of the Andaman Islands sample. There is also an

208 Table 7.9. The two highest ranked variable loadings for the repeated PCA of the raw and Ln-transformed male-only data after the exclusion of samples with n < 5. Italics represent a change of variable from the original analysis. Variable 1 Variable 2 Raw PC 1 NS: -0.721 PR: 0.571 PC 2 mSSA: -0.613 m NFA: -0.393 PC 3 mOCA: 0.730 mPAA2 : -0.342 PC 4 n-ns-zyo: -0.580 FRA: 0.410

Ln-transfor med PC 1 mf-n-zyo: -0.896 P R: 0.341 PC 2 PR: - 0.569 NS: 0.454 PC 3 ns-n-zyo: -0.563 BBA: 0.423 PC 4 n-ns-zyo: -0.527 ns-n-ba: 0.357

observable north-south cline observed on PC 1, with Southeast Asians exhibiting the more negative scores to the left of the plot, and Northeast Asians positioned slightly more to the right. The angles exhibiting the highest loadings for both PC 1 and 2 remain unchanged from the original analysis in table 7.6. There were no observable groupings or divisions in the plot of PC 3 versus PC 4 due to considerable overlap between all samples (results not shown). The plot of object scores for PC 3 and PC 4 log-transformed data (fig 7.21) showed a clear separation of the majority of comparative populations from East Asians on PC 3, with the exception of the Andaman sample. Suggestion of a north-south cline is also observable on PC 4. Lower facial projection with respect to the mid-face (n-ns-zyo), remains as one of the two highest variables contributing to PC 3 variance, with the basion angle (BBH), a measure of the slope of the frontal bone, replacing PR from the original analysis. Both angles exhibit moderate values (-0.563 and 0.423 respectively). The angle n- ns-zyo also remains as the highest ranked variable for PC 4, while the prosthion angle (PRA) from the original analysis is now replaced by ns-n-ba. The former angle exhibits a moderate loading (-0.527), while the latter angle has a low loading (0.357).

209 -45 PC 2 Population Key

-50 NA - Native America Mel Aust Sib - Siberia Mon - Mongolia Jap - Japan -55 Af N.Chi - North China And Bur - Burma Lao - Laos Cauc Viet - Vietnam -60 Mic Thai - Thailand Phi - Philippines NA Bur And - Andaman Is. Bor Sib Nic - Nicobar Is. -65 Bor - Borneo Nic Indo Thai Jap Indo - Indonesia Mel - Melanesia Phi N.Chi Mic - Micronesia -70 Lao Mon Viet Aus - Australia Af - Africa PC 1 Cauc - Caucasian -75 -105 -100 -95 -90 -85 -80 -75 -70 -65 -60

Figure 7.20 Scatterplot of object scores for PC1 and PC2 from principal components of 18 angles and 19 objects after exclusion of Korea, the Ainu, South China and Cambodia and a repeat anal ysis. Scores calculated from raw male-only data. Closed triangles, East Asians; Open squares, comparative populations.

-3.35 PC 4 Population Key Mel Sib NA - Native America -3.4 Sib - Siberia Mon - Mongolia Mon Jap - Japan Jap N.Chi - North China Af Aus N.Chi Bur - Burma -3.45 And Bor Lao - Laos Thai Viet - Vietnam Mic Nic Thai - Thailand Viet NA Lao Phi - Philippines -3.5 Phi And - Andaman Is. Cauc Nic - Nicobar Is. Bor - Borneo Indo - Indonesia Bur Mel - Melanesia -3.55 Indo Mic - Micronesia Aus - Australia Af - Africa Cauc - Caucasian PC 3 -3.6 -2.9 -2.85 -2.8 -2.75 -2.7 -2.65 -2.6

Figure 7.21 Scatterplot of object scores for PC3 and PC4 from principal compone nts of 18 angles and 19 objects after the removal of Korea, the Ainu, South China and Cambodia and a repeat a nalysis. Scores calculated from log-transformed male-only data. Closed triangles, East Asians; Open squares, comparative populations.

210 The removal of the small samples (n < 5) from the log-transformed male-only analysis (not shown) served only to increase the separation of East Asian and comparative samples for PC 1 versus PC 2 observed above in figure 7.19. However, the angles with the highest loadings were altered during the repeated analysis. Variables contributing to the variance on PC 1 are upper facial flatness angle mf-n-zyo (-0.896) with a small contribution from an angle quantifying prognathism (PR: 0.341). PC 2 highlights moderately the degree of prognathism (PR: -0.569) and lower facial flatness (NS: 0.454).

7.2.2.3 Female-Only A summary of the PCA results for the female-only dataset is provided in table 7.10. The highest two variable loadings are also provided, with the complete set of variable loading presented in Appendix 17. The PCA was performed on both raw and log- transformed data containing 18 variables and 23 objects. Approximately 81 % of the raw data variance and 88 % of the total variance of the log-transformed data is explained by the first 4 PCs, with 100 % explained by 18 PC axes for both sets of data. Subsequent PCs are not described here, as the contribution of each axis to the total variance is less than 5 %.

Table 7.10. Eigenvalues, variance and variable loadings for the first 4 axes of principal components analysis of raw and Ln-transformed female-only median data (18 angles and 23 objects). Eigenvalue % variance Cumulative % Variable 1 Variable 2 Raw PC 1 90.603 44.7 44.7 NS: -0.673 PR: 0.578 PC 2 39.128 19.3 64.0 mSSA: -0.569 n-ns-zyo: 0.417 PC 3 20.402 10.1 74.1 n-ns-zyo: 0.611 mSSA: 0.493 PC 4 13.049 6.4 80.5 mFRA: 0.633 mPAA1: -0.336

Ln-transformed PC 1 0.020 38.5 38.5 PR: 0.612 mf-n-zyo: -0.536 PC 2 0.014 25.8 67 mf-n-zyo: -0.819 PR: -0.395 PC 3 0.009 16.1 80.4 n-ns-zyo: -0.726 PR: -0.353 PC 4 0.004 7.2 87.6 n-ns-zyo: -0.505 ns-n-ba: 0.415

211 A plot of raw data object scores for PC 1 (44.7%) versus PC 2 ( fig 7.22) shows overlap between East Asian samples on both axes, but evidence of an Asian versus non- Asian separation on PC 2 (19.3%). Melanesian, Australian, African and the Caucasian samples exhibit the highest scores on PC 2, while remaining comparative groups are located within range of the East Asians, who display moderate to low PC 2 scores. The average difference between the Asian and non-Asian clusters is highly significant (p < 0.001) using a Student’s t-test. Andaman and Nicobar Islanders are located closest to the aforementioned outgroups. Variables contributing the highest influence on PC 1 are lower facial flatness angle NS (-0.673) and angle of prognathism PR (0.578). The orthogonal axis is influenced most strongly by upper and mid-facial flatness angles mSSA (-0.569) and n- ns-zyo (0.417). A plot of log-transformed object scores for PC 1 versus PC 2 shows considerable overlap on both axes both amongst East Asia, and between East Asia and comparative groups. Hence, the results are not shown here.

-60 Population Key PC 2 NA - Native America -65 Aus Sib - Siberia Mon - Mongolia Ain - Ainu Kor - Korea -70 Cauc Af Jap - Japan S.Chi - South China Mel N.Chi - North China -75 Nic And Mic Bur - Burma Lao - Laos NA Phi N.Chi Sib Viet - V ietnam -80 Ain Mon Thai - Thailand Cam - Cambodia Bur Cam Bor Jap Phi - Philippines Viet -85 Lao And - Andaman Is. Indo Nic - Nicobar Is. S.Chi Bor - Borneo Indo - Indonesia -90 Thai Kor Mel - Melanesia Mic - Micronesia PC 1 Aus - Australia -95 Af - Africa -100 -95 -90 -85-80 -75-70 -65 -60 -55 -50 Cauc - Caucasian

Figure 7.22 Scatterplot of obj ect score s for P C1 and PC2 from princi pal components of 18 angles and 2 3 objects. Scores calculated fro m raw female-o nly data. Closed trian gles, East Asians; Open squares, comparativ e populatio ns.

212 A plot of raw object scores for female-only PC 3 versus PC 4 shows no observable patterns, with considerable overlap on both axes both amongst East Asia, and between East Asia and comparative groups. Figure 7.23 is a plot of female-only log-transformed object scores for PCs 3 and 4, which together contribute to 16.5% of the total variance. Substantial overlap is observed between East Asian populations on both axes. However, a division between East Asia and comparative populations is found on PC 3 (10.1%), albeit slight. East Asian populations tend to display the less negative PC 1 object scores, while the comparative samples are located on the left of the axis with the strongest negative scores. Caucasian, African and Australian samples are distinctly isolated from all remaining samples, possessing the most extreme negative scores. This division has a significant average difference (p < 0.001). The outstanding comparative populations appear to be positioned along the border of the most negative East Asian samples, but some overlap is observed between these two groups. No other groupings or separations are observed on either axis of this plot. Variable loadings

-1.95 Population Key PC 4 NA - Native America Sib - Siberia -2 Mel Mon - Mongolia Aus Ain - Ainu Kor - Korea And S.Chi Jap - Japan -2.05 Mon S.Chi - South China N.Chi - North China Viet Bur - Burma -2.1 Jap Lao - Laos Cam Viet - Vietnam N.Chi Af Mic Thai - Thailand Sib Cam - Cambodia -2.15 Phi - Philippines Bor Lao Bur And - Andaman Is. Phi Nic - Nicobar Is. Thai Cauc Nic Ain Kor Bor - Borneo -2.2 NA Indo Indo - Indonesia Mel - Melanesia Mic - Micronesia PC 3 Aus - Australia -2.25 Af - Africa -4.4 -4.35 -4.3 -4.25 -4.2 -4.15 -4.1 -4.05 -4 Cauc - Caucasian

Figure 7.23 Scatterplot of object scores for PC3 and PC4 from principal components of 18 angles and 23 objects. Scores calculated from log-transformed female-only data. Closed triangles, East Asians; Open squares, comparative populations.

213 indicate that angles influencing PC 3 most strongly are lower facial projection angles n-ns- zyo (-0.726) and PR (-0.353). The two highest ranked angles for PC 4 are n-ns-zyo (-0.505) and facial flatness angle ns-n-ba (0.415). The PCA for the female-only dataset was repeated upon the removal of samples with n < 5, as confidence in the reliability of the medians of these small samples is low. This resulted in the exclusion of all East Asia sensu stricto and the Nicobar Islands sample from the repeat analysis. Table 7.11 summarises the two highest ranked variables after the repeated analysis. A full set of the new variable loadings is presented in Appendix 18. No change is observable in the sample relationships described above (fig 7.22) for the raw data of female only PC 1 versus PC 2 after the removal of populations with small sample numbers (results not shown). Considerable overlap of samples is still apparent in log-transformed PC 1 versus PC 2, and raw PC 3 versus PC 4 plots, and thus, no results are shown here. Removal of the aforementioned small samples resulted in the separation of further comparative populations from East Asia in a plot of log-transformed PC 3 versus PC 4 object scores (fig 7.24). All comparative samples, with the exception of the Native

Table 7.11. The two highe st ranked variable loadin gs for the repeated PCA of the raw and Ln-tra nsformed female-only data after the exclusion of sa mples with n < 5. Italics represent a cha nge of variable fr om the original analysis. Variable 1 Variable 2 Raw PC 1 NS: -0.655 PR: 0.570 PC 2 mSSA: -0. 744 ns-n-ba: 0.303 PC 3 n-ns-zyo: 0.692 mSSA: -0.342 PC 4 mPAA1: -0.541 mf-n-zyo: -0.395

Ln-transformed PC 1 mf-n-zyo: -0.814 PR: 0.428 PC 2 PR: - 0.635 mf-n-zyo: -0.527 PC 3 ns-n-zyo: -0.406 n-ns-zyo: -0.427 PC 4 n-ns-zyo: -0.719 ns-n-ba: 0.395

214 Americans, are clearly distinct from East Asia on PC 3. The separation of the Asian and non-Asian samples exhibits a statistically significant average difference in object scores (p < 0.001). Variables loadings of the repeated analysis show the highest ranking angles are altered sli ghtly for PC 3. Previously PC 3 was influenced the most by angles n-ns-zyo (mid- facial flatness) and PR (degree of prognathism). Mid-facial flatness remains as an influential variable, but the angle of prognathism has been replaced by upper facial flatness angle ns-n-zyo after the repeat analysis. Angles remain unchanged for PC 4 (table 7.11).

-3.2 Population Key PC 4 NA - Native America Mon Sib - Siberia -3.25 Mon - Mongolia Aus And Ain - Ainu Kor - Korea Jap - Japan -3.3 Mel Viet S.Chi - South China N.Chi - North China Bur - Burma -3.35 Lao - Laos Sib Viet - Vietnam Cam Thai Bur Thai - Thailand Mic Lao Cam - Cambodia -3.4 Phi - Philippines Indo And - Andaman Is. Bor Nic - Nicobar Is. Af Cauc Phi NA Bor - Borneo -3.45 Indo - Indonesia Mel - Melanesia Mic - Micronesia PC 3 Aus - Australia -3.5 Af - Africa -2.25 -2.2 -2.15 -2.1 -2.05 -2 -1.95 -1.9 Cauc - Caucasian

Figure 7.24 Scatterplot o f object scores for PC3 and PC4 from pri ncipal components of 18 angles and 17 objects after the removal of East Asia in sensu stricto and the Nicobar Islands and a repeat analysis. Scores calculated from log-transformed female-onl y data. Closed triangle s, East Asia ns; Open squares, comparative populations.

7.2.2.4 Testing the Association of Latitude with Observed Variation As above, linear regression, us ing la titude as the indepe ndent var iable, was applied to the object scores of axes 1-6 (raw data a nd log-tran sformed ) to determine whether observed shape changes were associated with climate. The result s are summarised in table 7.12.

215 Table 7.12 Summary table of significant correlations of PC object scores with latitude PC 1 PC 2 PC 3 PC 4 PC 5 PC 6 Pooled Sex r :0.8 Raw n.s n.s n.s n.s n.s p<0.001 r :0.74 Ln-transformed n.s n.s n.s n.s n.s p<0.001 Male-Only Raw r :0.65 r :-0.46 n.s n.s n.s n.s p=0.001 p=0.03 r :-0.62 Ln-transformed n.s n.s n.s n.s n.s p<0.01 Female-Only r :0.74 Raw n.s n.s n.s n.s n.s p<0.001 r :0.75 Ln-transformed n.s n.s n.s n.s n.s p<0.001

Moderately-strong to high significant correlations for both raw data PC 1 object scores are apparent for all three samples; pooled sex, ma le-only samples and female- only. These results suggest that size differences are thus largely ex plained by latitude/clima te (Ruff, 2002). The two highest influencing variables for PC1 for all three samples are those quantifying prognathism (PR, NS; see tables 7.6, 7.8 and 7.10). Angle of prognathism, PR, and mf-n-zyo, an angle quantifying superior nasal projection, are th e two strongest variables influencing variation on log transformed PC 1 axes for pooled sex and female- only plots (tables 7.6 and 7.10, respectively), with this axis exhibiting moderate to strong, highly significant correlations with latitude for both samples. The male-only provides similar results on the log-transformed PC 1 axis (r: 0.7, p < 0.001), only after the exclusion of small samples (n < 5). No other plots exhibited significant associations with latitude after the exclusion of small samples. PC 2 is the only subsequent axis to exhibit significant correlations with latitude, with this result apparent in the male plots only. Results were significant for both raw and log-transformed analyses. Variables most strongly associated with the variation observed on these axes are facial and frontal flatness angles mSSA and mNFA (raw) and aforementioned prognathic and facial flatness angles PR and mf-n-zyo (log transformed).

216 7.3 Summary and Conclusions

Principal components analysis identified a complex of features that distinguished both East Asian from non-Asian samp les, as well as distinctions between northern and southern East Asians. These divisions were apparent for both linear and angular analyses.

7.3.1 East Asia n vers us n on-As ian Divisions between Asian and non-Asian samples were also observed through PCA, although overlap between samples was evident, and not all comparative samples were distinct. Linear variables displayed separation largely on the basis of shape rather than size, with significant Asian-non Asian distinctions on log-transformed PC 2 axis and Mosimann shape axes PCs 1 and 2. Log-transformed pooled sex and male-only datasets generally exhibited similar separations and contributing variables, while the female-only datasets displayed results different to pooled sex and male-only samples. The discrepancy may be attributed to i) small female-only sample sizes for most populations, ii) sexual dimorphism or iii) a reflection of the different population histories of males and females (Perez et al, 2007). Inferior malar length (IML) was common to both log-transformed pooled sex and male groups as contributing the most to total variance, distinguishing Australia, Melanesia and Africa from the East Asian samples. These three comparative samples exhibit the longest malar lengths (anterior-posterior). In his study on the biometrics of the malar bone, Woo (1937) concluded that chord and arc measurements of the malar were effective in differentiating geographic groups, and that ‘racial’ variation of the zygomatic was correlated with geographic variation in facial flatness (Woo, 1937; Kean and Houghton, 1990). This may explain the division of East Asians from the aforementioned non-Asians, who as well as displaying the longest IML, also exhibit a greater degree of prognathism. Asian and non-Asian samples are distinct in the log-transformed female-only linear dataset, with nasal aperture breadth (al-al) the predominant discriminating variable. Non- Asian female samples exhibited broader nasal apertures in comparison to East Asian

217 females. Variation of the nasal region may be linked to climate, with narrow nasal breadth considered a cold-climate adaptation (Harvati and Weaver, 2006a). However, separation based on nasal breadth is not observed in the pooled sex and male-only PCA, and thus the division observed in the female analysis may be attributed to one or a combination of factors outlined above. Analysis of linear variables converted to Mosimann variables distinguished Asian from the majority of the non-Asian samples, largely on cranial length and breadth (anterior and posterior) variables for all three datasets (pooled sex, male-only and female-only). Comparative samples were characterised by long cranial vaults that are narrow anteriorly in Australia, Africa and Melanesia, and narrow postero-inferiorly (eg AUB) in most non- Asian samples when compared to the East Asians. Anterior cranial breadth values of the remaining comparative samples were within East Asian ranges. Thus, East Asian samples exhibit a more brachycephalic morphology (short and broad) than most non-Asian samples. Coon (1955) suggested that a brachycephalic morphology would be advantageous in cold climates. This hypothesis was based on the effect of surface area:mass ratios that underlie the rules of Allen and Bergmann. In sum, East Asian samples can be distinguished from a majority of non-Asian samples, particularly Australia, Africa and Melanesia on the basis of:  shorter malars (zygomatics) antero-posteriorly  broader cranial breadth, both anteriorly and posteriorly  shorter cranial length It is interesting to note that all of these features were found to be significantly correlated with latitude (see table 7.5). Asian/non-Asian divisions were also apparent in the angular analyses. The raw angle data revealed the modified zygomaxillary angle (mSSA), a measure of mid-facial flatness, as a common distinguishing variable for pooled sex, male-only and female-only daasets, with Asian samples exhibiting larger angles, and thus broader, flatter faces. Other mid-facial flatness (and cranial base flexion) angles n-ns-zyo and ns-n-ba also feature as variables contributing most strongly to total variance. Log-transformed analyses also isolated facial flatness and prognathic angles as distinguishing variables common to all three datasets (pooled sex, male-only and female-

218 only). Angles ns-n-zyo (upper), n-ns-zyo (mid) and PR (prognathism) featured in pooled sex, male-only and female-only datasets, while mf-n-zyo (upper facial flatness) was a contributing variable in the former two groups results only (pooled sex, male-only). Although identified above as north-south East Asian discriminators in the current study, it is not surprising that variation in facial flatness and alveolar projection also separates Asian and non-Asian samples, as it has been discussed in previous studies (eg. Howells, 1989; Bass, 1995; Hanihara 1997, 2000; Ishida and Dodo, 1998; Hennessy and Stringer, 2002). In sum, angles were useful in distinguishing East Asia sensu lato from a majority of comparative samples, particularly Australia, Africa and Melanesia. East Asia sensu lato differs from comparative samples by exhibiting:  flatter upper and mid-facial regions  orthognathic faces (alveolar region) These features were found to have highly significant correlations with latitude.

7.3.2 Northern versus Southern East Asia For all three datasets of log-transformed linear variables (pooled sex, male-only and female-only), PC 1 consistently separated northern (Northeast Asia, Korea, Ainu, Japan and North China) and southern (South China, mainland and island Southeast Asia) East Asian samples. Variables contributing most strongly to this separation were alveolar height (pr-ns) and up p er facial height (NPH), with the northern samples exhibiting the longer facial height. W hen size is removed (Mosimann shape variables used), the northern and southern East Asian samples were distinguished predominantly by anterior cranial breadth (biporionic breadth, STB, bipterionic breadth) and cranial height (BBH), with Northeast Asians exhibiting broader but shorter crania. Raw angle data separated northern and southern East Asian samples on the basis of degree of alveolar projection/prognathism (NS and PR angles), while log-transformed angles describing upper and mid-facial projection and cranial base flexion (n-ns-zyo, mf-n- zyo and ns-n-ba) were the strongest north-south discriminators. In sum, the linear variable and angular multivariate results distinguished northern East Asian samples from southern samples, with the former group possessing:  a longer, orthognathic (flat) face

219  broader cranium (anteriorly and posteriorly)  shorter cranial height These features were all significantly correlated with latitudinal differences (tables 7.5 and 7.12). These results support previous studies which concluded that Siberians, Mongolians and Northern Chinese are characterised by tall facial skeletons, and can be distinguished from other East Asian samples on the basis of facial flatness variables (Howells, 1989; Ishida and Kondo, 1998; Hanihara, 2000).

220 Chapter 8 Results Three Dimensional Analysis Part A: East Asia and Comparative populations Introduction

To define, describe and understand the cranial morphology of contemporary East Asians, 54 cranial landmarks were subjected to 3-D morphometric analysis using Morphologika (O’Higgins and Jones, 2006), where shape differences are able to be examined with the use of PCA and 3-D illustrations. The landmark obelion has been excluded from all further analyses due to its absence in a large number of crania, resulting in a reduction of the total number of crania used from 530 to 347 (see table 1). Three datasets (pooled sex, male-only and female-only) were examined to assess the presence of significant shape differences between populations (sex aggregated and sex specific). Samples were then plotted against latitude to determine whether shape changes, if any, were associated with climate. Centroid size was also examined, as it provides a reasonable estimate of cranial size, and in the absence of body mass data, is the best available surrogate for body size (Singleton, 2007). It is thus the commonly employed measure of overall size in 3D morphometrics. Plotting PC object scores against centroid size can provide insight into relationships between shape and size. Sample means (means of Procrustes distnaces) were used in place of all objects to aid in the better visualisation of the results. Table 8.1 provides a summary of the sample numbers of each population in each dataset.

Results

Dataset 1: Pooled sex Sample Dispersion Pooled sex results depict all populations, with the exclusion of Korean and Ainu samples, as it was found that the presence, and subsequent removal of these two n = 1 samples (n =1) dramatically altered the relationships between all other samples. These n = 1 samples acted as outliers in the analysis, resulting in the remaining samples

221 clustering close together, with no separation or groupings discernible. Thus, it was deemed appropriate that they be removed.

Table 8.1. Summary of sample numbers of each population to be used in Morphologika analysis Population Male Female Pooled Northeast Asia Siberia 10 8 18 Mongolia 12 6 18 East Asia in sensu stricto Korea 1 - 1 Ainu 1 - 1 Japan 5 1 6 South China 1 2 3 North China 3 2 5 Mainland Southeast Asia Burma 18 14 32 Laos 15 5 20 Vietnam 11 8 19 Thailand 14 6 20 Cambodia 2 7 9 Island Southeast Asia Philippines 11 5 16 Andaman Islands 16 13 29 Nicobar Islands 14 2 16 Borneo 18 7 25 Indonesia 15 7 22 Comparative Populations Melanesia 7 6 13 Micronesia 3 5 8 Australia 15 9 24 Africa 11 4 15 Caucasian 11 3 14 Native America 4 9 13 Total 218 129 347

222 The mean dispersion of all populations was examined on PCs 1-7, as subsequent axes contributed < 4% each. Figure 8.1 is a plot of PC 1 versus PC 2 scores for all pooled sex sample means. The two axes combined account for approximately 44% of the total variance, with PC 1 contributing 26.2%. East Asia is separated from Africa, Australia and Melanesia on PC 1, the latter three populations exhibiting strong negative scores. All East Asian samples possess positive PC 1 scores, with the exception of the Andaman and Nicobar Islands, which cluster with Micronesia and exhibit negative scores. Shape changes observed on this axis between negative and positive scores represent a narrowing of postorbital breadth combined with increased cranial length (negative) and broader postorbital breadth with shorter cranial length (positive). Increased facial length and reduced facial projection characterize East Asians in PC 1. Northeast Asia and East Asia sensu stricto, with the exception of South China, are distinct from Southeast Asia on PC 2, displaying high positive scores. South China clusters with Southeast Asia, the majority of which possess negative scores. Negatively scored populations are characterised by a high and short cranial vault, broad cranium superiorly and broad zygomatics inferiorly. Positively scoring populations exhibit a long vault and tall facial skeleton, with decreased alveolar projection (reduced prognathism) and shorter cranial height. In figure 8.2 a north-south trend from East Asia sensu stricto to Southeast Asia is detected on PC 3 (15% of total variance), with East Asia sensu stricto displaying positive scores, island Southeast Asia exhibiting negative scores, and mainland Southeast Asia intermediate (low positive to low negative). The Caucasian sample is clearly separate from all remaining populations on this axis. Shape changes associated with this axis include increased superior cranial breadth and decreased zygomatic breadth towards negative loadings. Increased facial length and decreased cranial height are observed in the positive range of PC 3. Positive samples also exhibit greater alveolar projection (prognathism). No groupings or separations are observed on PC 4. Sample dispersion on PCs 5, 6 and 7 display no obvious clusters or divisions, either among East Asians, or between East Asia and non-Asian populations (not shown).

223 PC 2 0.03

0.03 Caucasian Siberia 0.02 North China Japan 0.02 Mongolia Native America 0.01

Africa 0.01 Australia Nicobar Borneo 0.00 PC 1

-0.05 -0.04 -0.03 -0.02 -0.01 0.00Vietnam 0.01 0.02 0.03 -0.01 Melanesia Burma Indonesia Philippines Micronesia -0.01 Cambodia Thailand Andaman -0.02 Laos South China -0.02

-0.03

Figure 8.1. Mean dispersion of East Asia and comparative populations of pooled sex along PC 1 (26.2%) and PC 2 (17.2%). Lateral wireframe and rendered anterior profiles depict shape changes at the extreme of each axis.

224 PC 4 0.03

South China 0.03

0.02

0.02

Caucasian 0.01 Australia

Africa 0.01 Siberia North China Mongolia Andaman Cambodia 0.00 PC 3 BurmaI ndon esia Native America -0.04 -0.03 -0.02 -0.01 0.00Laos 0.01 0.02 0.03 Borneo Thai land Philippines-0.01 Nicobar Vietnam Melanesia -0.01 Micronesia

-0.02 Japan

-0.02

Figure 8.2. Mean dispersion of East Asia and comparative populations of pooled sex along PC 3 (15.0%) and PC 4 (7.74%). Lateral wireframe and rendered anterior profiles depict shape changes at the extreme of PC 3.

225 Latitude Object scores of PCs 1-7 were plotted against latitude to determine if observed shape differences could be attributed to latitudinal differences (ie. an environmental cline). Multiple regression (MANOVA) was performed on the first 7 PCs using latitude as the independent variable. PCs 1 and 2 demonstrated a weak but nonetheless statistically significant correlation with latitude (the results of which are presented below). Subsequent axes (PCs 3-7) showed no significant associations with latitude (not shown). A plot of PC 2 scores versus latitude (fig. 8.4) demonstrates a highly significant but moderate correlation (R2 = 0.4, p < 0.001). Separation between northern and southern East Asian populations is observed on PC 2, with populations from high latitudes (Siberia, Mongolia, Japan and North China) displaying high positive scores. Native American and Caucasian samples also display large positive scores. South China and Southeast Asia occupy lower latitudes and possess negative scores. Shape changes between the extreme positive and negative scores are displayed in figure 8.4 (A-D) as morphed rendered images and transformation grids. Positive populations demonstrate greater cranial and facial length as well as greater glabellar projection. Greater alveolar projection (prognathism), larger inferior zygomatic breadth and greater superior cranial breadth are observable in negatively scoring populations. Cranial height is greater in negative populations. The frontal bone exhibits a lower angle in positively scored samples compared to negatively scored samples.

Centroid Size The relationship between mean centroid size and PCs 1-7 was assessed with multiple regression. PCs 2, 3 and 5 were found to have a weak but significant correlation with size, indicating that allometric scaling is present on these axes. Figure 8.5 is a plot of PC 2 scores versus mean centroid size (R2 = 0.16, p < 0.05). All samples appear to possess similar mean centroid sizes, with the exception of Africa and the Northeast Asians, which display the highest centroids, and the Andaman Islands sample, which is clearly the smallest population. Phenetic relationships between populations echo the latitude vs PC 2 analysis, with Northeast Asia, Japan, North China and the Native American and Caucasian comparative samples possessing positive scores and South China and Southeast Asia

226 Latitude 80

60 Siberia Caucasian

Mongolia Native America 40 North China Japan

A South China Burma B 20 Vietnam Laos Thailand Andaman Cambodia Africa Nicobar Philippines Borneo 0 PC 1 -0.05 -0.04 -0.03 -0.02 -0.01 0.00 0.01 0.02 0.03 Melanesia Micronesia Indonesia

-20

Australia -40

C D Figure 8.3. Pooled sex PC 1 vs Latitude (R2= 0.30, p < 0.01). Anterior and lateral rendered images and anterior coronal (A,B) and lateral mid-sagittal (C,D) transformation grids show variation in cranial shape on PC 1 extreme negative (A and C: PC1=-0.04) and extreme positive (B and D: PC1=0.03).

227 Latitude 80

60 Siberia

Mongolia Caucasian

Native America North China 40 Japan

South China Vietnam Laos Burma 20 A Thailand Nicobar B Andaman Philippines Cambodia Africa Borneo Indonesia 0 PC 2 -0.03 -0.02 -0.02 -0.01 - 0.01 0.00 0.01 0.01 0.02 0.02 0.03 0.03 Micronesia Melanesia -20

Australia -40

D C

Figure 8.4. Pooled sex PC 2 vs Latitude (R2= 0.40, p < 0.001). Anterior and lateral rendered images and anterior coronal (A,B) and lateral mid-sagittal (C,D) transformation grids show variation in cranial shape on PC 1 extreme negative (A and C: PC1=-0.02) and extreme positive (B and D: PC1=0.03).

228 having negative scores. Shape differences are for the most part explained by increased cranial and facial length, and greater glabellar projection (in positively scored samples). Greater alveolar projection, broad superior cranial breadth and narrow postorbital breadth are characteristics of samples with negative scores. A change is cranial height is also evident, with negatively scored samples exhibiting the greater height. A regression analysis between centroid size and latitude yielded a weak correlation that was not significant. This suggests that while both size and latitude are affecting shape changes observed on PC 2, they are acting independently of eachother (associations between size and latitude were also assessed for male-only and female-only samples, resulting no significant correlation for either sample). Centroid size versus PC 3 (R2 = 0.15, p < 0.05) appears to separate East Asia sensu stricto (North China, South China and Japan) from Southeast Asia, with the former group possessing the largest positive scores and greater mean centroid sizes (fig. 8.6). The Andaman Islands sample is clearly the smallest (sized) population, with a negative score similar to island samples Nicobar Islands and Borneo. The Caucasian sample exhibits the most negative PC 3 score. Morphing along PC 3 from extreme positive to negative (fig 8.6 A-D) shows a shortened, flattened face, posterior projection of the posterior vault at lambda and a greater cranial height (towards negative scores). Samples with positive scores display broad zygomatic and nasal breadths and narrow bi- parietal breadth. A plot of PC 5 versus centroid size (R2 = 0.16, p < 0.05) is presented in figure 8.7 and suggests a north-south trend between Northeast Asia and Southeast Asia. Northeast Asian populations are from high latitudes and exhibit positive PC 5 scores, while island Southeast Asian populations are from lower latitudes and display predominantly negative scores. Mainland Southeast Asians are positioned between the aforementioned groups, and display positive scores which are lower than those for Northeast Asians. Warped transformation grids between extreme negative and positive PC 5 scores show a greater superior cranial breadth and cranial length in negatively scored samples and a broader zygomatic breadth in populations with positive scores. Negative populations also exhibit a flatter face and a higher frontal angle.

229 Centroid size 530 Africa Mongolia 520 Siberia South China North China Vietnam Micronesia Australia Burma Borneo Japan Indonesia 510 Native America Thailand Melanesia Caucasian Cambodia Philippines Nicobar Laos 500 B A 490

Andaman 480

470 PC 2 -0.03 -0.02 -0.02 -0.01 -0.01 0.00 0.01 0.01 0.02 0.02 0.03 0.03

C D Figure 8.5. Pooled sex PC 2 vs Centroid size (R2= 0.16, p < 0.05). Anterior and lateral rendered images and anterior coronal (A,B) and lateral mid-sagittal (C,D) transformation grids show variation in cranial shape on PC 1 extreme negative (A and C: PC1=-0.02) and extreme positive (B and D: PC1=0.02)

230 Centroid size 530 Africa Siberia Mongolia 520 North China South China Vietnam Native America Australia Borneo Laos Japan 510 Melanesia Philippines IndonesiaMicronesia Thailand Cambodia Caucasian Nicobar Burma 500 A B

490

Andaman 480

470 PC 3 -0.04-0.03 -0.02 -0.01 0. 0 0 0.01 0.02 0.03

C D

Figure 8.6. Pooled sex PC 3 vs Centroid size (R2 = 0.15, p < 0.05). Anterior and lateral rendered images and anterior coronal (A,B) and lateral mid-sagittal (C,D) transformation grids show variation in cranial shape on PC 3 extreme negative (A and C: PC1=-0.03) and extreme positive (B and D: PC1=0.02).

231 Centroid size 530 Africa Mongolia Siberia 520 North China South China Vietnam Native America Japan Melanesia Australia Micronesia510 Laos Caucasian Borneo Indonesia PhilippinesCambodia Thailand Nicobar Burma 500

B A 490

Andaman 480

470 PC 5 -0.03-0.03 -0.02-0.02 -0.02 -0.01 -0.01 0.00 0.01 0.01 0.02 0.02

C D Figure 8.7. Pooled sex PC 5 vs Centroid size (R2 = 0.16, p < 0.05). Anterior and lateral rendered images and anterior coronal (A,B) and lateral mid-sagittal (C,D) transformation grids show variation in cranial shape on PC 5 extreme negative (A and C: PC1=-0.03) and extreme positive (B and D: PC1=0.02).

232 Correlation with centroid size was tested a second time after the removal of the Andaman Islands sample to assess if the presence of very small (sized) samples (or extreme point) influence the results. After the exclusion of this sample, significant but weak results were still observable, with PCs 3 and 4 exhibiting significant correlations with size. Figure 8.8 shows the results of PC 3 versus centroid size after the Andaman Islands sample is excluded. Relationships between samples are essentially the same as those previously observed in the original PC 3 versus size analysis above. East Asia sensu stricto displays the highest positive PC 3 scores, separating these populations from Southeast Asia which possess predominantly negative scores. The former group also displays the higher mean centroid size. Shape changes for PC 3 associated with size (figs. 8.8 A-D) are a narrow and short vault due to reduced occipital height and a rounding of the frontal bone (in positive populations).A broad and high vault, narrowing across the zygomatics and greater alveolar projection is observed when morphing towards the negative. A plot of PC4 and centroid size is displayed in figure 8.8. Northeast Asia and both Chinese samples exhibit negative scores, overlapping with comparative samples Australia, Africa and the Caucasians. Mainland and island Southeast Asia possess positive PC 4 scores, with the majority of mainland populations clustering close to zero, putting them between Northeast and island Southeast Asia. Populations with negative scores exhibit greater glabellar projection, while the positive samples display increased alveolar projection. Positive populations display a posterior projection of the vault at lambda, resulting in a slight lengthening of the vault. The extreme positive cranial morphology also features a high and narrow vault. Warping to the extreme negative, a broad, short face and vault is observed. Transformation grids and rendered images below illustrate the variation outlined above (figs. 8.9 A-D).

233 Centroid size 530

Africa 525

Mongolia Siberia 520

South China North China A 515 B Native America Australia Vietnam Micronesia Laos Melanesia Japan Borneo Philippines 510 Caucasian Thailand Indonesia Cambodia

Nicobar 505 Burma

500 PC 3 -0.03 -0.02 -0.02 -0.01 -0.01 0.00 0.01 0.01 0.02 0.02 0.03 0.03

D C Figure 8. Pooled sex PC 3 vs Centroid size after the exclusion of the Andaman Islands (R2 = 0.16, p < 0.05). Anterior and lateral rendered images and anterior coronal (A,B) and lateral mid-sagittal (C,D) transformation grids show variation in cranial shape on PC 3 extreme negative (A and C: PC1=-0.03) and extreme positive (B and D: PC1=0.03).

234 Centroid size 530

Africa 525

Mongolia Siberia 520

South China North China 515 A Borneo Native America Japan Australia Laos B Vietnam Melanesia 510 Micronesia Cambodia Indonesia Philippines Caucasian Thailand

505 Nicobar Burma

500 PC 4 -0.03 -0.03 -0.02 -0.02 -0.01 -0.01 0.00 0.01 0.01 0.02 0.02

C D Figure 8.8. Pooled sex PC 4 vs Centroid size after the exclusion of the Andaman Islands (R2 = 0.16, p < 0.05). Anterior and lateral rendered images and anterior coronal (A,B) and lateral mid-sagittal (C,D) transformation grids show variation in cranial shape on PC 4 extreme negative (A and C: PC1=-0.03) and extreme positive (B and D: PC1=0.02).

235 Dataset 2: Male-Only Sample Dispersion Male-only results depict all samples with the exclusion of Korea, Ainu and South China, as it was found that the presence, and subsequent removal of these n = 1 samples altered the relationships between all other populations. Thus, it was deemed appropriate that they be removed from the male-only analyses. The mean dispersion of all male-only samples was examined on PCs 1-7, as these axes explained most of the observed variation. Figure 8.10 is a plot of PC1 versus PC 2 scores. Most comparative populations, with the exception of the Caucasians and Native Americans, display the highest positive scores for PC 1 (23.5%), clearly separating them from all East Asians. Northeast Asia and East Asia sensu stricto possess the strongest negative PC 1 scores, followed by a cluster of combined mainland and island Southeast Asia, which exhibit intermediate object scores (weak positive and negative scores). These results are suggestive of a possible north-south cline on PC 1, as well as a separation of Asian and non-Asian populations. Shape changes observed by warping between the extremes of this axis (fig. 8.10) are a long vault, narrowing of post orbital breadth, increased alveolar and mid-facial projection towards the positive extreme (PC 1 = 0.04), while the negative extreme (PC 1 = -0.03), is characterised by a broad, long face, and posteriorly sloping mid-face and low frontal angle. East Asia sensu stricto and Northeast Asia are clearly distinct from Southeast Asia on PC 2, with the two clusters displaying positive and negative PC 2 scores respectively (fig. 8.10). The majority of comparative populations appear to separate the two distinct Asian clusters, with minimal overlap observed between comparative and East Asian positive PC 2 object scores. Rendered anterior and wireframe lateral images demonstrate positively scored populations as having a long and low cranial vault. Populations possessing negative PC scores exhibit a short, high vault and a short face, with a greater degree of alveolar projection. A plot of PC 3 versus PC 4 showed no obvious patterns either between Asian and non-Asian populations, or within East Asia. Figure 8.11 is a plot of PC 5 versus PC 6, which contribute a combined 10.74% of the total variance. Northeast Asia, displaying negative scores is clearly separate from all remaining East Asian populations on PC 5 (6.02%), with the remaining samples possessing positive scores. Micronesia is also separate from all samples on this axis,

236 PC 2 0.04

0.03 Siberia North China

Japan 0.02 Melanesia Caucasian Africa Mongolia 0.01 Australia Native America Nicobar 0 PC 1 -0.04 -0.03 -0.02 -0.01 0 0.01 0.02 0.03 0.04 Borneo -0.01 Andaman Philippines Burma Micronesia Vietnam Indonesia Laos Thailand -0.02

Cambodia -0.03

-0.04

Figure 8.10. Mean dispersion of East Asia and comparative populations (male-only) along PC 1 (23.5%) and PC 2 (21.1%). Lateral wireframe and rendered anterior profiles depict shape changes at the extreme of each axis.

237 PC 6 0.02

0.015 Africa

Siberia 0.01

Nicobar Andaman 0.005 Laos Micronesia Mongolia Borneo Philippines Native Ameri ca Vietnam Japan PC 5 Thailand 0 -0.03 -0.02 -0.01 Burma 0 0.01 0.02 Indonesia -0.005 Australia Melanesia

-0.01 Cambodia Caucasian

-0.015 North China -0.02

Figure 8.11. Mean dispersion of East Asia and comparative populations (male-only) along PC 5 (6.02%) and PC 6 (4.72%). Lateral wireframe and rendered anterior profiles depict shape changes at the extreme of each axis.

238 exhibiting the strongest negative score. Rendered and wireframe images display the extreme positive scores as demonstrating a broad superior posterior cranial breadth, and a posteriorly sloped frontal bone and facial region, thus increasing alveolar projection (prognathism). Extreme negative scores show a narrow biparietal breadth, and a more vertical orientation of the face and frontal bone. No discernible phenetic relationships (divisions or clusters) between samples are observed on PC 6. A plot of PC 7 scores against previously described PC 1 displays no detectable groupings or separations between any populations, East Asian or otherwise.

Latitude The latitude of each population mean was plotted against PCs 1-7 to determine if observed shape differences could be attributed to latitudinal differences. Multiple regression was performed on the first 7 PCs with latitude as the independent variable, where it was found that PCs 1 and 2 demonstrated significant correlations with latitude, the results of which are presented below. Higher axes (PCs 3-7) showed no significant correlations with latitude. Figure 8.12 is a plot of PC 1 scores versus latitude (R2 = 0.54, p < 0.001). Samples from high latitudes tend to exhibit negative scores, while low latitude populations display positive PC 1 scores. A north-south East Asian cline is detectable, with Northeast Asia possessing the most negative scores and island Southeast Asia displaying predominantly positive scores. However, the most notable observation is a separation of Asian from low latitude non-Asian populations (Africa, Micronesia, Melanesia and Australia). These latter samples display the most positive scores, and exhibit no overlap with any East Asian sample. Warped transformation grids and rendered images demonstrate the shape changes between the negative (PC 1 = -0.03) and positive (PC 1 = 0.04) extremes of this x-axis (fig 8.12 A-D). Narrow post orbital breadth, anterior projection of the mid-face and alveolar region, wide nasal aperture and a long vault are characteristics displayed towards the extreme positive value. A broad and tall face that recedes in the mid-facial region (ie, concave mid-face), and a short and rounded vault are displayed by extreme negative populations.

239 Latitude 80

Siberia 60 Caucasian Mongolia Native America North China 40 Japan

A Burma B Vietnam 20 Laos Thailand Cambodia Andaman Philippines PC 1 Nicobar Africa 0 Borneo -0.04 -0.03 -0.02 -0.01 0 0.01 0.02 0.03 0.04 Indonesia Micronesia Melanesia -20

Australia -40

C D

Figure 8.12. Male-only PC 1 vs Latitude (R2 = 0.54, p < 0.001). Anterior and lateral rendered images and anterior coronal (A,B) and lateral mid-sagittal (C,D) transformation grids show variation in cranial shape on PC 1 extreme negative (A and C: PC1=-0.03) and extreme positive (B and D: PC1=0.04).

240 Latitude 80

60 Siberia

Caucasian Mongolia 40 Native America North China

Japan A Burma B Laos Vietnam 20 Andaman Thailand Nicobar Cambodia Philippines Africa Borneo 0 PC 2

-0.04 -0.03 -0.02 -0.01 0 0.01Melanesia 0.02 0.03 0.04 Indonesia Micronesia -20

Australia -40

C D

Figure 8.13. Male-only PC 2 vs Latitude (R2 = 0.17, p < 0.05). Anterior and lateral rendered images and anterior coronal (A,B) and lateral mid-sagittal (C,D) transformation grids show variation in cranial shape on PC 2 extreme negative (A and C: PC1=-0.03) and extreme positive (B and D: PC1=0.03).

241 A plot of PC 2 versus latitude (R2 = 0.17, p < 0.05) is provided below in figure 8.13. A north to south cline is visible, with Northeast Asia and East Asia sensu stricto exhibiting positive PC 2 scores, and Southeast Asia possessing negative scores. There is no observable overlap between northern and southern East Asian populations. All comparative populations, with the exception of Micronesia, exhibit positive scores, overlapping with the northern Asian samples. Figures 8.13 A-D demonstrate extreme negative (PC 2 = -0.03) and positive (PC 2 = 0.03) cranial shapes. Positive populations possess a long and low vault with a receding frontal bone. Compared to the negatively scored populations, positive samples display a broader face and nose and greater prosthion-nasospinale length, with prosthion (pr) below the level of the inferior zygomatics. The shape of negatively scored samples includes a high and short vault, vertical frontal bone and a greater degree of alveolar projection (prognathism) compared to the positive samples. A broad superior posterior cranial breadth is also evident. Prosthion-nasospinale is short, with prosthion virtually in line with the inferior malars, giving the face a square appearance.

Centroid Size To assess the relationship between cranial shape and cranial/body size, multiple regression, using mean centroid size as the independent variable, was undertaken on PCs 1-7. This revealed PCs 3 and 5 as possessing a significant correlation with size. A plot of PC 3 and mean centroid size (R2 = 0.23, p < 0.01) is provided below in figure 8.14. Considerable overlap is evident for most samples. There is some evidence of separation among East Asians based on cranial size. Northeast Asia exhibits the greatest centroid size, followed by East Asia sensu stricto (North China and Japan) and mainland Southeast Asia, all of which predominantly possess positive PC 3 scores. The majority of the island Southeast Asian samples display negative scores for this axis, although this includes the Andaman Islands, which is dramatically smaller than most other East Asians. Most comparative samples, with the exception of the Caucasians, exhibit centroid sizes similar to mainland Southeast Asians, and display mostly positive scores. The Caucasian sample is clearly separate from all populations, displaying the most negative PC 3 score. Warping to the extreme negative PC 3 score (-0.04) displays a tall vault with expanded frontal and occipital bones, broad superior biparietal breadth and a narrow, flat face (fig 8.14 A and C). The positive extreme (PC 3 = 0.02), shows a

242 narrower vault, with less projection (bulging) of the parietals, a greater degree of alveolar projection and a broad face across the zygomatics (fig 8.14 B and C). Figure 8.15 is a plot of PC 5 versus mean centroid size (R2 = 0.26, p < 0.01). Northeast Asia is separate from all remaining East Asian populations, exhibiting the most negative Asian PC scores, and possessing the largest mean centroid sizes. Micronesia is clearly distinct, but it is also of small sample size (n = 3) and so may not be an accurate representation of the population mean. The Andaman Islands is clearly the population with the smallest mean centroid, and exhibits the most positive PC 5 score. Warping towards the extreme positive axis (PC 5 = 0.02) shows a slight posterior slope of the face and flatter frontal angle, and rounding of the occipital. Broad superior breadth across the parietals is also evident (fig 8.15 A and D). The extreme negative morphology (fig 8.15 B and D) displays a vertical face and frontal bone, and depressed vault in comparison to the extreme positive morphology. Narrow superior cranial breadth and broad post-orbital breadth are also present. Correlation with centroid size was tested a second time after the removal of the Andaman Islands sample to assess if the presence of this cranially small population has an effect on observed phenetic relationships. After the exclusion of this sample, no significant correlation was returned between mean centroid size and PCs 1-7. Thus, in the male-only analysis, this outlier is pulling the distribution in the positive direction, creating a more linear association than would be otherwise present.

243 Centroid size 535 Mongolia Siberia Cambodia 530 Africa North China Micronesia 525 Vietnam Australia Melanesia 520 Native America Indonesia Philippines Japan Thailand Borneo A Burma515 Caucasian Laos B 510

Nicobar 505

500

495

490 Andaman 485 PC 3 -0.04-0.04 -0.03 -0.02 -0.01 0 0.01 0.02 0.03

D C Figure 8.14. Male-only PC 3 vs Centroid size(R2 = 0.23, p < 0.01). Anterior and lateral rendered images and anterior coronal (A,B) and lateral mid-sagittal (C,D) transformation grids show variation in cranial shape on PC 3 extreme negative (A and C: PC1=-0.04) and extreme positive (B and D: PC1=0.02).

244 Centroid size 535 Siberia Cambodia Mongolia 530 Africa North China Micronesia 525 Vietnam Australia Melanesia Native America 520 Indonesia Thailand Philippines Japan Borneo 515 Burma Caucasian Laos 510 B A 505 Nicobar

500

495

490 Andaman 485 PC 5 -0.03 -0.02 -0.01 0 0.01 0.020.02

C D Figure 8.15. Male-only PC 5 vs Centroid size (R2 = 0.26, p < 0.01). Anterior and lateral rendered images and anterior coronal (A,B) and lateral mid-sagittal (C ,D) transformation grids show variation in cranial shape on PC 5 extreme negative (A and C: PC1=-0.03) and extreme positive (B and D: PC1=0.02).

245 Dataset 3: Female-Only Sample Dispersion The mean dispersion of female-only samples was examined on PCs 1-7,as most of the total variance was explained by these axes. Female-only results represent all samples, with the exception of Korean and Ainu samples, whose female crania have been removed due to one or more of the criteria outlined above. Japan, with a sample number of n = 1 (see table 8.1), is also excluded, as it was found that the presence, and subsequent removal of this individual altered the relationships between all remaining populations on PCs 5-7. Figure 8.16 is a plot of PC 1 and PC 2 scores, which combined, explain 42.5% of total variance. Comparative populations Australia, Africa and Melanesia are imperfectly separated from all remaining populations on PC 1 (26.0%), displaying the most negative scores. Accompanying this comparative sample cluster is the Nicobar Islands, which is clearly distinct on this axis from remaining East Asian samples. Considerable overlap is evident between all East Asian populations not previously mentioned above. Warping between the negative (-0.04) and positive (0.04) extremes of PC 1 demonstrates the following shape changes: Narrow postorbital breadth and broad biparietal breadth is observed when warping towards the negative samples, as is an increased degree of alveolar projection and a long cranial vault. Positive populations exhibit a rounded, high vault and a flat face. A similar pattern is observed on PC 2 (16.5%), where comparative populations, with the exception of Micronesia and the Native Americans, possess the most positive scores and East Asia is predominantly negative. The separation of Asian versus non Asian samples is imperfect, however, with the Southeast Asian sample from the Nicobar Islands clustering with the comparative samples. The Caucasian sample exhibits the highest positive PC 2 score, clearly separating them from all other samples. No pattern is observed between East Asian populations. Shape changes observed on the PC 2 axis are similar to those observed above. A long, low cranial vault and a short face are seen when warping towards the comparative populations, or positive extreme (0.04). The negative extreme (-0.04), or East Asian samples, displays a tall, rounded vault with a long face. A plot of PC 3 versus PC 4 object scores (fig 8.17), displays no obvious groupings or separations between any samples on either axis, with the exception of a distinct

246 PC 2 0.05

0.04 Caucasian

0.03

Africa Australia 0.02 Nicobar Melanesia 0.01 Philippines Borneo Andaman Micronesia Laos Siberia 0.00 PC 1 Vietnam Indonesia Mongolia -0.04 -0.03 -0.02 -0.010.00 0.01 0.02 0.030. 04 Native Ameri ca -0.01 Burma South China Cambodia Thailand -0.02

-0.03

-0.04 North China -0.05

Figure 8.16. Mean dispersion of East Asia and comparative populations (female-only) along PC 1 (26.0%) and PC 2 (16.5%). Lateral wireframe and rendered anterior profiles depict shape changes at the extreme of each axis.

247 PC 4 0.03

Nicobar Thailand 0.02

0.02 Andaman

0.01 Burma Indonesia Laos Borneo 0.01Mongolia Philippines Cambodia Africa 0.00 PC 3 Australia Vietnam -0.04 -0.03 -0.02 -0.01 0. 00 0.01 0.02 0.03 0.04 0.05 -0.01 Micronesia Melanesia Siberia North China -0.01

-0.02 Native America -0.02 Caucasian South China -0.03

Figure 8.17. Mean dispersion of East Asia and comparative populations (female-only) along PC 3 (11.4%) and PC 4 (8.3%). Lateral wireframe and rendered anterior profiles depict shape changes at the extreme of each axis.

248 separation of North and South China on PC 3 (11.4%). The former sample possesses the most negative object score, while the latter exhibits has the extreme positive score. Both samples are clearly distinct from all remaining samples. However, both North and South China are represented by only 2 individuals (see table 8.1), and therefore may not be an accurate representative of the population mean. Thus this result should be regarded with caution. Warping to the negative extreme (PC 3 = -0.04) shows a long cranial vault with a long and narrow face. A broad, short face and short vault represented the positive extreme PC 3 score (0.04). A plot of PC 5 versus PC 6 showed no obvious groupings or separations either between Asian and non-Asian populations, or within East Asia. A plot of PC 7 scores against previously described PC 1 displays no detectable clusters or divisions between any populations, East Asian or otherwise.

Latitude The latitude of each sample was plotted against PCs 1-7 to determine if observed shape differences could be attributed to latitudinal affects. Multiple regression was performed on the first 7 PCs with latitude as the independent variable, where it was found that PCs 1 demonstrated weak, yet significant correlations with latitude, the results of which are presented below. Figure 8.18 is a plot of PC 1 object scores and mean latitude (R2 = 0.37, p < 0.001). Considerable overlap between all samples is evident, yet suggestion of a separation of high and low latitude populations can be observed. Northeast Asian and Caucasian samples are from the highest latitudes, and tend to display the highest PC 1 object scores. Mainland Southeast Asians exhibit the next highest PC scores, followed by the island samples, which possess both positive and negative values. Australia and Melanesia display the most negative object scores, and two of the lowest latitudes. Africa also displays a low latitude and a negative object score. The aforementioned comparative samples are distinct from all East Asian samples, with the exception of the Nicobar and Andaman Islanders, who possess negative scores, and are positioned close to Africa (both latitudinally, and in the plot). Negative populations display narrow anterior breadths at stephanion and pterion, marked alveolar projection and a long vault (fig 8.18 A and C). Warping towards the positive extreme shows a high, rounded vault, with posterior orientation of the mid-face (fig 8.18 B and D).

249 Latitude 80

60 Siberia Caucasian Native America North China Mongolia 40

Vietnam 20 Burma A South China Laos Andaman Thailand Nicobar B Africa Cambodia Philippines Borneo 0 PC 1 -0.04-0.04 -0.03 -0.02 -0.01 0.00 0.01 0.02 0.03 0.040.04 Melanesia Micronesia Indonesia -20

Australia -40

C

D

Figure 8.18 Female-only PC 1 vs Latitude (R2 = 0.37, p < 0.001). Anterior and lateral rendered images and anterior coronal (A,B) and lateral mid-sagittal (C,D) transformation grids show variation in cranial shape on PC 5 extreme negative (A and C: PC1=-0.04) and extreme positive (B and D: PC1=0.04).

250 Centroid Size The relationship between mean centroid size and PCs 1-7 was assessed with multiple regression analysis, where PC 7 only was found to have a weak yet significant correlation with size. A plot of PC 7 object scores and mean centroid size (R2 = 0.16, p < 0.05) is provided below (fig. 8.19). Populations with the largest centroid size, Africa, Siberia, native America and Laos, tend to display the most positive object scores, while all remaining East Asian and comparative populations display similar mean centroids and both positive and negative PC 7 scores. The Andaman Islands sample clearly has a very small mean centroid, and possesses a moderate PC score of close to zero. The extreme negative value (-0.02) is characterised by a short, broad face, wide nasal aperture and broad biparietal breadth (fig 8.19 A and C), while the positive extreme (0.03) displays a broad and long mid-face (zm-zm and pr-ns respectively), with narrow superior posterior cranial breadth (fig. 8.19 B and D). The mid-face slopes posteriorly in the extreme positive morphology, revealing marked projection of glabella. Correlation with centroid size was tested a second time after the removal of the Andaman Islands sample to assess if the presence of the cranially small population alters results. After the exclusion of this sample, a significant correlation was observed for PC 6 (R2 = 0.34, p < 0.001). As figure 8.20 shows, populations with large mean centroids generally possess negative scores, which progress towards the positive axis as centroid size decreases. This pattern however is imperfect, as overlap between large and small centroids and PC 6 object scores is evident. Shape changes observed between the extreme scores have not altered from those observed when the Andaman sample is present (fig 8.19).

251 Centroid size 520

Africa Cambodia 510 Native America Siberia Mongolia South China North China Laos Micronesia Vietnam 500 Nicobar Melanesia Borneo Australia Philippines Caucasian Indonesia Thailand 490 Burma A B 480

470 Andaman

460 PC 7 -0.03 -0.02 -0.02 -0.01 -0.01 0.00 0.01 0.01 0.02 0.02 0.03

C D

Figure 8.19. Female-only PC 7 vs Centroid size (R2 = 0.16, p < 0.05). Anterior and lateral rendered images and anterior coronal (A,B) and lateral mid-sagittal (C,D) transformation grids show variation in cranial shape on PC 5 extreme negative (A and C: PC1=-0.02) and extreme positive (B and D: PC1=0.03).

252 Centroid size 520

Africa 515 Laos

Native America 510 Siberia South China Mongolia 505 Cambodia Vietnam Nicobar Micronesia 500 North China A Borneo Melanesia B Australia 495 Indonesia Caucasian Philippines Thailand 490 Burma

485 PC 6 -0.025 -0.02 -0.015 -0.01 -0.005 0 0.005 0.01 0.015 0.02 0.025

C D Figure 8.20. Female-only PC 6 vs Centroid size after the exclusion of the Andaman Islands (R2 = 0.34, p < 0.001). Anterior and lateral rendered images and anterior coronal (A,B) and lateral mid-sagittal (C,D) transformation grids show variation in cranial shape on PC 6 extreme negative (A and C: PC1=-0.025) and extreme positive (B and D: PC1=0.02).

253 Summary and Conclusions

In sum, in using geometric morphometrics to analyse populational shape differences, the following observations were made:

East Asian versus non-Asian East Asia sensu lato and non-Asian samples, particularly Australia, Melanesia and Africa, can be largely separated on differences in vault shape (length, breadth and height), with facial height also a distinguishing feature. East Asia sensu lato thus exhibits the following defining craniofacial shape:

o Short cranial length and high cranial height o Broad post-orbital breadth o Tall, orthognathic facial skeleton

Caucasians are also distinguishable from East Asia sensu lato, exhibiting comparatively taller and broader cranial vault and shorter narrower facial skeletons. Most observed shape differences were found to be significantly correlated with latitude. Aspects of cranial breadth, length and height are also influenced by centroid/body size. While allometric scaling is apparent, these effects are observed on the higher axes (ie PC 2 and above), suggesting that allometric effects are not the major underlying influence on variation. Significant correlations with latitude are predominantly observed on PC 1, which traditionally explains most of the total variance, thus indicating that latitude has a stronger influence than size on observed variation. Further more, there is evidence to suggest that while latitude and size can effect variation on a single axes (refer to pooled sex sample), they are not significantly correlated and thus may be acting independently on shape.

Northern versus Southern East Asia A north-south East Asian cline was also observed. Northeast Asia, North China and Japan tended to form a cluster that separated them from Southeast Asia. Characteristics observed in the northern samples were:

254 o Long and low cranial vault o Low frontal angle o Tall facial height o Orthognathism o Vertical mid-face

In comparison to the southern samples, which exhibited:

o High, rounded cranial vault shape o High frontal angle o Broad superior cranial breadth o Receding mid-face o Prognathism

These north-south East Asian shape differences were significantly correlated with latitude. A more detailed study of shape variation within East Asia sensu lato is provided in Chapter 10. It is interesting to note that while the observed shape variation above is largely associated with latitude and thus climate (Ruff, 2002) and partly by allometric scaling, there are aspects of cranial shape that suggest that these factors can not wholly determine cranial shape. Cold-climate Northeast Asians and warm-climate Africans, Australians and Melanesians share a similar long and low vault shape, with differences in facial morphology. This suggests that aspects of the face are may be more susceptible to climatic changes, while the vault is reflective of both environmental influences and neutral genetic (Roseman, 2004; Harvati and Weaver, 2006a, b). This hypothesis may also explain cold-climate shape discrepancies observed between the current study and the literature: Traditionally, a broad and/or round vault shape (brachycephaly) is thought to be advantageous in colder climates (e.g Coon, 1955), which is in contrast to the observed long, low cranial shape of the Northeast Asians in the present study.

255 Chapter 9 Results Three Dimensional Analysis Part B: East Asia sensu lato

9.1 Introduction

East Asian populations were isolated from comparative samples to further assess the presence of trends and clines within East Asia noted previously in Chapter 8. The methods employed for the current analysis are outlined in Chapter 8. Relationships between population means will be examined, as will the effect of latitude and size, the results of which are to be described below, divided into pooled sex, male-only and female-only datasets. Table 9.1 is a summary of the individuals (crania) used in the current analyses.

9.2 Results

9.2.1 Pooled Sex 9.2.1.1 Sample Dispersion Population means (Procrustes means) were analysed with PCA to examine the phenetic relationships among pooled sex East Asian samples. Korean and Ainu samples have been excluded, as it was found that the presence, and subsequent removal of these two n = 1 samples dramatically altered relationships (see Chapter 8). Mean population dispersion was examined on PCs 1-6, which account for approximately 84% of total variance. Subsequent PCs each contribute less than 4% to the total variance, and 100% of the variance is explained by 15 principal components. Figure 9.1 is a plot of mean object scores for PC 1 (27.0%) and PC 2 (17.7%). Northeast Asia and northern East Asia sensu stricto (Japan and North China) are clearly distinct from mainland and island Southeast Asia on PC 1, with the former populations exhibiting negative scores, and the latter, positive. South China is clearly separated from North China, displaying a positive PC 1 object score. Shape changes observed between the negative (-0.04) and positive (0.02) extremes of PC 1 show a long face, and a long and low vault in samples with negative scores, and tall, rounded vault with broad

256 Table 9.1. Summary of sample numbers of each population to be used in Morphologika analysis

Population Male Female Pooled Northeast Asia Siberia 10 8 18 Mongolia 12 6 18 East Asia sensu stricto Korea 1 - 1 Ainu 1 - 1 Japan 5 1 6 South China 1 2 3 North China 3 2 5 Mainland Southeast Asia Burma 18 14 32 Laos 15 5 20 Vietnam 11 8 19 Thailand 14 6 20 Cambodia 2 7 9 Island Southeast Asia Philippines 11 5 16 Andaman Islands 16 13 29 Nicobar Islands 14 2 16 Borneo 18 7 25 Indonesia 15 7 22 Total 167 93 260

biparietal breadth, a short face and alveolar projection in populations exhibiting positive scores. Separation between mainland and island Southeast Asia is observed on PC 2. Island populations predominantly exhibit high positive PC 2 scores, while the majority of mainland populations display negative scores. Northeast Asia and East Asia sensu stricto (excluding South China) possess scores similar to the mainland Southeast Asian samples. South China is clearly separated from all samples, displaying the lowest negative score. Figure 9.1 demonstrates the shape changes observed between PC 2 negative (-0.03) and positive (0.03) extremes. A long vault and broad superior parietal breadth is observed in populations with high scores. A short cranial vault and broad face are characteristics of populations with low, or negative, PC 2 scores.

257 PC 2 0.03

Nicobar 0.02 Andaman Borneo 0.01 Vietnam Japan Burma Siberia PC 1 0.00 Philippines North China Indonesia Thailand -0.03- 0.02Mongolia - 0.01 0.00 Cambodia0.01 0.02 0.03 -0.01 Laos

-0.02

-0.03 South China

-0.04

Fig 9.1. Mean dispersion of East Asia (pooled sex) along PC 1 (27.0%) and PC 2 (17.7%). Lateral wireframe and rendered anterior profiles depict shape changes at the extreme of each axis. Northeast Asia,'; East Asia sensu stricto,; mainland Southeast Asia,; island Southeast Asia, .

258 No obvious groupings or separations are observable between East Asian populations on PCs 3-6.

9.2.1.2 Latitude Permutation tests (1000 random permutations) of the East Asian pooled sex sample indicated that the Procrustes distances between regional (Procrustes) means (Northeast, East sensu stricto, mainland and island Southeast) are statistically significant (table 9.2). Each regional grouping is thus significantly different in mean cranial shape to the remaining three East Asian groups. This result lends support to the separation of these regions in all the preceding analyses. Based on these results, object scores from PCs 1-6 were subjected to multiple regression to determine if shape changes could be attributed to the effects of latitude. A significant result was returned for PC 1 only (R2 = 0.61, p < 0.001). Figure 9.2 displays a plot of PC 1 scores versus latitude. The plot clearly shows that populations from the highest latitudes (Northeast Asia, Japan and North China) exhibit negative scores, while those from low latitudes display positive scores. Transformation grids and rendered images show the shape changes associated with latitude (fig 9.2 A-D).

Table 9.2. Pooled sex Procrustes distances between each geographical region of East Asia sensu lato defined in the study. Upper half of table gives calculated Procrustes distances. Lower half of the table gives the permuted significance of the differences between the ‘regional’ means.

East Asia sensu Mainland Island Northeast Asia stricto Southeast Asia Southeast Asia

Northeast Asia 0.0311 0.0319 0.0368

East Asia sensu stricto 0.0263 0.0325 0.0329

Mainland Southeast Asia 0.0161 0.0181 0.019

Island Southeast Asia 0.0168 0.0215 0.007

259 Latitude 70

Siberia 60

50 Mongolia

North China 40 Japan 30 A B Vietnam South China 20 Burma Laos Thailand Andaman Nicobar Cambodia 10 Philippines

Borneo 0 PC 1 -0.03 -0.-0.03 03 -0.02 -0.02 -0.01 -0.01 0.00 0.01 0.01 0.02 0.02 0.03 -10 Indonesia

-20

C D Figure 9.2. Pooled sex PC 1 vs Latitude (R2= 0.61, p < 0.001). Anterior and lateral rendered images and anterior coronal (A,B) and lateral mid-sagittal (C,D) transformation grids show variation in cranial shape on PC 1 extreme negative (A and C: PC1=-0.03) and extreme positive (B and D: PC1=0.03). Northeast Asia,'; East Asia sensu stricto,; mainland Southeast Asia,; island Southeast Asia, . 260 Changes observed in the PC 1 versus latitude analysis echo those observed above on PC 1 versus PC 2 object scores (fig 9.1). Populations with low scores (Northeast Asia, Japan and North China) are characterised by a long, low cranial vault with a long, flat face (fig 9.2 A and C), while Southeast Asian populations (positive scores) exhibit a short, broad face with a high, rounded vault and broad superior parietal breadth (fig 9.2. B and D).

9.2.1.3 Centroid Size The relationship between mean centroid size and PCs 1-6 was assessed with multiple regression to determine if observed shape changes between East Asian groups could be influenced by cranial size. A significant correlation was found for PCs 1 and 2, indicating that allometry is apparent on these axes. A plot of PC 1 object scores and mean centroid size (R2 = 0.34, p < 0.01) is provided in figure 9.3. Populations from Northeast Asia and East Asia sensu stricto exhibit the highest mean centroids, and with the exception of South China, display negative PC 1 scores. Remaining populations cluster with lower mean centroids, exhibiting positive scores The Andaman sample is clearly distinct from all East Asian populations, possessing a significantly smaller mean centroid. Warped transformation grids and rendered images portray shape changes between negative and positive extremes of the x-axis (-0.03 and 0.02 respectively). Populations exhibiting positive object scores (mainland and island Southeast Asians) are characterised by a high, short cranial vault, broad parietal breadth and a broad short face (fig 9.3 B and D). Warping towards the extreme negative axis displays these populations (Northeast Asia, Japan and North China) as possessing a long and low vault, long mid-face (pr-ns) and narrow superior cranial breadth (biparietal breadth). Alveolar projection (prognathism) is marginally reduced in negatively scored populations compared to positively scored samples. A regression between centroid size and latitude yields no significant correlation unless the Andaman sample is removed (r = 0.75, p = 0.002). Thus, unlike Chapter 8, there appears to be clinal variation in body size within East Asia, but only if the Andaman sample, which is cranially very small, is not included.

261 Centroid size 525 Mongolia Siberia 520 North China South China 515 Vietnam Japan Borneo Laos 510 Indonesia Thailand PhilippinesCambodia 505 Nicobar Burma A 500 B 495

490

485 Andaman 480

475 PC 1 -0.03 -0.03 -0.02 -0.02 -0.01 -0.01 0.00 0.01 0.01 0.02 0.02 0.03

C D Figure 9.3. Pooled sex PC 1 vs Centroid size (R2= 0.34, p < 0.01). Anterior and lateral rendered images and anterior coronal (A,B) an d lateral mid-sagittal (C,D) transformation grids show variation in cra nial shape on PC 1 extreme negativ e (A a nd C: PC1=-0.03) and extrem e positive (B and D: PC1=0.02). Northeast Asia,'; East Asia sensu stricto,; mainland Southeas t Asia,; island Southeast Asia, .

262 Centroid size 525 Mongolia Siberia 520 South China North China 515 Japan Vietnam Laos Thailand Borneo Cambodia 510 Philippines Indonesia

505 Burma Nicobar

500 A B 495

490

485

480 Andaman

475 PCPC22 -0.-0.0404 -0.03 -0.02 -0.01 0.00 0.01 0.02 0.030.03

C D Figure 9.4. Pooled sex PC 2 vs C entroid size (R2= 0.28, p < 0.05). Anterior and lateral rendered images and anterior coronal (A,B) and lateral mid-sagittal (C,D) transformation grids show variation in cranial shape on PC 1 extreme negative (A and C: PC 2=-0.03) and extreme positive (B and D: PC 2=0.02). Northeast Asia,'; East Asia sensu stricto,; mainland Southeast Asia,; island Southeast Asia, .

263 Figure 9.4 is a plot of PC 2 object scores versus mean centroid size. Regression analysis revealed a weak, but statistically significant correlation between the two variables (R2 = 0.28, p < 0.05). The figure shows Northeast Asia and East Asia sensu stricto, the populations possessing high mean centroids, as displaying negative PC 2 scores, a majority of island Southeast Asians, who typically demonstrate low centroid sizes, as possessing positive scores. Mainland Southeast Asians overlap between negative and positive PC 2 scores. The morphology that characterises the extreme positive axis (0.03), and thus small centroids, is a long, tall and superiorly broad vault and narrow facial skeleton (fig 9.4 B and D). The extreme negative axis (high centroids; -0.04) demonstrates a broad, flat face, and a short and narrow cranial vault (fig 9.4 A and C). Due to considerable overlap between most samp les around the origin of the x- axis, the observed shape differences are likely to be heavily influenced by, and thus reflective of, the samples isolated at the peripheries of the plot. Removing the Andaman Islands sample to assess the effects of cranially small populations on the analysis has little effect on the significance and plotting on PC 1 (not shown). A significant correlation was also observed on PC 3 after the removal of the Andaman Islands sam ple. Figure 9.5 is a plot of PC 3 object scores versus mean centroid size (R2= 0.32, p < 0.01). Northeast Asia is clearly separate from all remaining populations, possessing the largest mean centroids and the highest negative PC 3 scores. All remaining samples displa y predominantly positive scores, although a number of populations with small centroids exhibit negative scores. These populations however, possess weaker negative scores than those of Northeast Asia. Shape changes associated with the extreme negative (-0 .02) and positive (0.03) object scores are: a short, round cranial vault and long face is observed at the extreme negative, while a long, tall vault with narrow post-orbital and a short face with marked alveolar projection (at the extreme positive) (fig. 9.5 A-D).

264 Centroid size 524 Mongolia 522 Siberia 520 South China 518 North China 516

A 514 Vietnam Japan B 512 Laos Philippines Borneo 510 Thailand Indonesia Cambodia 508

506 Nicobar 504 Burma

502 PC 3 -0.025 -0.02 -0.015 -0.01 -0.005 0 0.005 0.01 0.015 0.02 0.0250.03

C D

Figure 9.5. Pooled sex PC 3 vs Centroid size (R2= 0.32, p < 0.01) after the Andaman Islands are excluded. Anterior and lateral rendered images and anterior coronal (A,B) and lateral mid-sagittal (C,D) transformation grids s how variation in cranial shape on PC 3 extreme negative (A and C: PC3=-0.02) and extreme positive (B and D: PC3=0.03). Northeast Asia, '; East Asia sensu stricto,; mainland Southeast Asia,; island Southeast Asia, .

265 Thus, cranial length and breadth appear to be the features most affected by centroid size (ie. longer length, broad post-orbital breadth, narrow biparietal breadth associated with larger centroids), with similar patterns of variation of these f e atures a lso observed in the latitude analysis. Based on correlation coefficients (R2), latitude has a stronger influence on vault shape than overall size, as well as having a strong influence on facial shape, as facial shape variation is not as prevalent in the centroid analysis.

9.2.2 Male-Only 9.2.2.1 Sample Dispersal Mean data (Procrustes means) for each sample was analysed with PCA to examine the phenetic relationships between East Asian male-only sa mples. Korean, Ainu and South Chinese samples have been excluded, as it was found that the inclusion of these n = 1 samples dramatically affected the results (see Chapter 8). Mean population dispersion was examined on PCs 1-6, which account for approximately 85% of total variance. Subsequent PCs each contribute less than 4% to the total variance, and 100% of the variance is explained by 14 principal components. Figure 9.6 is a plot of mean object scores for PC 1 (35.3%) and PC 2 (17.1%). Northeast Asia and East Asia sensu st ricto (Japan and North China) are clearly separate from mainland and island Southeast Asia on PC 1, with the northern populations possessing positive object scores, and all Southeast Asian samples exhibiting negative scores. Shape changes observed between the negative (-0.03) and positive (0.04) extremes of PC 1 show a long, flat face with anteriorly projecting malars, and a long and low vault in samples with positive scores, and a tall, rounded vault with broad superior cranial breadth, a short face and increased alveolar projection in populations exhibiting negative scores. Separation is observed on PC 2 between mainland and island Southeast Asia. Island populations, with the exclusion of Indonesia and the Philippines, exhibit high positive PC 2 scores, while the majority of mainland populations display negative scores. Northeast Asia possesses scores similar to the mainland Southeast Asian samples, while East Asia sensu stricto separates the island and mainland Southeast Asians, exhibiting low positive PC 2 object scores. Figure 9.6 demonstrates the shape changes observed between PC 2 negative (-0.02) and positive (0.03) extremes, which is predominantly, changes between the samples from Andaman and Nicobar Islands and Borneo (positiv e) and remaining samples from East Asia sensu lato. A long vault, broad

266 PC 2 0.04

Andaman 0.03 0.03 Nicobar 0.02

0.02

Borneo 0.01 North China 0.01 Japan

Burma 0.00 PC 1 Vietnam -0.04 -0.03 -0.02 -0.01 0.00 0.010.020.030.04 Indonesia -0.01 Laos Philippines Thailand -0.01 Siberia Mongolia Cambodia -0.02

-0.02

Fig 9.6. Mean dispersion of Ea st Asia (male-only) along PC 1 (35.3%) a nd P C 2 (1 7.1%). La teral wireframe and rendered anterior profiles depict shape changes at the extreme of each axis. Northeast Asia, ' ; East Asia sensu stricto,; mainlan d Sou theast Asia,; island Southeast Asia, .

267 superior parietal breadth and more vertical frontal bone is observed in populations with high scores. A short cranial vault and long face are characteristics of populations with low, or negative, PC 2 scores. No obvious groupings of samples are observable between East Asian populations on PCs 3-6.

9.2.2.2 Latitude Permutation tests (1000 random permutations) of the East Asian m ale-only sample indicate that the Procrustes distances between regional means (Northeast, East sensu stricto, mainland and island Southeast) are statistically significant (table 9.3). Each East to Asian region is thus significantly different in mean cranial shape to the remaining three East Asian groups. Based on these results, object scores from PCs 1-6 were subjected multiple regression to determine if shape changes could be attributed to the effects of latitude. A highly significant result was returned for PC 1 only (R2 = 0.68, p < 0.001).

Table 9.3. Male-only Procrustes distances between each geographical regi on of East Asia sensu lato defined in the study. Upper half of table gives calculated Procrustes distances. Lower half of the table gives the permuted significance of the differences between the ‘regi onal’ means.

East Asia Mainland Island Northeast Asi a sensu stricto Southeast Asia Southeast As ia

Northeast Asia 0.0391 0.0386 0.0422

East Asia sensu stricto 0.0282 0.0463 0.0447

Mainland Southeast Asia 0.0174 0.0239 0.0203

Island Southeast Asia 0.0176 0.0262 0.0128

268 itudeLat 70

60 Siberia

50 Mongolia

40 North China B Japan A 30

Burma Laos Vietnam20 Thailand Cambodia Andama n Philippines 10 Nicobar

Borneo 0 PC 1 -0.04 -0.03 -0.02 -0.01 0.00 0.01 0.02 0.03 0.04 Indonesia -10

-20

C D Figure 9.7. Male-only PC 1 vs Latitude (R2 = 0.68, p < 0.00 1) . Anteri or and lateral rendered i mages and anterior coronal (A,B) and lateral mid-sagittal (C,D) transformation grids show variation in cranial shape on PC 1 ex treme n egativ e (A and C: PC1=-0.03) and ex treme positive (B and D: PC1=0.04). Northeast Asia,'; East Asia sensu stricto,; mainland Southeast Asia,; i sland S outhea st Asia, .

269 Figure 9.7 displays a plot of PC 1 object scores versus latitude. The plot clearly shows that populations with the highest latitudes (Northeast Asia, Japan and North China) exhibit high positive scores, while those with low latitudes displa y low negative scores. Transforma tion grids and rendered images show shape changes associated with latitudinal changes (fig 9.7 A-D). Northeast Asia, Japan and North China are characterised by a long, low cranial vault and a long face flattened in the alveolar region and projecting slightly anteriorly at the mid-face (fig 9.7 B and D). The northern samples also appear broader post-orbitally and across the zygom atics. Southeast Asian populations (negative scores) exhibit a short, more prognathic face, and a high rounded vault, with broad superior parietal breadth (fig 9.7 A and C).

9.2.2.3 Centroid Size The relationship between m ean centroid size and PCs 1-6 was assessed with multiple regression analysis to determine if observed shape changes between East Asian groups could be influenced by cranial size. A significant correlation was found for PC 2 only, indicating that allometric scaling is apparent on this axis. A plot of PC 2 object scores and mean centroid size (R2 = 0.62, p < 0.001) is provide d in figure 9.8. Samples from Northeast Asia exhibit the highest mean centroids, and display negative object scores. Mainland Southeast Asian sam ples exhibit lower negative PC scores, approaching zero, while island Southeast Asia is predominantly positive. East Asia sensu stricto possesses positive scores between island and mainland Southeast Asian samples. The Andaman sample is clearly distinct from all East Asian populations, possessing a very small m ean centroid. However, removing the Andaman sample from the analysis does not affect th e results, or the significance (R2 = 0.51, p < 0.001). Warped transformation grids and rendered profiles portray shape changes between negative and positive extremes of the x-axis (-0.02 and 0.03 respectively). Populations exhibiting positive object scores (East Asia sensu stricto and island Southeast Asian, excluding Philippines and Indonesia) are characterised by a long vault with high frontal bone, broad parietal breadth and a short, more prognathic face (fig 9.8 B and D). Warping towards the extreme negative axis displays these populations (Northeast Asia, mainland Southeast Asia) as possessing a short vault, long face and narrow superior cranial breadth.

270 Centroid size 535 Cambodia Siberia Mongolia 530 North China 525 Vietnam Philippines 520 Burma Indonesia Japan 515 Thailand Borneo Laos A B 510

505 Nicobar

500

495

490 Andaman 485 PC 2 -0.02 -0.02 -0.01 -0.01 0.00 0.01 0.01 0.02 0.02 0.03 0.03 0.04

C D Figure 9.8. Male-only PC 2 vs Centroid size (R2= 0.58, p < 0.001). Anterior and lateral rend ered images and ante rior coronal (A,B) and lateral mid-sagitta l (C,D) transformation grids show variation in cr anial shape on PC 1 extreme negative (A and C: PC 2=-0.02) and extrem e positive (B and D: PC 2 = 0.03). No rthea st Asia,'; East Asia sensu stricto,; mainland Sou theast Asia, ; island Southeast Asia , .

271 A significant correlation between centroid size and latitude (inclusive of Andaman Islands: r = 0.56, p = 0.04) is indicative of clinal variation in body size within East Asia sensu lato for ma le-only samples.

9.2.3 Female-Only 9.2.3.1 Population Dispersal Sample means (Procrustes means) were analysed with PCA to examine the phenetic relationships of female East Asia sensu lato. All East Asia sensu stricto samples and the Nicobar Islands sample have been excluded, as it was found that the inclusion of these small samples affected relationships considerably. M ean population dispersion was examined on PCs 1-6, which account for approximately 84% of total variance. Subsequent PCs each contribute less than 5% to the total variance, with 100% of the variance explained by 11 principal compon ents. Figure 9.9 is a plot of mean object scores for PC 1 (29.6%) and PC 2 (16.7%) and shows a near perfect north to south cline on the main axis. Northeast Asia exhibit high negative object scores, followed by mainland Southeast Asia with scores approaching zero, and island Southeast Asia with predominantly positive PC 1 object scores. Marring the north to south cline is the position of the sample from the Philippines, which cluste rs with the highly negative Northeast Asians. Removal of the Philipinnes from the analysis results in no change to phenetic relationships. The Andaman Islands clearly exhibits the highest PC 1 score, distinct from all other Asian samples. W arping along the PC 1 axis between the negative (-0.03) and positive (0.04) extremes shows a long, orthognathic face with anteriorly projecting malars, and rounded vault in samples approaching the extreme negative sco re, and a lengthened vault with broad superior cranial breadth, narrow post orbital breadth, and a short, more prognathic face towards the positive extreme. No clear sample divisions or grouping are observed on the orthogonal axis (PC 2), or subsequent axes (PCs 1-6).

272 9.2.3.2 Latitude Permutation tests (1000 random permutations) of the East Asia sensu lato female only samples indicate that the Procrustes distances between regional means (Northeast, mainland and island Southeast) are statistically significant (table 9.4). Female-only East Asia sensu stricto samples were not included, due to the affect that their inclusion had on phenetic relationships (above). Each remaining East Asia sensu lato region is thus significantly different in mean cranial shape to the remaining two East Asian groups. Based on these results, object scores from PCs 1-6 underwent multiple regression to determine if shape changes could be attributed to the effects of latitude. A significant result was returned for PC 1 only (R2 = 0.38, p = 0.01). Figure 9.10 is a plot of PC 1 object scores versus latitude. The plot clearly shows that populations with the highest latitudes (Northeast Asia) exhibiting the highest negative scores, with scores approaching positive with decreasing latitude. As above, a north to south cline is observable from Siberia to the Andaman Islands, with the exception of the Philippines, which once again demonstrate similar PC scores to Northeast Asia.

Table 9.4. Female-only Procrustes distances between each geographical region of East Asia sensu lato defined in the study. Upper half of table gives calculated Procrustes distances. Lower half of the table gives the permuted significance of the differences between the ‘regional’ means. East Asia sensu stricto was not included due to its affect on phenetic relationships (see above).

Northeast Asia Mainland Southeast Island Southeast Asia Asia

Northeast Asia 0.029 0.0382

Mainland Southeast Asia 0.0224 0.023

Island Southeast Asia 0.0211 0.0127

273 PC 2 0.03 Thailand 0.03

0.02

0.02

0.01 Mongolia Cambodia 0.01 Andaman Burma 0.00 PC 1 Laos Indonesia -0.03 -0.02 -0.01 0.00 0.01 0.02 0.03 0.04 -0.01 Philippines Vietnam -0.01 Borneo

Siberia -0.02

-0.02

Fig 9.9. Mean dispersion of East Asia (female-only sex) along PC 1 (29.6 %) and PC 2 (16.7%). Lateral wireframe and rend ered anterior profiles depict shape changes at t he extreme of each axis. Northeast Asia, '; mainland Southeast Asia,; island Southeast Asia, .

274 Latitude 70

Siberia 60

50 Mongolia

40

30

B A Burma 20 Vietnam Laos Cambodia Philippines Andaman 10 Thailand Borneo 0 PC 1 -0.03 -0.02 -0.01 0.00 0.01 0.02 0.03 0.04 -10 Indonesia

-20

C D Figure 9.9. Female-only PC 1 vs Latitude (R2= 0.38, p = 0.01). Anterior and lateral rendered images and anterior coronal (A,B) and lateral mid-sagittal (C,D) transformation grids show variation in cranial shape on PC 1 extreme negative (A and C: PC1=-0.03) and extreme positive (B and D: PC1=0.04). Northeast Asia,'; mainland Southeast Asia,; island Southeast Asia, .

275 Transformation grids and rendered images show the shape changes associated with the latitudinal changes (fig 9.10 A-D). Craniofacial morphology at the extreme positive (0.04) includes a long, broad (superior), depressed vault and a short, broad, prognathic face (fig. 9.10 B and D). The negative extreme (-0.03) is characterised by a more rounded vault as a result of a flattened and lengthened occipital bone, and a long, forward projecting mid-face and orthognathic lower face. Superior breadth is narrower than in the positive samples (eg. Andaman Islands), and postorbital breadth is broader. Both breadth variables appear similar in the negatively scored populations (egM ongolia, Siberia, Philippines), giving the vault a rounded appearance anteriorly (fig 9.10 A and C).

9.2.3.3 Centroid Size The relationship between mean centroid size and PCs 1-6 was assessed with multip le regression to determine if observed shape changes between East Asian females coul d be influenced by cranial size. A weak but significant correlation was found for PC 1 only, thus allometry is explaining some o f the observed variation on this axis. A plo t of PC 1 object s cores and mean centroid size (R2 = 0.27, p < 0.05) is provided in figure 9.11. Northeast Asians are among samples possessing the highest mean centroids, and exhibiting negative PC 1 object scores, together with the Philippines, are distinct from Southeast Asia. As a bove, a north to south cline is observable, with mainland Southeast Asian samples situated between island Southeast Asia and Northeast A sia, which exhibit positive and negative scores, respectively. The Andaman sample is cle arl y distinct from all East Asian populations, possessing the smallest m ean centroid. Removing the Andaman Islanders from the analysis resulted in no significant correlation of shape and centroid size. Warped transformation grids and rendered profiles (fig 9.11 A-D) portray shape changes between negative and positive extremes of the x-axis (-0.03 and 0.04 respectively). Populations exhibiting positive object scores (ie Andaman Islands) are characterised by a broad superior and narrow inferior (post orbital) cranial breadth and a short, broad face (fig 9.11 B and D). Warping towards the extreme neg ative axis displays these populations (Northeast Asia, Philippines) as possessing a more rounded and taller vault that is narrower superiorly, with a long

276 Centroid size 515 Laos 510 Siberia Mongolia 505 Vietnam Cambodia 500 Borneo

495 Philippines Indonesia Thailand Burma 490 A B 485

480

475

470 Andaman 465 PC 1 -0.03 -0.02 -0.01 0.00 0.01 0.02 0.03 0.04

D C Figure 9.11. Female-only PC 1 vs Centroid size (R2= 0.27, p = 0.05). Anterior and lateral rendered images and anterior coronal (A,B) and lateral mid-sagittal (C,D) transformation grids show variation in cranial shape on PC 1 e xtrem e nega tive (A and C: PC 1=-0.03) and extreme positive (B and D: PC1=0.04). Northeast Asia,'; mainland Southeast Asia,; island Southeast Asia, .

277 narrow face (fig 9.11 A and C). No correlation of size with latitude was apparent for the female-only sample.

9.3 Summary and Conclusions

Distinctions observed between northern and southern East Asian samples previously in Chapter 8 were analysed in greater detail above. The geographic groupings comprising East Asia sensu lato used in the preceding chapters (ie. Northeast Asia, East Asia sensu stricto, mainland Southeast Asia and island Southeast Asia) were found to be justified, as they were all found to significantly differ from one another (tables 9.2-9.4). The northern cluster tended to contain Northeast Asia, Japan and North China, while the southern cluster involved all remaining East Asia sensu lato samples. Major shape differences between these two clusters were a long low vault with narrow parietal breadth in the north and a superiorly broad (parietal breadth) cranial breadth, tall heig ht and short length in th e sou th. Differences of the facial region include a tall, orthognathic face in the northern p opulations (No rtheast Asia, Japan and North China) and a shorter, more prognathic face in South China and Southeast Asia, The mid-facial region also differed between the two clusters, with a more vertical morphology in northern samp les, and a concave mid-face in the southern samples. The shape differences described above were all significantly correlate d with latitude, while features of cranial length and cranial breadth were also correlated with centroid size. These results are consistent with those of Chapter 8, where it was apparent that while allometric scaling effects explai ned some of the observed variation, particularly variation in cranial vault shape, latitude has a stronger correlation with cranial shape, as evidenced by higher correlation coefficients. Pooled sex and male-only samples exhibited a significant correlation with size, thus indicating variation in size (cranial and body) is clinal. The fact that female- only samples do not exhibit correlations between these two factors may be due to the smaller sample sizes for female samples (table 9.1), sexual dimorphism or reflection of sex-specific population histories, as found in other regions (Perez et al, 2007). A division between mainland and island Southeast Asia was also observed, with the mainland samples exhibiting the southern morphology described above (tall, rounded vault with short, prognathic face). The island samples exhibited a mixed

278 morphology, retaining the shortened, prognathic features of the mainland cluster, but exhibiting a long, low vault like that of the Northeast Asians. When reviewing the sample dispersions in Chapter 8, island Southeast Asians samples Andaman and Nicobar Islands tended to cluster with the Africa, Australia, Melanesia cluster, while Borneo was intermediate between the aforementioned samples and mainland Southeast Asia. These samples are from low latitudes, suggesting that vault shape is affected by climate. However, the climate argument does not wholly explain the long, low vault of the northern East Asian samples, which contradicts the purported vault shape of cold-climate populations (ie. broad and round headed). This suggests that other factors, such as neutral genetics, may also be determining vault shape (Roseman, 2004; Harvati and Weaver, 2006a, b).

279 Chapter 10 Summary and Discussion

10.1 Summary

The primary aims of the present study are presented below. A summary of the results of the study that address these aims is also presented:

1. To undertake a comprehensive metrical assessment of the morphology of the cranium of contemporary East Asians for the purpose of understanding variation within this region and between East Asians and other populations

A total of 55 landmarks were obtained from 530 crania from 16 contemporary East Asian and non-Asian populations using a 3D digitiser. These landmarks were converted to 45 linear measurements, 23 indices and 14 angles, which were then subjected to univariate and multivariate analyses. Additionally, they were studied with geometric morphometric analyses in order to assess and visualise cranial morphology in three dimensions. By employing three methods of analysis, variation was assessed more comprehensively than in most published studies of cranial morphology. Univariate analysis enabled the assessment of variation within and between samples on a variable by variable basis, identifying features that exhibited apparent divisions between samples. Multivariate analysis (PCA) identified combinations of features that explain the majority of observed variation between samples and allowed identification of important contributing variables. The advantage that 3D analysis had over PCA is that the variation between samples was not just quantified (as with PCA), but visualised, targeting the specific regions on the cranium that differed between samples, and allowed assessment of the effect of the environment t on size and shape. These data were analysed in three samples; pooled sex (sex aggregated), male- only and female-only (sex disaggregated), so as to assess the presence of sex specific effects and trends. Results for pooled sex and male-only samples tended to closely resemble one another, while female-only samples exhibited differences to pooled and male samples in phenetic associations for some variables. These discrepancies may be

280 attributed smaller sample sizes in the female-only samples. In other words, male-only samples predominantly exhibited larger sample sizes in comparison to females, possibly resulting in a disproportionate impact on the central tendencies of the sex aggregated samples. However, Box and Whisker plots (Chapters 4-6) showed that samples were mostly normally distributed, with the exception of very small sample sizes (n < 5). If males were disproportionately influencing sample medians, the sample would have been positively skewed. Other possible explanations for observed discrepancies between sex disaggregated samples could be that both samples are reflecting sex-specific morphological differences as a result of sexual dimorphism, or complex sex-specific population histories, as found in other regions (Perez et al, 2007).

2. To broaden the geographical sample of East Asian groups and in doing so, more comprehensively describe and define the cranial morphology of contemporary East Asians and better understand causes of variation

Previous craniometric (e.g Brace and Tracer, 1992; Hanihara 1997; Pietrusewsky and Chang, 2003), dental (e.g. Turner, 1987; Irish, 1998) and genetic (e.g Chu et al, 1998; Ding et al, 2000) studies in East Asia have tended to focus on populations from China, Japan and island Southeast Asia, presumably because the fossil evidence in East Asia has predominantly surfaced in these areas. The current study has expanded on these studies by also including populations from Northeast Asia to the Andaman and Nicobar Islands. Broadly, the collective sample has been defined as East Asia sensu lato, with subdivisions Northeast Asia, East Asia sensu stricto, mainland Southeast Asia and island Southeast Asia (see Materials and Methods for further details). These populations were assessed alongside some non-Asian populations (Africa, Australia, Melanesia, Micronesia, Caucasian and Native America) to help identify possible cranial features that broadly distinguish contemporary East Asians. All methods of analyses (univariate, multivariate, 3D) revealed overlap between East Asia sensu lato and comparative samples with no single cranial variable that divides East Asians from non-East Asians. Moreover, Caucasians and Native Americans commonly cluster with East Asians. Siberians, Andaman and Nicobar Islanders are sometimes observed sharing features with Africans, Australians and Melanesians, features not exhibited by other East Asians. In comparison to the majority of non-Asians included in this study, East Asians may be broadly defined as a group by a:

281 o high, rounded cranial vault o short cranium (anterior-posterior) o long, flat, face in the upper nasal and mid-facial regions o orthognathic face o short malar (zygomatic) and palate lengths o narrow interorbital breadth o rounded post-orbital region (absence of constriction)

It is important to note, however, that all of these features have been found in the present study to be significantly correlated with latitude. This will be discussed further below.

3. To assess for the presence of proposed morphological trends associated with geography/latitude within East Asia

North-south East Asian divisions have previously been identified on the basis of craniometric (e.g Coon, 1962; Brace and Tracer, 1992; Hanihara, 1994; Pietrusewsky and Chang 2003), dental (Turner, 1987; Irish, 1998) and genetic evidence (e.g. Chu et al, 1998; Yoshiura et al, 2005). A distinction between northern and southern Chinese populations has also been suggested on the basis of genetics and metric and non-metric cranial data (Etler, 1992; Chu et al, 1998; Zhao et al, 2005). The present study sought to assess the presence of the proposed north-south divisions both within East Asia sensu lato and within China. Univariate, multivariate and 3D analyses showed clear distinctions between the northern samples from Northeast Asia, North China and Japan and all remaining East Asian samples. The Northern samples are characterised in the extreme by the following features:

o Long, low, vault o Broad vault (anterior and posterior) o Tall, flat, facial skeleton (upper and mid-facial) o High degree of orthognathism (flat alveolar region)

While southern samples exhibit:

282 o Tall, rounded, vault o Narrow cranium (anterior and posterior) o Short, broad, facial skeleton o Projecting of superior and inferior nasal bones o Projecting alveolar region (prognathism)

Separation between mainland and island Southeast Asian samples on the basis of vault shape was also found, with island samples from Borneo and the Andaman and Nicobar Islands exhibiting long, low, and broad vaults in comparison to the high, rounded, vaults of the mainland samples. It is interesting to note that the island Southeast Asians exhibit similar vault shape to the extreme Northeast Asians (discussed below). Small sizes of the Chinese samples, particularly sex disaggregated, meant that an accurate assessment of the proposed north-south divisions within China was difficult, as the samples, in particular those from South China, may not be a true representation of the mean/median for that population. Further studies with larger sample sizes are required before any conclusion can be made.

4. For the first time, apply cutting edge morphometric approaches to the question of cranial variation in East Asia and in so doing, contribute to understanding the causes of cranial variation in a region that today contains around half of the world’s population

Three dimensional geometric morphometric methods were applied in the current study as both a data collection and analysis tool. As Chapters 9 and 10 have demonstrated, this method has proven very useful in demonstrating and quantifying morphological shape differences, as well as aiding in the explanation of the causes of variation that may otherwise have not been observable using traditional linear analyses. The methods utilised in the current study allowed for instant visualisation of shape changes between samples in three dimensions, while also providing explanations for these observed differences, ie. latitude and size. Compared to standard methods of interpreting two- dimensional linear shape indices, this method was considered more efficient and provided greater detail in the current study.

283 The 3D technique was also able to both clarify and refute previously described characteristics of East Asians (see Discussion below), as well as identify features that challenge previously conceived theories. For example, in the present study, cold-climate Northeast Asians exhibited long, low cranial vaults, which is a contradiction to the heat- preserving rounded vaults described in the literature (e.g Coon, 1955; Beals et al, 1983; Hernandez et al, 1997). A number of benefits were identified by using a geometric morphometric method of data collection in place of standard caliper methods. These include:

o New variables, both linear and angular, could be created and assessed for their diagnostic abilities. Calipers are unable to access all sutures, fossae, protuberances etc. Thus, the method allows for the easy definition and recording of novel measurements, angles and points that are study/question specific o By converting the three-dimensional x, y and z co-ordinates into linear variables, results are thus comparable to previous and future linear studies. Also, both linear and 3D analytical methods can be applied to the data, adding to the statistical power of the results o The method is non-invasive and relatively efficient

10.2 Discussion

10.2.1 Current versus Previous Research The defining features of East Asians described above in part concur with previous studies, which describe modern East Asian characteristics of a rounded vault with a tall and flat facial skeleton (e.g. Blumenbach, 1865; Hanihara, 1994; Ishida and Dodo, 1997) in comparison to non-Asians. Flatness of the upper and mid-face, and a lack of prognathism, appear to be retained primitive features, with studies describing these features as ‘defining’ features of fossil human Chinese (Wolpoff et al, 1984; Pope, 1992; Wu, 2004). A clear north-south division was observed within East Asia sensu lato which was significantly correlated with latitude. Populations from Northeast Asia, Japan and North China exhibited long and low cranial vaults and the longest, flattest, and most

284 orthognathic facial skeletons. Southern populations, with the exception of the Andaman and Nicobar Islanders, demonstrated a high, short, and superiorly broad vault, more vertical frontal bone and shorter, more projecting (prognathic) faces. The Andaman and Nicobar samples appeared to display a combination of the two above morphologies: the long, low, vault of the northern samples, and the shorter, more prognathic faces of the southern samples. This combination of features saw the Andaman and Nicobar samples clustering with non-Asians (Africa, Australia, Melanesia and Micronesia) when all samples were analysed together, and the southern East Asian samples when assessing East Asia sensu lato alone. The Andaman sample also tended to be separate from all samples on the basis of size, commonly exhibiting the smallest features. The long, low vault observed in the Northeast Asians, the Andaman and Nicobar Islanders (when analysed with non-Asians), as well as comparative samples from Africa, Australia and the Pacific, has also been observed in fossil East Asians (Weidenreich, 1939; Wu, 1959, 1961; Brown, 1999) and thus may be considered a ‘primitive’ feature. The retention of differing fossil features in both northern and southern East Asian populations, and what appear to be common features between Northeast Asia and comparative samples from Africa, Australia and the Pacific, thus raises questions about the population histories of the East Asian samples. Unfortunately, these issues are beyond the scope of the present study and will be addressed in future research.

10.2.2 Defining the East Asian Cranial Form Based on the results of this study, it is apparent that defining the morphology of any population, in this case East Asia sensu lato, is difficult. At no time in the study did a single variable stand out that distinguishes all East Asian samples from non-Asians, with overlap between samples commonplace. Thus, there are no ‘absolutes’ when defining East Asian cranial form. However, it has been demonstrated (above) that a combination of features serves to broadly distinguish East Asians from non-East Asian populations. These features are not uniform within East Asia, with obvious and significant shape differences observed between northern and southern populations (above). Below is a discussion of the predominant cranial features that define East Asians from others, and the causes of the observed variation.

285 10.2.2.1 Vault Shape Studies by Beals et al (1983) and Roseman (2004) have suggested that the shape of the neurocranium is related to climatic adaptation, with a brachycephalic shape (cranial index of 80.00-84.99, broad or round headed) suited to colder climates (Coon, 1955; Beals et al, 1972; Hernandez, 1997). Despite not using the standard cranial index in the present study, results do not follow these published findings. Linear analyses showed Southeast Asians, who inhabit tropical environments, to have broad and short crania, while warmer-climate comparative groups, particularly Africa, Australia, Melanesia and Micronesia, have long and narrow crania. Northeast Asian samples from cold-climates exhibit broad and long crania, dimensions that do not fit neatly into purported cranial shape adaptations for cold climate populations. The results of the 3D analysis also showed that the Northeast Asians exhibit long and low vaults. This finding rejects the theory that a broad, rounded, head is a cold-climate adaptation for the purposes of heat retention (e.g. Coon, 1955; Beals et al 1983; Hernandez, 1997) as it was not a feature of the samples from cold climates in the present study. A study by Harrison et al (1964) found that some Eskimo populations are notably dolichocephalic (long and narrow), thus adding support to the rejection of the ‘brachycephalic = cold climate hypothesis’. In addition, the 3D results showed Northeast Asians and the warm-climate comparative samples from Australia, Africa, Melanesia and Micronesia as both exhibiting this long, low cranial shape. This could possibly be explained by retention of ancestral features by these populations, as dolichocephaly was the common condition in Pleistocene crania (Hernandez, 1997), irrespective of climate. Support for the current findings may lie in Roseman (2004) and Harvati and Weaver (2006a), who suggest that a combination of natural selection and neutral genetics determines cranial shape.

10.2.2.2 Facial Flatness The definition of ‘facial flatness’ in the literature is unclear, yet the degree of flatness is a feature of the facial skeleton that is constantly referred to in biological anthropology (e.g Woo and Morant, 1934; Woo, 1937; Brown, 1992; Ishida, 1992; Dodo et al, 2000; Hanihara, 2000; Sardi et al, 2005). Facial flatness is customarily discussed when describing two kinds of measurements: 1) angular measurements in the median sagittal plane, usually describing prognathism (projecting jaw) or projection of the nasal bones,

286 and 2) transverse flattening of the face (Woo and Morant, 1934). In the current study, angular measurements of both the median sagittal plane (e.g NAA) and transverse plane (e.g mSSA) between nasion and nasospinale are defined as ‘facial flatness’ variables, while those describing projection or flatness of the alveolar bone (ie between nasospinale and prosthion) are defined as descriptors of prognathism. While these latter angles are a form of facial flatness, in the present study, they are considered a separate set of descriptive variables. In the present study, variation in facial flatness and alveolar projection (prognathism) was commonly observed to distinguish East Asians from comparative populations and northern East Asian samples from southern. The flatter facial skeletons of the East Asians in comparison to Australians, Africans and Melanesians, as found in the current study, is consistent with results found in previous studies (Howells, 1989; Bass, 1995; Hanihara, 1997, 2000; Ishida and Dodo, 1998; Hennessy and Stringer, 2002). The variation of facial flatness observed within East Asia sensu lato (ie, flat, orthognathic faces in northern populations) and more projecting faces in southern populations, is also consistent with the findings of previous studies (e.g Howells, 1989; Ishida and Kondo, 1998; Hanihara, 2000). A number of studies have suggested that marked flatness, particularly of the nasal region, is an adaptive response to an extreme cold climate and/or biomechanical efficiency (Coon et al, 1950; Garn, 1965; Száthmary, 1984; Ishida, 1992; Viðarsdóttir et al, 2002; Harvati and Weaver, 2006a). A study by Hanihara (2000) suggested that the flat faces of East Asians, particularly Northeast Asians, may be an example of the ‘regional characters’ of East Asians as summarised by Wolpoff (1992), suggesting that modern East Asian morphology is derived from a Pleistocene fossil East Asian source, reflecting an ancestor-descendant relationship. This proposed relationship between archaic and modern East Asians and the correlation of facial features with climate potentially has important implications for palaeoanthropology. The fact that facial flatness is apparent in both Pleistocene and modern East Asians, and that this feature is strongly associated with latitude (and thus climate; Ruff, 2002), suggests that facial flatness might be unreliable for inferring phylogeny. Alveolar projection (prognathism) was found in the present study to be a significant discriminating trait, both between East Asia sensu lato and comparative (non-Asian) samples, and between northern and southern East Asian populations. Glanville (1969) concluded that alveolar prognathism, intercanine distance and nasal

287 morphology are linked, and that interpopulation differences are most likely due to environmental stresses on one or more of these features. Glanville (1969) also postulated that as nasal morphology is determined by climatic factors, and prognathism and nasal shape are linked, variation in prognathism might also be linked to climate. Brown (1992) stated that prognathism and posterior tooth size are functionally related (large posterior teeth = pronounced prognathism). Changes in tooth size have also been attributed to dietary differences (e.g Brace, 1978; Aiello and Wells, 2002) and overall body size (Sofaer, 1973; Macchiarelli and Bondioli, 1986). Tooth size, and its association with alveolar projection, was not examined in the present study. However, variation in prognathism observed in the present study, from the orthognathic East Asians to the marked prognathic faces of the Australians, is consistent with the literature (eg. Lahr, 1996; Hanihara, 2000; Brown and Maeda, 2004). Conversely, the findings of a study by Viðarsdóttir et al (2002) raised questions as to the plasticity of facial growth patterns, thus challenging the theories above. According to this study (Viðarsdóttir et al, 2002), alveolar projection is believed to be determined by population specific ontogenetic trajectories, and that distinctive features of facial shape that distinguish modern populations are probably already present at birth.

10.2.2.3 The Malar (Zygomatic) In his metrical study Woo (1937) concluded that chord and arc measurements of the malar were effective in differentiating geographic groups, and that ‘racial’ variation of the bone was correlated with geographic variation in facial flatness (Woo, 1937; Kean and Houghton, 1990). Measures of the malar in the current study are not directly comparable to those of Woo (1937). However, a modified malar length variable (IML) used in the present study does separate East Asian and the majority of non-Asian samples, and thus a correlation with facial flatness variation, as described by Woo (1937), may still apply.

10.2.3 Geometric (3D) Morphometrics The use of geometric morphometric techniques, although relatively recent, is becoming widespread in many scientific disciplines, including biological anthropology (e.g. Hennessy and Stringer, 2002; Harvati, 2003; Pan et al, 2003; O’Higgins and Pan, 2004; Franklin et al, 2006). These methods of data collection and statistical analysis are considered to be advantageous relative to traditional methods because the physical

288 integrity of the object being studied is preserved, rather than collapsing the object into a series of linear and angular measures in which aspects of ‘shape’ are generally lost (Harvati, 2003; Franklin et al, 2006). The technique is non-invasive, and allows for the capture, modification and analysis of a greater volume of data that would otherwise be impossible (Nasab, 2006). Perhaps the greatest advantage is the ability to visualise and more comprehensively analyse statistically shape differences (Pan et al, 2003), thus providing a means of studying these shape differences that traditional methods can only deal with qualitatively and inadequately (Harvati, 2003; Nasab, 2006). In the present study, landmark data were collected using a 3D digitiser and Rhinoceros, a computer software program that allowed for the instant visualisation of landmarks. This method is efficient and allows for storage of a large volume of data to be analysed at a later time. This method of data collection also enables the present study to be comparable to previous (traditional) work, with the landmark data readily being converted into linear and angular measures. The software program Morphologika (O’Higgins and Jones, 1996) was used to analyse the landmark data in 3D form, allowing the identification and visualisation of shape differences between individual specimens and group means. This method of analysis quantitatively identified shape differences, particularly those between northern and southern East Asian samples (e.g. long, low, vault versus high, rounded, vault), that appears to be previously unreported. The answers to specific questions, such as the effects of latitude (and thus climate) and size on cranial shape, were able to be both quantified and visualised, with the results generated from these analyses providing a valuable contribution to the understanding of variation and its causes.

289 Chapter 11 Conclusions 11.1 Conclusion

The present study was designed to comprehensively assess cranial variation of contemporary East Asians for the purposes of better understanding causes of observed variation and in doing so, describe and define their cranial morphology. The study also aimed to utilise an innovative approach to data collection and analysis in the form of geometric morphometrics to assess the aims above. Attempts to collect data from an equal number of individuals from each population, as well as similar numbers of male and female samples, was restricted by the use of museum specimens, which were often unsexed and incomplete. This resulted in some populations, such as those from East Asia sensu stricto (Korea, Ainu, Japan and North and South China), being represented by small sample numbers in comparison to remaining populations in the study, particularly when the sex aggregated sample was disaggregated to sex-specific samples. Despite these limitations, a comprehensive study of East Asian cranial morphology was produced from the available data, using an innovative data collection and analysis technique (geometric morphometrics) for the first time to assess cranial variation in this region. A large degree of East Asian inter-group variation was apparent throughout the study, with significant shape differences observed between northern and southern East Asian samples. Northern populations (Northeast Asia, Japan and North China) are characterised by a long, low, vault with a long, orthognathic, face. This is in contrast to the tall, rounded, vault, shortened face and increased prognathism observed in mainland Southeast Asians. Island Southeast Asian populations, particularly Andaman and Nicobar Islanders, appear to retain the mainland facial form, but differ in vault shape, exhibiting a long, low vault similar in shape to Northeast Asians. The changes in cranial shape are significantly correlated with latitude/climate, yet cannot be wholly explained by this. The long, low, vault of the cold-climate (high latitude) northern samples is similar in shape to warm-climate (low latitude) samples from Africa, Melanesia and Australia and is thus in contradiction to the brachycephalic shape (broad or round) previously proposed for cold climates (e.g Coon, 1955; Hernandez, 1997). Both facial

290 flatness and a long low vault have been suggested to be retained fossil East Asian features (Weidenreich, 1939; Wu, 1959; Wolpoff et al, 1984, Pope, 1992; Wu, 2004). The degree of inter-group variation within East Asia (above) meant that the identification of ‘defining’ cranial features of East Asians was difficult. Adding to the difficulty was a certain amount of overlap between Asian and non-Asian samples. In spite of this, a suite of features were identified that distinguished East Asians from a majority of non-Asian samples in the present study. These ‘defining’ East Asian features are: o high, rounded, cranial vault o shorter cranial length o long, flat, faces in the upper nasal and mid-facial regions o orthognathism o shorter malar and palate length o shorter interorbital breadth o rounded post-orbital region It is apparent from the results that explaining observed variation in modern humans is complex. In the present study, the modern cranial form appears to be a mix of climate and phylogeny, as evidenced by significant correlations between shape and latitude and the identification of ancestral phenotypes (see above) in some samples (Siberia and Andaman and Nicobar Islands). These finding thus have important implications for palaeoanthropological studies in that 1) the presence of fossil features in these selected samples may have an effect on purported theories on the origins and affinities of the modern East Asian form and 2) if these ancestral features (ie. facial flatness) are indeed affected by climate, they may be unreliable for inferring phylogeny.

11.2 Areas of Future Research The current study has highlighted that more research into the effects of climate on contemporary cranial form is needed. Proposed future studies may involve the disentangling of climate controlled features from phenetic studies (previous and future) in a hope to reveal genetically determined features, and thus provide a better understanding of the causes cranial variation. Alternatively, a combined craniometric and genetic study may reveal those features that retain a genetic signal, thus revealing the features that are most susceptible to environmental and other non-genetic effects.

291 More detailed analysis of the presence of ancestral features in modern East Asians, the associations of these features with climate, and the implications these features have on the population histories of this region is also warranted. Further study within China is suggested in order to assess the proposed north- south division that were otherwise not accurately determined in the present study due to small samples. Also, as China has been suggested as the original homeland of East Asia sensu lato a detailed phenetic-genetic study of contemporary Chinese crania may reveal new or more detailed information on the population history China, and in doing so, may further the understanding of population histories of surrounding populations. Geometric morphometrics, while fast becoming more widespread in biological anthropology, is still in its infancy. Thus further investigation into its capabilities, as well as more sophisticated methods, such as 3D scanning, is suggested for future studies. The latter method may be advantageous in revealing more detailed shape changes, as the method reproduces more surface detail, as opposed to landmark point clouds that form more rigid shapes.

292 References

Aiello LC and Wells JCK (2002). Energetics and the evolution of the genus Homo. Annual Review of Anthropology 31, 323-328.

Anderson D and Popovich F (1983). Relation of cranial base flexure to cranial form and mandibular position. American Journal of Physical Anthropology 61, 181-187.

Antón SC and Swisher CC (2004). Early dispersals of Homo from Africa. Annual Review of Anthropology 33, 271-296.

Argyropoulos E, Sassouni V and Xeniotou A (1989). A comparative cephalometric investigation of the Greek craniofacial pattern through 4,000 years. Angle Orthodontist 59, 195-204.

Ballinger SW, Schurr TG, Torroni A, Han YY, Hodge JA, Hassan K, Chen KH and Wallace DC (1992). Southeast Asian Mitochondrial DNA analysis reveals genetic continuity of ancient Mongoloid migrations. Genetics 130, 139-152.

Bass WM (1995). Human Osteology: A Laboratory and Field Manual 4th Ed. Columbia: Missouri Archaeological Society.

Beals KL, Smith CL and Dodd SM (1983). Climate and the evolution of brachycephalisation. American Journal of Physical Anthropology 62, 425-437.

Bellwood P (1985). Prehistory of the Indo-Malaysian Archipelago. Sydney: Academic Press.

Bellwood P (1987). The prehistory of the Island Southeast Asia: a multidisciplinary review of recent research. Journal of World Prehistory 1, 171-224.

Bellwood P (1991). The Austronesian dispersal and the origin of languages. Scientific American 265, 88-93.

293 Bellwood P (1996). Early agriculture and the dispersal of the southern Mongoloids. In T Akazawa and EJE Szathmary (eds) Prehistoric Mongoloid Dispersals, pp 287-302. Oxford: Oxford University Press.

Bellwood P (1997). Prehistory of the Indo-Malaysian Archipelago. Revised edition. Honolulu: University of Hawaii Press.

Bellwood P, Gillespie R, Thompson GB, Vogel JS, Ardika IW and Datan I (1992). New dates for prehistoric Asian rice. Asian Perspectives 31, 161-170.

Benevolenskaya YD (1980). The world distribution of the occipito-parietal index. In Recent Problems and New Methods in Anthropology pp 70-90. Nauka: Leningad (in Russian).

Blumenbach JF (1865). On the natural variation of mankind 3rd edition. In T Bendyshe (ed) The Anthropological Treatises of Johann Blumenbach (translated by T Bendyshe). London: Longman Green .

Blust RA (1984-85). The Austronesian homeland: a linguistic perspective. Asian Perspectives 26, 45-68.

Bookstein FL (1991). Morphometric tools for landmark data: Geometry and biology. Cambridge: Cambridge University Press.

Brace CL (1978). Tooth reduction in the Orient. Asian Perspectives 19, 203-219.

Brace CL, Tracer DP and Hunt KD (1991). Human craniofacial form and the evidence for the peopling of the Pacific. Bulletin of the Indo-Pacific Prehistory Association 12, 247-269.

294 Brace CL and Tracer DP (1992). Craniofacial continuity and change: a comparison of Late Pleistocene and recent Europe and Asia. In T Akazawa (ed) The Evolution and Dispersal of modern humans in Asia, pp 439-471. Tokyo: Hokusen-Sha.

Bräuer G (1992). The origins of modern Asians: by regional evolution or by replacement? In T Akazawa (ed) The evolution and dispersal of modern humans in Asia pp 401-413. Tokyo: Hokusen-Sha.

Brown P (1992). Recent human evolution in East Asia and Australasia. Philosophical transactions of the Royal Society London, Series B 337, 235-242.

Brown P (1999). The first modern East Asians?: another look at Upper Cave 101, Liujiang and Minotogawa 1. In K Omoto (ed) Interdisciplinary Perspectives on the Origins of the Japanese, pp 105-130. Kyoto: International Research Center for Japanese Studies.

Brown P (2001). Chinese Middle Pleistocene hominids and modern human origins in East Asia. In L Barham and K Robson Brown (eds) Human Roots- Africa and Asia in the Middle Pleistocene pp 135-147. Bristol: Western Academic and Specialist Publishers.

Brown P and Maeda T (2004). Post-Pleistocene diachronic change in East Asian facial skeletons: the size, shape and volume of the orbits. Anthropological Science 112, 29-40.

Carson EA (2006). Maximum likelihood estimation of human craniometric heritabilities. American Journal of Physical Anthropology 131, 169-180.

Cavalli-Sforza LL (1986). African pygmies: an evaluation of the state of research. In R Kirk and E Szathmary (eds) In Out of Asia: Peopling the Americas and the Pacific pp 123-131. Canberra: The Journal of Pacific History.

Cavalli-Sforza LL, Piazza A, Menozzi P and Mountain J (1988). Reconstruction of human evolution: Bringing together genetic, archaeological and linguistic data. Proceedings of the National Academy of Sciences USA 85, 6002-6006.

295 Cavalli-Sforza LL, Menozzi P and Piazza A (1994). The History and Geography of Human Genes. New Jersey: Princeton University Press.

Cavalli-Sforza LL and Cavalli-Sforza F (1995). The Great Human Diasporas. The History of Diversity and Evolution. Massachusetts: Perseus Books.

Capelli C, Wilson JF, Richards M, Stumpf MPH, Gratrix F, Oppenheimer S, Underhill PA, Pascali VL, Ko T-M and Goldstein DB (2001). A predominantly indigenous paternal heritage for the Austronesian speaking peoples of insular Southeast Asia and Oceania. American Journal of Human Genetics 68, 432-443.

Chu JY, Huang W, Kuang SQ, Wang JM, Xu JJ, Chu ZT, Yang ZQ, Lin KQ, Li P, Wu M, Geng ZC, Tan CC, Du RF and Jin L (1998). Genetic relationship of populations in China. Proceedings of the National Academy of Sciences USA 95, 11763-11768.

Coon CS (1955). Some problems of human variability and natural selection in climate and culture. American Naturalist 89, 257-279.

Coon CS (1962). The Origin of Races. New York: Alfred A Knoph.

Coon CS, Garn SM and Birdsell JB (1950). Races: A study of the problems of race formation in man. Illinois: Charles C Thomas.

Corruccini RS and Beecher R (1984). Occlusofacial morphological integration lowered in baboons raised on soft diet. Journal of Craniofacial Genetics and Developmental Biology 4, 135-142.

Curnoe D (2006). Odontometric systematic assessment of the Swartkrans SK 15 mandible. HOMO-Journal of Comparative Human Biology 57, 263-294. DiBennardo R and Taylor JV (1983). Multiple discriminant function analysis of sex and race in the postcranial skeleton. American Journal of Physical Anthropology 61, 305- 314.

296 Ding YC, Wooding S, Harpending HC, Chi HC, Li HP, Fu YX, Pang JF, Yao, YG, Xiang JG, Moyzis R and Zhang YP (2000). Population structure and history in East Asia. Proceedings of the National Academy of Sciences USA 97, 14003-14006.

Dodo Y and Ishida H (1990). Population history of Japan as viewed from cranial non- metric variation. Journal of the Anthropological Society of Nippon 98, 269-287.

Dodo Y and Ishida H (1992). Consistency of nonmetric cranial trait expression during the last 2000 years in the habitants of the central islands of Japan. Journal of Anthropological Society of Nippon 100, 417-423.

Du R, Xiao CJ and Cavalli-Sforza LL (1997). Genetic distances between Chinese groups calculated on gene frequencies of 38 loci. Science in China (Series C) 40, 613- 621.

Duckworth WLH (1934). Human remains from rock shelters and caves in Perak, Pahang and Perlis and from Selinsing. Journal of Malayan Branch of the Royal Asiatic Society 12, 149-167.

Enlow DH and Hans MG (1996). Essentials of facial growth. Philadelphia: WB Saunders Co.

Etler DA (1992). Recent developments in the study of human biology in China. Review. Human Biology 64, 567-585.

Etler D (1996). The fossil evidence for human evolution in Asia. The Annual Review of Anthropology 25, 275-301.

Fagan BM (2000). Ancient North America: The archaeology of a continent. New York: Thames and Hudson.

Franklin D, Freedman L and Milne N (2005a). Three-dimensional technology for linear morphological studies: a re-examination of cranial variation in four southern indigenous populations. HOMO-Journal of Comparative Human Biology 56, 17-34.

297 Franklin D, Freedman L and Milne N (2005b). Sexual dimorphism and discrimiant function sexing in indigenous South African crania. HOMO- Journal of Comparative Human Biology 55, 213-218.

Franklin D, Freedman L, Milne N and Oxnard CE (2006). A geometric morphometric study of sexual dimorphism in the crania of indigenous southern Africans. South African Journal of Science 102, 229-238.

Garn SM (1965). Human Races, 2nd Edition. Illinois: Charles C Thomas.

Glanville EV (1969). Nasal shape, prognathism and adaptation in man. American Journal of Physical Anthroplogy 30, 29-37.

Glover IC and Higham CFW (1996). New evidence for evidence of early cultivation in South, Southeast and East Asia. In DR Harris (ed) The origins and spread of agriculture and pastoralism in Eurasia pp 413-441. London: UCL Press.

González-José R, Dahinten SL, Luis MA, Hernández M and Puccierelli HM (2001). Craniometric variation and the settlement of the Americas: testing hypothesis by means of R-Matrix and matrix correlation analyses. American Journal of Physical Anthropology 116, 154-165.

Grün R, Huang P-H, Wu X, Stringer CB, Thorne AG and McCulloch M (1997). ESR analysis of teeth from the palaeoanthropological site of Zhoukoudian, China. Journal of Human Evolution 32, 83-91.

Hammer Ø, Harper DAT and Ryan PD (2001). PAST: Paleontological Statistics Software Package fro Education and Data Analysis. Palaeontologica Electronica 4, 1-9.

Hanihara K (1985 a). Geographic variation of modern Japanese crania and its relationship to the origin of Japanese. Homo 36, 1-10.

298 Hanihara K (1985 b). Origins and affinities of Japanese as viewed from cranial measurements. In R Kirk and E Szathmary (eds) Out of Asia: Peopling the Americas and the Pacific pp105-112. Canberra: The Journal of Pacific History.

Hanihara K (1991). Dual structure model for the population history of Japanese. Japan Review 2, 1-33.

Hanihara T (1991). The origin and microevolution of Ainu as viewed from dentition: The basic populations of East Asia, VIII. Journal of the Anthropological Society of Nippon 99, 345-361.

Hanihara T (1992). Dental and cranial affinities among populations of East Asia and the Pacific: the basic populations in East Asia, IV. American Journal of Physical Anthropology 88, 163-182.

Hanihara T (1993). Population history of East Asia and the Pacific as viewed from craniofacial morphology: the basic populations in East Asia IV. American Journal of Physical Anthropology 91, 173-187.

Hanihara T (1994). Craniofacial continuity and discontinuity of Far Easterners in the Late Pleistocene and Holocene. Journal of Human Evolution 27, 417-441.

Hanihara T (1997). Craniofacial affinities of Mariana Islanders and circum-Pacific peoples. American Journal of Physical Anthropology 104, 411-425.

Hanihara T (2000). Frontal and Facial Flatness of Major Human Populations. American Journal of Physical Anthropology 111, 105-134.

Hanihara T, Ishida H and Dodo Y (2003). Charactersation of Biological Diversity through analysis of discrete cranial traits. American Journal of Physical Anthropology 121, 241-251.

Harcourt-Smith W (2002). Form and function in the hominoid tarsal skeleton. PhD dissertation, University College London.

299 Harrison G, Weiner J, Tanner J and Barnicot N (1964). Human Biology. New York: Oxford University Press.

Harvati K (2001a). The Neanderthal problem: 3-D geometric morphometric models of cranial shape variation within and among species. PhD dissertation, City University of New York.

Harvati K (2001b). Models of shape variation within and among species and the Neanderthal taxonomic position: a 3-D geometric approach on temporal bone morphology. Journal of Human Evolution 40, 9-10.

Harvati K (2003). Quantitative analysis of Neanderthal temporal bone morphology using three-dimensional geometric morphometrics. American Journal of Physical Anthropology 120, 323-338.

Harvati K and Weaver TD (2006a). Human cranial anatomy and the differential preservation of population history and climatic signatures. The Anatomical Record Part A 288A, 1225-1233.

Harvati K and Weaver TD (2006b). Reliability of cranial morphology in reconstructing Neanderthal phylogeny. In K Harvati and T Harrison (eds) Neanderthals revisited: new approaches and perspectives pp 239-254. Dordrecht: Springer.

Hennessey RJ and Stringer CB (2002). Geometric morphometric study of the regional variation of modern human craniofacial form. American Journal of Physical Anthropology 117, 37-48.

Hernández M, Fox, CL and Garcia-Moro C (1997). Fuegian Cranial Morphology: The adaptation to a cold, harsh environment. American Journal of Physical Anthropology 103, 103-117.

Hey J (2005). On the number of New World Founders: A population genetic portrait of the peopling of the Americas. Public Library of Science, Biology 3, 965-975.

300 Higa T, Hanihara T, Sunakawa H and Ishida H (2003). Dental variation of Ryukyu Islanders: A comparative study among Ryukyu, Ainu and other Asian populations. American Journal of Human Biology 15, 127-143.

Horai S, Murayama K, Hayasaka K, Matsubayashi S, Hattori Y, Fucharoen G, Harihara S, Park KS, Omoto K, Pan I-H (1996). mtDNA polymorphism in east Asian populations, with special reference to the peopling of Japan. American Journal of Human Genetics 59, 579-590.

Howells WW (1973). Cranial variation in Man. A study by multivariate analysis of patterns of difference among recent human populations. Papers of the Peabody Museum, Harvard University, vol 67.

Howells WW (1984). Prehistoric remains from China. In I Schwidetzky (ed) Rassengeschichte der Menscheheit. 10 Lieferung, Asian III: Ostasien pp 29-38. München: R. Oldenbourg Verlag.

Howells WW (1989). Skull shapes and the map. Cambridge: Peabody Museum of Archaeology and Ethnology, Harvard University.

Howells WW (1990). Micronesia to Macromongolia. Micro-polynesian craniometrics and the Mongoloid population complex. Micronesica Supplement 2, 363-372.

Huang P, Jin S, Liang R, Zheng L, Yuan Z, Cai B and Fang Z (1991). Study of ESR date for burying age of the first skull of Peking Man and chronological scale of the cave deposit in Zhoukoudian site Loc. 1. Acta Anthropologica Sinica 10, 107-115. (In Chinese with English abstract).

Hubert M, Rousseeuw PJ and Branden KV (2005). ROBPCA: a new approach to robust principal component analysis. Technometrics 47, 64-79.

301 Hylander WL (1977). The adaptive significance of Eskimo craniofacial morphology. In AA Dahlberg and TM Graber (eds) Orofacial growth and development pp129-169. Paris: Mouton Publishers.

Irish JD (1998). Ancestral dental traits in recent Sub-Saharan Africans and the origins of modern humans. Journal of Human Evolution 34, 81-98.

Ishida H (1992). Flatness of facial skeletons in Siberian and other circum-Pacific populations. Zietschrift für Morphologie und Anthropologie 79, 53-67.

Ishida H and Dodo Y (1993). Nonmetric cranial variation and the population affinities of the Pacific peoples. American Journal of Physical Anthropology 90, 49-57.

Ishida H and Dodo Y (1997). Cranial variation in prehistoric human skeletal remains from the Marianas. American Journal of Physical Anthropology 104, 399-410.

Ishida H and Kondo O (1998). Human cranial variations based on different sets of measurement variables. Anthropological Science 106, 41-60.

Jacob T (1967). Some problems pertaining to the racial history of the Indonesian region. PhD dissertation, University of Utrecht.

Jin L and Su B (2000). Natives or immigrants: modern human origin in East Asia. Nature Reviews Genetics 1, 126-133.

Jolly CJ (2003). Cranial anatomy and baboon diversity. Anatomical Record 275A, 1043-1047.

Kajanoja P (1966). Sex determination of Finnish crania by discriminant function analysis. American Journal of Physical Anthropology 24, 29-34.

Kamminga J and Wright RVS (1988). The Upper Cave at Zhoukoudian and the origins of Mongoloids. Journal of Human Evolution 17, 739-767.

302 Karafet TM, Zegura SL, Posukh O, Osipova L, Bergen A, Long J, Goldman D, Klitz W, Hanihara S, de Knijff P, Weibe V, Griffiths RC, Templeton AR and Hammer MF (1999). Ancestral Asian source(s) of New World Y-chromosome founder haplotypes. American Journal of Human Genetics 64, 817-831.

Karafet T, Liping X, Ruofo D, Wang W, Feng S, Wells RS, Redd AJ, Zegura SL and Hammer MF (2001). Paternal population history of East Asia: Sources, patterns and microevolutionary processes. American Journal of Human genetics 69, 615-628.

Kean MR and Houghton P (1990). Polynesian face and dentition: Functional perspective. American Journal of Physical Anthropology 82, 361-369.

Keen JA (1950). A study of the differences between male and female skulls. American Journal of Physical Anthropology 8, 65-80.

Klecka WR (1980). Discriminant Analysis. Beverly Hills: Sage Publications.

Kobayashi H, Hirose Y, Sugino M and Watanabe N (1974). TK-99. Radiocarbon 16, 384.

Kuroe K, Rosas A and Molleson T (2004). Variation in the cranial base orientation and facial skeleton in dry skulls samples from three major populations. European Journal of Orthodontics 26, 201-207.

Lahr M (1995). Patterns of modern human diversification: Implications for Amerindian Origins. Yearbook of Physical Anthropology 38, 163-198.

Lahr M (1996). The evolution of modern human diversity: a study of cranial variation. Cambridge: Cambridge University Press.

Lahr M and Wright RVS (1996). The question of robusticity and the relationship between cranial size and shape in Homo sapiens. Journal of Human Evolution 31, 157- 191.

303 Li Y, Brace CL, Gao Q and Tracer DP (1991). Dimensions of face in Asia in the perspective of geography and prehistory. American Journal of Physical Anthropology 85, 269-279.

Lieberman DE, Krovitz GE, Yates FW, Devlin M and St Claire M (2004). Effects of food processing on masticatory strain and craniofacial growth in a retrognathic face. Journal of Human Evolution 46, 655-677.

Liu S, Zhang F, Hu R, Liu J, Guo S, Zhou S, Meng W, Zhang P, Sun S and Hao X (1985). Dating Peking Man Site by the fission-track method. In IVPP (eds) Multidisciplinary study of the Peking Man site at Zhoukoudian pp 241-245. Beijing: Science Press (In Chinese).

Liu W, Yang M and Wang Y (1991). Study of metric traits and geographical variations of modern Chinese skulls. Acta Anthropologica Sinica 10, 96-106.

Macchiarelli R and Bondioli L (1986). Post-Pleistocene reductions in human dental structure: a reappraisal in terms of increasing population density. Netherlands: Springer.

Macintosh NWG and Larnach SL (1976). Aboriginal affinities looked at in world context. In RL Kirk and AG Thorne (eds) The Origin of Australians pp 113-126. Canberra: Australian Institute of Aboriginal Studies.

Manabe Y, Oyamada J, Kitagawa Y, Rokutanda A, Kato K and Matsushita T (2003). Dental morphology of the Dawenkou Neolithic population in North China: implications for the origin and distribution of Sinodonty. Journal of Human Evolution 45, 369-380.

Marcus LF, Corti M, Loy A, Naylor GJP and Slice D (1996). Advances in Morphometrics. Nato ASI series. New York: Plenum Press

Martin R and Saller K (1957). Lehrbuch der Anthropologie. Stuttgart: Gustav Fischer.

304 Matsumoto H (1988). Characteristics of Mongoloid and neighbouring populations based on the genetic markers of human immunoglobulins. Human Genetics 80, 207-218.

Matsumura H and Hudson MJ (2005). Dental perspectives on the population history of Southeast Asia. American Journal of Physical Anthropology 127, 182-209.

Movessian AA (2005). Phenetic Analysis in Paleoanthropology: Phenogeography of Peoples of the World. Russian Journal of Genetics 41, 1046-1054.

Nasab HV (2006). Three-dimensional study of the mid-facial region in European Middle and Late Pleistocene hominids. PhD Dissertation, Arizona State University.

Nei M and Roychoudhury AK (1993). Evolutionary relationships of human populations on a global scale. Molecular Biology and Evolution 10, 927-943.

Neves WA and Puccierelli HM (1990). The origin of the first Americans: an analysis based on the cranial morphology of early South American human remains. American Journal of Physical Anthropology 81, 274.

Neves WA and Puccierelli HM (1991). Morphological affinities of the first Americans: An exploratory analysis based on early South American human remains. Journal of Human Evolution 21, 261-273.

Neves WA, Pucciarelli HM and Meyer D (1993). The contribution of the morphology of early South and North American skeletal remains to the understanding of the peopling of the Americas. American Journal of Physical Anthropology (Suppl) 16, 150- 151.

O’Higgins P (2000). The study of morphological variation in the hominid fossil record: biology, landmarks and geometry. Journal of Anatomy 197, 103-120.

305 O’Higgins P and Jones N (1998). Facial growth in Cercocebus torquatus: an application of three-dimensional geometric morphometric techniques to the study of morphological variation. Journal of Anatomy 193, 251-272.

O’Higgins P and Pan R (2004). Advances in the analysis of form and pattern: facial growth in African colobines. In F Anapol, RZ German and NG Jablonski (eds) Shaping Primate Evolution pp 24-44. Cambridge: Cambridge University Press.

Omoto K (1995). Genetic diversity and the origin of ‘Mongoloids’. In S Brenner and K Hanihara (eds) The Origin and Past of Modern Humans as viewed from DNA pp 92- 109. Singapore: World Scientific.

Omoto K and Saitou N (1997). Genetic origins of the Japanese: A partial support for the dual structure hypothesis. American Journal of Physical Anthropology 102, 437-446.

Oota H, Saitou N, Matsushita T and Ueda S (1995). A genetic study of 2,000 yr old human remains from Japan using mitochondrial DNA sequences. American Journal of Physical Anthropology 98, 133-145.

Oota H, Saitou N, Matsushita T and Ueda S (1999). Molecular genetic analysis of remains of a 2,000 year old human population in China-and its relevance for the origin of the modern Japanese population. American Journal of Human Genetics 64, 250-258.

Oota H, Kurosaki K, Pookajorn S, Ishida T and Ueda S (2001). Genetic study of the Paleolithic and Neolithic Southeast Asians. Human Biology 73, 225-231.

Pan R, Wei F and Li M (2003). Craniofacial variation of the Chinese Macaques explored with Morphologika. Journal of Morphology 256, 342-348.

Pan R, Groves C and Oxnard C (2004). Relationships between Fossil Colobine Mesopithecus pentelicus and Extant Cercopithecoids, based on dental metrics. American Journal of Primatology 62, 287-299.

306 Patil KR and Mody RN (2005). Determination of sex by discriminant function analysis and stature by regression analysis: a lateral cephalometric study. Forensic Science International 147, 175-180.

Pei J (1985). Thermoluminescence dating of the Peking Man site and other caves. In IVPP (eds) Multidisciplinary study of the Peking Man site at Zhoukoudian pp 256-260. Beijing: Science Press (In Chinese).

Perez SI, Bernal V, Gonzalez PN (2007). Morphological differentiation of Aboriginal human populations from Tierra del Fuego (Patagonia): Implications for South American peopling. American Journal of Physical Anthropology 133, 1067-1079.

Pietrusewsky M (1994). Pacific-Asian relationships: A physical anthropological perspective. Oceanic Linguistics 33, 407-429. Pietrusewsky M (1997). The people of Ban Chiang: An early Bronze site in Northeast Thailand. Bulletin of the Indo-pacific Prehistory Association 16, 119-147.

Pietrusewsky M (1999). A multivariate craniometric investigation of the inhabitants of the Ryukyu Islands and comparisons with cranial series from Japan, Asia and the Pacific. Anthropological Science 107, 255-281.

Pietrusewsky M (2000). Metric analysis of skeletal remains: methods and applications. In MA Katzenberg and SR Saunders (eds) Biological Anthropology of the Human Skeleton pp 375-415. New York: Wiley-Liss.

Pietrusewsky M and Chang C (2003). Taiwan Aboriginals and peoples of the Pacific- Asia region: Multivariate craniometric comparisons. Anthropological Science 111, 293- 332.

Pope GG (1992). Craniofacial evidence for the origin of modern humans in China. Yearbook of Physical Anthropology 35, 243-298.

Rightmire GP (1998). Human evolution in the Middle Pleistocene: the role of Homo heidelbergensis. Evolutionary Anthropology 6, 218-227.

307 Rosas A and Bastir M (2002). Thin-plate spline analysis of allometry and sexual dimorphism in the human craniofacial complex. American Journal of Physical Anthropology 117, 236-245.

Roseman CC (2004). Detecting interregionally diversifying natural selection on modern human cranial from by using matched molecular and morphometric data. Proceedings of the National Academy of Sciences, USA 101, 12824-12829.

Sardi ML, Rozzi FS, González-José and Pucciarelli HM (2005). South Amerindian Craniofacial Morphology: Diversity and Implications for Amerindian Evolution. American Journal of Physical Anthropology 128, 747-756.

Schneider A and Roberts AE (2004). Classification and Relations of Meaning. Qulaity and Quantity 38, 547-557.

Schurr TG (2004).The peopling of the New World: Perspectives from molecular anthropology. Annual Review of Anthropology 33, 551-583.

Shen G, Wang W, Wang Q, Zhao J, Collerson K, Zhou C and Tobias PV (2002). U- Series dating of Liujiang hominid site in Guangxi, Southern China. Journal of Human Evolution 43, 817-829.

Sofaer JA (1973). A model relation developmental interaction and differential evolutionary reduction of tooth size. Evolution 27, 427-434.

Steegmann AT Jr (1970). Cold adaptation and the human face. American Journal of Physical Anthropology 32, 243-250.

Steele DG and Powell JF (1992). Peopling of the Americas: Palaeobiological evidence. Human Biology 64, 303-336.

Stringer C (2002). Modern human origins: progress and prospects. Philosophical transactions of the Royal Society London, Series B. 357, 563-579.

308 Su B, Xiao J, Underhill P, Deka R, Zhang W, Akey J, Huang W, Shen D, Lu D, Luo J, Chu J, Tan J, Shen P, Davis R, Cavalli-Sforza L, Chakraborty, Xiong M, Du R, Oefner P, Chen Z and Jin L (1999). Y-Chromosome evidence for a northward migration of modern humans into Eastern Asia during the Last Ice Age. The American Journal of Human Genetics 65, 1718-1724.

Sutton DN, Lewis BRK, Patel M and Cawood JI (2004). Changes in facial form relative to progressive atrophy of edentulous jaws. International Journal of Oral and Maxilliofacial Surgery. 33, 676-682.

Szathmáry E (1984). Human Biology of the Arctic. In D Damas (ed) Handbook of North American Indians, Vol 5, Arctic pp 64-71. Washington DC: Smithsonian Institution.

Tabachnick BG and Fidell LS (2001). Using Multivariate Statistics, 5th Edition. USA: Pearson Education Ltd.

Tan SG (2001). Genetic relationships among sixteen ethnic groups from Malaysia and Southeast Asia. In L Jin, M Seielstad and C Xiao (eds) Genetic, linguistic and archaeological perspectives on human diversity in Southeast Asia pp 83-91. Singapore: World Scientific.

Tanaka M, Cabrera VM, González AM, Larruga JM, Takeyasu T, Fuku N, Guo L-J, Hirose R, Fujita Y, Kurata M, Shinoda K, Umetsu K, Yamada Y, Oshida Y, Sato Y, Hattori N, Mizuno Y, Arai Y, Hirose N, Ohta S, Ogawa O, Tanaka Y, Kawamori R, Shamoto-Nagai M, Maruyama W, Shimokata H, Suzuki R and Shimodaira H (2004). Mitochondrial genome variation in eastern Asia and the peopling of Japan. Genome Research 14, 1832-1850.

Trevor JC and Brothwell DR (1962). The human remains of Mesolithic and Neolithic date from Gua Cha, Kelantan. Federation Museum Journal 7, 6-22.

309 Tryon D (1995). Proto-Austronesian and the major Austronesian subgroups. In P Bellwood, JJ Fox and D Tryon (eds) The Austronesians: historical and comparative perspectives pp17-38. Canberra: RSPAS, Australian National University.

Turner CG II (1976). Dental evidence on the origin of the Ainu and Japanese. Science 193, 911-913.

Turner CG II (1987). Late Pleistocene and Holocene population history of East Asia based on dental variation. American Journal of Physical Anthropology 73, 305-321.

Turner CG II (1989). Teeth and Prehistory in Asia. Scientific American Feb, 70-77.

Turner CG II (1990). Major features of sundadonty and sinodonty, including suggestions about East Asia microevolution, population history and Late Pleistocene relationships with Australian Aboriginals. American Journal of Physical Anthropology 82, 295-317.

Turner CG II (1992). Microevolution of East Asian and European populations: dental perspective. In T Akazawa (ed) The evolution and dispersal of modern humans in Asia pp 415-438. Tokyo: Hokusen-Sha.

Uytterschaut HT (1986). Sexual dimorphism in human skulls. A comparison of sexual dimorphism in different populations. Human Evolution 1, 243-250.

Van Vark GN and Howells WW (eds) (1984). Multivariate statistics in Physical Anthropology. Dordrecht: D.Reidel Publishing Co.

Viðarsdóttir US, O’Higgins P and Stringer C (2002). A geometric morphometric study of regional differences in the ontogeny of the modern human facial skeleton. Journal of Anatomy 201, 211-229.

Wang L (1986). Secular change and geographical variation in Chinese Neolithic and modern inhabitants: A statistical study of cranial metric traits. Acta Anthropologica Sinica 5, 243-258.

310 Wang L, Oota H, Saitou N, Jin F, Matsushita T and Ueda S (2000). Genetic structure of a 2,500 year old human population in China and its spatiotemporal changes. Molecular Biology and Evolution 17, 1396-1400.

Weidenreich F (1935). The Sinanthropus population of Choukoutien (Locality 1) with a preliminary report on new discoveries. Bulletin Geological Society of China 14, 427- 461.

Weidenreich F (1936). The mandible of Sinanthropus Pekinensis. A comparative study. Palaeontologica Sinica D7, 1-132

Weidenreich F (1939). On the earliest representatives of modern mankind recovered on the soil of East Asia. Bulletin of the Natural History Society of Peking 13, 161-174.

Weidenreich F (1943). The skull of Sinanthropus Pekinensis: a comparative study of a primitive hominid skull. Palaeontologica Sinica D10, 1-485.

Weidenreich F (1946). Apes, Giants and Man. Chicago: Chicago University Press.

Williams BA and Rogers TL (2006). Evaluating the accuracy and precision of cranial morphological traits for sex determination. Journal of Forensic Sciences 51, 729-735.

Wolpoff MH, Wu X and Thorne AG (1984). Modern Homo sapiens origins: A general theory of hominid evolution involving the fossil evidence from East Asia. In FH Smith and F Spencer (eds) The origins of modern humans: a world survey of the fossil evidence pp 411-483. New York: Alan. R. Liss.

Woo TL (1937). A biometric study of the human malar bone. Biometrika 29, 113-123.

Woo TL and Morant GM (1934). A biometric study of the “flatness” of the facial skeleton in Man. Biometrika 26, 196-250.

311 Wu X (1990). The origin and dispersals of the anatomically modern Homo sapiens of China. In T Akazawa (ed) The evolution and dispersal of modern humans in Asia pp 48. Tokyo: The University Museum, The University of Tokyo.

Wu X (1992). The origin and dispersal of anatomically modern humans in East Asia and Southeast Asia. In T Akazawa (ed) The evolution and dispersal of modern humans in Asia pp 373-378. Tokyo: Hokusen-Sha.

Wu X (2004). On the origin of modern humans in China. Quaternary International 117, 131-140.

Wu X and Poirier FE (1995). Human evolution in China. Oxford: Oxford University Press

Wu R and Wu X (1997). China. In F Spencer (ed) History of Physical Anthropology an Encyclopedia pp 273-282. New York: Garland.

Wu X and Zhang Z (1985).Homo sapiens remains from late Palaeolithic and Neolithic China. In R. Wu and JW Olsen (eds) Palaeoanthropology and Palaeolithic Archaeology in the People’s Republic of China pp 107-133. London: Academic Press.

Yamaguchi B (1992). Skeletal morphology of the Jomon people. In K Hanihara (ed) Japanese as a member of the Asian and Pacific Populations: International Symposium 4 pp 53-63. Kyoto: IRCJS Press.

Yongyi L, Brace CL, Qiang G and Tracer DP (1991). Dimensions of face in Asia in the perspective of geography and prehistory. American Journal of Physical Anthropology 85, 269-279.

Yoshiura K, Kinoshita A, Ishida T, Ninokata A, Ishikawa T, Kaname T, Bannai M, Tokunaga K, Sonoda S, Komaki R, Ihara M, Saenko V, Alipov G, Sekine I, Komatsu K, Takahashi H, Nakashima M, Sosonkina N, Mapendano C, Ghadami M, Nomura M, Liang D, Miwa N, Kim D, Garidkhuu A, Natsume N, Ohta T, Tomita H, Kaneko A, Kikuchi M, Russomando G, Hirayama K, Ishibashi M, Takahashi A, Saitou N, Murray

312 J, Saito S, Nakamura Y and Niikawa N (2006). A SNP in the ABCC11 gene is the determinant of human earwax type. Nature Genetics 38, 324-330.

Zhao S, Sha M, Zhang C, Liu M, Wang S, Wu Q, and Ma Z (1985). Uranium series dating of Peking Man site. In IVPP (eds) Multidisciplinary study of the Peking Man site at Zhoukoudian pp 246-250. Beijing: Science Press (In Chinese).

Zhao TM and Lee TD (1989). Gm and Km allotypes in 74 Chinese populations: A hypothesis of the origin of the Chinese nation. Human Genetics 83, 101-110.

Zheng H-Y, Zhao P, Suganami H, Ohasi Y, Ikegaya H, Kim J-C, Sugimoto C, Takasaka T, Kitamura T and Yogo Y (2004). Regional distribution of two related Northeast Asian genotypes of JC virus, CY-a and –b: implications fro the dispersal of Northeast Asians. Microbes and Infection 6, 596-603.

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Appendix

Appendix 1 Summary Statistics for Linear Measurements Prosthion-Nasospinale

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (mm) (mm) (%) (mm) (mm) (%) (mm) (mm) (%)

Siberia 28 20.36 14.45 - 25.74 3.09 48.18 18 21.34 14.45 - 25.74 3.28 15.60 10 19.75 15.51 - 24.96 2.71 13.67 Mongolia 24 18.98 13.05 - 30.61 4.07 22.65 15 19.39 13.05 - 30.61 4.64 23.19 9 18.49 14.52 - 24.54 3.02 16.03 Korea 4 18.36 12.04 - 21.50 4.23 24.09 2 19.03 16.56 - 21.50 3.49 27.54 2 16.10 12.04 - 20.16 5.74 53.48 Ainu 3 20.68 17.06 - 22.05 2.58 12.94 2 18.87 17.06 - 20.68 2.56 20.36 1 22.05 22.05 - 22.05 - - Japan 13 17.12 11.84 - 24.29 3.26 18.74 10 16.87 13.85 - 24.29 3.17 17.88 3 17.12 11.84 - 19.57 3.95 42.73 S. China 6 17.71 10.70 - 19.51 3.25 19.80 3 18.36 18.14 - 19.51 0.73 6.88 3 14.63 10.70 - 17.28 3.31 40.80 N. China 16 19.16 12.59 - 26.34 3.90 20.24 13 18.87 12.59 - 26.34 3.95 20.45 3 19.46 14.40 - 23.42 4.52 41.43 Burma 39 17.30 9.73 - 24.12 3.50 20.27 22 17.67 12.20 - 24.12 3.26 18.04 17 15.60 9.73 - 22.69 3.61 22.25 Laos 24 19.08 13.07 - 25.56 3.07 16.59 16 17.07 13.07 - 25.56 3.50 19.28 8 19.30 14.94 - 21.63 1.98 10.35 Vietnam 23 17.79 12.22 - 22.90 2.82 15.95 13 18.39 15.09 - 22.90 2.66 14.05 10 16.97 12.22 - 19.29 2.29 14.20 Thailand 21 16.53 6.64 - 24.78 3.78 22.74 15 16.53 12.45 - 24.78 3.02 17.72 6 16.63 6.64 - 22.68 5.49 35.05 Cambodia 13 15.10 6.63 - 22.69 4.40 29.32 4 16.49 14.39 - 22.69 3.65 41.73 9 12.94 6.63 - 19.99 4.43 31.82 Philippines 28 16.96 9.08 - 23.38 3.27 19.88 22 16.66 9.89 - 23.38 3.13 18.96 6 17.45 9.08 - 21.26 4.08 25.04 Andaman Is. 36 14.03 7.84 - 20.48 2.90 20.58 18 13.60 8.39 - 20.48 3.20 23.30 18 14.47 7.84 - 18.36 2.60 18.02 Nicobar Is. 20 16.92 7.81 - 22.55 4.24 26.30 17 16.75 7.81 - 22.55 4.56 28.62 3 17.10 15.64 - 18.71 1.53 15.66 Borneo 37 17.25 6.91 - 22.26 3.15 18.72 26 17.09 6.91 - 22.26 3.31 19.65 11 17.25 12.19 - 20.20 2.87 17.15 Indonesia 27 17.95 10.82 - 24.85 3.14 17.44 20 17.54 10.82 - 24.85 3.63 20.25 7 18.51 16.55 - 19.35 1.01 5.50 Melanesia 30 15.27 10.86 - 21.16 2.88 18.13 20 16.64 11.36 - 21.16 2.80 16.89 10 14.06 10.86 - 18.99 2.70 18.53 Micronesia 15 15.58 8.61 - 19.68 2.84 18.53 7 15.11 12.27 - 18.56 2.33 15.61 8 15.95 8.61 - 19.68 3.34 21.37 Australia 27 18.27 13.59 - 24.73 2.68 14.70 18 18.57 13.59 - 24.73 2.90 15.51 9 17.63 13.72 - 20.36 1.95 11.32 Africa 29 18.01 7.89 - 28.64 4.33 24.21 18 17.93 7.89 - 28.64 4.77 26.49 11 18.35 12.21 - 24.68 3.72 21.00 Nat. America 33 20.92 10.92 - 27.11 2.97 14.35 10 21.37 15.78 - 23.69 2.90 14.13 23 20.92 10.92 - 27.11 3.06 14.73 Caucasian 29 19.84 7.09 - 25.51 4.26 22.55 15 20.45 9.32 - 24.23 3.38 17.52 14 19.68 7.09 - 25.51 5.12 27.84 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980) 315 Prosthion-Nasion (NPH)

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (mm) (mm) (%) (mm) (mm) (%) (mm) (mm) (%)

Siberia 28 72.65 62.45 - 82.70 5.23 7.27 18 74.14 64.94 - 82.70 5.06 6.87 10 67.53 62.45 - 75.04 3.87 5.64 Mongolia 24 70.22 58.54 - 82.58 5.46 7.71 15 71.67 62.46 - 82.58 5.26 7.25 9 68.37 58.54 - 75.50 4.64 6.83 Korea 4 71.49 57.02 - 76.39 8.93 25.85 2 72.04 67.70 - 76.39 6.14 12.79 2 66.15 57.02 - 75.29 12.92 29.29 Ainu 3 65.88 64.99 - 74.16 5.06 12.95 2 65.43 64.99 - 65.88 0.63 1.44 1 74.16 74.16 - 74.16 - - Japan 13 66.49 53.04 - 76.21 5.71 8.48 10 68.01 63.41 - 76.21 4.06 5.88 3 64.24 53.04 - 68.59 8.03 22.67 S. China 6 68.03 56.72 - 70.56 5.11 7.75 3 68.69 67.38 - 70.56 1.60 4.05 3 63.58 56.72 - 68.98 6.14 17.04 N. China 16 71.65 60.79 - 83.11 6.18 8.68 13 71.72 63.49 - 83.11 5.43 7.55 3 64.06 60.79 - 78.44 9.39 24.25 Burma 39 65.31 55.43 - 74.89 4.60 6.93 22 69.12 59.43 - 74.89 4.31 6.35 17 63.94 55.43 - 72.45 4.48 6.92 Laos 24 68.10 61.27 - 73.24 3.34 4.93 16 68.10 61.27 - 72.66 3.45 5.10 8 68.18 64.11 - 73.24 3.32 4.86 Vietnam 23 67.66 60.02 - 73.60 3.59 5.37 13 68.98 63.32 - 73.60 2.83 4.12 10 64.99 60.02 - 68.04 3.02 4.69 Thailand 21 67.01 50.58 - 75.16 6.03 9.11 15 67.45 60.93 - 75.16 3.74 5.47 6 61.03 50.58 - 70.25 7.31 12.07 Cambodia 13 64.56 60.89 - 70.92 3.52 5.43 4 66.74 61.90 - 70.02 3.60 10.85 9 64.08 60.89 - 70.92 3.51 5.45 Philippines 28 63.39 57.61 - 72.51 4.43 6.88 22 63.85 58.70 - 72.51 4.29 6.63 6 60.89 57.61 - 70.46 5.06 8.03 Andaman Is. 36 59.19 50.04 - 68.33 4.33 7.30 18 59.34 51.27 - 68.33 3.96 6.59 18 58.01 50.04 - 67.65 4.69 8.00 Nicobar Is. 20 63.56 55.05 - 72.13 5.07 7.97 17 63.61 55.05 - 72.13 5.43 8.52 3 62.91 59.86 - 64.25 2.25 6.32 Borneo 37 64.87 55.12 - 73.30 4.43 6.85 26 65.49 55.12 - 73.30 4.70 7.21 11 61.55 59.70 - 70.95 3.55 5.60 Indonesia 27 67.06 59.59 - 76.50 4.14 6.19 20 67.79 60.80 - 76.50 3.99 5.93 7 64.22 59.59 - 73.25 4.65 7.07 Melanesia 30 65.76 54.55 - 73.83 4.62 7.12 20 66.27 61.30 - 73.83 3.15 4.74 10 61.20 54.55 - 70.86 5.76 9.30 Micronesia 15 64.13 59.89 - 72.47 3.50 5.42 7 66.37 60.65 - 72.47 4.01 6.08 8 63.21 59.89 - 67.43 2.65 4.19 Australia 27 65.20 55.28 - 73.53 4.50 6.92 18 67.36 59.33 - 73.53 3.92 5.88 9 62.34 55.28 - 66.83 4.04 6.53 Africa 29 65.12 56.96 - 75.41 4.83 7.32 18 65.12 56.96 - 75.41 5.23 7.86 11 63.91 59.28 - 72.38 4.12 6.35 Nat. America 33 68.39 58.91 - 78.60 4.25 6.18 10 70.76 58.91 - 75.88 4.97 7.10 23 68.04 62.88 - 78.60 3.89 5.70 Caucasian 29 66.36 55.89 - 75.24 4.84 7.31 15 66.91 58.25 - 75.24 4.91 7.25 14 64.38 55.89 - 72.26 4.31 6.67 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

316 Prosthion-Glabella

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (mm) (mm) (%) (mm) (mm) (%) (mm) (mm) (%)

Siberia 28 81.83 70.69 - 93.41 6.00 7.35 18 82.77 70.69 - 93.41 5.94 7.11 10 77.22 71.63 - 86.65 4.78 6.10 Mongolia 24 82.58 68.97 - 93.29 6.03 7.29 15 85.52 72.27 - 93.29 5.47 6.43 9 78.99 68.97 - 86.26 4.95 6.28 Korea 4 73.79 65.19 - 89.38 12.26 32.22 2 81.59 73.79 - 89.38 11.02 20.27 1 65.19 65.19 - 65.19 - - Ainu 3 76.54 76.31 - 83.84 4.28 9.50 2 76.42 76.31 - 76.54 0.16 0.32 1 83.84 83.84 - 83.84 - - Japan 13 76.12 67.27 - 83.26 4.51 5.88 10 78.13 71.42 - 83.26 3.84 4.93 3 74.69 67.27 - 75.26 4.46 10.78 S. China 5 75.92 68.25 - 81.78 5.13 15.31 2 79.99 78.21 - 81.78 2.53 4.74 3 73.07 68.25 - 75.92 3.88 9.37 N. China 16 82.15 72.06 - 93.45 6.12 7.49 13 83.04 75.30 - 93.45 5.21 6.31 3 73.61 72.06 - 90.04 9.96 22.19 Burma 39 76.59 64.96 - 85.38 5.07 6.63 22 78.83 67.05 - 85.38 5.15 6.63 17 74.51 64.96 - 81.43 4.68 6.25 Laos 24 78.85 71.42 - 84.14 3.52 4.45 16 78.57 71.42 - 84.14 3.86 4.91 8 80.03 75.58 - 83.39 2.75 3.45 Vietnam 23 77.96 71.16 - 83.17 3.75 4.90 13 79.17 71.18 - 83.17 3.63 4.64 10 74.10 71.16 - 78.86 2.53 3.40 Thailand 21 76.14 61.75 - 82.45 5.54 7.32 15 78.78 69.22 - 82.45 4.32 5.58 6 72.26 61.75 - 79.07 6.50 9.08 Cambodia 13 76.43 66.41 - 80.32 4.55 6.07 4 78.80 71.37 - 79.54 3.87 10.04 9 75.39 66.41 - 80.32 4.72 6.37 Philippines 28 73.77 63.39 - 85.27 5.26 7.16 22 74.03 66.48 - 85.27 4.86 6.59 6 69.94 63.39 - 81.14 6.96 9.61 Andaman Is. 36 70.01 57.89 - 79.90 4.55 6.46 18 70.21 61.41 - 79.90 4.43 6.27 18 69.72 57.89 - 76.03 4.78 6.80 Nicobar Is. 20 72.59 64.24 - 84.36 6.18 8.44 17 72.19 64.24 - 84.36 6.68 9.10 3 73.15 70.11 - 74.01 2.05 4.95 Borneo 37 73.65 65.48 - 84.70 4.57 6.13 26 74.70 65.48 - 84.70 4.88 6.52 11 71.90 69.58 - 80.62 3.79 5.15 Indonesia 27 75.54 67.36 - 87.41 4.68 6.17 20 75.62 69.28 - 87.41 4.59 6.04 7 73.10 67.36 - 81.69 5.25 6.98 Melanesia 30 74.05 64.73 - 83.94 4.64 6.32 20 74.10 69.52 - 83.94 3.45 4.61 10 69.97 64.73 - 80.62 5.80 8.16 Micronesia 15 73.53 69.68 - 79.57 3.91 5.26 7 77.58 69.73 - 79.57 3.93 5.18 8 71.08 69.68 - 78.00 3.63 4.98 Australia 27 72.68 65.52 - 83.22 3.99 5.47 18 73.25 68.37 - 83.22 4.02 5.45 9 72.01 65.52 - 75.50 3.55 4.98 Africa 29 73.86 64.37 - 86.34 5.28 7.00 18 74.46 64.37 - 86.34 6.05 7.97 11 73.86 66.74 - 80.94 3.87 5.18 Nat. America 33 78.59 67.44 - 87.91 4.17 5.28 10 79.46 67.44 - 84.47 5.16 6.53 23 77.95 72.92 - 87.91 3.79 4.81 Caucasian 29 74.92 62.45 - 84.15 4.87 6.55 15 75.42 65.85 - 84.15 4.46 5.88 14 73.69 62.45 - 79.49 4.99 6.85 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

317 Prosthion-Bregma

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (mm) (mm) (%) (mm) (mm) (%) (mm) (mm) (%)

Siberia 28 173.52 153.12 - 183.47 7.56 4.37 18 174.89 166.57 - 183.47 5.55 3.16 10 165.86 153.12 - 179.48 8.50 5.05 Mongolia 24 170.46 163.41 - 191.79 7.85 4.55 15 173.15 163.72 - 191.79 8.44 4.83 9 168.42 163.41 - 182.06 5.64 3.33 Korea 4 175.30 158.29 - 183.96 11.24 12.98 2 177.62 171.29 - 183.96 8.96 7.57 2 168.80 158.29 - 179.32 14.87 13.21 Ainu 3 174.69 171.58 - 175.12 1.93 1.95 2 173.35 171.58 - 175.12 2.51 2.17 1 174.69 174.69 - 174.69 - - Japan 13 166.44 153.19 - 185.30 7.62 4.54 10 168.96 163.68 - 185.30 6.44 3.79 3 160.79 153.19 - 166.44 6.65 7.27 S. China 6 167.88 158.04 - 180.10 8.39 4.96 3 177.39 167.95 - 180.10 6.38 6.37 3 163.04 158.04 - 167.80 4.88 5.24 N. China 16 173.79 157.66 - 193.70 10.01 5.72 13 174.16 163.18 - 193.70 9.19 5.20 3 163.29 157.66 - 178.54 10.80 11.36 Burma 39 168.23 150.93 - 183.57 7.97 4.74 22 173.39 152.53 - 183.57 7.63 4.43 17 163.78 150.93 - 169.93 5.15 3.15 Laos 24 170.13 158.37 - 181.01 5.72 3.36 16 170.92 158.37 - 181.01 6.29 3.70 8 169.45 164.93 - 177.14 4.74 2.79 Vietnam 23 171.63 162.58 - 182.71 5.82 3.41 13 172.84 167.44 - 182.71 4.59 2.64 10 164.84 162.58 - 171.63 3.18 1.92 Thailand 21 170.14 152.42 - 183.37 7.75 4.56 15 170.61 160.88 - 183.37 6.08 3.53 6 162.61 152.42 - 177.12 9.02 5.49 Cambodia 13 167.24 150.26 - 183.83 8.86 5.30 4 172.62 166.10 - 183.83 7.38 8.49 9 164.48 150.26 - 177.63 8.03 4.89 Philippines 28 166.20 156.97 - 180.15 6.56 3.93 22 167.39 158.23 - 180.15 6.29 3.75 6 162.64 156.97 - 177.91 7.61 4.62 Andaman Is. 36 159.13 150.40 - 170.50 5.83 3.66 18 162.05 151.25 - 170.50 5.76 3.56 18 155.66 150.40 - 166.70 4.92 3.14 Nicobar Is. 20 167.67 150.26 - 177.11 6.78 4.06 17 167.62 150.26 - 177.11 7.34 4.40 3 167.95 165.05 - 169.61 2.31 2.41 Borneo 37 166.90 156.67 - 181.89 6.57 3.91 26 167.80 156.67 - 181.89 6.91 4.08 11 164.27 158.30 - 176.34 4.84 2.92 Indonesia 27 169.72 156.54 - 184.38 6.36 3.75 20 170.08 164.17 - 184.38 5.24 3.05 7 163.85 156.54 - 176.15 7.19 4.36 Melanesia 30 168.80 149.72 - 179.70 7.45 4.44 20 170.48 159.38 - 179.70 6.09 3.59 10 168.68 149.72 - 173.37 8.66 5.29 Micronesia 15 168.53 161.88 - 179.10 4.98 2.95 7 170.63 161.88 - 179.10 5.92 3.45 8 167.54 162.85 - 169.64 2.85 1.71 Australia 27 168.94 158.09 - 185.60 7.07 4.14 18 174.15 162.49 - 185.60 6.40 3.69 9 164.12 158.09 - 174.22 4.77 2.89 Africa 29 168.59 158.84 - 180.23 6.41 3.78 18 168.70 162.05 - 180.23 7.14 4.18 11 168.59 158.84 - 172.07 4.57 2.73 Nat. America 33 172.05 156.92 - 181.81 6.87 4.02 10 176.77 156.92 - 181.81 7.13 4.09 23 168.63 157.27 - 178.57 6.23 3.68 Caucasian 29 166.46 152.86 - 182.00 7.74 4.68 15 169.53 152.86 - 182.00 7.86 4.66 14 159.64 153.35 - 174.75 6.15 3.79 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

318 Nasion-Alare

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (mm) (mm) (%) (mm) (mm) (%) (mm) (mm) (%)

Siberia 28 55.36 48.63 - 62.04 3.78 6.87 18 56.56 48.83 - 62.04 3.48 6.17 10 52.88 48.63 - 58.19 3.08 5.87 Mongolia 24 53.81 43.93 - 58.49 3.16 5.88 15 55.39 50.64 - 58.49 2.33 4.23 9 51.95 43.93 - 55.85 3.32 6.43 Korea 4 55.00 47.24 - 57.62 4.74 17.65 2 55.38 53.13 - 57.62 3.17 8.59 2 52.05 47.24 - 56.87 6.80 19.61 Ainu 3 51.84 47.24 - 57.05 4.91 16.51 2 49.54 47.24 - 51.84 3.25 9.85 1 57.05 57.05 - 57.05 - - Japan 13 52.10 44.41 - 56.49 3.47 6.72 10 53.22 49.51 - 56.49 2.31 4.37 3 46.38 44.41 - 51.46 3.64 13.42 S. China 6 51.28 46.42 - 56.21 3.62 7.02 3 51.37 51.20 - 56.21 2.85 9.41 3 49.10 46.42 - 54.92 4.34 15.15 N. China 16 53.20 44.79 - 62.40 4.54 8.41 13 53.32 49.75 - 62.40 4.06 7.40 3 50.48 44.79 - 55.89 5.55 19.28 Burma 39 52.46 46.67 - 58.47 3.13 5.95 22 54.19 47.22 - 58.16 3.21 6.05 17 50.75 46.67 - 58.47 2.88 5.57 Laos 24 52.92 48.58 - 59.44 2.85 5.36 16 52.92 48.58 - 58.57 2.83 5.32 8 52.70 49.25 - 59.44 3.08 5.82 Vietnam 23 52.04 47.77 - 56.33 2.48 4.80 13 52.62 48.36 - 55.24 2.08 3.96 10 50.83 47.77 - 56.33 2.75 5.42 Thailand 21 53.30 42.70 - 58.28 4.19 8.08 15 53.78 49.07 - 58.28 2.72 5.08 6 47.06 42.70 - 55.99 4.53 9.50 Cambodia 13 52.38 49.76 - 57.44 2.24 4.29 4 50.69 50.54 - 54.12 1.74 6.77 9 52.39 49.76 - 57.44 2.45 4.65 Philippines 28 52.02 45.96 - 59.60 3.56 6.78 22 52.28 46.57 - 59.60 3.62 6.84 6 51.53 45.96 - 54.22 3.12 6.12 Andaman Is. 36 47.71 38.99 - 55.51 3.19 6.72 18 48.27 42.31 - 52.10 2.50 5.18 18 46.24 38.99 - 55.51 3.67 7.85 Nicobar Is. 20 50.65 47.43 - 59.60 3.17 6.15 17 50.92 47.43 - 59.60 3.33 6.41 3 49.38 48.98 - 50.65 0.88 3.09 Borneo 37 50.79 46.46 - 59.88 3.05 5.93 26 51.11 46.80 - 59.88 2.94 5.67 11 49.36 46.46 - 57.00 3.07 6.12 Indonesia 27 53.68 48.94 - 59.55 3.21 5.98 20 54.40 48.94 - 59.55 3.03 5.57 7 50.00 49.19 - 56.61 3.00 5.82 Melanesia 30 52.14 46.03 - 61.38 3.57 6.84 20 53.68 48.19 - 61.38 3.32 6.23 10 49.09 46.03 - 55.05 2.97 5.97 Micronesia 15 52.85 45.56 - 61.14 4.02 7.64 7 54.29 47.86 - 61.14 4.15 7.58 8 50.85 45.56 - 55.72 3.16 6.21 Australia 27 51.14 43.98 - 58.19 3.23 6.34 18 51.48 47.50 - 58.19 2.69 5.18 9 50.23 43.98 - 54.06 3.66 7.44 Africa 29 51.02 46.52 - 60.66 2.95 5.71 18 51.26 48.71 - 60.66 3.01 5.76 11 50.58 46.52 - 56.23 2.75 5.42 Nat. America 33 50.62 32.73 - 57.25 4.65 9.27 10 52.43 45.29 - 56.27 3.36 6.49 23 49.26 32.73 - 57.25 5.00 10.12 Caucasian 29 50.47 47.20 - 57.36 2.62 5.13 15 51.13 47.20 - 57.36 2.84 5.49 14 49.88 47.95 - 56.46 2.20 4.38 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

319 Right Frontomalare Orbitale-Maxillofrontale

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (mm) (mm) (%) (mm) (mm) (%) (mm) (mm) (%)

Siberia 28 42.69 38.21 - 46.84 2.12 4.96 18 43.68 40.71 - 46.84 1.91 4.41 10 41.20 38.21 - 46.20 2.14 5.15 Mongolia 24 41.36 38.06 - 45.65 1.97 4.73 15 42.05 39.72 - 45.65 1.96 4.63 9 40.37 38.06 - 42.48 1.46 3.60 Korea 4 39.75 34.46 - 41.71 3.26 16.74 2 39.75 38.57 - 40.94 1.68 6.33 2 38.08 34.46 - 41.71 5.12 20.17 Ainu 3 41.87 36.85 - 43.65 3.53 15.14 2 40.25 36.85 - 43.65 4.81 17.93 1 41.87 41.87 - 41.87 - - Japan 13 40.33 37.38 - 45.97 2.31 5.61 10 40.80 39.19 - 45.97 2.27 5.47 3 39.99 37.38 - 41.68 2.17 9.57 S. China 6 39.98 36.64 - 45.95 3.19 7.86 3 42.10 39.22 - 45.95 3.38 13.94 3 39.04 36.64 - 40.74 2.06 9.31 N. China 16 41.23 35.44 - 45.39 2.61 6.36 13 41.32 37.81 - 45.39 2.31 5.55 3 39.52 35.44 - 41.58 3.12 14.06 Burma 39 41.16 36.52 - 45.18 2.36 5.73 22 42.18 38.83 - 45.18 1.68 3.97 17 39.71 36.52 - 44.37 2.27 5.73 Laos 24 41.02 36.88 - 43.19 1.63 4.01 16 40.90 37.69 - 43.00 1.45 3.57 8 41.20 36.88 - 43.19 2.06 5.04 Vietnam 23 41.08 38.25 - 44.63 1.83 4.47 13 41.54 38.53 - 44.63 1.93 4.64 10 40.74 38.25 - 41.95 1.42 3.54 Thailand 21 40.50 36.08 - 44.85 1.96 4.84 15 40.57 38.65 - 44.85 1.73 4.21 6 38.96 36.08 - 41.98 1.87 4.79 Cambodia 13 41.03 37.60 - 46.10 2.43 5.89 4 42.48 40.60 - 46.10 2.38 11.10 9 40.72 37.60 - 44.41 2.21 5.43 Philippines 28 40.38 36.58 - 44.54 1.88 4.66 22 40.59 37.05 - 44.54 1.63 3.98 6 38.18 36.58 - 41.05 1.48 3.86 Andaman Is. 36 38.60 36.27 - 41.77 1.32 3.41 18 38.75 36.27 - 41.19 1.33 3.44 18 38.44 36.29 - 41.77 1.33 3.44 Nicobar Is. 20 40.75 37.52 - 44.89 1.60 3.91 17 40.81 37.52 - 44.89 1.70 4.14 3 39.87 39.82 - 41.20 0.78 3.40 Borneo 37 39.94 35.00 - 46.92 2.22 5.48 26 40.48 35.00 - 46.92 2.44 5.96 11 39.38 37.98 - 43.74 1.43 3.60 Indonesia 27 40.23 37.47 - 45.74 2.20 5.40 20 40.54 37.73 - 45.74 2.21 5.36 7 38.99 37.47 - 41.21 1.37 3.48 Melanesia 30 41.32 37.98 - 45.12 1.81 4.35 20 42.20 40.47 - 45.12 1.39 3.28 10 40.33 37.98 - 41.09 1.22 3.05 Micronesia 15 41.95 38.12 - 46.40 2.16 5.14 7 43.05 40.26 - 45.57 1.56 3.63 8 40.75 38.12 - 46.40 2.40 5.82 Australia 27 43.34 38.50 - 47.29 2.00 4.66 18 43.62 40.59 - 47.29 1.68 3.84 9 42.08 38.50 - 44.66 2.01 4.82 Africa 29 41.88 38.91 - 44.90 1.76 4.20 18 41.97 39.20 - 44.90 1.76 4.19 11 41.43 38.91 - 44.03 1.77 4.28 Nat. America 33 40.94 37.30 - 43.41 1.78 4.39 10 41.41 37.30 - 43.40 1.91 4.66 23 40.43 37.51 - 43.41 1.73 4.30 Caucasian 29 40.87 37.26 - 45.54 2.04 5.03 15 41.01 37.75 - 45.54 2.28 5.58 14 40.60 37.26 - 42.10 1.72 4.28 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

320 Left Frontomalare Orbitale-Maxillofrontale

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (mm) (mm) (%) (mm) (mm) (%) (mm) (mm) (%)

Siberia 28 42.18 37.81 - 46.92 2.43 5.75 18 42.48 37.81 - 46.92 2.46 5.76 10 41.01 38.26 - 45.96 2.27 5.49 Mongolia 24 41.18 37.33 - 46.78 2.27 5.54 15 41.18 38.21 - 46.78 2.36 5.67 9 39.39 37.33 - 42.28 1.81 4.52 Korea 4 40.51 33.59 - 41.20 3.59 18.45 2 40.95 40.70 - 41.20 0.35 1.28 2 36.95 33.59 - 40.31 4.76 19.31 Ainu 3 40.56 37.04 - 43.22 3.10 13.49 2 40.13 37.04 - 43.22 4.38 16.35 1 40.56 40.56 - 40.56 - - Japan 13 39.56 38.75 - 45.33 1.84 4.54 10 40.26 38.75 - 45.33 1.99 4.88 3 39.47 39.17 - 39.56 0.21 0.92 S. China 6 41.41 35.27 - 46.01 3.78 9.23 3 43.35 41.55 - 46.01 2.24 9.00 3 38.25 35.27 - 41.28 3.00 13.74 N. China 16 40.46 34.29 - 45.41 2.74 6.84 13 40.79 36.65 - 45.41 2.41 5.93 3 37.97 34.29 - 40.77 3.25 15.09 Burma 39 40.67 35.77 - 44.34 2.15 5.33 22 41.52 37.46 - 44.34 1.66 4.02 17 39.14 35.77 - 42.55 2.10 5.37 Laos 24 40.70 37.20 - 42.69 1.52 3.77 16 40.63 37.20 - 42.50 1.42 3.54 8 41.08 37.90 - 42.69 1.78 4.40 Vietnam 23 40.47 37.44 - 43.20 1.63 4.03 13 41.03 38.10 - 42.52 1.52 3.72 10 40.37 37.44 - 43.20 1.78 4.45 Thailand 21 39.82 35.60 - 43.80 1.80 4.53 15 40.00 38.41 - 43.80 1.55 3.83 6 38.47 35.60 - 40.69 1.66 4.32 Cambodia 13 40.47 36.74 - 43.42 2.35 5.88 4 41.71 40.83 - 43.42 1.16 5.53 9 39.26 36.74 - 43.24 2.27 5.80 Philippines 28 39.69 36.43 - 43.87 2.29 5.75 22 40.34 36.63 - 43.87 2.14 5.29 6 37.19 36.43 - 40.63 1.62 4.28 Andaman Is. 36 37.54 34.78 - 41.16 1.43 3.81 18 37.90 34.78 - 40.02 1.34 3.54 18 37.14 35.35 - 41.16 1.55 4.13 Nicobar Is. 20 39.45 36.60 - 41.98 1.28 3.25 17 39.54 36.60 - 41.98 1.39 3.50 3 39.15 39.04 - 39.71 0.36 1.59 Borneo 37 39.44 36.57 - 45.10 2.16 5.43 26 39.83 36.75 - 45.10 2.19 5.43 11 38.01 36.57 - 41.51 1.55 4.00 Indonesia 27 39.76 37.15 - 45.71 1.88 4.69 20 40.53 38.16 - 45.71 1.78 4.38 7 38.52 37.15 - 39.76 1.00 2.61 Melanesia 30 41.35 37.88 - 44.86 1.80 4.36 20 41.83 37.88 - 44.86 1.89 4.52 10 40.06 38.48 - 41.68 1.01 2.51 Micronesia 15 40.16 36.83 - 46.53 2.86 6.99 7 42.04 39.32 - 46.53 2.38 5.66 8 39.37 36.83 - 46.45 3.02 7.57 Australia 27 42.58 38.76 - 46.24 1.77 4.17 18 43.04 40.33 - 46.24 1.52 3.55 9 41.02 38.76 - 43.57 1.76 4.27 Africa 29 41.56 38.04 - 44.96 1.78 4.30 18 42.10 39.59 - 44.96 1.67 3.99 11 40.13 38.04 - 42.83 1.58 3.91 Nat. America 33 40.94 36.20 - 43.45 1.71 4.21 10 41.21 37.73 - 42.58 1.50 3.67 23 40.89 36.20 - 43.45 1.82 4.48 Caucasian 29 39.32 36.46 - 45.15 2.32 5.84 15 39.81 36.62 - 45.15 2.60 6.42 14 39.06 36.46 - 41.55 1.80 4.60 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

321 Bijugal Breadth (JUB)

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (mm) (mm) (%) (mm) (mm) (%) (mm) (mm) (%)

Siberia 28 116.86 106.39 - 126.89 5.59 4.74 18 121.18 109.21 - 126.89 4.74 3.92 10 113.37 106.39 - 115.26 2.74 2.43 Mongolia 24 116.63 103.86 - 128.58 6.65 5.71 15 119.33 113.56 - 128.58 4.77 3.98 9 109.08 103.86 - 122.43 5.76 5.19 Korea 4 116.98 106.18 - 119.62 6.07 10.56 2 117.63 115.64 - 119.62 2.82 3.59 2 112.25 106.18 - 118.31 8.58 11.46 Ainu 3 114.25 110.24 - 120.61 5.23 7.96 2 117.43 114.25 - 120.61 4.50 5.74 1 110.24 110.24 - 110.24 - - Japan 13 115.85 104.88 - 122.43 5.46 4.76 10 116.73 109.95 - 122.43 4.15 3.56 3 106.35 104.88 - 115.85 5.96 9.56 S. China 6 120.00 111.38 - 128.29 6.37 5.36 3 121.94 118.49 - 128.29 4.97 7.08 3 112.42 111.38 - 121.52 5.58 8.48 N. China 16 114.67 97.51 - 126.34 7.22 6.29 13 116.78 109.92 - 126.34 5.35 4.57 3 105.86 97.51 - 113.13 7.81 12.96 Burma 39 114.41 101.00 - 122.54 6.01 5.29 22 117.65 106.34 - 122.54 5.01 4.31 17 110.38 101.00 - 119.42 5.55 5.04 Laos 24 114.01 109.51 - 122.09 3.68 3.21 16 116.61 109.98 - 122.09 3.90 3.37 8 112.69 109.51 - 117.37 2.37 2.09 Vietnam 23 116.61 109.52 - 124.92 4.60 3.97 13 118.41 109.73 - 124.92 4.31 3.65 10 112.89 109.52 - 116.66 2.27 2.02 Thailand 21 115.09 102.97 - 126.25 4.91 4.28 15 116.65 112.02 - 126.25 3.41 2.91 6 110.61 102.97 - 111.27 3.18 2.92 Cambodia 13 114.29 104.25 - 122.01 4.69 4.11 4 116.91 113.61 - 122.01 4.19 7.14 9 114.29 104.25 - 117.03 4.31 3.83 Philippines 28 114.68 102.76 - 125.84 5.66 4.96 22 115.98 106.45 - 125.84 4.46 3.85 6 106.97 102.76 - 112.73 3.40 3.17 Andaman Is. 36 108.36 102.25 - 115.83 3.89 3.60 18 110.38 102.25 - 114.34 3.35 3.06 18 105.41 102.76 - 115.83 3.97 3.73 Nicobar Is. 20 113.13 106.65 - 122.42 3.96 3.50 17 113.43 107.31 - 122.42 3.71 3.26 3 109.03 106.65 - 110.73 2.05 3.30 Borneo 37 113.45 102.32 - 125.02 5.71 5.01 26 116.43 102.32 - 125.02 5.43 4.68 11 109.14 103.19 - 111.76 2.32 2.13 Indonesia 27 116.57 106.02 - 122.21 4.66 4.03 20 117.54 106.02 - 122.21 4.02 3.42 7 110.35 107.21 - 115.21 2.51 2.26 Melanesia 30 113.83 101.58 - 124.33 5.04 4.46 20 115.18 110.03 - 124.33 3.58 3.10 10 109.50 101.58 - 114.46 4.20 3.88 Micronesia 15 114.66 104.87 - 124.22 5.97 5.24 7 118.32 114.61 - 124.22 3.79 3.19 8 108.99 104.87 - 115.89 3.95 3.60 Australia 27 116.60 104.08 - 124.39 6.08 5.26 18 119.67 105.95 - 124.39 4.87 4.12 9 110.80 104.08 - 118.27 4.75 4.30 Africa 29 118.09 108.79 - 123.75 4.21 3.58 18 118.26 108.79 - 123.75 4.19 3.55 11 117.86 111.16 - 123.29 4.38 3.74 Nat. America 33 114.73 106.10 - 120.89 3.81 3.33 10 115.21 109.99 - 120.88 3.57 3.08 23 114.26 106.10 - 120.89 3.81 3.35 Caucasian 29 111.31 100.70 - 120.96 5.01 4.51 15 113.15 106.23 - 120.96 4.35 3.82 14 108.44 100.70 - 115.09 4.26 3.92 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

322 Interorbital Breadth (mf-mf)

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (mm) (mm) (%) (mm) (mm) (%) (mm) (mm) (%)

Siberia 28 18.52 13.13 - 24.81 3.22 17.66 18 18.94 14.18 - 24.81 2.96 15.64 10 15.60 13.13 - 21.56 3.38 19.99 Mongolia 24 16.89 12.64 - 22.35 2.27 13.39 15 16.76 14.47 - 20.30 1.75 10.31 9 17.02 12.64 - 22.35 3.08 18.16 Korea 4 17.22 15.26 - 17.44 1.03 12.24 2 17.28 17.13 - 17.44 0.22 1.94 2 16.28 15.26 - 17.31 1.46 13.40 Ainu 3 17.61 17.26 - 19.17 1.02 9.88 2 18.39 17.61 - 19.17 1.10 8.97 1 17.26 17.26 - 17.26 - - Japan 13 16.41 13.25 - 20.59 1.86 11.34 10 16.41 14.52 - 18.06 1.25 7.66 3 16.14 13.25 - 20.59 3.70 38.84 S. China 6 20.86 17.62 - 24.83 2.58 12.36 3 20.57 18.69 - 24.83 3.15 25.78 3 21.14 17.62 - 22.30 2.44 20.96 N. China 16 18.39 13.70 - 20.60 2.46 13.86 13 19.04 13.70 - 20.60 2.62 14.51 3 16.42 15.32 - 18.15 1.43 15.02 Burma 39 16.90 11.58 - 25.39 2.52 14.79 22 17.62 13.41 - 25.39 2.75 15.55 17 16.39 11.58 - 19.54 1.95 12.08 Laos 24 17.72 14.90 - 22.36 1.82 10.05 16 18.61 16.17 - 22.36 1.65 8.84 8 16.57 14.90 - 20.34 1.71 10.05 Vietnam 23 18.69 13.72 - 21.83 2.57 14.23 13 20.03 14.47 - 21.83 2.41 12.59 10 16.64 13.72 - 19.18 2.13 12.79 Thailand 21 17.57 12.08 - 20.43 2.39 13.81 15 18.37 12.73 - 20.43 2.40 13.57 6 16.63 12.08 - 18.77 2.27 13.92 Cambodia 13 18.97 15.34 - 25.52 2.86 15.17 4 19.51 16.64 - 25.52 3.76 37.04 9 18.24 15.34 - 22.50 2.33 12.82 Philippines 28 18.65 13.64 - 26.37 2.33 12.44 22 18.88 13.64 - 26.37 2.57 13.68 6 18.31 17.11 - 19.90 1.14 6.22 Andaman Is. 36 18.67 13.99 - 23.14 2.10 11.20 18 18.88 16.48 - 22.27 1.75 9.12 18 18.12 13.99 - 23.14 2.40 13.02 Nicobar Is. 20 17.49 13.83 - 21.69 2.37 13.14 17 17.24 13.83 - 21.69 2.47 13.81 3 19.45 16.78 - 20.27 1.83 16.96 Borneo 37 18.69 12.38 - 28.01 3.53 19.27 26 19.87 12.94 - 28.01 3.55 18.41 11 16.21 12.38 - 19.81 2.18 13.67 Indonesia 27 18.54 15.33 - 21.47 2.04 11.06 20 18.60 15.33 - 21.47 1.88 10.03 7 16.39 15.43 - 21.36 2.41 13.64 Melanesia 30 18.08 13.55 - 24.33 2.46 13.43 20 19.69 13.55 - 24.33 2.35 12.27 10 16.49 14.79 - 20.66 1.81 10.88 Micronesia 15 18.42 15.44 - 24.54 2.26 12.15 7 18.42 16.73 - 24.54 2.73 14.12 8 18.41 15.44 - 19.81 1.62 9.07 Australia 27 18.92 15.85 - 27.00 2.61 13.44 18 20.66 16.23 - 27.00 2.54 12.46 9 17.56 15.85 - 20.67 1.49 8.50 Africa 29 21.13 17.92 - 26.63 2.42 11.03 18 22.72 17.92 - 26.29 2.47 11.08 11 20.31 18.75 - 26.63 2.32 10.89 Nat. America 33 18.93 15.39 - 25.27 2.34 12.05 10 18.68 16.96 - 25.27 2.91 14.69 23 19.03 15.39 - 23.64 2.12 11.04 Caucasian 29 19.16 13.79 - 25.32 2.96 15.33 15 20.26 16.40 - 24.48 2.65 13.04 14 18.56 13.79 - 25.32 2.97 16.32 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

323 Bi-frontomalare Orbitale

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (mm) (mm) (%) (mm) (mm) (%) (mm) (mm) (%)

Siberia 28 100.45 93.38 - 107.69 4.10 4.11 18 101.69 93.70 - 107.69 3.66 3.60 10 96.35 93.38 - 102.30 3.11 3.21 Mongolia 24 96.44 89.15 - 105.41 4.42 4.56 15 97.07 91.45 - 105.41 4.04 4.11 9 94.17 89.15 - 102.55 4.26 4.50 Korea 4 94.77 84.29 - 96.52 5.60 12.10 2 95.46 94.40 - 96.52 1.50 2.35 2 89.71 84.29 - 95.14 7.67 12.82 Ainu 3 96.23 88.84 - 101.97 6.58 12.04 2 95.40 88.84 - 101.97 9.29 14.60 1 96.23 96.23 - 96.23 - - Japan 13 94.51 89.74 - 103.99 3.77 3.96 10 95.29 91.84 - 103.99 3.67 3.82 3 92.44 89.74 - 93.49 1.94 3.69 S. China 6 100.07 87.51 - 107.90 6.74 6.80 3 102.07 100.32 - 107.90 3.97 6.71 3 97.03 87.51 - 99.82 6.45 11.92 N. China 16 96.76 83.37 - 101.80 5.04 5.25 13 98.34 89.48 - 101.80 3.80 3.91 3 91.70 83.37 - 93.52 5.41 10.57 Burma 39 94.89 87.47 - 106.42 5.01 5.27 22 97.45 89.45 - 106.42 4.14 4.24 17 90.79 87.47 - 101.13 4.08 4.44 Laos 24 96.48 91.81 - 99.85 2.18 2.26 16 96.96 91.81 - 99.85 2.06 2.12 8 94.65 93.13 - 99.36 1.98 2.08 Vietnam 23 96.25 89.23 - 103.55 3.87 4.01 13 96.96 91.59 - 103.55 3.44 3.50 10 93.27 89.23 - 98.64 2.63 2.81 Thailand 21 95.87 86.53 - 103.13 3.67 3.85 15 96.68 89.76 - 103.13 2.91 3.00 6 92.43 86.53 - 93.60 2.62 2.86 Cambodia 13 96.36 89.82 - 104.52 4.50 4.64 4 102.19 96.36 - 104.52 3.51 6.92 9 94.97 89.82 - 99.21 3.43 3.61 Philippines 28 95.71 87.00 - 103.70 4.39 4.57 22 96.61 90.95 - 103.70 3.63 3.74 6 90.49 87.00 - 98.47 4.02 4.40 Andaman Is. 36 90.21 83.96 - 99.86 2.99 3.30 18 91.03 86.86 - 95.92 2.54 2.78 18 89.66 83.96 - 99.86 3.34 3.70 Nicobar Is. 20 95.31 90.01 - 105.03 3.09 3.23 17 95.49 90.01 - 105.03 3.34 3.48 3 95.05 94.59 - 95.19 0.32 0.58 Borneo 37 93.78 84.91 - 109.55 5.51 5.78 26 96.78 84.91 - 109.55 5.47 5.63 11 91.05 87.29 - 95.30 2.36 2.59 Indonesia 27 96.62 87.83 - 105.42 4.27 4.43 20 97.58 89.86 - 105.42 3.60 3.68 7 93.27 87.83 - 96.21 3.60 3.90 Melanesia 30 97.10 89.55 - 109.55 4.10 4.20 20 99.09 95.33 - 109.55 3.27 3.29 10 93.16 89.55 - 97.12 2.02 2.16 Micronesia 15 98.17 90.73 - 106.27 5.29 5.42 7 99.04 97.65 - 106.27 3.74 3.71 8 93.14 90.73 - 105.27 4.94 5.22 Australia 27 102.16 92.30 - 109.29 4.70 4.64 18 103.34 94.48 - 109.29 3.81 3.68 9 96.16 92.30 - 103.17 3.08 3.18 Africa 29 100.47 94.29 - 107.96 3.79 3.77 18 101.13 94.29 - 107.96 3.79 3.74 11 97.97 94.56 - 103.27 3.40 3.43 Nat. America 33 97.92 90.10 - 103.64 3.17 3.25 10 99.60 91.86 - 103.64 3.53 3.58 23 97.61 90.10 - 103.28 2.99 3.07 Caucasian 29 95.48 83.42 - 107.00 5.30 5.51 15 97.24 91.75 - 107.00 5.08 5.16 14 93.64 83.42 - 102.08 4.60 4.90 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

324 Bi-frontomalare Temporale

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (mm) (mm) (%) (mm) (mm) (%) (mm) (mm) (%)

Siberia 28 105.60 96.96 - 113.28 4.08 3.87 18 106.83 98.05 - 113.28 3.80 3.55 10 102.52 96.96 - 105.99 2.78 2.72 Mongolia 24 102.03 94.78 - 112.12 5.00 4.87 15 103.12 96.32 - 111.26 4.70 4.51 9 99.77 94.78 - 112.12 5.09 5.05 Korea 4 101.31 88.74 - 102.58 6.58 13.36 2 102.47 102.36 - 102.58 0.15 0.23 2 94.50 88.74 - 100.26 8.15 12.93 Ainu 3 102.11 96.63 - 109.99 6.72 11.43 2 103.31 96.63 - 109.99 9.45 13.72 1 102.11 102.11 - 102.11 - - Japan 13 100.22 94.48 - 107.36 4.28 4.27 10 101.77 95.70 - 107.36 4.13 4.07 3 95.77 94.48 - 100.22 3.01 5.44 S. China 6 105.95 97.50 - 115.23 5.63 5.31 3 106.38 105.89 - 115.23 5.26 8.43 3 105.14 97.50 - 106.01 4.68 7.96 N. China 16 102.29 88.90 - 110.13 5.47 5.40 13 102.88 93.26 - 110.13 4.54 4.42 3 96.71 88.90 - 99.44 5.47 10.07 Burma 39 101.30 92.02 - 109.97 4.81 4.77 22 103.44 96.85 - 109.97 3.70 3.59 17 96.94 92.02 - 106.88 4.40 4.49 Laos 24 103.45 98.43 - 107.22 2.38 2.31 16 103.73 98.43 - 107.22 2.18 2.10 8 101.03 99.44 - 106.00 2.52 2.48 Vietnam 23 102.05 95.63 - 108.98 4.02 3.92 13 105.61 96.61 - 108.98 3.38 3.22 10 99.67 95.63 - 103.91 2.40 2.42 Thailand 21 100.85 93.31 - 110.64 4.44 4.39 15 104.12 98.26 - 110.64 3.25 3.14 6 96.83 93.31 - 98.24 2.18 2.27 Cambodia 13 101.15 95.64 - 108.77 4.41 4.34 4 107.89 101.15 - 108.77 3.54 6.65 9 99.73 95.64 - 102.72 2.80 2.81 Philippines 28 102.67 91.61 - 110.25 4.68 4.59 22 102.92 96.26 - 110.25 3.97 3.85 6 97.24 91.61 - 104.99 4.36 4.48 Andaman Is. 36 96.73 92.57 - 105.25 2.83 2.91 18 98.48 94.73 - 103.72 2.51 2.55 18 95.62 92.57 - 105.25 2.91 3.02 Nicobar Is. 20 101.84 97.69 - 111.88 3.29 3.22 17 102.04 97.69 - 111.88 3.42 3.34 3 100.08 99.20 - 100.36 0.61 1.06 Borneo 37 100.97 88.10 - 114.33 5.54 5.43 26 103.57 88.10 - 114.33 5.65 5.44 11 97.36 95.59 - 102.24 1.79 1.83 Indonesia 27 103.01 94.80 - 111.71 4.30 4.18 20 104.30 94.94 - 111.71 3.80 3.65 7 99.76 94.80 - 103.01 3.28 3.32 Melanesia 30 104.09 93.41 - 112.15 4.20 4.08 20 105.20 101.07 - 112.15 2.60 2.47 10 98.61 93.41 - 101.59 2.36 2.40 Micronesia 15 104.62 97.12 - 115.19 5.55 5.34 7 106.76 104.30 - 115.19 4.07 3.77 8 98.39 97.12 - 108.52 4.06 4.05 Australia 27 106.78 98.86 - 114.81 5.39 5.05 18 110.76 99.35 - 114.81 4.49 4.10 9 100.87 98.86 - 106.78 2.54 2.50 Africa 29 107.52 99.73 - 113.95 3.76 3.51 18 108.33 102.03 - 113.95 3.43 3.18 11 104.80 99.73 - 111.68 4.08 3.86 Nat. America 33 104.70 96.93 - 110.49 3.32 3.19 10 104.80 97.22 - 109.85 3.66 3.51 23 103.86 96.93 - 110.49 3.24 3.12 Caucasian 29 100.05 88.52 - 111.14 5.13 5.07 15 102.75 97.37 - 111.14 4.78 4.63 14 98.68 88.52 - 106.12 4.60 4.65 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

325 Bi-zygomaxillare (ZMB)

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (mm) (mm) (%) (mm) (mm) (%) (mm) (mm) (%)

Siberia 28 98.47 88.29 - 106.54 5.36 5.45 18 101.18 89.56 - 106.54 4.93 4.91 10 94.60 88.29 - 99.61 3.98 4.21 Mongolia 24 98.54 90.26 - 111.07 5.19 5.23 15 101.00 92.11 - 111.07 4.99 4.93 9 97.88 90.26 - 102.72 4.24 4.40 Korea 4 94.83 92.13 - 103.91 5.52 11.46 2 98.02 92.13 - 103.91 8.33 12.74 2 94.83 92.38 - 97.28 3.46 5.48 Ainu 3 100.80 97.69 - 102.70 2.53 4.41 2 101.75 100.80 - 102.70 1.35 1.99 1 97.69 97.69 - 97.69 - - Japan 13 99.95 90.28 - 104.51 4.16 4.22 10 100.80 93.42 - 104.51 3.48 3.48 3 94.59 90.28 - 99.11 4.42 8.17 S. China 6 101.71 95.18 - 106.21 4.53 4.46 3 106.08 99.73 - 106.21 3.70 6.23 3 98.11 95.18 - 103.68 4.32 7.64 N. China 16 99.09 88.87 - 105.93 5.72 5.81 13 101.19 88.87 - 105.93 5.03 5.03 3 91.64 90.07 - 92.33 1.16 2.22 Burma 39 97.52 82.73 - 116.59 6.98 7.16 22 99.57 87.04 - 116.59 7.27 7.28 17 94.41 82.73 - 102.65 5.24 5.55 Laos 24 99.33 92.04 - 108.32 3.88 3.90 16 100.17 94.37 - 108.32 3.72 3.70 8 97.66 92.04 - 99.94 2.98 3.07 Vietnam 23 101.06 87.60 - 104.72 4.90 4.95 13 102.51 91.40 - 104.72 3.88 3.83 10 97.16 87.60 - 101.06 4.23 4.42 Thailand 21 99.18 92.41 - 108.16 4.86 4.85 15 102.47 94.52 - 108.16 4.32 4.25 6 95.09 92.41 - 103.13 3.84 4.00 Cambodia 13 98.95 90.73 - 117.53 7.05 7.05 4 98.98 96.32 - 107.38 4.81 9.58 9 98.36 90.73 - 117.53 8.11 8.12 Philippines 28 96.87 89.61 - 108.51 5.06 5.20 22 97.08 92.34 - 108.51 4.87 4.94 6 93.04 89.61 - 97.32 2.91 3.13 Andaman Is. 36 92.74 83.06 - 101.11 4.56 4.95 18 94.85 83.06 - 101.11 4.49 4.79 18 89.25 83.48 - 97.20 4.02 4.45 Nicobar Is. 20 97.52 91.65 - 104.53 3.56 3.65 17 97.61 91.65 - 104.53 3.81 3.91 3 97.52 94.28 - 97.65 1.91 3.47 Borneo 37 98.66 87.78 - 110.34 5.45 5.52 26 100.35 87.78 - 110.34 5.51 5.50 11 95.76 90.71 - 101.36 3.36 3.53 Indonesia 27 97.92 90.64 - 106.42 4.62 4.70 20 100.39 91.85 - 106.42 4.54 4.57 7 95.13 90.64 - 102.02 3.53 3.71 Melanesia 30 94.77 84.80 - 103.90 5.04 5.31 20 95.27 87.36 - 103.90 4.42 4.58 10 90.68 84.80 - 98.28 4.67 5.10 Micronesia 15 99.50 94.54 - 106.32 3.89 3.90 7 102.62 98.96 - 106.32 2.95 2.87 8 96.27 94.54 - 100.21 2.04 2.10 Australia 27 93.59 82.18 - 100.70 5.04 5.47 18 94.94 82.18 - 100.70 5.18 5.55 9 90.36 84.27 - 94.31 3.84 4.28 Africa 29 100.30 94.03 - 117.98 5.11 5.07 18 99.81 94.03 - 117.98 5.65 5.61 11 102.25 94.56 - 109.24 4.34 4.29 Nat. America 33 99.64 90.91 - 107.96 4.53 4.56 10 100.91 95.47 - 107.58 4.07 4.03 23 98.81 90.91 - 107.96 4.65 4.71 Caucasian 29 92.71 77.85 - 104.78 5.46 5.97 15 92.76 82.87 - 98.47 4.23 4.57 14 88.99 77.85 - 104.78 6.47 7.17 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

326 Bi-alare

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (mm) (mm) (%) (mm) (mm) (%) (mm) (mm) (%)

Siberia 28 14.32 10.71 - 17.18 1.57 11.05 18 14.42 11.73 - 17.18 1.45 10.09 10 13.54 10.71 - 16.92 1.83 13.08 Mongolia 24 13.75 12.41 - 16.61 1.38 9.69 15 15.01 12.41 - 16.61 1.56 10.71 9 13.39 12.94 - 15.76 0.92 6.64 Korea 4 16.87 15.64 - 17.85 0.98 11.70 2 16.74 15.64 - 17.85 1.56 14.01 2 16.87 16.40 - 17.34 0.66 5.91 Ainu 3 14.85 14.85 - 16.44 0.92 10.46 2 15.65 14.85 - 16.44 1.12 10.77 1 14.85 14.85 - 14.85 - - Japan 13 16.16 12.59 - 18.75 1.49 9.18 10 16.48 15.37 - 18.75 1.08 6.52 3 15.90 12.59 - 17.66 2.57 29.26 S. China 6 15.15 11.07 - 18.13 2.25 15.06 3 15.33 15.01 - 18.13 1.72 18.60 3 15.12 11.07 - 15.19 2.36 29.92 N. China 16 15.64 13.86 - 19.46 1.38 8.77 13 15.96 13.86 - 19.46 1.45 9.10 3 14.87 14.24 - 15.59 0.68 7.96 Burma 39 14.14 11.87 - 18.16 1.39 9.73 22 14.32 11.87 - 16.85 1.36 9.41 17 14.08 12.00 - 18.16 1.43 10.23 Laos 24 14.11 11.40 - 17.45 1.53 10.78 16 14.01 11.40 - 17.45 1.54 10.95 8 14.24 12.33 - 17.25 1.59 11.11 Vietnam 23 14.16 10.92 - 16.35 1.08 7.60 13 14.10 10.92 - 16.35 1.24 8.81 10 14.25 12.99 - 15.50 0.87 6.14 Thailand 21 13.51 11.72 - 18.29 1.68 11.99 15 13.67 11.98 - 18.29 1.82 12.87 6 13.45 11.72 - 15.46 1.32 9.71 Cambodia 13 13.57 12.44 - 15.42 0.91 6.66 4 14.00 13.31 - 14.73 0.59 8.46 9 13.17 12.44 - 15.42 1.03 7.58 Philippines 28 14.92 12.13 - 17.37 1.26 8.52 22 15.09 12.13 - 17.37 1.39 9.45 6 14.85 13.87 - 15.66 0.62 4.16 Andaman Is. 36 13.47 11.69 - 17.28 1.38 10.08 18 14.19 11.97 - 17.28 1.57 11.04 18 13.02 11.69 - 14.78 0.85 6.50 Nicobar Is. 20 13.18 11.96 - 17.43 1.45 10.52 17 13.23 11.96 - 17.43 1.55 11.22 3 13.13 13.09 - 14.57 0.84 10.80 Borneo 37 13.76 11.24 - 18.68 1.55 11.03 26 14.17 12.00 - 18.68 1.55 10.78 11 13.19 11.24 - 15.61 1.34 10.06 Indonesia 27 14.42 11.94 - 18.09 1.50 10.29 20 14.54 12.60 - 18.09 1.47 9.93 7 13.82 11.94 - 16.05 1.57 11.17 Melanesia 30 17.03 14.27 - 18.62 1.14 6.73 20 17.03 14.27 - 18.62 1.23 7.31 10 17.04 15.67 - 18.50 0.99 5.79 Micronesia 15 16.05 14.82 - 19.97 1.53 9.16 7 15.94 15.47 - 19.97 1.68 9.92 8 16.13 14.82 - 19.17 1.49 8.97 Australia 27 15.58 13.17 - 17.78 1.07 6.89 18 15.78 14.07 - 17.78 1.05 6.65 9 15.00 13.17 - 17.04 1.03 6.80 Africa 29 14.90 12.27 - 19.35 1.53 10.25 18 15.12 12.58 - 19.35 1.61 10.45 11 14.20 12.27 - 16.31 1.21 8.46 Nat. America 33 16.69 14.96 - 18.89 0.94 5.59 10 17.14 14.96 - 18.40 1.02 5.94 23 16.64 15.30 - 18.89 0.89 5.35 Caucasian 29 14.64 10.28 - 17.99 1.92 13.28 15 14.98 12.92 - 17.99 1.62 10.70 14 14.18 10.28 - 16.25 1.97 14.41 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

327 Cranial Height (BBH)

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (mm) (mm) (%) (mm) (mm) (%) (mm) (mm) (%)

Siberia 28 128.90 117.89 - 141.61 6.84 5.28 18 130.24 121.13 - 141.61 6.33 4.83 10 125.37 117.89 - 139.46 7.21 5.68 Mongolia 24 127.98 115.64 - 146.47 8.02 6.24 15 128.45 116.69 - 146.47 8.65 6.69 9 127.58 115.64 - 135.93 7.05 5.55 Korea 4 138.24 133.27 - 144.00 4.41 6.38 2 141.43 138.87 - 144.00 3.63 3.85 2 135.44 133.27 - 137.61 3.07 3.40 Ainu 3 131.03 129.74 - 136.68 3.69 4.87 2 133.21 129.74 - 136.68 4.91 5.52 1 131.03 131.03 - 131.03 - - Japan 13 132.37 123.03 - 138.84 5.01 3.79 10 134.84 125.51 - 138.84 3.91 2.92 3 126.12 123.03 - 128.56 2.77 3.85 S. China 6 131.05 125.66 - 142.29 6.09 4.59 3 131.47 130.62 - 136.89 3.40 4.47 3 128.16 125.66 - 142.29 8.97 11.89 N. China 16 135.30 125.14 - 149.83 7.24 5.33 13 137.92 126.99 - 149.83 6.25 4.53 3 126.47 125.14 - 129.15 2.04 2.81 Burma 39 133.31 117.25 - 144.22 6.21 4.69 22 135.58 125.98 - 144.22 4.58 3.39 17 126.26 117.25 - 137.89 5.87 4.58 Laos 24 132.29 125.14 - 141.52 3.88 2.92 16 133.63 130.11 - 139.33 2.80 2.09 8 129.23 125.14 - 141.52 4.96 3.79 Vietnam 23 135.30 116.22 - 146.86 6.56 4.85 13 138.02 116.22 - 146.86 7.63 5.56 10 133.59 125.98 - 136.61 3.76 2.84 Thailand 21 134.48 124.53 - 145.65 4.93 3.66 15 135.48 128.82 - 145.65 4.62 3.39 6 131.92 124.53 - 134.12 3.56 2.72 Cambodia 13 132.24 121.40 - 142.13 5.51 4.14 4 137.24 130.08 - 142.13 5.33 7.80 9 132.18 121.40 - 138.50 5.08 3.86 Philippines 28 130.25 118.34 - 144.10 5.83 4.43 22 129.92 118.34 - 144.10 6.49 4.91 6 130.46 128.09 - 131.47 1.37 1.06 Andaman Is. 36 125.30 116.62 - 142.14 5.72 4.51 18 130.41 121.26 - 142.14 5.38 4.13 18 123.05 116.62 - 131.82 3.32 2.69 Nicobar Is. 20 132.90 125.20 - 140.36 4.21 3.17 17 133.47 125.20 - 140.36 4.49 3.38 3 132.66 129.02 - 132.72 2.12 2.82 Borneo 37 133.39 118.86 - 145.59 5.91 4.41 26 135.67 118.86 - 145.59 6.07 4.51 11 131.33 125.90 - 142.00 5.37 4.06 Indonesia 27 134.25 121.12 - 146.47 5.67 4.25 20 135.57 128.09 - 146.47 4.18 3.09 7 126.18 121.12 - 135.55 5.10 4.00 Melanesia 30 132.03 121.29 - 144.47 5.83 4.42 20 132.03 121.29 - 144.47 5.38 4.05 10 129.81 122.09 - 141.69 6.67 5.12 Micronesia 15 134.02 130.49 - 143.37 4.27 3.16 7 137.71 131.32 - 143.37 4.70 3.42 8 132.13 130.49 - 139.02 2.80 2.11 Australia 27 131.40 119.50 - 143.41 6.00 4.55 18 133.13 125.00 - 143.41 4.76 3.54 9 126.32 119.50 - 130.87 3.77 2.99 Africa 29 129.60 117.25 - 143.93 5.78 4.45 18 131.81 121.73 - 143.93 5.09 3.86 11 127.98 117.25 - 136.73 5.94 4.67 Nat. America 33 130.98 120.36 - 142.75 4.39 3.36 10 132.61 127.50 - 142.75 4.12 3.09 23 130.01 120.36 - 138.92 4.07 3.14 Caucasian 29 126.84 113.48 - 145.85 6.43 5.05 15 130.79 124.67 - 145.85 5.66 4.30 14 124.34 113.48 - 130.20 4.12 3.34 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

328 Parietal Length (PAC)

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (mm) (mm) (%) (mm) (mm) (%) (mm) (mm) (%)

Siberia 28 106.41 93.56 - 117.91 6.61 6.17 18 108.77 97.35 - 117.91 5.97 5.48 10 100.98 93.56 - 113.69 6.46 6.24 Mongolia 24 105.36 92.94 - 116.01 6.12 5.82 15 108.82 92.94 - 116.01 7.25 6.85 9 104.62 97.93 - 110.17 3.68 3.54 Korea 4 109.56 95.26 - 114.14 8.89 16.59 2 113.95 113.76 - 114.14 0.27 0.35 2 100.31 95.26 - 105.37 7.14 10.68 Ainu 3 122.51 112.18 - 123.69 6.33 9.28 2 123.10 122.51 - 123.69 0.84 1.02 1 112.18 112.18 - 112.18 - - Japan 13 110.56 92.68 - 120.98 7.86 7.19 10 112.16 99.89 - 120.98 6.76 6.07 3 106.51 92.68 - 107.81 8.39 87.12 S. China 6 104.68 77.68 - 121.79 15.19 14.57 3 115.17 77.68 - 121.79 23.79 39.70 3 101.94 101.89 - 107.42 3.18 89.38 N. China 16 108.57 96.20 - 127.08 9.23 8.35 13 108.63 102.86 - 127.08 8.83 7.85 3 101.48 96.20 - 108.54 6.19 84.47 Burma 39 107.13 92.27 - 122.65 6.60 6.14 22 110.74 96.84 - 118.57 6.08 5.54 17 102.97 92.27 - 122.65 6.28 6.01 Laos 24 104.61 91.07 - 115.16 6.70 6.45 16 105.17 91.07 - 115.16 7.50 7.18 8 102.48 96.68 - 109.55 4.91 4.78 Vietnam 23 110.30 89.25 - 116.79 6.52 6.04 13 111.16 102.71 - 114.66 4.08 3.71 10 106.20 89.25 - 116.79 8.21 7.80 Thailand 21 102.76 93.22 - 116.98 6.47 6.24 15 103.66 98.22 - 113.37 4.89 4.66 6 96.86 93.22 - 116.98 9.26 9.18 Cambodia 13 104.74 90.72 - 122.19 8.22 7.85 4 108.64 104.74 - 113.58 4.35 7.99 9 100.29 90.72 - 122.19 9.05 8.80 Philippines 28 105.57 84.44 - 115.96 7.27 6.97 22 104.52 84.44 - 113.49 7.71 7.43 6 105.87 100.28 - 115.96 5.31 4.98 Andaman Is. 36 103.77 93.27 - 114.80 5.49 5.25 18 107.74 102.14 - 114.80 3.79 3.49 18 100.73 93.27 - 111.21 4.03 4.00 Nicobar Is. 20 113.62 97.33 - 126.08 6.31 5.51 17 113.12 97.33 - 126.08 6.86 5.99 3 113.74 113.50 - 115.72 1.22 1.87 Borneo 37 112.63 101.05 - 125.13 6.16 5.45 26 113.38 106.00 - 125.02 5.59 4.94 11 111.61 101.05 - 125.13 7.59 6.75 Indonesia 27 106.81 96.42 - 125.28 6.95 6.47 20 108.34 99.21 - 125.28 6.54 6.01 7 101.53 96.42 - 115.84 6.52 6.33 Melanesia 30 113.46 99.19 - 130.87 7.84 6.93 20 113.57 99.19 - 130.87 8.76 7.68 10 111.64 104.54 - 121.75 5.51 4.95 Micronesia 15 109.39 103.39 - 128.19 7.57 6.64 7 108.93 103.39 - 128.19 9.10 7.98 8 113.39 105.76 - 123.55 6.61 5.81 Australia 27 113.31 103.98 - 123.44 5.40 4.72 18 117.73 106.01 - 123.44 4.79 4.12 9 109.40 103.98 - 118.74 4.23 3.83 Africa 29 113.12 94.10 - 130.49 6.87 6.08 18 114.44 107.04 - 130.49 6.22 5.41 11 110.70 94.10 - 119.08 7.02 6.39 Nat. America 33 106.70 95.64 - 121.34 6.30 5.85 10 106.47 99.05 - 121.34 8.72 8.01 23 106.70 95.64 - 116.53 5.04 4.71 Caucasian 29 111.23 97.90 - 125.19 7.72 6.88 15 111.23 100.26 - 124.81 7.01 6.18 14 110.98 97.90 - 125.19 8.45 7.63 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

329 Nasion-Nasospinale

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (mm) (mm) (%) (mm) (mm) (%) (mm) (mm) (%)

Siberia 28 51.47 43.85 - 57.64 4.08 7.90 18 53.40 44.95 - 57.34 3.52 6.63 10 49.37 43.85 - 57.64 4.00 8.14 Mongolia 24 52.08 44.08 - 56.53 3.03 5.86 15 52.70 48.60 - 56.53 2.19 4.12 9 50.34 44.08 - 52.43 2.84 5.75 Korea 4 54.15 46.49 - 56.06 4.41 16.74 2 54.15 52.66 - 55.64 2.10 5.83 2 51.28 46.49 - 56.06 6.76 19.78 Ainu 3 49.44 46.27 - 52.62 3.18 11.24 2 47.86 46.27 - 49.44 2.25 7.05 1 52.62 52.62 - 52.62 - - Japan 13 51.77 43.17 - 54.68 2.99 5.88 10 52.09 48.89 - 54.68 1.66 3.20 3 47.61 43.17 - 50.13 3.53 13.13 S. China 6 49.61 46.52 - 54.52 3.28 6.54 3 49.70 49.53 - 53.58 2.29 7.88 3 47.13 46.52 - 54.52 4.45 15.78 N. China 16 51.39 42.12 - 60.30 4.34 8.27 13 51.43 49.01 - 60.30 3.60 6.77 3 50.26 42.12 - 55.28 6.64 23.62 Burma 39 50.20 44.30 - 57.82 3.29 6.57 22 50.91 44.30 - 57.82 3.44 6.79 17 48.52 45.04 - 55.72 2.98 6.05 Laos 24 49.96 46.86 - 55.61 2.53 5.03 16 50.30 46.86 - 55.61 2.64 5.24 8 49.12 47.43 - 53.58 2.46 4.90 Vietnam 23 50.14 46.28 - 55.00 2.51 5.02 13 51.05 46.69 - 53.98 1.95 3.84 10 48.17 46.28 - 55.00 2.85 5.83 Thailand 21 51.24 43.54 - 55.37 3.59 7.13 15 52.00 47.55 - 55.37 2.33 4.47 6 45.68 43.54 - 49.02 2.21 4.80 Cambodia 13 51.02 47.81 - 54.38 2.24 4.41 4 49.91 47.81 - 52.77 2.23 8.91 9 51.15 47.85 - 54.38 2.31 4.53 Philippines 28 49.37 44.02 - 57.86 3.36 6.85 22 49.37 44.02 - 57.86 3.40 6.85 6 47.40 44.20 - 51.24 2.98 6.27 Andaman Is. 36 45.87 37.86 - 51.62 3.17 6.94 18 46.60 39.18 - 51.62 3.18 6.83 18 44.42 37.86 - 50.23 2.96 6.62 Nicobar Is. 20 48.38 43.65 - 56.10 2.91 5.94 17 48.43 44.87 - 56.10 2.84 5.75 3 48.09 43.65 - 49.72 3.14 11.66 Borneo 37 48.11 43.63 - 57.40 3.08 6.30 26 48.61 45.19 - 57.40 3.21 6.51 11 47.61 43.63 - 51.95 2.36 4.96 Indonesia 27 50.69 43.21 - 55.76 3.19 6.34 20 51.28 43.21 - 55.76 3.19 6.29 7 49.16 45.62 - 54.49 3.28 6.63 Melanesia 30 49.12 43.54 - 57.50 3.31 6.63 20 49.76 46.92 - 57.50 2.89 5.70 10 47.46 43.54 - 53.49 3.68 7.62 Micronesia 15 50.73 41.24 - 56.66 4.09 8.13 7 52.81 45.95 - 56.66 3.36 6.46 8 49.12 41.24 - 54.13 4.25 8.72 Australia 27 47.66 41.37 - 53.09 2.85 5.97 18 49.20 44.64 - 53.09 2.46 5.05 9 46.95 41.37 - 48.01 2.49 5.44 Africa 29 48.23 41.90 - 53.23 2.73 5.60 18 48.20 45.23 - 53.23 2.69 5.48 11 48.33 41.90 - 51.79 2.74 5.72 Nat. America 33 48.88 42.23 - 57.30 3.42 7.00 10 49.76 44.11 - 57.30 3.67 7.30 23 47.65 42.23 - 55.36 3.20 6.64 Caucasian 29 47.33 42.58 - 53.62 3.14 6.61 15 48.61 44.13 - 53.62 3.48 7.16 14 47.09 42.58 - 50.32 2.36 5.09 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

330 Frontal Length (FRC)

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (mm) (mm) (%) (mm) (mm) (%) (mm) (mm) (%)

Siberia 28 110.52 92.27 - 119.77 5.93 5.38 18 111.62 98.02 - 119.77 5.36 4.81 10 107.89 92.27 - 115.04 6.60 6.10 Mongolia 24 112.60 103.06 - 120.63 4.73 4.25 15 113.16 103.06 - 120.63 5.17 4.63 9 109.20 104.36 - 115.33 4.00 3.63 Korea 4 114.49 105.15 - 118.36 5.90 10.43 2 114.49 112.29 - 116.69 3.11 4.08 2 111.75 105.15 - 118.36 9.34 12.53 Ainu 3 114.45 108.85 - 115.08 3.43 5.33 2 114.77 114.45 - 115.08 0.44 0.58 1 108.85 108.85 - 108.85 - - Japan 13 106.44 100.12 - 117.12 4.13 3.86 10 108.44 100.12 - 117.12 4.36 4.04 3 104.50 102.91 - 105.78 1.44 2.42 S. China 6 106.37 104.71 - 115.77 5.02 4.61 3 115.26 106.01 - 115.77 5.49 8.55 3 106.14 104.71 - 106.60 0.99 1.63 N. China 16 111.56 103.45 - 122.17 5.98 5.35 13 112.39 104.41 - 122.17 5.64 4.99 3 103.62 103.45 - 111.18 4.41 7.28 Burma 39 108.92 99.62 - 119.12 4.93 4.51 22 112.49 100.44 - 119.12 4.92 4.41 17 106.60 99.62 - 110.99 3.06 2.87 Laos 24 108.26 99.15 - 115.08 4.24 3.92 16 109.38 99.15 - 115.08 4.91 4.54 8 107.91 104.63 - 112.62 2.71 2.51 Vietnam 23 109.01 103.07 - 121.32 4.51 4.09 13 111.20 106.41 - 121.32 4.31 3.83 10 108.49 103.07 - 112.15 3.02 2.81 Thailand 21 109.54 97.36 - 120.48 5.60 5.12 15 109.54 97.36 - 117.97 5.14 4.68 6 108.36 99.84 - 120.48 7.08 6.53 Cambodia 13 109.28 96.66 - 119.88 6.28 5.79 4 111.29 108.45 - 119.88 5.22 9.26 9 107.04 96.66 - 115.71 5.98 5.61 Philippines 28 108.11 101.06 - 119.10 4.47 4.10 22 108.49 102.07 - 119.10 4.40 4.02 6 108.07 101.06 - 115.84 5.07 4.68 Andaman Is. 36 104.35 97.23 - 114.94 4.49 4.28 18 106.51 99.49 - 114.94 4.75 4.45 18 102.73 97.23 - 110.49 3.29 3.20 Nicobar Is. 20 109.81 95.85 - 119.22 5.02 4.60 17 109.80 95.85 - 119.22 5.45 5.00 3 109.81 109.32 - 110.76 0.73 1.17 Borneo 37 107.78 101.26 - 122.90 4.70 4.30 26 109.30 101.26 - 118.07 4.29 3.90 11 107.40 102.54 - 122.90 5.43 5.04 Indonesia 27 109.25 98.90 - 118.29 5.00 4.58 20 111.43 104.72 - 118.29 4.05 3.65 7 104.94 98.90 - 113.04 4.70 4.49 Melanesia 30 108.40 96.84 - 114.87 5.60 5.20 20 109.19 99.28 - 114.87 5.61 5.18 10 107.74 96.84 - 112.28 5.65 5.31 Micronesia 15 110.05 102.79 - 115.77 3.67 3.34 7 111.63 106.07 - 115.77 3.55 3.20 8 108.85 102.79 - 114.87 3.79 3.48 Australia 27 110.66 97.27 - 122.40 5.72 5.16 18 112.49 97.27 - 122.40 5.87 5.21 9 106.88 102.19 - 114.37 3.57 3.33 Africa 29 109.82 101.15 - 124.17 5.14 4.63 18 111.78 104.59 - 124.17 5.48 4.88 11 109.16 101.15 - 116.64 4.17 3.81 Nat. America 33 109.49 96.85 - 119.15 5.25 4.78 10 111.21 100.48 - 119.15 5.72 5.10 23 109.10 96.85 - 116.49 4.82 4.43 Caucasian 29 109.08 98.57 - 125.36 6.62 6.04 15 113.53 98.57 - 125.36 7.30 6.53 14 106.56 99.53 - 116.71 5.06 4.72 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

331 Nasion-Lambda

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (mm) (mm) (%) (mm) (mm) (%) (mm) (mm) (%)

Siberia 28 171.56 155.14 - 188.83 8.36 4.88 18 174.34 162.78 - 188.83 7.11 4.08 10 165.58 155.14 - 178.01 7.56 4.57 Mongolia 24 168.37 158.91 - 184.35 6.13 3.63 15 170.76 159.28 - 184.35 6.57 3.85 9 165.13 158.91 - 173.20 4.02 2.43 Korea 4 169.79 151.90 - 173.39 10.08 12.13 2 173.28 173.17 - 173.39 0.16 0.14 2 159.16 151.90 - 166.42 10.26 9.67 Ainu 3 174.75 144.31 - 188.13 22.46 23.25 2 166.22 144.31 - 188.13 30.99 27.96 1 174.75 174.75 - 174.75 - - Japan 13 169.54 154.51 - 184.48 8.07 4.76 10 171.22 158.81 - 184.48 7.31 4.26 3 165.46 154.51 - 166.34 6.59 7.12 S. China 6 161.34 152.55 - 182.80 10.85 6.59 3 170.87 152.55 - 182.80 15.24 15.80 3 159.11 158.15 - 163.57 2.89 3.15 N. China 16 171.76 158.73 - 185.80 7.58 4.41 13 173.29 163.98 - 185.80 6.51 3.75 3 160.00 158.73 - 170.57 6.50 6.97 Burma 39 166.19 152.06 - 179.29 7.30 4.39 22 169.75 158.63 - 179.29 6.04 3.56 17 161.81 152.06 - 176.76 7.09 4.36 Laos 24 163.43 153.07 - 173.87 5.57 3.43 16 164.09 154.96 - 173.87 5.49 3.35 8 158.29 153.07 - 165.05 4.55 2.86 Vietnam 23 169.24 147.49 - 183.72 7.61 4.52 13 170.04 160.57 - 183.72 6.21 3.65 10 167.82 147.49 - 175.16 8.91 5.36 Thailand 21 162.58 152.90 - 182.06 7.62 4.67 15 162.71 156.56 - 176.48 5.90 3.59 6 156.39 152.90 - 182.06 11.08 6.90 Cambodia 13 160.26 153.58 - 177.97 7.68 4.72 4 163.19 160.26 - 177.72 7.98 9.60 9 158.26 153.58 - 177.97 7.49 4.65 Philippines 28 167.48 152.63 - 176.53 6.47 3.90 22 167.61 152.63 - 176.53 6.22 3.73 6 160.41 155.22 - 171.24 6.88 4.23 Andaman Is. 36 160.69 151.50 - 171.60 4.88 3.04 18 163.69 154.12 - 171.60 4.41 2.70 18 157.22 151.50 - 164.22 3.07 1.95 Nicobar Is. 20 171.91 159.44 - 180.34 5.93 3.45 17 172.02 159.44 - 180.34 6.39 3.72 3 171.70 171.24 - 175.50 2.34 2.37 Borneo 37 169.92 156.92 - 184.20 6.89 4.05 26 171.06 156.92 - 184.20 6.67 3.90 11 167.71 157.90 - 183.22 7.39 4.39 Indonesia 27 166.15 150.85 - 184.09 8.86 5.31 20 167.37 150.85 - 184.09 8.87 5.27 7 162.46 151.35 - 173.85 7.84 4.83 Melanesia 30 172.36 157.48 - 187.25 7.21 4.19 20 174.16 162.48 - 187.25 6.96 4.00 10 170.08 157.48 - 177.29 6.40 3.80 Micronesia 15 171.02 161.69 - 182.69 6.17 3.60 7 176.86 164.35 - 179.23 5.29 3.04 8 169.51 161.69 - 182.69 6.40 3.78 Australia 27 173.07 164.87 - 187.31 6.37 3.65 18 178.02 165.87 - 187.31 5.91 3.34 9 168.73 164.87 - 173.07 2.59 1.53 Africa 29 177.92 164.19 - 189.44 5.82 3.27 18 180.24 169.35 - 189.44 5.62 3.13 11 176.30 164.19 - 180.08 4.57 2.62 Nat. America 33 171.05 152.41 - 181.07 6.14 3.62 10 173.19 152.41 - 181.07 8.53 4.96 23 170.26 158.16 - 176.22 4.66 2.76 Caucasian 29 173.52 162.59 - 190.07 7.28 4.16 15 178.48 166.55 - 190.07 7.22 4.06 14 171.41 162.59 - 185.44 6.36 3.69 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

332 Nasion-Opisthion

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (mm) (mm) (%) (mm) (mm) (%) (mm) (mm) (%)

Siberia 28 134.23 126.26 - 150.19 6.94 5.06 18 140.11 127.05 - 150.19 6.57 4.71 10 132.62 126.26 - 147.85 5.94 4.46 Mongolia 24 133.50 121.68 - 144.49 5.66 4.27 15 134.02 125.67 - 144.49 5.91 4.41 9 132.15 121.68 - 134.45 4.65 3.57 Korea 4 134.57 126.99 - 136.22 4.17 6.26 2 135.11 134.00 - 136.22 1.57 1.74 2 131.07 126.99 - 135.15 5.77 6.60 Ainu 3 136.36 134.28 - 136.67 1.30 1.68 2 136.51 136.36 - 136.67 0.22 0.24 1 134.28 134.28 - 134.28 - - Japan 13 134.47 122.66 - 136.89 4.73 3.57 10 135.47 125.97 - 136.89 3.59 2.68 3 126.96 122.66 - 131.14 4.24 5.84 S. China 6 129.74 123.49 - 137.61 6.38 4.90 3 133.85 125.63 - 136.32 5.60 7.42 3 124.55 123.49 - 137.61 7.87 10.71 N. China 16 132.73 123.33 - 141.54 5.00 3.78 13 133.62 129.08 - 141.54 3.44 2.56 3 124.44 123.33 - 127.05 1.91 2.67 Burma 39 130.26 121.12 - 141.29 5.49 4.18 22 134.39 125.16 - 141.29 4.75 3.55 17 128.74 121.12 - 140.56 4.70 3.67 Laos 24 129.35 121.69 - 136.93 3.72 2.88 16 129.66 126.50 - 136.93 3.03 2.32 8 126.73 121.69 - 134.40 4.25 3.34 Vietnam 23 131.79 121.27 - 141.96 4.63 3.50 13 134.30 128.89 - 141.96 4.21 3.14 10 131.30 121.27 - 136.16 4.33 3.33 Thailand 21 130.62 119.79 - 137.47 5.14 3.96 15 131.70 124.87 - 137.47 3.53 2.67 6 123.16 119.79 - 130.57 3.60 2.90 Cambodia 13 131.61 125.96 - 140.58 4.80 3.64 4 133.22 131.61 - 140.58 4.23 6.29 9 128.82 125.96 - 138.47 4.82 3.68 Philippines 28 129.76 117.32 - 143.83 6.04 4.62 22 131.78 117.32 - 143.83 5.93 4.51 6 126.35 120.77 - 139.48 6.22 4.86 Andaman Is. 36 122.72 116.45 - 132.24 4.40 3.58 18 125.00 119.96 - 132.24 3.82 3.04 18 119.36 116.45 - 124.91 2.78 2.32 Nicobar Is. 20 129.62 122.17 - 141.29 4.67 3.60 17 130.06 122.17 - 141.29 4.57 3.52 3 129.49 126.12 - 137.95 6.10 8.13 Borneo 37 131.20 120.18 - 141.92 5.03 3.82 26 132.81 120.18 - 141.92 5.45 4.12 11 129.06 124.75 - 132.77 2.85 2.21 Indonesia 27 132.48 119.20 - 142.63 5.96 4.54 20 133.33 122.45 - 142.63 5.48 4.13 7 124.50 119.20 - 134.21 5.40 4.26 Melanesia 30 133.17 121.05 - 142.49 5.60 4.22 20 133.73 126.61 - 140.90 4.16 3.10 10 128.72 121.05 - 142.49 7.24 5.56 Micronesia 15 133.25 122.35 - 142.86 6.57 4.94 7 139.08 127.37 - 142.86 5.46 3.96 8 129.44 122.35 - 134.47 4.17 3.24 Australia 27 133.02 123.63 - 148.25 6.27 4.70 18 135.16 127.57 - 148.25 5.83 4.28 9 128.30 123.63 - 133.87 3.42 2.67 Africa 29 136.42 125.83 - 144.20 4.51 3.31 18 137.54 125.83 - 144.20 4.77 3.48 11 136.12 129.42 - 142.33 4.00 2.96 Nat. America 33 132.67 123.21 - 147.27 5.24 3.93 10 136.92 123.21 - 147.27 6.69 4.93 23 131.36 125.16 - 141.98 4.27 3.23 Caucasian 29 132.25 120.09 - 142.22 5.48 4.17 15 133.68 127.37 - 142.22 4.14 3.07 14 127.32 120.09 - 133.69 4.03 3.16 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

333 Nasion-Basion (BNL)

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (mm) (mm) (%) (mm) (mm) (%) (mm) (mm) (%)

Siberia 28 98.80 91.95 - 109.78 4.92 4.91 18 100.37 94.75 - 109.78 4.55 4.48 10 98.19 91.95 - 108.62 4.78 4.90 Mongolia 24 96.46 88.75 - 108.50 4.38 4.52 15 96.66 89.40 - 108.50 4.73 4.85 9 96.27 88.75 - 98.88 3.56 3.73 Korea 4 100.13 95.45 - 102.75 3.04 6.10 2 100.13 100.03 - 100.22 0.13 0.20 2 99.10 95.45 - 102.75 5.16 7.81 Ainu 3 99.66 99.64 - 100.11 0.26 0.46 2 99.88 99.64 - 100.11 0.33 0.49 1 99.66 99.66 - 99.66 - - Japan 13 99.92 88.56 - 104.79 4.56 4.62 10 100.81 94.12 - 104.79 3.50 3.49 3 94.60 88.56 - 99.54 5.50 10.21 S. China 6 91.90 88.30 - 106.22 6.71 7.12 3 92.18 91.62 - 97.97 3.51 6.55 3 89.61 88.30 - 106.22 9.99 18.46 N. China 16 98.42 88.50 - 103.90 4.51 4.62 13 99.24 91.96 - 103.90 3.57 3.61 3 91.73 88.50 - 95.71 3.61 6.87 Burma 39 96.12 88.43 - 105.44 4.36 4.50 22 98.97 88.43 - 105.44 3.95 4.00 17 94.50 88.72 - 103.08 3.52 3.74 Laos 24 95.31 89.79 - 101.04 3.19 3.33 16 96.03 92.88 - 101.04 2.72 2.82 8 93.46 89.79 - 99.63 3.80 4.02 Vietnam 23 97.53 88.61 - 104.13 3.86 3.97 13 98.50 91.61 - 104.13 3.69 3.74 10 95.61 88.61 - 101.93 3.68 3.85 Thailand 21 97.14 86.65 - 104.86 4.51 4.69 15 97.37 93.72 - 104.86 2.85 2.90 6 90.63 86.65 - 92.36 2.00 2.22 Cambodia 13 97.37 88.56 - 103.25 3.96 4.09 4 98.49 91.86 - 103.25 4.77 9.73 9 96.83 88.56 - 100.42 3.75 3.89 Philippines 28 96.50 87.27 - 105.17 4.82 4.98 22 97.30 87.27 - 105.17 5.06 5.20 6 93.96 91.59 - 101.97 3.61 3.80 Andaman Is. 36 90.60 85.03 - 100.35 4.00 4.39 18 92.42 87.12 - 100.35 3.72 3.99 18 87.93 85.03 - 93.38 2.65 3.00 Nicobar Is. 20 96.48 91.23 - 106.77 3.49 3.62 17 96.48 91.23 - 106.77 3.63 3.77 3 96.35 94.38 - 100.38 3.06 5.52 Borneo 37 96.18 89.41 - 104.53 3.94 4.09 26 97.88 89.41 - 104.53 4.22 4.35 11 95.86 90.99 - 100.28 2.91 3.06 Indonesia 27 98.07 89.80 - 109.30 4.71 4.82 20 98.79 91.36 - 109.30 4.56 4.61 7 94.22 89.80 - 101.55 3.79 4.00 Melanesia 30 99.38 89.34 - 107.94 4.58 4.65 20 100.17 89.96 - 107.94 4.06 4.06 10 95.01 89.34 - 103.60 4.49 4.69 Micronesia 15 97.74 90.33 - 105.62 4.76 4.83 7 103.55 97.48 - 105.62 2.86 2.79 8 96.30 90.33 - 97.86 2.91 3.05 Australia 27 98.57 90.21 - 107.73 5.02 5.08 18 101.07 95.56 - 107.73 4.10 4.05 9 92.91 90.21 - 99.32 3.09 3.28 Africa 29 100.04 90.63 - 109.14 3.95 3.93 18 101.50 90.63 - 109.14 4.41 4.35 11 98.86 95.76 - 104.27 2.53 2.56 Nat. America 33 99.05 89.69 - 109.19 4.39 4.45 10 100.89 89.69 - 109.19 5.56 5.56 23 98.96 92.12 - 106.42 3.79 3.86 Caucasian 29 96.05 87.32 - 107.67 4.72 4.90 15 98.01 93.32 - 107.67 3.86 3.89 14 92.62 87.32 - 98.87 3.07 3.30 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

334 Basion-Prosthion (BPL)

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (mm) (mm) (%) (mm) (mm) (%) (mm) (mm) (%)

Siberia 28 97.42 90.08 - 108.57 5.05 5.16 18 98.78 90.08 - 108.57 5.31 5.35 10 94.54 90.67 - 101.27 3.49 3.66 Mongolia 24 94.48 85.22 - 102.63 4.58 4.85 15 95.32 85.22 - 102.63 5.26 5.52 9 93.30 87.39 - 97.97 2.95 3.17 Korea 4 91.22 89.37 - 93.47 1.79 3.92 2 91.22 90.45 - 91.99 1.08 1.78 2 91.42 89.37 - 93.47 2.90 4.76 Ainu 3 98.91 96.25 - 104.26 4.08 7.15 2 100.26 96.25 - 104.26 5.66 8.47 1 98.91 98.91 - 98.91 - - Japan 13 96.17 85.83 - 102.72 4.43 4.59 10 97.22 92.62 - 102.72 3.10 3.18 3 92.47 85.83 - 98.96 6.57 12.43 S. China 6 92.59 87.77 - 100.64 4.70 5.07 3 93.89 91.29 - 100.64 4.82 8.86 3 88.65 87.77 - 94.56 3.69 7.16 N. China 16 94.53 82.67 - 98.56 4.12 4.40 13 95.00 82.67 - 98.56 4.13 4.38 3 91.38 87.52 - 92.39 2.57 4.98 Burma 39 92.30 81.08 - 105.98 6.06 6.55 22 94.23 84.07 - 105.98 5.76 6.05 17 88.62 81.08 - 98.59 4.72 5.29 Laos 24 96.04 87.55 - 104.09 4.49 4.72 16 96.04 88.49 - 104.09 4.46 4.70 8 95.77 87.55 - 100.87 4.84 5.07 Vietnam 23 94.16 87.53 - 101.64 4.26 4.52 13 94.25 89.17 - 101.64 3.72 3.91 10 91.23 87.53 - 101.56 4.70 5.06 Thailand 21 96.19 86.85 - 103.05 4.87 5.13 15 97.07 89.43 - 103.05 4.07 4.21 6 89.28 86.85 - 96.80 3.71 4.11 Cambodia 13 93.14 86.48 - 104.33 5.91 6.30 4 100.54 88.49 - 104.33 6.92 14.04 9 90.85 86.48 - 100.39 4.39 4.78 Philippines 28 95.45 81.17 - 106.82 6.44 6.79 22 96.20 81.17 - 106.82 6.34 6.64 6 93.77 83.82 - 99.86 6.91 7.46 Andaman Is. 36 90.14 83.33 - 98.50 4.03 4.43 18 92.47 83.68 - 98.50 3.89 4.23 18 89.39 83.33 - 97.91 4.01 4.46 Nicobar Is. 20 96.80 79.58 - 103.16 5.77 6.03 17 95.06 79.58 - 103.16 5.95 6.27 3 99.22 97.22 - 102.26 2.54 4.47 Borneo 37 93.94 86.96 - 106.69 4.99 5.27 26 94.22 87.27 - 106.69 5.03 5.27 11 92.53 86.96 - 99.56 4.60 4.96 Indonesia 27 97.27 88.71 - 101.76 3.86 4.01 20 97.39 88.71 - 101.38 4.02 4.19 7 95.92 90.58 - 101.76 3.64 3.78 Melanesia 30 102.11 91.36 - 113.67 5.70 5.63 20 103.16 93.14 - 113.67 5.34 5.19 10 96.91 91.36 - 105.17 5.08 5.19 Micronesia 15 96.73 88.44 - 109.25 5.86 6.00 7 102.05 96.73 - 109.25 4.83 4.71 8 94.87 88.44 - 96.75 2.85 3.04 Australia 27 102.00 90.76 - 110.79 4.34 4.28 18 102.71 90.76 - 110.79 4.65 4.55 9 99.14 95.09 - 104.48 3.12 3.13 Africa 29 100.30 90.15 - 111.50 5.69 5.70 18 100.83 90.15 - 108.45 5.56 5.60 11 99.35 93.44 - 111.50 6.11 6.09 Nat. America 33 96.24 87.73 - 107.55 4.36 4.50 10 98.26 93.79 - 107.55 4.40 4.45 23 94.79 87.73 - 106.12 4.10 4.28 Caucasian 29 89.71 80.69 - 99.74 5.13 5.75 15 89.98 83.23 - 99.74 4.97 5.48 14 87.91 80.69 - 96.78 5.01 5.71 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

335 Occipital Length (OCC)

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (mm) (mm) (%) (mm) (mm) (%) (mm) (mm) (%)

Siberia 28 93.23 83.86 - 113.34 6.39 6.83 18 92.92 85.19 - 113.34 6.93 7.38 10 93.23 83.86 - 100.39 5.55 5.97 Mongolia 24 94.97 84.92 - 105.13 5.36 5.63 15 96.22 84.92 - 105.13 5.47 5.68 9 94.62 85.95 - 100.30 4.91 5.26 Korea 4 95.88 84.75 - 105.54 8.55 17.89 2 101.25 96.96 - 105.54 6.07 8.99 2 89.78 84.75 - 94.80 7.11 11.88 Ainu 3 97.14 94.84 - 99.90 2.53 4.56 2 98.52 97.14 - 99.90 1.95 2.97 1 94.84 94.84 - 94.84 - - Japan 13 94.36 90.41 - 100.37 3.60 3.79 10 96.48 90.41 - 100.37 3.68 3.84 3 91.38 91.20 - 94.36 1.78 3.37 S. China 6 94.09 90.58 - 116.74 9.59 9.84 3 94.30 93.88 - 116.74 13.08 22.52 3 93.76 90.58 - 95.38 2.44 4.58 N. China 16 96.50 89.21 - 117.32 7.39 7.55 13 97.58 91.45 - 117.32 6.95 7.06 3 90.25 89.21 - 107.67 10.37 18.96 Burma 39 93.92 82.39 - 104.02 5.34 5.67 22 96.48 82.39 - 104.02 5.53 5.79 17 90.90 85.35 - 103.90 4.69 5.07 Laos 24 93.31 78.53 - 126.21 8.99 9.47 16 95.79 90.04 - 126.21 9.04 9.24 8 88.83 78.53 - 98.35 5.95 6.66 Vietnam 23 98.98 82.17 - 110.29 7.16 7.34 13 98.98 82.17 - 110.29 7.98 8.23 10 99.57 83.54 - 106.48 6.23 6.32 Thailand 21 97.53 86.38 - 109.79 6.19 6.38 15 96.21 86.38 - 109.79 6.57 6.83 6 100.34 90.31 - 105.26 5.10 5.16 Cambodia 13 92.45 85.46 - 105.15 5.42 5.81 4 93.85 85.46 - 100.56 6.32 13.52 9 92.45 86.57 - 105.15 5.39 5.79 Philippines 28 97.64 82.85 - 110.59 7.08 7.31 22 98.76 82.85 - 110.59 6.76 6.85 6 89.17 88.07 - 92.20 1.71 1.91 Andaman Is. 36 89.83 81.48 - 103.21 4.81 5.30 18 89.79 84.67 - 100.78 4.62 5.08 18 89.83 81.48 - 103.21 5.14 5.65 Nicobar Is. 20 95.43 88.71 - 101.45 3.94 4.15 17 95.60 88.71 - 101.45 3.81 4.02 3 92.59 91.08 - 101.28 5.50 10.14 Borneo 37 96.01 82.91 - 107.74 6.05 6.29 26 96.77 82.91 - 107.74 6.01 6.20 11 92.81 87.13 - 105.60 6.11 6.46 Indonesia 27 94.64 84.06 - 105.11 5.72 5.98 20 96.07 84.06 - 105.11 5.91 6.14 7 93.12 86.27 - 101.22 4.57 4.92 Melanesia 30 94.42 86.38 - 110.09 5.61 5.87 20 95.23 90.04 - 110.09 5.71 5.88 10 92.24 86.38 - 98.56 3.84 4.17 Micronesia 15 96.24 85.64 - 107.62 5.04 5.23 7 98.84 93.19 - 107.62 4.47 4.53 8 94.24 85.64 - 100.65 4.66 4.96 Australia 27 92.09 83.09 - 108.67 5.73 6.14 18 92.54 87.37 - 108.67 5.82 6.16 9 90.97 83.09 - 96.57 5.06 5.57 Africa 29 92.69 87.01 - 109.76 5.16 5.48 18 94.65 88.19 - 109.76 5.71 6.01 11 91.53 87.01 - 98.09 3.64 3.95 Nat. America 33 93.88 86.58 - 108.86 5.28 5.54 10 95.14 87.55 - 108.86 7.30 7.49 23 92.96 86.58 - 100.76 3.95 4.19 Caucasian 29 95.35 86.19 - 110.86 5.72 5.97 15 96.80 88.55 - 110.86 6.09 6.23 14 94.21 86.19 - 101.41 4.85 5.15 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

336 Bistephanic Breadth (STB)

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (mm) (mm) (%) (mm) (mm) (%) (mm) (mm) (%)

Siberia 28 110.84 83.71 - 122.34 9.41 8.65 18 107.79 83.71 - 122.34 10.55 9.80 10 111.97 93.40 - 117.75 7.04 6.37 Mongolia 24 110.45 93.98 - 124.60 6.91 6.30 15 109.44 93.98 - 124.60 6.97 6.41 9 114.13 102.13 - 121.15 6.84 6.13 Korea 4 109.49 99.13 - 120.58 8.92 16.27 2 114.01 107.44 - 120.58 9.29 12.23 2 105.33 99.13 - 111.54 8.78 12.50 Ainu 3 107.77 106.38 - 114.73 4.47 7.14 2 111.25 107.77 - 114.73 4.93 6.64 1 106.38 106.38 - 106.38 - - Japan 13 105.74 89.40 - 122.40 8.95 8.54 10 107.06 89.40 - 122.40 9.78 9.23 3 100.23 96.80 - 105.74 4.51 7.82 S. China 6 108.77 101.26 - 118.31 6.31 5.82 3 111.70 101.26 - 118.31 8.60 13.62 3 108.40 102.17 - 109.13 3.83 6.29 N. China 16 105.98 87.30 - 120.85 10.03 9.52 13 109.39 88.17 - 120.85 9.79 9.16 3 104.06 87.30 - 105.02 9.97 17.65 Burma 39 108.82 93.50 - 121.45 7.00 6.47 22 110.49 98.93 - 121.45 6.18 5.62 17 104.52 93.50 - 118.63 7.43 7.02 Laos 24 110.54 93.92 - 123.92 7.08 6.44 16 111.10 93.92 - 123.92 8.09 7.35 8 110.54 102.64 - 117.34 4.95 4.51 Vietnam 23 108.42 95.45 - 118.92 6.42 5.93 13 111.89 103.26 - 118.92 4.89 4.38 10 103.12 95.45 - 114.75 5.65 5.44 Thailand 21 111.00 98.46 - 121.54 5.58 5.02 15 113.34 98.46 - 121.54 6.25 5.59 6 109.68 104.30 - 113.07 3.12 2.85 Cambodia 13 109.84 97.23 - 120.43 6.77 6.24 4 113.46 111.45 - 120.43 4.03 7.02 9 105.37 97.23 - 114.62 6.02 5.68 Philippines 28 108.48 94.66 - 120.58 6.36 5.80 22 110.25 94.66 - 120.58 6.60 5.99 6 106.59 101.49 - 115.38 5.60 5.19 Andaman Is. 36 103.25 89.51 - 118.91 6.48 6.28 18 106.06 96.56 - 118.91 5.34 5.02 18 100.10 89.51 - 109.62 5.66 5.69 Nicobar Is. 20 104.25 96.22 - 121.57 6.03 5.71 17 104.09 98.86 - 121.57 6.09 5.74 3 104.41 96.22 - 106.78 5.54 9.46 Borneo 37 108.31 96.94 - 122.05 5.97 5.47 26 109.20 100.16 - 122.05 5.97 5.44 11 107.94 96.94 - 115.49 5.95 5.53 Indonesia 27 112.47 91.30 - 126.98 7.76 7.01 20 112.93 101.69 - 120.70 5.46 4.88 7 103.76 91.30 - 126.98 11.92 11.17 Melanesia 30 99.93 83.07 - 114.80 6.99 6.96 20 101.71 83.07 - 114.80 7.99 7.88 10 99.02 90.39 - 104.67 4.02 4.08 Micronesia 15 108.09 98.30 - 122.25 6.71 6.20 7 112.61 103.24 - 122.25 6.25 5.54 8 103.61 98.30 - 110.35 4.20 4.03 Australia 27 102.55 86.48 - 110.52 5.56 5.48 18 103.78 95.73 - 110.52 3.82 3.68 9 98.53 86.48 - 104.70 6.32 6.49 Africa 29 108.04 89.68 - 118.63 7.40 6.92 18 108.31 90.59 - 118.63 7.68 7.18 11 107.73 89.68 - 115.72 7.29 6.80 Nat. America 33 103.28 84.68 - 113.78 7.50 7.35 10 106.16 84.69 - 111.13 9.29 9.12 23 102.01 84.68 - 113.78 6.82 6.68 Caucasian 29 114.08 93.74 - 125.29 9.02 8.11 15 115.22 93.74 - 125.29 9.47 8.41 14 110.95 95.91 - 122.70 8.65 7.87 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

337 Bipterionic Breadth

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (mm) (mm) (%) (mm) (mm) (%) (mm) (mm) (%)

Siberia 28 117.62 100.01 - 126.95 5.54 4.75 18 117.90 109.21 - 126.95 4.39 3.73 10 115.69 100.01 - 123.55 7.11 6.19 Mongolia 24 116.57 106.73 - 130.10 5.72 4.86 15 118.82 108.13 - 130.10 5.97 5.00 9 114.57 106.73 - 120.53 3.94 3.44 Korea 4 119.28 110.10 - 130.01 8.26 13.80 2 125.49 120.98 - 130.01 6.39 7.64 2 113.84 110.10 - 117.58 5.29 6.97 Ainu 3 112.65 110.89 - 119.24 4.40 6.74 2 115.95 112.65 - 119.24 4.66 6.03 1 110.89 110.89 - 110.89 - - Japan 13 112.52 101.81 - 124.11 6.72 6.03 10 114.11 104.34 - 124.11 5.86 5.16 3 103.68 101.81 - 106.01 2.11 3.55 S. China 6 108.44 106.07 - 118.22 5.22 4.71 3 116.98 108.01 - 118.22 5.57 8.52 3 107.69 106.07 - 108.87 1.41 2.29 N. China 16 112.86 97.48 - 125.37 8.64 7.69 13 113.41 97.48 - 125.37 8.12 7.11 3 100.79 99.95 - 113.15 7.39 12.36 Burma 39 109.79 98.71 - 122.92 6.49 5.86 22 113.78 102.44 - 122.92 5.99 5.30 17 105.75 98.71 - 118.92 5.93 5.51 Laos 24 110.28 101.86 - 121.72 5.86 5.28 16 115.03 101.86 - 121.72 6.47 5.76 8 108.27 103.99 - 113.17 3.18 2.95 Vietnam 23 113.23 96.72 - 123.73 7.50 6.74 13 114.82 108.65 - 123.73 4.65 4.03 10 103.90 96.72 - 118.11 7.61 7.15 Thailand 21 111.01 104.16 - 121.50 4.79 4.28 15 112.74 107.97 - 121.50 4.12 3.64 6 105.99 104.16 - 115.06 4.90 4.52 Cambodia 13 106.33 91.95 - 123.42 7.89 7.35 4 110.38 105.57 - 115.11 5.39 9.78 9 106.33 91.95 - 123.42 8.73 8.23 Philippines 28 109.31 96.12 - 127.37 6.79 6.16 22 109.31 96.12 - 127.37 7.05 6.37 6 109.52 100.38 - 114.01 6.00 5.52 Andaman Is. 36 104.76 87.50 - 111.68 5.67 5.44 18 108.32 96.39 - 110.96 4.05 3.79 18 103.21 87.50 - 111.68 6.11 6.00 Nicobar Is. 20 104.29 99.13 - 115.81 4.86 4.63 17 104.38 99.13 - 115.81 5.00 4.74 3 101.61 99.28 - 105.13 2.95 5.05 Borneo 37 110.99 100.89 - 118.96 5.44 4.91 26 113.14 100.89 - 118.96 4.84 4.30 11 106.13 101.78 - 116.49 4.74 4.44 Indonesia 27 113.16 100.92 - 120.81 4.59 4.09 20 113.67 107.06 - 120.81 3.82 3.38 7 110.20 100.92 - 119.32 5.82 5.31 Melanesia 30 106.20 90.35 - 115.65 5.86 5.59 20 107.22 97.33 - 115.65 5.34 5.01 10 102.85 90.35 - 108.34 5.57 5.49 Micronesia 15 107.17 101.37 - 123.79 6.61 6.09 7 112.85 104.88 - 123.79 6.75 5.95 8 104.25 101.37 - 108.37 2.48 2.38 Australia 27 105.09 93.02 - 113.40 5.06 4.86 18 106.38 93.02 - 113.40 4.93 4.65 9 100.15 96.31 - 105.09 2.85 2.83 Africa 29 111.03 95.34 - 118.14 5.46 4.98 18 111.41 95.34 - 115.45 5.56 5.06 11 109.04 98.63 - 118.14 5.56 5.08 Nat. America 33 111.46 101.61 - 121.41 5.29 4.75 10 111.42 105.86 - 119.62 4.54 4.07 23 111.46 101.61 - 121.41 5.67 5.11 Caucasian 29 115.58 102.00 - 127.34 6.39 5.53 15 119.00 102.00 - 127.34 6.68 5.65 14 112.06 103.80 - 122.64 4.65 4.13 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

338 Biauricular Breadth (AUB)

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (mm) (mm) (%) (mm) (mm) (%) (mm) (mm) (%)

Siberia 28 127.18 111.95 - 143.33 7.31 5.75 18 129.34 111.95 - 143.33 7.12 5.49 10 121.65 115.45 - 130.44 5.26 4.29 Mongolia 24 130.30 115.11 - 134.68 5.23 4.09 15 130.78 122.22 - 134.68 3.38 2.59 9 124.69 115.11 - 130.28 4.96 4.01 Korea 4 126.62 118.62 - 128.12 4.33 6.93 2 126.62 126.02 - 127.22 0.85 1.00 2 123.37 118.62 - 128.12 6.71 8.16 Ainu 3 119.44 118.12 - 127.97 5.35 7.68 2 123.71 119.44 - 127.97 6.03 7.31 1 118.12 118.12 - 118.12 - - Japan 13 123.95 112.89 - 130.85 5.11 4.16 10 124.13 114.17 - 130.85 4.40 3.55 3 117.77 112.89 - 123.49 5.30 7.86 S. China 6 123.03 118.45 - 128.97 4.82 3.91 3 127.62 118.45 - 128.97 5.72 8.01 3 119.79 118.77 - 126.27 4.07 5.86 N. China 16 126.28 113.46 - 133.19 6.13 4.94 13 127.06 116.02 - 133.19 4.82 3.83 3 113.66 113.46 - 120.29 3.89 5.87 Burma 39 120.03 104.04 - 138.80 7.29 6.09 22 123.44 109.15 - 138.80 6.84 5.60 17 115.05 104.04 - 127.83 6.47 5.57 Laos 24 123.51 112.54 - 132.96 4.57 3.73 16 124.06 116.81 - 132.96 4.02 3.25 8 119.82 112.54 - 127.44 4.98 4.15 Vietnam 23 124.32 112.75 - 133.91 5.52 4.46 13 125.48 117.85 - 133.91 4.62 3.67 10 119.91 112.75 - 127.39 5.33 4.42 Thailand 21 124.63 115.65 - 129.55 4.18 3.38 15 126.13 120.92 - 129.55 2.93 2.33 6 118.84 115.65 - 124.08 3.38 2.83 Cambodia 13 124.30 108.81 - 131.19 6.27 5.09 4 124.11 122.55 - 131.19 3.87 6.17 9 124.97 108.81 - 128.47 7.00 5.74 Philippines 28 123.17 113.10 - 132.84 5.29 4.31 22 123.60 115.11 - 132.84 4.60 3.71 6 117.78 113.10 - 127.95 5.28 4.47 Andaman Is. 36 109.69 100.80 - 117.08 4.30 3.91 18 112.55 104.70 - 117.08 3.76 3.38 18 108.80 100.80 - 116.55 4.41 4.07 Nicobar Is. 20 115.33 107.30 - 121.45 4.02 3.50 17 115.71 107.30 - 121.45 4.04 3.50 3 111.48 109.86 - 117.31 3.92 6.08 Borneo 37 120.41 98.61 - 132.31 6.70 5.57 26 123.18 107.06 - 132.31 5.81 4.75 11 117.54 98.61 - 121.89 6.39 5.54 Indonesia 27 124.64 104.90 - 132.57 6.26 5.10 20 125.57 119.54 - 132.57 3.72 2.97 7 115.82 104.90 - 124.64 6.46 5.59 Melanesia 30 118.82 103.42 - 125.51 5.16 4.35 20 121.56 112.33 - 125.51 4.27 3.55 10 115.63 103.42 - 119.35 4.47 3.91 Micronesia 15 117.83 106.61 - 133.02 8.10 6.81 7 126.17 117.83 - 133.02 4.94 3.94 8 113.31 106.61 - 124.77 5.62 4.96 Australia 27 116.78 110.92 - 129.62 4.87 4.16 18 118.96 110.92 - 129.62 4.74 3.98 9 112.18 111.52 - 118.42 2.71 2.38 Africa 29 117.47 110.38 - 123.33 2.81 2.39 18 117.92 112.94 - 123.33 2.79 2.36 11 117.47 110.38 - 119.97 2.79 2.39 Nat. America 33 124.03 112.87 - 132.05 5.22 4.25 10 125.02 117.69 - 132.05 5.07 4.06 23 124.02 112.87 - 129.42 5.11 4.19 Caucasian 29 118.26 110.65 - 132.82 5.78 4.85 15 122.61 114.04 - 132.82 5.71 4.67 14 116.59 110.65 - 122.92 4.03 3.47 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

339 Biporionic Breadth

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (mm) (mm) (%) (mm) (mm) (%) (mm) (mm) (%)

Siberia 28 109.07 98.01 - 131.41 7.41 6.78 18 110.07 98.01 - 131.41 8.29 7.49 10 106.92 99.81 - 115.28 4.90 4.59 Mongolia 24 108.46 100.89 - 122.84 5.70 5.21 15 108.55 104.09 - 122.06 4.92 4.46 9 105.31 100.89 - 122.84 6.82 6.33 Korea 4 108.82 100.87 - 116.22 6.68 12.30 2 111.10 105.98 - 116.22 7.24 9.78 2 106.27 100.87 - 111.66 7.63 10.77 Ainu 3 104.80 99.99 - 115.72 8.06 13.20 2 107.85 99.99 - 115.72 11.12 15.46 1 104.80 104.80 - 104.80 - - Japan 13 106.73 92.69 - 113.72 6.14 5.78 10 107.53 92.69 - 113.72 6.29 5.86 3 104.96 97.13 - 105.13 4.57 7.81 S. China 6 106.09 100.96 - 111.81 5.48 5.16 3 110.51 100.96 - 111.81 5.92 9.62 3 101.66 100.96 - 111.16 5.70 9.53 N. China 16 106.68 98.14 - 115.90 5.00 4.73 13 107.55 99.43 - 115.90 4.52 4.22 3 99.83 98.14 - 101.52 1.69 2.97 Burma 39 105.22 92.44 - 118.52 5.49 5.19 22 106.20 92.44 - 118.52 5.98 5.61 17 104.15 96.65 - 116.23 4.75 4.53 Laos 24 105.42 94.87 - 117.64 4.98 4.71 16 105.42 94.87 - 117.64 5.45 5.17 8 105.49 101.28 - 112.04 4.18 3.94 Vietnam 23 103.01 97.34 - 118.73 5.16 4.95 13 104.70 97.34 - 118.73 6.03 5.69 10 102.44 98.15 - 104.44 2.27 2.23 Thailand 21 106.06 97.26 - 110.43 3.50 3.32 15 106.06 97.26 - 110.43 3.87 3.69 6 106.65 103.19 - 109.04 2.33 2.19 Cambodia 13 104.11 98.16 - 114.38 4.55 4.33 4 107.72 102.43 - 114.38 5.71 10.57 9 103.24 98.16 - 108.59 3.66 3.52 Philippines 28 104.42 95.22 - 119.78 5.49 5.23 22 105.65 97.50 - 119.78 5.37 5.06 6 100.49 95.22 - 104.53 3.54 3.52 Andaman Is. 36 97.69 88.25 - 108.35 4.66 4.77 18 100.07 94.09 - 108.35 4.06 4.06 18 95.76 88.25 - 107.16 4.39 4.58 Nicobar Is. 20 102.34 95.88 - 111.25 3.87 3.79 17 101.62 95.88 - 111.25 3.96 3.89 3 105.66 102.46 - 106.44 2.11 3.52 Borneo 37 104.93 97.56 - 115.34 4.53 4.29 26 107.46 98.09 - 115.34 4.26 3.98 11 102.25 97.56 - 107.74 2.98 2.92 Indonesia 27 104.98 96.21 - 113.77 5.25 4.99 20 105.35 98.01 - 113.77 5.10 4.81 7 101.95 96.21 - 111.10 5.20 5.06 Melanesia 30 107.27 98.20 - 118.89 4.73 4.42 20 108.78 98.20 - 118.89 4.64 4.26 10 102.78 100.56 - 107.13 2.40 2.32 Micronesia 15 103.94 92.71 - 114.86 6.50 6.21 7 105.99 103.79 - 114.86 4.92 4.54 8 100.62 92.71 - 112.91 6.13 6.05 Australia 27 105.95 92.44 - 119.40 5.59 5.27 18 106.23 98.12 - 119.40 5.57 5.19 9 104.21 92.44 - 107.54 4.65 4.51 Africa 29 104.86 94.34 - 113.31 4.75 4.54 18 107.08 99.08 - 113.31 3.96 3.71 11 99.76 94.34 - 109.77 4.25 4.19 Nat. America 33 105.45 95.90 - 119.68 4.99 4.77 10 106.52 100.02 - 119.68 5.37 4.99 23 103.96 95.90 - 112.56 4.43 4.29 Caucasian 29 107.13 98.16 - 117.61 5.71 5.34 15 111.61 100.64 - 117.61 5.07 4.60 14 103.06 98.16 - 110.74 3.83 3.71 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

340 Biasterionic Breadth (ASB)

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (mm) (mm) (%) (mm) (mm) (%) (mm) (mm) (%)

Siberia 28 109.07 98.01 - 131.41 7.41 6.78 18 110.07 98.01 - 131.41 8.29 7.49 10 106.92 99.81 - 115.28 4.90 4.59 Mongolia 24 108.46 100.89 - 122.84 5.70 5.21 15 108.55 104.09 - 122.06 4.92 4.46 9 105.31 100.89 - 122.84 6.82 6.33 Korea 4 108.82 100.87 - 116.22 6.68 12.30 2 111.10 105.98 - 116.22 7.24 9.78 2 106.27 100.87 - 111.66 7.63 10.77 Ainu 3 104.80 99.99 - 115.72 8.06 13.20 2 107.85 99.99 - 115.72 11.12 15.46 1 104.80 104.80 - 104.80 - - Japan 13 106.73 92.69 - 113.72 6.14 5.78 10 107.53 92.69 - 113.72 6.29 5.86 3 104.96 97.13 - 105.13 4.57 7.81 S. China 6 106.09 100.96 - 111.81 5.48 5.16 3 110.51 100.96 - 111.81 5.92 9.62 3 101.66 100.96 - 111.16 5.70 9.53 N. China 16 106.68 98.14 - 115.90 5.00 4.73 13 107.55 99.43 - 115.90 4.52 4.22 3 99.83 98.14 - 101.52 1.69 2.97 Burma 39 105.22 92.44 - 118.52 5.49 5.19 22 106.20 92.44 - 118.52 5.98 5.61 17 104.15 96.65 - 116.23 4.75 4.53 Laos 24 105.42 94.87 - 117.64 4.98 4.71 16 105.42 94.87 - 117.64 5.45 5.17 8 105.49 101.28 - 112.04 4.18 3.94 Vietnam 23 103.01 97.34 - 118.73 5.16 4.95 13 104.70 97.34 - 118.73 6.03 5.69 10 102.44 98.15 - 104.44 2.27 2.23 Thailand 21 106.06 97.26 - 110.43 3.50 3.32 15 106.06 97.26 - 110.43 3.87 3.69 6 106.65 103.19 - 109.04 2.33 2.19 Cambodia 13 104.11 98.16 - 114.38 4.55 4.33 4 107.72 102.43 - 114.38 5.71 10.57 9 103.24 98.16 - 108.59 3.66 3.52 Philippines 28 104.42 95.22 - 119.78 5.49 5.23 22 105.65 97.50 - 119.78 5.37 5.06 6 100.49 95.22 - 104.53 3.54 3.52 Andaman Is. 36 97.69 88.25 - 108.35 4.66 4.77 18 100.07 94.09 - 108.35 4.06 4.06 18 95.76 88.25 - 107.16 4.39 4.58 Nicobar Is. 20 102.34 95.88 - 111.25 3.87 3.79 17 101.62 95.88 - 111.25 3.96 3.89 3 105.66 102.46 - 106.44 2.11 3.52 Borneo 37 104.93 97.56 - 115.34 4.53 4.29 26 107.46 98.09 - 115.34 4.26 3.98 11 102.25 97.56 - 107.74 2.98 2.92 Indonesia 27 104.98 96.21 - 113.77 5.25 4.99 20 105.35 98.01 - 113.77 5.10 4.81 7 101.95 96.21 - 111.10 5.20 5.06 Melanesia 30 107.27 98.20 - 118.89 4.73 4.42 20 108.78 98.20 - 118.89 4.64 4.26 10 102.78 100.56 - 107.13 2.40 2.32 Micronesia 15 103.94 92.71 - 114.86 6.50 6.21 7 105.99 103.79 - 114.86 4.92 4.54 8 100.62 92.71 - 112.91 6.13 6.05 Australia 27 105.95 92.44 - 119.40 5.59 5.27 18 106.23 98.12 - 119.40 5.57 5.19 9 104.21 92.44 - 107.54 4.65 4.51 Africa 29 104.86 94.34 - 113.31 4.75 4.54 18 107.08 99.08 - 113.31 3.96 3.71 11 99.76 94.34 - 109.77 4.25 4.19 Nat. America 33 105.45 95.90 - 119.68 4.99 4.77 10 106.52 100.02 - 119.68 5.37 4.99 23 103.96 95.90 - 112.56 4.43 4.29 Caucasian 29 107.13 98.16 - 117.61 5.71 5.34 15 111.61 100.64 - 117.61 5.07 4.60 14 103.06 98.16 - 110.74 3.83 3.71 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

341 Jugale-Auriculare

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (mm) (mm) (%) (mm) (mm) (%) (mm) (mm) (%)

Siberia 28 55.41 47.25 - 65.16 4.38 7.72 18 57.55 52.53 - 65.16 3.93 6.81 10 54.07 47.25 - 62.73 4.79 8.72 Mongolia 24 55.52 48.19 - 62.36 4.01 7.26 15 56.74 48.19 - 62.36 3.82 6.75 9 51.75 48.79 - 57.94 3.32 6.28 Korea 4 56.09 53.73 - 57.21 1.51 5.40 2 56.87 56.52 - 57.21 0.49 1.29 2 54.69 53.73 - 55.66 1.36 3.74 Ainu 3 57.25 56.62 - 59.94 1.76 5.32 2 58.59 57.25 - 59.94 1.90 4.86 1 56.62 56.62 - 56.62 - - Japan 13 56.49 49.84 - 64.37 3.91 6.93 10 57.47 49.84 - 64.37 4.00 7.00 3 54.80 50.89 - 56.49 2.87 9.30 S. China 6 53.05 48.59 - 57.67 3.35 6.36 3 53.96 48.59 - 57.67 4.57 14.96 3 52.21 49.36 - 53.88 2.29 7.73 N. China 16 53.64 45.60 - 60.96 3.50 6.49 13 54.92 51.86 - 60.96 2.58 4.69 3 49.68 45.60 - 52.79 3.61 12.78 Burma 39 52.59 42.68 - 58.40 3.74 7.22 22 53.75 44.30 - 58.40 3.70 7.06 17 51.67 42.68 - 55.62 3.78 7.39 Laos 24 52.93 47.68 - 60.15 3.16 5.91 16 54.24 50.96 - 60.15 2.70 4.96 8 51.29 47.68 - 58.22 3.48 6.71 Vietnam 23 53.54 44.44 - 62.32 3.84 7.16 13 55.19 50.03 - 62.32 3.93 7.20 10 53.49 44.44 - 56.17 3.44 6.58 Thailand 21 52.74 47.45 - 59.59 3.00 5.73 15 53.04 47.45 - 59.59 2.90 5.46 6 50.51 47.91 - 54.65 2.46 4.87 Cambodia 13 52.58 43.98 - 59.24 3.93 7.45 4 52.57 50.57 - 59.24 3.83 14.27 9 52.58 43.98 - 58.83 4.10 7.86 Philippines 28 53.84 45.13 - 58.53 3.65 6.80 22 54.38 49.35 - 58.53 3.26 6.02 6 52.92 45.13 - 58.20 4.73 9.11 Andaman Is. 36 47.60 41.54 - 53.25 2.70 5.66 18 48.77 43.62 - 52.54 2.41 4.96 18 46.46 41.54 - 53.25 2.58 5.55 Nicobar Is. 20 50.85 45.42 - 53.51 2.41 4.78 17 50.93 45.42 - 53.51 2.47 4.86 3 48.22 48.09 - 51.63 2.01 4.07 Borneo 37 52.95 43.92 - 64.00 3.82 7.16 26 53.31 43.92 - 64.00 4.21 7.83 11 52.95 49.09 - 58.11 2.81 5.31 Indonesia 27 53.92 44.71 - 58.71 3.34 6.27 20 54.65 47.90 - 58.71 2.80 5.17 7 51.84 44.71 - 54.90 3.72 7.33 Melanesia 30 56.45 50.64 - 60.16 2.57 4.60 20 56.63 51.48 - 60.16 2.35 4.16 10 54.99 50.64 - 58.96 2.73 4.97 Micronesia 15 55.19 53.50 - 61.63 2.46 4.37 7 57.52 54.57 - 61.63 2.65 4.64 8 54.85 53.50 - 59.82 2.03 3.66 Australia 27 55.45 49.85 - 61.61 3.30 5.92 18 55.48 51.49 - 61.61 3.24 5.76 9 54.56 49.85 - 59.64 3.24 5.94 Africa 29 55.55 51.35 - 65.51 3.49 6.23 18 55.43 51.78 - 65.51 3.50 6.24 11 57.32 51.35 - 60.66 3.65 6.52 Nat. America 33 55.50 47.81 - 60.93 2.58 4.64 10 55.72 51.99 - 58.23 2.16 3.89 23 55.50 47.81 - 60.93 2.79 5.00 Caucasian 29 53.35 45.06 - 59.36 3.48 6.53 15 55.20 51.90 - 59.36 2.09 3.78 14 51.23 45.06 - 58.60 3.44 6.71 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

342 Zygomaxillare-Auriculare

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (mm) (mm) (%) (mm) (mm) (%) (mm) (mm) (%)

Siberia 28 72.06 63.25 - 85.33 6.25 8.46 18 75.43 66.10 - 85.33 6.24 8.22 10 70.98 63.25 - 78.66 4.60 6.54 Mongolia 24 69.55 60.85 - 80.01 4.49 6.33 15 72.82 67.97 - 80.01 4.05 5.56 9 68.97 60.85 - 70.37 3.17 4.68 Korea 4 67.74 63.28 - 72.14 3.78 11.18 2 69.26 66.37 - 72.14 4.08 8.83 2 66.19 63.28 - 69.10 4.12 9.33 Ainu 3 72.04 69.33 - 74.59 2.63 6.39 2 73.31 72.04 - 74.59 1.81 3.69 1 69.33 69.33 - 69.33 - - Japan 13 70.18 66.02 - 78.19 4.29 6.01 10 72.62 66.02 - 78.19 4.29 5.92 3 67.38 66.83 - 68.79 1.01 2.61 S. China 6 72.43 65.60 - 77.47 4.06 5.64 3 73.78 69.80 - 77.47 3.84 9.11 3 71.20 65.60 - 73.66 4.13 10.30 N. China 16 69.73 58.85 - 79.49 5.25 7.50 13 70.65 64.97 - 79.49 4.31 6.05 3 63.65 58.85 - 69.08 5.12 14.03 Burma 39 67.27 58.40 - 74.76 4.06 6.05 22 68.42 60.42 - 74.76 3.46 5.05 17 66.17 58.40 - 72.16 4.06 6.24 Laos 24 69.77 62.10 - 76.45 3.72 5.31 16 70.25 64.91 - 76.45 3.19 4.51 8 67.16 62.10 - 75.46 4.41 6.44 Vietnam 23 70.12 66.47 - 78.19 3.49 4.93 13 70.96 66.89 - 78.19 3.89 5.45 10 68.79 66.47 - 73.82 2.86 4.09 Thailand 21 68.90 56.98 - 73.58 3.96 5.84 15 69.77 63.00 - 73.58 2.96 4.28 6 65.01 56.98 - 68.90 3.95 6.17 Cambodia 13 69.72 46.79 - 76.42 7.42 10.96 4 71.37 65.20 - 76.42 4.60 12.94 9 69.14 46.79 - 73.70 8.16 12.31 Philippines 28 68.52 61.08 - 75.80 3.61 5.26 22 68.61 63.29 - 75.80 3.29 4.74 6 67.39 61.08 - 70.73 4.07 6.13 Andaman Is. 36 63.22 57.63 - 70.89 3.01 4.74 18 63.56 60.17 - 70.89 3.11 4.84 18 62.54 57.63 - 68.45 2.78 4.43 Nicobar Is. 20 66.78 60.33 - 73.00 3.44 5.16 17 67.29 60.33 - 73.00 3.40 5.08 3 63.96 61.80 - 69.24 3.82 10.30 Borneo 37 69.07 61.43 - 77.80 4.06 5.90 26 69.55 61.59 - 77.80 4.16 6.00 11 67.60 61.43 - 73.74 3.77 5.56 Indonesia 27 70.72 62.40 - 77.92 4.01 5.69 20 71.45 64.88 - 77.92 3.65 5.10 7 67.71 62.40 - 70.92 3.38 5.03 Melanesia 30 70.74 65.41 - 79.58 3.65 5.10 20 73.20 68.99 - 79.58 3.03 4.14 10 68.90 65.41 - 70.15 2.04 2.99 Micronesia 15 70.30 65.86 - 80.64 3.75 5.25 7 74.05 69.31 - 80.64 4.29 5.82 8 69.87 65.86 - 71.59 1.83 2.63 Australia 27 71.53 65.15 - 83.38 4.30 5.89 18 73.88 66.83 - 83.38 4.31 5.82 9 70.49 65.15 - 78.39 3.49 4.93 Africa 29 72.66 63.06 - 81.89 4.75 6.53 18 72.74 63.06 - 81.89 5.01 6.87 11 70.41 65.63 - 80.49 4.48 6.20 Nat. America 33 71.01 66.98 - 78.05 3.15 4.41 10 71.77 67.65 - 75.79 3.49 4.87 23 71.01 66.98 - 78.05 3.06 4.29 Caucasian 29 68.22 60.91 - 76.18 3.68 5.40 15 70.49 65.36 - 76.18 2.96 4.22 14 65.67 60.91 - 71.01 3.09 4.67 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

343 Biparietal Breadth

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (mm) (mm) (%) (mm) (mm) (%) (mm) (mm) (%)

Siberia 28 113.47 105.28 - 130.00 6.19 5.39 18 113.99 105.97 - 130.00 6.86 5.94 10 113.47 105.28 - 119.10 4.55 4.02 Mongolia 24 116.58 102.36 - 127.94 6.56 5.63 15 117.52 107.59 - 127.94 5.65 4.80 9 112.57 102.36 - 124.18 7.61 6.67 Korea 4 119.14 111.71 - 129.67 7.81 13.02 2 125.95 122.23 - 129.67 5.27 6.27 2 113.88 111.71 - 116.05 3.07 4.04 Ainu 3 123.27 122.69 - 127.95 2.88 4.04 2 125.61 123.27 - 127.95 3.30 3.95 1 122.69 122.69 - 122.69 - - Japan 13 118.14 106.56 - 127.99 7.81 6.70 10 118.65 106.56 - 127.99 8.30 7.07 3 110.72 109.57 - 121.19 6.40 9.84 S. China 6 117.56 106.93 - 124.75 5.89 5.03 3 119.84 115.55 - 124.75 4.60 6.71 3 116.79 106.93 - 118.33 6.18 9.49 N. China 16 120.24 114.75 - 129.98 4.58 3.80 13 120.57 114.75 - 129.98 4.92 4.05 3 118.13 117.33 - 119.34 1.01 1.50 Burma 39 117.62 105.50 - 137.96 6.90 5.87 22 119.76 105.95 - 137.96 7.99 6.70 17 115.57 105.50 - 124.38 4.57 3.96 Laos 24 115.04 105.20 - 124.16 5.55 4.82 16 115.95 105.20 - 124.16 5.92 5.11 8 111.08 107.71 - 120.12 4.57 4.03 Vietnam 23 115.31 95.13 - 128.49 8.02 6.93 13 118.23 111.04 - 128.49 5.91 4.95 10 113.27 95.13 - 120.79 7.78 7.03 Thailand 21 118.67 101.83 - 128.48 6.64 5.60 15 118.30 101.83 - 128.36 6.51 5.51 6 118.92 107.14 - 128.48 7.49 6.26 Cambodia 13 114.90 107.63 - 123.96 4.54 3.89 4 117.50 114.24 - 120.32 3.27 5.57 9 114.81 107.63 - 123.96 5.14 4.42 Philippines 28 117.79 105.45 - 127.06 6.00 5.13 22 118.23 109.15 - 127.06 4.83 4.07 6 108.28 105.45 - 118.96 5.96 5.38 Andaman Is. 36 116.80 110.41 - 129.01 5.21 4.43 18 120.22 110.41 - 129.01 5.77 4.85 18 115.78 110.41 - 124.82 4.48 3.84 Nicobar Is. 20 114.48 102.21 - 129.44 6.39 5.58 17 113.96 102.21 - 129.44 6.67 5.83 3 118.62 109.77 - 119.39 5.35 8.07 Borneo 37 118.88 104.52 - 129.22 6.18 5.24 26 118.86 104.52 - 129.22 6.75 5.73 11 119.57 112.27 - 126.04 4.75 4.00 Indonesia 27 120.55 111.34 - 132.77 5.18 4.30 20 121.89 112.49 - 132.77 5.05 4.15 7 118.05 111.34 - 121.96 3.72 3.18 Melanesia 30 114.75 103.07 - 123.75 5.12 4.46 20 115.11 103.07 - 123.75 5.34 4.64 10 113.92 105.27 - 119.80 4.79 4.21 Micronesia 15 116.50 106.05 - 127.91 6.22 5.36 7 117.18 113.17 - 127.91 4.95 4.17 8 113.01 106.05 - 124.63 6.76 5.93 Australia 27 114.27 103.52 - 128.55 5.72 5.01 18 114.25 106.16 - 121.61 4.83 4.23 9 114.54 103.52 - 128.55 7.53 6.61 Africa 29 116.15 106.13 - 128.86 5.82 4.99 18 116.50 106.13 - 128.86 5.76 4.93 11 114.52 109.21 - 128.55 6.11 5.27 Nat. America 33 111.64 105.55 - 124.57 4.23 3.79 10 114.89 112.56 - 124.57 3.94 3.40 23 109.28 105.55 - 118.01 3.13 2.84 Caucasian 29 117.03 105.30 - 138.09 6.72 5.66 15 121.84 105.30 - 138.09 7.92 6.53 14 115.92 110.44 - 125.03 3.88 3.34 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

344 Bi-superior Zygomatic Breadth

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (mm) (mm) (%) (mm) (mm) (%) (mm) (mm) (%)

Siberia 28 124.58 112.49 - 136.56 6.37 5.13 18 128.57 112.49 - 136.56 5.23 4.10 10 117.83 114.20 - 121.26 2.39 2.03 Mongolia 24 120.07 107.61 - 133.60 7.24 5.98 15 124.84 116.62 - 133.60 5.12 4.10 9 113.77 107.61 - 126.05 5.70 4.97 Korea 4 123.33 112.52 - 125.41 5.93 9.79 2 123.33 122.03 - 124.62 1.83 2.22 2 118.96 112.52 - 125.41 9.12 11.50 Ainu 3 123.72 115.04 - 125.00 5.42 7.82 2 124.36 123.72 - 125.00 0.91 1.10 1 115.04 115.04 - 115.04 - - Japan 13 120.24 109.87 - 125.72 4.91 4.09 10 122.64 116.19 - 125.72 3.27 2.68 3 112.98 109.87 - 118.01 4.11 6.33 S. China 6 123.96 117.11 - 129.57 5.29 4.29 3 127.52 121.07 - 129.57 4.44 6.16 3 118.12 117.11 - 126.86 5.36 7.77 N. China 16 118.40 99.69 - 131.38 8.44 7.13 13 121.20 112.08 - 131.38 6.23 5.14 3 109.54 99.69 - 114.02 7.33 11.91 Burma 39 118.57 104.48 - 128.05 6.50 5.52 22 123.18 110.08 - 128.05 5.30 4.38 17 114.66 104.48 - 123.00 5.58 4.91 Laos 24 118.84 112.03 - 126.26 3.97 3.34 16 119.75 112.82 - 126.26 4.27 3.57 8 117.26 112.03 - 121.46 3.04 2.59 Vietnam 23 119.99 113.20 - 128.78 4.78 3.97 13 123.12 113.20 - 128.78 4.77 3.89 10 118.71 114.25 - 120.19 2.63 2.25 Thailand 21 119.19 108.55 - 128.66 5.55 4.67 15 120.35 114.95 - 128.66 4.23 3.48 6 113.74 108.55 - 115.81 2.75 2.44 Cambodia 13 118.85 108.03 - 124.86 5.01 4.22 4 120.60 117.31 - 124.86 3.67 6.08 9 118.85 108.03 - 124.63 5.39 4.58 Philippines 28 120.03 106.68 - 131.05 5.87 4.92 22 121.54 113.29 - 131.05 4.31 3.54 6 111.65 106.68 - 120.50 4.55 4.04 Andaman Is. 36 111.58 104.04 - 119.52 4.39 3.94 18 113.49 104.04 - 119.52 4.23 3.73 18 109.01 105.04 - 117.35 3.84 3.51 Nicobar Is. 20 117.36 106.97 - 124.59 4.56 3.92 17 117.46 109.61 - 124.59 3.81 3.24 3 111.02 106.97 - 112.34 2.80 4.45 Borneo 37 118.97 106.81 - 129.95 5.91 4.99 26 120.78 106.81 - 129.95 5.62 4.66 11 113.29 107.68 - 118.39 3.09 2.72 Indonesia 27 119.86 109.22 - 129.81 5.30 4.42 20 121.25 111.60 - 129.81 4.83 3.97 7 115.50 109.22 - 118.83 2.98 2.59 Melanesia 30 117.00 106.33 - 126.93 4.98 4.26 20 119.26 112.34 - 126.93 3.73 3.13 10 113.79 106.33 - 119.59 4.51 4.00 Micronesia 15 118.13 108.06 - 129.42 6.90 5.80 7 124.02 117.25 - 129.42 4.52 3.63 8 112.88 108.06 - 118.96 3.76 3.32 Australia 27 120.20 110.15 - 133.36 6.15 5.11 18 123.10 112.13 - 133.36 5.15 4.18 9 113.84 110.15 - 122.05 3.94 3.42 Africa 29 124.08 115.48 - 128.53 3.67 2.98 18 124.26 115.48 - 128.53 3.82 3.09 11 120.99 119.11 - 126.19 3.28 2.69 Nat. America 33 119.97 110.36 - 125.81 4.17 3.49 10 120.56 118.46 - 125.81 2.82 2.32 23 119.70 110.36 - 125.35 4.35 3.67 Caucasian 29 116.55 104.27 - 128.78 5.32 4.56 15 118.70 114.77 - 128.78 3.89 3.26 14 112.10 104.27 - 119.75 4.57 4.05 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

345 Bi-inferior Zygomatic Breadth

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (mm) (mm) (%) (mm) (mm) (%) (mm) (mm) (%)

Siberia 28 128.31 115.95 - 139.53 5.88 4.65 18 129.06 123.97 - 139.53 3.68 2.83 10 119.15 115.95 - 124.22 3.06 2.55 Mongolia 24 125.66 110.35 - 135.49 6.99 5.63 15 128.13 122.58 - 135.49 3.75 2.92 9 117.41 110.35 - 125.66 5.01 4.27 Korea 4 124.24 116.12 - 129.20 5.43 8.79 2 124.24 123.91 - 124.57 0.46 0.56 2 122.66 116.12 - 129.20 9.25 11.32 Ainu 3 123.82 117.18 - 130.45 9.39 13.27 1 130.45 130.45 - 130.45 - - 1 117.18 117.18 - 117.18 - - Japan 13 122.70 115.38 - 128.40 4.12 3.36 10 124.51 119.50 - 128.40 2.99 2.41 3 115.90 115.38 - 121.08 3.15 4.69 S. China 6 123.90 117.75 - 130.48 5.67 4.57 3 129.42 120.40 - 130.48 5.54 7.64 3 118.89 117.75 - 127.39 5.27 7.60 N. China 16 123.04 102.99 - 132.28 8.46 6.94 13 126.04 115.49 - 132.28 5.37 4.30 3 110.47 102.99 - 119.17 8.09 12.78 Burma 39 120.43 106.42 - 130.18 6.92 5.78 22 123.46 110.15 - 130.18 5.86 4.78 17 116.53 106.42 - 126.42 6.58 5.66 Laos 24 121.26 114.53 - 128.01 3.82 3.16 16 122.64 114.95 - 128.01 3.52 2.87 8 117.53 114.53 - 120.13 1.85 1.57 Vietnam 23 122.30 115.03 - 131.90 5.12 4.16 13 125.23 119.75 - 131.90 4.48 3.56 10 120.48 115.03 - 125.42 3.65 3.05 Thailand 21 122.87 111.02 - 134.61 4.96 4.07 15 123.74 120.97 - 134.61 3.47 2.79 6 117.59 111.02 - 120.86 3.63 3.11 Cambodia 13 121.84 110.99 - 129.97 5.20 4.26 4 123.79 121.91 - 129.67 3.48 5.58 9 121.54 110.99 - 129.97 5.47 4.54 Philippines 28 122.40 109.43 - 134.46 6.39 5.21 22 124.60 115.15 - 134.46 5.07 4.07 6 114.51 109.43 - 122.41 4.85 4.23 Andaman Is. 36 113.68 105.96 - 122.29 4.28 3.73 18 116.25 105.96 - 122.29 4.39 3.78 18 112.03 107.64 - 119.32 3.64 3.22 Nicobar Is. 20 117.33 109.35 - 123.66 4.06 3.47 17 118.20 109.76 - 123.66 3.66 3.10 3 113.40 109.35 - 114.54 2.73 4.25 Borneo 37 121.27 106.79 - 135.30 6.27 5.17 26 124.19 107.87 - 135.30 5.61 4.55 11 116.65 106.79 - 120.38 4.16 3.60 Indonesia 27 121.62 113.88 - 130.60 5.42 4.44 20 123.58 115.70 - 130.60 4.65 3.74 7 116.80 113.88 - 119.98 2.29 1.96 Melanesia 30 118.45 108.38 - 132.29 5.91 4.92 20 122.45 115.38 - 132.29 5.05 4.14 10 115.33 108.38 - 125.38 5.24 4.54 Micronesia 15 122.04 112.10 - 134.63 6.66 5.48 7 126.89 119.23 - 134.63 4.77 3.77 8 115.80 112.10 - 123.08 4.17 3.58 Australia 27 120.36 113.16 - 132.95 5.84 4.76 18 126.52 113.16 - 132.95 5.87 4.70 9 118.09 114.96 - 123.18 2.65 2.24 Africa 29 124.11 116.35 - 132.45 3.86 3.13 18 124.19 119.31 - 132.45 3.68 2.96 11 122.89 116.35 - 125.31 3.94 3.24 Nat. America 33 122.20 111.13 - 131.56 4.46 3.65 10 123.47 118.75 - 131.56 4.15 3.33 23 121.70 111.13 - 127.86 4.26 3.52 Caucasian 29 119.44 109.48 - 127.47 4.44 3.72 15 121.23 117.44 - 127.47 2.83 2.34 14 114.32 109.48 - 122.29 4.86 4.23 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

346 Bimastoidale

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (mm) (mm) (%) (mm) (mm) (%) (mm) (mm) (%)

Siberia 28 106.59 92.93 - 118.95 6.00 5.65 18 107.58 92.93 - 118.95 6.65 6.18 10 102.58 97.94 - 108.31 3.36 3.25 Mongolia 24 108.55 95.06 - 115.60 5.41 5.03 15 108.69 100.99 - 114.84 3.88 3.58 9 106.09 95.06 - 115.60 7.46 7.01 Korea 4 107.38 103.60 - 109.67 3.07 5.74 2 105.49 103.60 - 107.38 2.67 3.80 1 109.67 109.67 - 109.67 - - Ainu 3 98.12 94.56 - 103.06 4.27 7.58 2 100.59 98.12 - 103.06 3.49 5.21 1 94.56 94.56 - 94.56 - - Japan 13 103.19 93.90 - 112.07 5.28 5.18 10 103.23 93.90 - 112.07 5.26 5.10 3 98.68 94.17 - 103.29 4.56 8.08 S. China 6 102.44 97.21 - 113.97 6.10 5.86 3 103.00 97.21 - 113.97 8.51 14.23 3 101.88 99.88 - 108.21 4.35 7.37 N. China 16 103.43 93.75 - 111.48 5.00 4.81 13 105.40 100.71 - 111.48 3.48 3.30 3 95.60 93.75 - 101.18 3.87 6.99 Burma 39 102.35 90.19 - 119.42 6.19 6.09 22 103.65 94.13 - 119.42 5.34 5.16 17 96.79 90.19 - 110.29 6.56 6.60 Laos 24 102.55 94.63 - 112.06 4.12 4.01 16 103.25 97.56 - 112.06 4.13 3.99 8 102.34 94.63 - 104.92 3.63 3.60 Vietnam 23 104.23 98.78 - 113.34 3.56 3.41 13 104.78 99.78 - 113.34 3.58 3.39 10 102.46 98.78 - 108.70 3.23 3.13 Thailand 21 102.15 97.15 - 113.05 4.31 4.17 15 104.87 97.15 - 113.05 4.51 4.32 6 100.64 97.75 - 105.18 2.50 2.48 Cambodia 13 103.39 93.69 - 112.97 6.26 6.10 4 103.63 98.85 - 108.36 4.39 8.48 9 103.39 93.69 - 112.97 7.13 6.98 Philippines 28 100.71 87.65 - 114.65 6.05 5.98 22 101.79 87.65 - 114.65 6.43 6.31 6 98.23 94.14 - 102.89 3.70 3.75 Andaman Is. 36 90.89 82.49 - 99.91 3.93 4.32 18 92.57 86.45 - 99.91 3.54 3.83 18 89.35 82.49 - 95.30 3.48 3.91 Nicobar Is. 20 96.95 90.70 - 104.28 4.19 4.33 17 97.78 90.70 - 104.28 4.28 4.41 3 94.19 91.37 - 96.40 2.52 4.69 Borneo 37 101.97 86.98 - 111.00 5.58 5.46 26 103.67 90.55 - 111.00 4.86 4.67 11 97.09 86.98 - 105.38 4.81 4.91 Indonesia 27 102.50 90.56 - 110.69 5.39 5.29 20 103.04 91.91 - 110.69 4.86 4.72 7 98.37 90.56 - 106.62 5.71 5.80 Melanesia 30 99.44 93.28 - 117.02 5.86 5.81 20 99.66 94.56 - 117.02 5.60 5.49 10 98.76 93.28 - 113.38 5.97 6.06 Micronesia 15 103.22 93.21 - 107.49 4.81 4.72 7 105.45 100.64 - 107.49 2.27 2.16 8 98.76 93.21 - 105.43 4.49 4.54 Australia 27 99.50 92.10 - 109.38 4.36 4.38 18 100.98 93.05 - 109.38 4.44 4.40 9 96.74 92.10 - 100.63 2.56 2.64 Africa 29 99.59 91.19 - 108.26 4.03 4.01 18 101.00 93.82 - 108.26 3.90 3.85 11 98.69 91.19 - 105.61 3.99 4.03 Nat. America 33 103.51 93.42 - 116.73 5.27 5.12 10 103.18 99.28 - 116.73 5.19 4.97 23 103.66 93.42 - 108.59 5.25 5.15 Caucasian 29 102.96 82.93 - 113.00 6.96 6.88 15 104.77 94.26 - 113.00 4.85 4.61 14 99.03 82.93 - 104.22 6.61 6.80 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

347 Mastoidale-Obelion

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (mm) (mm) (%) (mm) (mm) (%) (mm) (mm) (%)

Siberia 28 135.81 127.50 - 150.04 6.73 4.90 18 139.67 131.82 - 150.04 6.15 4.40 10 131.25 127.50 - 146.59 5.78 4.33 Mongolia 24 139.96 126.25 - 147.49 6.34 4.60 15 140.75 129.65 - 147.49 4.80 3.41 9 138.71 126.25 - 143.90 6.93 5.12 Korea 4 145.87 135.49 - 152.88 7.33 10.10 2 150.30 147.73 - 152.88 3.64 3.63 2 139.75 135.49 - 144.00 6.02 6.46 Ainu 3 144.46 139.89 - 149.03 6.46 7.83 1 149.03 149.03 - 149.03 - - 1 139.89 139.89 - 139.89 - - Japan 13 139.93 132.12 - 144.06 4.14 2.98 10 140.48 135.24 - 144.06 3.01 2.14 3 132.82 132.12 - 133.51 0.99 1.30 S. China 6 140.42 129.29 - 142.67 6.19 4.48 3 142.38 142.10 - 142.67 0.41 0.50 3 134.02 129.29 - 138.74 6.68 8.72 N. China 16 143.59 130.92 - 160.40 8.75 6.07 13 144.90 130.92 - 160.40 8.51 5.83 3 135.42 134.28 - 136.55 1.60 2.07 Burma 39 136.50 125.86 - 153.60 8.07 5.83 22 143.28 127.46 - 153.60 8.26 5.84 17 134.53 125.86 - 146.00 5.66 4.22 Laos 24 139.29 130.81 - 150.14 5.17 3.70 16 142.91 137.56 - 150.14 4.00 2.81 8 134.44 130.81 - 143.04 3.69 2.73 Vietnam 23 141.71 130.08 - 154.39 6.15 4.35 13 146.64 138.08 - 154.39 4.47 3.07 10 136.92 130.08 - 146.17 4.46 3.26 Thailand 21 142.62 133.58 - 151.65 5.38 3.79 15 143.78 135.06 - 151.65 4.88 3.40 6 136.18 133.58 - 144.29 5.01 3.64 Cambodia 13 139.01 131.71 - 148.52 5.69 4.05 4 147.24 140.58 - 148.52 3.62 4.97 9 138.19 131.71 - 139.45 3.09 2.26 Philippines 28 141.62 128.75 - 152.96 6.47 4.59 22 143.07 130.64 - 152.96 5.83 4.08 6 133.96 128.75 - 139.53 4.17 3.11 Andaman Is. 36 132.11 123.99 - 138.89 4.31 3.27 18 134.45 124.09 - 138.89 4.20 3.14 18 128.81 123.99 - 134.72 3.27 2.52 Nicobar Is. 20 138.86 132.89 - 157.79 5.92 4.21 17 139.86 135.01 - 157.79 5.91 4.17 3 134.48 132.89 - 140.61 4.08 5.24 Borneo 37 141.96 128.33 - 153.32 6.70 4.75 26 145.13 129.49 - 153.32 6.49 4.54 11 136.27 128.33 - 143.74 4.85 3.55 Indonesia 27 140.03 131.14 - 156.21 7.50 5.33 20 143.69 132.31 - 156.21 6.62 4.61 7 133.42 131.14 - 134.07 1.12 0.84 Melanesia 30 139.09 123.37 - 156.07 7.31 5.21 20 139.96 134.92 - 156.07 6.32 4.43 10 138.03 123.37 - 143.30 7.35 5.43 Micronesia 15 140.66 131.49 - 153.73 7.22 5.12 7 146.37 145.77 - 153.73 3.81 2.57 8 135.97 131.49 - 143.27 4.31 3.17 Australia 27 137.06 127.09 - 144.67 5.59 4.10 18 137.14 129.52 - 144.67 5.22 3.80 9 129.73 127.09 - 138.51 5.98 4.54 Africa 29 140.21 128.36 - 146.11 4.78 3.45 18 140.86 132.22 - 146.11 3.55 2.53 11 136.93 128.36 - 141.88 5.30 3.91 Nat. America 33 133.50 126.37 - 155.07 7.17 5.33 10 138.10 134.81 - 142.82 3.51 2.52 23 131.39 126.37 - 155.07 7.53 5.67 Caucasian 29 133.13 112.27 - 144.11 7.65 5.73 15 139.50 132.27 - 144.11 4.48 3.23 14 130.03 112.27 - 141.25 7.67 5.88 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

348 Mastoid Height (ms-po)

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (mm) (mm) (%) (mm) (mm) (%) (mm) (mm) (%)

Siberia 28 30.72 25.85 - 37.19 3.33 10.73 18 30.34 25.85 - 36.57 2.98 9.90 10 32.64 28.08 - 37.19 3.40 10.38 Mongolia 24 30.61 21.28 - 35.24 3.71 12.15 15 31.53 21.28 - 35.24 4.43 14.55 9 30.14 27.85 - 34.71 2.28 7.43 Korea 4 33.07 29.91 - 37.41 3.27 19.58 2 35.91 34.40 - 37.41 2.13 8.89 2 30.83 29.91 - 31.74 1.29 6.30 Ainu 3 31.01 29.98 - 34.63 2.44 13.41 2 32.82 31.01 - 34.63 2.56 11.71 1 29.98 29.98 - 29.98 - - Japan 13 31.13 26.92 - 41.79 3.74 11.50 10 32.08 30.59 - 41.79 3.58 10.67 3 29.68 26.92 - 30.98 2.08 12.45 S. China 6 33.41 29.38 - 38.71 3.13 9.38 3 31.38 29.38 - 38.71 4.91 25.93 3 33.63 33.19 - 34.13 0.47 2.43 N. China 16 32.65 25.61 - 39.18 4.03 12.07 13 32.56 25.61 - 39.18 3.87 11.74 3 37.16 29.61 - 39.18 5.05 25.00 Burma 39 32.66 25.26 - 38.32 3.51 10.75 22 33.39 28.39 - 38.32 2.84 8.43 17 30.02 25.26 - 37.17 3.84 12.30 Laos 24 31.20 25.99 - 38.01 2.87 9.22 16 31.26 25.99 - 38.01 3.32 10.65 8 30.62 29.27 - 34.51 1.87 6.00 Vietnam 23 31.57 24.72 - 36.82 2.94 9.38 13 30.64 24.72 - 36.82 3.38 10.90 10 32.21 27.81 - 34.60 2.34 7.34 Thailand 21 33.17 25.05 - 38.23 3.57 10.77 15 33.37 28.82 - 38.23 3.24 9.59 6 31.51 25.05 - 37.04 4.08 12.98 Cambodia 13 34.45 25.84 - 41.91 4.20 12.15 4 34.80 33.84 - 35.92 0.96 5.49 9 34.45 25.84 - 41.91 5.22 15.16 Philippines 28 32.44 28.19 - 37.32 2.81 8.64 22 32.44 28.19 - 37.32 2.74 8.40 6 31.66 28.74 - 36.65 3.36 10.33 Andaman Is. 36 27.69 22.64 - 43.46 3.87 13.52 18 29.44 24.21 - 43.46 4.27 14.19 18 26.89 22.64 - 33.27 2.79 10.29 Nicobar Is. 20 31.29 27.30 - 36.92 2.56 8.11 17 31.54 27.30 - 36.92 2.55 8.02 3 30.33 27.47 - 32.53 2.54 14.76 Borneo 37 31.08 24.23 - 37.54 3.17 10.24 26 32.24 26.04 - 37.54 2.52 7.84 11 28.78 24.23 - 32.72 2.68 9.54 Indonesia 27 32.13 24.17 - 37.26 2.78 8.69 20 32.07 28.12 - 37.26 2.52 7.79 7 32.13 24.17 - 33.81 3.45 11.12 Melanesia 30 31.34 23.55 - 41.13 3.93 12.29 20 32.65 23.55 - 39.30 3.94 12.26 10 29.81 28.35 - 41.13 4.09 12.93 Micronesia 15 32.04 27.10 - 39.92 3.39 10.46 7 32.17 27.10 - 34.31 2.80 8.96 8 32.04 29.50 - 39.92 3.67 10.94 Australia 27 30.73 23.11 - 39.50 3.70 11.93 18 32.36 27.68 - 39.50 2.74 8.37 9 27.86 23.11 - 30.88 2.89 10.46 Africa 29 32.17 24.37 - 38.30 3.25 10.25 18 32.32 24.37 - 38.30 3.57 11.25 11 31.21 28.55 - 37.20 2.77 8.71 Nat. America 33 30.49 22.41 - 35.86 2.92 9.65 10 30.60 27.69 - 35.86 2.65 8.66 23 30.14 22.41 - 34.91 3.07 10.21 Caucasian 29 29.82 22.66 - 37.01 3.13 10.64 15 31.14 25.45 - 37.01 2.66 8.69 14 28.49 22.66 - 33.17 3.19 11.34 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

349 Inferior Malar Length (IML)

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (mm) (mm) (%) (mm) (mm) (%) (mm) (mm) (%)

Siberia 28 33.36 27.11 - 42.09 4.21 12.41 18 34.05 28.56 - 42.09 4.27 12.17 10 32.17 27.11 - 36.61 3.36 10.55 Mongolia 24 32.12 23.00 - 37.47 3.58 11.35 15 33.16 27.50 - 37.47 2.86 8.63 9 29.87 23.00 - 31.68 2.95 10.26 Korea 4 28.64 26.36 - 32.25 2.60 17.95 2 29.31 26.36 - 32.25 4.16 21.30 2 28.64 27.52 - 29.77 1.59 8.32 Ainu 3 31.09 28.72 - 32.15 1.76 10.03 2 31.62 31.09 - 32.15 0.74 3.53 1 28.72 28.72 - 28.72 - - Japan 13 31.28 26.27 - 35.39 2.73 8.88 10 31.04 26.27 - 35.39 3.07 9.98 3 31.28 28.95 - 31.78 1.51 8.62 S. China 6 34.61 29.94 - 37.39 2.82 8.23 3 36.48 32.80 - 37.39 2.43 11.97 3 33.19 29.94 - 36.03 3.05 16.14 N. China 16 31.88 20.07 - 41.52 4.52 14.25 13 32.12 29.17 - 41.52 3.44 10.56 3 30.17 20.07 - 34.73 7.50 46.34 Burma 39 30.54 24.96 - 38.72 3.33 10.71 22 31.41 28.13 - 38.72 3.15 9.85 17 29.45 24.96 - 35.81 3.28 10.96 Laos 24 32.23 26.70 - 40.05 3.27 10.05 16 32.79 28.49 - 40.05 3.19 9.81 8 31.59 26.70 - 37.62 3.63 11.22 Vietnam 23 32.62 27.75 - 38.33 2.92 8.80 13 33.73 27.75 - 37.40 2.77 8.41 10 31.94 30.67 - 38.33 3.23 9.63 Thailand 21 30.82 20.46 - 36.64 3.96 12.93 15 32.93 27.12 - 36.64 2.81 8.82 6 30.35 20.46 - 30.82 4.86 17.69 Cambodia 13 33.14 28.03 - 42.25 3.51 10.37 4 34.34 32.16 - 42.25 4.74 26.48 9 33.14 28.03 - 36.78 2.70 8.20 Philippines 28 30.76 25.03 - 37.66 3.30 10.56 22 31.51 27.28 - 37.66 3.18 9.98 6 29.58 25.03 - 34.05 3.21 10.98 Andaman Is. 36 32.23 26.62 - 37.61 2.83 8.89 18 32.36 26.62 - 37.61 3.41 10.71 18 32.15 27.51 - 37.49 2.20 6.91 Nicobar Is. 20 31.15 23.82 - 37.84 3.68 11.86 17 31.48 23.82 - 37.84 3.42 10.83 3 26.47 24.76 - 32.68 4.17 26.06 Borneo 37 31.89 25.82 - 42.56 3.50 10.69 26 31.89 25.82 - 42.56 3.79 11.52 11 32.05 28.58 - 36.57 2.75 8.49 Indonesia 27 31.36 26.34 - 38.17 3.47 10.74 20 33.48 29.33 - 38.17 3.14 9.38 7 28.74 26.34 - 31.36 1.85 6.37 Melanesia 30 34.62 27.85 - 41.81 3.58 10.19 20 37.22 29.79 - 41.81 3.11 8.49 10 32.66 27.85 - 35.79 2.49 7.74 Micronesia 15 33.20 27.60 - 39.55 3.33 9.81 7 36.67 32.62 - 39.55 2.67 7.37 8 32.47 27.60 - 35.60 2.53 7.93 Australia 27 38.02 28.93 - 45.93 3.92 10.30 18 38.44 33.98 - 45.93 3.36 8.49 9 35.18 28.93 - 40.88 3.53 10.00 Africa 29 34.78 23.36 - 42.91 4.03 11.62 18 35.56 23.36 - 42.91 4.14 11.84 11 34.05 28.40 - 39.91 3.97 11.64 Nat. America 33 32.01 27.61 - 37.82 2.74 8.48 10 32.68 28.51 - 37.82 3.09 9.46 23 31.99 27.61 - 37.79 2.63 8.17 Caucasian 29 31.18 26.02 - 36.88 2.59 8.19 15 32.04 28.04 - 36.88 2.61 8.07 14 30.42 26.02 - 34.53 2.35 7.65 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

350 Zygomaxillare-Frontomalare Orbitale

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (mm) (mm) (%) (mm) (mm) (%) (mm) (mm) (%)

Siberia 28 44.71 38.27 - 54.15 4.06 9.03 18 44.63 39.54 - 54.15 4.34 9.53 10 44.74 38.27 - 49.41 3.43 7.82 Mongolia 24 44.47 38.55 - 50.02 2.69 6.08 15 44.52 41.74 - 47.82 2.17 4.84 9 42.31 38.55 - 50.02 3.38 7.78 Korea 4 45.03 39.31 - 51.96 5.22 23.03 2 48.90 45.85 - 51.96 4.33 13.27 2 41.76 39.31 - 44.21 3.47 12.45 Ainu 3 44.47 39.97 - 45.07 2.79 11.29 2 42.52 39.97 - 45.07 3.60 12.71 1 44.47 44.47 - 44.47 - - Japan 13 41.96 39.48 - 46.87 2.22 5.23 10 42.32 39.79 - 46.87 2.10 4.89 3 40.00 39.48 - 44.14 2.56 10.86 S. China 6 41.21 39.30 - 44.54 1.98 4.74 3 40.94 39.30 - 43.80 2.28 9.64 3 41.47 40.77 - 44.54 2.01 8.31 N. China 16 45.70 39.94 - 50.68 2.76 6.12 13 45.63 39.94 - 48.34 2.48 5.54 3 46.29 42.45 - 50.68 4.12 15.50 Burma 39 42.52 34.47 - 52.89 3.82 8.91 22 43.03 37.70 - 52.89 3.87 8.80 17 41.25 34.47 - 47.65 3.34 8.06 Laos 24 42.75 39.04 - 57.61 3.94 9.09 16 42.84 39.04 - 57.61 4.47 10.16 8 42.08 39.26 - 46.77 2.50 5.91 Vietnam 23 42.85 37.07 - 48.50 2.92 6.78 13 42.81 37.07 - 47.74 2.92 6.79 10 43.14 39.00 - 48.50 3.07 7.14 Thailand 21 42.16 38.46 - 47.92 2.35 5.54 15 42.30 38.68 - 47.92 2.40 5.64 6 41.95 38.46 - 45.63 2.36 5.63 Cambodia 13 44.16 38.71 - 50.09 3.17 7.06 4 44.08 42.61 - 45.39 1.14 5.16 9 44.99 38.71 - 50.09 3.74 8.25 Philippines 28 42.87 37.72 - 48.35 2.87 6.78 22 43.05 38.74 - 48.35 2.75 6.44 6 40.87 37.72 - 45.00 3.08 7.52 Andaman Is. 36 39.90 33.98 - 44.48 2.12 5.33 18 40.85 33.98 - 42.21 1.97 4.90 18 38.99 36.15 - 44.48 2.19 5.58 Nicobar Is. 20 40.70 38.49 - 48.49 2.92 7.03 17 41.38 38.49 - 48.49 3.04 7.25 3 39.23 39.11 - 40.93 1.02 4.49 Borneo 37 43.11 38.04 - 50.70 2.74 6.34 26 43.96 39.50 - 50.70 2.73 6.21 11 41.48 38.04 - 46.01 2.13 5.11 Indonesia 27 44.04 38.78 - 49.80 3.37 7.60 20 44.80 38.78 - 49.80 3.32 7.35 7 41.21 38.80 - 44.42 1.72 4.14 Melanesia 30 43.35 35.67 - 49.39 3.21 7.53 20 43.55 35.67 - 49.39 3.57 8.36 10 41.98 39.43 - 46.31 2.50 5.89 Micronesia 15 42.89 38.77 - 48.41 3.10 7.20 7 43.20 38.77 - 48.41 3.70 8.60 8 42.30 40.18 - 47.25 2.73 6.35 Australia 27 42.10 36.69 - 48.28 3.08 7.24 18 43.19 37.90 - 48.28 2.79 6.46 9 40.41 36.69 - 47.85 3.35 8.13 Africa 29 43.12 37.54 - 50.15 2.81 6.49 18 42.89 39.80 - 50.15 2.60 6.00 11 43.41 37.54 - 49.98 3.31 7.64 Nat. America 33 43.37 38.73 - 48.56 2.50 5.73 10 45.40 40.92 - 47.71 2.48 5.52 23 42.86 38.73 - 48.56 2.35 5.46 Caucasian 29 40.86 36.54 - 47.62 2.99 7.18 15 40.99 37.84 - 47.62 3.24 7.69 14 40.74 36.54 - 46.49 2.71 6.61 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

351 Zygomaxillare-Frontomalare Temporale

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (mm) (mm) (%) (mm) (mm) (%) (mm) (mm) (%)

Siberia 28 48.95 41.70 - 57.63 3.93 8.07 18 50.14 43.84 - 57.63 3.88 7.72 10 45.97 41.70 - 49.42 2.13 4.65 Mongolia 24 48.60 40.84 - 54.68 3.24 6.67 15 50.54 44.93 - 54.68 2.57 5.14 9 47.40 40.84 - 50.62 3.08 6.65 Korea 4 49.31 42.91 - 55.64 5.25 21.28 2 52.91 50.18 - 55.64 3.86 10.95 2 45.67 42.91 - 48.44 3.91 12.84 Ainu 3 45.21 42.58 - 47.43 2.42 9.41 2 46.32 45.21 - 47.43 1.57 5.08 1 42.58 42.58 - 42.58 - - Japan 13 47.40 42.48 - 51.01 2.55 5.42 10 47.48 42.48 - 51.01 2.66 5.63 3 45.93 44.11 - 49.11 2.53 9.55 S. China 6 48.98 45.49 - 53.95 3.21 6.56 3 49.03 48.93 - 53.95 2.87 9.93 3 45.52 45.49 - 50.61 2.95 10.93 N. China 16 48.63 42.64 - 57.10 3.52 7.19 13 48.80 45.57 - 57.10 3.17 6.37 3 44.84 42.64 - 48.78 3.11 11.97 Burma 39 45.73 37.46 - 54.75 3.76 8.18 22 46.28 41.75 - 54.75 3.48 7.33 17 45.05 37.46 - 49.80 3.30 7.49 Laos 24 47.08 43.66 - 61.41 3.74 7.87 16 47.56 44.41 - 51.57 2.25 4.75 8 46.08 43.66 - 61.41 5.92 12.39 Vietnam 23 47.55 41.70 - 52.07 2.98 6.31 13 47.90 44.81 - 52.05 2.20 4.57 10 45.68 41.70 - 52.07 3.59 7.78 Thailand 21 47.28 40.97 - 54.10 3.56 7.52 15 47.54 40.97 - 54.10 3.68 7.71 6 46.30 41.47 - 51.08 3.42 7.36 Cambodia 13 48.87 40.81 - 52.59 3.61 7.60 4 49.73 48.23 - 52.59 1.83 7.31 9 46.69 40.81 - 50.71 3.65 7.88 Philippines 28 45.82 41.50 - 52.36 3.26 7.03 22 47.32 41.95 - 52.36 3.13 6.65 6 43.12 41.50 - 48.44 2.55 5.83 Andaman Is. 36 43.07 36.97 - 47.81 2.24 5.24 18 43.46 36.97 - 45.69 2.05 4.75 18 41.88 37.36 - 47.81 2.40 5.67 Nicobar Is. 20 45.02 42.40 - 50.23 2.17 4.79 17 44.95 42.40 - 50.23 2.34 5.16 3 45.36 44.86 - 46.80 1.00 3.85 Borneo 37 47.69 42.25 - 55.58 2.76 5.82 26 48.21 43.48 - 55.58 2.59 5.36 11 45.02 42.25 - 48.36 1.43 3.17 Indonesia 27 47.44 41.94 - 56.55 4.02 8.35 20 49.55 43.05 - 56.55 4.15 8.46 7 45.76 41.94 - 47.44 1.78 3.92 Melanesia 30 47.72 39.55 - 53.89 3.53 7.50 20 48.56 42.62 - 53.89 2.96 6.11 10 44.14 39.55 - 50.23 3.04 6.84 Micronesia 15 46.98 43.30 - 50.89 2.55 5.47 7 47.66 44.22 - 50.89 2.46 5.12 8 45.41 43.30 - 47.33 1.87 4.13 Australia 27 47.19 42.20 - 52.98 2.99 6.38 18 48.03 42.97 - 52.98 2.86 6.00 9 45.72 42.20 - 50.23 2.80 6.17 Africa 29 47.55 42.60 - 52.92 2.67 5.62 18 48.81 44.42 - 52.92 2.15 4.42 11 45.33 42.60 - 50.44 2.25 4.94 Nat. America 33 47.06 41.79 - 52.97 2.73 5.78 10 48.80 45.66 - 52.97 2.20 4.51 23 46.17 41.79 - 52.61 2.71 5.81 Caucasian 29 44.04 39.35 - 49.75 2.70 6.09 15 44.74 39.35 - 49.75 3.14 7.02 14 43.59 39.76 - 47.21 2.14 4.88 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

352 Zygoorbitale-Superior Zygomatic

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (mm) (mm) (%) (mm) (mm) (%) (mm) (mm) (%)

Siberia 28 45.61 37.62 - 57.12 4.72 10.29 18 46.26 43.04 - 57.12 4.00 8.35 10 41.41 37.62 - 48.41 3.38 8.04 Mongolia 24 43.67 35.90 - 51.25 3.98 9.07 15 45.13 39.16 - 51.25 3.84 8.49 9 41.51 35.90 - 47.50 3.40 8.13 Korea 4 44.83 42.03 - 47.76 2.35 10.50 2 46.46 45.15 - 47.76 1.84 5.95 2 43.27 42.03 - 44.52 1.76 6.10 Ainu 3 42.57 42.11 - 45.26 1.70 6.88 2 43.91 42.57 - 45.26 1.90 6.50 1 42.11 42.11 - 42.11 - - Japan 13 43.68 38.75 - 47.88 2.71 6.18 10 43.95 39.91 - 47.88 2.56 5.77 3 43.10 38.75 - 44.52 3.01 12.50 S. China 6 44.10 42.10 - 50.02 2.95 6.60 3 43.55 42.30 - 44.65 1.17 4.71 3 45.95 42.10 - 50.02 3.96 15.06 N. China 16 44.51 35.34 - 54.52 5.46 12.43 13 44.68 35.79 - 54.52 5.46 12.17 3 41.87 35.34 - 42.95 4.12 17.99 Burma 39 41.12 33.00 - 47.71 3.73 9.10 22 42.45 35.37 - 47.71 3.17 7.46 17 39.62 33.00 - 45.29 3.66 9.35 Laos 24 41.38 37.04 - 50.02 2.59 6.21 16 41.57 39.17 - 44.55 1.57 3.79 8 41.06 37.04 - 50.02 4.01 9.45 Vietnam 23 43.69 37.71 - 54.00 3.30 7.54 13 44.26 38.98 - 54.00 3.63 8.14 10 42.42 37.71 - 46.96 2.49 5.86 Thailand 21 42.52 35.06 - 52.87 3.92 9.17 15 43.82 35.06 - 52.87 4.44 10.26 6 41.22 38.96 - 44.10 1.85 4.45 Cambodia 13 42.23 37.08 - 46.43 2.70 6.44 4 42.64 40.32 - 44.03 1.54 7.27 9 41.56 37.08 - 46.43 3.14 7.54 Philippines 28 40.13 34.33 - 51.63 4.07 9.90 22 41.81 34.33 - 51.63 3.96 9.41 6 38.07 34.46 - 39.95 2.22 5.90 Andaman Is. 36 39.27 33.43 - 46.84 2.99 7.61 18 40.21 36.50 - 46.84 2.69 6.65 18 38.13 33.43 - 42.91 2.97 7.76 Nicobar Is. 20 42.10 34.98 - 47.35 3.33 8.07 17 42.31 34.98 - 47.35 2.87 6.82 3 36.56 34.99 - 39.34 2.20 10.42 Borneo 37 41.77 36.23 - 46.10 2.51 6.04 26 41.98 36.23 - 46.10 2.39 5.68 11 40.30 36.39 - 44.36 2.65 6.52 Indonesia 27 41.63 33.96 - 48.94 3.46 8.25 20 42.86 36.83 - 48.94 3.41 7.98 7 40.67 33.96 - 42.81 2.86 7.17 Melanesia 30 42.34 33.69 - 46.47 2.74 6.52 20 42.99 36.61 - 46.47 2.13 4.97 10 40.15 33.69 - 44.25 3.20 7.92 Micronesia 15 42.25 35.98 - 49.37 3.94 9.34 7 43.51 41.45 - 49.37 3.11 6.96 8 39.97 35.98 - 45.79 3.29 8.21 Australia 27 43.92 38.01 - 51.57 3.58 8.17 18 45.48 41.11 - 51.57 2.78 6.10 9 40.22 38.01 - 46.31 2.74 6.72 Africa 29 43.35 33.84 - 50.70 4.05 9.46 18 45.42 35.55 - 48.73 3.58 8.20 11 41.70 33.84 - 50.70 4.51 10.89 Nat. America 33 41.73 36.05 - 46.88 2.48 5.94 10 43.25 36.05 - 46.88 3.17 7.43 23 41.26 37.78 - 45.50 2.03 4.91 Caucasian 29 42.11 35.57 - 48.89 3.22 7.57 15 44.03 39.87 - 48.89 3.04 6.92 14 40.99 35.57 - 44.43 2.73 6.67 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

353 Foramen Magnum Length (FOL)

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (mm) (mm) (%) (mm) (mm) (%) (mm) (mm) (%)

Siberia 28 39.56 32.05 - 45.51 3.33 8.49 18 41.33 32.05 - 45.51 3.14 7.78 10 36.23 34.44 - 42.39 2.54 6.87 Mongolia 24 37.90 30.32 - 41.97 3.40 9.15 15 38.57 30.32 - 41.97 3.30 8.68 9 36.82 30.58 - 39.90 3.29 9.20 Korea 4 35.31 33.81 - 39.15 2.29 12.76 2 37.09 35.03 - 39.15 2.91 11.78 2 34.71 33.81 - 35.60 1.26 5.46 Ainu 3 37.65 37.23 - 38.53 0.66 3.06 2 38.09 37.65 - 38.53 0.62 2.44 1 37.23 37.23 - 37.23 - - Japan 13 36.08 33.92 - 40.69 2.18 5.96 10 36.52 33.94 - 40.69 2.20 5.93 3 34.87 33.92 - 35.50 0.79 4.00 S. China 6 36.80 35.42 - 46.26 4.02 10.53 3 37.09 35.42 - 46.26 5.83 25.79 3 36.67 36.51 - 36.93 0.21 1.00 N. China 16 37.96 32.17 - 40.47 2.46 6.52 13 38.75 32.17 - 40.47 2.27 5.91 3 34.58 34.30 - 36.64 1.28 6.36 Burma 39 36.13 32.10 - 42.28 2.44 6.68 22 36.61 33.67 - 42.28 2.44 6.55 17 35.44 32.10 - 39.57 2.24 6.27 Laos 24 36.09 31.99 - 38.32 1.83 5.08 16 36.80 33.42 - 38.32 1.66 4.57 8 35.38 31.99 - 37.92 2.11 5.95 Vietnam 23 37.51 33.97 - 45.60 2.65 7.04 13 37.51 33.97 - 45.60 3.03 7.91 10 37.65 34.01 - 39.56 1.98 5.36 Thailand 21 36.33 33.03 - 39.41 1.76 4.83 15 36.45 34.00 - 39.21 1.50 4.07 6 35.37 33.03 - 39.41 2.16 6.07 Cambodia 13 37.08 32.41 - 43.93 3.32 8.83 4 38.00 34.74 - 43.93 3.90 20.18 9 35.94 32.41 - 42.72 3.14 8.49 Philippines 28 36.11 30.95 - 43.69 2.93 8.10 22 36.56 30.95 - 43.69 2.85 7.83 6 34.70 31.12 - 39.11 3.20 9.12 Andaman Is. 36 34.15 27.77 - 37.92 2.16 6.32 18 34.85 31.57 - 37.92 1.94 5.57 18 33.97 27.77 - 36.24 2.13 6.38 Nicobar Is. 20 35.56 28.98 - 42.22 3.11 8.71 17 35.95 28.98 - 42.22 3.11 8.72 3 34.26 32.80 - 39.94 3.77 18.50 Borneo 37 37.52 31.63 - 41.12 2.49 6.68 26 37.82 31.63 - 41.12 2.79 7.42 11 36.14 34.44 - 38.61 1.34 3.69 Indonesia 27 35.91 31.00 - 40.91 2.54 7.15 20 35.84 31.67 - 40.91 2.43 6.78 7 35.95 31.00 - 38.58 2.81 8.10 Melanesia 30 36.72 30.70 - 43.53 2.87 7.83 20 36.31 33.04 - 40.99 2.31 6.33 10 36.95 30.70 - 43.53 3.88 10.48 Micronesia 15 37.02 30.88 - 39.62 2.82 7.78 7 38.78 30.88 - 39.62 3.56 9.61 8 35.31 33.28 - 39.20 2.02 5.68 Australia 27 36.34 31.29 - 42.10 2.53 6.89 18 37.30 31.29 - 42.10 2.78 7.47 9 35.34 34.08 - 39.14 1.77 4.92 Africa 29 38.16 34.08 - 46.59 3.11 8.10 18 37.71 34.09 - 46.59 3.24 8.48 11 39.13 34.08 - 43.69 3.01 7.79 Nat. America 33 36.25 32.50 - 40.96 2.21 6.07 10 37.97 33.40 - 39.75 2.23 5.99 23 35.67 32.50 - 40.96 2.12 5.90 Caucasian 29 37.56 31.76 - 40.46 2.31 6.26 15 37.84 32.79 - 40.46 2.07 5.49 14 36.68 31.76 - 38.94 2.24 6.23 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

354 Basion-Sphenobasion

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (mm) (mm) (%) (mm) (mm) (%) (mm) (mm) (%)

Siberia 28 26.26 22.03 - 33.28 3.05 11.49 18 26.46 23.19 - 33.28 2.93 10.89 10 25.40 22.03 - 32.54 3.27 12.68 Mongolia 24 26.21 18.94 - 29.11 2.46 9.52 15 27.02 18.94 - 28.95 2.61 10.01 9 25.02 21.00 - 29.11 2.25 8.86 Korea 4 26.06 23.75 - 30.14 2.66 20.09 2 26.95 23.75 - 30.14 4.52 25.18 2 26.06 25.97 - 26.16 0.14 0.78 Ainu 3 25.52 25.33 - 30.50 2.93 18.92 2 28.01 25.52 - 30.50 3.52 18.85 1 25.33 25.33 - 25.33 - - Japan 13 27.42 22.84 - 29.86 2.04 7.57 10 27.25 24.52 - 29.86 1.67 6.19 3 27.42 22.84 - 29.69 3.49 22.91 S. China 6 26.45 20.15 - 30.21 4.12 16.11 3 25.67 21.14 - 27.23 3.16 22.42 3 28.95 20.15 - 30.21 5.48 36.29 N. China 16 26.94 20.43 - 29.96 2.57 9.62 13 27.13 23.66 - 29.96 2.13 7.85 3 26.94 20.43 - 27.87 4.05 28.28 Burma 39 25.92 21.90 - 29.14 1.91 7.35 22 26.89 21.90 - 29.14 2.04 7.72 17 24.87 23.32 - 29.05 1.61 6.35 Laos 24 26.27 21.97 - 32.06 2.24 8.46 16 26.90 21.97 - 32.06 2.37 8.87 8 25.26 24.02 - 29.53 1.98 7.63 Vietnam 23 28.12 24.16 - 32.89 2.25 7.98 13 28.75 25.17 - 32.89 2.09 7.27 10 27.14 24.16 - 31.23 2.33 8.51 Thailand 21 26.87 23.28 - 32.96 2.76 10.03 15 28.40 24.35 - 32.96 2.41 8.45 6 24.68 23.28 - 26.65 1.37 5.51 Cambodia 13 27.49 23.42 - 31.61 2.34 8.67 4 26.58 24.83 - 27.94 1.49 11.22 9 27.49 23.42 - 31.61 2.68 9.84 Philippines 28 25.47 19.02 - 29.03 2.26 8.94 22 25.65 19.02 - 29.03 2.20 8.64 6 24.62 20.26 - 27.33 2.45 10.05 Andaman Is. 36 24.05 17.60 - 30.35 2.65 10.87 18 25.71 20.87 - 30.35 2.26 8.78 18 23.21 17.60 - 27.85 2.26 9.87 Nicobar Is. 20 27.03 23.63 - 29.91 1.63 6.12 17 27.03 23.63 - 29.91 1.56 5.85 3 25.74 23.87 - 27.62 2.65 18.04 Borneo 37 26.62 19.87 - 32.08 2.73 10.36 26 26.97 19.87 - 31.51 2.75 10.33 11 25.54 21.19 - 32.08 2.73 10.60 Indonesia 27 25.83 21.10 - 28.86 2.26 8.98 20 26.23 21.10 - 28.86 2.08 8.14 7 22.82 21.71 - 28.23 2.63 10.89 Melanesia 30 24.43 19.63 - 27.73 2.62 10.77 20 25.53 19.63 - 27.73 2.41 9.66 10 23.01 20.09 - 26.53 2.64 11.47 Micronesia 15 23.70 20.79 - 31.03 2.93 12.14 7 26.48 20.93 - 31.03 3.67 14.54 8 23.04 20.79 - 26.80 1.82 7.85 Australia 27 25.22 21.66 - 29.44 2.35 9.23 18 26.50 22.63 - 29.44 2.37 9.04 9 24.36 21.66 - 25.80 1.42 5.92 Africa 29 26.91 22.73 - 32.02 2.32 8.66 18 27.47 23.33 - 32.02 2.11 7.76 11 25.70 22.73 - 30.19 2.62 10.00 Nat. America 33 25.33 20.99 - 29.73 2.13 8.36 10 27.13 22.61 - 29.73 2.50 9.46 23 25.17 20.99 - 27.68 1.86 7.40 Caucasian 29 24.25 18.73 - 29.49 2.87 11.63 15 27.36 20.86 - 29.49 2.59 9.85 14 22.97 18.73 - 27.23 1.99 8.70 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

355 Sphenobasion-Staphylion

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (mm) (mm) (%) (mm) (mm) (%) (mm) (mm) (%)

Siberia 28 33.34 27.65 - 46.80 3.63 10.72 18 34.73 30.83 - 46.80 3.69 10.55 10 31.54 27.65 - 36.62 2.68 8.41 Mongolia 24 34.57 29.46 - 44.02 3.48 10.05 15 35.52 31.43 - 44.02 3.06 8.53 9 31.42 29.46 - 38.83 3.30 10.12 Korea 4 32.18 30.19 - 39.37 4.83 28.47 2 34.78 30.19 - 39.37 6.49 27.99 1 32.18 32.18 - 32.18 - - Ainu 3 32.79 31.37 - 34.22 2.01 10.74 1 31.37 31.37 - 31.37 - - 1 34.22 34.22 - 34.22 - - Japan 13 30.89 29.01 - 37.49 2.37 7.39 10 32.68 30.17 - 37.49 2.35 7.17 3 30.51 29.01 - 30.70 0.93 5.40 S. China 6 33.48 28.52 - 35.88 2.74 8.32 3 35.03 34.18 - 35.88 0.85 4.25 3 31.11 28.52 - 32.78 2.15 12.20 N. China 16 33.11 29.18 - 35.35 1.86 5.65 13 33.33 29.18 - 35.35 1.88 5.66 3 31.17 30.73 - 34.03 1.79 9.80 Burma 39 30.98 24.84 - 37.73 2.98 9.46 22 32.27 27.03 - 37.73 2.49 7.68 17 29.61 24.84 - 36.97 3.22 10.63 Laos 24 32.38 29.47 - 38.22 2.56 7.73 16 32.37 29.47 - 37.40 2.33 7.05 8 32.38 29.54 - 38.22 3.14 9.46 Vietnam 23 31.64 28.05 - 35.68 1.79 5.66 13 31.66 29.67 - 35.68 1.92 6.04 10 31.23 28.05 - 33.35 1.63 5.21 Thailand 21 32.82 28.56 - 35.52 2.17 6.70 15 33.52 28.73 - 35.52 2.17 6.59 6 31.17 28.56 - 32.54 1.34 4.33 Cambodia 13 34.47 30.08 - 39.18 2.99 8.86 4 36.83 30.92 - 39.18 3.53 19.63 9 32.70 30.08 - 35.47 2.30 7.03 Philippines 28 33.57 26.71 - 39.07 3.05 9.19 22 33.92 26.71 - 38.82 2.92 8.72 6 31.39 28.47 - 39.07 3.68 11.37 Andaman Is. 36 29.67 25.25 - 41.98 2.75 9.14 18 29.70 26.96 - 34.23 1.84 6.13 18 29.59 25.25 - 41.98 3.53 11.70 Nicobar Is. 20 32.68 28.92 - 36.87 2.25 6.87 17 32.68 28.92 - 36.87 2.36 7.19 3 32.15 31.30 - 33.00 1.20 6.56 Borneo 37 32.81 27.15 - 42.27 3.07 9.31 26 33.70 27.44 - 42.27 3.04 8.99 11 31.46 27.15 - 33.68 2.26 7.28 Indonesia 27 33.27 27.73 - 35.76 2.18 6.59 20 33.88 27.73 - 35.76 2.20 6.64 7 32.55 28.16 - 34.99 2.18 6.71 Melanesia 30 33.61 27.85 - 38.93 2.59 7.63 20 34.34 31.40 - 38.93 2.33 6.75 10 33.16 27.85 - 38.33 2.96 8.97 Micronesia 15 33.19 28.45 - 35.40 1.89 5.78 7 33.37 30.93 - 35.40 1.57 4.74 8 32.56 28.45 - 35.16 2.19 6.74 Australia 27 31.50 29.14 - 37.97 2.22 6.95 18 31.88 29.14 - 37.97 2.28 7.03 9 30.33 29.21 - 35.14 1.88 6.06 Africa 29 32.17 26.49 - 40.88 3.25 10.16 18 31.48 27.07 - 38.31 2.87 8.95 11 32.69 26.49 - 40.88 3.96 12.36 Nat. America 33 32.04 27.42 - 36.56 2.25 7.04 10 32.96 27.46 - 36.56 3.27 10.01 23 31.36 27.42 - 34.43 1.72 5.41 Caucasian 29 30.51 25.14 - 40.82 3.44 11.05 15 31.24 27.44 - 36.90 2.79 8.83 14 29.82 25.14 - 40.82 4.08 13.31 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

356 Palate Length (sta-ol)

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (mm) (mm) (%) (mm) (mm) (%) (mm) (mm) (%)

Siberia 28 47.11 31.67 - 55.02 5.08 10.75 18 47.96 31.67 - 55.02 6.09 12.78 10 46.10 40.51 - 50.19 2.73 5.87 Mongolia 24 43.64 35.80 - 50.04 3.94 8.88 15 45.74 39.06 - 50.04 4.01 8.84 9 43.27 35.80 - 47.31 3.49 8.14 Korea 4 42.00 41.61 - 42.35 0.37 1.75 2 41.81 41.61 - 42.00 0.27 0.97 1 42.35 42.35 - 42.35 - - Ainu 3 46.47 45.15 - 47.79 1.87 7.03 1 45.15 45.15 - 45.15 - - 1 47.79 47.79 - 47.79 - - Japan 13 45.69 40.68 - 49.50 2.65 5.84 10 45.78 41.95 - 49.50 2.04 4.44 3 41.23 40.68 - 47.58 3.84 15.55 S. China 6 42.77 39.77 - 50.68 3.94 8.99 3 45.95 42.22 - 50.68 4.24 16.04 3 41.18 39.77 - 43.32 1.79 7.54 N. China 16 43.64 40.52 - 50.58 2.86 6.41 13 44.43 41.38 - 50.58 2.92 6.50 3 43.35 40.52 - 44.46 2.03 8.30 Burma 39 45.61 35.95 - 52.49 3.59 7.92 22 45.89 43.33 - 52.49 2.30 4.94 17 43.65 35.95 - 51.58 4.28 9.79 Laos 24 45.73 37.05 - 51.67 3.66 7.97 16 45.16 37.05 - 51.67 3.68 8.04 8 45.89 39.82 - 51.41 3.89 8.40 Vietnam 23 45.07 37.92 - 51.66 3.39 7.47 13 45.57 42.12 - 50.16 2.42 5.24 10 43.48 37.92 - 51.66 4.26 9.62 Thailand 21 45.23 37.63 - 54.22 4.03 8.81 15 46.98 37.63 - 54.22 3.99 8.54 6 42.59 40.11 - 49.00 3.11 7.20 Cambodia 13 42.62 36.47 - 50.86 4.17 9.69 4 47.12 36.47 - 50.86 6.50 28.62 9 41.77 39.16 - 45.61 2.50 5.96 Philippines 28 44.44 36.33 - 52.43 4.39 9.83 22 44.46 36.33 - 52.43 4.41 9.81 6 43.52 36.75 - 49.73 4.58 10.50 Andaman Is. 36 43.96 32.51 - 52.57 3.97 9.06 18 43.39 35.07 - 49.59 4.04 9.23 18 44.24 32.51 - 52.57 4.02 9.16 Nicobar Is. 20 45.53 36.00 - 51.62 3.88 8.55 17 44.35 36.00 - 48.91 3.44 7.75 3 50.04 49.92 - 51.62 0.95 3.27 Borneo 37 45.35 37.75 - 52.26 3.12 6.89 26 45.52 37.75 - 52.26 3.28 7.24 11 44.61 41.69 - 50.68 2.84 6.29 Indonesia 27 47.55 41.57 - 52.11 2.75 5.84 20 47.30 41.57 - 52.11 2.99 6.34 7 47.55 44.21 - 50.86 2.15 4.56 Melanesia 30 48.83 43.19 - 57.53 3.51 7.18 20 49.25 43.70 - 57.53 3.52 7.11 10 47.12 43.19 - 53.45 3.31 6.96 Micronesia 15 45.31 41.96 - 50.93 3.31 7.17 7 50.01 44.02 - 50.93 2.56 5.23 8 43.88 41.96 - 45.66 1.40 3.19 Australia 27 50.89 46.75 - 55.15 2.04 3.98 18 51.25 48.64 - 55.15 1.97 3.83 9 50.36 46.75 - 53.02 1.89 3.77 Africa 29 48.96 31.38 - 56.34 4.92 10.17 18 48.50 31.38 - 53.63 5.13 10.72 11 49.24 43.44 - 56.34 4.67 9.50 Nat. America 33 46.51 41.83 - 53.05 2.40 5.17 10 48.08 44.81 - 50.48 1.95 4.09 23 45.75 41.83 - 53.05 2.41 5.24 Caucasian 29 44.63 36.18 - 51.71 3.30 7.34 15 46.62 40.36 - 51.71 2.71 5.89 14 43.75 36.18 - 50.67 3.53 8.06 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

357 Palate Breadth (enm-enm)

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (mm) (mm) (%) (mm) (mm) (%) (mm) (mm) (%)

Siberia 28 41.91 36.64 - 47.96 2.16 5.15 18 41.58 38.31 - 47.96 2.24 5.33 10 41.98 36.64 - 44.21 2.08 5.00 Mongolia 24 39.68 35.52 - 46.48 3.03 7.50 15 41.64 35.52 - 46.48 3.27 7.89 9 38.99 36.59 - 41.20 1.54 3.98 Korea 4 42.83 35.99 - 45.54 4.20 20.08 2 42.83 41.62 - 44.04 1.71 6.00 2 40.76 35.99 - 45.54 6.75 24.85 Ainu 3 40.42 35.83 - 43.12 3.68 16.20 2 41.77 40.42 - 43.12 1.91 6.84 1 35.83 35.83 - 35.83 - - Japan 13 39.46 35.67 - 45.58 2.84 7.18 10 40.28 35.67 - 45.58 2.81 6.96 3 37.48 36.16 - 37.56 0.79 3.71 S. China 6 41.31 34.84 - 42.75 3.45 8.66 3 42.46 40.71 - 42.75 1.10 4.59 3 36.10 34.84 - 41.90 3.77 17.53 N. China 16 41.54 35.12 - 47.28 3.10 7.52 13 41.95 36.72 - 47.28 2.60 6.18 3 38.32 35.12 - 39.08 2.10 9.79 Burma 39 40.00 32.29 - 45.61 3.17 7.97 22 40.65 35.49 - 45.61 3.23 8.01 17 39.99 32.29 - 44.32 3.01 7.72 Laos 24 40.81 37.33 - 44.74 1.94 4.76 16 40.86 38.45 - 44.74 1.93 4.68 8 40.33 37.33 - 41.71 1.74 4.36 Vietnam 23 40.28 34.46 - 45.84 2.95 7.29 13 40.28 34.46 - 45.84 3.43 8.46 10 40.01 36.66 - 44.06 2.37 5.86 Thailand 21 40.65 36.56 - 47.37 2.65 6.52 15 41.15 37.67 - 47.37 2.40 5.79 6 37.55 36.56 - 41.46 2.26 5.87 Cambodia 13 41.18 37.07 - 45.76 2.54 6.15 4 41.58 38.31 - 43.70 2.26 10.96 9 41.18 37.07 - 45.76 2.78 6.74 Philippines 28 40.68 33.79 - 46.33 3.26 8.04 22 40.98 34.99 - 46.33 2.93 7.11 6 37.80 33.79 - 43.48 3.55 9.29 Andaman Is. 36 36.51 33.12 - 44.01 2.48 6.71 18 37.25 33.12 - 40.77 2.55 6.84 18 36.34 33.40 - 44.01 2.44 6.66 Nicobar Is. 20 38.57 31.82 - 45.58 3.19 8.22 17 39.89 31.82 - 45.58 3.41 8.73 3 37.46 36.55 - 38.49 0.97 4.53 Borneo 37 39.85 35.50 - 46.79 2.61 6.54 26 39.87 36.82 - 46.79 2.45 6.07 11 37.72 35.50 - 44.47 2.92 7.46 Indonesia 27 40.41 34.19 - 45.08 2.29 5.70 20 40.91 37.54 - 45.08 2.17 5.35 7 40.10 34.19 - 41.81 2.52 6.42 Melanesia 30 39.40 34.05 - 47.57 3.37 8.46 20 39.65 36.36 - 47.57 3.02 7.43 10 37.24 34.05 - 43.44 3.56 9.31 Micronesia 15 38.16 35.25 - 46.07 3.29 8.34 7 42.13 37.06 - 46.07 3.63 8.72 8 37.33 35.25 - 41.43 1.95 5.15 Australia 27 40.46 32.29 - 45.31 3.35 8.37 18 41.38 34.03 - 45.31 2.84 6.88 9 36.82 32.29 - 42.16 2.70 7.25 Africa 29 40.09 35.70 - 43.69 2.30 5.83 18 38.78 35.70 - 42.89 2.39 6.14 11 40.23 36.47 - 43.69 1.90 4.69 Nat. America 33 41.45 36.68 - 45.42 2.28 5.50 10 42.61 39.17 - 45.16 1.97 4.65 23 41.18 36.68 - 45.42 2.33 5.66 Caucasian 29 39.94 34.55 - 45.80 2.73 6.77 15 40.22 37.12 - 45.80 2.67 6.55 14 39.79 34.55 - 45.10 2.86 7.16 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

358 Glabella-Lambda

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (mm) (mm) (%) (mm) (mm) (%) (mm) (mm) (%)

Siberia 28 171.64 153.26 - 187.87 8.76 5.13 18 174.68 161.19 - 187.87 7.14 4.10 10 164.56 153.26 - 180.11 8.27 5.03 Mongolia 24 167.77 156.30 - 183.58 6.67 3.97 15 170.32 156.30 - 183.58 7.23 4.26 9 164.67 157.78 - 174.54 4.73 2.86 Korea 4 172.62 153.85 - 174.51 11.42 13.68 2 173.56 172.62 - 174.51 1.33 1.15 1 153.85 153.85 - 153.85 - - Ainu 3 184.35 173.86 - 190.51 8.42 8.06 2 187.43 184.35 - 190.51 4.36 3.49 1 173.86 173.86 - 173.86 - - Japan 13 170.41 155.16 - 188.17 8.88 5.20 10 172.48 159.37 - 188.17 8.23 4.75 3 165.94 155.16 - 166.50 6.39 6.88 S. China 6 161.49 150.88 - 171.45 7.41 4.60 3 161.17 150.88 - 171.45 14.55 15.79 3 161.49 158.84 - 162.83 2.03 2.21 N. China 16 171.74 158.63 - 188.11 8.42 4.90 13 173.14 164.77 - 188.11 7.49 4.31 3 159.23 158.63 - 171.37 7.19 7.71 Burma 39 167.04 149.83 - 182.34 7.63 4.59 22 169.87 157.38 - 182.34 5.88 3.47 17 161.16 149.83 - 176.67 7.65 4.73 Laos 24 163.97 151.80 - 175.57 5.95 3.65 16 165.66 156.50 - 175.57 5.72 3.47 8 158.95 151.80 - 166.41 5.09 3.19 Vietnam 23 170.53 148.76 - 184.76 7.74 4.60 13 170.57 162.54 - 184.76 6.11 3.58 10 168.52 148.76 - 175.57 8.96 5.41 Thailand 21 163.06 152.73 - 180.59 8.03 4.90 15 163.43 157.77 - 178.98 6.44 3.89 6 155.16 152.73 - 180.59 10.71 6.70 Cambodia 13 161.84 153.76 - 179.77 8.28 5.07 4 165.30 161.84 - 179.27 7.74 9.21 9 158.27 153.76 - 179.77 8.00 4.97 Philippines 28 167.70 151.86 - 176.19 7.02 4.24 22 168.09 151.86 - 176.19 6.63 3.98 6 159.27 153.89 - 171.89 7.89 4.87 Andaman Is. 36 159.59 150.93 - 172.19 5.22 3.27 18 163.08 154.09 - 172.19 4.44 2.72 18 156.28 150.93 - 162.21 3.06 1.96 Nicobar Is. 20 174.47 159.94 - 184.75 6.76 3.89 17 175.61 159.94 - 184.75 7.31 4.21 3 173.32 172.78 - 177.27 2.45 2.46 Borneo 37 171.81 157.22 - 183.72 6.94 4.06 26 171.91 157.22 - 183.27 6.46 3.76 11 167.10 158.34 - 183.72 7.73 4.59 Indonesia 27 167.89 149.57 - 184.88 9.34 5.61 20 168.64 149.57 - 184.88 8.89 5.27 7 159.31 149.57 - 172.84 8.31 5.18 Melanesia 30 174.64 158.15 - 191.22 8.04 4.61 20 176.19 162.41 - 191.22 7.83 4.43 10 172.04 158.15 - 181.21 6.84 4.02 Micronesia 15 171.74 163.37 - 182.41 5.86 3.39 7 175.95 170.83 - 181.58 4.48 2.55 8 171.01 163.37 - 182.41 5.89 3.46 Australia 27 176.45 166.67 - 193.23 7.20 4.05 18 180.11 166.67 - 193.23 7.04 3.90 9 172.35 167.49 - 175.46 2.60 1.51 Africa 29 177.09 161.07 - 190.31 6.42 3.62 18 180.08 169.29 - 190.31 5.96 3.32 11 173.62 161.07 - 178.68 5.15 2.97 Nat. America 33 171.03 152.84 - 181.96 6.40 3.77 10 174.86 152.84 - 181.96 8.94 5.18 23 170.47 158.52 - 174.20 4.60 2.73 Caucasian 29 174.38 162.07 - 193.08 7.56 4.31 15 178.50 168.06 - 193.08 7.03 3.93 14 171.60 162.07 - 183.98 6.69 3.89 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

359 Appendix 2 Kruskal Wallis results for Linear Data: p-values* for post-hoc non-parametric group comparisons (Bonferonni corrected)

Interorbital Breadth (mf-mf): Pooled Sex H: 86.60; p: 2.89E-10

NA Sib Mon Jap SChi NChi Bur Lao Viet Thai Cam Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA -<0.001<0.001--<0.0010.042-0.008------<0.001- Sib ------<0.001- Mon -0.004------0.0050.003--0.020-0.0480.001<0.0010.003 Jap 0.003 - - 0.016 - - 0.027 0.001 0.001 - - 0.008 0.016 0.009 <0.001 <0.001 0.003 SChi 0.025 0.004 0.016 0.046 0.008 - - - 0.026 - - 0.032 - - - - NChi ------<0.001- Bur 0.044 - - 0.039 0.003 <0.001 - - 0.007 0.031 0.023 <0.001 <0.001 0.001 Lao ------0.044<0.001- Viet ------<0.001- Thai --0.032-----0.014<0.0010.018 Cam ------<0.001- Phi ------<0.001- And ------<0.001- Nic -----<0.001- Bor - - - - <0.001 - Indo - - - <0.001 - Mel - - <0.001 - Mic - <0.001 - Aus <0.001 - Af <0.001 Cauc *significant p-values (p 0.05) only presented here

360 Interorbital Breadth: Male-Only H: 64.69; p: 3.50E-7

NA Sib Mon Jap Nchi Bur Lao Viet Thai Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA-0.0170.003------0.029- Sib 0.0330.015------0.001- Mon - - - 0.013 0.012 - 0.015 0.004 - 0.017 0.014 0.007 - <0.001 <0.001 0.001 Jap - - 0.003 0.008 - 0.002 <0.001 - 0.017 0.002 0.001 0.007 <0.001 <0.001 0.002 Nchi ------0.017<0.001- Bur - - - - 0.031 - - - 0.040 - 0.002 <0.001 0.009 Lao ------0.018<0.001- Viet ------0.004- Thai ------0.006<0.0010.011 Phi ------0.049<0.001- And ------<0.001- Nic ----0.010<0.0010.026 Bor ----0.002- Indo - - 0.045 <0.001 - Mel --<0.001- Mic -0.023- Aus 0.035 - Af 0.045 Cauc *significant p-values (p 0.05) only presented here

361 Interorbital Breadth: Female-Only H: 48.18; p:4.46E-5

NA Sib Mon Bur Lao Viet Thai Cam Phi And Bor Indo Mel Mic Aus Af Cauc NA - 0.049 <0.001 0.014 0.007 0.014 - - - 0.001 - 0.004 - 0.036 0.027 - Sib ------0.018- Mon ------0.005- Bur - - - 0.046 0.013 0.008 - - - 0.039 - <0.001 0.045 Lao ------0.002- Viet ------<0.001- Thai ------0.002- Cam ------0.010- Phi - 0.018 - 0.045 - - 0.008 - And 0.010 - - - - 0.004 - Bor ----<0.001- Indo - - - 0.019 - Mel - - <0.001 - Mic - 0.003 - Aus 0.001 - Af 0.003 Cauc *significant p-values (p 0.05) only presented here

362 Bi-frontomalare Orbitale: Pooled Sex H: 120.70; p: 2.15E-116

NA Sib Mon Jap SChi NChi Bur Lao Viet Thai Cam Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA 0.037 - 0.020 - - 0.018 - - 0.018 - - <0.001 0.031 0.042 - - - 0.003 0.008 - Sib 0.034 0.002 - 0.016 <0.001 0.002 0.003 <0.001 - 0.003 <0.001 0.001 <0.001 0.007 0.039 - - - 0.006 Mon ------<0.001-----0.0030.005- Jap ------<0.001-----<0.001<0.001- SChi ------0.009------NChi ------<0.001-----0.0020.005- Bur - - - - - <0.001 - - - 0.031 - <0.001 <0.001 - Lao ----<0.001-----<0.001<0.001- Viet ---<0.001-----<0.001<0.001- Thai --<0.001-----<0.001<0.001- Cam -<0.001-----0.0120.028- Phi <0.001-----<0.001<0.001- And <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 Nic ----<0.001<0.001- Bor - - - <0.001 <0.001 - Indo - - <0.001 <0.001 - Mel - 0.003 0.007 - Mic 0.038 - - Aus - <0.001 Af <0.001 Cauc *significant p-values (p 0.05) only presented here

363 Bi-frontomalare Temporale: Pooled Sex H: 114.20; p: 3.36E-15

NA Sib Mon Jap SChi NChi Bur Lao Viet Thai Cam Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA - - 0.010 - - 0.006 - - 0.016 - - <0.001 0.021 0.037 - - - - 0.005 0.012 Sib 0.043 0.004 - 0.017 <0.001 0.016 0.017 0.003 0.012 0.006 <0.001 0.004 0.007 0.043 - - - - 0.002 Mon ------<0.001-----0.0160.002- Jap 0.048------0.015-----0.001<0.001- SChi -0.0430.046-0.044--0.001------NChi ------0.003-----0.006<0.001- Bur -----<0.001-----<0.001<0.001- Lao ----<0.001-----0.021<0.001- Viet ---<0.001-----0.008<0.001- Thai --<0.001-----<0.001<0.001- Cam -0.001-----0.007<0.001- Phi <0.001-----0.002<0.001- And <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 Nic ----0.004<0.001- Bor - - - 0.001 <0.001 - Indo - - 0.018 <0.001 - Mel - 0.017 0.002 - Mic --- Aus - <0.001 Af <0.001 Cauc *significant p-values (p 0.05) only presented here

364 Bi-frontomalare Orbitale: Male-Only H: 95.96; p: 1.21E-12

NA Sib Mon Jap Nchi Bur Lao Viet Thai Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA0.042------<0.001-----0.005-- Sib 0.045 0.003 0.008 0.004 <0.001 0.026 0.001 0.001 <0.001 <0.001 0.006 0.005 - - - - - Mon ------<0.001-----0.0030.041- Jap ------0.002---0.017 0.017 <0.001 0.003 - Nchi -----<0.001-----<0.0010.019- Bur ----<0.001-----<0.0010.007- Lao - - - <0.001 - - - 0.010 0.008 <0.001 <0.001 - Viet --<0.0010.033----<0.0010.048- Thai - <0.001 - - - 0.015 0.007 <0.001 <0.001 - Phi <0.001 - - - 0.038 0.050 <0.001 0.003 - And <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 Nic - - <0.001 0.003 <0.001 <0.001 - Bor - - - <0.001 0.011 - Indo - - <0.001 0.005 - Mel - <0.001 - - Mic --- Aus -0.006 Af - Cauc *significant p-values (p 0.05) only presented here

365 Bi-frontmalare Orbitale: Female-Only H: 75.16; p:1.23E-9

NA Sib Mon Bur Lao Viet Thai Cam Phi And Bor Indo Mel Mic Aus Af Cauc NA - - <0.001 - 0.005 0.001 - 0.007 <0.001 <0.001 0.006 0.002 - - - 0.018 Sib - 0.004 - 0.009 0.002 - 0.015 <0.001 <0.001 0.036 0.017 - - - - Mon ------0.006 - - - - - 0.028 - Bur 0.039 ------0.003 <0.001 - Lao - 0.008 - 0.033 <0.001 0.006 - - - - 0.013 - Viet - - - 0.008 - - - - 0.037 0.001 - Thai ------0.006 0.001 - Cam - 0.003 0.023 - - - - 0.040 - Phi - - - - - 0.029 0.008 - And - - 0.003 0.004 <0.001 <0.001 0.007 Bor - - - <0.001 <0.001 - Indo - - 0.034 0.007 - Mel - 0.013 0.001 - Mic - 0.029 - Aus -- Af 0.007 Cauc *significant p-values (p 0.05) only presented here

366 Bi-zygomaxillare (ZMB): Pooled Sex H:119.80; p: 3.13E-16

NA Sib Mon Jap SChi NChi Bur Lao Viet Thai Cam Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA ------<0.001---0.002-<0.001-<0.001 Sib ------<0.001---0.025-<0.001-<0.001 Mon ------<0.001---0.007-<0.001-<0.001 Jap ------<0.001---0.038-<0.001-<0.001 SChi ------<0.0010.039--0.010-0.001-<0.001 NChi ------<0.001-----0.002-<0.001 Bur -----<0.001-----0.0030.049<0.001 Lao - - - - <0.001 - - - 0.002 - <0.001 - <0.001 Viet - - - <0.001 - - - 0.005 - <0.001 - <0.001 Thai - - <0.001 - - - 0.001 - <0.001 - <0.001 Cam - <0.001 - - - 0.032 - <0.001 - <0.001 Phi <0.001-----0.0020.009<0.001 And <0.001 <0.001 <0.001 0.041 <0.001 - <0.001 - Nic ----0.0020.014<0.001 Bor - 0.009 - <0.001 - <0.001 Indo 0.025 - <0.001 - <0.001 Mel 0.005 - <0.001 0.016 Mic <0.001 - <0.001 Aus <0.001 - Af <0.001 Cauc *significant p-values (p 0.05) only presented here

367

Bi-zygomaxillare (ZMB): Male-Only H: 78.92; p:1.32E-9

NA Sib Mon Jap Nchi Bur Lao Viet Thai Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA------<0.001---0.040-0.001-<0.001 Sib ------<0.001---0.020-<0.001-<0.001 Mon ------<0.001---0.017-<0.001-<0.001 Jap ---0.038--0.002-----0.003-<0.001 Nchi -----0.002---0.034-0.003-0.001 Bur ----0.005-----0.005-0.003 Lao - - - <0.001 0.035 - - 0.009 - <0.001 - <0.001 Viet - 0.043 <0.001 0.010 - - 0.002 - <0.001 - <0.001 Thai - <0.001 0.014 - - 0.003 - <0.001 - <0.001 Phi 0.011----0.0260.015-0.001 And 0.024 <0.001 0.002 - <0.001 - <0.001 - Nic - - - 0.006 0.040 - 0.004 Bor - 0.025 - <0.001 - <0.001 Indo - - 0.002 - <0.001 Mel 0.005 - 0.025 0.021 Mic <0.001 - <0.001 Aus <0.001 - Af <0.001 Cauc *significant p-values (p 0.05) only presented here

368

Bi-zygomaxillare (ZMB): Female-Only H: 68.95; p:1.52E-8

NA Sib Mon Bur Lao Viet Thai Cam Phi And Bor Indo Mel Mic Aus Af Cauc NA 0.024 - 0.011 - - - - 0.009 <0.001 0.033 - <0.001 - <0.001 - <0.001 Sib ------0.020 - - - - 0.030 0.008 0.043 Mon ------0.003 - - 0.025 - 0.010 0.048 0.018 Bur - - - - - 0.024 - - - - 0.024 0.004 0.045 Lao - - - - 0.001 - - 0.015 - 0.005 - 0.010 Viet - - - 0.008 - - 0.045 - 0.016 0.027 0.033 Thai - - 0.012 - - - - 0.011 - 0.043 Cam - 0.001 - - 0.013 - 0.005 - 0.004 Phi - - - - 0.024 - 0.006 - And 0.004 0.023 - 0.001 - <0.001 - Bor - - - 0.010 0.007 0.028 Indo - - 0.011 0.007 0.033 Mel 0.046 - 0.001 - Mic <0.001 0.023 0.004 Aus <0.001 - Af <0.001 Cauc *significant p-values (p 0.05) only presented here

369 Bi-inferior Zygomatic Breadth: Pooled Sex H: 86.69; p:2.79E-10

NA Sib Mon Jap SChi NChi Bur Lao Viet Thai Cam Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA 0.006------<0.001<0.001------0.023 Sib - 0.027 - - <0.001 0.001 - 0.012 0.041 0.040 <0.001 <0.001 0.002 0.014 <0.001 0.020 0.032 - <0.001 Mon - - - 0.023 0.043 - - - - <0.001 0.001 - - 0.038 - - - 0.011 Jap ------<0.0010.003------0.043 SChi ------0.0020.015------NChi ------0.0020.032------Bur -----<0.001------Lao ----<0.0010.006------Viet ---<0.001<0.001------0.029 Thai --<0.0010.001------0.032 Cam -<0.0010.005------Phi <0.0010.003------And 0.037 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 Nic 0.014 0.009 - - 0.004 <0.001 - Bor ------Indo ----- Mel --0.025- Mic --- Aus -- Af 0.004 Cauc *significant p-values (p 0.05) only presented here

370 Bi-inferior Zygomatic: Male-Only H: 93.82; p:2.95E-12

NA Sib Mon Jap Nchi Bur Lao Viet Thai Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA0.013------<0.0010.002------0.037 Sib - <0.001 0.043 <0.001 <0.001 0.043 <0.001 0.004 <0.001 <0.001 <0.001 0.003 <0.001 0.048 0.021 <0.001 <0.001 Mon 0.008 - 0.002 <0.001 - 0.004 0.025 <0.001 <0.001 0.002 0.012 0.002 - - 0.006 <0.001 Jap ------<0.001<0.001------0.026 Nchi -----<0.0010.005------0.050 Bur ----<0.0010.006------Lao ---<0.0010.002------Viet --<0.001<0.001------0.009 Thai -<0.001<0.001------0.005 Phi <0.001<0.001------0.028 And - <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 0.001 Nic 0.002 0.001 0.049 0.002 0.001 <0.001 0.031 Bor ------Indo ----0.049 Mel 0.037--- Mic --0.012 Aus -0.048 Af 0.025 Cauc *significant p-values (p 0.05) only presented here

371 Bi-alare: Pooled Sex H: 184.90; p: 1.04E-28

NA Sib Mon Jap SChi NChi Bur Lao Viet Thai Cam Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA <0.001 <0.001 - 0.014 0.002 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 - - <0.001 <0.001 <0.001 Sib -<0.001-0.006------<0.001<0.001<0.001-- Mon 0.001-0.005------<0.001<0.0010.002-- Jap 0.048 - <0.001 <0.001 <0.001 <0.001 <0.001 0.001 <0.001 <0.001 <0.001 0.007 - - - 0.005 0.004 SChi ------0.0170.027--- NChi <0.001 0.003 <0.001 0.001 <0.001 0.050 <0.001 <0.001 <0.001 0.022 0.003 - - - 0.031 Bur ------<0.001<0.001<0.0010.027- Lao ------<0.001<0.001<0.001-- Viet - - - 0.045 - - - <0.001 <0.001 <0.001 0.028 - Thai ------<0.001 <0.001 <0.001 0.045 - Cam 0.011 - - - - <0.001 <0.001 <0.001 0.007 - Phi 0.002 0.012 0.017 - <0.001 <0.001 0.021 - - And - - 0.016 <0.001 <0.001 <0.001 <0.001 0.032 Nic - - <0.001 <0.001 <0.001 0.006 - Bor - <0.001 <0.001 <0.001 0.015 - Indo <0.001 0.001 0.015 - - Mel - <0.001 <0.001 <0.001 Mic 0.019 <0.001 <0.001 Aus 0.040 0.019 Af - Cauc *significant p-values (p 0.05) only presented here

372 Bi-alare: Male-Only H: 96.55; p:9.43E-13

NA Sib Mon Jap Nchi Bur Lao Viet Thai Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA <0.001 <0.001 - 0.014 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 - - 0.004 0.003 0.005 Sib -<0.0010.011------<0.0010.0010.002-- Mon 0.0070.043------<0.0010.0140.034-- Jap - <0.001 <0.001 <0.001 0.003 0.002 0.001 <0.001 <0.001 0.008 - - - 0.023 0.038 Nchi 0.008 0.005 0.003 0.007 0.039 0.009 0.002 0.002 0.041 0.033 - - - - Bur ------<0.0010.0020.002-- Lao ------<0.0010.002<0.0010.021- Viet ------<0.0010.002 <0.001 0.011 - Thai -----<0.0010.0070.005-- Phi ----<0.0010.0050.018-- And - - - <0.001 0.004 0.004 - - Nic - 0.040 <0.001 0.003 <0.001 0.005 0.019 Bor - <0.001 0.001 <0.001 0.028 - Indo <0.001 0.036 0.029 - - Mel - 0.011 0.003 0.004 Mic -0.020- Aus -- Af - Cauc *significant p-values (p 0.05) only presented here

373 Bi-alare: Female-Only H:96.13; p:1.83E-13

NA Sib Mon Bur Lao Viet Thai Cam Phi And Bor Indo Mel Mic Aus Af Cauc NA <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 - - <0.001 <0.001 <0.001 Sib ------0.001 0.019 - - - Mon - - - - - 0.039 - - - <0.001 0.002 0.017 - - Bur - - - - 0.046 0.023 - - <0.001 <0.001 0.011 - - Lao ------0.003 0.010 - - - Viet - - - 0.006 - - <0.001 0.001 0.041 - - Thai - - - - - 0.001 0.004 - - - Cam - - - - <0.001 0.001 0.009 - - Phi 0.002 0.031 - 0.001 0.017 - - - And - - <0.001 <0.001 <0.001 0.008 - Bor - <0.001 <0.001 0.015 - - Indo 0.003 0.015 - - - Mel - 0.002 <0.001 <0.001 Mic 0.043 0.004 0.003 Aus -- Af - Cauc *significant p-values (p 0.05) only presented here

374 Bistephanic Breadth (STB): Pooled Sex H: 98.85; p:2.02E-12

NA Sib Mon Jap SChi NChi Bur Lao Viet Thai Cam Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA 0.001 <0.001 - 0.049 - 0.002 <0.001 0.004 <0.001 0.009 <0.001 - - <0.001 <0.001 - 0.022 - 0.012 <0.001 Sib ------0.002---<0.001-<0.001-- Mon ------<0.0010.035--<0.001-<0.001-- Jap -----0.019-----0.046----0.036 SChi ------0.012-0.038-- NChi ------0.035---- Bur -----0.004---<0.001-<0.001-- Lao - - - - <0.001 0.028 - - <0.001 - <0.001 - - Viet ---0.005---<0.001-0.001-- Thai - - <0.001 0.004 - - <0.001 - <0.001 0.045 - Cam - 0.022 - - - 0.002 - 0.005 - - Phi <0.001 0.020 - - <0.001 - <0.001 - - And - <0.001 <0.001 - 0.031 - 0.011 <0.001 Nic 0.022 0.013 0.009 - - - 0.015 Bor - <0.001 - <0.001 - - Indo <0.001 - <0.001 - - Mel 0.001 - <0.001 <0.001 Mic 0.006 - - Aus 0.002 <0.001 Af 0.040 Cauc *significant p-values (p 0.05) only presented here

375

Bistephanic Breadth (STB): Male-Only H: 57.03; p:6.11E-6

NA Sib Mon Jap Nchi Bur Lao Viet Thai Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA - - - - 0.016 0.029 0.006 0.007 0.024 - - 0.025 0.002 - 0.013 - - 0.016 Sib ------0.023---- Mon ------0.007-0.007-- Jap ------Nchi ------Bur ------<0.001-0.001-- Lao ------0.004-0.008-- Viet - - 0.010 0.012 - - <0.001 - <0.001 - - Thai - 0.011 0.014 - - <0.001 - <0.001 - - Phi - 0.035 - - <0.001 - 0.001 - - And - - 0.006 0.039 0.043 - - 0.031 Nic - 0.006 - 0.026 - - 0.031 Bor - <0.001 - <0.001 - - Indo <0.001 - <0.001 0.037 - Mel 0.003 - 0.039 0.002 Mic 0.003 - - Aus -0.003 Af - Cauc *significant p-values (p 0.05) only presented here

376 Bistephanic Breadth (STB): Female-Only H: 58.46; p:9.49E-7

NA Sib Mon Bur Lao Viet Thai Cam Phi And Bor Indo Mel Mic Aus Af Cauc NA 0.002 0.003 - 0.007 - 0.012 - - - 0.045 - - - - 0.043 0.009 Sib - - - 0.031 - - - <0.001 - - 0.002 0.029 0.002 - - Mon - - 0.037 - - - <0.001 - - <0.001 0.039 0.004 - - Bur - - - - - 0.018 - - 0.006 - 0.024 - - Lao 0.037 - - - <0.001 - - <0.001 0.031 0.002 - - Viet 0.045 - - - - - 0.031 - - - - Thai - - 0.002 - - 0.002 0.024 0.003 - - Cam - 0.022 - - 0.008 - 0.022 - - Phi 0.010 - - 0.004 - 0.011 - - And 0.003 - - - - 0.004 0.001 Bor - 0.002 - 0.004 - - Indo ----- Mel 0.015 - 0.003 0.005 Mic 0.039 - - Aus 0.005 0.003 Af - Cauc *significant p-values (p 0.05) only presented here

377 Bipterionic Breadth: Pooled Sex H:150.40; p:5.18E-22

NA Sib Mon Jap SChi NChi Bur Lao Viet Thai Cam Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA <0.001<0.001------<0.001<0.001--<0.001-<0.001-0.010 Sib - 0.015 0.020 - <0.001 0.001 0.008 0.003 <0.001 <0.001 <0.001 <0.001 <0.001 0.002 <0.001 <0.001 <0.001 <0.001 - Mon 0.013 0.031 - <0.001 <0.001 0.005 0.002 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 - Jap ------0.0030.007--0.012-0.005-- SChi ------0.0390.008--0.032-0.011-- NChi ------<0.0010.015--0.007-0.002-- Bur -----<0.0010.001--<0.001-<0.001-0.009 Lao - - - - <0.001 <0.001 - - 0.002 - <0.001 - 0.012 Viet - - - <0.001 0.004 - - 0.002 - <0.001 - - Thai - - <0.001 <0.001 - - <0.001 0.040 <0.001 - 0.032 Cam ----0.017----0.002 Phi <0.001 0.002 - - 0.004 - <0.001 - 0.003 And - <0.001 <0.001 - - - <0.001 <0.001 Nic <0.001 <0.001 - - - 0.005 <0.001 Bor - <0.001 - <0.001 - 0.003 Indo <0.001 0.019 <0.001 - 0.033 Mel - - 0.003 <0.001 Mic - - 0.003 Aus <0.001 <0.001 Af <0.001 Cauc *significant p-values (p 0.05) only presented here

378

Bipterionic Breadth: Male-Only H: 111.20; p:1.90E-15

NA Sib Mon Jap Nchi Bur Lao Viet Thai Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA0.0050.003------0.0230.005--0.033-0.009-0.008 Sib - - - 0.022 0.022 - 0.010 <0.001 <0.001 <0.001 <0.001 0.005 <0.001 - <0.001 <0.001 - Mon 0.038 - 0.008 0.007 - 0.006 <0.001 <0.001 <0.001 <0.001 0.001 <0.001 - <0.001 <0.001 - Jap ------0.0030.002--0.007-0.005-0.033 Nchi -----0.0020.007--0.010-0.005-- Bur - - - - 0.002 <0.001 - - 0.001 - 0.001 - 0.023 Lao - - - 0.019 0.003 - - 0.019 - 0.014 - 0.013 Viet - 0.018 <0.001 <0.001 - - <0.001 - <0.001 0.015 - Thai - <0.001 <0.001 - - <0.001 - <0.001 - 0.009 Phi -0.005----0.027-0.004 And - <0.001 <0.001 - 0.032 - 0.017 <0.001 Nic <0.001 <0.001 - 0.009 - 0.031 <0.001 Bor - <0.001 - <0.001 - 0.001 Indo <0.001 - <0.001 - 0.004 Mel 0.029 - - <0.001 Mic 0.020 - - Aus 0.024 <0.001 Af <0.001 Cauc *significant p-values (p 0.05) only presented here

379 Bipterionic Breadth: Female-Only H: 71.16; p:6.24E-9

NA Sib Mon Bur Lao Viet Thai Cam Phi And Bor Indo Mel Mic Aus Af Cauc NA - - 0.049 - - - 0.049 - <0.001 0.036 - <0.001 0.003 <0.001 - - Sib - 0.017 0.026 0.021 - 0.025 - <0.001 0.015 - 0.001 0.005 0.001 0.045 - Mon 0.007 0.005 0.013 0.039 0.013 - <0.001 0.004 - <0.001 0.001 <0.001 0.037 - Bur - - - - - 0.022 - - 0.033 - 0.002 - 0.025 Lao - - - - 0.017 - - 0.009 0.031 0.001 - 0.029 Viet ------Thai - - 0.021 - - - - 0.004 - - Cam ------0.018 Phi 0.033 - - - - 0.011 - - And 0.041 0.010 - - - 0.007 <0.001 Bor - - - 0.004 - 0.008 Indo 0.013 - 0.003 - - Mel - - 0.006 <0.001 Mic 0.018 0.023 <0.001 Aus 0.003 <0.001 Af - Cauc *significant p-values (p 0.05) only presented here

380 Biauricular Breadth (AUB): Pooled Sex H: 185.40; p:8.56E-29

NA Sib Mon Jap SChi NChi Bur Lao Viet Thai Cam Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA 0.009 <0.001 - - - 0.034 - - - - - <0.001 <0.001 - - 0.002 - <0.001 <0.001 0.010 Sib - 0.032 - - <0.001 0.005 - - - 0.018 <0.001 <0.001 <0.001 0.021 <0.001 0.004 <0.001 <0.001 <0.001 Mon 0.007 0.041 0.034 <0.001 <0.001 0.011 0.004 0.014 0.001 <0.001 <0.001 <0.001 0.002 <0.001 0.001 <0.001 <0.001 <0.001 Jap ------<0.001<0.001--0.018-0.0020.001- SChi ------<0.0010.003--0.044-0.0180.008- NChi 0.027 - - - - - <0.001 <0.001 - - 0.004 - 0.001 <0.001 0.017 Bur - 0.021 0.013 - - <0.001 0.008 - 0.035 - - - - - Lao - - - - <0.001 <0.001 - - 0.004 - <0.001 <0.001 0.015 Viet - - - <0.001 <0.001 - - 0.001 - <0.001 <0.001 0.009 Thai - - <0.001 <0.001 0.031 - <0.001 - <0.001 <0.001 0.003 Cam - <0.001 <0.001 - - 0.011 - 0.002 0.001 0.041 Phi <0.001 <0.001 - - 0.004 - <0.001 <0.001 0.019 And <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 Nic <0.001 <0.001 0.015 - - 0.017 0.010 Bor - - - 0.015 0.010 - Indo 0.002 - <0.001 <0.001 0.013 Mel ---- Mic --- Aus -- Af - Cauc *significant p-values (p 0.05) only presented here

381 Biporionic Breadth: Pooled Sex H: 167.30; p:2.93E-25

NA Sib Mon Jap SChi NChi Bur Lao Viet Thai Cam Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA -<0.001------<0.001<0.001--0.0120.0450.0060.001- Sib - - - - 0.009 0.004 - - - - <0.001 <0.001 0.006 - <0.001 0.002 <0.001 <0.001 0.002 Mon 0.007 - - <0.001 <0.001 0.003 0.012 0.029 0.002 <0.001 <0.001 <0.001 0.005 <0.001 <0.001 <0.001 <0.001 <0.001 Jap ------<0.0010.001-----0.036- SChi ------<0.0010.005-----0.046- NChi ------<0.001<0.001--0.0090.0230.0040.007- Bur -----<0.001<0.001------Lao - 0.043 - - <0.001 <0.001 - - - - - 0.049 - Viet - - - <0.001 <0.001 - - 0.028 0.045 0.021 0.008 - Thai - - <0.001 <0.001 - - 0.002 0.016 0.001 <0.001 0.021 Cam - <0.001 <0.001 - - 0.027 - 0.022 0.009 - Phi <0.001 <0.001 - - 0.016 0.031 0.004 0.007 - And <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 Nic <0.001 <0.001 0.002 - 0.003 <0.001 <0.001 Bor ------Indo 0.003 0.024 0.001 0.001 0.043 Mel ---- Mic --- Aus -- Af - Cauc *significant p-values (p 0.05) only presented here

382

Biauricular (AUB): Male-Only H: 146.0; p:4.36E-22

NA Sib Mon Jap Nchi Bur Lao Viet Thai Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA-0.005------<0.001<0.001----0.0110.001- Sib - 0.006 - <0.001 0.001 - 0.018 0.002 <0.001 <0.001 <0.001 0.012 <0.001 - <0.001 <0.001 0.002 Mon 0.002 0.007 <0.001 <0.001 0.008 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 0.029 <0.001 <0.001 <0.001 Jap ------<0.001<0.001--0.029-0.0060.001- Nchi 0.050 - - - - <0.001 <0.001 - - 0.002 - 0.002 <0.001 - Bur --0.040-<0.001<0.001-----0.006- Lao - - - <0.001 <0.001 - - 0.032 - 0.003 <0.001 - Viet - - <0.001 <0.001 - - 0.005 - 0.001 <0.001 - Thai - <0.001 <0.001 0.050 - <0.001 - <0.001 <0.001 0.038 Phi <0.001 <0.001 - - 0.018 - 0.003 <0.001 - And 0.006 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 Nic <0.001 <0.001 0.002 <0.001 0.020 0.033 0.002 Bor 0.049 - - 0.031 0.002 - Indo 0.001 - <0.001 <0.001 - Mel 0.016 - 0.048 - Mic 0.012 0.002 - Aus -- Af 0.029 Cauc *significant p-values (p 0.05) only presented here

383 Biporionic Breadth: Male-Only H: 135.20; p:5.38E-20

NA Sib Mon Jap Nchi Bur Lao Viet Thai Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA-0.004------<0.001<0.001--0.041-0.0200.003- Sib - - - 0.006 0.002 - - 0.023 <0.001 <0.001 0.005 - <0.001 - <0.001 <0.001 0.029 Mon 0.001 0.013 <0.001 <0.001 0.003 0.002 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 0.017 <0.001 <0.001 0.001 Jap ------<0.001<0.001--0.029-0.0370.004- Nchi - 0.037 - - - <0.001 <0.001 - - 0.005 - 0.002 <0.001 - Bur - - - - <0.001 <0.001 - 0.035 - - - - - Lao - - - <0.001 <0.001 - 0.029 - - - 0.016 - Viet - - <0.001 <0.001 - - 0.023 - 0.039 0.004 - Thai - <0.001 <0.001 - - 0.003 - 0.003 <0.001 - Phi <0.001<0.001----0.0310.003- And 0.006 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 Nic <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 Bor ----0.010- Indo 0.001 - <0.001 <0.001 - Mel ---- Mic -0.020- Aus -- Af 0.009 Cauc *significant p-values (p 0.05) only presented here

384 Biauricular Breadth (AUB): Female-Only H: 77.38; p:4.93E-10

NA Sib Mon Bur Lao Viet Thai Cam Phi And Bor Indo Mel Mic Aus Af Cauc NA - - 0.007 - - - - - <0.001 0.010 0.044 0.003 0.003 <0.001 0.017 0.002 Sib - 0.017 - - - - - <0.001 0.018 0.028 0.003 0.005 0.002 0.015 0.011 Mon 0.007 - - - - - <0.001 0.006 0.011 0.002 0.005 0.001 0.003 0.004 Bur - - - 0.046 - <0.001 ------Lao - - - - <0.001 - - 0.029 0.031 0.006 - - Viet - - - <0.001 - - 0.025 0.024 0.006 - - Thai - - <0.001 - - 0.034 0.045 0.016 - - Cam - <0.001 0.048 - 0.030 0.018 0.017 - 0.035 Phi <0.001 - - - - 0.039 - - And 0.001 0.020 0.007 0.043 0.002 <0.001 <0.001 Bor ------Indo ----- Mel - - 0.049 - Mic - 0.043 - Aus 0.033 - Af - Cauc *significant p-values (p 0.05) only presented here

385 Biporionic Breadth: Female-Only H: 71.72; p:4.97E-9

NA Sib Mon Bur Lao Viet Thai Cam Phi And Bor Indo Mel Mic Aus Af Cauc NA - - - 0.050 - - - - <0.001 0.017 0.035 0.005 0.004 0.003 0.025 0.006 Sib ------<0.001 0.032 - 0.007 0.004 0.003 - 0.015 Mon - - - - - 0.039 <0.001 0.008 0.034 0.003 0.003 <0.001 0.048 0.005 Bur - - - - - <0.001 - - - 0.044 - - - Lao ----<0.001----0.049-- Viet - - - <0.001 - - 0.045 0.015 0.018 - - Thai --<0.001----0.029-- Cam - <0.001 0.048 - 0.030 0.049 0.034 - 0.035 Phi <0.001 - - - 0.045 - - - And <0.001 0.020 0.006 0.018 <0.001 <0.001 <0.001 Bor ------Indo ----- Mel ---- Mic --- Aus 0.019 - Af - Cauc *significant p-values (p 0.05) only presented here

386 Bimastoidale: Pooled Sex H: 145.20; p: 5.14E-21

NA Sib Mon Jap SChi NChi Bur Lao Viet Thai Cam Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA 0.0470.003------<0.001<0.001--0.045-0.018-- Sib - 0.048 - - 0.006 0.034 - - - 0.003 <0.001 <0.001 0.020 0.019 <0.001 0.033 <0.001 <0.001 0.019 Mon 0.007 - - <0.001 0.002 0.033 0.011 0.025 <0.001 <0.001 <0.001 0.001 <0.001 <0.001 0.003 <0.001 <0.001 0.001 Jap ------<0.0010.005------SChi ------<0.0010.014------NChi ------<0.001 <0.001 - - 0.024 - 0.006 0.019 - Bur -----<0.0010.002------Lao - - - - <0.001 <0.001 - - 0.039 - 0.014 - - Viet - - 0.020 <0.001 <0.001 - - <0.001 - <0.001 <0.001 - Thai - - <0.001 <0.001 - - 0.026 - 0.005 0.028 - Cam -<0.0010.008------Phi <0.0010.007------And <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 Nic <0.001 0.001 0.015 0.003 0.040 0.007 0.004 Bor - - - 0.033 - - Indo ----- Mel ---- Mic --- Aus -- Af - Cauc *significant p-values (p 0.05) only presented here

387 Bimastoidale: Male-Only H: 101.60; p:1.11E-13

NA Sib Mon Jap Nchi Bur Lao Viet Thai Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA-0.040------<0.0010.001------Sib - 0.015 - 0.019 0.040 - - 0.008 <0.001 <0.001 - 0.030 0.004 - 0.003 0.002 - Mon 0.003 - 0.003 0.004 - 0.038 0.002 <0.001 <0.001 0.013 0.003 <0.001 - <0.001 <0.001 - Jap ------<0.0010.014------Nchi ----0.042<0.001<0.001--0.013-0.0050.007- Bur ----<0.001<0.001------Lao ---<0.001<0.001------Viet - - <0.001 <0.001 - - 0.010 - 0.008 0.009 - Thai -<0.001<0.001----0.045-- Phi <0.0010.018------And 0.003 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 Nic <0.001 0.001 0.017 <0.001 0.022 0.013 <0.001 Bor - - - 0.040 0.040 - Indo ----- Mel 0.050 - - 0.039 Mic 0.027 0.023 - Aus -0.013 Af 0.022 Cauc *significant p-values (p 0.05) only presented here

388 Bimastoidale: Female-Only H: 65.64; p: 5.72E-8

NA Sib Mon Bur Lao Viet Thai Cam Phi And Bor Indo Mel Mic Aus Af Cauc NA ------<0.001 - - - - 0.025 - 0.031 Sib ------<0.001 0.010 - 0.014 0.046 0.001 0.022 0.028 Mon 0.027 - - - - - <0.001 0.033 0.044 0.013 0.049 0.006 0.019 0.018 Bur -----<0.001------Lao ----<0.001----0.049-- Viet - - - <0.001 0.010 - 0.013 0.049 0.001 0.019 0.035 Thai --<0.001----0.011-- Cam - <0.001 ------Phi <0.001------And <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 0.001 Bor ------Indo ----- Mel ---- Mic --- Aus -- Af - Cauc *significant p-values (p 0.05) only presented here

389 Basion-Prosthion (BPL): Pooled Sex H: 142.50; p:1.66E-20

NA Sib Mon Jap SChi NChi Bur Lao Viet Thai Cam Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA - - - - - 0.001 - - - - - <0.001 - - - 0.001 - <0.001 0.030 <0.001 Sib 0.023 - 0.034 0.013 <0.001 - 0.010 - 0.042 - <0.001 - 0.012 - 0.031 - 0.009 - <0.001 Mon ------0.005---<0.001-<0.001<0.0010.002 Jap - 0.038 0.025 - - - - - <0.001 - - - 0.021 - 0.002 - <0.001 SChi ------0.004-0.0030.008- NChi ------0.021 - - 0.049 <0.001 - <0.001 0.002 0.011 Bur ------0.030-0.007<0.0010.007<0.001<0.0010.037 Lao - - - - <0.001 - - - <0.001 - <0.001 0.005 <0.001 Viet - - - 0.008 - - - <0.001 - <0.001 <0.001 0.002 Thai - - 0.004 - - - <0.001 - <0.001 0.007 <0.001 Cam - - - - - 0.001 - <0.001 0.006 0.036 Phi 0.004 - - - <0.001 - <0.001 0.009 0.001 And <0.001 0.003 <0.001 <0.001 <0.001 <0.001 <0.001 - Nic - - 0.003 - <0.001 0.035 <0.001 Bor - <0.001 - <0.001 <0.001 <0.001 Indo <0.001 - <0.001 0.017 <0.001 Mel - - - <0.001 Mic 0.020 - <0.001 Aus - <0.001 Af <0.001 Cauc *significant p-values (p 0.05) only presented here

390

Basion-Prosthion (BPL): Male-Only H:89.71; p:1.63E-11

NA Sib Mon Jap Nchi Bur Lao Viet Thai Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA---0.032-----<0.001-0.042---0.042-0.002 Sib 0.049 - 0.009 0.038 0.022 0.036 - - <0.001 - 0.020 - - - - - <0.001 Mon ------<0.0010.014<0.001-- Jap 0.038-----0.001---0.0100.0360.004-0.001 Nchi -----0.044---<0.0010.002<0.0010.029- Bur ------<0.0010.009<0.0010.0330.049 Lao ------<0.0010.007<0.0010.0370.011 Viet - - 0.039 - - - <0.001 0.009 <0.001 0.029 0.038 Thai - 0.003 - - - 0.002 0.034 0.001 - 0.002 Phi 0.027 - - - <0.001 0.012 <0.001 - 0.029 And 0.042 0.039 0.005 <0.001 <0.001 <0.001 <0.001 - Nic - - <0.001 0.011 <0.001 0.039 0.038 Bor - <0.001 0.007 <0.001 0.026 0.024 Indo <0.001 0.016 <0.001 - 0.002 Mel ---<0.001 Mic --<0.001 Aus -<0.001 Af <0.001 Cauc *significant p-values (p 0.05) only presented here

391 Basion-Prosthion (BPL): Female-Only H: 76.17; p:8.10E-10

NA Sib Mon Bur Lao Viet Thai Cam Phi And Bor Indo Mel Mic Aus Af Cauc NA - - <0.001 - - 0.009 0.026 - <0.001 - - - - 0.007 0.030 <0.001 Sib - 0.002 - - 0.026 - - 0.002 - - - - 0.025 0.045 <0.001 Mon 0.020 - - - - - 0.033 - 0.044 0.045 - 0.001 0.003 0.009 Bur 0.011 ------0.004 <0.001 0.025 <0.001 <0.001 - Lao - - - - 0.013 ------0.005 Viet ------0.034 - 0.008 0.010 0.050 Thai - - - - 0.038 0.015 - 0.003 0.004 - Cam - - - 0.044 0.013 - 0.005 0.004 - Phi ------And - 0.002 <0.001 0.028 <0.001 <0.001 - Bor - 0.038 - 0.004 0.007 0.031 Indo ----0.002 Mel - - - <0.001 Mic 0.002 0.019 0.010 Aus - <0.001 Af <0.001 Cauc *significant p-values (p 0.05) only presented here

392 Inferior Malar Length (IML): Pooled Sex H: 92.83; p:2.36E-11

NA Sib Mon Jap SChi NChi Bur Lao Viet Thai Cam Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA ------0.002-<0.0010.005- Sib -0.021--0.008--0.031-0.0320.0470.036----<0.001-0.040 Mon ------0.001-<0.0010.003- Jap 0.016---0.043------<0.0010.013<0.0010.002- SChi -0.029------0.028-0.038 NChi ------0.011-<0.0010.015- Bur -0.011-----0.046-<0.0010.008<0.001<0.001- Lao ------0.012-<0.0010.029- Viet 0.028-0.031------<0.001-- Thai ------<0.001 0.022 <0.001 <0.001 - Cam ------<0.001-- Phi - - - - <0.001 0.023 <0.001 0.001 - And - - - <0.001 0.029 <0.001 <0.001 - Nic - - <0.001 0.037 <0.001 0.003 - Bor - 0.011 - <0.001 0.020 - Indo 0.007 - <0.001 0.023 - Mel - 0.010 - <0.001 Mic 0.002 - 0.023 Aus 0.004 <0.001 Af <0.001 Cauc *significant p-values (p 0.05) only presented here

393 Inferior Malar Length (IML): Male-Only H: 80.71; p:6.43E-10

NA Sib Mon Jap Nchi Bur Lao Viet Thai Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA------0.0050.036<0.001 - - Sib -0.014-0.017--0.0450.0270.0450.024----0.005-0.047 Mon ------0.002-<0.001-- Jap ------<0.0010.004<0.0010.005- Nchi ------0.0020.031<0.0010.014- Bur ------<0.0010.007<0.0010.004- Lao ------0.0010.025<0.0010.029- Viet ------0.0040.027<0.001-- Thai -----<0.0010.014<0.0010.005- Phi ----<0.0010.006<0.0010.006- And - - - <0.001 0.008 <0.001 0.015 - Nic - - <0.001 0.007 <0.001 0.008 - Bor - 0.001 0.018 <0.001 0.025 - Indo 0.007 0.050 <0.001 - - Mel - 0.034 - <0.001 Mic 0.049 - 0.007 Aus <0.001 <0.001 Af 0.010 Cauc *significant p-values (p 0.05) only presented here

394 Inferior Malar Length (IML): Female-Only H: 42.61; p:0.0003

NA Sib Mon Bur Lao Viet Thai Cam Phi And Bor Indo Mel Mic Aus Af Cauc NA - 0.005 0.043 - - 0.017 - 0.046 - - 0.005 - - 0.015 - - Sib ------Mon - - 0.013 - - - 0.008 0.030 - 0.030 0.030 0.002 0.006 - Bur - 0.008 ------0.004 0.021 - Lao ------0.043----- Viet 0.004 - 0.015 - - 0.013 - - - - - Thai - - 0.015 - - - 0.045 0.008 0.014 - Cam ------0.042-- Phi - - - - - 0.011 0.027 - And - 0.005 - - 0.006 - - Bor 0.028 - - - - - Indo 0.022 0.024 0.003 0.009 - Mel ---- Mic 0.049 - - Aus - 0.004 Af 0.045 Cauc *significant p-values (p 0.05) only presented here

395 Nasion-Lambda: Pooled Sex H: 160.60; p:5.86E-24

NA Sib Mon Jap SChi NChi Bur Lao Viet Thai Cam Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA - - - - - 0.039 <0.001 - 0.001 0.004 0.032 <0.001 - - 0.043 - - 0.025 <0.001 0.008 Sib ----0.027<0.001-0.0020.0040.020<0.001------0.002- Mon ----<0.001-0.0040.008-<0.001-----0.004<0.0010.002 Jap ---0.004-0.0210.031-<0.001------0.0020.044 SChi ------0.0270.0100.022 NChi 0.046 <0.001 - 0.003 0.007 0.026 <0.001 - - 0.043 - - - 0.004 - Bur 0.027 - - - - <0.001 0.007 0.036 - 0.005 0.028 <0.001 <0.001 <0.001 Lao 0.002 - - 0.030 - <0.001 <0.001 - <0.001 <0.001 <0.001 <0.001 <0.001 Viet 0.0150.018-<0.001-----0.009<0.0010.009 Thai - - - <0.001 0.001 - <0.001 0.001 <0.001 <0.001 <0.001 Cam - - 0.002 0.002 - 0.001 0.004 <0.001 <0.001 <0.001 Phi <0.001 0.003 0.023 - 0.003 0.040 <0.001 <0.001 <0.001 And <0.001 <0.001 0.002 <0.001 <0.001 <0.001 <0.001 <0.001 Nic - 0.017 - - - 0.002 - Bor - - - 0.039 <0.001 0.016 Indo 0.010 0.049 <0.001 <0.001 <0.001 Mel - - 0.003 - Mic - 0.004 - Aus 0.048 - Af - Cauc *significant p-values (p 0.05) only presented here

396

Glabella-Lambda: Pooled Sex H: 173.80; p: 1.55E-26

NA Sib Mon Jap SChi NChi Bur Lao Viet Thai Cam Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA - - - 0.025 - 0.038 <0.001 - 0.004 0.006 0.029 <0.001 0.025 - - 0.025 - <0.001 <0.001 0.005 Sib --0.025-0.0440.002-0.0060.0170.035<0.001-----0.0060.005- Mon - - - - 0.012 - 0.035 0.029 - <0.001 0.007 - - 0.003 0.030 <0.001 <0.001 <0.001 Jap ---0.009-0.0280.027-<0.001-----0.0190.019- SChi 0.029--0.048----0.0070.018-0.0070.0090.0020.0020.003 NChi 0.042 <0.001 - 0.007 0.008 0.023 <0.001 - - 0.046 - - 0.029 0.017 - Bur - - - - - <0.001 <0.001 0.016 - <0.001 0.005 <0.001 <0.001 <0.001 Lao 0.008 - - - 0.043 <0.001 <0.001 - <0.001 <0.001 <0.001 <0.001 <0.001 Viet 0.027 0.032 - <0.001 0.014 - - 0.012 - <0.001 <0.001 0.004 Thai - - - <0.001 0.001 - <0.001 0.001 <0.001 <0.001 <0.001 Cam - - 0.001 0.002 - <0.001 0.002 <0.001 <0.001 <0.001 Phi <0.001 <0.001 0.008 - <0.001 0.004 <0.001 <0.001 <0.001 And <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 Nic -0.003----- Bor 0.044 - - <0.001 <0.001 0.019 Indo 0.002 0.016 <0.001 <0.001 <0.001 Mel ---- Mic 0.038 0.040 - Aus -- Af - Cauc *significant p-values (p 0.05) only presented here

397 Nasion-Lambda: Male-Only H: 106.30; p:1.56E-14

NA Sib Mon Jap Nchi Bur Lao Viet Thai Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA -----0.011-0.0120.0360.003------0.014- Sib - - - 0.043 <0.001 - <0.001 0.002 <0.001 - - 0.023 - - - 0.018 - Mon ---0.006-0.013-0.004-----0.007<0.0010.016 Jap --0.007-0.018-0.003------0.007- Nchi - <0.001 - 0.001 0.010 <0.001 - - 0.031 - - - 0.008 - Bur 0.011-0.013-0.003-----<0.001<0.0010.002 Lao 0.010 - - - 0.002 0.001 - <0.001 0.003 <0.001 <0.001 <0.001 Viet 0.024-0.005-----0.006<0.0010.013 Thai - - 0.006 0.006 - <0.001 0.002 <0.001 <0.001 <0.001 Phi 0.038 0.026 0.040 - 0.003 0.018 <0.001 <0.001 <0.001 And <0.001 <0.001 - <0.001 0.001 <0.001 <0.001 <0.001 Nic ----0.022<0.0010.019 Bor - - - 0.006 <0.001 0.008 Indo 0.021 - 0.002 <0.001 0.002 Mel --0.011- Mic -0.037- Aus -- Af - Cauc *significant p-values (p 0.05) only presented here

398 Glabella-Lambda: Male-Only H: 114.0; p:5.62E-16

NA Sib Mon Jap Nchi Bur Lao Viet Thai Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA -----0.014-0.0350.0160.004-----0.0260.042- Sib - - - 0.035 <0.001 - 0.002 0.003 <0.001 - - 0.039 - - 0.012 0.018 - Mon - - - 0.038 - - - 0.005 - - - 0.017 0.045 <0.001 <0.001 0.003 Jap --0.011-0.0280.0440.003-----0.0260.035- Nchi - 0.003 - 0.004 0.012 <0.001 - - 0.049 - - 0.021 0.026 - Bur 0.028 - 0.043 - 0.001 0.043 - - 0.004 0.015 <0.001 <0.001 <0.001 Lao 0.030 - - - <0.001 0.001 - <0.001 <0.001 <0.001 <0.001 <0.001 Viet 0.024 - 0.001 - - - 0.026 0.048 <0.001 <0.001 0.005 Thai - - 0.004 0.004 - <0.001 0.005 <0.001 <0.001 <0.001 Phi 0.027 0.004 0.013 - <0.001 0.002 <0.001 <0.001 <0.001 And <0.001 <0.001 0.019 <0.001 <0.001 <0.001 <0.001 <0.001 Nic ----0.0100.020- Bor - 0.044 - <0.001 <0.001 0.006 Indo 0.010 0.025 <0.001 <0.001 0.001 Mel ---- Mic --- Aus -- Af - Cauc *significant p-values (p 0.05) only presented here

399 Nasion-Lambda: Female-Only H: 75.28; p:1.16E-9

NA Sib Mon Bur Lao Viet Thai Cam Phi And Bor Indo Mel Mic Aus Af Cauc NA - - 0.005 <0.001 - 0.022 0.004 0.049 <0.001 - 0.035 - - - 0.003 - Sib ------0.005 - - - - - 0.010 0.033 Mon - 0.009 - - - - <0.001 - - - - - 0.003 0.015 Bur - - - - - 0.015 - - - 0.033 0.013 <0.001 0.001 Lao - - - - - 0.007 - 0.007 0.005 <0.001 <0.001 <0.001 Viet - - - 0.007 - - - - - 0.012 - Thai ------0.045 0.039 0.031 0.023 Cam - - 0.023 - 0.037 0.018 0.010 0.004 0.003 Phi ------0.004 0.015 And <0.001 - <0.001 <0.001 <0.001 <0.001 <0.001 Bor - - - - 0.030 - Indo - - - 0.004 0.015 Mel - - 0.027 - Mic - 0.043 - Aus 0.010 - Af - Cauc *significant p-values (p 0.05) only presented here

400 Glabella-Lambda: Female-Only H:78.26 ; p:3.41E-10

NA Sib Mon Bur Lao Viet Thai Cam Phi And Bor Indo Mel Mic Aus Af Cauc NA - - 0.005 <0.001 - 0.022 0.003 - <0.001 - 0.024 - - 0.049 0.008 - Sib ------0.005 - - - - 0.020 0.022 0.033 Mon - 0.049 - - - - <0.001 - - - - 0.008 0.006 0.021 Bur - - - - - 0.013 - - 0.017 0.016 0.002 <0.001 0.001 Lao - - - - - 0.015 - 0.005 0.005 <0.001 <0.001 <0.001 Viet - - - 0.007 - - - - - 0.018 - Thai - - - - - 0.045 0.033 0.039 0.039 0.015 Cam - - 0.019 - 0.016 0.011 0.006 0.006 0.003 Phi - - - - - 0.029 0.010 0.023 And <0.001 - <0.001 <0.001 <0.001 <0.001 <0.001 Bor - - - - 0.042 - Indo 0.036 - 0.008 0.003 0.012 Mel ---- Mic --- Aus -- Af - Cauc *significant p-values (p 0.05) only presented here

401 Parietal Length (PAC): Male-Only H: 77.04; p:2.81E-9

NA Sib Mon Jap Nchi Bur Lao Viet Thai Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA ------0.029-- Sib ------0.038-0.0260.019---<0.0010.011- Mon 0.049------0.0020.003-0.009-<0.0010.0020.025 Jap --0.033-0.0120.016------Nchi -0.033-0.0240.025------Bur 0.043-0.0130.007-0.036----0.0010.033- Lao 0.033 - - - <0.001 <0.001 - 0.004 0.035 <0.001 <0.001 0.008 Viet 0.0080.011-0.040----0.0020.043- Thai - 0.047 <0.001 <0.001 - 0.002 0.041 <0.001 <0.001 0.001 Phi - <0.001 <0.001 - <0.001 0.023 <0.001 <0.001 0.002 And <0.001 0.005 - 0.023 - <0.001 <0.001 0.038 Nic -0.005----- Bor 0.028 - - - - - Indo 0.036 - <0.001 0.005 0.034 Mel ---- Mic --- Aus -- Af - Cauc *significant p-values (p 0.05) only presented here

402 Parietal Length (PAC): Female-Only H: 58.39; p:9.74E-7

NA Sib Mon Bur Lao Viet Thai Cam Phi And Bor Indo Mel Mic Aus Af Cauc NA - - - 0.050 - - 0.049 - <0.001 - - - 0.016 - - - Sib ------0.010 - 0.014 0.009 0.030 0.038 - Mon ------0.037 0.015 - 0.010 0.005 0.010 0.033 - Bur - - - - - 0.011 0.011 - 0.006 0.004 0.005 0.016 0.028 Lao - - - - - 0.009 - 0.009 0.007 0.011 0.023 0.022 Viet ------Thai - - - 0.031 - - 0.017 - - 0.043 Cam - - 0.015 - 0.030 0.024 0.034 - 0.035 Phi 0.012 - - - 0.024 - - - And <0.001 - <0.001 <0.001 <0.001 <0.001 <0.001 Bor 0.024 - - - - - Indo 0.022 0.007 0.020 - - Mel ---- Mic --- Aus -- Af - Cauc *significant p-values (p 0.05) only presented here

403 Palate Length: Pooled Sex H: 109.40; p: 2.56E-14

NA Sib Mon Jap SChi NChi Bur Lao Viet Thai Cam Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA - - - - 0.022 - - - - 0.004 - 0.001 - - - 0.008 - <0.001 0.045 0.043 Sib 0.037 - - 0.029 - - - - 0.004 0.033 0.002 - 0.028 - - - 0.001 - 0.030 Mon ------0.023<0.001-<0.001<0.001- Jap ------0.004-<0.0010.022- SChi ------0.0380.007-<0.0010.017- NChi ------0.007<0.001-<0.0010.002- Bur ------0.042<0.001-<0.0010.003- Lao - - 0.030 - 0.026 - - - 0.010 - <0.001 0.028 - Viet ------0.002-<0.0010.005- Thai ------0.008 - <0.001 0.017 - Cam - - - - 0.003 <0.001 - <0.001 <0.001 - Phi - - - 0.027 <0.001 - <0.001 0.002 - And - - <0.001 <0.001 - <0.001 <0.001 - Nic - - 0.006 - <0.001 0.014 - Bor 0.018 <0.001 - <0.001 0.001 - Indo - - <0.001 - 0.009 Mel 0.037 0.010 - <0.001 Mic <0.001 0.047 - Aus 0.018 <0.001 Af 0.002 Cauc *significant p-values (p 0.05) only presented here

404

Palate Length: Male-Only H: 75.21; p:5.82E-9

NA Sib Mon Jap Nchi Bur Lao Viet Thai Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA ---0.043-----0.0140.0150.022---<0.001-- Sib ------0.028------Mon ------0.0070.035<0.001-- Jap ------0.0080.034<0.001-- Nchi ------0.0010.017<0.0010.021- Bur ----0.022---0.0060.021<0.001-- Lao ------0.010-<0.0010.045- Viet ------0.0090.032<0.001-- Thai - 0.045 - - - 0.048 - <0.001 - - Phi ----0.0020.047<0.0010.017- And - - 0.015 <0.001 0.004 <0.001 0.003 - Nic - 0.040 <0.001 0.005 <0.001 0.007 - Bor - <0.001 0.017 <0.001 0.013 - Indo 0.036 - <0.001 - - Mel - 0.036 - 0.008 Mic 0.021 - 0.039 Aus 0.008 <0.001 Af - Cauc *significant p-values (p 0.05) only presented here

405 Palate Length: Female-Only H: 56.38; p:2.10E-6

NA Sib Mon Bur Lao Viet Thai Cam Phi And Bor Indo Mel Mic Aus Af Cauc NA - 0.011 0.036 - - 0.029 <0.001 - 0.033 - - - 0.016 <0.001 - 0.027 Sib 0.030 - - - - 0.002 - 0.011 - - - 0.017 0.005 - 0.021 Mon ------0.008 0.017 - <0.001 0.005 - Bur ------0.033 0.031 - 0.001 0.010 - Lao --0.020------Viet ------0.008 0.022 - Thai - - - - 0.038 0.039 - 0.004 0.008 - Cam - - 0.033 0.004 0.003 - <0.001 0.002 - Phi -----0.011-- And - 0.013 0.013 - <0.001 0.006 - Bor - - - 0.002 0.042 - Indo - 0.011 0.030 - 0.012 Mel 0.011 - - 0.023 Mic 0.001 0.014 - Aus - <0.001 Af 0.007 Cauc *significant p-values (p 0.05) only presented here

406 Foramen Magnum Length (FOL): Pooled Sex H: 74.44; p: 3.37E-8

NA Sib Mon Jap SChi NChi Bur Lao Viet Thai Cam Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA <0.001---0.048------<0.001------0.010- Sib - 0.015 - - <0.001 <0.001 - 0.002 - 0.001 <0.001 0.002 0.014 <0.001 0.006 0.007 0.005 - 0.009 Mon ------<0.001--0.037----- Jap ------0.002------SChi ------0.004------NChi - 0.012 - 0.040 - - <0.001 0.029 - 0.010 - - - - - Bur -----<0.001------0.018- Lao 0.022 - - - 0.001 - 0.047 - - - - 0.005 - Viet - - - <0.001 0.033 - 0.005 - - - - - Thai --<0.001------0.029- Cam -<0.001------Phi 0.003------0.014- And 0.029 <0.001 0.020 <0.001 0.021 <0.001 <0.001 <0.001 Nic -----0.012- Bor 0.011 - - - - - Indo - - - 0.001 0.030 Mel - - 0.047 - Mic --- Aus -- Af - Cauc *significant p-values (p 0.05) only presented here

407 Foramen Magnum Length (FOL): Male-Only H: 58.33; p:3.80E-6

NA Sib Mon Jap Nchi Bur Lao Viet Thai Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA 0.005------0.018------Sib 0.041 0.005 0.040 <0.001 <0.001 0.021 <0.001 <0.001 <0.001 <0.001 0.002 <0.001 <0.001 0.017 0.002 0.018 0.006 Mon - - - 0.026 - - - 0.002 0.031 - 0.021 - - - - - Jap ------0.026------Nchi - 0.004 - 0.012 0.017 <0.001 0.004 - 0.007 0.021 - - - - Bur ----0.005------Lao ---0.031------Viet - - 0.002 0.033 - 0.015 - - - - - Thai -0.008------Phi ------And - 0.002 - 0.044 - 0.008 <0.001 <0.001 Nic 0.024 - - - - 0.049 0.015 Bor 0.028 - - - - - Indo - - - 0.014 0.011 Mel ---- Mic --- Aus -- Af - Cauc *significant p-values (p 0.05) only presented here

408 Prosthion-Nasospinale: Pooled sex H:119.80; p: 3.09E-16

NA Sib Mon Jap SChi NChi Bur Lao Viet Thai Cam Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA - - 0.002 0.003 - <0.001 0.005 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 0.002 - Sib - 0.007 0.017 - <0.001 0.021 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 0.004 <0.001 <0.001 0.005 0.009 - Mon - - - 0.042 - 0.015 0.019 0.005 0.003 <0.001 0.023 0.016 - 0.001 0.002 - - - Jap ------0.004------SChi ------NChi - - - - 0.013 0.033 <0.001 - - - 0.005 0.008 - - - Bur -----<0.001------0.027 Lao - - 0.023 0.043 <0.001 - - - 0.003 0.005 - - - Viet ---0.003------0.007 Thai --0.005------0.010 Cam - - - - 0.033 - - 0.019 0.049 0.010 Phi 0.004 - - 0.035 - - 0.024 - 0.005 And 0.044 <0.001 <0.001 0.022 - <0.001 <0.001 <0.001 Nic ------0.015 Bor -----0.002 Indo 0.023 0.005 - - - Mel - 0.009 - <0.001 Mic 0.005 0.040 <0.001 Aus -- Af - Cauc *significant p-values (p 0.05) only presented here

409 Prosthion-Nasospinale: Male-Only H: 64.74; p: 3.43E-7

NA Sib Mon Jap Nchi Bur Lao Viet Thai Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA ------0.0140.003<0.0010.0110.005-0.0040.003--- Sib - 0.018 - 0.008 0.017 - 0.002 <0.001 <0.001 0.002 <0.001 0.013 <0.001 0.001 0.037 0.033 - Mon ------0.010<0.0010.0290.038-0.0210.011--- Jap ------0.004------Nchi ----0.046<0.001----0.014--- Bur ----<0.001----0.032--- Lao ---<0.001----0.049--- Viet -0.021<0.001----0.013--- Thai -0.007------0.014 Phi 0.010-----0.017-0.006 And - 0.002 0.003 0.007 - <0.001 0.008 <0.001 Nic ------0.027 Bor -----0.004 Indo -0.043--- Mel ---0.003 Mic 0.010 - 0.004 Aus -- Af - Cauc *significant p-values (p 0.05) only presented here

410 Prosthion-Nasospinale: Female-Only H: 65.49; p:6.06E-8

NA Sib Mon Bur Lao Viet Thai Cam Phi And Bor Indo Mel Mic Aus Af Cauc NA - - <0.001 - <0.001 0.022 <0.001 0.007 <0.001 <0.001 0.008 <0.001 <0.001 <0.001 0.017 - Sib - 0.015 - 0.005 - 0.006 - <0.001 0.038 - 0.002 0.015 - - - Mon - - - - 0.022 - 0.002 - - 0.010 - - - - Bur 0.029------Lao 0.007 - 0.024 - <0.001 - - 0.002 0.024 0.049 - - Viet - - - - - 0.036 - - - - 0.040 Thai ------Cam ------Phi ------And 0.048 <0.001 - - 0.011 0.014 0.003 Bor ------Indo 0.010 - - - - Mel - 0.045 0.045 0.015 Mic --- Aus -- Af - Cauc *significant p-values (p 0.05) only presented here

411 Prosthion-Nasion (NPH): Pooled Sex H:131.90; p: 1.79E-18

NA Sib Mon Jap SChi NChi Bur Lao Viet Thai Cam Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA 0.032------0.0060.001<0.0010.001<0.001-0.0020.0010.0020.0150.036 Sib - 0.026 0.049 - <0.001 0.005 0.001 0.003 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 Mon - - - 0.006 0.036 0.007 0.014 0.001 <0.001 <0.001 <0.001 <0.001 0.008 <0.001 <0.001 <0.001 0.002 0.002 Jap ------0.048<0.0010.0450.036--0.038--- SChi ------0.008------NChi 0.010 - 0.033 0.033 0.006 <0.001 <0.001 0.001 <0.001 0.022 0.002 0.004 0.003 0.010 0.014 Bur -----<0.0010.038------Lao - - 0.018 0.005 <0.001 0.004 0.003 - 0.021 0.009 0.021 - - Viet - - - <0.001 0.028 0.037 - - 0.044 - - - Thai --<0.001------Cam -<0.001------Phi <0.001 - - 0.040 - - - - - And 0.004 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 Nic -0.033----- Bor 0.049 - - - - - Indo ----- Mel ---- Mic --- Aus -- Af - Cauc *significant p-values (p 0.05) only presented here

412

Prosthion-Nasion (NPH): Male-Only H:95.10; p: 1.73E-12

NA Sib Mon Jap Nchi Bur Lao Viet Thai Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA ------0.009<0.0010.0120.017-0.023-0.033-- Sib - 0.020 - <0.001 0.001 0.006 0.005 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 0.004 <0.001 <0.001 0.005 Mon - - 0.012 0.010 0.024 0.028 <0.001 <0.001 <0.001 <0.001 0.004 <0.001 0.011 0.001 0.005 0.020 Jap -----0.019<0.0010.0250.025------Nchi 0.033 0.027 - - <0.001 <0.001 0.002 0.002 0.013 0.004 0.039 0.012 0.020 - Bur ---0.029<0.0010.023------Lao --0.043<0.0010.032------Viet - 0.013 <0.001 0.019 0.013 - 0.019 - - - - Thai 0.020 <0.001 0.019 0.036 ------Phi 0.001------And 0.042 <0.001 <0.001 <0.001 0.005 <0.001 <0.001 <0.001 Nic ------0.034 Bor ------Indo ----- Mel ---- Mic --- Aus -- Af - Cauc *significant p-values (p 0.05) only presented here

413 Prosthion-Nasion (NPH): Female-Only H: 58.71; p: 8.61E-7

NA Sib Mon Bur Lao Viet Thai Cam Phi And Bor Indo Mel Mic Aus Af Cauc NA - - 0.038 - 0.007 0.022 0.011 0.043 <0.001 0.002 - 0.010 0.002 <0.001 0.039 0.016 Sib - - - 0.045 0.026 0.025 - <0.001 0.004 - 0.014 0.009 0.003 - 0.038 Mon - - 0.045 - - - <0.001 0.033 - 0.045 0.018 0.008 - 0.047 Bur -----0.001------Lao - 0.033 0.039 - <0.001 0.019 - 0.029 0.018 0.008 - - Viet ---0.003------Thai ------Cam -0.005------Phi ------And 0.011 0.008 - 0.012 - 0.002 0.002 Bor ------Indo ----- Mel ---- Mic --- Aus -- Af - Cauc *significant p-values (p 0.05) only presented here

414 Prosthion-Glabella: Pooled Sex H: 143.0; p: 1.13E-20

NA Sib Mon Jap SChi NChi Bur Lao Viet Thai Cam Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA -0.005------0.035<0.001<0.0010.001<0.0010.008<0.0010.004<0.0010.004<0.001 Sib - 0.017 0.047 - <0.001 - 0.003 0.001 0.002 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 Mon 0.004 0.019 - <0.001 0.012 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 Jap - 0.030 - - - - - 0.042 <0.001 - - - 0.044 - 0.012 - - SChi ------0.049------NChi 0.005 - 0.010 0.009 0.006 <0.001 <0.001 <0.001 <0.001 0.002 <0.001 0.001 <0.001 0.001 <0.001 Bur - - - - 0.031 <0.001 - - - 0.018 - 0.005 - - Lao 0.047 - 0.025 <0.001 <0.001 0.002 <0.001 0.008 <0.001 0.002 <0.001 0.006 <0.001 Viet - - 0.023 <0.001 - - - 0.014 0.049 0.004 - - Thai --<0.001-----0.027-- Cam -0.005------Phi 0.028------And - <0.001 <0.001 0.010 0.006 0.042 <0.001 0.001 Nic ------Bor ------Indo - - 0.020 - - Mel ---- Mic --- Aus -- Af - Cauc *significant p-values (p 0.05) only presented here

415 Prosthion-Glabella: Male-Only H: 101.80; p:1.05E-13

NA Sib Mon Jap Nchi Bur Lao Viet Thai Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA -0.006------0.0090.0010.0370.027-0.010-0.010-- Sib - 0.018 - 0.003 0.017 0.012 0.002 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 0.007 <0.001 0.001 <0.001 Mon 0.003 - <0.001 0.001 0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 0.002 <0.001 <0.001 <0.001 Jap 0.044----0.016<0.001---0.033-0.014-- Nchi 0.016 - - 0.017 <0.001 <0.001 0.001 <0.001 0.001 <0.001 0.017 <0.001 0.004 0.001 Bur - - - 0.021 <0.001 - - - 0.033 - 0.013 - - Lao - - 0.002 <0.001 0.032 0.015 - 0.004 - 0.002 - - Viet - 0.005 <0.001 - 0.024 - 0.005 - 0.004 - - Thai 0.029<0.001-----0.027-- Phi 0.049------And - 0.004 0.002 0.003 0.014 0.028 0.005 0.003 Nic ------Bor ------Indo ----- Mel ---- Mic --- Aus -- Af - Cauc *significant p-values (p 0.05) only presented here

416 Prosthion-Glabella: Female-Only H: 58.98; p:7.77E-7

NA Sib Mon Bur Lao Viet Thai Cam Phi And Bor Indo Mel Mic Aus Af Cauc NA - - 0.027 - 0.002 0.015 0.024 - <0.001 0.002 - 0.002 0.004 <0.001 0.010 <0.001 Sib ------<0.001 0.027 - 0.017 0.029 0.005 - 0.033 Mon - - 0.025 0.039 - - <0.001 0.040 - 0.013 0.018 0.008 0.033 0.013 Bur 0.021----0.012------Lao 0.002 0.017 0.018 - <0.001 0.004 - 0.004 0.005 <0.001 0.006 0.002 Viet ------Thai ------Cam ------Phi ------And -----0.029- Bor ------Indo ----- Mel ---- Mic --- Aus -- Af - Cauc *significant p-values (p 0.05) only presented here

417

Nasion-Nasospinale: Pooled Sex H: 98.32; p: 2.514E-12

NA Sib Mon Jap SChi NChi Bur Lao Viet Thai Cam Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA 0.008 0.002 0.038 - 0.002 - - - - 0.043 - <0.001 - - 0.048 - - - - - Sib ------0.020<0.0010.0150.002---<0.0010.004<0.001 Mon - - - 0.049 - 0.024 - - 0.004 <0.001 0.003 <0.001 - - - <0.001 <0.001 <0.001 Jap ------<0.0010.0360.014---0.0020.0150.004 SChi ------0.008------NChi 0.032 - 0.027 - - 0.002 <0.001 0.008 <0.001 - 0.035 - <0.001 0.001 <0.001 Bur -----<0.001-----0.016-0.004 Lao - - - - <0.001 - 0.025 - - - 0.003 0.043 0.001 Viet ---<0.001-----0.016-0.005 Thai --<0.001-----0.009-0.007 Cam - <0.001 - 0.016 - - - 0.003 0.014 0.003 Phi <0.001------And <0.001 <0.001 <0.001 <0.001 <0.001 0.010 <0.001 - Nic ------Bor 0.027 - - - - - Indo - - 0.004 0.037 0.002 Mel -0.027-0.009 Mic 0.029 - 0.015 Aus -- Af - Cauc *significant p-values (p 0.05) only presented here

418 Nasion-Nasospinale: Male-Only H: 74.21; p:8.67E-9

NA Sib Mon Jap Nchi Bur Lao Viet Thai Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA -0.025-0.044-----0.015------Sib - - - - 0.022 - - 0.004 <0.001 0.002 0.002 0.042 0.022 - <0.001 0.002 0.003 Mon - - 0.032 0.007 0.008 - 0.001 <0.001 <0.001 <0.001 0.022 0.013 - <0.001 <0.001 0.001 Jap -----0.024<0.0010.0060.009---0.0020.0120.016 Nchi ----0.003<0.0010.0080.002---<0.0010.0040.006 Bur ----0.002------Lao ---<0.001------Viet --<0.001-----0.032-- Thai 0.010 <0.001 0.011 0.007 - - - <0.001 0.005 0.007 Phi 0.009------And 0.020 0.019 <0.001 <0.001 0.005 - 0.022 - Nic ------Bor ------Indo - - 0.039 - - Mel ---- Mic 0.020 - - Aus -- Af - Cauc *significant p-values (p 0.05) only presented here

419 Appendix 3 Summary Statistics for Angular Measurements Naion Angle (NAA)

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (deg.) (deg.) (%) (deg.) (deg.) (%) (deg.) (deg.) (%)

Siberia 28 67.22 58.89 - 71.48 2.91 4.34 18 66.91 60.40 - 71.48 2.69 4.02 10 68.41 58.89 - 71.14 3.37 4.99 Mongolia 24 66.17 59.00 - 71.95 3.58 5.39 16 65.69 59.00 - 71.95 3.95 5.98 8 67.68 63.20 - 70.92 2.76 4.11 Korea 4 61.39 57.83 - 70.55 5.45 17.35 2 61.39 61.02 - 61.76 0.52 1.28 2 64.19 57.83 - 70.55 9.00 21.02 Ainu 3 67.60 67.53 - 74.97 4.27 10.68 2 71.28 67.60 - 74.97 5.21 10.97 1 67.53 67.53 - 67.53 - - Japan 13 68.10 65.65 - 69.50 1.10 1.62 10 67.32 65.65 - 69.12 0.99 1.47 3 69.33 68.14 - 69.50 0.74 1.87 S. China 6 69.17 61.02 - 71.23 3.76 5.51 3 70.04 67.75 - 71.23 1.77 4.44 3 68.30 61.02 - 70.70 5.04 13.23 N. China 16 65.45 58.50 - 71.57 3.45 5.30 13 65.38 58.50 - 70.45 3.27 5.06 3 66.48 63.17 - 71.57 4.23 11.04 Burma 39 65.69 59.10 - 74.04 3.73 5.65 22 66.89 59.10 - 74.04 3.63 5.46 17 64.65 59.54 - 72.37 3.81 5.84 Laos 24 68.97 62.32 - 73.88 3.26 4.75 16 67.82 62.32 - 73.88 3.71 5.45 8 69.66 66.95 - 73.39 1.91 2.74 Vietnam 23 66.32 63.12 - 74.00 2.84 4.23 14 66.13 63.47 - 70.43 2.30 3.46 9 68.02 63.12 - 74.00 3.46 5.09 Thailand 21 68.88 61.08 - 74.47 3.79 5.50 15 68.02 61.08 - 73.25 3.68 5.40 6 71.86 64.91 - 74.47 3.90 5.54 Cambodia 13 66.09 63.44 - 75.25 3.60 5.33 4 70.64 66.09 - 75.25 3.76 10.64 9 65.83 63.44 - 71.20 2.68 4.04 Philippines 28 68.10 57.48 - 80.36 5.52 8.03 22 68.45 57.48 - 80.36 5.34 7.75 6 66.63 61.16 - 76.66 6.69 9.78 Andaman Is. 36 71.42 63.90 - 81.38 4.30 6.06 18 69.90 63.99 - 75.79 3.60 5.16 18 72.12 63.90 - 81.38 4.71 6.53 Nicobar Is. 20 70.58 57.95 - 78.30 5.43 7.74 17 69.88 57.95 - 75.92 5.37 7.73 3 74.81 68.37 - 78.30 5.04 11.94 Borneo 37 68.99 61.71 - 76.21 3.50 5.10 26 69.52 62.68 - 76.21 3.41 4.96 11 67.81 61.71 - 74.98 3.85 5.63 Indonesia 27 68.52 60.65 - 75.62 3.86 5.64 20 67.98 60.65 - 72.37 3.41 5.05 7 72.80 64.67 - 75.62 3.83 5.37 Melanesia 30 73.54 62.89 - 85.06 4.48 6.10 20 73.36 64.39 - 82.00 3.95 5.38 10 74.08 62.89 - 85.06 5.63 7.67 Micronesia 15 69.68 64.80 - 73.55 2.03 2.90 7 71.13 68.37 - 73.55 1.83 2.59 8 69.22 64.80 - 70.84 1.88 2.73 Australia 27 73.28 65.51 - 86.32 3.97 5.41 18 71.95 65.51 - 75.78 2.70 3.77 9 75.92 70.75 - 86.32 4.48 5.86 Africa 29 70.94 63.27 - 79.14 4.24 6.05 18 70.86 63.27 - 73.46 3.52 5.11 11 73.40 67.36 - 79.14 4.66 6.44 Nat. America 33 67.49 61.36 - 75.10 3.40 5.01 10 67.63 64.66 - 75.10 3.55 5.18 23 67.49 61.36 - 73.84 3.37 4.99 Caucasian 29 62.87 57.50 - 69.92 3.36 5.28 15 61.95 57.50 - 67.81 3.12 5.00 14 64.15 59.78 - 69.92 3.31 5.12 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980) 420 Prosthion Angle (PRA)

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (deg.) (deg.) (%) (deg.) (deg.) (%) (deg.) (deg.) (%)

Siberia 28 70.51 63.11 - 83.59 4.10 5.81 18 70.44 63.11 - 83.59 4.36 6.21 10 70.98 66.67 - 79.70 3.74 5.28 Mongolia 24 69.64 64.21 - 75.83 3.56 5.08 16 69.00 64.21 - 75.83 3.97 5.68 8 70.82 67.00 - 74.26 2.74 3.89 Korea 4 75.51 72.39 - 76.99 2.16 5.76 2 74.69 72.39 - 76.99 3.25 6.53 2 75.51 74.34 - 76.69 1.66 3.30 Ainu 3 68.61 68.02 - 73.15 2.81 7.03 2 70.59 68.02 - 73.15 3.63 7.71 1 68.61 68.61 - 68.61 - - Japan 13 71.71 67.00 - 75.40 2.60 3.62 10 71.94 67.00 - 75.40 2.73 3.81 3 71.71 70.24 - 75.14 2.51 6.08 S. China 6 69.54 66.52 - 79.32 4.65 6.59 3 67.18 66.52 - 69.16 1.37 3.55 3 71.71 69.92 - 79.32 4.99 11.86 N. China 16 71.52 66.74 - 75.27 3.02 4.25 13 71.62 67.08 - 75.27 2.79 3.89 3 67.58 66.74 - 73.96 3.95 9.95 Burma 39 73.36 62.21 - 80.86 3.90 5.34 22 72.97 62.21 - 80.21 4.01 5.53 17 74.29 66.81 - 80.86 3.77 5.11 Laos 24 69.82 62.53 - 77.40 3.10 4.45 16 70.82 62.93 - 77.40 3.17 4.50 8 69.10 62.53 - 70.68 2.51 3.68 Vietnam 23 71.95 66.21 - 78.97 3.15 4.37 14 71.89 66.87 - 78.97 3.18 4.40 9 71.95 66.21 - 76.40 3.28 4.57 Thailand 21 70.95 62.81 - 79.58 3.32 4.70 15 69.91 66.89 - 79.58 3.25 4.59 6 72.02 62.81 - 72.78 3.80 5.39 Cambodia 13 71.63 68.49 - 79.45 3.85 5.29 4 69.60 68.49 - 71.63 1.32 3.77 9 75.44 69.06 - 79.45 3.96 5.35 Philippines 28 71.11 63.02 - 83.98 5.04 7.00 22 71.11 63.02 - 83.98 4.90 6.81 6 70.96 66.98 - 81.10 6.03 8.33 Andaman Is. 36 71.13 64.00 - 78.47 3.69 5.20 18 72.40 64.36 - 78.47 3.96 5.47 18 69.58 64.00 - 74.16 2.80 4.02 Nicobar Is. 20 70.94 64.66 - 79.44 4.01 5.62 17 72.10 66.38 - 79.44 3.96 5.53 3 69.58 64.66 - 73.72 4.54 11.45 Borneo 37 71.67 66.07 - 77.60 3.18 4.43 26 71.63 66.07 - 77.60 3.10 4.34 11 72.54 68.43 - 77.60 3.44 4.76 Indonesia 27 70.54 66.02 - 78.37 3.72 5.22 20 71.70 66.39 - 78.37 3.69 5.11 7 68.36 66.02 - 71.29 1.99 2.91 Melanesia 30 69.29 61.75 - 74.50 3.66 5.33 20 68.32 62.23 - 74.50 3.27 4.78 10 71.01 61.75 - 73.52 4.46 6.43 Micronesia 15 72.14 66.94 - 74.90 2.16 3.02 7 71.70 66.94 - 74.90 2.51 3.50 8 72.45 68.34 - 73.85 1.99 2.78 Australia 27 69.25 60.95 - 74.33 3.58 5.20 18 69.47 65.12 - 74.33 3.17 4.53 9 66.10 60.95 - 72.39 3.41 5.13 Africa 29 71.19 63.72 - 82.37 3.97 5.57 18 73.07 66.03 - 82.37 4.11 5.68 11 69.25 63.72 - 75.14 3.22 4.61 Nat. America 33 70.87 66.21 - 76.75 2.63 3.71 10 70.81 66.21 - 75.15 3.06 4.36 23 70.87 67.16 - 76.75 2.43 3.41 Caucasian 29 75.02 67.88 - 79.95 3.44 4.59 15 77.36 71.55 - 79.95 2.69 3.54 14 73.50 67.88 - 79.13 3.78 5.14 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

421 Basion Angle (BAA)

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (deg.) (deg.) (%) (deg.) (deg.) (%) (deg.) (deg.) (%)

Siberia 28 42.40 36.01 - 48.40 2.69 6.33 18 42.49 36.01 - 48.40 3.02 7.01 10 41.80 38.76 - 44.13 1.71 4.13 Mongolia 24 43.10 38.57 - 49.86 3.15 7.26 16 44.36 38.57 - 49.86 3.06 6.95 8 41.59 38.76 - 48.44 3.17 7.51 Korea 4 43.37 35.12 - 46.59 5.20 24.70 2 43.92 41.25 - 46.59 3.77 12.89 2 40.30 35.12 - 45.48 7.33 27.29 Ainu 3 39.25 37.01 - 43.86 3.49 15.25 2 38.13 37.01 - 39.25 1.58 6.22 1 43.86 43.86 - 43.86 - - Japan 13 40.15 35.37 - 45.04 2.59 6.42 10 40.61 37.42 - 45.04 2.43 5.95 3 40.15 35.37 - 40.43 2.85 12.88 S. China 6 41.69 37.58 - 43.44 2.22 5.38 3 43.09 41.59 - 43.44 0.98 4.02 3 39.65 37.58 - 41.78 2.10 9.26 N. China 16 42.07 38.41 - 52.06 4.29 9.82 13 42.30 38.41 - 52.06 4.32 9.88 3 41.69 39.56 - 49.25 5.10 20.50 Burma 39 40.96 34.74 - 48.51 3.09 7.53 22 40.89 36.40 - 48.51 3.12 7.62 17 41.40 34.74 - 46.17 3.14 7.63 Laos 24 41.60 36.55 - 46.33 2.31 5.55 16 41.60 36.55 - 46.33 2.60 6.29 8 41.60 40.50 - 44.87 1.60 3.80 Vietnam 23 40.80 37.56 - 44.74 2.02 4.95 14 41.62 37.56 - 44.74 2.13 5.16 9 39.84 38.16 - 43.12 1.75 4.35 Thailand 21 41.46 33.68 - 46.77 3.53 8.70 15 41.66 34.85 - 46.77 3.15 7.66 6 39.56 33.68 - 44.00 4.31 11.03 Cambodia 13 39.42 36.26 - 45.06 2.60 6.55 4 39.75 36.26 - 42.27 2.49 12.59 9 38.53 37.08 - 45.06 2.79 7.01 Philippines 28 39.37 33.61 - 44.57 3.16 8.06 22 39.37 33.61 - 44.57 2.88 7.34 6 38.20 33.93 - 44.49 4.38 11.18 Andaman Is. 36 37.53 33.44 - 42.64 2.50 6.57 18 37.44 34.21 - 41.79 2.13 5.64 18 37.75 33.44 - 42.64 2.85 7.45 Nicobar Is. 20 38.13 32.52 - 44.89 3.29 8.52 17 39.02 32.52 - 44.89 3.46 8.91 3 37.04 35.61 - 37.91 1.16 5.52 Borneo 37 39.57 34.53 - 43.16 2.49 6.30 26 39.64 34.53 - 43.16 2.51 6.35 11 38.96 35.45 - 42.88 2.55 6.47 Indonesia 27 40.52 34.77 - 46.97 2.68 6.63 20 40.72 34.77 - 45.52 2.44 6.04 7 39.75 36.51 - 46.97 3.50 8.67 Melanesia 30 37.46 33.19 - 45.31 2.87 7.58 20 37.93 34.35 - 45.31 2.65 6.94 10 36.68 33.19 - 43.60 3.31 8.91 Micronesia 15 37.77 36.34 - 42.44 1.92 5.00 7 36.97 36.39 - 39.51 1.21 3.22 8 38.97 36.34 - 42.44 2.13 5.44 Australia 27 37.49 32.72 - 42.41 2.62 6.92 18 38.09 34.35 - 42.41 2.66 6.95 9 37.08 32.72 - 39.78 2.49 6.72 Africa 29 37.63 33.38 - 43.30 2.86 7.45 18 38.37 34.26 - 42.90 2.79 7.23 11 36.86 33.38 - 43.30 3.07 8.07 Nat. America 33 40.94 37.37 - 47.82 2.47 6.00 10 41.78 37.37 - 44.30 2.83 6.86 23 40.94 37.37 - 47.82 2.37 5.75 Caucasian 29 41.34 34.73 - 48.56 3.13 7.53 15 40.60 37.93 - 48.14 3.22 7.76 14 42.19 34.73 - 48.56 3.15 7.56 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

422 Nasion Angle (NBA)

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (deg.) (deg.) (%) (deg.) (deg.) (%) (deg.) (deg.) (%)

Siberia 28 76.04 71.35 - 83.10 2.88 3.80 18 76.08 71.36 - 80.71 2.73 3.60 10 76.02 71.35 - 83.10 3.30 4.35 Mongolia 24 76.87 68.06 - 81.76 3.81 5.01 16 76.87 68.06 - 81.76 3.97 5.23 8 76.37 70.74 - 80.69 3.71 4.88 Korea 4 82.14 76.62 - 83.12 3.01 7.43 2 82.14 81.47 - 82.81 0.95 1.73 2 79.87 76.62 - 83.12 4.60 8.63 Ainu 3 77.73 73.95 - 78.83 2.56 5.82 2 76.39 73.95 - 78.83 3.45 6.77 1 77.73 77.73 - 77.73 - - Japan 13 79.78 76.99 - 82.20 1.81 2.27 10 80.66 76.99 - 82.20 1.90 2.37 3 78.07 78.00 - 79.25 0.70 1.57 S. China 6 81.04 77.10 - 83.92 2.52 3.12 3 79.43 77.10 - 82.80 2.87 6.28 3 82.13 79.95 - 83.92 1.99 4.25 N. China 16 79.58 76.39 - 90.33 3.74 4.64 13 79.88 76.39 - 90.33 4.01 4.95 3 79.41 76.85 - 82.03 2.59 5.71 Burma 39 79.22 73.06 - 85.92 3.15 3.96 22 79.83 74.74 - 85.55 2.72 3.40 17 79.05 73.06 - 85.92 3.71 4.68 Laos 24 80.67 76.56 - 87.07 2.77 3.41 16 81.04 77.16 - 87.07 2.89 3.54 8 80.36 76.56 - 83.48 2.36 2.95 Vietnam 23 81.63 67.66 - 87.69 3.88 4.78 14 81.68 67.66 - 87.69 4.63 5.72 9 80.91 77.95 - 84.84 2.54 3.13 Thailand 21 80.41 76.86 - 88.51 4.07 4.98 15 80.41 77.56 - 88.51 3.95 4.84 6 81.10 76.86 - 87.55 4.75 5.79 Cambodia 13 80.77 75.74 - 85.10 2.70 3.34 4 79.51 78.20 - 85.10 3.14 7.79 9 80.92 75.74 - 84.14 2.68 3.33 Philippines 28 78.62 72.52 - 86.50 3.34 4.21 22 78.62 72.52 - 86.50 3.31 4.16 6 79.33 75.16 - 84.00 3.80 4.79 Andaman Is. 36 80.54 73.97 - 84.39 2.24 2.79 18 80.80 77.24 - 84.39 1.94 2.39 18 79.90 73.97 - 83.26 2.39 3.00 Nicobar Is. 20 79.75 75.64 - 87.92 3.26 4.07 17 79.91 75.64 - 87.92 3.40 4.22 3 77.72 77.18 - 80.91 2.02 4.49 Borneo 37 80.42 76.85 - 88.26 2.84 3.50 26 80.94 76.85 - 88.26 2.77 3.42 11 80.29 76.85 - 86.33 3.12 3.84 Indonesia 27 80.83 73.41 - 85.41 3.20 3.99 20 81.13 73.41 - 85.41 3.17 3.95 7 79.97 73.60 - 84.05 3.39 4.27 Melanesia 30 79.84 71.48 - 84.29 2.79 3.51 20 79.70 71.48 - 82.62 2.80 3.54 10 80.12 74.97 - 84.29 2.76 3.45 Micronesia 15 80.93 72.83 - 84.59 3.33 4.13 7 80.73 72.83 - 83.66 3.45 4.31 8 82.11 75.45 - 84.59 3.37 4.15 Australia 27 77.37 71.13 - 81.95 2.50 3.23 18 77.69 71.13 - 81.95 2.37 3.05 9 76.93 72.20 - 81.19 2.83 3.68 Africa 29 75.57 70.29 - 82.21 3.41 4.51 18 76.26 70.40 - 81.41 3.33 4.38 11 74.58 70.29 - 82.21 3.63 4.84 Nat. America 33 77.71 71.79 - 84.00 2.70 3.48 10 78.12 71.79 - 84.00 3.40 4.36 23 77.66 74.30 - 82.25 2.41 3.12 Caucasian 29 76.32 70.18 - 81.05 3.35 4.40 15 76.93 70.18 - 81.05 3.45 4.49 14 75.80 70.32 - 80.65 3.26 4.31 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

423 Basion Angle (BBA)

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (deg.) (deg.) (%) (deg.) (deg.) (%) (deg.) (deg.) (%)

Siberia 28 56.12 48.39 - 60.49 3.05 5.49 18 55.62 51.51 - 60.49 2.99 5.39 10 56.79 48.39 - 59.76 3.32 5.95 Mongolia 24 56.70 52.72 - 64.91 2.83 4.96 16 56.66 52.72 - 64.91 3.19 5.59 8 57.32 54.29 - 60.84 2.13 3.71 Korea 4 53.31 51.57 - 56.80 2.20 8.19 2 53.31 53.10 - 53.52 0.30 0.83 2 54.18 51.57 - 56.80 3.70 10.24 Ainu 3 55.24 54.27 - 58.48 2.21 6.90 2 56.86 55.24 - 58.48 2.29 6.05 1 54.27 54.27 - 54.27 - - Japan 13 52.70 50.64 - 57.24 2.12 4.00 10 52.21 50.64 - 56.70 1.94 3.69 3 53.28 52.68 - 57.24 2.48 7.97 S. China 6 54.95 48.15 - 59.76 3.88 7.11 3 55.86 53.13 - 59.76 3.33 10.37 3 54.03 48.15 - 56.27 4.19 13.90 N. China 16 54.49 46.95 - 58.67 2.92 5.39 13 54.90 46.95 - 58.67 3.18 5.89 3 54.49 54.10 - 56.96 1.55 4.92 Burma 39 54.86 48.47 - 59.82 2.47 4.54 22 54.83 48.47 - 58.44 2.40 4.42 17 54.86 50.74 - 59.82 2.62 4.81 Laos 24 53.48 48.42 - 58.12 2.72 5.08 16 52.88 48.42 - 58.12 3.07 5.79 8 54.98 52.24 - 56.18 1.54 2.83 Vietnam 23 53.39 49.25 - 61.70 2.63 4.91 14 53.61 49.25 - 61.70 2.74 5.10 9 52.98 49.82 - 57.96 2.59 4.85 Thailand 21 53.52 46.51 - 61.02 3.44 6.44 15 53.33 46.51 - 57.26 3.00 5.68 6 55.65 49.21 - 61.02 4.23 7.68 Cambodia 13 53.94 49.52 - 56.12 2.32 4.35 4 54.32 53.01 - 55.82 1.19 4.37 9 53.36 49.52 - 56.12 2.64 4.98 Philippines 28 54.15 47.87 - 60.56 2.64 4.86 22 54.08 47.87 - 60.56 2.49 4.59 6 54.46 50.17 - 59.68 3.38 6.16 Andaman Is. 36 54.68 50.55 - 60.22 2.03 3.71 18 54.02 50.55 - 57.68 1.91 3.52 18 54.79 52.46 - 60.22 2.01 3.64 Nicobar Is. 20 53.92 49.25 - 59.92 2.89 5.34 17 53.50 49.25 - 59.92 3.09 5.74 3 54.63 54.46 - 56.09 0.89 2.84 Borneo 37 53.71 48.39 - 57.94 2.19 4.09 26 53.79 48.39 - 57.48 2.19 4.07 11 53.57 50.72 - 57.94 2.30 4.30 Indonesia 27 53.02 49.66 - 58.78 2.28 4.24 20 53.76 49.66 - 58.56 2.18 4.06 7 52.56 51.49 - 58.78 2.73 5.08 Melanesia 30 53.20 47.66 - 63.83 3.21 6.01 20 52.62 47.66 - 63.83 3.65 6.85 10 53.81 50.41 - 57.44 2.23 4.16 Micronesia 15 52.85 49.74 - 58.43 2.50 4.70 7 52.75 49.74 - 57.14 2.47 4.71 8 53.33 51.55 - 58.43 2.51 4.65 Australia 27 55.59 48.28 - 60.04 2.54 4.58 18 54.98 48.28 - 57.37 2.28 4.16 9 55.88 52.39 - 60.04 2.91 5.17 Africa 29 56.19 50.20 - 61.99 3.07 5.50 18 56.58 50.20 - 61.99 3.32 5.96 11 55.38 51.79 - 61.39 2.75 4.89 Nat. America 33 54.90 49.00 - 60.12 2.33 4.23 10 54.37 51.61 - 60.12 2.65 4.80 23 55.26 49.00 - 59.25 2.24 4.08 Caucasian 29 56.14 49.06 - 63.05 3.69 6.51 15 55.58 49.06 - 62.48 3.99 7.14 14 57.34 50.82 - 63.05 3.28 5.72 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

424 Nasiofrontal Angle (mNFA)

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (deg.) (deg.) (%) (deg.) (deg.) (%) (deg.) (deg.) (%)

Siberia 28 144.56 133.25 - 151.54 5.74 4.00 18 144.56 133.25 - 151.54 6.19 4.33 10 145.07 137.00 - 150.17 5.11 3.56 Mongolia 24 147.18 138.27 - 157.73 5.10 3.47 16 147.68 138.27 - 157.73 5.58 3.77 8 146.19 139.52 - 149.00 3.57 2.46 Korea 4 144.56 139.74 - 153.58 5.85 8.03 2 144.56 143.48 - 145.64 1.53 1.59 2 146.66 139.74 - 153.58 9.79 10.01 Ainu 3 144.68 142.50 - 151.78 4.85 5.80 2 147.14 142.50 - 151.78 6.56 6.69 1 144.68 144.68 - 144.68 -- Japan 13 145.53 138.68 - 155.53 4.79 3.30 10 146.02 138.68 - 155.53 4.82 3.29 3 140.01 139.93 - 145.53 3.21 3.97 S. China 6 146.08 140.38 - 155.23 5.23 3.56 3 146.75 140.38 - 149.79 4.80 5.77 3 145.41 143.12 - 155.23 6.43 7.61 N. China 16 144.39 137.29 - 157.74 5.02 3.45 13 145.44 141.45 - 157.74 4.70 3.22 3 141.80 137.29 - 150.70 6.82 8.33 Burma 39 144.07 131.52 - 155.10 5.87 4.11 22 143.27 131.52 - 155.10 6.76 4.74 17 144.33 135.72 - 151.12 4.61 3.21 Laos 24 146.13 136.90 - 155.00 4.78 3.28 16 146.34 136.90 - 152.57 4.41 3.01 8 144.01 138.71 - 155.00 5.60 3.87 Vietnam 23 145.25 133.76 - 152.35 4.85 3.36 14 144.44 133.76 - 152.35 4.76 3.31 9 146.56 134.01 - 150.56 5.03 3.45 Thailand 21 147.56 140.36 - 157.44 4.43 3.01 15 143.99 140.36 - 151.78 3.86 2.65 6 149.81 144.89 - 157.44 4.25 2.82 Cambodia 13 142.93 138.34 - 147.89 3.09 2.16 4 141.97 138.81 - 146.66 3.35 4.70 9 142.93 138.34 - 147.89 3.16 2.21 Philippines 28 145.62 135.82 - 158.37 5.18 3.57 22 146.91 135.82 - 158.37 5.09 3.49 6 142.15 136.32 - 148.40 4.53 3.19 Andaman Is. 36 141.76 129.15 - 150.08 3.90 2.76 18 141.19 136.44 - 147.03 3.22 2.28 18 142.04 129.15 - 150.08 4.58 3.24 Nicobar Is. 20 143.55 139.35 - 155.01 4.75 3.27 17 145.21 139.35 - 155.01 4.84 3.31 3 141.56 140.86 - 141.71 0.45 0.56 Borneo 37 144.97 135.30 - 155.49 4.44 3.06 26 145.23 135.30 - 155.49 4.52 3.12 11 144.97 138.39 - 153.04 4.45 3.07 Indonesia 27 143.50 137.42 - 151.77 3.70 2.57 20 143.34 137.42 - 151.77 3.82 2.65 7 143.61 140.71 - 149.31 3.56 2.46 Melanesia 30 140.54 133.83 - 154.73 4.99 3.52 20 139.80 133.97 - 154.73 4.73 3.36 10 145.34 133.83 - 147.78 5.33 3.71 Micronesia 15 142.21 134.64 - 154.00 5.14 3.61 7 143.13 136.82 - 154.00 5.28 3.68 8 140.47 134.64 - 147.68 4.93 3.50 Australia 27 140.61 130.91 - 153.55 4.80 3.40 18 139.86 130.91 - 147.51 4.70 3.35 9 141.33 138.27 - 153.55 4.87 3.41 Africa 29 139.37 134.13 - 151.20 3.99 2.84 18 139.09 135.07 - 149.16 3.10 2.22 11 143.01 134.13 - 151.20 5.06 3.58 Nat. America 33 143.89 129.90 - 154.32 4.56 3.20 10 142.52 129.90 - 154.32 6.65 4.70 23 144.71 136.72 - 147.19 3.38 2.37 Caucasian 29 140.37 130.57 - 148.13 4.34 3.09 15 140.37 130.57 - 148.13 4.75 3.38 14 140.02 133.64 - 146.34 4.02 2.86 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

425 Zygomaxillary Angle (mSSA)

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (deg.) (deg.) (%) (deg.) (deg.) (%) (deg.) (deg.) (%)

Siberia 28 135.77 119.26 - 152.82 7.10 5.23 18 134.20 119.26 - 143.65 6.98 5.16 10 136.26 120.99 - 152.82 7.63 5.60 Mongolia 24 136.20 123.18 - 148.97 7.15 5.21 16 138.43 126.90 - 148.97 7.44 5.36 8 135.10 123.18 - 141.58 5.64 4.21 Korea 4 136.30 131.09 - 141.85 4.83 7.09 2 137.84 133.83 - 141.85 5.67 6.17 2 134.93 131.09 - 138.77 5.43 6.03 Ainu 3 139.09 135.12 - 146.76 5.92 7.38 2 142.93 139.09 - 146.76 5.42 5.69 1 135.12 135.12 - 135.12 -- Japan 13 135.61 125.27 - 147.85 6.60 4.87 10 134.11 125.27 - 147.85 7.08 5.23 3 136.45 128.46 - 140.05 5.93 7.69 S. China 6 137.59 134.11 - 144.62 4.56 3.29 3 139.08 134.11 - 144.62 5.25 6.60 3 136.10 134.15 - 143.20 4.76 6.05 N. China 16 134.55 126.38 - 152.50 7.23 5.35 13 136.50 126.38 - 152.50 7.35 5.39 3 129.24 127.01 - 132.25 2.63 3.55 Burma 39 134.09 123.49 - 154.05 6.99 5.19 22 132.90 123.49 - 148.89 6.12 4.56 17 134.11 124.99 - 154.05 8.14 6.01 Laos 24 138.60 112.10 - 148.04 7.79 5.64 16 138.85 125.08 - 148.04 5.93 4.24 8 137.84 112.10 - 143.89 10.33 7.66 Vietnam 23 137.98 126.49 - 146.14 5.46 3.96 14 138.64 126.49 - 144.41 5.53 4.02 9 137.35 127.62 - 146.14 5.65 4.09 Thailand 21 136.06 121.82 - 144.59 5.56 4.13 15 135.15 126.66 - 144.59 4.96 3.70 6 138.24 121.82 - 141.65 7.16 5.26 Cambodia 13 135.95 114.04 - 146.74 9.67 7.19 4 132.86 125.07 - 146.74 9.08 13.51 9 136.41 114.04 - 145.64 10.45 7.77 Philippines 28 135.83 49.60 - 146.11 17.12 12.80 22 136.96 49.60 - 146.11 19.37 14.51 6 135.38 131.83 - 137.81 2.33 1.73 Andaman Is. 36 128.75 121.68 - 138.18 4.50 3.47 18 127.55 122.38 - 136.43 4.39 3.41 18 129.18 121.68 - 138.18 4.59 3.52 Nicobar Is. 20 139.62 121.49 - 154.20 7.37 5.31 17 139.96 132.95 - 154.20 6.08 4.32 3 130.93 121.49 - 134.16 6.58 8.94 Borneo 37 137.53 125.66 - 146.63 5.67 4.16 26 137.63 125.66 - 146.63 5.63 4.12 11 137.04 127.45 - 144.27 6.07 4.47 Indonesia 27 137.09 128.25 - 145.92 4.60 3.35 20 137.22 130.51 - 145.92 4.59 3.33 7 137.09 128.25 - 141.90 4.81 3.53 Melanesia 30 124.73 108.40 - 138.12 6.39 5.11 20 125.77 112.51 - 138.12 6.42 5.09 10 123.69 108.40 - 128.64 5.99 4.88 Micronesia 15 133.74 121.10 - 141.54 5.92 4.47 7 134.62 121.10 - 137.19 5.80 4.39 8 132.76 124.24 - 141.54 6.39 4.80 Australia 27 125.37 116.65 - 138.87 6.59 5.23 18 126.98 116.65 - 138.87 7.26 5.72 9 120.74 119.76 - 132.17 4.68 3.78 Africa 29 134.53 124.12 - 145.32 5.58 4.18 18 133.38 124.12 - 145.32 5.52 4.15 11 134.53 125.81 - 142.26 5.66 4.19 Nat. America 33 136.91 125.30 - 144.79 4.62 3.39 10 135.01 127.39 - 139.43 4.20 3.13 23 137.36 125.30 - 144.79 4.53 3.30 Caucasian 29 129.07 121.61 - 139.28 4.94 3.81 15 131.19 123.36 - 137.99 4.50 3.46 14 127.66 121.61 - 139.28 5.46 4.24 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

426 Frontal Angle (mFRA)

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (deg.) (deg.) (%) (deg.) (deg.) (%) (deg.) (deg.) (%)

Siberia 28 85.84 78.45 - 92.12 3.40 3.98 18 86.62 78.45 - 92.12 3.68 4.29 10 84.87 78.58 - 88.27 2.81 3.33 Mongolia 24 84.04 77.28 - 91.20 3.28 3.91 16 84.04 77.28 - 91.20 3.87 4.61 8 83.92 80.93 - 86.40 1.82 2.18 Korea 4 84.20 78.56 - 86.45 3.63 8.71 2 84.20 82.54 - 85.86 2.35 4.18 2 82.50 78.56 - 86.45 5.58 10.15 Ainu 3 85.95 82.61 - 89.81 3.61 7.33 2 87.88 85.95 - 89.81 2.73 4.66 1 82.61 82.61 - 82.61 - - Japan 13 87.25 74.69 - 91.55 5.07 5.90 10 87.20 76.25 - 91.55 4.32 4.99 3 87.33 74.69 - 88.59 7.69 16.10 S. China 6 84.88 62.49 - 91.84 10.20 12.41 3 85.40 62.49 - 91.84 15.43 33.78 3 84.37 82.21 - 87.10 2.45 5.08 N. China 16 84.26 76.58 - 90.69 4.36 5.18 13 84.71 76.58 - 90.69 4.33 5.10 3 81.65 77.39 - 84.51 3.58 7.72 Burma 39 84.11 76.78 - 96.29 4.31 5.11 22 84.85 76.78 - 96.29 4.70 5.53 17 83.88 77.16 - 92.77 3.84 4.57 Laos 24 84.05 70.54 - 90.38 4.97 5.93 16 84.86 70.54 - 90.38 5.74 6.87 8 83.30 80.53 - 89.84 3.20 3.81 Vietnam 23 87.39 76.29 - 91.99 4.39 5.12 14 84.22 79.79 - 89.98 3.74 4.41 9 87.89 76.29 - 91.99 5.06 5.79 Thailand 21 83.10 74.10 - 89.69 4.45 5.42 15 83.17 75.46 - 88.05 3.35 4.04 6 76.93 74.10 - 89.69 6.25 7.84 Cambodia 13 84.84 74.09 - 89.08 4.20 5.03 4 85.20 82.68 - 89.08 2.65 6.19 9 83.07 74.09 - 88.60 4.56 5.53 Philippines 28 82.87 72.63 - 91.92 5.03 6.04 22 81.81 72.63 - 91.92 4.95 6.03 6 87.78 83.96 - 91.31 2.49 2.85 Andaman Is. 36 82.54 75.24 - 90.79 3.58 4.32 18 83.68 78.88 - 90.79 3.59 4.25 18 81.52 75.24 - 87.40 2.78 3.43 Nicobar Is. 20 88.87 83.98 - 95.60 3.43 3.84 17 89.34 83.98 - 95.60 3.58 4.00 3 87.28 86.74 - 92.13 2.97 5.86 Borneo 37 87.17 79.78 - 94.55 3.62 4.17 26 87.38 79.84 - 94.55 3.69 4.22 11 86.65 79.78 - 90.26 3.43 4.00 Indonesia 27 83.38 75.34 - 89.21 3.53 4.25 20 83.46 75.34 - 89.21 3.52 4.22 7 81.89 78.14 - 86.82 3.71 4.51 Melanesia 30 89.49 78.07 - 94.99 3.75 4.24 20 89.76 78.07 - 94.99 4.33 4.88 10 88.76 82.49 - 90.66 2.36 2.68 Micronesia 15 88.91 79.95 - 95.30 3.99 4.50 7 87.71 79.95 - 95.30 4.83 5.52 8 90.55 84.97 - 93.26 3.03 3.38 Australia 27 90.21 79.90 - 95.63 4.00 4.48 18 90.85 82.60 - 95.63 3.25 3.60 9 85.82 79.90 - 94.06 4.72 5.41 Africa 29 87.88 75.83 - 94.00 3.81 4.37 18 87.67 81.45 - 94.00 3.06 3.48 11 88.45 75.83 - 89.78 4.78 5.54 Nat. America 33 87.56 78.58 - 92.94 3.75 4.30 10 86.05 80.76 - 92.94 4.05 4.70 23 87.56 78.58 - 92.58 3.58 4.08 Caucasian 29 85.89 79.68 - 95.15 4.33 5.05 15 85.89 79.68 - 92.72 4.24 4.97 14 85.73 80.05 - 95.15 4.53 5.25 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

427 Parietal Angle 1 (mPAA1)

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (deg.) (deg.) (%) (deg.) (deg.) (%) (deg.) (deg.) (%)

Siberia 28 85.84 78.45 - 92.12 3.40 3.98 18 86.62 78.45 - 92.12 3.68 4.29 10 84.87 78.58 - 88.27 2.81 3.33 Mongolia 24 84.04 77.28 - 91.20 3.28 3.91 16 84.04 77.28 - 91.20 3.87 4.61 8 83.92 80.93 - 86.40 1.82 2.18 Korea 4 84.20 78.56 - 86.45 3.63 8.71 2 84.20 82.54 - 85.86 2.35 4.18 2 82.50 78.56 - 86.45 5.58 10.15 Ainu 3 85.95 82.61 - 89.81 3.61 7.33 2 87.88 85.95 - 89.81 2.73 4.66 1 82.61 82.61 - 82.61 - - Japan 13 87.25 74.69 - 91.55 5.07 5.90 10 87.20 76.25 - 91.55 4.32 4.99 3 87.33 74.69 - 88.59 7.69 16.10 S. China 6 84.88 62.49 - 91.84 10.20 12.41 3 85.40 62.49 - 91.84 15.43 33.78 3 84.37 82.21 - 87.10 2.45 5.08 N. China 16 84.26 76.58 - 90.69 4.36 5.18 13 84.71 76.58 - 90.69 4.33 5.10 3 81.65 77.39 - 84.51 3.58 7.72 Burma 39 84.11 76.78 - 96.29 4.31 5.11 22 84.85 76.78 - 96.29 4.70 5.53 17 83.88 77.16 - 92.77 3.84 4.57 Laos 24 84.05 70.54 - 90.38 4.97 5.93 16 84.86 70.54 - 90.38 5.74 6.87 8 83.30 80.53 - 89.84 3.20 3.81 Vietnam 23 87.39 76.29 - 91.99 4.39 5.12 14 84.22 79.79 - 89.98 3.74 4.41 9 87.89 76.29 - 91.99 5.06 5.79 Thailand 21 83.10 74.10 - 89.69 4.45 5.42 15 83.17 75.46 - 88.05 3.35 4.04 6 76.93 74.10 - 89.69 6.25 7.84 Cambodia 13 84.84 74.09 - 89.08 4.20 5.03 4 85.20 82.68 - 89.08 2.65 6.19 9 83.07 74.09 - 88.60 4.56 5.53 Philippines 28 82.87 72.63 - 91.92 5.03 6.04 22 81.81 72.63 - 91.92 4.95 6.03 6 87.78 83.96 - 91.31 2.49 2.85 Andaman Is. 36 82.54 75.24 - 90.79 3.58 4.32 18 83.68 78.88 - 90.79 3.59 4.25 18 81.52 75.24 - 87.40 2.78 3.43 Nicobar Is. 20 88.87 83.98 - 95.60 3.43 3.84 17 89.34 83.98 - 95.60 3.58 4.00 3 87.28 86.74 - 92.13 2.97 5.86 Borneo 37 87.17 79.78 - 94.55 3.62 4.17 26 87.38 79.84 - 94.55 3.69 4.22 11 86.65 79.78 - 90.26 3.43 4.00 Indonesia 27 83.38 75.34 - 89.21 3.53 4.25 20 83.46 75.34 - 89.21 3.52 4.22 7 81.89 78.14 - 86.82 3.71 4.51 Melanesia 30 89.49 78.07 - 94.99 3.75 4.24 20 89.76 78.07 - 94.99 4.33 4.88 10 88.76 82.49 - 90.66 2.36 2.68 Micronesia 15 88.91 79.95 - 95.30 3.99 4.50 7 87.71 79.95 - 95.30 4.83 5.52 8 90.55 84.97 - 93.26 3.03 3.38 Australia 27 90.21 79.90 - 95.63 4.00 4.48 18 90.85 82.60 - 95.63 3.25 3.60 9 85.82 79.90 - 94.06 4.72 5.41 Africa 29 87.88 75.83 - 94.00 3.81 4.37 18 87.67 81.45 - 94.00 3.06 3.48 11 88.45 75.83 - 89.78 4.78 5.54 Nat. America 33 87.56 78.58 - 92.94 3.75 4.30 10 86.05 80.76 - 92.94 4.05 4.70 23 87.56 78.58 - 92.58 3.58 4.08 Caucasian 29 85.89 79.68 - 95.15 4.33 5.05 15 85.89 79.68 - 92.72 4.24 4.97 14 85.73 80.05 - 95.15 4.53 5.25 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

428 Parietal Angle 2 (mPAA2)

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (deg.) (deg.) (%) (deg.) (deg.) (%) (deg.) (deg.) (%)

Siberia 28 116.79 109.95 - 125.28 3.73 3.18 18 116.67 110.80 - 124.03 3.63 3.09 10 116.98 109.95 - 125.28 4.12 3.51 Mongolia 24 117.12 109.82 - 122.43 3.49 2.98 16 118.72 112.07 - 122.43 3.47 2.95 8 115.63 109.82 - 120.70 3.32 2.87 Korea 4 112.16 106.84 - 122.27 6.45 11.38 2 112.16 112.10 - 112.22 0.09 0.12 2 114.56 106.84 - 122.27 10.91 14.29 Ainu 3 116.05 109.03 - 119.55 5.35 8.16 2 112.54 109.03 - 116.05 4.96 6.61 1 119.55 119.55 - 119.55 -- Japan 13 115.18 109.25 - 118.59 2.68 2.33 10 114.94 111.28 - 118.59 2.34 2.03 3 116.25 109.25 - 116.69 4.17 6.40 S. China 6 114.62 110.06 - 120.62 3.71 3.23 3 115.53 113.71 - 120.62 3.58 5.38 3 112.26 110.06 - 116.90 3.49 5.41 N. China 16 113.05 109.10 - 121.69 3.10 2.72 13 113.73 110.89 - 121.69 3.06 2.68 3 111.35 109.10 - 112.56 1.76 2.77 Burma 39 114.80 108.80 - 124.81 3.92 3.40 22 115.60 108.80 - 124.81 3.97 3.42 17 114.08 109.42 - 123.16 3.83 3.34 Laos 24 113.50 108.79 - 120.47 3.53 3.10 16 112.35 108.79 - 120.47 3.69 3.25 8 114.17 110.06 - 120.23 3.21 2.80 Vietnam 23 114.36 107.79 - 121.17 3.30 2.88 14 114.39 111.82 - 118.68 2.20 1.92 9 113.02 107.79 - 121.17 4.70 4.10 Thailand 21 113.04 109.53 - 117.94 2.52 2.22 15 113.36 109.53 - 117.94 2.50 2.21 6 112.08 109.67 - 117.59 2.71 2.41 Cambodia 13 115.59 110.95 - 118.98 2.28 1.98 4 114.07 112.14 - 116.57 2.39 4.18 9 115.59 110.95 - 118.98 2.29 1.98 Philippines 28 112.78 102.37 - 121.28 4.31 3.81 22 112.78 102.37 - 120.73 4.24 3.76 6 113.54 107.00 - 121.28 4.88 4.29 Andaman Is. 36 110.64 103.21 - 119.13 3.41 3.08 18 112.28 107.15 - 119.13 3.15 2.81 18 108.92 103.21 - 117.57 3.27 2.99 Nicobar Is. 20 116.41 111.38 - 126.66 3.57 3.05 17 116.62 111.38 - 126.66 3.72 3.18 3 116.19 113.36 - 119.67 3.16 4.75 Borneo 37 116.49 108.00 - 121.24 3.34 2.87 26 117.75 109.32 - 121.24 2.93 2.49 11 114.50 108.00 - 119.77 3.33 2.92 Indonesia 27 113.35 104.42 - 117.09 2.82 2.49 20 113.29 104.42 - 117.09 3.07 2.72 7 113.38 111.07 - 117.01 2.07 1.83 Melanesia 30 117.24 111.49 - 124.84 3.41 2.92 20 117.59 112.08 - 124.84 3.39 2.88 10 115.69 111.49 - 120.92 3.16 2.73 Micronesia 15 113.70 109.87 - 118.48 2.87 2.51 7 117.37 111.84 - 118.48 2.55 2.20 8 112.62 109.87 - 117.09 2.31 2.05 Australia 27 118.88 111.74 - 125.34 3.73 3.15 18 119.53 112.85 - 125.34 3.33 2.79 9 114.95 111.74 - 124.09 4.11 3.51 Africa 29 117.35 109.91 - 123.55 2.91 2.49 18 117.49 112.46 - 123.55 2.72 2.31 11 117.12 109.91 - 119.52 3.21 2.75 Nat. America 33 118.78 111.92 - 124.35 3.19 2.69 10 117.23 111.94 - 122.52 3.00 2.54 23 119.01 111.92 - 124.35 3.29 2.77 Caucasian 29 116.35 108.52 - 122.37 3.26 2.81 15 116.03 108.52 - 122.37 3.72 3.20 14 116.75 109.27 - 118.71 2.78 2.40 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

429 Occipital Angle (mOCA)

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (deg.) (deg.) (%) (deg.) (deg.) (%) (deg.) (deg.) (%)

Siberia 28 121.99 103.86 - 133.52 7.18 6.01 18 121.08 103.86 - 133.52 7.63 6.42 10 122.23 111.18 - 128.23 6.54 5.43 Mongolia 24 118.07 102.47 - 131.18 6.57 5.54 16 116.86 102.47 - 124.58 5.77 4.97 8 122.98 115.76 - 131.18 5.81 4.72 Korea 4 121.34 114.44 - 131.75 7.46 12.21 2 116.57 114.44 - 118.69 3.00 3.87 2 127.87 123.98 - 131.75 5.50 6.45 Ainu 3 119.38 117.34 - 125.94 4.50 6.51 2 118.36 117.34 - 119.38 1.44 1.83 1 125.94 125.94 - 125.94 -- Japan 13 123.12 112.70 - 131.12 5.93 4.82 10 122.87 112.70 - 131.12 6.58 5.34 3 123.39 117.96 - 125.25 3.79 5.42 S. China 6 119.78 113.62 - 132.32 8.08 6.65 3 115.86 113.62 - 123.70 5.29 7.87 3 129.60 114.76 - 132.32 9.45 13.18 N. China 16 119.15 100.40 - 129.59 9.18 7.75 13 119.39 100.40 - 129.59 9.67 8.18 3 118.90 111.25 - 127.79 8.27 12.14 Burma 39 126.82 110.17 - 138.81 6.80 5.39 22 128.49 110.17 - 138.81 7.40 5.86 17 125.12 117.44 - 137.86 6.16 4.88 Laos 24 127.20 116.86 - 134.50 5.94 4.70 16 125.74 116.86 - 134.50 5.69 4.56 8 131.10 118.33 - 134.19 5.68 4.39 Vietnam 23 125.86 114.01 - 135.90 5.71 4.59 14 126.00 114.01 - 129.99 5.08 4.09 9 123.85 116.43 - 135.90 6.88 5.50 Thailand 21 129.39 119.14 - 139.12 4.57 3.55 15 128.41 119.14 - 139.12 4.87 3.78 6 129.86 122.11 - 134.44 4.15 3.22 Cambodia 13 124.28 107.80 - 136.01 7.93 6.29 4 129.15 107.80 - 134.55 12.51 19.98 9 124.01 119.59 - 136.01 5.92 4.68 Philippines 28 124.92 115.37 - 139.36 5.67 4.56 22 125.22 115.37 - 139.36 6.23 5.00 6 124.70 119.83 - 128.93 3.27 2.63 Andaman Is. 36 128.01 110.40 - 140.09 6.20 4.88 18 126.43 110.40 - 132.36 5.52 4.39 18 129.63 117.85 - 140.09 6.65 5.17 Nicobar Is. 20 119.21 111.43 - 129.92 5.33 4.45 17 117.86 111.43 - 129.92 4.99 4.20 3 124.66 123.08 - 129.33 3.25 4.52 Borneo 37 124.61 112.16 - 137.73 6.59 5.30 26 123.81 112.16 - 137.73 7.26 5.84 11 126.68 115.06 - 130.20 5.04 4.04 Indonesia 27 127.03 118.70 - 137.27 4.17 3.29 20 126.29 118.70 - 132.05 3.66 2.89 7 127.37 121.96 - 137.27 5.43 4.22 Melanesia 30 121.20 107.77 - 135.56 6.31 5.19 20 118.83 107.77 - 135.56 6.53 5.45 10 125.19 120.26 - 131.44 3.74 2.98 Micronesia 15 123.82 114.93 - 138.12 5.51 4.43 7 122.90 114.93 - 130.07 5.41 4.37 8 124.14 118.44 - 138.12 5.90 4.72 Australia 27 125.43 117.39 - 143.33 5.69 4.55 18 124.98 117.39 - 143.33 6.69 5.35 9 125.82 119.15 - 129.97 3.19 2.55 Africa 29 122.68 107.21 - 134.27 6.76 5.48 18 121.77 107.21 - 134.27 6.84 5.58 11 125.48 112.62 - 133.84 6.79 5.46 Nat. America 33 122.35 110.59 - 130.20 5.02 4.13 10 119.83 110.59 - 130.20 6.07 5.05 23 122.72 112.34 - 129.36 4.50 3.68 Caucasian 29 118.50 109.02 - 126.06 4.09 3.45 15 118.09 110.23 - 124.48 3.97 3.35 14 119.27 109.02 - 126.06 4.36 3.67 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

430 Nasospinale Angle (NS)

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (deg.) (deg.) (%) (deg.) (deg.) (%) (deg.) (deg.) (%)

Siberia 28 105.91 92.81 - 117.65 6.65 6.33 18 105.91 95.03 - 117.65 6.44 6.16 10 106.42 92.81 - 115.98 7.29 6.88 Mongolia 24 107.92 87.14 - 115.81 7.13 6.67 16 108.27 87.14 - 115.59 7.74 7.23 8 105.61 98.96 - 115.81 6.24 5.84 Korea 4 111.15 105.77 - 125.34 8.98 15.84 2 111.15 107.22 - 115.07 5.55 7.49 2 115.55 105.77 - 125.34 13.84 17.97 Ainu 3 110.12 109.10 - 122.96 7.73 11.86 2 116.54 110.12 - 122.96 9.08 11.69 1 109.10 109.10 - 109.10 -- Japan 13 110.46 102.99 - 128.31 7.53 6.70 10 109.36 102.99 - 123.37 6.62 5.96 3 114.62 109.67 - 128.31 9.65 14.37 S. China 6 113.78 99.63 - 121.23 7.42 6.58 3 113.34 110.29 - 121.23 5.64 8.59 3 114.21 99.63 - 117.50 9.51 15.07 N. China 16 106.58 91.02 - 123.32 7.67 7.08 13 105.98 91.02 - 123.32 7.82 7.26 3 107.18 105.40 - 119.92 7.92 12.50 Burma 39 111.22 92.55 - 130.09 8.68 7.84 22 111.05 92.55 - 130.09 8.57 7.71 17 111.22 92.88 - 123.36 9.07 8.22 Laos 24 114.04 96.45 - 129.56 7.07 6.14 16 112.71 96.45 - 129.56 7.90 6.92 8 117.46 108.52 - 123.20 4.94 4.23 Vietnam 23 111.34 95.59 - 123.41 6.81 6.12 14 109.78 95.59 - 123.41 7.49 6.75 9 114.19 104.32 - 119.94 5.98 5.34 Thailand 21 114.69 98.96 - 129.71 7.40 6.38 15 114.38 98.96 - 124.59 6.53 5.72 6 121.21 109.47 - 129.71 8.20 6.82 Cambodia 13 109.02 94.24 - 127.49 11.37 10.18 4 120.39 109.39 - 126.78 7.98 13.38 9 106.50 94.24 - 127.49 11.37 10.49 Philippines 28 115.94 99.16 - 143.33 9.96 8.54 22 116.75 99.16 - 143.33 10.02 8.53 6 114.56 100.06 - 125.36 10.10 8.87 Andaman Is. 36 111.78 97.42 - 132.56 7.85 6.98 18 109.04 97.42 - 121.28 6.80 6.24 18 114.75 104.31 - 132.56 7.43 6.41 Nicobar Is. 20 120.21 96.78 - 138.80 12.41 10.22 17 119.11 96.78 - 138.80 13.00 10.77 3 126.83 116.48 - 134.09 8.85 12.31 Borneo 37 113.73 91.77 - 136.31 9.70 8.50 26 113.62 91.77 - 136.31 9.94 8.68 11 117.32 96.75 - 126.61 9.52 8.40 Indonesia 27 116.70 103.34 - 135.28 10.13 8.57 20 116.17 103.34 - 131.23 9.35 8.07 7 128.51 105.17 - 135.28 9.84 7.87 Melanesia 30 118.95 107.57 - 130.40 5.79 4.87 20 118.90 107.57 - 130.40 5.75 4.86 10 119.91 109.66 - 129.59 6.00 5.00 Micronesia 15 115.35 107.03 - 127.46 6.30 5.37 7 115.35 112.36 - 125.59 5.83 4.93 8 115.24 107.03 - 127.46 6.92 5.95 Australia 27 115.45 104.94 - 137.94 7.92 6.79 18 114.80 104.94 - 124.16 6.01 5.24 9 119.09 109.49 - 137.94 10.12 8.40 Africa 29 110.68 70.84 - 128.91 11.91 10.94 18 102.78 70.84 - 128.91 13.37 12.65 11 115.33 102.80 - 122.87 6.77 5.94 Nat. America 33 109.75 99.35 - 123.33 4.80 4.35 10 109.95 105.20 - 121.43 5.18 4.65 23 109.75 99.35 - 123.33 4.67 4.25 Caucasian 29 97.01 85.53 - 117.11 6.66 6.79 15 93.23 85.53 - 101.08 4.29 4.57 14 102.14 95.58 - 117.11 5.94 5.80 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

431 Prosthion Angle (PR)

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (deg.) (deg.) (%) (deg.) (deg.) (%) (deg.) (deg.) (%)

Siberia 28 62.52 52.93 - 74.54 6.16 9.74 18 62.61 52.93 - 73.96 5.87 9.23 10 62.29 53.50 - 74.54 6.93 11.07 Mongolia 24 60.50 52.00 - 80.37 6.77 10.97 16 59.17 52.00 - 80.37 7.40 12.04 8 63.54 55.30 - 68.83 5.71 9.20 Korea 4 57.63 48.62 - 61.69 5.82 20.64 2 57.63 55.39 - 59.88 3.18 8.27 2 55.16 48.62 - 61.69 9.24 25.13 Ainu 3 58.74 47.46 - 60.30 7.01 22.10 2 53.88 47.46 - 60.30 9.08 25.28 1 58.74 58.74 - 58.74 - - Japan 13 58.92 45.48 - 67.64 6.54 11.28 10 59.68 48.80 - 67.64 6.01 10.12 3 55.02 45.48 - 60.28 7.51 24.51 S. China 6 56.15 49.91 - 71.60 7.26 12.52 3 56.01 49.91 - 58.47 4.41 14.08 3 56.29 55.55 - 71.60 9.06 25.92 N. China 16 60.51 48.26 - 78.63 7.00 11.53 13 60.86 48.26 - 78.63 7.40 12.05 3 60.45 52.23 - 60.56 4.78 14.48 Burma 39 59.52 39.70 - 79.11 8.27 13.94 22 59.43 39.70 - 79.11 8.69 14.79 17 60.95 47.64 - 76.56 7.90 13.16 Laos 24 55.77 43.66 - 74.30 6.57 11.97 16 57.06 43.66 - 74.30 7.26 12.98 8 51.85 47.41 - 60.72 4.68 8.85 Vietnam 23 58.46 48.75 - 75.52 6.32 10.76 14 58.74 48.75 - 75.52 7.07 12.05 9 56.21 52.77 - 66.47 5.34 9.09 Thailand 21 55.68 45.82 - 68.36 5.94 10.80 15 56.57 47.94 - 68.36 5.36 9.47 6 49.25 45.82 - 58.99 5.93 11.60 Cambodia 13 61.58 43.42 - 79.37 11.93 19.90 4 49.88 46.11 - 61.79 7.15 27.55 9 64.11 43.42 - 79.37 12.14 19.11 Philippines 28 54.91 31.01 - 73.93 9.63 17.66 22 54.61 31.01 - 73.93 9.85 18.29 6 56.93 46.33 - 69.87 9.18 16.12 Andaman Is. 36 60.50 43.70 - 73.85 7.46 12.56 18 62.88 49.19 - 73.85 6.93 11.00 18 57.71 43.70 - 64.22 6.27 11.24 Nicobar Is. 20 50.61 35.09 - 74.07 11.30 22.41 17 50.73 35.09 - 74.07 11.80 23.06 3 44.49 39.01 - 55.24 8.26 31.24 Borneo 37 56.59 36.64 - 77.56 9.01 15.91 26 56.76 36.64 - 77.56 9.32 16.54 11 55.36 44.03 - 72.16 8.62 15.07 Indonesia 27 53.51 37.49 - 67.54 8.71 16.64 20 55.50 41.21 - 67.54 7.89 14.47 7 42.70 37.49 - 63.22 8.47 18.35 Melanesia 30 53.66 42.09 - 62.15 4.99 9.38 20 54.05 42.09 - 62.15 5.13 9.58 10 52.89 45.08 - 61.57 4.90 9.32 Micronesia 15 57.10 47.81 - 64.43 5.33 9.74 7 57.51 47.81 - 59.90 5.12 9.42 8 56.28 48.08 - 64.43 5.83 10.59 Australia 27 54.45 35.57 - 67.53 6.99 12.91 18 54.69 47.64 - 67.53 5.26 9.44 9 52.77 35.57 - 62.69 9.17 17.94 Africa 29 58.49 43.74 - 104.42 12.07 19.59 18 64.45 43.74 - 104.42 13.89 21.51 11 53.67 49.30 - 69.91 6.16 10.86 Nat. America 33 57.96 46.79 - 66.74 4.14 7.12 10 57.32 50.31 - 64.57 4.85 8.42 23 57.96 46.79 - 66.74 3.89 6.65 Caucasian 29 70.33 58.88 - 88.10 6.49 9.27 15 73.01 66.67 - 88.10 5.33 7.22 14 65.73 58.88 - 76.94 4.85 7.38 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

432 mf-n-zyo

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (deg.) (deg.) (%) (deg.) (deg.) (%) (deg.) (deg.) (%)

Siberia 28 18.86 6.91 - 35.58 6.32 32.19 18 18.86 6.91 - 35.58 7.26 35.90 10 19.08 10.25 - 23.44 4.50 24.11 Mongolia 24 18.36 9.05 - 30.63 5.82 31.30 16 19.38 9.05 - 30.63 6.34 33.03 8 15.52 12.70 - 25.78 4.79 27.50 Korea 4 16.01 11.79 - 19.07 3.07 39.00 2 14.32 11.79 - 16.85 3.58 37.46 2 17.12 15.18 - 19.07 2.75 24.08 Ainu 3 20.46 14.45 - 22.12 4.04 37.18 2 17.45 14.45 - 20.46 4.25 36.56 1 22.12 22.12 - 22.12 - - Japan 13 19.60 15.15 - 33.26 4.96 24.01 10 19.78 15.35 - 33.26 5.28 25.03 3 18.89 15.15 - 23.61 4.24 38.62 S. China 6 15.89 12.58 - 22.24 3.43 21.13 3 15.33 12.58 - 17.19 2.32 26.98 3 16.45 13.49 - 22.24 4.45 44.76 N. China 16 20.67 8.49 - 28.79 5.08 24.37 13 21.61 8.49 - 28.79 5.58 26.29 3 18.83 18.02 - 20.88 1.47 13.38 Burma 39 18.78 11.20 - 28.37 4.07 21.21 22 19.56 11.20 - 28.37 3.91 20.25 17 17.49 11.35 - 28.17 4.39 23.03 Laos 24 18.29 10.77 - 27.20 4.53 24.64 16 16.92 10.77 - 27.20 4.87 27.24 8 19.62 13.42 - 25.32 3.86 19.87 Vietnam 23 18.95 8.86 - 24.69 4.12 22.61 14 18.86 8.86 - 22.57 4.17 24.58 9 19.11 14.85 - 24.69 3.38 16.78 Thailand 21 19.73 13.32 - 28.05 4.64 24.19 15 17.57 13.32 - 28.05 4.31 23.33 6 23.60 13.71 - 25.93 5.38 25.71 Cambodia 13 18.85 12.81 - 35.90 6.27 32.21 4 16.84 13.90 - 23.29 4.29 48.42 9 19.63 12.81 - 35.90 7.06 34.88 Philippines 28 17.99 10.80 - 25.18 3.78 21.11 22 17.99 11.79 - 25.18 3.95 21.62 6 17.93 10.80 - 18.50 3.00 18.08 Andaman Is. 36 14.76 8.57 - 43.30 6.25 38.99 18 13.74 8.57 - 24.66 4.45 29.74 18 15.18 10.68 - 43.30 7.63 44.63 Nicobar Is. 20 19.06 11.46 - 25.87 4.36 22.98 17 19.60 11.46 - 25.87 4.35 22.67 3 17.53 12.71 - 22.99 5.14 50.73 Borneo 37 18.58 9.02 - 39.71 6.42 32.46 26 18.17 9.02 - 32.25 5.71 30.81 11 19.59 14.65 - 39.71 7.32 32.29 Indonesia 27 19.75 11.11 - 30.76 4.03 20.36 20 20.13 14.62 - 30.76 4.00 19.52 7 18.51 11.11 - 21.62 3.60 20.27 Melanesia 30 21.55 14.78 - 35.16 5.34 23.77 20 20.24 14.78 - 35.16 4.60 22.27 10 25.27 20.33 - 34.12 5.08 19.51 Micronesia 15 21.97 13.27 - 34.19 6.90 29.67 7 20.98 13.27 - 34.19 8.05 33.10 8 22.38 13.91 - 31.76 6.13 27.45 Australia 27 22.15 13.68 - 41.83 6.53 28.06 18 21.19 13.68 - 41.83 6.08 27.03 9 22.72 15.86 - 40.46 7.47 30.06 Africa 29 17.53 7.94 - 28.16 4.55 26.64 18 17.89 10.20 - 27.42 4.23 24.33 11 15.98 7.94 - 28.16 5.21 31.42 Nat. America 33 20.45 9.22 - 33.05 5.65 27.61 10 22.14 9.22 - 25.28 5.94 30.86 23 19.93 11.77 - 33.05 5.60 26.73 Caucasian 29 18.97 10.51 - 32.36 5.08 26.17 15 20.08 12.38 - 32.36 5.87 29.08 14 18.42 10.51 - 28.92 4.12 22.19 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

433 ns-n-zyo

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (deg.) (deg.) (%) (deg.) (deg.) (%) (deg.) (deg.) (%)

Siberia 28 44.48 40.10 - 49.64 3.16 7.05 18 44.48 40.10 - 49.64 3.10 6.99 10 45.59 40.26 - 49.38 3.26 7.13 Mongolia 24 44.70 39.65 - 50.14 3.00 6.68 16 44.70 39.65 - 50.14 3.04 6.75 8 44.03 41.20 - 48.51 3.11 6.97 Korea 4 41.38 38.52 - 43.28 1.98 9.64 2 39.79 38.52 - 41.05 1.80 6.77 2 42.50 41.71 - 43.28 1.11 3.92 Ainu 3 46.62 43.96 - 46.75 1.58 6.03 2 46.69 46.62 - 46.75 0.09 0.30 1 43.96 43.96 - 43.96 - - Japan 13 45.03 39.66 - 52.03 3.73 8.07 10 44.91 39.66 - 52.03 4.13 8.93 3 45.03 44.71 - 49.39 2.62 9.88 S. China 6 50.78 42.22 - 52.25 4.02 8.19 3 51.92 51.79 - 52.25 0.24 0.80 3 46.30 42.22 - 49.77 3.78 14.35 N. China 16 44.15 30.94 - 54.77 5.44 12.19 13 44.05 30.94 - 54.77 6.02 13.51 3 44.25 43.22 - 47.21 2.07 8.08 Burma 39 47.07 39.51 - 54.14 3.26 6.86 22 47.42 43.06 - 53.16 2.54 5.29 17 46.60 39.51 - 54.14 4.04 8.59 Laos 24 48.22 42.07 - 53.52 3.18 6.69 16 48.02 42.31 - 53.52 3.05 6.39 8 48.75 42.07 - 50.60 3.61 7.66 Vietnam 23 46.94 40.56 - 49.96 2.60 5.59 14 45.65 40.56 - 49.12 2.68 5.88 9 48.09 44.55 - 49.96 1.87 3.92 Thailand 21 47.83 36.84 - 54.76 4.33 9.14 15 47.83 36.84 - 54.76 4.44 9.38 6 47.42 41.90 - 52.81 4.45 9.40 Cambodia 13 47.42 44.00 - 52.47 2.36 4.93 4 49.89 48.00 - 52.47 2.20 8.80 9 46.84 44.00 - 50.04 1.72 3.67 Philippines 28 49.05 40.31 - 53.84 3.72 7.72 22 49.05 40.31 - 53.84 4.00 8.32 6 48.76 45.20 - 52.45 2.66 5.47 Andaman Is. 36 49.03 36.74 - 59.65 4.09 8.29 18 49.33 36.74 - 54.41 4.01 8.16 18 48.36 44.84 - 59.65 4.28 8.65 Nicobar Is. 20 47.20 41.13 - 53.01 3.07 6.47 17 47.17 41.13 - 52.27 2.83 6.02 3 51.31 46.32 - 53.01 3.48 12.12 Borneo 37 47.93 38.66 - 53.99 3.22 6.71 26 48.02 38.66 - 53.99 3.43 7.17 11 47.77 45.05 - 53.67 2.78 5.73 Indonesia 27 47.00 41.76 - 51.27 2.63 5.58 20 46.98 41.76 - 51.27 2.75 5.86 7 47.00 44.51 - 50.79 2.38 5.01 Melanesia 30 49.08 44.59 - 55.19 2.78 5.61 20 48.63 44.59 - 55.19 3.10 6.27 10 49.86 47.84 - 54.72 2.09 4.17 Micronesia 15 50.65 47.22 - 56.36 2.53 4.94 7 50.38 49.15 - 55.93 2.40 4.72 8 51.98 47.22 - 56.36 2.75 5.32 Australia 27 50.85 44.39 - 55.23 3.17 6.23 18 50.86 44.39 - 55.23 3.21 6.36 9 50.78 45.63 - 55.18 3.11 6.02 Africa 29 49.97 44.54 - 59.28 2.87 5.70 18 49.76 44.54 - 59.28 3.01 5.97 11 50.59 45.61 - 54.34 2.78 5.52 Nat. America 33 47.86 43.44 - 58.26 3.06 6.41 10 47.31 44.52 - 52.57 2.57 5.41 23 48.00 43.44 - 58.26 3.30 6.89 Caucasian 29 45.32 39.52 - 51.37 3.05 6.72 15 44.42 39.52 - 51.17 3.02 6.74 14 47.11 40.18 - 51.37 3.07 6.66 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

434 n-ns-zyo

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (deg.) (deg.) (%) (deg.) (deg.) (%) (deg.) (deg.) (%)

Siberia 28 49.80 34.97 - 64.55 7.31 14.56 18 46.97 34.97 - 64.55 8.29 16.91 10 51.25 46.00 - 59.97 4.77 9.11 Mongolia 24 47.99 40.28 - 55.04 4.10 8.56 16 48.55 40.28 - 55.04 4.47 9.31 8 46.65 42.93 - 54.27 3.49 7.33 Korea 4 46.90 39.51 - 50.13 5.18 22.60 2 44.82 39.51 - 50.13 7.51 25.13 2 46.90 43.75 - 50.05 4.45 14.25 Ainu 3 49.75 49.53 - 52.29 1.53 5.31 2 50.91 49.53 - 52.29 1.95 5.75 1 49.75 49.75 - 49.75 - - Japan 13 46.05 41.97 - 55.01 3.93 8.29 10 46.32 41.97 - 55.01 4.15 8.70 3 45.53 43.18 - 50.19 3.57 13.49 S. China 6 48.33 40.61 - 50.72 4.15 8.83 3 48.36 48.31 - 50.72 1.38 4.91 3 43.21 40.61 - 50.66 5.21 20.36 N. China 16 46.94 21.31 - 57.58 9.18 20.42 13 46.62 21.31 - 57.58 10.03 22.45 3 47.30 40.59 - 50.52 5.07 19.21 Burma 39 52.44 39.23 - 60.27 5.68 10.86 22 53.71 39.23 - 59.97 5.72 10.89 17 51.32 42.57 - 60.27 5.78 11.13 Laos 24 50.03 37.94 - 59.14 5.21 10.44 16 50.03 41.27 - 59.14 4.74 9.39 8 49.66 37.94 - 56.06 6.30 12.86 Vietnam 23 47.27 39.31 - 65.06 6.43 13.11 14 47.54 39.31 - 65.06 7.24 14.66 9 46.33 41.46 - 56.02 5.32 10.95 Thailand 21 48.63 33.38 - 55.07 4.70 9.70 15 48.63 33.38 - 55.07 5.31 10.98 6 49.01 45.09 - 53.68 3.08 6.30 Cambodia 13 50.97 39.48 - 60.21 5.18 10.34 4 50.77 50.08 - 53.93 1.75 6.81 9 50.97 39.48 - 60.21 6.16 12.43 Philippines 28 50.91 40.61 - 65.31 5.59 10.67 22 50.39 40.61 - 65.31 5.27 10.28 6 55.59 48.70 - 65.22 5.31 9.42 Andaman Is. 36 52.68 46.35 - 61.65 3.75 7.14 18 52.68 46.67 - 60.43 3.18 6.07 18 52.77 46.35 - 61.65 4.33 8.24 Nicobar Is. 20 51.59 44.25 - 61.81 5.35 10.34 17 50.37 44.25 - 61.81 5.27 10.33 3 57.19 51.50 - 59.57 4.15 12.94 Borneo 37 52.37 43.51 - 61.92 5.12 9.85 26 50.71 43.51 - 61.92 5.57 10.73 11 52.47 46.32 - 59.23 4.09 7.83 Indonesia 27 54.10 42.78 - 58.61 4.18 8.02 20 54.12 42.78 - 58.61 4.43 8.47 7 51.27 47.38 - 57.26 3.70 7.13 Melanesia 30 51.05 39.17 - 57.65 4.23 8.34 20 51.89 45.91 - 56.31 2.93 5.63 10 48.19 39.17 - 57.65 5.49 11.36 Micronesia 15 52.23 42.12 - 56.07 3.70 7.36 7 52.23 42.12 - 56.07 4.84 9.68 8 52.22 46.47 - 52.58 2.67 5.28 Australia 27 53.85 44.71 - 63.16 4.46 8.33 18 54.13 45.95 - 60.07 3.60 6.69 9 53.08 44.71 - 63.16 6.00 11.37 Africa 29 56.12 47.68 - 65.60 5.14 9.02 18 54.99 47.68 - 65.60 5.23 9.37 11 60.92 50.92 - 63.87 4.64 7.89 Nat. America 33 53.24 42.19 - 63.61 4.16 7.79 10 52.30 48.77 - 55.56 2.59 4.95 23 54.13 42.19 - 63.61 4.67 8.69 Caucasian 29 55.12 47.14 - 66.14 4.57 8.25 15 53.59 47.14 - 63.22 3.94 7.28 14 56.84 48.35 - 66.14 4.92 8.66 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

435 ns-n-ba

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (deg.) (deg.) (%) (deg.) (deg.) (%) (deg.) (deg.) (%)

Siberia 28 64.02 57.21 - 71.11 3.36 5.22 18 64.04 57.67 - 70.82 3.23 5.03 10 63.87 57.21 - 71.11 3.75 5.84 Mongolia 24 63.70 54.94 - 69.99 3.99 6.30 16 63.35 54.94 - 69.99 4.32 6.86 8 64.86 58.65 - 68.33 3.34 5.20 Korea 4 55.67 52.49 - 64.09 4.99 17.53 2 55.67 55.12 - 56.22 0.78 2.10 2 58.29 52.49 - 64.09 8.20 21.11 Ainu 3 63.41 63.19 - 65.92 1.52 4.14 2 64.55 63.19 - 65.92 1.93 4.49 1 63.41 63.41 - 63.41 - - Japan 13 63.37 61.48 - 67.32 1.71 2.70 10 63.23 61.48 - 67.32 1.88 2.96 3 63.42 61.69 - 64.05 1.22 3.39 S. China 6 64.25 58.96 - 67.19 3.09 4.83 3 65.45 62.93 - 66.86 1.99 5.35 3 63.06 58.96 - 67.19 4.12 11.42 N. China 16 60.59 51.34 - 67.45 4.33 7.07 13 60.61 51.34 - 66.89 4.49 7.36 3 60.33 60.16 - 67.45 4.16 11.62 Burma 39 61.43 55.93 - 69.14 3.34 5.45 22 61.47 56.47 - 69.14 3.21 5.21 17 61.43 55.93 - 67.09 3.57 5.86 Laos 24 62.91 59.19 - 68.31 2.27 3.59 16 62.88 59.19 - 66.76 2.15 3.43 8 63.46 61.10 - 68.31 2.52 3.95 Vietnam 23 62.65 56.20 - 68.76 3.12 5.00 14 61.92 56.20 - 65.46 2.68 4.35 9 63.75 58.56 - 68.76 3.45 5.41 Thailand 21 64.38 58.37 - 70.85 3.76 5.88 15 63.28 58.37 - 70.40 3.83 6.01 6 64.55 59.83 - 70.85 3.88 6.04 Cambodia 13 63.45 58.27 - 68.09 2.48 3.91 4 63.33 62.93 - 68.09 2.46 7.63 9 63.48 58.27 - 66.84 2.48 3.94 Philippines 28 62.94 55.52 - 73.86 4.39 6.98 22 63.04 55.52 - 73.86 4.46 7.10 6 61.97 57.67 - 69.00 4.53 7.16 Andaman Is. 36 66.21 60.57 - 78.43 4.08 6.05 18 66.21 61.50 - 74.14 3.59 5.36 18 67.30 60.57 - 78.43 4.57 6.72 Nicobar Is. 20 63.22 56.48 - 69.44 4.00 6.30 17 63.12 56.48 - 69.40 4.06 6.44 3 64.34 62.64 - 69.44 3.54 9.46 Borneo 37 63.73 54.63 - 70.23 3.48 5.46 26 63.84 54.63 - 70.23 3.81 5.96 11 63.31 58.31 - 68.80 2.64 4.17 Indonesia 27 62.75 54.69 - 68.87 3.31 5.32 20 62.13 54.69 - 68.87 3.65 5.92 7 63.52 60.26 - 65.19 1.63 2.58 Melanesia 30 67.90 56.77 - 80.45 4.65 6.78 20 67.90 60.81 - 77.64 3.91 5.69 10 68.26 56.77 - 80.45 6.12 8.93 Micronesia 15 64.92 60.62 - 68.45 2.39 3.68 7 66.08 64.24 - 68.45 1.76 2.66 8 63.74 60.62 - 66.74 2.46 3.86 Australia 27 67.90 59.06 - 75.79 4.42 6.53 18 66.61 59.06 - 72.74 3.97 5.97 9 72.43 63.80 - 75.79 4.17 5.90 Africa 29 66.68 59.29 - 73.82 3.70 5.57 18 66.54 59.29 - 71.77 3.26 4.96 11 66.94 61.53 - 73.82 4.27 6.32 Nat. America 33 62.53 56.71 - 69.01 2.84 4.54 10 63.35 59.28 - 69.01 3.03 4.78 23 62.28 56.71 - 67.80 2.73 4.39 Caucasian 29 61.53 55.74 - 66.86 3.22 5.23 15 61.08 56.61 - 66.86 3.28 5.34 14 61.97 55.74 - 66.73 3.27 5.29 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

436 n-ns-ba

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (deg.) (deg.) (%) (deg.) (deg.) (%) (deg.) (deg.) (%)

Siberia 28 84.56 77.97 - 94.87 4.04 4.76 18 84.26 77.97 - 94.87 4.45 5.27 10 85.86 81.89 - 90.75 3.24 3.78 Mongolia 24 84.88 76.32 - 91.73 4.27 5.04 16 84.88 76.32 - 91.73 4.69 5.54 8 84.97 79.79 - 88.44 3.57 4.22 Korea 4 91.62 86.81 - 94.57 3.45 7.58 2 91.62 90.06 - 93.17 2.20 3.60 2 90.69 86.81 - 94.57 5.49 9.07 Ainu 3 86.61 84.87 - 87.11 1.17 2.38 2 86.86 86.61 - 87.11 0.35 0.61 1 84.87 84.87 - 84.87 - - Japan 13 86.82 79.62 - 89.14 2.69 3.14 10 86.97 79.62 - 87.45 2.85 3.34 3 86.41 85.82 - 89.14 1.77 3.56 S. China 6 83.19 80.88 - 90.16 3.51 4.17 3 81.78 80.88 - 84.61 1.95 4.13 3 85.33 81.42 - 90.16 4.38 8.95 N. China 16 84.73 78.71 - 96.70 4.91 5.69 13 85.03 80.34 - 96.70 4.67 5.40 3 84.73 78.71 - 92.36 6.84 14.04 Burma 39 87.74 81.27 - 93.36 3.16 3.61 22 87.56 81.27 - 93.36 3.32 3.80 17 87.79 81.93 - 92.46 3.04 3.48 Laos 24 85.78 77.72 - 90.40 2.55 2.99 16 85.96 81.27 - 90.40 2.29 2.67 8 85.05 77.72 - 86.97 2.96 3.51 Vietnam 23 86.79 81.14 - 95.92 3.70 4.26 14 86.81 82.46 - 95.92 3.70 4.22 9 83.87 81.14 - 91.69 3.51 4.10 Thailand 21 85.30 78.71 - 92.75 3.83 4.52 15 84.77 79.28 - 92.75 3.90 4.61 6 86.77 78.71 - 88.82 3.97 4.66 Cambodia 13 85.20 79.93 - 91.08 3.07 3.61 4 84.20 82.76 - 88.48 2.61 6.14 9 85.81 79.93 - 91.08 3.40 3.99 Philippines 28 86.46 80.20 - 92.85 3.58 4.13 22 86.46 80.20 - 92.85 3.74 4.32 6 87.01 83.23 - 90.02 3.22 3.72 Andaman Is. 36 82.81 75.95 - 90.68 3.86 4.66 18 83.59 75.95 - 90.68 4.18 5.02 18 81.97 76.15 - 86.56 3.49 4.26 Nicobar Is. 20 85.78 79.46 - 93.10 3.55 4.12 17 85.74 79.46 - 93.10 3.51 4.08 3 87.69 80.40 - 88.73 4.54 9.29 Borneo 37 85.52 79.43 - 92.42 3.21 3.74 26 85.44 79.43 - 92.42 3.37 3.94 11 85.92 82.29 - 91.26 2.77 3.20 Indonesia 27 85.56 81.73 - 93.77 3.50 4.03 20 86.72 81.87 - 93.77 3.68 4.20 7 85.03 81.73 - 88.61 2.30 2.70 Melanesia 30 81.37 71.60 - 90.66 4.01 4.93 20 81.36 74.58 - 85.68 3.10 3.82 10 82.13 71.60 - 90.66 5.59 6.85 Micronesia 15 85.26 79.45 - 90.83 3.07 3.62 7 84.56 79.45 - 86.34 2.51 2.99 8 85.42 81.61 - 90.83 3.43 4.01 Australia 27 82.70 76.86 - 92.65 4.68 5.60 18 84.07 77.04 - 92.65 4.66 5.49 9 81.20 76.86 - 87.86 3.59 4.44 Africa 29 83.73 78.44 - 90.33 3.08 3.63 18 84.84 80.51 - 90.33 2.68 3.14 11 83.30 78.44 - 88.52 3.54 4.23 Nat. America 33 88.23 81.86 - 92.85 2.46 2.80 10 86.93 81.86 - 89.79 2.52 2.91 23 88.47 84.23 - 92.85 2.23 2.52 Caucasian 29 89.56 81.05 - 95.09 3.29 3.70 15 89.84 82.14 - 95.09 3.38 3.78 14 88.42 81.05 - 92.57 3.22 3.64 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

437 Appendix 4 Kruskal Wallis results for Angular Data: p-values* for post-hoc non-parametric group comparisons (Bonferonni corrected) Nasion Angle (NAA): Pooled Sex H: 163.90; p:1.09E-23

NA Sib Mon Jap Schi Nchi Bur Lao Viet Thai Cam Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA - - - - 0.004 0.027 - - - - - 0.006 - - - <0.001 0.008 <0.001 0.019 <0.001 Sib - - - 0.014 ------<0.001 0.024 0.038 - <0.001 <0.001 <0.001 0.003 <0.001 Mon ------<0.001 0.017 0.037 - <0.001 0.002 <0.001 0.002 0.002 Jap - 0.003 0.048 - - - - - 0.028 - - - <0.001 0.001 <0.001 - <0.001 Schi 0.042 ------0.002 - 0.003 - 0.004 Nchi - 0.003 0.036 0.003 - 0.022 <0.001 0.002 0.001 0.003 <0.001 <0.001 <0.001 <0.001 - Bur 0.008 - 0.009 - - <0.001 0.003 0.001 0.010 <0.001 <0.001 <0.001 <0.001 0.006 Lao ------<0.001 - <0.001 - <0.001 Viet - - - 0.001 0.029 0.043 - <0.001 0.001 <0.001 0.004 <0.001 Thai ------<0.001 - <0.001 - <0.001 Cam - 0.019 - - - <0.001 0.034 <0.001 0.033 0.002 Phi - - - - <0.001 - <0.001 - <0.001 And - - - 0.006 - 0.014 - <0.001 Nic ------<0.001 Bor - <0.001 - <0.001 - <0.001 Indo <0.001 - <0.001 - <0.001 Mel <0.001 - 0.007 <0.001 Mic 0.001 - <0.001 Aus 0.012 <0.001 Af <0.001 Cauc *significant p-values (p 0.05) only presented here

438

Nasion Angle (NAA): Male-Only H: 111.50; p:6.00E-14

NA Sib Mon Jap Nchi Bur Lao Viet Thai Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA ---0.017------0.002-0.019-<0.001 Sib - - 0.036 - - - - - 0.042 - 0.022 - <0.001 <0.001 <0.001 0.037 <0.001 Mon ------0.028-0.045-<0.0010.003<0.0010.0280.007 Jap 0.008------<0.001<0.001<0.001-<0.001 Nchi - 0.033 - 0.017 0.017 0.003 0.011 0.002 0.017 <0.001 <0.001 <0.001 0.002 - Bur - - - - 0.040 - 0.020 - <0.001 <0.001 <0.001 0.040 <0.001 Lao ------<0.001-0.003-<0.001 Viet - - 0.036 - 0.028 - <0.001 <0.001 <0.001 0.029 <0.001 Thai -----<0.0010.0370.004-<0.001 Phi - - - - <0.001 0.044 0.006 - <0.001 And - - - 0.003 - 0.049 - <0.001 Nic - - 0.026 - - - <0.001 Bor - <0.001 0.030 0.002 - <0.001 Indo <0.001 0.004 <0.001 - <0.001 Mel 0.043 - 0.001 <0.001 Mic - - <0.001 Aus 0.034 <0.001 Af <0.001 Cauc *significant p-values (p 0.05) only presented here

439

Nasion Angle (NAA): Female-Only H:70.07; p:9.72E-9

NA Sib Mon Bur Lao Viet Thai Cam Phi And Bor Indo Mel Mic Aus Af Cauc NA --0.032-----0.002-0.0260.002-<0.0010.0070.020 Sib ------0.018-0.0450.004-<0.001-- Mon ------0.016-0.0430.009-<0.001-- Bur 0.010 - 0.011 - - <0.001 0.039 0.004 <0.001 0.020 <0.001 0.001 - Lao --0.018----0.015-0.001-0.003 Viet - - - 0.032 - - 0.016 - 0.001 - - Thai 0.029------0.022 - 0.012 Cam - 0.002 - 0.011 0.006 0.042 <0.001 0.003 - Phi ------And ----0.024-<0.001 Bor - 0.019 - <0.001 - 0.025 Indo - - 0.044 - 0.005 Mel 0.010 - - <0.001 Mic <0.001 - 0.006 Aus - <0.001 Af 0.001 Cauc *significant p-values (p 0.05) only presented here

440 Nasiofrontal Angle (mNFA): Pooled Sex H: 80.47; p:1.35E-8

NA Sib Mon Jap Schi Nchi Bur Lao Viet Thai Cam Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA - 0.001 - - - - 0.017 - 0.016 ------0.013 - Sib 0.048------Mon - - - 0.014 - - - 0.009 - <0.001 - - 0.037 <0.001 0.007 <0.001 <0.001 <0.001 Jap ------0.017 - - - 0.039 - 0.019 0.003 0.007 Schi ------0.011 - - - 0.036 - 0.018 0.005 0.006 Nchi ------0.013 - - - 0.016 - 0.011 0.001 0.002 Bur - - 0.023 ------0.029 - Lao - - - - <0.001 - - - 0.006 - 0.002 <0.001 <0.001 Viet - - - 0.003 - - - 0.029 - 0.009 0.002 0.004 Thai 0.010 - <0.001 - - 0.035 <0.001 0.020 <0.001 <0.001 <0.001 Cam ------0.038- Phi 0.004 - - - 0.017 - 0.008 0.001 0.003 And 0.011 <0.001 0.020 - - - -- Nic - - 0.009 - 0.006 <0.001 0.002 Bor - 0.008 - 0.003 <0.001 <0.001 Indo 0.026 - 0.013 <0.001 0.004 Mel ---- Mic --- Aus -- Af - Cauc *significant p-values (p 0.05) only presented here

441

Nasiofrontal Angle (mNFA): Male-Only H:69.67; p:7.46E-7

NA Sib Mon Jap Nchi Bur Lao Viet Thai Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA -0.011---0.042------Sib 0.047------Mon - - 0.016 - - - - <0.001 - - 0.027 <0.001 0.034 <0.001 <0.001 0.001 Jap ------0.010 - - - 0.004 - 0.009 0.002 0.011 Nchi - - - - - 0.005 - - - <0.001 - 0.005 <0.001 0.003 Bur ------Lao - - - 0.002 - - - 0.001 - 0.002 <0.001 0.004 Viet ------0.036-0.0480.013- Thai - 0.005 - - - <0.001 - 0.004 <0.001 0.007 Phi 0.007 - - - 0.002 - 0.003 <0.001 0.010 And 0.0070.008------Nic - - <0.001 - 0.003 <0.001 0.008 Bor - 0.002 - 0.009 <0.001 0.012 Indo 0.005 - 0.029 0.001 - Mel 0.043 - - - Mic - 0.014 - Aus -- Af - Cauc *significant p-values (p 0.05) only presented here

442

Nasiofrontal Angle (mNFA): Female-Only H:29.17; p:0.02

NA Sib Mon Bur Lao Viet Thai Cam Phi And Bor Indo Mel Mic Aus Af Cauc NA ----0.0350.008------Sib ----0.036------Mon ------0.009 Bur --0.026------Lao ------Viet ---0.011------0.011 Thai 0.020 0.027 0.005 - - 0.046 0.015 0.026 0.014 0.003 Cam ------Phi ------And 0.020------Bor ----0.0450.029 Indo ----0.028 Mel ---- Mic --- Aus -- Af - Cauc *significant p-values (p 0.05) only presented here

443 mf-n-zyo: Pooled Sex H:61.17; p:1.50E-5

NA Sib Mon Jap Schi Nchi Bur Lao Viet Thai Cam Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA ------0.026<0.001------0.013- Sib ------0.004------Mon ------0.044 - - - 0.019 0.028 0.043 - - Jap ------0.002------0.038 - Schi ------0.016 0.043 0.028 - - Nchi - - - - - 0.026 0.002 ------0.016 - Bur - - - - - <0.001 - - - 0.013 0.031 0.032 - - Lao - - - - 0.023 - - - 0.009 0.020 0.020 - - Viet - - - 0.010 - - - 0.004 0.019 0.015 - - Thai - - 0.021 - - - 0.023 0.036 0.039 - - Cam -0.035------Phi 0.011 - - - <0.001 0.005 0.002 - - And 0.008 0.005 0.003 <0.001 <0.001 <0.001 - 0.003 Nic ------Bor - 0.019 0.043 0.033 - - Indo ----- Mel - - <0.001 0.008 Mic - 0.002 0.036 Aus <0.001 0.034 Af - Cauc *significant p-values (p 0.05) only presented here

444 mf-n-zyo: Female-Only H:39.68; p:8.70E-4

NA Sib Mon Bur Lao Viet Thai Cam Phi And Bor Indo Mel Mic Aus Af Cauc NA ------0.0480.006--0.028--0.036- Sib ------0.018---- Mon ------0.009-0.039-- Bur -----0.017--0.004---- Lao ------0.019---- Viet - - 0.039 0.021 - - 0.033 - - 0.048 - Thai ------Cam ----0.048---- Phi - - - 0.001 - 0.022 - - And 0.030 - <0.001 0.021 0.002 - 0.049 Bor ------Indo 0.002 - 0.026 - - Mel - - <0.001 <0.001 Mic - 0.033 - Aus 0.008 0.018 Af - Cauc *significant p-values (p 0.05) only presented here

445 ns-n-zyo: Pooled Sex H: 138.0; p:8.53E-19

NA Sib Mon Jap Schi Nchi Bur Lao Viet Thai Cam Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA <0.001 <0.001 - - 0.003 ------0.010 <0.001 <0.001 <0.001 0.003 Sib - - 0.005 - 0.002 0.007 - 0.021 0.016 <0.001 <0.001 0.012 <0.001 0.010 <0.001 <0.001 <0.001 <0.001 - Mon - 0.010 - 0.003 0.007 - 0.016 0.014 0.001 <0.001 0.022 <0.001 0.013 <0.001 <0.001 <0.001 <0.001 - Jap ------0.019 - - - 0.008 0.002 <0.001 0.003 - Schi 0.037 - - 0.031 ------0.012 Nchi 0.010 0.020 - 0.039 0.014 0.003 <0.001 0.020 0.002 0.021 <0.001 <0.001 <0.001 <0.001 - Bur ------0.005 <0.001 <0.001 0.001 0.012 Lao ------0.033 0.001 0.001 0.004 0.017 Viet - - - 0.008 - - - <0.001 <0.001 <0.001 <0.001 - Thai ------0.034 0.003 0.004 0.012 0.029 Cam - - - - - 0.022 0.003 0.011 0.004 0.021 Phi - - - - - 0.012 0.007 0.043 0.002 And - - 0.024 - - - - <0.001 Nic - - 0.006 0.002 0.003 0.001 0.043 Bor - 0.044 0.003 0.003 0.004 0.001 Indo 0.001 <0.001 <0.001 <0.001 - Mel - - - <0.001 Mic - - <0.001 Aus - <0.001 Af <0.001 Cauc *significant p-values (p 0.05) only presented here

446

ns-n-zyo: Male-Only H:98.53; p:1.17E-11

NA Sib Mon Jap Nchi Bur Lao Viet Thai Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA 0.0170.042-0.050------0.0100.0370.0120.014 Sib - - - 0.001 0.008 - 0.020 0.004 <0.001 0.018 0.003 0.017 <0.001 <0.001 <0.001 <0.001 - Mon - - 0.005 0.029 - 0.044 0.012 0.001 - 0.008 - <0.001 <0.001 <0.001 <0.001 - Jap ------0.0360.0340.0110.023- Nchi 0.019 0.044 - - 0.018 0.010 - 0.022 - 0.002 0.005 0.001 0.002 - Bur -0.019------0.0070.0240.0160.003 Lao ------0.0100.0280.0200.014 Viet - 0.039 0.003 - 0.043 - <0.001 <0.001 <0.001 <0.001 - Thai ------0.0140.0400.0420.023 Phi - - - - - 0.047 - - 0.005 And 0.023-0.023----<0.001 Nic - - 0.013 0.001 0.007 <0.001 0.040 Bor - - 0.008 0.021 0.010 0.004 Indo 0.011 0.002 0.003 0.001 0.040 Mel ---<0.001 Mic - - <0.001 Aus - <0.001 Af <0.001 Cauc *significant p-values (p 0.05) only presented here

447 ns-n-zyo: Female-Only H:44.26; p:1.80E-4

NA Sib Mon Bur Lao Viet Thai Cam Phi And Bor Indo Mel Mic Aus Af Cauc NA -0.014------0.0460.0190.0040.031- Sib ------0.041--0.0080.0060.0010.014- Mon - - 0.039 - - 0.045 0.016 0.028 - 0.001 0.005 0.002 0.003 - Bur ------0.0290.0110.034- Lao ------0.0390.011-- Viet ------0.0280.0420.008-- Thai ------Cam ----0.0010.0100.0050.005- Phi ------And ------Bor ------Indo - 0.034 0.026 0.030 - Mel - - - 0.001 Mic - - 0.003 Aus - 0.001 Af 0.003 Cauc *significant p-values (p 0.05) only presented here

448 Zygomaxillary Angle (mSSA): Pooled Sex H:161.60; p:3.07E-23

NA Sib Mon Jap Schi Nchi Bur Lao Viet Thai Cam Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA - - - - - 0.042 - - - - - <0.001 - - - <0.001 0.009 <0.001 0.033 <0.001 Sib ------<0.001 - - - <0.001 - <0.001 - <0.001 Mon ------<0.001 - - - <0.001 0.024 <0.001 - <0.001 Jap ------0.008 - - - <0.001 - <0.001 - 0.009 Schi ------0.001 - - - <0.001 - <0.001 - 0.002 Nchi ------0.004 - - - <0.001 - <0.001 - 0.006 Bur 0.009 0.028 - - 0.033 <0.001 0.018 - 0.023 <0.001 - <0.001 - 0.003 Lao - 0.020 - - <0.001 - - - <0.001 0.002 <0.001 0.004 <0.001 Viet 0.037 - - <0.001 - - - <0.001 0.003 <0.001 0.009 <0.001 Thai - - 0.002 0.040 - - <0.001 - <0.001 - 0.003 Cam - 0.032 - - - 0.003 - 0.003 - 0.036 Phi <0.001 - - - <0.001 0.009 <0.001 0.019 <0.001 And <0.001 <0.001 <0.001 0.004 - 0.005 0.003 - Nic - - <0.001 0.005 <0.001 0.013 <0.001 Bor - <0.001 0.024 <0.001 - <0.001 Indo <0.001 0.004 <0.001 0.010 <0.001 Mel 0.003 - <0.001 0.008 Mic 0.004 - - Aus <0.001 0.009 Af 0.006 Cauc *significant p-values (p 0.05) only presented here

449 Zygomaxillary Angle: male-Only H:111.50; p:6.06E-14

NA Sib Mon Jap Nchi Bur Lao Viet Thai Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA -----0.016--0.0450.0210.010--0.004-0.010-- Sib ------0.009---<0.001-0.001-0.031 Mon -----0.044-<0.001---<0.0010.025<0.0010.0220.003 Jap ------0.026 0.037 - - 0.003 - 0.006 - - Nchi - - - - - 0.005 - - - <0.001 - 0.001 - 0.036 Bur 0.005 - - 0.018 0.007 0.002 - 0.015 <0.001 - 0.001 - - Lao - 0.004 - <0.001 - - - <0.001 0.003 <0.001 0.001 <0.001 Viet 0.044 - <0.001 - - - <0.001 0.013 <0.001 0.015 0.002 Thai 0.024 0.014 0.002 - 0.019 <0.001 - 0.005 - - Phi <0.001 - - - <0.001 0.031 <0.001 0.007 <0.001 And <0.001 <0.001 <0.001 - - - 0.033 - Nic - - <0.001 0.002 <0.001 <0.001 <0.001 Bor - <0.001 - <0.001 0.047 0.001 Indo <0.001 0.017 <0.001 0.005 <0.001 Mel - - 0.001 0.043 Mic --- Aus 0.007 - Af - Cauc *significant p-values (p 0.05) only presented here

450

Zygomaxillary Angle: Female-Only H:62.86; p:1.71E-7

NA Sib Mon Bur Lao Viet Thai Cam Phi And Bor Indo Mel Mic Aus Af Cauc NA ------<0.001--<0.0010.047<0.001-<0.001 Sib ------0.014--0.004-<0.001-0.024 Mon ------0.007-0.005-- Bur -----0.043--<0.001-0.001-0.016 Lao ----0.021--0.012-0.014-0.037 Viet - - - 0.003 - - <0.001 - <0.001 - 0.005 Thai - - 0.015 - - 0.009 - 0.004 - 0.048 Cam ----0.033-0.017-- Phi 0.033 - - 0.006 - 0.004 - 0.029 And 0.010 0.018 0.004 - 0.009 0.011 - Bor - <0.001 - <0.001 - 0.006 Indo 0.004 - 0.002 - 0.012 Mel 0.012 - 0.001 - Mic 0.008 - - Aus 0.001 0.035 Af 0.011 Cauc *significant p-values (p 0.05) only presented here

451 ns-n-ba: Pooled Sex H:148.30; p:9.97E-21

NA Sib Mon Jap Schi Nchi Bur Lao Viet Thai Cam Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA 0.028 ------<0.001 - - - <0.001 0.001 <0.001 <0.001 - Sib - - - 0.011 0.002 - - - - - 0.006 - - 0.046 <0.001 - 0.003 0.027 0.004 Mon ------0.002 - - - <0.001 - 0.001 0.009 - Jap ------0.001 - - - <0.001 0.029 0.002 0.007 - Schi - 0.040 ------0.005 - 0.046 - 0.048 Nchi - - - 0.020 - - <0.001 - 0.031 - <0.001 0.002 <0.001 <0.001 - Bur 0.029 - 0.002 - - <0.001 0.045 0.005 - <0.001 <0.001 <0.001 <0.001 - Lao - - - - <0.001 - - - <0.001 0.012 <0.001 <0.001 - Viet - - - <0.001 - - - <0.001 0.006 <0.001 <0.001 - Thai - - 0.005 - - - <0.001 - 0.003 0.021 0.008 Cam - 0.002 - - - <0.001 0.048 0.002 0.013 - Phi <0.001 - - - <0.001 0.018 <0.001 <0.001 - And 0.004 <0.001 <0.001 - - - - <0.001 Nic - - <0.001 - 0.003 0.016 - Bor - <0.001 - <0.001 0.004 0.018 Indo <0.001 0.003 <0.001 <0.001 - Mel <0.001 - 0.040 <0.001 Mic 0.041 - <0.001 Aus - <0.001 Af <0.001 Cauc *significant p-values (p 0.05) only presented here

452 ns-n-ba: Male-Only H:97.55; p:1.72E-11

NA Sib Mon Jap Nchi Bur Lao Viet Thai Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA ------0.029---<0.0010.025--- Sib --0.0260.012-0.022-----0.048<0.001---0.015 Mon ------0.023---<0.0010.0190.0250.042- Jap ------0.029 - - - <0.001 0.003 0.039 0.029 - Nchi - - - 0.026 - 0.003 - 0.044 - <0.001 0.002 0.002 0.002 - Bur - - 0.012 - <0.001 - 0.026 - <0.001 <0.001 <0.001 <0.001 - Lao - - - 0.003 - - - <0.001 0.001 0.004 0.004 - Viet 0.022 - <0.001 - 0.043 - <0.001 <0.001 <0.001 <0.001 - Thai ----0.048<0.001---0.015 Phi 0.003 - - - <0.001 0.006 0.003 0.004 - And 0.024 0.046 <0.001 0.043 - - - <0.001 Nic - - <0.001 0.031 0.028 0.031 - Bor - <0.001 0.036 0.032 - 0.023 Indo <0.001 0.001 <0.001 0.002 - Mel - - 0.013 <0.001 Mic - - <0.001 Aus - <0.001 Af <0.001 Cauc *significant p-values (p 0.05) only presented here

453

ns-n-ba: Female-Only H:61.95; p:2.45E-7

NA Sib Mon Bur Lao Viet Thai Cam Phi And Bor Indo Mel Mic Aus Af Cauc NA ------<0.001--<0.001-<0.0010.002- Sib ------0.045-0.006-- Mon ------0.011-- Bur -----<0.001--<0.001-<0.0010.001- Lao ----0.016--0.023-0.0060.043- Viet - - - 0.027 - - 0.040 - 0.005 - - Thai - - 0.043 - - 0.046 - 0.015 - - Cam - 0.002 - - 0.006 - 0.001 0.040 - Phi -----0.016-- And 0.001 0.006 - 0.024 - - <0.001 Bor - 0.003 - <0.001 0.039 - Indo 0.005 - 0.004 0.046 - Mel 0.015 - - 0.001 Mic 0.004 0.040 - Aus - <0.001 Af 0.003 Cauc *significant p-values (p 0.05) only presented here

454 n-ns-zyo: Pooled Sex H: 114.50; p:1.69E-14

NA Sib Mon Jap Schi Nchi Bur Lao Viet Thai Cam Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA 0.012 <0.001 <0.001 0.002 <0.001 - 0.009 0.005 <0.001 0.032 - - - - - 0.013 0.005 - 0.011 - Sib ------0.028 - - - - - 0.012 <0.001 <0.001 Mon - - - 0.003 - - - - 0.001 <0.001 0.031 0.003 0.001 0.013 - <0.001 <0.001 <0.001 Jap - - 0.005 - - - - 0.004 <0.001 0.019 0.004 0.003 0.016 - <0.001 <0.001 <0.001 Schi - 0.040 - - - - 0.021 0.006 - 0.037 0.014 - - 0.005 <0.001 <0.001 Nchi 0.001 - - - 0.039 0.001 <0.001 0.010 0.001 0.001 0.008 - <0.001 <0.001 <0.001 Bur - 0.023 0.017 ------0.005 - Lao ------0.011 <0.001 <0.001 Viet - - 0.026 0.014 - 0.027 0.032 - - 0.004 <0.001 <0.001 Thai - 0.010 0.001 - 0.035 0.004 - - <0.001 <0.001 <0.001 Cam ------0.032 <0.001 0.002 Phi ------0.003 0.031 And - - - - 0.021 - <0.001 0.009 Nic - - - - - 0.003 0.012 Bor - - - - <0.001 0.012 Indo - - - 0.003 0.028 Mel - 0.014 <0.001 <0.001 Mic 0.003 <0.001 <0.001 Aus 0.041 - Af - Cauc *significant p-values (p 0.05) only presented here

455

n-ns-zyo: Male-Only H:65.73; p:3.06E-6

NA Sib Mon Jap Nchi Bur Lao Viet Thai Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA -0.0110.0210.024---0.025------Sib ------0.0480.013-0.0480.0400.031-0.0070.0020.008 Mon - - 0.019 - - - 0.044 0.003 - - 0.009 0.008 - <0.001 <0.001 <0.001 Jap - 0.018 - - - 0.047 0.006 - 0.041 0.017 0.014 - 0.001 0.001 0.001 Nchi 0.005 - - - 0.012 0.003 0.045 0.012 0.010 0.008 - <0.001 <0.001 0.002 Bur --0.037------Lao ------0.0140.0050.012 Viet ------0.0170.0090.029 Thai - 0.008 - - 0.015 0.015 - <0.001 <0.001 0.001 Phi ------0.0110.049 And ------Nic - - - - 0.029 0.011 0.018 Bor ----0.039- Indo ----- Mel - 0.028 0.019 - Mic 0.012 0.012 0.027 Aus -- Af - Cauc *significant p-values (p 0.05) only presented here

456 n-ns-zyo: Female-Only H:44.26; p:1.80E-4

NA Sib Mon Bur Lao Viet Thai Cam Phi And Bor Indo Mel Mic Aus Af Cauc NA -0.014------0.0460.0190.0040.031- Sib ------0.041--0.0080.0060.0010.014- Mon - - 0.039 - - 0.045 0.016 0.028 - 0.001 0.005 0.002 0.003 - Bur ------0.0290.0110.034- Lao ------0.0390.011-- Viet ------0.0280.0420.008-- Thai ------Cam ----0.0010.0100.0050.005- Phi ------And ------Bor ------Indo - 0.034 0.026 0.030 - Mel - - - 0.001 Mic - - 0.003 Aus - 0.001 Af 0.003 Cauc *significant p-values (p 0.05) only presented here

457 Nasospinale Angle (NS): Pooled Sex H:156.40; p:2.96E-22

NA Sib Mon Jap Schi Nchi Bur Lao Viet Thai Cam Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA <0.001 - - - 0.039 - 0.005 - 0.004 - 0.016 - <0.001 0.023 0.005 <0.001 <0.001 <0.001 - <0.001 Sib - 0.010 0.011 - 0.004 <0.001 0.007 <0.001 - <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 0.029 <0.001 Mon - 0.036 - - <0.001 - <0.001 - 0.001 0.011 <0.001 0.002 <0.001 <0.001 <0.001 <0.001 - <0.001 Jap ------0.028 - - 0.005 0.036 - - <0.001 Schi ------0.039 - - - <0.001 Nchi - 0.002 - 0.002 - 0.006 0.035 0.002 0.007 0.003 <0.001 <0.001 <0.001 - <0.001 Bur - - 0.031 - 0.035 - <0.001 - 0.008 <0.001 0.003 0.007 - <0.001 Lao - - - - - 0.046 - - 0.023 - - - <0.001 Viet 0.034 - - - 0.004 - 0.041 <0.001 0.007 0.010 - <0.001 Thai ------<0.001 Cam - - 0.045 - - 0.039 - - - <0.001 Phi ------<0.001 And 0.002 - 0.025 <0.001 0.010 0.030 - <0.001 Nic 0.041 - - - - 0.006 <0.001 Bor - 0.023 - - - <0.001 Indo - - - 0.020 <0.001 Mel - - 0.001 <0.001 Mic - 0.021 <0.001 Aus 0.029 <0.001 Af <0.001 Cauc *significant p-values (p 0.05) only presented here

458 Nasospinale Angle (NS): Male-Only H:107.80; p:2.67E-13

NA Sib Mon Jap Nchi Bur Lao Viet Thai Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA 0.010------0.037--0.0040.016--<0.001 Sib - 0.042 - 0.005 <0.001 0.046 <0.001 <0.001 0.043 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 - <0.001 Mon - - - 0.023 - 0.011 0.005 - 0.001 0.014 0.005 <0.001 0.001 0.002 - <0.001 Jap ------0.0050.013--<0.001 Nchi - 0.014 - 0.013 0.006 - 0.009 0.016 0.017 <0.001 0.002 0.004 - <0.001 Bur -----0.010--0.0010.018--<0.001 Lao ------0.043---<0.001 Viet - - - 0.031 - - 0.002 0.021 - - <0.001 Thai - 0.044 - - - 0.029 - - - <0.001 Phi 0.009------0.030<0.001 And 0.003 0.042 0.032 <0.001 0.003 0.012 - <0.001 Nic -----0.012<0.001 Bor -----<0.001 Indo ----<0.001 Mel - - 0.005 <0.001 Mic - 0.037 <0.001 Aus 0.039 <0.001 Af <0.001 Cauc *significant p-values (p 0.05) only presented here

459 Basion Angle (BAA): Pooled Sex H: 137.10; p:1.25E-18

NA Sib Mon Jap Schi Nchi Bur Lao Viet Thai Cam Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA 0.025 0.004 ------0.015 <0.001 0.006 0.016 - <0.001 <0.001 <0.001 <0.001 - Sib - 0.015 - - - - 0.024 - 0.005 <0.001 <0.001 <0.001 <0.001 0.002 <0.001 <0.001 <0.001 <0.001 - Mon 0.009 - - 0.010 - 0.005 0.017 0.001 <0.001 <0.001 <0.001 <0.001 0.001 <0.001 <0.001 <0.001 <0.001 0.033 Jap - 0.049 ------0.025 - - - 0.008 0.015 0.010 - - Schi ------0.025 - - - 0.017 0.014 0.015 0.046 - Nchi - - - - 0.014 0.002 <0.001 <0.001 0.002 0.018 <0.001 <0.001 <0.001 <0.001 - Bur - - - - 0.028 <0.001 0.010 0.032 - <0.001 <0.001 <0.001 <0.001 - Lao - - 0.032 0.003 <0.001 0.002 0.004 - <0.001 <0.001 <0.001 <0.001 - Viet - - 0.031 <0.001 0.014 - - <0.001 <0.001 <0.001 0.002 - Thai - - 0.009 - - - 0.003 0.017 0.004 0.031 - Cam -----0.039---- Phi ------0.015 And - 0.020 0.004 - - - - <0.001 Nic ------0.009 Bor - 0.006 0.046 0.013 - 0.023 Indo <0.001 0.005 0.001 0.014 - Mel - - - <0.001 Mic - - <0.001 Aus - <0.001 Af <0.001 Cauc *significant p-values (p 0.05) only presented here

460

Basion Angle (BAA): Male-Only H:98.37; p:1.24E-11

NA Sib Mon Jap Nchi Bur Lao Viet Thai Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA -0.048------0.010---0.0100.0040.0150.035- Sib - 0.047 - 0.033 - - - <0.001 <0.001 0.001 <0.001 0.003 <0.001 <0.001 <0.001 <0.001 0.040 Mon 0.014 - 0.006 0.020 0.016 0.021 <0.001 <0.001 <0.001 <0.001 0.001 <0.001 <0.001 <0.001 <0.001 0.018 Jap ------0.012 - - - 0.009 0.002 0.021 - - Nchi - - - - 0.002 <0.001 0.005 0.007 0.026 <0.001 <0.001 <0.001 0.002 - Bur - - - - 0.004 - - - 0.002 0.006 0.005 0.019 - Lao - - 0.020 0.001 0.028 - - <0.001 <0.001 0.002 0.011 - Viet - 0.018 0.001 0.045 - - <0.001 <0.001 0.002 0.010 - Thai - 0.005 - - - 0.003 0.005 0.009 0.032 - Phi ------And -0.0320.009----0.008 Nic ------Bor - 0.025 0.025 - - - Indo 0.002 0.002 0.012 - - Mel - - - 0.004 Mic - - 0.004 Aus - 0.014 Af 0.049 Cauc *significant p-values (p 0.05) only presented here

461

Basion Angle (BAA): Female-Only H:46.77; p:7.39E-5

NA Sib Mon Bur Lao Viet Thai Cam Phi And Bor Indo Mel Mic Aus Af Cauc NA ------0.005--0.0040.032<0.0010.007- Sib ------0.0040.044-0.0060.0160.0020.015- Mon ------0.009--0.0090.0430.0050.015- Bur -----0.010--0.008-0.0050.016- Lao 0.024 - - - 0.005 0.037 - 0.003 0.024 <0.001 0.010 - Viet ------0.006-- Thai ------Cam ------Phi ------And ------0.002 Bor -----0.048 Indo ----- Mel - - - 0.005 Mic - - 0.021 Aus - 0.002 Af 0.017 Cauc *significant p-values (p 0.05) only presented here

462 Nasion Angle (NBA): Pooled Sex H:132.20; p:1.03E-17

NA Sib Mon Jap Schi Nchi Bur Lao Viet Thai Cam Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA 0.020 - 0.011 0.006 0.007 0.005 <0.001 <0.001 - 0.002 0.027 <0.001 0.005 <0.001 0.002 0.010 <0.001 - 0.032 - Sib - <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 0.002 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 0.018 - - Mon - - - - 0.009 0.005 - 0.042 - 0.033 - 0.003 - - 0.030 --- Jap ------0.013 <0.001 0.001 Schi ------0.005 0.002 0.002 Nchi ------0.014 <0.001 0.002 Bur - 0.044 ------0.011 <0.001 <0.001 Lao ------<0.001<0.001<0.001 Viet - - 0.029 - - - - 0.016 - <0.001 <0.001 <0.001 Thai ------0.003 0.012 Cam ------0.004 <0.001 <0.001 Phi - - 0.035 - - - 0.040 <0.001 0.002 And - - - - - <0.001 <0.001 <0.001 Nic - - - - 0.009 <0.001 <0.001 Bor - 0.044 - <0.001 <0.001 <0.001 Indo - - 0.003 <0.001 <0.001 Mel - 0.021 <0.001 0.001 Mic <0.001 <0.001 <0.001 Aus 0.038 - Af - Cauc *significant p-values (p 0.05) only presented here

463

Nasion Angle (NBA): Male-Only H:93.78; p:7.74E-11

NA Sib Mon Jap Nchi Bur Lao Viet Thai Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA -----0.0110.0150.022-0.014-0.021--0.037--- Sib - <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 0.003 0.001 0.031 - - Mon 0.008 0.005 0.002 <0.001 0.001 <0.001 0.004 <0.001 0.002 <0.001 0.002 0.029 0.014 - - - Jap ------0.0210.0030.008 Nchi ------0.0340.0020.033 Bur ------0.0310.0010.019 Lao - - 0.041 - - - - 0.019 - <0.001 <0.001 <0.001 Viet - 0.050 - - - - 0.014 - 0.001 <0.001 0.001 Thai -----0.049-0.002<0.0010.003 Phi ------0.004- And - - - 0.032 - <0.001 <0.001 0.002 Nic - - - - 0.029 0.002 0.011 Bor - 0.023 - <0.001 <0.001 <0.001 Indo - - 0.014 <0.001 0.004 Mel - - 0.015 - Mic 0.007 0.003 0.002 Aus -- Af - Cauc *significant p-values (p 0.05) only presented here

464 Nasion Angle (NBA): Female-Only H:63.62; p:1.27E-7

NA Sib Mon Bur Lao Viet Thai Cam Phi And Bor Indo Mel Mic Aus Af Cauc NA - 0.004 - 0.025 0.002 - 0.004 - 0.004 0.001 - 0.010 0.004 - 0.035 - Sib 0.008 0.022 0.011 0.002 - 0.010 - 0.003 0.001 0.045 0.010 0.008 - - - Mon ---0.008------0.0220.0030.004 Bur --0.022------0.0070.009 Lao -0.011------0.0490.0070.006 Viet 0.002------0.0080.002<0.001 Thai 0.010 - 0.003 0.001 0.045 0.010 0.008 - - - Cam ------0.0170.0040.002 Phi ------And ----0.0340.003<0.001 Bor - - - 0.025 0.001 0.001 Indo - - - 0.037 0.028 Mel - 0.028 0.003 0.003 Mic 0.022 0.003 0.004 Aus -- Af - Cauc *significant p-values (p 0.05) only presented here

465 Basion Angle (BBA): Pooled Sex H:76.12; p:6.97E-8

NA Sib Mon Jap Schi Nchi Bur Lao Viet Thai Cam Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA - 0.026 0.003 - - - 0.021 0.006 0.015 0.036 - - - 0.009 0.011 0.008 0.003 - - - Sib - 0.007 - - - 0.018 0.019 0.014 0.028 - - - 0.008 0.016 0.007 0.005 - - - Mon <0.001 - 0.002 <0.001 <0.001 <0.001 <0.001 0.001 0.001 0.001 0.002 <0.001 <0.001 <0.001 <0.001 0.029 - - Jap ------0.008 - - - - - 0.007 0.003 0.003 Schi ------Nchi ------0.025 Bur ------0.036 0.015 Lao ------0.026 0.009 0.004 Viet - - - 0.028 - - - - - 0.014 0.006 0.002 Thai - - 0.044 - - - - - 0.020 0.005 0.003 Cam ------0.049 0.015 0.011 Phi - - - - - 0.035 - - 0.019 And - - - 0.023 0.005 - - 0.026 Nic ------0.015 Bor - - - 0.014 0.003 0.001 Indo - - 0.011 0.009 0.003 Mel - 0.012 0.005 0.003 Mic 0.003 0.002 0.002 Aus -- Af - Cauc *significant p-values (p 0.05) only presented here

466 Basion Angle (BBA): Male-Only H:42.26; p:0.005

NA Sib Mon Jap Nchi Bur Lao Viet Thai Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA --0.026------0.014--- Sib -0.012--0.034-0.027------0.042--- Mon <0.001 0.015 0.014 0.002 0.005 0.001 0.012 0.012 0.014 0.001 0.003 0.004 0.001 - - - Jap - 0.044 - - - 0.030 0.041 - - - - - 0.010 0.012 0.042 Nchi ------Bur ------Lao ------0.021- Viet ------Thai ------0.0290.015- Phi -----0.039--- And ----0.044--- Nic ------Bor ----0.027- Indo - - - 0.049 - Mel - - 0.043 - Mic 0.012 0.016 - Aus -- Af - Cauc *significant p-values (p 0.05) only presented here

467 Basion Angle (BBA): Female-Only H:36.85; p:0.002

NA Sib Mon Bur Lao Viet Thai Cam Phi And Bor Indo Mel Mic Aus Af Cauc NA ----0.044-0.040--0.050-0.021---0.039 Sib ------0.038---- Mon 0.025 0.027 0.006 - 0.011 - 0.026 0.005 0.043 0.003 0.011 - - - Bur ------0.022 Lao ------0.027 Viet ------0.0470.0230.006 Thai ------Cam ------0.0400.006 Phi ------And - - 0.023 - - - 0.028 Bor ----0.0360.004 Indo ----0.033 Mel - 0.040 0.036 0.004 Mic - 0.028 0.013 Aus -- Af - Cauc *significant p-values (p 0.05) only presented here

468 Parietal Angle 1 (mPAA1): Pooled Sex H:126.50; p:1.14E-16

NA Sib Mon Jap Schi Nchi Bur Lao Viet Thai Cam Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA 0.016 <0.001 - - 0.009 0.002 0.015 - <0.001 0.006 0.003 <0.001 - - <0.001 - - - - - Sib ------0.004 - - 0.004 0.002 0.038 0.047 <0.001 0.006 <0.001 0.018 - Mon 0.023 - - - - 0.048 - - - - <0.001 <0.001 - <0.001 <0.001 <0.001 <0.001 - Jap - - - - - 0.007 - - 0.009 - - 0.015 - ---- Schi ------0.016 - - 0.033 0.037 0.025 - - Nchi ------0.001 0.025 - 0.001 0.002 <0.001 0.026 - Bur - - 0.019 - - 0.040 <0.001 0.006 - <0.001 0.002 <0.001 0.005 - Lao - - - - - 0.002 - - 0.001 0.007 <0.001 - - Viet 0.002 - - 0.004 - - 0.010 - - 0.022 - - Thai - - - <0.001 <0.001 - <0.001 <0.001 <0.001 <0.001 0.003 Cam - - <0.001 0.010 - <0.001 0.003 <0.001 0.007 - Phi - <0.001 0.005 - <0.001 0.002 <0.001 0.004 - And <0.001 <0.001 - <0.001 <0.001 <0.001 <0.001 0.003 Nic - <0.001 - - - - 0.005 Bor <0.001 0.041 - 0.042 - - Indo <0.001 <0.001 <0.001 <0.001 0.032 Mel - - - 0.007 Mic - - 0.032 Aus - 0.005 Af - Cauc *significant p-values (p 0.05) only presented here

469

Parietal Angle 2 (mPAA2): Pooled Sex H:150.70; p:3.51E-21

NA Sib Mon Jap Schi Nchi Bur Lao Viet Thai Cam Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA - - <0.001 0.020 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 0.026 0.008 <0.001 0.030 <0.001 - 0.038 0.003 Sib - 0.032 - <0.001 0.035 0.005 0.012 <0.001 0.012 <0.001 <0.001 - - <0.001 - 0.025 - - - Mon - - 0.002 - 0.012 0.035 <0.001 0.037 0.002 <0.001 - - <0.001 - 0.041 --- Jap - - - - - 0.045 - - <0.001 - - - - - 0.002 0.020 - Schi ------0.009-----0.031-- Nchi ------0.010 0.003 0.002 - 0.001 - <0.001 <0.001 0.005 Bur - - 0.008 - 0.029 <0.001 - - - - - 0.001 0.028 - Lao - - - - <0.001 0.037 0.020 - 0.014 - <0.001 0.005 - Viet 0.048 - - <0.001 - 0.037 - - - <0.001 0.007 - Thai - - 0.010 <0.001 <0.001 - <0.001 - <0.001 <0.001 <0.001 Cam - 0.003 - 0.040 - 0.045 - 0.001 0.005 - Phi 0.012 0.002 0.001 - 0.001 - <0.001 <0.001 0.004 And <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 Nic -0.002----- Bor <0.001 - - 0.018 - - Indo <0.001 - <0.001 <0.001 0.003 Mel - 0.041 - - Mic <0.001 0.020 - Aus - 0.006 Af - Cauc *significant p-values (p 0.05) only presented here

470 Parietal Angle 1 (mPAA1): Male-Only H:75.11; p:1.01E-7

NA Sib Mon Jap Nchi Bur Lao Viet Thai Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA ------0.037------0.029-- Sib ------0.024--0.020--0.023-0.002-- Mon 0.048------0.0010.007-0.002-<0.0010.005- Jap - - - - 0.008 0.030 - - - 0.021 - - 0.037 - - Nchi ------0.013--0.026-0.003-- Bur -----0.007--0.008-<0.0010.035- Lao ----0.022--0.024-0.001-- Viet - - - 0.025 - - 0.026 - 0.003 - - Thai - - <0.001 <0.001 - <0.001 0.006 <0.001 <0.001 - Phi - <0.001 0.001 - <0.001 0.035 <0.001 0.001 - And <0.001 0.012 - 0.003 - <0.001 0.011 - Nic -<0.001----0.014 Bor <0.001 - - 0.029 - - Indo <0.001 0.025 <0.001 0.001 - Mel - - - 0.035 Mic --- Aus 0.026 0.002 Af - Cauc *significant p-values (p 0.05) only presented here

471

Parietal Angle 1 (mPAA1): Female-Only H:68.87; p:1.57E-8

NA Sib Mon Bur Lao Viet Thai Cam Phi And Bor Indo Mel Mic Aus Af Cauc NA0.0070.0020.0020.014-0.0030.003-<0.001-0.004----- Sib ------0.006--0.0030.004--- Mon - - 0.039 - - 0.024 0.012 - - 0.002 0.002 - - - Bur ----0.0390.018--0.0020.002--- Lao 0.049------0.0120.008--- Viet 0.0200.034-0.003-0.026----- Thai - 0.038 - 0.031 - 0.011 0.006 0.026 - 0.023 Cam 0.039 - - - 0.003 0.003 - 0.048 - Phi <0.001-0.018----- And <0.001 - <0.001 <0.001 <0.001 0.003 <0.001 Bor 0.038 - 0.030 - - - Indo 0.003 0.004 - - - Mel ---- Mic - - 0.047 Aus -- Af - Cauc *significant p-values (p 0.05) only presented here

472 Appendix 5 Summary Statistics for Indices Length/Breadth (anterior)

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (%) (%) (%) (%) (%) (%) (%) (%) (%)

Siberia 28 62.47 47.99 - 75.84 6.88 10.82 18 60.88 47.99 - 74.55 7.00 11.39 10 68.04 61.12 - 75.84 4.78 7.08 Mongolia 24 63.75 58.51 - 73.59 4.42 6.76 16 63.71 59.40 - 73.16 3.62 5.62 8 69.27 58.51 - 73.59 5.51 8.21 Korea 4 64.43 58.46 - 69.85 5.70 17.74 1 69.85 69.85 - 69.85 - - 2 61.44 58.46 - 64.43 4.22 10.31 Ainu 3 61.19 60.22 - 76.80 9.31 24.65 2 60.71 60.22 - 61.19 0.68 1.69 1 76.80 76.80 - 76.80 - - Japan 13 59.98 52.50 - 74.03 5.11 8.33 10 59.90 52.50 - 64.63 3.56 5.93 3 64.60 58.14 - 74.03 7.99 21.33 S. China 6 66.58 54.69 - 69.00 5.92 9.18 3 68.85 68.70 - 69.00 0.21 0.53 3 63.26 54.69 - 66.58 6.13 17.45 N. China 16 62.65 50.94 - 70.87 5.71 9.18 13 61.26 53.51 - 70.87 5.05 8.10 3 65.95 50.94 - 68.73 9.57 27.07 Burma 39 64.31 53.75 - 76.33 4.87 7.49 22 64.08 59.44 - 71.61 3.92 6.02 17 64.31 53.75 - 76.33 6.01 9.26 Laos 24 66.67 60.45 - 79.05 5.24 7.73 16 66.67 60.45 - 79.05 5.72 8.44 8 66.51 62.50 - 75.23 4.48 6.61 Vietnam 23 64.42 55.61 - 73.16 4.47 6.94 14 64.95 60.37 - 73.16 3.81 5.83 9 64.24 55.61 - 70.50 5.23 8.30 Thailand 21 68.67 58.21 - 73.45 3.93 5.76 15 67.49 58.21 - 73.44 3.68 5.43 6 70.27 61.44 - 73.45 4.80 6.98 Cambodia 13 67.44 61.04 - 72.84 4.00 5.98 4 69.32 63.86 - 72.84 3.71 10.77 9 67.05 61.04 - 71.44 4.05 6.13 Philippines 28 66.14 57.80 - 73.15 4.21 6.36 22 66.13 57.80 - 73.15 4.42 6.68 6 66.14 60.46 - 71.49 3.65 5.54 Andaman Is. 36 64.26 57.99 - 71.66 3.52 5.44 18 64.48 59.52 - 71.66 3.38 5.16 18 63.96 57.99 - 68.89 3.54 5.55 Nicobar Is. 20 61.09 53.85 - 66.10 3.56 5.84 17 61.15 53.85 - 66.10 3.27 5.34 3 60.24 54.28 - 65.91 5.82 16.92 Borneo 37 63.82 56.98 - 71.86 4.06 6.33 26 63.24 56.98 - 71.18 4.19 6.55 11 63.82 58.30 - 71.86 3.91 6.07 Indonesia 27 67.51 55.41 - 73.67 4.99 7.53 20 66.76 55.41 - 73.09 4.73 7.17 7 68.91 58.25 - 73.67 5.97 8.86 Melanesia 30 57.64 46.99 - 63.86 3.83 6.66 20 57.63 46.99 - 63.86 3.95 6.93 10 58.71 53.96 - 63.83 3.57 6.11 Micronesia 15 62.01 57.24 - 69.23 3.39 5.42 7 64.87 58.67 - 69.23 3.67 5.73 8 61.33 57.24 - 65.44 2.64 4.32 Australia 27 57.20 52.95 - 63.04 2.82 4.91 18 56.94 53.07 - 63.04 3.13 5.44 9 58.00 52.95 - 59.66 2.22 3.88 Africa 29 60.74 50.19 - 68.04 4.70 7.80 18 59.37 51.32 - 65.48 4.42 7.47 11 62.55 50.19 - 68.04 4.85 7.84 Nat. America 33 60.89 48.48 - 69.32 4.67 7.75 10 60.80 48.48 - 69.32 6.18 10.45 23 61.20 52.99 - 68.03 3.92 6.46 Caucasian 29 64.40 51.99 - 71.21 4.37 6.90 15 63.93 51.99 - 69.49 4.67 7.42 14 64.93 55.59 - 71.21 4.15 6.50 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980) 473 Length/Breadth (posterior)

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (%) (%) (%) (%) (%) (%) (%) (%) (%)

Siberia 28 61.92 54.82 - 80.08 5.78 9.06 18 61.92 54.82 - 80.08 6.36 9.98 10 63.35 56.60 - 71.87 4.87 7.61 Mongolia 24 63.55 60.55 - 75.86 4.37 6.71 16 63.29 60.75 - 73.02 4.04 6.21 8 63.55 60.55 - 75.86 5.27 8.04 Korea 4 65.57 54.24 - 67.32 7.10 22.77 1 67.32 67.32 - 67.32 - - 2 59.90 54.24 - 65.57 8.01 20.05 Ainu 3 60.74 60.28 - 71.09 6.12 16.71 2 60.51 60.28 - 60.74 0.33 0.81 1 71.09 71.09 - 71.09 - - Japan 13 62.05 54.15 - 67.64 3.59 5.79 10 61.52 54.15 - 65.23 2.99 4.87 3 66.91 58.34 - 67.64 5.17 14.08 S. China 6 64.11 62.95 - 68.27 2.09 3.23 3 64.01 63.56 - 64.46 0.63 1.73 3 64.11 62.95 - 68.27 2.80 7.51 N. China 16 62.04 57.17 - 69.13 3.43 5.55 13 61.86 57.17 - 67.06 2.96 4.81 3 63.76 58.25 - 69.13 5.44 14.93 Burma 39 64.48 54.67 - 70.74 3.68 5.79 22 62.61 54.67 - 70.74 3.69 5.88 17 64.63 59.02 - 70.11 3.57 5.54 Laos 24 63.93 58.19 - 74.27 3.75 5.78 16 63.47 58.19 - 74.27 4.20 6.51 8 66.28 61.64 - 69.48 2.76 4.21 Vietnam 23 61.36 55.54 - 70.36 3.67 5.92 14 60.99 55.54 - 70.36 3.70 5.96 9 62.12 55.90 - 68.04 3.85 6.21 Thailand 21 64.27 59.51 - 70.46 3.16 4.89 15 64.16 60.07 - 70.31 2.46 3.85 6 67.28 59.51 - 70.46 4.44 6.74 Cambodia 13 64.90 57.43 - 69.03 3.49 5.38 4 65.27 61.95 - 68.79 3.04 9.30 9 64.90 57.43 - 69.03 3.82 5.91 Philippines 28 62.36 58.44 - 70.65 3.37 5.31 22 62.46 58.89 - 70.65 3.26 5.13 6 62.08 58.44 - 70.29 4.00 6.37 Andaman Is. 36 61.60 55.54 - 68.34 2.87 4.68 18 61.40 55.54 - 66.39 3.02 4.92 18 61.74 56.65 - 68.34 2.81 4.58 Nicobar Is. 20 59.42 52.55 - 63.32 2.92 4.96 17 59.18 52.55 - 63.32 3.08 5.24 3 60.48 57.80 - 61.41 1.88 5.48 Borneo 37 61.63 55.43 - 68.06 3.28 5.29 26 61.59 57.23 - 68.06 3.03 4.86 11 61.69 55.43 - 67.43 3.73 6.13 Indonesia 27 62.74 57.34 - 69.77 3.53 5.60 20 62.16 57.34 - 69.77 3.59 5.74 7 65.57 60.72 - 69.63 3.02 4.66 Melanesia 30 61.36 55.51 - 68.75 2.75 4.49 20 61.47 55.51 - 68.75 3.09 5.01 10 61.23 57.54 - 64.48 2.01 3.30 Micronesia 15 59.08 55.79 - 67.08 3.64 6.01 7 60.84 57.68 - 67.08 3.57 5.80 8 58.45 55.79 - 66.13 3.63 6.10 Australia 27 59.20 55.48 - 65.40 2.35 3.95 18 59.09 55.62 - 65.40 2.53 4.24 9 59.72 55.48 - 61.81 2.09 3.52 Africa 29 59.58 52.80 - 65.11 2.75 4.63 18 60.38 53.82 - 62.34 2.31 3.87 11 58.62 52.80 - 65.11 3.34 5.70 Nat. America 33 61.68 55.78 - 70.51 3.44 5.57 10 62.30 57.14 - 70.51 4.92 7.83 23 61.50 55.78 - 66.42 2.71 4.42 Caucasian 29 60.77 54.49 - 67.51 3.90 6.38 15 62.01 54.49 - 67.51 3.85 6.23 14 60.55 54.80 - 67.28 3.89 6.47 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

474 Length/Height

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (%) (%) (%) (%) (%) (%) (%) (%) (%)

Siberia 28 77.03 67.55 - 83.50 3.80 4.99 18 75.03 67.55 - 80.89 3.57 4.74 10 77.89 68.62 - 83.50 4.09 5.30 Mongolia 24 76.45 67.30 - 84.40 4.40 5.76 16 76.01 67.30 - 84.40 4.73 6.22 8 77.68 71.41 - 82.57 3.81 4.93 Korea 4 83.42 79.58 - 86.63 3.53 8.48 2 81.50 79.58 - 83.42 2.72 5.00 1 86.63 86.63 - 86.63 - - Ainu 3 74.14 68.10 - 75.37 3.89 9.38 2 71.12 68.10 - 74.14 4.27 9.01 1 75.37 75.37 - 75.37 - - Japan 13 76.88 72.58 - 84.25 3.56 4.59 10 77.30 72.58 - 84.25 3.46 4.47 3 76.00 73.90 - 82.85 4.68 10.56 S. China 6 79.84 78.71 - 88.11 4.63 5.61 3 83.49 79.84 - 87.14 5.16 10.81 3 79.12 78.71 - 88.11 5.31 11.34 N. China 16 79.22 73.16 - 87.05 3.60 4.57 13 79.44 73.16 - 87.05 3.91 4.94 3 78.59 75.36 - 79.73 2.26 5.09 Burma 39 79.88 71.17 - 91.66 4.25 5.33 22 80.22 73.11 - 88.25 3.14 3.92 17 79.13 71.17 - 91.66 5.47 6.88 Laos 24 81.13 75.20 - 87.51 3.07 3.77 16 80.50 78.14 - 87.51 3.03 3.73 8 82.07 75.20 - 86.12 3.33 4.07 Vietnam 23 81.32 62.90 - 89.54 5.35 6.65 14 81.27 62.90 - 89.16 5.63 7.01 9 82.04 73.89 - 89.54 5.22 6.48 Thailand 21 83.25 74.27 - 91.31 4.46 5.41 15 82.87 76.16 - 91.31 4.27 5.17 6 84.30 74.27 - 87.60 5.34 6.50 Cambodia 13 81.61 76.20 - 86.01 2.95 3.61 4 80.99 79.28 - 84.44 2.22 5.46 9 82.85 76.20 - 86.01 3.34 4.08 Philippines 28 78.80 73.06 - 87.98 4.16 5.22 22 78.57 73.06 - 87.98 4.11 5.17 6 81.93 74.52 - 85.43 4.67 5.81 Andaman Is. 36 79.39 71.90 - 85.40 2.42 3.06 18 79.28 75.86 - 85.40 2.60 3.26 18 79.47 71.90 - 82.59 2.20 2.79 Nicobar Is. 20 76.36 71.13 - 80.77 2.41 3.16 17 76.54 71.13 - 80.77 2.55 3.33 3 74.87 74.44 - 76.78 1.25 2.89 Borneo 37 77.49 73.84 - 85.19 3.42 4.36 26 77.53 73.90 - 85.19 3.52 4.49 11 77.29 73.84 - 84.08 3.35 4.26 Indonesia 27 81.10 72.14 - 90.59 4.15 5.17 20 81.36 72.62 - 90.59 3.97 4.93 7 80.12 72.14 - 86.34 4.89 6.14 Melanesia 30 75.60 70.94 - 82.06 2.53 3.33 20 75.48 70.94 - 79.83 2.47 3.27 10 76.39 73.07 - 82.06 2.60 3.40 Micronesia 15 78.48 71.54 - 81.14 2.72 3.48 7 78.48 74.83 - 80.76 1.88 2.41 8 78.99 71.54 - 81.14 3.43 4.39 Australia 27 74.59 67.43 - 78.56 2.68 3.61 18 74.95 67.43 - 78.56 2.82 3.79 9 74.32 69.82 - 75.95 2.27 3.10 Africa 29 73.08 68.44 - 78.96 2.70 3.67 18 73.53 68.44 - 77.97 2.82 3.85 11 72.79 69.81 - 78.96 2.61 3.56 Nat. America 33 77.06 72.09 - 83.42 2.81 3.65 10 75.91 73.48 - 83.42 3.81 4.93 23 77.10 72.09 - 81.07 2.34 3.04 Caucasian 29 72.53 66.73 - 78.85 3.17 4.36 15 73.75 69.38 - 77.13 2.67 3.63 14 70.82 66.73 - 78.85 3.47 4.84 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

475 Height/Breadth (anterior)

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (%) (%) (%) (%) (%) (%) (%) (%) (%)

Siberia 28 84.31 59.32 - 97.29 9.13 10.83 18 81.49 59.32 - 96.93 9.85 12.03 10 88.34 77.95 - 97.29 5.97 6.75 Mongolia 24 85.40 74.97 - 98.97 6.07 7.13 16 84.84 74.97 - 94.73 5.77 6.83 8 86.50 77.37 - 98.97 6.80 7.86 Korea 4 79.95 74.38 - 83.74 3.96 9.96 2 82.40 81.05 - 83.74 1.90 3.46 2 76.61 74.38 - 78.85 3.16 6.19 Ainu 3 88.43 81.19 - 91.16 5.15 10.37 2 84.81 81.19 - 88.43 5.12 9.06 1 91.16 91.16 - 91.16 1.00 2.00 Japan 13 78.68 67.54 - 84.96 5.08 6.44 10 79.20 67.54 - 84.66 5.47 6.98 3 78.68 77.96 - 84.96 3.85 8.37 S. China 6 81.05 68.66 - 86.84 7.85 9.90 3 86.43 77.52 - 86.84 5.26 6.30 3 71.80 68.66 - 84.58 8.43 19.68 N. China 16 79.82 67.60 - 88.82 6.10 7.66 13 78.92 70.76 - 88.82 5.44 6.81 3 83.92 67.60 - 85.30 9.85 21.83 Burma 39 81.06 71.95 - 91.00 4.45 5.47 22 80.47 73.95 - 91.00 4.26 5.23 17 81.61 71.95 - 89.51 4.83 5.92 Laos 24 82.01 74.46 - 95.24 5.26 6.33 16 82.01 74.46 - 95.24 5.61 6.74 8 82.06 78.18 - 91.14 4.84 5.84 Vietnam 23 80.16 73.58 - 98.78 5.63 7.00 14 81.50 73.58 - 98.78 6.38 7.82 9 76.33 74.91 - 85.89 3.91 4.97 Thailand 21 83.64 73.83 - 92.54 4.23 5.13 15 82.76 73.83 - 92.54 4.75 5.81 6 84.02 81.02 - 87.31 2.09 2.49 Cambodia 13 82.64 73.65 - 86.43 4.20 5.15 4 84.07 80.55 - 86.43 3.01 7.19 9 82.64 73.65 - 85.78 4.44 5.51 Philippines 28 82.39 72.19 - 94.59 5.78 6.94 22 82.39 72.19 - 94.59 6.14 7.37 6 83.17 77.20 - 88.65 4.71 5.64 Andaman Is. 36 81.62 73.88 - 89.01 3.90 4.79 18 82.31 74.82 - 89.01 4.13 5.04 18 81.21 73.88 - 86.67 3.70 4.57 Nicobar Is. 20 79.53 72.50 - 86.61 4.56 5.71 17 78.14 73.39 - 86.61 4.29 5.38 3 80.92 72.50 - 86.50 7.05 15.43 Borneo 37 81.01 75.58 - 91.85 3.93 4.81 26 80.98 76.09 - 91.85 3.70 4.52 11 81.33 75.58 - 90.11 4.61 5.66 Indonesia 27 82.86 72.70 - 98.83 5.93 7.14 20 82.61 75.07 - 94.23 4.86 5.92 7 85.66 72.70 - 98.83 8.25 9.65 Melanesia 30 75.95 62.52 - 88.07 5.83 7.67 20 75.55 62.52 - 88.07 5.82 7.72 10 78.37 68.32 - 86.71 5.93 7.67 Micronesia 15 79.02 74.49 - 85.73 3.90 4.87 7 82.75 78.41 - 85.73 3.21 3.91 8 76.91 74.49 - 84.56 3.75 4.79 Australia 27 76.94 71.74 - 87.17 4.02 5.18 18 76.93 72.49 - 84.48 3.34 4.33 9 78.15 71.74 - 87.17 5.28 6.76 Africa 29 83.19 69.01 - 91.88 6.52 7.93 18 81.78 69.01 - 91.86 6.55 8.10 11 84.77 69.78 - 91.88 6.10 7.23 Nat. America 33 79.98 62.49 - 86.86 5.94 7.60 10 79.25 62.49 - 83.09 7.30 9.55 23 79.98 66.60 - 86.86 5.26 6.68 Caucasian 29 88.60 71.67 - 98.77 6.98 7.99 15 84.91 71.67 - 96.68 7.13 8.32 14 89.88 74.44 - 98.77 6.59 7.39 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

476 Height/Breadth (posterior)

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (%) (%) (%) (%) (%) (%) (%) (%) (%)

Siberia 28 83.97 73.23 - 102.77 7.15 8.46 18 83.81 73.23 - 102.77 8.53 10.04 10 83.97 76.51 - 90.29 3.84 4.59 Mongolia 24 84.99 74.11 - 106.23 8.55 10.04 16 86.07 74.11 - 104.60 8.10 9.49 8 82.62 75.85 - 106.23 9.95 11.75 Korea 4 78.20 73.16 - 81.15 3.90 10.04 2 80.93 80.71 - 81.15 0.31 0.57 2 74.42 73.16 - 75.69 1.79 3.61 Ainu 3 84.38 79.98 - 89.19 4.61 9.54 2 84.59 79.98 - 89.19 6.51 11.55 1 84.38 84.38 - 84.38 - - Japan 13 81.26 68.46 - 86.45 4.51 5.65 10 81.56 68.46 - 86.45 5.06 6.32 3 78.94 76.79 - 81.64 2.43 5.37 S. China 6 80.61 71.45 - 86.73 5.40 6.68 3 80.73 80.34 - 85.60 2.93 6.23 3 80.49 71.45 - 86.73 7.69 16.91 N. China 16 77.59 71.53 - 85.79 4.00 5.11 13 77.33 71.53 - 84.04 3.68 4.75 3 81.13 77.30 - 85.79 4.25 9.14 Burma 39 79.77 72.16 - 87.78 3.63 4.56 22 78.78 72.16 - 85.93 3.77 4.79 17 81.25 75.30 - 87.78 3.12 3.85 Laos 24 78.93 71.22 - 89.53 4.61 5.79 16 79.27 71.22 - 88.95 4.41 5.56 8 78.72 73.33 - 89.53 5.26 6.55 Vietnam 23 75.80 66.28 - 102.16 6.68 8.61 14 75.48 66.28 - 102.16 8.29 10.70 9 77.31 73.21 - 82.90 3.30 4.25 Thailand 21 78.73 68.18 - 87.56 4.39 5.63 15 78.24 68.18 - 82.84 4.05 5.25 6 79.61 74.23 - 87.56 4.62 5.74 Cambodia 13 79.76 73.36 - 85.57 3.86 4.89 4 79.74 73.36 - 85.57 5.02 12.62 9 79.76 74.16 - 84.26 3.55 4.51 Philippines 28 78.88 72.43 - 93.84 5.08 6.36 22 79.53 74.08 - 89.53 4.43 5.55 6 77.79 72.43 - 93.84 7.53 9.45 Andaman Is. 36 77.65 68.73 - 85.62 4.29 5.56 18 77.73 68.73 - 82.97 4.64 6.07 18 77.60 71.28 - 85.62 3.94 5.06 Nicobar Is. 20 76.96 71.74 - 82.50 2.70 3.50 17 76.58 71.74 - 80.08 2.48 3.24 3 79.38 77.20 - 82.50 2.66 5.84 Borneo 37 79.02 71.72 - 86.98 3.53 4.46 26 79.55 74.37 - 86.98 3.12 3.90 11 75.90 71.72 - 82.21 3.78 4.91 Indonesia 27 78.33 73.68 - 86.47 3.89 4.92 20 76.61 73.68 - 85.56 3.57 4.58 7 83.13 76.62 - 86.47 3.19 3.89 Melanesia 30 81.00 72.19 - 91.58 4.43 5.47 20 81.87 72.19 - 91.58 4.93 6.05 10 80.59 74.99 - 87.04 3.38 4.20 Micronesia 15 78.10 68.87 - 86.53 4.81 6.20 7 79.15 72.99 - 83.53 3.86 4.89 8 76.22 68.87 - 86.53 5.43 7.12 Australia 27 79.73 72.73 - 90.03 4.21 5.25 18 79.69 72.73 - 89.00 4.32 5.41 9 79.73 76.27 - 90.03 4.14 5.11 Africa 29 80.68 73.40 - 89.44 4.28 5.30 18 81.68 73.76 - 87.30 4.41 5.41 11 79.90 73.40 - 89.44 4.06 5.08 Nat. America 33 80.01 72.09 - 88.30 3.68 4.59 10 80.23 76.41 - 88.30 3.99 4.95 23 79.98 72.09 - 86.24 3.61 4.52 Caucasian 29 83.77 74.83 - 93.41 4.55 5.41 15 85.23 74.83 - 93.41 4.76 5.66 14 83.65 77.35 - 91.27 4.49 5.35 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

477 Posterior Cranial Breadth Proportion (sup/inf B)

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (%) (%) (%) (%) (%) (%) (%) (%) (%)

Siberia 28 105.56 91.16 - 118.60 6.66 6.33 18 105.56 91.16 - 118.60 7.88 7.51 10 105.67 99.84 - 113.77 3.86 3.65 Mongolia 24 107.01 89.80 - 122.85 7.58 7.10 16 106.93 96.28 - 118.06 6.16 5.77 8 108.28 89.80 - 122.85 10.34 9.73 Korea 4 113.31 100.04 - 115.34 7.18 12.99 2 113.46 111.58 - 115.34 2.66 3.51 2 107.54 100.04 - 115.04 10.61 14.80 Ainu 3 117.08 110.57 - 123.28 6.36 9.51 2 116.92 110.57 - 123.28 8.99 11.53 1 117.08 117.08 - 117.08 -- Japan 13 111.86 94.66 - 120.91 7.35 6.69 10 111.28 94.66 - 120.91 7.95 7.25 3 114.00 104.23 - 115.47 6.11 9.61 S. China 6 109.67 103.35 - 118.70 6.25 5.66 3 112.88 103.35 - 118.70 7.75 12.15 3 106.45 105.19 - 115.68 5.73 9.19 N. China 16 116.62 104.64 - 121.89 5.89 5.14 13 111.18 104.64 - 121.89 6.11 5.38 3 119.55 115.57 - 120.37 2.57 3.79 Burma 39 113.08 98.89 - 121.80 5.72 5.14 22 113.48 98.89 - 121.80 5.86 5.23 17 110.32 101.20 - 119.28 5.59 5.06 Laos 24 110.07 96.14 - 120.97 6.10 5.59 16 111.19 97.15 - 120.97 6.05 5.49 8 108.64 96.14 - 115.09 6.04 5.64 Vietnam 23 111.94 96.27 - 122.72 7.19 6.47 14 113.93 101.69 - 122.72 6.79 5.99 9 108.38 96.27 - 117.21 6.63 6.17 Thailand 21 113.52 101.75 - 124.50 5.44 4.83 15 114.01 101.75 - 121.03 4.67 4.15 6 110.50 102.67 - 124.50 7.56 6.72 Cambodia 13 113.08 100.45 - 119.78 6.67 6.01 4 108.99 100.45 - 117.46 8.67 15.92 9 113.08 104.37 - 119.78 5.97 5.34 Philippines 28 112.53 97.78 - 121.58 6.09 5.44 22 112.98 97.78 - 121.58 6.21 5.53 6 111.11 100.88 - 118.42 5.89 5.34 Andaman Is. 36 120.48 105.70 - 137.22 7.70 6.38 18 119.76 110.13 - 133.28 7.50 6.29 18 121.49 105.70 - 137.22 7.86 6.44 Nicobar Is. 20 112.22 103.07 - 123.50 5.34 4.76 17 114.35 103.07 - 123.50 5.66 5.04 3 111.45 107.13 - 112.99 3.04 4.81 Borneo 37 112.38 100.15 - 123.98 5.97 5.33 26 109.88 100.15 - 120.68 5.28 4.80 11 115.48 109.84 - 123.98 4.93 4.23 Indonesia 27 114.10 102.40 - 127.85 5.92 5.16 20 114.89 102.40 - 127.85 6.41 5.57 7 113.79 107.43 - 119.81 4.55 3.99 Melanesia 30 106.37 99.23 - 120.04 5.34 4.97 20 105.34 99.23 - 120.04 5.21 4.92 10 111.34 102.57 - 119.10 4.69 4.26 Micronesia 15 111.32 102.59 - 121.39 5.09 4.58 7 110.36 102.59 - 114.93 4.15 3.79 8 112.78 104.81 - 121.39 5.63 5.00 Australia 27 108.44 96.37 - 119.54 5.22 4.84 18 107.27 96.37 - 113.11 4.85 4.55 9 110.69 100.73 - 119.54 5.16 4.67 Africa 29 110.42 99.66 - 125.56 6.50 5.83 18 109.21 99.66 - 120.84 5.09 4.64 11 110.75 101.17 - 125.56 7.76 6.79 Nat. America 33 106.43 94.60 - 120.24 5.55 5.18 10 106.90 94.60 - 120.05 7.28 6.73 23 106.02 100.94 - 120.24 4.85 4.55 Caucasian 29 111.93 93.87 - 127.36 7.42 6.66 15 111.93 93.87 - 124.88 8.36 7.60 14 111.70 105.20 - 127.36 6.29 5.59 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

478 Anterior Breadth Proprtion (sup/inf B)

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (%) (%) (%) (%) (%) (%) (%) (%) (%)

Siberia 28 92.84 76.65 - 105.39 7.00 7.51 18 90.84 76.65 - 105.39 7.65 8.36 10 95.39 90.96 - 104.89 4.51 4.69 Mongolia 24 92.68 82.55 - 104.16 5.94 6.36 16 90.65 82.55 - 100.76 4.92 5.38 8 99.26 87.16 - 104.16 6.09 6.25 Korea 4 91.39 88.81 - 94.86 2.72 5.94 2 90.78 88.81 - 92.75 2.78 4.60 2 92.45 90.03 - 94.86 3.41 5.54 Ainu 3 95.93 95.66 - 96.22 0.28 0.51 2 95.94 95.66 - 96.22 0.39 0.62 1 95.93 95.93 - 95.93 - - Japan 13 95.02 81.69 - 103.75 5.93 6.30 10 93.57 81.69 - 103.75 6.34 6.80 3 98.45 93.36 - 99.74 3.37 6.08 S. China 6 100.90 85.65 - 103.42 6.93 7.07 3 101.13 85.65 - 103.42 9.66 17.48 3 100.66 93.84 - 102.88 4.71 8.32 N. China 16 95.13 77.09 - 105.07 8.50 9.04 13 94.54 77.09 - 104.71 7.02 7.49 3 103.25 77.16 - 105.07 15.62 28.72 Burma 39 99.03 85.96 - 104.09 4.34 4.42 22 97.40 87.50 - 104.09 4.33 4.42 17 99.38 85.96 - 102.62 4.48 4.56 Laos 24 98.76 92.21 - 104.90 3.55 3.58 16 97.72 92.21 - 104.43 3.18 3.24 8 102.66 95.55 - 104.90 3.16 3.11 Vietnam 23 97.95 89.24 - 107.04 5.11 5.24 14 97.03 89.24 - 103.33 4.60 4.73 9 98.26 89.38 - 107.04 6.11 6.25 Thailand 21 99.14 90.72 - 108.72 5.37 5.40 15 99.14 90.72 - 108.72 5.88 5.95 6 100.64 96.43 - 107.00 3.84 3.81 Cambodia 13 103.04 88.94 - 108.57 5.84 5.76 4 105.51 96.81 - 108.45 5.07 9.74 9 102.25 88.94 - 108.57 6.03 6.02 Philippines 28 99.33 83.87 - 111.53 6.05 6.07 22 99.08 83.87 - 111.53 6.66 6.68 6 99.74 95.14 - 104.57 3.39 3.41 Andaman Is. 36 98.83 90.34 - 109.80 5.15 5.20 18 99.31 92.14 - 108.96 4.66 4.66 18 98.41 90.34 - 109.80 5.54 5.66 Nicobar Is. 20 101.19 91.52 - 113.25 5.77 5.73 17 100.61 91.59 - 113.25 5.58 5.54 3 102.75 91.52 - 107.55 8.23 14.31 Borneo 37 98.97 87.30 - 108.91 5.52 5.59 26 98.44 87.30 - 108.91 5.05 5.17 11 102.58 88.45 - 108.64 6.12 6.06 Indonesia 27 97.89 90.47 - 108.79 5.25 5.33 20 98.24 91.60 - 108.79 4.76 4.82 7 94.05 90.47 - 106.42 6.68 6.88 Melanesia 30 96.23 79.56 - 105.37 5.99 6.25 20 96.23 79.56 - 105.37 6.47 6.80 10 96.60 88.48 - 103.84 4.93 5.07 Micronesia 15 100.27 90.04 - 107.97 4.99 5.01 7 100.27 90.04 - 107.97 6.11 6.13 8 99.46 94.47 - 105.32 4.22 4.23 Australia 27 96.18 87.87 - 111.38 5.72 5.87 18 96.31 88.00 - 111.38 5.96 6.09 9 96.18 87.87 - 103.66 5.50 5.68 Africa 29 100.10 81.25 - 105.85 6.64 6.80 18 100.10 81.25 - 104.95 7.05 7.23 11 99.49 86.34 - 105.85 6.18 6.31 Nat. America 33 92.68 72.26 - 104.25 7.07 7.70 10 92.45 77.41 - 103.26 8.33 9.11 23 92.79 72.26 - 104.25 6.65 7.23 Caucasian 29 97.72 78.16 - 106.23 6.09 6.32 15 96.47 78.16 - 105.47 6.47 6.80 14 98.62 85.93 - 106.23 5.63 5.77 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

479 Frontal Index (STB/FRC)

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (%) (%) (%) (%) (%) (%) (%) (%) (%)

Siberia 28 99.13 74.40 - 111.77 8.73 8.87 18 96.46 74.40 - 111.77 9.63 9.98 10 104.71 93.42 - 109.13 5.70 5.60 Mongolia 24 97.38 88.55 - 110.29 6.30 6.37 16 97.17 88.55 - 110.29 6.22 6.35 8 101.30 90.99 - 108.84 6.49 6.45 Korea 4 94.25 94.16 - 103.33 4.56 9.45 2 98.79 94.24 - 103.33 6.43 9.77 2 94.21 94.16 - 94.27 0.08 0.13 Ainu 3 99.70 97.74 - 111.90 7.68 13.03 2 98.72 97.74 - 99.70 1.39 2.11 1 111.90 111.90 - 111.90 -- Japan 13 97.17 85.58 - 105.37 5.37 5.52 10 97.70 85.58 - 102.85 5.22 5.37 3 95.91 91.51 - 105.37 7.08 12.70 S. China 6 99.24 87.47 - 103.53 7.44 7.69 3 102.64 87.47 - 102.81 8.81 15.79 3 95.84 88.26 - 103.53 7.64 13.94 N. China 16 95.53 78.52 - 106.59 8.43 8.86 13 94.23 78.76 - 106.59 7.81 8.17 3 99.18 78.52 - 101.35 12.60 23.71 Burma 39 98.23 85.22 - 112.57 6.38 6.46 22 97.49 89.84 - 112.57 6.26 6.32 17 98.96 85.22 - 110.96 6.73 6.83 Laos 24 101.04 91.16 - 121.68 6.83 6.70 16 101.87 91.16 - 121.68 7.77 7.54 8 98.83 95.61 - 108.87 4.28 4.27 Vietnam 23 98.85 91.12 - 110.31 5.02 5.10 14 100.18 92.35 - 110.31 5.63 5.66 9 95.90 91.12 - 101.86 3.41 3.54 Thailand 21 100.70 89.88 - 118.52 7.11 6.97 15 100.70 89.88 - 118.52 7.35 7.19 6 100.64 92.10 - 111.63 7.16 7.03 Cambodia 13 101.98 90.63 - 109.35 6.14 6.11 4 104.06 95.50 - 106.30 4.78 9.34 9 99.05 90.63 - 109.35 6.69 6.73 Philippines 28 101.41 90.01 - 109.86 5.81 5.77 22 101.41 90.01 - 109.86 6.11 6.05 6 101.37 93.57 - 104.97 4.97 4.98 Andaman Is. 36 98.38 88.85 - 105.90 5.07 5.16 18 100.18 91.75 - 105.90 4.39 4.40 18 97.78 88.85 - 104.52 5.40 5.57 Nicobar Is. 20 96.22 85.71 - 110.15 6.57 6.75 17 97.08 85.71 - 110.15 6.31 6.47 3 95.08 86.87 - 105.54 9.36 17.08 Borneo 37 100.78 89.45 - 108.77 4.62 4.61 26 100.35 89.45 - 106.96 4.59 4.60 11 101.13 93.98 - 108.77 4.85 4.81 Indonesia 27 100.38 90.37 - 112.33 5.88 5.81 20 100.08 92.84 - 109.11 5.11 5.08 7 102.95 90.37 - 112.33 7.90 7.69 Melanesia 30 92.75 82.17 - 102.92 5.00 5.36 20 93.00 82.17 - 100.44 4.74 5.09 10 91.59 85.93 - 102.92 5.75 6.17 Micronesia 15 96.75 88.60 - 111.05 6.77 6.86 7 104.48 89.18 - 111.05 7.35 7.21 8 95.53 88.60 - 104.72 5.01 5.23 Australia 27 90.92 85.54 - 106.52 5.21 5.62 18 90.12 85.54 - 106.52 5.66 6.14 9 93.40 86.86 - 102.41 4.31 4.61 Africa 29 97.14 79.32 - 106.50 7.47 7.82 18 95.92 79.32 - 104.67 7.53 8.03 11 99.88 83.17 - 106.50 6.87 7.00 Nat. America 33 93.96 76.72 - 105.44 7.22 7.76 10 91.99 76.72 - 105.44 8.86 9.73 23 93.96 80.96 - 105.34 6.41 6.83 Caucasian 29 100.46 84.57 - 116.89 7.38 7.26 15 100.20 84.57 - 116.89 7.71 7.64 14 101.45 92.82 - 116.62 7.19 7.02 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

480 Frontal Length Proportion (FRC/g-l)

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (%) (%) (%) (%) (%) (%) (%) (%) (%)

Siberia 28 64.78 57.86 - 70.06 3.07 4.75 18 63.88 59.68 - 70.06 2.43 3.80 10 66.88 57.86 - 69.50 3.86 5.88 Mongolia 24 65.95 62.70 - 69.98 1.95 2.95 16 65.66 62.70 - 69.98 1.90 2.88 8 66.23 64.30 - 69.95 2.00 2.99 Korea 4 67.60 64.35 - 68.35 2.13 6.37 2 65.97 64.35 - 67.60 2.30 5.23 2 68.35 68.35 - 68.35 - - Ainu 3 62.09 60.41 - 62.61 1.15 3.26 2 61.25 60.41 - 62.09 1.19 2.91 1 62.61 62.61 - 62.61 - - Japan 13 62.01 61.06 - 68.63 2.42 3.85 10 61.53 61.06 - 68.63 2.29 3.67 3 63.53 62.01 - 67.35 2.75 7.48 S. China 6 66.83 64.31 - 70.26 2.18 3.25 3 68.74 67.23 - 70.26 2.15 5.46 3 66.01 64.31 - 66.83 1.29 3.42 N. China 16 65.15 60.34 - 70.98 2.95 4.54 13 65.26 60.34 - 70.98 3.30 5.08 3 65.08 64.88 - 65.21 0.17 0.45 Burma 39 66.11 61.10 - 71.35 2.30 3.49 22 66.02 62.47 - 71.35 2.16 3.27 17 66.11 61.10 - 71.15 2.54 3.85 Laos 24 66.58 58.86 - 72.66 3.10 4.67 16 65.51 58.86 - 72.66 3.27 4.97 8 67.81 62.87 - 71.17 2.36 3.49 Vietnam 23 65.77 59.88 - 71.01 2.92 4.46 14 66.17 59.88 - 69.23 2.10 3.19 9 64.85 59.93 - 71.01 3.96 6.09 Thailand 21 66.24 59.69 - 71.91 2.67 4.00 15 66.24 59.69 - 69.99 2.49 3.75 6 66.46 65.06 - 71.91 3.02 4.45 Cambodia 13 66.74 62.65 - 69.58 1.89 2.85 4 66.94 66.13 - 68.52 1.00 2.98 9 65.77 62.65 - 69.58 2.16 3.27 Philippines 28 65.66 59.73 - 71.78 3.05 4.63 22 65.66 59.73 - 71.71 2.99 4.55 6 65.72 63.20 - 71.78 3.39 5.07 Andaman Is. 36 65.45 62.24 - 69.23 1.87 2.85 18 65.39 62.24 - 69.11 2.03 3.11 18 65.57 63.31 - 69.23 1.72 2.61 Nicobar Is. 20 63.00 59.49 - 65.76 1.73 2.75 17 62.82 59.49 - 65.76 1.87 2.98 3 63.27 62.48 - 63.36 0.48 1.34 Borneo 37 63.60 59.82 - 68.72 2.35 3.67 26 63.55 59.82 - 68.72 2.45 3.83 11 64.14 60.81 - 67.32 2.21 3.45 Indonesia 27 65.43 59.68 - 70.06 2.16 3.29 20 66.42 59.68 - 70.06 2.28 3.46 7 65.38 62.76 - 68.62 1.86 2.84 Melanesia 30 61.78 57.19 - 64.88 1.98 3.22 20 61.25 57.19 - 64.88 2.04 3.35 10 62.08 60.03 - 64.88 1.56 2.50 Micronesia 15 63.50 60.20 - 67.37 2.08 3.28 7 62.16 60.67 - 65.80 1.92 3.05 8 63.97 60.20 - 67.37 2.23 3.48 Australia 27 62.31 58.36 - 66.49 2.00 3.20 18 62.18 58.36 - 66.49 2.11 3.37 9 62.88 59.79 - 65.90 1.89 3.01 Africa 29 62.80 57.52 - 66.39 1.90 3.03 18 62.68 57.52 - 65.25 1.97 3.16 11 62.80 60.35 - 66.39 1.77 2.81 Nat. America 33 65.02 59.96 - 68.03 2.08 3.22 10 65.25 61.79 - 67.99 2.11 3.25 23 65.00 59.96 - 68.03 2.10 3.26 Caucasian 29 62.71 55.09 - 65.84 2.63 4.21 15 62.81 55.09 - 65.84 2.95 4.73 14 62.55 57.07 - 65.46 2.33 3.74 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

481 Parietal Length Proportion (PAC/g-l)

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (%) (%) (%) (%) (%) (%) (%) (%) (%)

Siberia 28 62.49 54.86 - 67.97 2.64 4.20 18 62.62 54.86 - 66.39 2.64 4.22 10 61.85 59.90 - 67.97 2.76 4.39 Mongolia 24 62.42 58.38 - 67.01 2.41 3.85 16 62.06 58.38 - 67.01 2.73 4.38 8 62.47 61.13 - 66.13 1.63 2.59 Korea 4 65.19 61.92 - 66.12 2.21 6.85 2 65.65 65.19 - 66.12 0.66 1.50 2 61.92 61.92 - 61.92 - - Ainu 3 64.52 64.30 - 67.10 1.55 4.16 2 65.70 64.30 - 67.10 1.97 4.51 1 64.52 64.52 - 64.52 - - Japan 13 64.29 59.73 - 66.46 1.89 2.95 10 64.44 61.18 - 66.46 1.58 2.45 3 63.97 59.73 - 64.97 2.78 7.74 S. China 6 64.18 51.48 - 67.17 6.29 10.09 3 59.33 51.48 - 67.17 11.10 32.73 3 64.18 63.09 - 65.97 1.46 3.95 N. China 16 63.66 59.41 - 72.91 3.34 5.20 13 63.72 59.41 - 72.91 3.55 5.50 3 63.34 60.65 - 63.73 1.68 4.70 Burma 39 64.73 59.39 - 71.91 2.57 3.97 22 65.01 59.39 - 71.91 2.85 4.40 17 64.67 60.39 - 69.42 2.25 3.48 Laos 24 64.22 56.39 - 68.96 3.18 4.99 16 63.73 56.39 - 68.96 3.57 5.64 8 64.47 61.43 - 66.87 2.28 3.55 Vietnam 23 64.37 58.15 - 69.97 2.92 4.55 14 64.43 59.32 - 69.97 2.99 4.64 9 63.82 58.15 - 68.05 2.92 4.58 Thailand 21 62.79 58.23 - 68.20 2.67 4.22 15 62.67 60.10 - 68.16 2.43 3.83 6 63.27 58.23 - 68.20 3.45 5.47 Cambodia 13 64.30 57.51 - 68.92 3.11 4.85 4 64.34 63.36 - 67.49 1.83 5.63 9 64.30 57.51 - 68.92 3.60 5.63 Philippines 28 63.19 51.16 - 68.30 3.98 6.31 22 63.11 51.16 - 68.30 4.01 6.43 6 67.29 62.13 - 67.72 2.54 3.86 Andaman Is. 36 66.21 58.50 - 70.93 2.53 3.86 18 66.84 61.24 - 68.88 1.98 2.97 18 63.95 58.50 - 70.93 2.71 4.20 Nicobar Is. 20 65.80 60.86 - 69.94 2.18 3.30 17 65.92 60.86 - 69.94 2.36 3.58 3 65.63 65.28 - 65.69 0.22 0.59 Borneo 37 66.10 61.46 - 72.31 2.31 3.49 26 66.00 61.46 - 71.17 2.31 3.51 11 66.50 63.82 - 72.31 2.34 3.51 Indonesia 27 64.18 59.99 - 70.50 2.60 4.04 20 64.00 59.99 - 70.50 2.66 4.11 7 64.28 60.47 - 67.60 2.61 4.07 Melanesia 30 65.20 56.30 - 69.37 2.91 4.49 20 64.91 56.30 - 69.37 3.24 5.03 10 65.79 60.99 - 68.02 2.14 3.28 Micronesia 15 65.07 60.38 - 72.36 3.43 5.20 7 63.76 60.38 - 70.65 3.65 5.64 8 65.65 63.41 - 72.36 3.13 4.68 Australia 27 64.01 59.30 - 70.23 2.45 3.81 18 63.84 59.30 - 70.23 2.69 4.17 9 64.28 60.78 - 67.68 2.01 3.14 Africa 29 63.42 58.43 - 71.77 2.76 4.33 18 63.40 60.75 - 71.77 2.88 4.51 11 63.97 58.43 - 67.24 2.65 4.18 Nat. America 33 64.31 55.63 - 68.46 3.19 5.03 10 64.38 55.63 - 68.46 4.57 7.25 23 64.26 59.01 - 68.04 2.49 3.92 Caucasian 29 63.82 57.65 - 71.79 3.35 5.24 15 63.03 59.10 - 69.76 3.00 4.73 14 64.02 57.65 - 71.79 3.74 5.81 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

482 Upper Facial Index 1 (NPH/ZMB)

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (%) (%) (%) (%) (%) (%) (%) (%) (%)

Siberia 28 72.41 66.22 - 83.28 4.17 5.70 18 72.60 66.22 - 83.28 4.78 6.51 10 71.62 69.46 - 78.74 2.87 3.96 Mongolia 24 71.39 61.84 - 81.38 5.41 7.58 16 71.79 61.84 - 81.38 5.62 7.81 8 69.72 62.61 - 77.98 5.09 7.25 Korea 4 73.50 61.73 - 77.40 6.79 18.98 2 73.50 73.48 - 73.51 0.02 0.05 2 69.56 61.73 - 77.40 11.08 23.89 Ainu 3 64.48 64.14 - 75.91 6.70 17.20 2 64.31 64.14 - 64.48 0.24 0.55 1 75.91 75.91 - 75.91 - - Japan 13 67.91 58.75 - 75.33 4.68 6.85 10 68.18 63.17 - 75.33 4.25 6.14 3 67.91 58.75 - 69.21 5.70 15.29 S. China 6 65.66 59.59 - 67.56 2.85 4.39 3 66.51 64.67 - 67.56 1.46 3.87 3 64.80 59.59 - 66.53 3.61 9.93 N. China 16 70.25 62.73 - 85.60 7.24 9.99 13 71.11 62.73 - 83.55 6.94 9.62 3 69.38 67.49 - 85.60 9.95 23.49 Burma 39 68.28 60.22 - 78.18 4.32 6.32 22 67.23 62.07 - 78.18 4.15 6.10 17 69.78 60.22 - 74.75 4.63 6.74 Laos 24 67.71 60.94 - 75.71 4.04 5.91 16 67.08 60.94 - 73.52 3.50 5.20 8 71.50 64.27 - 75.71 4.42 6.27 Vietnam 23 67.25 60.47 - 80.53 3.99 5.90 14 67.24 60.47 - 80.53 4.52 6.68 9 67.45 62.34 - 73.20 3.26 4.82 Thailand 21 67.93 49.04 - 78.38 6.55 9.89 15 67.93 57.39 - 78.38 5.02 7.45 6 64.43 49.04 - 73.90 9.32 14.72 Cambodia 13 65.63 51.83 - 70.71 4.80 7.37 4 65.63 62.55 - 70.71 3.74 11.32 9 65.63 51.83 - 69.26 5.35 8.26 Philippines 28 66.20 57.30 - 74.35 4.26 6.42 22 66.17 57.30 - 74.09 4.27 6.48 6 67.58 61.66 - 74.35 4.29 6.34 Andaman Is. 36 64.18 53.82 - 75.04 4.57 7.09 18 62.84 53.82 - 75.04 4.86 7.58 18 65.67 56.53 - 71.29 4.36 6.72 Nicobar Is. 20 65.88 58.43 - 72.74 4.26 6.51 17 66.50 58.43 - 72.74 4.48 6.82 3 64.42 61.38 - 68.16 3.39 9.18 Borneo 37 65.76 55.36 - 76.09 4.81 7.31 26 65.59 55.36 - 75.84 4.80 7.36 11 66.16 60.14 - 76.09 4.82 7.19 Indonesia 27 68.40 62.03 - 77.60 3.90 5.71 20 67.74 62.16 - 73.75 3.62 5.33 7 68.57 62.03 - 77.60 4.80 6.95 Melanesia 30 67.48 60.56 - 78.85 4.30 6.28 20 69.25 60.56 - 75.27 3.82 5.55 10 66.14 61.50 - 78.85 5.26 7.78 Micronesia 15 63.78 61.29 - 68.85 2.74 4.23 7 63.78 61.29 - 68.45 2.39 3.73 8 65.71 61.50 - 68.85 3.05 4.66 Australia 27 70.38 61.19 - 83.91 4.87 6.90 18 71.45 61.19 - 83.91 5.27 7.37 9 69.65 61.87 - 73.96 3.70 5.36 Africa 29 65.45 54.12 - 75.64 5.44 8.31 18 65.95 54.12 - 75.64 6.09 9.19 11 64.39 57.24 - 72.21 4.18 6.49 Nat. America 33 69.10 59.64 - 78.65 3.95 5.72 10 68.00 59.64 - 75.06 5.01 7.28 23 69.21 63.64 - 78.65 3.58 5.18 Caucasian 29 73.48 60.27 - 82.32 5.96 8.21 15 73.83 64.25 - 82.32 5.49 7.49 14 72.55 60.27 - 81.32 6.54 9.11 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

483 Upper Facial Index 2 (NPH/JUB)

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (%) (%) (%) (%) (%) (%) (%) (%) (%)

Siberia 28 60.91 54.06 - 69.07 3.69 6.05 18 60.91 54.06 - 69.07 4.10 6.70 10 60.61 56.59 - 65.44 3.02 4.97 Mongolia 24 61.86 50.55 - 66.98 4.46 7.32 16 61.61 50.55 - 66.00 4.33 7.13 8 62.50 52.53 - 66.98 4.99 8.18 Korea 4 61.09 53.70 - 63.86 4.83 16.10 2 61.20 58.54 - 63.86 3.76 9.21 2 58.67 53.70 - 63.63 7.02 17.96 Ainu 3 56.88 54.62 - 67.27 6.75 19.82 2 55.75 54.62 - 56.88 1.60 4.31 1 67.27 67.27 - 67.27 - - Japan 13 59.21 49.87 - 63.51 3.73 6.36 10 59.11 53.93 - 63.51 2.98 5.03 3 59.21 49.87 - 61.25 6.07 18.70 S. China 6 56.54 50.45 - 57.08 2.54 4.59 3 56.33 55.00 - 56.87 0.96 3.01 3 56.76 50.45 - 57.08 3.74 11.94 N. China 16 60.55 52.60 - 71.17 5.09 8.19 13 60.44 52.60 - 71.17 5.24 8.51 3 62.34 60.52 - 69.34 4.66 12.72 Burma 39 58.54 50.04 - 65.77 3.68 6.26 22 58.19 52.70 - 65.77 3.46 5.91 17 59.51 50.04 - 64.82 4.05 6.86 Laos 24 59.28 54.94 - 64.36 2.89 4.90 16 58.33 54.94 - 64.36 2.84 4.86 8 60.54 56.59 - 63.95 2.70 4.47 Vietnam 23 57.79 53.38 - 66.37 2.85 4.93 14 58.32 53.38 - 66.37 3.19 5.48 9 56.95 54.71 - 59.57 2.02 3.56 Thailand 21 58.32 45.45 - 65.31 4.63 8.03 15 58.46 50.82 - 65.31 3.65 6.25 6 55.18 45.45 - 63.32 6.37 11.49 Cambodia 13 57.09 51.68 - 61.63 3.03 5.32 4 56.56 51.68 - 61.63 4.09 14.44 9 57.64 53.14 - 60.60 2.73 4.77 Philippines 28 56.53 50.54 - 67.24 3.95 6.98 22 56.52 50.54 - 60.73 3.18 5.68 6 57.51 51.10 - 67.24 5.73 9.73 Andaman Is. 36 54.60 48.55 - 60.82 3.04 5.54 18 54.27 49.37 - 59.76 3.05 5.56 18 54.89 48.55 - 60.82 3.11 5.67 Nicobar Is. 20 57.16 48.17 - 63.45 4.25 7.50 17 57.17 48.17 - 63.45 4.55 8.06 3 56.81 54.90 - 60.25 2.71 8.28 Borneo 37 57.14 47.63 - 65.73 3.84 6.75 26 56.89 47.63 - 62.49 3.96 7.03 11 58.00 54.78 - 65.73 3.33 5.73 Indonesia 27 58.20 50.27 - 66.55 3.61 6.24 20 57.30 50.27 - 63.12 3.39 5.90 7 58.62 52.80 - 66.55 4.13 6.96 Melanesia 30 56.91 49.71 - 64.64 3.60 6.27 20 57.49 49.71 - 64.64 3.25 5.65 10 56.35 50.38 - 63.11 4.40 7.69 Micronesia 15 56.99 50.41 - 60.69 2.75 4.85 7 56.10 50.41 - 58.57 2.94 5.30 8 57.84 53.76 - 60.69 2.26 3.92 Australia 27 56.04 48.93 - 66.48 4.01 7.12 18 55.25 48.93 - 66.48 4.60 8.15 9 56.26 52.55 - 59.68 2.69 4.80 Africa 29 56.35 48.17 - 65.07 4.43 7.87 18 56.04 48.17 - 62.71 4.41 7.76 11 56.61 49.23 - 65.07 4.57 8.22 Nat. America 33 59.53 51.13 - 67.53 3.19 5.33 10 60.36 51.13 - 64.99 4.05 6.77 23 59.17 53.49 - 67.53 2.89 4.83 Caucasian 29 59.29 51.61 - 69.22 4.37 7.32 15 58.84 53.23 - 67.21 4.27 7.16 14 60.87 51.61 - 69.22 4.66 7.80 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

484 Upper Facial Index 3 (fmo-fmo/zm-fmt)

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (%) (%) (%) (%) (%) (%) (%) (%) (%)

Siberia 28 48.71 43.06 - 58.09 3.76 7.70 18 49.40 43.06 - 58.09 4.29 8.65 10 47.93 44.19 - 50.09 2.09 4.41 Mongolia 24 50.52 44.10 - 54.65 2.92 5.81 16 51.59 44.10 - 54.65 2.84 5.58 8 48.24 45.82 - 53.75 2.56 5.27 Korea 4 51.45 50.90 - 58.93 3.87 14.54 2 55.46 51.99 - 58.93 4.91 13.29 2 50.91 50.90 - 50.91 0.01 0.02 Ainu 3 44.33 44.25 - 53.38 5.25 19.41 2 48.86 44.33 - 53.38 6.40 19.64 1 44.25 44.25 - 44.25 - - Japan 13 48.90 46.01 - 53.97 2.26 4.57 10 48.77 46.01 - 53.97 2.23 4.54 3 51.18 47.72 - 52.53 2.48 8.59 S. China 6 49.79 45.35 - 52.86 2.95 5.97 3 48.87 45.35 - 52.86 3.76 13.42 3 50.70 46.88 - 52.02 2.67 9.37 N. China 16 50.68 47.08 - 56.34 2.71 5.31 13 50.21 47.08 - 56.34 2.95 5.77 3 51.15 48.90 - 52.16 1.67 5.75 Burma 39 47.86 42.66 - 56.40 3.34 6.89 22 47.63 43.95 - 56.40 3.50 7.20 17 48.00 42.66 - 53.22 3.18 6.62 Laos 24 48.84 45.36 - 64.94 4.03 8.16 16 48.63 45.40 - 53.90 2.52 5.15 8 49.04 45.36 - 64.94 6.20 12.35 Vietnam 23 48.93 42.89 - 55.72 3.37 6.85 14 49.35 43.98 - 55.57 3.04 6.14 9 48.72 42.89 - 55.72 3.97 8.16 Thailand 21 49.44 42.08 - 55.53 3.56 7.17 15 49.44 42.08 - 55.53 3.83 7.77 6 50.13 47.93 - 55.09 2.80 5.51 Cambodia 13 49.72 44.57 - 53.40 2.78 5.69 4 49.60 47.36 - 51.20 1.62 6.56 9 49.72 44.57 - 53.40 3.23 6.64 Philippines 28 48.59 42.14 - 53.77 3.09 6.38 22 48.92 43.12 - 53.43 2.95 6.08 6 48.48 42.14 - 53.77 3.86 8.03 Andaman Is. 36 47.45 39.97 - 51.12 1.98 4.20 18 47.98 39.97 - 49.60 2.27 4.80 18 46.84 44.50 - 51.12 1.70 3.61 Nicobar Is. 20 47.16 44.28 - 50.86 1.99 4.21 17 47.12 44.28 - 50.86 2.11 4.45 3 47.65 47.20 - 49.48 1.20 4.38 Borneo 37 49.70 41.84 - 57.38 3.29 6.62 26 49.93 41.84 - 57.38 3.59 7.20 11 49.40 45.05 - 55.40 2.58 5.21 Indonesia 27 50.24 44.31 - 58.06 3.57 7.14 20 50.98 44.31 - 58.06 3.94 7.84 7 49.31 44.97 - 52.10 2.22 4.53 Melanesia 30 47.96 44.16 - 55.65 3.07 6.36 20 48.66 44.54 - 55.65 3.13 6.43 10 46.73 44.16 - 52.76 2.92 6.15 Micronesia 15 47.44 43.88 - 51.68 2.76 5.76 7 47.44 43.88 - 51.51 2.85 5.96 8 46.91 44.88 - 51.68 2.87 5.99 Australia 27 46.07 41.35 - 52.89 3.01 6.47 18 46.16 41.35 - 52.89 3.10 6.70 9 46.07 42.89 - 52.68 2.94 6.26 Africa 29 47.44 41.45 - 53.96 2.73 5.77 18 48.32 45.32 - 53.96 2.04 4.25 11 45.93 41.45 - 53.35 3.33 7.23 Nat. America 33 48.11 43.69 - 52.64 2.32 4.78 10 49.88 45.76 - 52.64 2.16 4.36 23 47.82 43.69 - 52.47 2.25 4.70 Caucasian 29 45.71 40.95 - 53.82 3.21 6.96 15 45.13 40.95 - 53.82 3.69 8.10 14 46.88 42.69 - 51.27 2.60 5.55 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

485 Interorbital Index (mf-mf/fmo-fmo)

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (%) (%) (%) (%) (%) (%) (%) (%) (%)

Siberia 28 18.26 13.05 - 24.38 3.06 16.76 18 18.40 13.58 - 24.38 2.91 15.58 10 16.37 13.05 - 21.74 3.30 18.92 Mongolia 24 17.70 13.42 - 21.80 2.04 11.66 16 17.62 14.88 - 21.10 1.50 8.66 8 17.99 13.42 - 21.80 2.93 16.42 Korea 4 18.11 16.04 - 20.54 1.84 20.25 2 18.11 18.07 - 18.14 0.05 0.41 2 18.29 16.04 - 20.54 3.19 26.13 Ainu 3 18.80 17.93 - 19.83 0.95 8.79 2 19.31 18.80 - 19.83 0.73 5.64 1 17.93 17.93 - 17.93 - - Japan 13 17.46 14.49 - 22.02 1.98 11.48 10 17.44 14.49 - 18.57 1.41 8.26 3 17.46 14.76 - 22.02 3.67 35.50 S. China 6 20.67 17.32 - 24.75 2.57 12.18 3 20.15 17.32 - 24.75 3.75 31.64 3 21.18 20.13 - 22.98 1.44 11.76 N. China 16 19.92 14.15 - 22.06 2.65 14.24 13 19.94 14.15 - 22.06 2.73 14.72 3 17.91 16.38 - 21.77 2.78 26.02 Burma 39 17.88 12.76 - 25.26 2.29 12.80 22 17.95 14.12 - 25.26 2.47 13.65 17 17.52 12.76 - 21.37 2.08 11.82 Laos 24 18.41 15.72 - 23.37 1.90 10.12 16 19.07 16.53 - 23.37 1.83 9.46 8 17.64 15.72 - 21.79 1.82 10.15 Vietnam 23 18.98 14.70 - 22.18 2.38 12.67 14 19.56 15.06 - 22.18 2.27 11.79 9 18.11 14.70 - 21.50 2.47 13.74 Thailand 21 18.79 13.03 - 21.24 2.35 12.95 15 18.87 13.16 - 21.24 2.38 13.04 6 18.62 13.03 - 20.05 2.46 13.81 Cambodia 13 18.78 15.46 - 24.85 2.70 13.87 4 18.92 17.27 - 24.85 3.33 33.36 9 18.78 15.46 - 23.47 2.55 13.29 Philippines 28 19.53 13.76 - 25.76 2.18 11.20 22 19.25 13.76 - 25.76 2.41 12.45 6 19.91 18.85 - 21.45 0.93 4.62 Andaman Is. 36 20.76 15.93 - 25.67 2.09 10.09 18 21.11 17.81 - 24.54 1.81 8.63 18 20.46 15.93 - 25.67 2.35 11.51 Nicobar Is. 20 18.69 14.45 - 22.57 2.27 12.05 17 18.31 14.45 - 22.57 2.33 12.51 3 20.46 17.74 - 21.30 1.86 16.41 Borneo 37 19.05 12.59 - 25.57 2.94 15.41 26 20.04 12.59 - 25.57 3.00 15.20 11 18.02 13.21 - 20.78 2.16 12.33 Indonesia 27 19.41 16.00 - 22.20 1.81 9.45 20 19.60 16.00 - 21.42 1.82 9.45 7 17.91 17.43 - 22.20 1.94 10.17 Melanesia 30 18.60 13.87 - 22.21 2.02 10.78 20 19.72 13.87 - 22.21 2.04 10.65 10 18.03 15.93 - 21.27 1.69 9.49 Micronesia 15 18.74 16.49 - 23.09 1.92 10.11 7 18.58 17.13 - 23.09 2.35 12.26 8 18.99 16.49 - 20.81 1.62 8.57 Australia 27 19.03 16.33 - 25.09 2.05 10.71 18 19.90 16.63 - 25.09 2.06 10.46 9 17.68 16.33 - 21.68 1.64 9.08 Africa 29 21.62 18.39 - 26.16 2.04 9.33 18 21.99 18.39 - 25.27 2.10 9.55 11 20.58 19.81 - 26.16 2.01 9.30 Nat. America 33 19.62 0.00 - 24.38 4.08 21.16 10 19.23 0.00 - 24.38 6.77 37.38 23 19.72 15.95 - 23.94 2.14 10.81 Caucasian 29 19.70 15.60 - 24.80 2.46 12.30 15 21.05 16.23 - 23.84 2.34 11.37 14 19.58 15.60 - 24.80 2.49 12.87 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

486 Nasal Index (al-al/n-ns)

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (%) (%) (%) (%) (%) (%) (%) (%) (%)

Siberia 28 27.26 18.58 - 38.58 4.24 15.24 18 27.13 20.88 - 35.03 3.62 13.28 10 29.15 18.58 - 38.58 5.24 18.22 Mongolia 24 27.93 23.08 - 32.07 2.77 10.01 16 27.93 23.08 - 32.07 3.18 11.45 8 27.31 25.28 - 30.02 1.89 6.87 Korea 4 30.88 29.25 - 37.28 3.69 23.00 2 30.88 29.69 - 32.08 1.69 8.20 2 33.27 29.25 - 37.28 5.68 25.62 Ainu 3 30.04 28.21 - 35.53 3.81 21.33 2 32.79 30.04 - 35.53 3.89 17.78 1 28.21 28.21 - 28.21 - - Japan 13 31.71 29.17 - 37.09 2.41 7.51 10 31.83 29.45 - 34.87 1.98 6.22 3 31.71 29.17 - 37.09 4.04 21.65 S. China 6 29.43 23.49 - 36.61 4.51 15.08 3 30.85 28.02 - 36.61 4.38 24.08 3 27.85 23.49 - 32.50 4.51 28.23 N. China 16 28.96 26.20 - 37.02 3.10 10.30 13 29.10 26.20 - 35.79 2.62 8.76 3 28.33 26.90 - 37.02 5.48 31.18 Burma 39 28.91 20.54 - 36.64 3.29 11.52 22 28.96 20.54 - 33.57 3.19 11.16 17 28.91 21.85 - 36.64 3.53 12.32 Laos 24 27.96 23.48 - 35.68 3.23 11.47 16 27.59 23.48 - 33.42 3.28 11.70 8 28.56 25.30 - 35.68 3.33 11.66 Vietnam 23 28.24 22.38 - 32.03 2.43 8.56 14 27.30 22.38 - 32.03 2.73 9.70 9 29.32 24.97 - 30.73 1.96 6.80 Thailand 21 28.53 22.78 - 35.17 3.69 13.22 15 26.27 22.78 - 35.17 3.72 13.65 6 30.20 25.14 - 34.53 3.27 11.00 Cambodia 13 27.28 24.48 - 30.51 2.11 7.80 4 27.82 27.28 - 28.98 0.72 5.16 9 25.37 24.48 - 30.51 2.43 9.12 Philippines 28 30.13 24.99 - 35.25 2.75 9.15 22 30.03 24.99 - 35.25 3.00 10.06 6 31.37 29.50 - 32.86 1.21 3.89 Andaman Is. 36 29.72 24.29 - 36.55 2.97 9.91 18 30.90 24.29 - 36.55 3.43 11.18 18 29.34 25.76 - 33.89 2.34 7.99 Nicobar Is. 20 27.09 23.06 - 36.01 3.45 12.24 17 26.95 23.06 - 36.01 3.49 12.45 3 27.23 26.41 - 33.37 3.80 22.96 Borneo 37 28.51 23.38 - 39.62 3.88 13.39 26 28.70 23.89 - 39.62 4.15 14.14 11 28.05 23.38 - 32.55 3.19 11.31 Indonesia 27 28.64 23.91 - 41.87 3.70 12.70 20 28.55 23.91 - 41.87 4.12 14.02 7 29.31 24.80 - 30.56 2.16 7.60 Melanesia 30 34.65 0.00 - 40.04 7.02 21.35 20 33.22 0.00 - 38.60 8.03 25.42 10 36.13 29.54 - 40.04 3.42 9.66 Micronesia 15 32.63 28.13 - 44.60 4.79 14.25 7 32.63 28.13 - 39.32 3.98 12.18 8 33.41 29.25 - 44.60 5.55 16.15 Australia 27 32.16 27.88 - 38.09 2.88 8.80 18 31.98 28.31 - 38.09 3.04 9.36 9 33.32 27.88 - 36.41 2.63 7.91 Africa 29 30.35 25.28 - 42.55 3.51 11.40 18 30.85 25.28 - 42.55 4.07 12.96 11 29.96 25.76 - 32.91 2.21 7.41 Nat. America 33 33.86 31.31 - 41.75 2.49 7.21 10 33.86 31.31 - 39.44 2.55 7.43 23 33.86 31.97 - 41.75 2.51 7.24 Caucasian 29 30.66 23.25 - 39.00 3.63 11.93 15 30.66 26.79 - 39.00 2.87 9.17 14 30.30 23.25 - 34.80 4.22 14.31 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

487 Zygomatic Index (zyo-supzyg/zm-fmo)

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (%) (%) (%) (%) (%) (%) (%) (%) (%)

Siberia 28 100.61 84.35 - 136.16 12.20 11.91 18 103.74 88.34 - 136.16 12.26 11.57 10 93.91 84.35 - 110.46 9.71 10.09 Mongolia 24 99.82 79.36 - 114.77 10.26 10.32 16 99.82 82.81 - 114.45 8.93 8.85 8 97.26 79.36 - 114.77 12.65 13.11 Korea 4 102.43 86.89 - 106.90 8.89 17.83 2 95.53 86.89 - 104.17 12.22 19.18 2 103.80 100.69 - 106.90 4.40 6.35 Ainu 3 94.68 94.45 - 113.22 10.77 18.70 2 103.84 94.45 - 113.22 13.27 19.17 1 94.68 94.68 - 94.68 - - Japan 13 106.17 94.36 - 112.77 6.37 6.17 10 106.24 94.36 - 108.87 6.00 5.80 3 97.64 96.87 - 112.77 8.97 15.32 S. China 6 104.82 96.57 - 120.61 8.56 7.98 3 106.37 96.57 - 113.59 8.54 14.17 3 103.27 103.17 - 120.61 10.04 16.12 N. China 16 96.00 69.73 - 124.57 14.04 14.36 13 96.00 81.88 - 124.57 12.88 12.82 3 90.44 69.73 - 101.18 15.98 32.11 Burma 39 96.34 75.43 - 116.58 8.45 8.80 22 96.68 82.33 - 116.58 9.03 9.31 17 96.34 75.43 - 103.26 7.68 8.12 Laos 24 96.77 72.47 - 116.21 10.44 10.76 16 95.08 72.47 - 110.14 9.46 9.94 8 101.93 79.20 - 116.21 11.92 11.82 Vietnam 23 100.60 80.18 - 133.59 10.75 10.51 14 102.40 91.51 - 133.59 11.50 11.01 9 100.45 80.18 - 108.11 8.98 9.09 Thailand 21 99.81 83.71 - 121.31 9.23 9.13 15 100.46 83.71 - 121.31 10.26 10.07 6 97.21 93.35 - 108.52 6.30 6.36 Cambodia 13 95.57 74.02 - 119.94 12.17 12.95 4 98.13 88.84 - 100.42 5.30 11.00 9 93.86 74.02 - 119.94 14.41 15.51 Philippines 28 95.78 78.45 - 122.10 11.18 11.47 22 98.82 78.45 - 122.10 11.93 12.06 6 91.75 85.80 - 102.58 5.87 6.36 Andaman Is. 36 98.61 87.03 - 118.06 7.30 7.36 18 98.86 89.66 - 118.06 8.00 7.95 18 97.52 87.03 - 108.48 6.41 6.56 Nicobar Is. 20 98.96 0.00 - 113.47 24.25 25.63 17 101.26 0.00 - 113.47 26.32 27.74 3 89.48 89.33 - 100.28 6.28 11.81 Borneo 37 96.59 79.44 - 108.89 7.29 7.56 26 96.38 84.85 - 106.57 6.30 6.57 11 100.70 79.44 - 108.89 9.44 9.64 Indonesia 27 92.85 77.54 - 107.31 8.39 8.88 20 92.34 77.54 - 106.96 8.40 8.98 7 95.76 82.84 - 107.31 8.49 8.76 Melanesia 30 97.51 74.94 - 123.36 10.95 11.09 20 97.51 84.63 - 123.36 11.15 11.10 10 96.92 74.94 - 111.16 10.30 10.79 Micronesia 15 95.32 83.61 - 125.29 12.35 12.50 7 102.19 89.88 - 125.29 14.39 13.71 8 92.12 83.61 - 106.75 7.52 8.05 Australia 27 100.47 90.03 - 126.33 9.21 8.91 18 102.72 93.93 - 126.33 9.18 8.70 9 96.78 90.03 - 116.19 8.32 8.37 Africa 29 102.98 70.27 - 115.23 11.65 11.77 18 104.88 82.82 - 115.23 10.45 10.36 11 96.62 70.27 - 112.19 13.42 14.01 Nat. America 33 95.68 82.61 - 112.27 7.11 7.42 10 95.20 84.49 - 106.49 6.73 7.06 23 95.68 82.61 - 112.27 7.40 7.71 Caucasian 29 104.18 88.16 - 122.34 9.01 8.78 15 104.79 90.25 - 122.34 7.62 7.28 14 98.31 88.16 - 120.44 10.16 10.13 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

488 Superior Zygomatic Projection 1 (bi-supzyg/JUB)

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (%) (%) (%) (%) (%) (%) (%) (%) (%)

Siberia 28 104.69 102.17 - 107.81 1.56 1.48 18 104.98 103.00 - 107.81 1.53 1.45 10 103.48 102.17 - 105.20 1.16 1.12 Mongolia 24 103.64 101.19 - 107.10 1.48 1.43 16 103.84 101.19 - 107.10 1.70 1.63 8 103.62 102.26 - 104.30 0.75 0.73 Korea 4 105.75 104.18 - 106.00 0.85 1.62 2 104.86 104.18 - 105.53 0.96 1.37 2 105.98 105.96 - 106.00 0.03 0.04 Ainu 3 104.36 103.64 - 108.28 2.50 4.15 2 105.96 103.64 - 108.28 3.28 4.65 1 104.36 104.36 - 104.36 -- Japan 13 104.76 101.77 - 107.69 1.93 1.85 10 104.92 101.77 - 107.69 1.96 1.87 3 104.76 101.86 - 106.23 2.22 3.73 S. China 6 104.28 100.99 - 106.05 1.82 1.76 3 102.18 100.99 - 104.58 1.82 3.11 3 104.39 104.17 - 106.05 1.03 1.72 N. China 16 103.75 100.79 - 106.78 1.37 1.33 13 103.99 101.96 - 106.78 1.15 1.11 3 102.23 100.79 - 103.47 1.34 2.30 Burma 39 103.56 100.88 - 106.74 1.48 1.43 22 104.17 100.88 - 106.74 1.48 1.42 17 103.20 101.07 - 106.41 1.37 1.32 Laos 24 103.16 101.90 - 106.27 1.31 1.27 16 102.89 101.90 - 106.27 1.30 1.26 8 104.06 102.31 - 106.05 1.26 1.21 Vietnam 23 104.60 101.90 - 106.76 1.51 1.45 14 104.63 102.52 - 106.76 1.63 1.56 9 104.46 101.90 - 105.50 1.36 1.31 Thailand 21 103.24 101.91 - 106.46 1.51 1.46 15 103.48 101.91 - 106.46 1.60 1.54 6 103.02 101.96 - 105.42 1.36 1.32 Cambodia 13 103.77 102.04 - 106.49 1.62 1.55 4 102.78 102.33 - 104.02 0.73 1.42 9 104.18 102.04 - 106.49 1.71 1.64 Philippines 28 104.14 101.96 - 107.08 1.20 1.15 22 103.90 101.96 - 107.08 1.16 1.11 6 104.73 103.81 - 106.89 1.21 1.16 Andaman Is. 36 102.91 100.65 - 107.00 1.36 1.32 18 103.30 101.02 - 107.00 1.52 1.47 18 102.81 100.65 - 104.91 1.05 1.02 Nicobar Is. 20 103.05 99.94 - 104.52 1.35 1.32 17 103.15 99.94 - 104.52 1.22 1.18 3 101.45 100.30 - 101.82 0.79 1.37 Borneo 37 104.02 100.08 - 107.10 1.56 1.50 26 103.78 100.08 - 107.10 1.63 1.57 11 104.88 102.01 - 105.94 1.39 1.33 Indonesia 27 103.43 100.99 - 107.59 1.61 1.55 20 103.62 100.99 - 107.59 1.68 1.62 7 103.14 101.88 - 105.81 1.52 1.47 Melanesia 30 103.79 101.22 - 107.31 1.42 1.37 20 103.79 101.83 - 107.31 1.56 1.50 10 104.12 101.22 - 104.67 1.18 1.14 Micronesia 15 104.33 102.31 - 106.67 1.26 1.21 7 104.39 102.31 - 106.67 1.31 1.25 8 103.93 102.60 - 106.46 1.26 1.21 Australia 27 104.55 101.40 - 108.91 1.99 1.90 18 104.92 101.44 - 108.91 2.07 1.97 9 104.46 101.40 - 107.98 1.93 1.85 Africa 29 104.12 102.22 - 107.41 1.43 1.37 18 104.48 102.69 - 106.46 1.22 1.17 11 103.20 102.22 - 107.41 1.99 1.91 Nat. America 33 104.05 102.52 - 106.38 0.93 0.90 10 104.14 103.38 - 105.58 0.70 0.67 23 103.91 102.52 - 106.38 1.02 0.98 Caucasian 29 104.63 102.30 - 109.72 2.00 1.91 15 105.24 102.30 - 109.72 2.15 2.04 14 103.60 102.79 - 108.39 1.81 1.74 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

489 Superior Zygomatic Projection 2 (bi-supzyg/ZMB)

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (%) (%) (%) (%) (%) (%) (%) (%) (%)

Siberia 28 125.84 120.58 - 135.21 3.61 2.86 18 125.60 121.31 - 135.21 3.54 2.79 10 126.46 120.58 - 129.66 3.80 3.04 Mongolia 24 122.17 111.98 - 136.58 5.70 4.68 16 123.09 114.71 - 136.58 5.92 4.80 8 118.34 111.98 - 124.17 3.98 3.35 Korea 4 125.36 119.93 - 132.46 5.90 9.39 2 126.20 119.93 - 132.46 8.86 10.53 2 125.36 121.80 - 128.93 5.04 6.03 Ainu 3 121.71 117.76 - 122.74 2.63 3.81 2 122.23 121.71 - 122.74 0.72 0.89 1 117.76 117.76 - 117.76 -- Japan 13 120.70 116.16 - 133.48 4.48 3.68 10 120.94 117.18 - 133.48 4.56 3.73 3 119.06 116.16 - 125.14 4.58 6.68 S. China 6 121.77 120.07 - 123.04 1.16 0.96 3 121.39 120.07 - 122.15 1.05 1.52 3 122.35 120.39 - 123.04 1.37 1.97 N. China 16 120.81 109.86 - 137.13 7.80 6.44 13 120.98 109.86 - 137.13 8.09 6.62 3 118.63 110.68 - 124.42 6.90 10.24 Burma 39 120.71 107.83 - 137.15 5.78 4.78 22 121.49 107.83 - 129.00 5.69 4.69 17 119.47 110.67 - 137.15 6.05 5.01 Laos 24 120.43 109.55 - 125.29 3.56 2.98 16 119.97 109.55 - 123.36 3.54 2.98 8 121.12 115.80 - 125.29 3.24 2.67 Vietnam 23 120.31 115.18 - 135.52 4.96 4.07 14 120.08 115.18 - 127.25 3.74 3.09 9 122.74 116.45 - 135.52 6.49 5.26 Thailand 21 119.64 111.14 - 128.44 4.80 4.02 15 120.98 112.41 - 128.44 5.01 4.18 6 118.69 111.14 - 122.46 4.18 3.55 Cambodia 13 119.07 103.85 - 128.11 5.64 4.74 4 120.57 116.28 - 124.33 3.44 5.71 9 118.80 103.85 - 128.11 6.44 5.45 Philippines 28 122.63 114.11 - 132.49 4.95 4.04 22 122.90 114.56 - 132.49 4.80 3.90 6 120.09 114.11 - 128.98 5.57 4.60 Andaman Is. 36 120.01 112.14 - 138.52 5.27 4.36 18 119.26 112.32 - 138.52 5.88 4.87 18 120.50 112.14 - 130.64 4.71 3.88 Nicobar Is. 20 119.25 113.46 - 126.36 4.20 3.53 17 119.74 113.53 - 126.36 3.85 3.20 3 113.85 113.46 - 115.04 0.82 1.26 Borneo 37 119.06 113.86 - 132.68 4.83 4.02 26 119.62 113.86 - 132.68 5.17 4.29 11 118.52 114.62 - 126.20 3.93 3.29 Indonesia 27 122.15 110.73 - 134.84 4.93 4.04 20 122.21 110.73 - 134.84 5.22 4.25 7 122.15 114.46 - 125.52 4.17 3.45 Melanesia 30 122.90 115.24 - 132.84 4.49 3.64 20 123.88 115.24 - 132.84 4.68 3.78 10 121.68 117.49 - 130.45 4.02 3.30 Micronesia 15 118.78 113.15 - 127.69 3.33 2.80 7 120.29 118.07 - 127.69 3.28 2.72 8 117.39 113.15 - 121.48 2.55 2.17 Australia 27 133.57 121.47 - 145.40 6.60 5.02 18 133.73 121.47 - 145.40 6.49 4.87 9 130.62 121.48 - 134.84 6.07 4.72 Africa 29 123.54 107.48 - 132.27 5.80 4.74 18 124.40 107.48 - 132.27 5.99 4.87 11 122.36 114.37 - 129.29 5.53 4.57 Nat. America 33 120.22 113.13 - 127.92 4.20 3.50 10 120.35 113.13 - 124.65 3.94 3.28 23 120.22 114.27 - 127.92 4.38 3.65 Caucasian 29 127.96 114.29 - 144.52 5.97 4.70 15 128.91 120.40 - 144.52 5.61 4.34 14 122.42 114.29 - 132.27 5.07 4.10 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

490 Inferior Zygomatic Projection 1 (bi-infzyg/JUB)

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (%) (%) (%) (%) (%) (%) (%) (%) (%)

Siberia 28 106.39 103.13 - 109.96 1.71 1.61 18 106.75 104.02 - 109.96 1.70 1.59 10 105.83 103.13 - 108.34 1.63 1.54 Mongolia 24 106.25 102.25 - 110.62 2.37 2.22 16 106.70 102.25 - 110.62 2.46 2.30 8 105.84 102.64 - 109.12 2.16 2.05 Korea 4 108.46 103.59 - 109.36 2.69 5.00 2 105.66 103.59 - 107.73 2.92 4.15 2 109.28 109.20 - 109.36 0.11 0.15 Ainu 3 107.23 106.30 - 108.16 1.32 2.15 1 108.16 108.16 - 108.16 - - 1 106.30 106.30 - 106.30 -- Japan 13 107.79 102.25 - 110.59 2.82 2.64 10 106.30 102.25 - 110.59 2.88 2.70 3 108.99 104.51 - 110.01 2.93 4.75 S. China 6 104.79 101.62 - 106.75 2.18 2.09 3 101.70 101.62 - 106.13 2.58 4.38 3 104.83 104.75 - 106.75 1.13 1.88 N. China 16 106.34 103.31 - 109.76 2.07 1.94 13 107.07 103.31 - 109.76 2.18 2.04 3 105.34 104.35 - 105.62 0.67 1.11 Burma 39 105.48 100.93 - 109.91 2.19 2.08 22 105.53 100.93 - 109.54 2.17 2.06 17 105.30 101.70 - 109.91 2.30 2.18 Laos 24 105.58 102.35 - 110.12 1.95 1.85 16 105.92 102.38 - 110.12 2.04 1.93 8 104.01 102.35 - 106.25 1.26 1.21 Vietnam 23 106.33 102.19 - 110.27 2.38 2.24 14 106.33 102.19 - 109.52 2.35 2.21 9 106.18 102.92 - 110.27 2.58 2.42 Thailand 21 106.67 103.10 - 109.90 1.73 1.62 15 106.32 103.58 - 109.90 1.62 1.52 6 107.20 103.10 - 109.26 2.06 1.92 Cambodia 13 106.46 101.78 - 111.06 2.32 2.17 4 106.94 101.78 - 109.91 3.42 6.43 9 106.46 105.22 - 111.06 1.88 1.76 Philippines 28 106.85 103.64 - 110.39 1.92 1.80 22 106.58 103.64 - 110.39 2.14 2.01 6 107.03 106.46 - 108.59 0.86 0.81 Andaman Is. 36 106.13 101.45 - 108.16 1.65 1.56 18 106.14 101.45 - 108.16 1.66 1.57 18 106.13 101.73 - 107.95 1.68 1.59 Nicobar Is. 20 103.36 100.81 - 106.04 1.38 1.34 17 103.28 100.81 - 106.04 1.49 1.44 3 103.44 102.53 - 104.00 0.74 1.26 Borneo 37 106.29 100.32 - 111.37 2.55 2.40 26 106.53 100.32 - 111.37 2.63 2.47 11 105.93 102.36 - 109.04 2.46 2.32 Indonesia 27 105.71 101.92 - 111.34 2.12 2.01 20 105.30 103.03 - 111.34 2.20 2.08 7 106.12 101.92 - 106.49 1.84 1.75 Melanesia 30 106.12 100.43 - 114.91 3.31 3.11 20 106.12 100.43 - 114.91 3.55 3.35 10 106.85 103.48 - 110.42 2.85 2.67 Micronesia 15 107.10 103.31 - 109.95 2.31 2.17 7 106.88 103.31 - 109.09 2.50 2.35 8 107.27 103.51 - 109.95 2.26 2.11 Australia 27 107.07 98.22 - 114.00 3.58 3.36 18 107.23 98.22 - 110.75 3.68 3.47 9 106.59 103.23 - 114.00 3.45 3.21 Africa 29 104.46 99.78 - 108.75 2.62 2.51 18 104.36 99.78 - 108.75 2.87 2.74 11 104.46 100.66 - 104.87 1.90 1.83 Nat. America 33 106.09 101.48 - 110.51 1.93 1.81 10 106.72 101.48 - 110.51 2.96 2.77 23 105.93 103.24 - 108.73 1.33 1.26 Caucasian 29 106.15 101.02 - 111.47 2.68 2.52 15 106.34 101.02 - 111.47 2.81 2.65 14 106.15 102.58 - 109.52 2.60 2.44 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

491 Inferior Zygomatic Projection 2 (bi-infzyg/ZMB)

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (%) (%) (%) (%) (%) (%) (%) (%) (%)

Siberia 28 126.81 122.81 - 136.10 3.65 2.85 18 126.81 123.30 - 136.10 3.80 2.97 10 126.89 122.81 - 132.58 3.53 2.77 Mongolia 24 123.57 114.49 - 136.83 5.34 4.27 16 126.89 118.03 - 136.83 5.44 4.29 8 122.65 114.49 - 124.54 3.26 2.68 Korea 4 129.26 119.26 - 135.21 7.23 11.27 2 127.23 119.26 - 135.21 11.28 22.55 2 129.26 125.70 - 132.82 5.04 5.85 Ainu 3 123.48 119.95 - 127.02 5.00 7.08 2 127.02 127.02 - 127.02 - 12.39 1 119.95 119.95 - 119.95 -- Japan 13 123.43 120.39 - 131.41 3.24 2.60 10 123.81 120.39 - 131.41 3.32 2.66 3 122.16 121.99 - 128.38 3.64 5.13 S. China 6 122.36 120.72 - 123.72 1.16 0.95 3 121.86 120.72 - 123.00 1.14 1.64 3 122.87 121.18 - 123.72 1.29 1.85 N. China 16 123.71 114.02 - 136.23 6.47 5.22 13 124.25 114.02 - 136.23 6.24 5.01 3 119.64 114.35 - 130.04 7.98 11.51 Burma 39 123.41 108.25 - 137.47 6.10 4.95 22 123.34 108.25 - 131.59 6.15 5.00 17 123.41 112.72 - 137.47 6.21 5.04 Laos 24 121.93 113.73 - 127.43 3.43 2.82 16 121.93 113.73 - 127.43 3.49 2.86 8 122.18 116.29 - 125.87 3.54 2.91 Vietnam 23 122.91 114.41 - 138.09 5.88 4.73 14 122.48 114.41 - 129.40 4.28 3.49 9 124.66 117.18 - 138.09 7.53 5.97 Thailand 21 123.81 114.05 - 127.98 4.19 3.42 15 123.76 114.05 - 127.98 4.23 3.45 6 123.81 115.24 - 124.98 4.35 3.58 Cambodia 13 122.33 102.64 - 131.33 6.64 5.44 4 124.65 120.76 - 127.42 2.98 4.80 9 122.05 102.64 - 131.33 7.71 6.36 Philippines 28 125.11 115.86 - 136.95 5.38 4.28 22 125.72 115.86 - 136.95 5.24 4.16 6 122.12 117.67 - 131.02 5.95 4.82 Andaman Is. 36 124.38 113.80 - 136.58 4.82 3.88 18 122.52 113.80 - 136.58 5.15 4.16 18 125.37 114.39 - 134.20 4.53 3.62 Nicobar Is. 20 120.97 112.24 - 124.49 3.54 2.95 17 122.19 112.24 - 124.49 3.47 2.87 3 116.29 115.98 - 117.29 0.69 1.03 Borneo 37 121.21 115.68 - 139.37 5.26 4.28 26 122.66 115.68 - 139.37 5.68 4.61 11 120.28 117.49 - 130.39 3.92 3.23 Indonesia 27 125.36 115.18 - 139.42 5.06 4.06 20 125.84 115.18 - 139.42 5.44 4.34 7 123.74 117.60 - 126.28 3.44 2.81 Melanesia 30 126.58 117.18 - 136.42 5.05 4.00 20 126.62 117.18 - 136.42 5.61 4.43 10 126.45 119.37 - 131.75 3.79 3.01 Micronesia 15 120.61 117.40 - 132.83 3.93 3.23 7 120.74 119.35 - 132.83 4.84 3.94 8 120.24 117.40 - 125.69 2.68 2.22 Australia 27 133.98 117.13 - 145.30 7.10 5.30 18 134.53 117.13 - 145.30 7.55 5.59 9 133.09 124.75 - 142.35 6.27 4.74 Africa 29 121.46 106.22 - 131.60 6.10 4.99 18 123.82 106.22 - 130.90 6.25 5.08 11 119.70 114.71 - 131.60 5.86 4.86 Nat. America 33 121.69 114.03 - 131.30 4.56 3.74 10 123.34 114.03 - 131.30 5.40 4.39 23 121.43 115.14 - 129.63 4.30 3.53 Caucasian 29 129.43 122.66 - 142.27 5.10 3.92 15 129.69 123.39 - 142.27 5.04 3.85 14 127.78 122.66 - 137.38 5.18 4.04 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

492 Palate Index (B/L)

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (%) (%) (%) (%) (%) (%) (%) (%) (%)

Siberia 28 89.75 74.42 - 129.08 10.51 11.69 18 89.75 74.42 - 129.08 12.49 13.87 10 89.46 81.32 - 104.55 6.46 7.20 Mongolia 24 90.20 76.87 - 116.31 9.26 10.13 16 88.99 76.87 - 116.31 9.87 10.83 8 90.92 82.00 - 105.15 8.62 9.37 Korea 4 100.01 84.97 - 104.87 10.37 21.47 2 102.44 100.01 - 104.87 3.44 5.03 1 84.97 84.97 - 84.97 - - Ainu 3 82.26 74.98 - 89.53 10.29 21.89 1 89.53 89.53 - 89.53 - - 1 74.98 74.98 - 74.98 - - Japan 13 88.03 74.81 - 99.80 7.56 8.61 10 89.14 74.81 - 99.80 8.04 9.12 3 87.71 78.78 - 92.34 6.90 13.99 S. China 6 89.68 80.42 - 101.75 8.59 9.43 3 88.60 84.36 - 100.58 8.41 16.14 3 90.75 80.42 - 101.75 10.67 20.52 N. China 16 88.39 79.13 - 114.25 9.42 10.17 13 91.08 79.13 - 114.25 10.29 10.95 3 87.90 86.67 - 88.38 0.88 1.76 Burma 39 87.08 74.02 - 118.91 8.95 10.13 22 87.63 74.02 - 99.35 7.69 8.83 17 85.93 77.58 - 118.91 10.32 11.49 Laos 24 89.09 76.77 - 113.23 8.21 9.20 16 89.16 76.77 - 113.23 8.88 9.80 8 85.44 77.35 - 93.76 5.72 6.65 Vietnam 23 89.22 77.10 - 111.56 8.62 9.61 14 86.32 79.44 - 102.86 7.56 8.58 9 90.76 77.10 - 111.56 10.08 10.96 Thailand 21 88.27 72.91 - 109.37 8.87 9.94 15 88.62 72.91 - 109.37 10.11 11.33 6 87.51 84.43 - 99.18 5.39 6.03 Cambodia 13 97.63 80.79 - 112.21 10.01 10.37 4 91.33 80.79 - 105.04 11.19 24.30 9 99.26 83.67 - 112.21 9.44 9.58 Philippines 28 90.13 72.33 - 108.63 9.91 10.85 22 90.13 78.55 - 108.63 8.67 9.41 6 86.64 72.33 - 106.83 13.94 15.72 Andaman Is. 36 81.84 70.75 - 115.49 10.47 12.28 18 81.34 70.75 - 115.49 11.27 13.11 18 81.91 71.72 - 114.79 9.82 11.63 Nicobar Is. 20 86.12 70.81 - 112.31 12.39 14.35 17 87.15 71.33 - 112.31 12.20 13.79 3 74.86 70.81 - 77.09 3.19 7.51 Borneo 37 87.60 70.05 - 111.51 9.50 10.69 26 87.79 77.03 - 111.51 8.95 10.00 11 84.50 70.05 - 106.66 11.02 12.60 Indonesia 27 84.14 71.44 - 99.92 7.31 8.52 20 84.90 72.68 - 99.92 7.47 8.64 7 84.14 71.44 - 91.14 6.74 8.09 Melanesia 30 80.65 63.70 - 94.33 8.35 10.29 20 80.19 67.11 - 94.33 7.55 9.33 10 82.95 63.70 - 92.19 10.19 12.51 Micronesia 15 83.89 75.11 - 93.81 5.93 6.98 7 83.76 75.11 - 92.24 7.62 9.13 8 84.00 81.15 - 93.81 4.73 5.50 Australia 27 77.57 64.12 - 87.20 5.70 7.28 18 80.99 69.74 - 87.20 4.88 6.09 9 74.41 64.12 - 83.51 5.64 7.57 Africa 29 81.71 0.00 - 118.92 18.25 22.78 18 80.01 0.00 - 118.92 22.29 28.45 11 81.71 73.02 - 97.21 8.57 10.32 Nat. America 33 89.81 76.91 - 99.51 5.76 6.46 10 85.93 81.58 - 99.51 6.72 7.58 23 90.27 76.91 - 97.91 5.50 6.15 Caucasian 29 88.16 0.00 - 112.89 19.40 22.17 15 87.96 0.00 - 104.03 24.90 29.93 14 91.58 78.26 - 112.89 9.93 10.77 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

493 Glabellar Projection (g-l/n-l)

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (%) (%) (%) (%) (%) (%) (%) (%) (%)

Siberia 28 99.72 97.76 - 101.67 0.86 0.86 18 99.78 97.76 - 101.67 0.81 0.81 10 98.83 98.53 - 101.18 0.92 0.93 Mongolia 24 99.64 98.13 - 101.44 0.79 0.79 16 99.70 98.13 - 100.46 0.77 0.77 8 99.61 99.28 - 101.44 0.78 0.78 Korea 4 100.77 99.56 - 101.28 0.89 1.76 2 100.16 99.56 - 100.77 0.86 1.29 1 101.28 101.28 - 101.28 -- Ainu 3 100.85 99.49 - 101.27 0.93 1.62 2 101.06 100.85 - 101.27 0.29 0.43 1 99.49 99.49 - 99.49 - - Japan 13 100.36 99.16 - 102.52 0.92 0.92 10 100.40 99.16 - 102.52 1.03 1.02 3 100.29 100.09 - 100.42 0.17 0.29 S. China 6 100.34 98.91 - 101.50 0.98 0.98 3 99.62 98.91 - 100.34 1.01 1.78 3 100.43 99.55 - 101.50 0.98 1.70 N. China 16 99.93 98.72 - 101.98 0.82 0.82 13 99.91 98.72 - 101.98 0.89 0.89 3 99.94 99.52 - 100.47 0.48 0.84 Burma 39 99.42 98.06 - 102.24 1.08 1.08 22 99.35 98.06 - 102.24 1.26 1.26 17 99.63 98.08 - 100.66 0.75 0.76 Laos 24 100.41 98.78 - 101.79 0.87 0.86 16 100.45 98.78 - 101.79 1.01 1.00 8 100.37 99.17 - 100.83 0.48 0.48 Vietnam 23 100.07 98.50 - 101.84 0.89 0.89 14 100.40 99.32 - 101.84 0.82 0.82 9 99.82 98.50 - 100.86 0.82 0.82 Thailand 21 100.43 98.16 - 102.11 1.03 1.02 15 100.76 98.88 - 102.11 0.94 0.93 6 99.66 98.16 - 100.43 0.79 0.79 Cambodia 13 100.12 99.08 - 102.28 0.85 0.85 4 100.93 100.32 - 102.28 0.83 1.64 9 99.91 99.08 - 101.01 0.62 0.62 Philippines 28 99.63 98.11 - 102.63 1.09 1.09 22 99.65 98.11 - 102.63 1.18 1.18 6 99.46 98.80 - 100.46 0.68 0.68 Andaman Is. 36 99.43 97.67 - 100.92 0.77 0.78 18 99.89 98.57 - 100.58 0.59 0.59 18 98.94 97.67 - 100.92 0.82 0.83 Nicobar Is. 20 100.98 99.29 - 102.79 0.91 0.90 17 101.15 99.29 - 102.79 0.99 0.97 3 100.94 100.90 - 101.01 0.05 0.09 Borneo 37 100.23 96.85 - 104.17 1.27 1.26 26 100.27 96.85 - 104.17 1.38 1.37 11 100.00 98.36 - 101.66 0.89 0.89 Indonesia 27 99.85 97.99 - 101.96 1.01 1.01 20 100.14 99.15 - 101.96 0.82 0.82 7 99.12 97.99 - 99.42 0.58 0.59 Melanesia 30 101.54 99.84 - 102.94 0.73 0.72 20 101.82 99.95 - 102.94 0.67 0.66 10 101.22 99.84 - 102.21 0.72 0.71 Micronesia 15 100.80 99.43 - 103.94 1.10 1.09 7 101.11 99.43 - 103.94 1.51 1.49 8 100.79 99.85 - 101.26 0.53 0.53 Australia 27 101.80 99.70 - 104.33 1.07 1.05 18 102.02 99.70 - 104.33 1.26 1.24 9 101.52 101.01 - 102.59 0.56 0.55 Africa 29 99.57 98.00 - 101.11 0.78 0.79 18 100.13 98.00 - 101.11 0.74 0.74 11 99.23 98.10 - 100.85 0.75 0.75 Nat. America 33 100.04 98.50 - 101.54 0.62 0.62 10 100.45 99.42 - 101.54 0.66 0.66 23 99.94 98.50 - 100.83 0.53 0.53 Caucasian 29 100.01 98.82 - 101.99 0.87 0.87 15 100.24 98.82 - 101.99 0.98 0.97 14 99.68 99.09 - 100.97 0.61 0.61 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

494 Gnathic Index (BPL/BNL)

Pooled Sex Male Female Population N Median Range SD CV* N Median Range SD CV* N Median Range SD CV* (%) (%) (%) (%) (%) (%) (%) (%) (%)

Siberia 28 98.16 87.02 - 104.32 4.05 4.14 18 97.98 87.50 - 104.32 3.99 4.08 10 98.61 87.02 - 103.06 4.38 4.47 Mongolia 24 97.47 88.73 - 104.92 4.39 4.50 16 98.26 88.73 - 104.92 5.01 5.12 8 96.45 93.51 - 101.81 3.10 3.18 Korea 4 91.10 86.98 - 97.93 4.57 9.96 2 91.10 90.42 - 91.78 0.96 1.58 2 92.45 86.98 - 97.93 7.74 12.56 Ainu 3 99.24 96.60 - 104.15 3.83 6.70 2 100.37 96.60 - 104.15 5.34 7.98 1 99.24 99.24 - 99.24 - - Japan 13 97.64 94.54 - 101.50 1.84 1.88 10 97.42 94.54 - 101.50 2.02 2.07 3 97.75 96.91 - 99.42 1.28 2.28 S. China 6 99.22 89.02 - 102.73 5.00 5.07 3 102.48 99.04 - 102.73 2.06 3.56 3 98.92 89.02 - 99.40 5.86 10.70 N. China 16 94.88 89.90 - 103.26 3.37 3.51 13 94.78 89.90 - 100.28 3.00 3.15 3 96.53 95.41 - 103.26 4.25 7.55 Burma 39 95.55 88.66 - 108.68 4.48 4.69 22 96.41 89.05 - 108.68 4.55 4.72 17 94.16 88.66 - 102.07 4.33 4.58 Laos 24 99.57 90.74 - 108.00 4.02 4.05 16 97.89 90.74 - 107.88 4.28 4.35 8 100.21 97.51 - 108.00 3.03 3.00 Vietnam 23 96.55 91.16 - 105.05 3.51 3.62 14 96.08 91.77 - 101.51 3.05 3.17 9 97.10 91.16 - 105.05 4.21 4.32 Thailand 21 99.78 91.95 - 107.61 4.02 4.07 15 99.78 91.95 - 103.99 3.90 3.96 6 100.01 95.12 - 107.61 4.44 4.44 Cambodia 13 96.33 91.01 - 103.94 4.11 4.24 4 100.66 96.33 - 103.94 3.14 6.26 9 94.41 91.01 - 101.36 3.58 3.75 Philippines 28 99.46 84.79 - 109.89 5.96 6.08 22 99.46 84.79 - 109.89 5.80 5.91 6 96.11 90.97 - 105.60 7.10 7.27 Andaman Is. 36 100.00 92.40 - 109.86 4.51 4.51 18 99.00 92.40 - 106.54 4.34 4.41 18 102.38 93.67 - 109.86 4.30 4.24 Nicobar Is. 20 100.45 86.45 - 108.35 5.52 5.57 17 99.42 86.45 - 104.25 5.42 5.50 3 102.97 96.84 - 108.35 5.76 9.81 Borneo 37 98.46 90.41 - 105.36 3.81 3.88 26 98.82 90.97 - 105.36 3.74 3.80 11 98.12 90.41 - 103.86 4.11 4.21 Indonesia 27 98.98 89.57 - 105.47 4.42 4.50 20 97.65 89.57 - 104.01 4.16 4.28 7 102.41 97.25 - 105.47 3.28 3.22 Melanesia 30 102.15 92.82 - 113.10 4.77 4.63 20 102.83 95.29 - 111.92 4.26 4.13 10 101.55 92.82 - 113.10 5.87 5.73 Micronesia 15 98.55 94.74 - 104.23 2.33 2.35 7 99.23 96.28 - 104.23 2.56 2.57 8 98.05 94.74 - 101.19 2.09 2.12 Australia 27 102.67 94.98 - 114.15 4.21 4.10 18 102.17 94.98 - 106.30 3.28 3.24 9 106.10 99.05 - 114.15 4.29 4.05 Africa 29 99.29 90.11 - 109.52 4.56 4.59 18 98.85 90.11 - 104.30 4.22 4.31 11 101.30 95.93 - 109.52 4.45 4.38 Nat. America 33 97.51 90.93 - 104.57 3.58 3.66 10 97.79 94.76 - 104.57 3.82 3.86 23 97.51 90.93 - 104.22 3.49 3.57 Caucasian 29 92.01 87.10 - 101.38 3.84 4.14 15 91.12 87.10 - 97.61 3.18 3.48 14 93.31 88.33 - 101.38 3.99 4.23 * CVs calculated from sample means. Samples n < 5 corrected for low sample size (after Sokal and Braumann, 1980)

495 Appendix 6 Kruskal Wallis results for Indices: p-values* for post-hoc non-parametric group comparisons (Bonferonni corrected) Length/Breadth (anterior): Pooled Sex H:181.30; p:4.96E-27

NA Sib Mon Jap Schi Nchi Bur Lao Viet Thai Cam Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA 0.015 <0.001 - <0.001 - <0.001 <0.001 0.002 <0.001 <0.001 <0.001 <0.001 - 0.001 <0.001 0.009 - 0.008 - 0.003 Sib ------0.030 ------<0.001 - <0.001 0.034 - Mon 0.019 - 0.049 - - - 0.026 - - - 0.002 - - <0.001 - <0.001 <0.001 - Jap 0.010 - 0.015 0.002 - <0.001 0.008 0.002 0.008 - - 0.004 0.012 - 0.011 - - Schi 0.012 ------0.048 <0.001 0.045 - <0.001 0.007 <0.001 0.001 0.013 Nchi 0.017 0.003 - <0.001 0.019 0.003 0.046 - - 0.005 0.011 - 0.008 - - Bur - - 0.021 - - - <0.001 - - <0.001 0.033 <0.001 <0.001 - Lao - - - - - <0.001 0.013 - <0.001 0.003 <0.001 <0.001 0.018 Viet 0.007 - - - 0.008 - - <0.001 - <0.001 0.003 - Thai - - <0.001 <0.001 <0.001 - <0.001 <0.001 <0.001 <0.001 <0.001 Cam - - 0.001 - - <0.001 0.021 <0.001 <0.001 - Phi - <0.001 0.040 - <0.001 0.004 <0.001 <0.001 0.019 And <0.001 - - <0.001 - <0.001 <0.001 - Nic 0.014 <0.001 0.003 - 0.002 - 0.014 Bor 0.027 <0.001 - <0.001 0.003 - Indo <0.001 0.007 <0.001 <0.001 0.025 Mel <0.001 - 0.006 <0.001 Mic <0.001 - - Aus 0.003 <0.001 Af 0.005 Cauc *significant p-values (p 0.05) only presented here

496 Length/Breadth (anterior): Male-Only H:144.80; p:3.92E-16

NA Sib Mon Jap Nchi Bur Lao Viet Thai Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA -0.017--0.0070.0060.005<0.0010.0020.003-0.0250.001----- Sib ----0.040-0.0160.038---0.0390.019-0.032-- Mon 0.043----0.004-----<0.001-<0.0010.002- Jap -0.0300.0160.0120.0040.0070.006--0.007----- Nchi 0.023 0.019 0.024 0.002 0.006 0.017 - - 0.008 0.049 - 0.031 - - Bur -----0.007--<0.001-<0.001<0.001- Lao ----0.004--<0.001-<0.001<0.001- Viet - - - 0.004 - - <0.001 - <0.001 <0.001 - Thai - 0.030 <0.001 0.012 - <0.001 0.014 <0.001 <0.001 0.004 Phi - <0.001 - - <0.001 - <0.001 <0.001 - And 0.001 - - <0.001 - <0.001 <0.001 - Nic - <0.001 0.007 - 0.006 - - Bor 0.040 <0.001 - <0.001 0.001 - Indo <0.001 - <0.001 <0.001 0.032 Mel 0.004 - - <0.001 Mic 0.002 0.039 - Aus - 0.001 Af 0.008 Cauc *significant p-values (p 0.05) only presented here

497 Length/Breadth (anterior): Female-Only H:69.88; p:1.05E-8

NA Sib Mon Bur Lao Viet Thai Cam Phi And Bor Indo Mel Mic Aus Af Cauc NA <0.001 0.001 0.004 <0.001 - 0.001 0.010 0.009 0.012 0.030 0.025 0.030 - 0.012 - 0.028 Sib ------<0.0010.020<0.0010.032- Mon ------0.037--<0.0010.0130.0010.023- Bur ------0.001-<0.001-- Lao 0.046 - - - 0.013 0.023 - <0.001 0.006 <0.001 0.009 0.037 Viet 0.028-----0.012-0.025-- Thai - - 0.012 0.038 - 0.001 0.011 0.001 0.011 0.040 Cam ----0.002-0.001-- Phi - - - 0.002 0.029 0.003 - - And - - <0.001 - <0.001 - - Bor - <0.001 - 0.001 - - Indo 0.004 - 0.004 - - Mel 0.008 - 0.007 0.001 Mic 0.008 - - Aus 0.012 0.002 Af - Cauc *significant p-values (p 0.05) only presented here

498 Length/Breadth (posterior): Pooled Sex H: 113.40; p:2.67E-14

NA Sib Mon Jap Schi Nchi Bur Lao Viet Thai Cam Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA - 0.004 - - - 0.025 0.007 - 0.003 0.039 - - 0.004 - - - - 0.024 0.001 - Sib ------<0.001 - - 0.044 0.033 0.003 <0.001 - Mon - - 0.021 - - 0.010 - - - <0.001 <0.001 0.007 - <0.001 0.003 <0.001 <0.001 0.002 Jap ------0.008 - - - - 0.046 0.008 - Schi ------0.030 0.003 - - 0.036 - 0.008 0.002 - Nchi 0.018 0.011 - 0.005 0.033 - - 0.025 - - - - - 0.022 - Bur - - - - - 0.003 <0.001 0.044 - 0.003 0.008 <0.001 <0.001 0.018 Lao 0.010 - - - <0.001 <0.001 0.005 - <0.001 0.004 <0.001 <0.001 0.003 Viet 0.010 0.046 - - 0.009 - - - - 0.043 0.002 - Thai - - <0.001 <0.001 0.007 - <0.001 0.003 <0.001 <0.001 0.003 Cam - 0.006 <0.001 0.034 - 0.004 0.024 <0.001 <0.001 0.020 Phi 0.022 <0.001 - - 0.009 0.015 <0.001 <0.001 0.050 And 0.007 - 0.028 - - - 0.003 - Nic 0.002 <0.001 0.014 - - - 0.035 Bor - - - 0.019 <0.001 - Indo 0.020 0.040 <0.001 <0.001 - Mel - - 0.004 - Mic --- Aus -- Af 0.022 Cauc *significant p-values (p 0.05) only presented here

499

Length/Breadth (posterior): Male-Only H:59.91; p:2.12E-6

NA Sib Mon Jap Nchi Bur Lao Viet Thai Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA ------Sib ------0.012----0.0390.022- Mon ------0.011<0.0010.048-0.005-<0.001<0.001- Jap ------0.015-----0.029- Nchi ------0.013-----0.043- Bur -----0.001----0.0090.002- Lao - - - 0.034 <0.001 - - 0.022 - 0.002 <0.001 - Viet ---0.011-----0.020- Thai - 0.004 <0.001 - - 0.005 - <0.001 <0.001 - Phi 0.035 <0.001 - - 0.018 - <0.001 <0.001 - And 0.022-----0.050- Nic <0.001 <0.001 0.026 0.015 - - 0.008 Bor - - - 0.013 0.003 - Indo - - 0.006 0.001 - Mel ---- Mic --- Aus -- Af 0.016 Cauc *significant p-values (p 0.05) only presented here

500

Length/Breadth (posterior): Female-Only H:57.11; p:1.59E-6

NA Sib Mon Bur Lao Viet Thai Cam Phi And Bor Indo Mel Mic Aus Af Cauc NA -0.0340.0060.001-0.015------0.037-0.009- Sib ------0.0450.0130.0200.0050.021 Mon ------0.015--0.0230.0130.0050.0030.015 Bur -----0.0080.014-0.0100.0020.005<0.0010.006 Lao 0.019 - - 0.024 0.002 0.006 - 0.001 0.003 0.001 0.001 0.002 Viet ------0.041- Thai - - 0.027 0.038 - 0.033 0.004 0.034 0.002 0.012 Cam ----0.0330.0340.0260.0140.040 Phi ------And -----0.021- Bor ------Indo - 0.020 0.044 0.005 - Mel - - 0.042 - Mic --- Aus -- Af - Cauc *significant p-values (p 0.05) only presented here

501 Length/Height: Pooled Sex H:21.60; p:1.56E-33

NA Sib Mon Jap Schi Nchi Bur Lao Viet Thai Cam Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA - - - 0.003 0.045 <0.001 <0.001 <0.001 <0.001 <0.001 0.006 <0.001 - 0.050 <0.001 - 0.029 0.007 <0.001 <0.001 Sib - - 0.002 0.022 <0.001 <0.001 <0.001 <0.001 <0.001 0.004 <0.001 - 0.027 <0.001 - 0.020 - 0.004 0.002 Mon - 0.014 - 0.008 <0.001 0.003 <0.001 0.001 0.028 0.015 - - 0.006 - - - 0.005 0.004 Jap 0.020 - - 0.003 0.024 0.002 0.007 - - - - 0.040 - - 0.015 0.001 <0.001 Schi ------0.002 0.030 - <0.001 - <0.001 <0.001 <0.001 Nchi - 0.012 0.039 0.009 0.032 - - 0.030 - - 0.002 - <0.001 <0.001 <0.001 Bur - - 0.016 - - - <0.001 - - <0.001 - <0.001 <0.001 <0.001 Lao - - - 0.032 0.005 <0.001 0.001 - <0.001 0.008 <0.001 <0.001 <0.001 Viet - - - 0.028 <0.001 0.022 - <0.001 0.022 <0.001 <0.001 <0.001 Thai - 0.015 0.002 <0.001 <0.001 0.032 <0.001 0.003 <0.001 <0.001 <0.001 Cam - 0.017 <0.001 0.007 - <0.001 0.010 <0.001 <0.001 <0.001 Phi - 0.005 - - <0.001 - <0.001 <0.001 <0.001 And <0.001 - - <0.001 - <0.001 <0.001 <0.001 Nic 0.044 <0.001 - 0.009 0.017 <0.001 <0.001 Bor - <0.001 - <0.001 <0.001 <0.001 Indo <0.001 - <0.001 <0.001 <0.001 Mel <0.001 - 0.008 0.004 Mic <0.001 <0.001 <0.001 Aus -- Af - Cauc *significant p-values (p 0.05) only presented here

502 Length/Height: Male-Only H:127.70; p:1.43E-18

NA Sib Mon Jap Nchi Bur Lao Viet Thai Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA -----0.0050.0370.002----0.041---0.023- Sib - - 0.011 <0.001 <0.001 <0.001 <0.001 0.003 <0.001 - 0.019 <0.001 - 0.015 - - - Mon --0.0120.0020.010<0.001-0.032--0.016----- Jap --0.0120.0140.006----0.029---0.0080.019 Nchi --0.0380.041-----0.003-0.003<0.0010.002 Bur -----<0.001--<0.001-<0.001<0.001<0.001 Lao - - 0.049 - <0.001 0.009 - <0.001 - <0.001 <0.001 <0.001 Viet - 0.021 0.040 <0.001 0.019 - <0.001 0.023 <0.001 <0.001 <0.001 Thai 0.016 0.018 <0.001 0.003 - <0.001 0.025 <0.001 <0.001 <0.001 Phi - 0.023 - - <0.001 - <0.001 <0.001 <0.001 And 0.005 - - <0.001 - <0.001 <0.001 <0.001 Nic - 0.001 - - - 0.004 0.014 Bor - 0.002 - 0.005 <0.001 <0.001 Indo <0.001 - <0.001 <0.001 <0.001 Mel 0.003 - - - Mic 0.005 <0.001 0.002 Aus -- Af - Cauc *significant p-values (p 0.05) only presented here

503 Length/Height: Female-Only H:73.98; p:1.98E-9

NA Sib Mon Bur Lao Viet Thai Cam Phi And Bor Indo Mel Mic Aus Af Cauc NA --0.0400.0010.0430.0170.008-0.002----0.0030.003<0.001 Sib --0.015------0.0200.0220.005 Mon -0.014-0.034------0.0480.005 Bur ------0.0030.003<0.001 Lao ----0.007--0.007-0.001<0.001<0.001 Viet ------0.0050.001<0.001 Thai -----0.026-0.0060.002<0.001 Cam ----0.011-0.0010.002<0.001 Phi -----0.0110.0080.003 And - - 0.006 - <0.001 <0.001 <0.001 Bor - - - 0.001 0.001 <0.001 Indo - - 0.026 0.009 0.003 Mel - 0.023 0.015 0.003 Mic 0.003 0.004 <0.001 Aus -- Af - Cauc *significant p-values (p 0.05) only presented here

504 Height/Breadth (anterior): Pooled Sex H:96.81; p:2.32E-11

NA Sib Mon Jap Schi Nchi Bur Lao Viet Thai Cam Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA 0.008 <0.001 - - - 0.030 0.021 - 0.007 - 0.005 0.037 - 0.047 0.014 - - - 0.014 <0.001 Sib - - - 0.019 - - 0.029 - - - - 0.020 - - <0.001 0.032 <0.001 - - Mon 0.005 - 0.002 0.007 - 0.001 0.028 0.020 - 0.006 0.001 0.005 - <0.001 <0.001 <0.001 - - Jap ------0.001 Schi ------0.042-0.031-- Nchi - 0.049 - 0.049 - 0.017 - - - 0.043 - - - - <0.001 Bur ------<0.001 - <0.001 - <0.001 Lao ------<0.001 - <0.001 - 0.016 Viet 0.033 - 0.017 - - - 0.049 - - 0.046 - <0.001 Thai ------<0.001 - <0.001 - 0.003 Cam - - - - - 0.019 - 0.015 - 0.007 Phi - 0.023 - - <0.001 0.020 <0.001 - 0.024 And - - - <0.001 - <0.001 - <0.001 Nic ------<0.001 Bor - <0.001 - <0.001 - <0.001 Indo <0.001 - <0.001 - 0.014 Mel - - <0.001 <0.001 Mic - - <0.001 Aus <0.001 <0.001 Af 0.005 Cauc *significant p-values (p 0.05) only presented here

505 Height/Breadth (anterior): Male-Only H:46.44; p:2.60E-4

NA Sib Mon Jap Nchi Bur Lao Viet Thai Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA -0.008------0.0200.031--0.023----0.007 Sib ------0.035-0.014-- Mon -0.030------0.004-<0.001-- Jap ------0.033 Nchi ----0.0160.044-0.0490.034----0.008 Bur ------0.036-0.001-- Lao ------0.032-0.007-- Viet ------0.017-- Thai -----0.026-0.003-- Phi - - - - 0.003 - <0.001 - - And - - - 0.011 - <0.001 - - Nic ------0.015 Bor - 0.018 - <0.001 - 0.035 Indo 0.006 - <0.001 - - Mel - - - 0.001 Mic --- Aus 0.026 <0.001 Af 0.049 Cauc *significant p-values (p 0.05) only presented here

506 Height/Breadth (anterior): Female-Only H:60.68; p:4.02E-7

NA Sib Mon Bur Lao Viet Thai Cam Phi And Bor Indo Mel Mic Aus Af Cauc NA0.0080.001---0.025------0.011<0.001 Sib - 0.037 - 0.005 - - - 0.014 0.032 - 0.002 0.010 0.010 - - Mon 0.020 - 0.002 - 0.020 - 0.002 0.012 - <0.001 0.003 0.005 - - Bur -0.020------0.002---0.004 Lao 0.019------0.0030.0300.030-- Viet 0.028-0.045------0.0220.002 Thai -----0.0040.026--0.019 Cam ----0.037---0.008 Phi ---0.010---- And - - 0.005 - - 0.033 <0.001 Bor - 0.009 - - - 0.004 Indo ----- Mel - - 0.004 <0.001 Mic - 0.023 0.002 Aus 0.040 0.001 Af - Cauc *significant p-values (p 0.05) only presented here

507 Height/Breadth (posterior): Pooled Sex H:93.45; p:8.80E-11

NA Sib Mon Jap Schi Nchi Bur Lao Viet Thai Cam Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA 0.025 0.017 - - 0.023 - - <0.001 - - - 0.005 0.001 - - - 0.025 - - 0.004 Sib - - - 0.001 0.006 0.008 <0.001 0.001 0.013 0.006 <0.001 <0.001 0.010 0.002 - <0.001 0.045 0.029 - Mon - - <0.001 0.004 0.007 <0.001 0.002 0.009 0.004 <0.001 <0.001 0.011 <0.001 - <0.001 0.036 0.012 - Jap - 0.030 - - 0.006 - - - 0.018 0.005 ------0.033 Schi ------Nchi 0.043 ------0.037 - 0.003 - 0.036 0.041 <0.001 Bur - 0.002 - - - 0.012 0.003 - - - 0.042 - - <0.001 Lao 0.028------0.002 Viet - - 0.014 - - 0.001 - <0.001 - 0.002 <0.001 <0.001 Thai ------0.008 - - - <0.001 Cam ------0.003 Phi - 0.033 - - 0.026 - - - <0.001 And - 0.011 - <0.001 - 0.009 0.014 <0.001 Nic 0.002 - <0.001 - 0.004 0.003 <0.001 Bor - - 0.042 - - 0.001 Indo 0.020 - - - <0.001 Mel 0.004 - - 0.037 Mic 0.026 0.031 <0.001 Aus - 0.012 Af 0.005 Cauc *significant p-values (p 0.05) only presented here

508 Height/Breadth (posterior): Male-Only H:61.53; p:1.16E-6

NA Sib Mon Jap Nchi Bur Lao Viet Thai Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA ------0.028---0.013------Sib --0.0240.0230.0400.0120.011-0.0050.003-0.016----- Mon - 0.007 0.005 0.013 0.004 0.004 0.025 0.002 <0.001 0.013 0.002 - 0.043 0.040 0.048 - Jap ------0.013------Nchi ------0.007---0.002 Bur ------0.008---0.002 Lao ------0.017---0.006 Viet - 0.029 - - 0.026 - 0.002 - 0.039 0.010 0.003 Thai -----0.003---<0.001 Phi -0.008------0.030 And - - - 0.002 - - 0.030 <0.001 Nic 0.004 - <0.001 - 0.011 0.002 <0.001 Bor - 0.033 - - - 0.004 Indo 0.002 - - 0.032 <0.001 Mel ---- Mic - - 0.016 Aus - 0.036 Af - Cauc *significant p-values (p 0.05) only presented here

509 Height/Breadth (posterior): Female-Only H:44.85; p:1.50E-4

NA Sib Mon Bur Lao Viet Thai Cam Phi And Bor Indo Mel Mic Aus Af Cauc NA 0.033 - - - 0.010 - - - 0.038 - - - 0.013 - - - Sib - - - 0.001 - 0.045 0.011 0.002 - - 0.027 0.005 - 0.022 - Mon - - 0.005 - - 0.039 0.013 - - - 0.010 - - - Bur - 0.001 - - 0.019 0.006 - - - 0.004 - - - Lao 0.046------Viet ----0.016---0.0160.038<0.001 Thai ------0.044--- Cam ------Phi ------0.012 And 0.033 - - - 0.033 - 0.001 Bor - - 0.017 - - - Indo ----- Mel 0.033 - - - Mic 0.017 0.033 0.001 Aus -- Af 0.046 Cauc *significant p-values (p 0.05) only presented here

510 Anterior Breath Proportion (sup/inf B): Pooled Sex H:75.72; p:2.06E-8

NA Sib Mon Jap Schi Nchi Bur Lao Viet Thai Cam Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA - - - 0.028 - <0.001 <0.001 0.002 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 0.007 <0.001 0.001 0.001 0.003 Sib - - 0.048 - 0.004 0.002 0.039 0.003 0.007 <0.001 0.002 <0.001 0.002 0.009 - 0.005 0.030 0.013 - Mon - - - 0.005 0.002 0.031 0.002 0.006 <0.001 0.001 <0.001 0.002 0.008 - 0.006 0.028 0.013 - Jap - - 0.024 0.010 - 0.016 0.013 0.004 0.013 0.006 0.020 0.050 - 0.029 - 0.047 - Schi ------Nchi - 0.019 - 0.026 0.017 0.010 0.026 0.011 0.019 - - 0.045 - - - Bur ------Lao ------0.049---- Viet ------Thai ------Cam - - - - - 0.025 - 0.039 - 0.050 Phi - - - - 0.010 - - - 0.017 And ------Nic - - 0.016 - - - 0.041 Bor ------Indo ----- Mel ---- Mic --- Aus -- Af - Cauc *significant p-values (p 0.05) only presented here

511 Anterior Breadth Proportion (sup/inf B): Male-Only H:59.84; p:2.17E-6

NA Sib Mon Jap Nchi Bur Lao Viet Thai Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA ----0.0230.018-0.0410.0040.0030.0040.0150.011--0.033-- Sib - - - 0.006 0.012 0.048 0.009 <0.001 <0.001 0.001 0.004 0.003 - 0.042 0.012 0.017 - Mon - - <0.001 <0.001 0.007 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 0.018 0.017 0.001 0.003 0.025 Jap -0.0490.033-0.0420.0070.0050.0050.0310.019----- Nchi 0.0420.029-0.0480.0060.0060.0040.0230.020----- Bur ------Lao ------Viet ------Thai ------Phi - - - - 0.022 - - - 0.019 And - - - 0.019 - - - 0.024 Nic - - 0.032 - - - 0.031 Bor ------Indo ----- Mel ---- Mic --- Aus -- Af - Cauc *significant p-values (p 0.05) only presented here

512 Posterior Breadth Proportion (sup/inf B): Pooled Sex H:122.0; p:1.20E-16

NA Sib Mon Jap Schi Nchi Bur Lao Viet Thai Cam Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA - - - - <0.001 0.002 0.039 0.011 <0.001 0.041 <0.001 <0.001 <0.001 <0.001 <0.001 - 0.007 - 0.001 0.015 Sib - 0.045 - <0.001 <0.001 0.014 0.006 <0.001 0.019 <0.001 <0.001 <0.001 <0.001 <0.001 - 0.004 - <0.001 0.005 Mon - - 0.003 0.011 - - 0.002 - 0.003 <0.001 0.011 0.004 <0.001 - 0.049 - 0.008 - Jap ------<0.001------Schi ------0.005------Nchi - 0.032 - - - - 0.009 - - - <0.001 - 0.003 - - Bur - - - - - <0.001 - - 0.045 0.005 - 0.006 - - Lao - 0.044 - - <0.001 - - 0.004 - - - - - Viet - - - <0.001 - - - 0.039 - - - - Thai - - <0.001 - - - <0.001 - 0.001 - - Cam -0.001------Phi <0.001 - - - 0.001 - 0.002 - - And <0.001 <0.001 0.002 <0.001 <0.001 <0.001 <0.001 <0.001 Nic - - 0.002 - 0.019 - - Bor - 0.002 - 0.002 - - Indo <0.001 0.048 <0.001 0.048 0.045 Mel 0.031 - 0.013 0.042 Mic --- Aus 0.018 - Af - Cauc *significant p-values (p 0.05) only presented here

513 Posterior Breadth Proportion (inf/sup B): Male-Only H:74.36; p:8.16E-9

NA Sib Mon Jap Nchi Bur Lao Viet Thai Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA ------0.0480.043<0.001--0.007----- Sib - - 0.007 0.007 0.031 0.010 0.004 0.002 <0.001 0.006 0.023 <0.001 - - - 0.030 - Mon -0.0220.037-0.0300.0090.008<0.0010.029-<0.001----- Jap ------0.010------Nchi - - - - - 0.014 - - - 0.004 - 0.012 - - Bur - - - - 0.004 - - - 0.003 - 0.002 - - Lao - - - 0.002 - - - 0.030 - 0.021 - - Viet ------0.005-0.010-- Thai - 0.011 - - - <0.001 0.044 <0.001 - - Phi 0.007 - - - <0.001 0.045 <0.001 - - And 0.004 <0.001 - <0.001 0.001 <0.001 <0.001 0.002 Nic - - <0.001 - 0.006 - - Bor 0.013 0.021 - 0.022 - - Indo <0.001 0.012 <0.001 0.013 - Mel - - 0.018 - Mic --- Aus 0.045 - Af - Cauc *significant p-values (p 0.05) only presented here

514 Posterior Breadth Proportion (sup/inf B): Female-Only H:65.19; p:6.83E-8

NA Sib Mon Bur Lao Viet Thai Cam Phi And Bor Indo Mel Mic Aus Af Cauc NA - - 0.027 - - 0.017 0.028 - <0.001 <0.001 0.002 0.032 0.004 0.037 0.003 0.002 Sib - 0.029 - - 0.028 0.045 - <0.001 <0.001 0.004 - 0.013 0.030 0.005 0.008 Mon ------<0.0010.005------Bur -----<0.0010.023------Lao ----<0.0010.0020.043---0.043- Viet ---<0.0010.019------Thai ------Cam -0.020------Phi 0.003------And 0.024 0.012 <0.001 0.008 <0.001 0.029 0.001 Bor - 0.009 - 0.014 - - Indo ----- Mel ---- Mic --- Aus -- Af - Cauc *significant p-values (p 0.05) only presented here

515 Frontal Length Proportion: Pooled Sex H:165.30; p:6.97E-25

NA Sib Mon Jap Schi Nchi Bur Lao Viet Thai Cam Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA - 0.035 0.012 0.048 - 0.041 0.027 - 0.002 0.031 - - - - - <0.001 - <0.001 <0.001 <0.001 Sib - 0.042 - - - - - 0.009 ------<0.001 - 0.006 0.007 0.011 Mon <0.001 ------0.018 0.001 - <0.001 0.001 <0.001 <0.001 <0.001 Jap 0.012 0.048 <0.001 0.001 0.016 <0.001 0.002 0.006 <0.001 0.020 - <0.001 - ---- Schi ------0.035 0.018 - <0.001 0.007 <0.001 <0.001 <0.001 Nchi - - - 0.012 ------<0.001 - 0.009 0.016 0.021 Bur ------0.049 0.002 - <0.001 0.001 <0.001 <0.001 <0.001 Lao - - - - - 0.035 0.003 - <0.001 0.002 <0.001 <0.001 <0.001 Viet - - - - - 0.023 - <0.001 0.030 <0.001 <0.001 <0.001 Thai - - 0.041 0.004 <0.001 - <0.001 <0.001 <0.001 <0.001 <0.001 Cam - - 0.029 0.004 - <0.001 0.003 <0.001 <0.001 <0.001 Phi - - 0.011 - <0.001 0.012 <0.001 <0.001 <0.001 And - 0.002 - <0.001 0.003 <0.001 <0.001 <0.001 Nic - 0.046 <0.001 - 0.010 0.015 0.026 Bor 0.004 <0.001 - 0.014 0.023 0.046 Indo <0.001 0.004 <0.001 <0.001 <0.001 Mel 0.002 - 0.019 0.040 Mic --- Aus -- Af - Cauc *significant p-values (p 0.05) only presented here

516 Frontal Length Proportion: Male-Only H:102.20; p:8.72E-14

NA Sib Mon Jap Nchi Bur Lao Viet Thai Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA --0.007----0.036-----<0.001-0.0130.011- Sib 0.0130.047-0.012-0.0080.002----0.015<0.001---- Mon <0.001------0.021-<0.0010.032<0.001<0.0010.001 Jap -<0.0010.0050.0070.0020.0110.0010.0070.0310.002----- Nchi ------0.001---- Bur ------0.011-<0.0010.012<0.001<0.001<0.001 Lao ------<0.001-0.0020.0010.014 Viet ----0.013-<0.0010.023<0.001<0.001<0.001 Thai - - 0.036 0.003 - <0.001 0.005 <0.001 <0.001 <0.001 Phi - - - - <0.001 - <0.001 <0.001 0.004 And - - - <0.001 0.044 <0.001 <0.001 0.003 Nic - - <0.001 - 0.013 0.011 - Bor 0.010<0.001---- Indo <0.001 0.013 <0.001 <0.001 0.002 Mel 0.021 0.038 0.044 0.041 Mic --- Aus -- Af - Cauc *significant p-values (p 0.05) only presented here

517 Frontal Length Proportion: Female-Only H:64.95; p:7.51E-8

NA Sib Mon Bur Lao Viet Thai Cam Phi And Bor Indo Mel Mic Aus Af Cauc NA -0.037-0.002-0.050-----0.003-0.0160.0220.003 Sib ------0.015-0.0300.0450.013 Mon ------0.021-<0.0010.0100.0010.002<0.001 Bur ------<0.001-0.0030.0080.001 Lao - - 0.032 - - 0.004 - <0.001 0.012 0.003 0.001 <0.001 Viet ------Thai - - - 0.031 - 0.001 0.020 0.002 0.005 <0.001 Cam ----0.004-0.0200.0240.008 Phi - - - 0.006 - 0.011 0.024 0.007 And 0.029 - <0.001 0.025 <0.001 <0.001 <0.001 Bor -0.045---- Indo 0.007 - 0.026 0.037 0.008 Mel ---- Mic --- Aus -- Af - Cauc *significant p-values (p 0.05) only presented here

518 Upper Facial Index 1 (NPH/ZMB): Pooled Sex H:121.40; p:1.55E-16

NA Sib Mon Jap Schi Nchi Bur Lao Viet Thai Cam Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA <0.001 - - 0.010 - - - - - 0.036 0.031 <0.001 0.023 0.010 - - <0.001 - 0.011 0.009 Sib - 0.006 <0.001 - <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 0.042 <0.001 - Mon - 0.003 - 0.041 0.049 0.007 0.007 0.002 <0.001 <0.001 <0.001 <0.001 0.027 0.031 <0.001 - <0.001 - Jap 0.032 ------0.014 - - - - 0.026 - - - Schi 0.002 0.032 0.040 0.039 ------0.030 - - 0.002 - 0.004 Nchi 0.032 0.034 0.014 0.014 0.006 0.002 <0.001 0.002 <0.001 0.036 0.021 <0.001 - <0.001 - Bur - - - - - <0.001 0.028 0.019 - - 0.002 - 0.023 0.005 Lao - - - - 0.002 - 0.047 - - 0.006 - 0.036 0.015 Viet - - - 0.011 - - - - 0.012 0.012 - 0.004 Thai ------0.017 - 0.004 Cam ------0.005 - 0.002 Phi ------0.001 - <0.001 And - - 0.003 0.003 - <0.001 - <0.001 Nic - - - - 0.001 - <0.001 Bor 0.036 - - <0.001 - <0.001 Indo - 0.002 - 0.037 0.003 Mel 0.006 - - 0.005 Mic <0.001 - <0.001 Aus <0.001 - Af <0.001 Cauc *significant p-values (p 0.05) only presented here

519 Upper facial Index 1 (NPH/ZMB): Male-Only H:81.17; p:5.35E-10

NA Sib Mon Jap Nchi Bur Lao Viet Thai Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA ------0.0490.016-0.044--0.010--- Sib - - - 0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 0.002 <0.001 - <0.001 - Mon - - 0.049 0.019 0.021 0.031 0.002 <0.001 0.005 <0.001 0.030 - <0.001 - 0.018 - Jap ------0.008-0.042--0.006--- Nchi - 0.044 - - 0.007 <0.001 0.013 0.003 - - 0.002 - 0.017 - Bur - - - - 0.008 - - - - 0.003 0.040 - 0.011 Lao - - - 0.019 - - - - 0.019 0.019 - 0.008 Viet - - 0.024 - - - - 0.011 0.028 - 0.018 Thai - 0.044 - - - - 0.017 0.040 - 0.019 Phi ------0.001 - <0.001 And - - 0.010 0.006 - <0.001 - <0.001 Nic - - - - 0.004 - <0.001 Bor - 0.031 - <0.001 - <0.001 Indo - 0.004 0.041 - 0.004 Mel 0.003 - - 0.012 Mic 0.001 - <0.001 Aus 0.014 - Af 0.006 Cauc *significant p-values (p 0.05) only presented here

520 Upper Facial Index 1 (NPH/ZMB): Female-Only H:41.10; p:5.40E-4

NA Sib Mon Bur Lao Viet Thai Cam Phi And Bor Indo Mel Mic Aus Af Cauc NA0.002------0.021---0.022-0.012- Sib - - - 0.002 0.045 <0.001 0.026 <0.001 0.008 - 0.038 <0.001 0.045 <0.001 - Mon ----0.026-0.013---0.019-0.015- Bur -----0.020-----0.024- Lao ----0.013---0.049-0.019- Viet ------Thai ------Cam ------0.040 Phi ------And ----0.019-0.005 Bor ------Indo - - - 0.046 - Mel ---- Mic - - 0.030 Aus 0.019 - Af 0.009 Cauc *significant p-values (p 0.05) only presented here

521 Upper Facial Index 2 (NPH/JUB): Pooled Sex H:104.10; p:2.34E-13

NA Sib Mon Jap Schi Nchi Bur Lao Viet Thai Cam Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA - - - <0.001 0.041 - - 0.007 - 0.041 <0.001 <0.001 0.007 0.006 0.046 0.004 <0.001 <0.001 0.002 - Sib - - <0.001 - 0.029 - 0.002 0.020 0.007 <0.001 <0.001 0.002 <0.001 0.005 <0.001 <0.001 <0.001 <0.001 - Mon - 0.004 - 0.022 0.041 0.005 0.014 0.009 <0.001 <0.001 0.005 0.001 0.005 0.001 <0.001 <0.001 <0.001 - Jap 0.017 0.043 - - - - - 0.048 0.001 - - - - 0.036 0.032 - - Schi <0.001 0.015 0.010 0.034 0.026 - - - - - 0.048 - - - - 0.016 Nchi 0.013 0.024 <0.001 0.012 0.006 <0.001 <0.001 <0.001 <0.001 0.004 <0.001 <0.001 <0.001 <0.001 - Bur - - - - 0.015 <0.001 - - - - 0.016 0.007 0.022 - Lao - - - 0.013 <0.001 - - - - 0.009 0.003 0.016 - Viet ---0.001------Thai --0.005------Cam -0.017------Phi ------0.013 And - 0.004 0.001 0.013 - - - <0.001 Nic ------Bor ------Indo ----- Mel ---- Mic - - 0.009 Aus - 0.004 Af 0.017 Cauc *significant p-values (p 0.05) only presented here

522 Upper Facial Index 2 (NPH/JUB): Male-Only H:61.67; p:1.10E-6

NA Sib Mon Jap Nchi Bur Lao Viet Thai Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA ------0.0030.0010.0210.0190.0410.0140.0080.0210.047- Sib - - - 0.039 0.044 0.039 - <0.001 <0.001 0.010 0.003 0.009 0.003 <0.001 0.001 0.009 - Mon - - 0.040 - - - <0.001 <0.001 0.020 0.004 0.012 0.008 0.004 0.010 0.018 - Jap - - - - - 0.014 0.003 - - - - 0.016 0.045 - - Nchi 0.046 0.040 0.039 - <0.001 <0.001 0.006 0.005 0.015 0.004 0.002 0.003 0.018 - Bur - - - 0.021 0.002 - - - - 0.028 - - - Lao ---0.001----0.022--- Viet - - 0.009 - - - - 0.038 - - - Thai 0.025 0.008 - - - - 0.017 - - - Phi ------0.026 And - - 0.026 0.050 - - - 0.003 Nic ------Bor ------Indo ----- Mel ---- Mic - - 0.025 Aus - 0.048 Af - Cauc *significant p-values (p 0.05) only presented here

523 Upper Facial Index 2 (NPH/JUB): Female-Only H:43.36; p:2.40E-4

NA Sib Mon Bur Lao Viet Thai Cam Phi And Bor Indo Mel Mic Aus Af Cauc NA ----0.013---<0.001---0.0450.0040.001- Sib - - - 0.013 - 0.045 - <0.001 - - 0.038 0.037 0.008 0.008 - Mon ------0.003----0.0340.023- Bur -----0.003----0.0440.041- Lao 0.018 - 0.018 - <0.001 - - - 0.049 0.008 0.029 - Viet ------Thai ------Cam ------Phi ------And 0.0150.020----0.005 Bor ------Indo - - - 0.037 - Mel ---- Mic --- Aus - 0.045 Af 0.049 Cauc *significant p-values (p 0.05) only presented here

524 Nasal Index: Pooled Sex H:166.50; p:4.15E-25

NA Sib Mon Jap Schi Nchi Bur Lao Viet Thai Cam Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA <0.001 <0.001 0.004 0.005 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 - - 0.004 <0.001 <0.001 Sib - <0.001 - 0.020 - - - - - 0.008 0.010 - - - <0.001 <0.001 <0.001 0.003 0.016 Mon <0.001 - 0.022 - - - - - 0.005 0.005 - - - <0.001 <0.001 <0.001 0.002 0.004 Jap - 0.024 <0.001 <0.001 <0.001 0.005 <0.001 - 0.048 0.001 0.002 0.003 - ---- Schi ------0.035---- Nchi - 0.047 - - 0.004 - - 0.025 - - <0.001 0.028 0.010 - - Bur - - - - 0.035 - - - - <0.001 <0.001 <0.001 0.017 0.041 Lao - - - 0.014 0.020 - - - <0.001 <0.001 <0.001 0.005 0.030 Viet - - 0.037 0.046 - - - <0.001 <0.001 <0.001 0.012 0.025 Thai - 0.025 0.032 - - - <0.001 0.002 <0.001 0.014 0.043 Cam <0.001 0.002 - - - <0.001 <0.001 <0.001 <0.001 0.004 Phi - 0.022 - - <0.001 0.043 0.005 - - And 0.017 - - <0.001 0.020 0.007 - - Nic - - <0.001 <0.001 <0.001 0.008 0.035 Bor - <0.001 <0.001 <0.001 0.016 - Indo <0.001 0.002 <0.001 0.042 - Mel - - <0.001 <0.001 Mic --- Aus 0.025 - Af - Cauc *significant p-values (p 0.05) only presented here

525 Nasal Index: Male-Only H:90.53; p:1.16E-11

NA Sib Mon Jap Nchi Bur Lao Viet Thai Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA <0.001 <0.001 - 0.001 <0.001 <0.001 <0.001 <0.001 <0.001 0.025 <0.001 0.001 <0.001 - - - 0.014 0.005 Sib - 0.001 0.008 - - - - 0.012 0.005 - - - <0.001 0.002 <0.001 0.002 0.001 Mon 0.002 - - - - - 0.033 0.011 - - - <0.001 0.006 <0.001 0.008 0.004 Jap 0.0330.0070.0040.0020.004--0.0030.0210.021----- Nchi - - 0.031 0.036 - - 0.041 - - 0.003 - 0.037 - - Bur ------<0.0010.0200.002-- Lao - - - 0.023 - - - <0.001 0.008 0.002 0.016 0.014 Viet - - 0.017 - - - <0.001 0.004 <0.001 0.011 0.005 Thai 0.008 0.005 - - - <0.001 0.008 <0.001 0.003 0.004 Phi ----0.001-0.043-- And 0.015------Nic - - <0.001 0.008 <0.001 0.009 0.005 Bor - <0.001 0.033 0.008 - - Indo <0.001 0.032 0.011 - - Mel - - 0.037 0.040 Mic --- Aus -- Af - Cauc

526 Nasal Index: Female-Only H:83.71; p:3.54E-11

NA Sib Mon Bur Lao Viet Thai Cam Phi And Bor Indo Mel Mic Aus Af Cauc NA <0.001 <0.001 <0.001 <0.001 <0.001 0.005 <0.001 <0.001 <0.001 <0.001 <0.001 - - - <0.001 <0.001 Sib ------0.008-0.025-- Mon -----0.018---<0.0010.0100.003-- Bur ----0.023---<0.0010.0070.003-- Lao - - - 0.033 - - - 0.002 0.011 0.018 - - Viet ------<0.001-0.004-- Thai 0.041----0.019---- Cam 0.008 0.014 - - <0.001 0.006 0.002 0.019 - Phi - - 0.018 0.031 - 0.039 - - And - - <0.001 0.025 0.002 - - Bor - <0.001 0.012 0.003 - - Indo 0.001 0.026 0.006 - - Mel - - 0.002 0.005 Mic --- Aus 0.008 - Af - Cauc *significant p-values (p 0.05) only presented here

527 Palate Index: Pooled Sex H:96.89; p:4.53E-12

NA Sib Mon Jap Schi Nchi Bur Lao Viet Thai Cam Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA ------0.002 - - 0.027 <0.001 0.019 <0.001 <0.001 - Sib ------0.023 - - - 0.002 - <0.001 0.003 - Mon ------0.005 - - 0.031 <0.001 0.027 <0.001 <0.001 - Jap ------0.036- <0.001 0.044 - Schi ------0.035 - 0.001 0.031 - Nchi ------0.010 - - 0.046 0.003 - <0.001 0.001 - Bur - - - 0.021 - - - - - 0.006 - <0.001 0.004 - Lao - - - - 0.036 - - - 0.003 - <0.001 0.002 - Viet - - - 0.024 - - - 0.002 - <0.001 0.003 - Thai - - 0.019 - - - 0.004 - <0.001 0.004 - Cam - 0.002 0.034 0.027 0.006 <0.001 0.011 <0.001 <0.001 - Phi 0.003 - - 0.014 <0.001 0.032 <0.001 <0.001 - And - 0.035 - - - 0.003 - 0.003 Nic ----0.012-- Bor - 0.004 - <0.001 0.004 - Indo - - <0.001 - 0.023 Mel - - - <0.001 Mic 0.001 - 0.046 Aus 0.044 <0.001 Af <0.001 Cauc *significant p-values (p 0.05) only presented here

528 Palate Index: Male-Only H:56.28; p:8.04E-6

NA Sib Mon Jap Nchi Bur Lao Viet Thai Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA ------0.011-<0.0010.018- Sib ------0.012-0.0010.022- Mon ------0.004-<0.0010.004- Jap ------0.047-0.003-- Nchi ------0.004-<0.0010.003- Bur - - - 0.034 - - - - 0.037 - 0.002 0.038 - Lao ------0.003-<0.0010.003- Viet ------0.024-0.0040.039- Thai -----0.014-<0.0010.022- Phi 0.014 - - 0.019 <0.001 - <0.001 <0.001 - And ------Nic - - - - 0.008 - - Bor - 0.004 - <0.001 0.005 - Indo 0.037 - 0.003 - - Mel - - - 0.003 Mic --- Aus - <0.001 Af 0.003 Cauc *significant p-values (p 0.05) only presented here

529 Palate Index: Female-Only H:44.42; p:1.70E-4

NA Sib Mon Bur Lao Viet Thai Cam Phi And Bor Indo Mel Mic Aus Af Cauc NA ------0.005-0.0280.020-<0.0010.032- Sib ------0.022----<0.001-- Mon ------0.041----<0.001-- Bur ------<0.001-- Lao ------0.004-- Viet ---0.033----<0.001-- Thai ------0.002-- Cam - 0.008 - 0.041 0.015 0.024 0.001 0.019 - Phi ------And ----0.003-0.021 Bor - - - 0.005 - - Indo - - 0.015 - 0.048 Mel - - - 0.038 Mic 0.002 - - Aus 0.028 <0.001 Af 0.032 Cauc *significant p-values (p 0.05) only presented here

530 Glabellar Index: Pooled Sex H:161.5; p:3.87E-24

NA Sib Mon Jap Schi Nchi Bur Lao Viet Thai Cam Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA 0.042 0.033 0.020 - - 0.045 0.048 - - - - 0.001 <0.001 - - <0.001 0.006 <0.001 - - Sib - <0.001 - - - 0.002 - 0.007 - - - <0.001 0.012 - <0.001 <0.001 <0.001 - - Mon 0.001 - - - 0.003 - 0.012 - - - <0.001 0.014 - <0.001 <0.001 <0.001 - - Jap - - 0.010 - - - - 0.031 <0.001 0.037 - 0.023 0.019 - 0.002 0.011 0.040 Schi ------0.030 - - - 0.019 - 0.005 - - Nchi ------0.007 <0.001 - - <0.001 0.031 <0.001 - - Bur 0.010 - 0.017 - - - <0.001 0.023 - <0.001 <0.001 <0.001 - - Lao - - - 0.032 <0.001 0.006 - - <0.001 - <0.001 0.011 - Viet - - - 0.020 <0.001 - - <0.001 0.016 <0.001 - - Thai - 0.043 <0.001 0.012 - - <0.001 - <0.001 0.014 - Cam - 0.015 0.007 - - <0.001 - <0.001 - - Phi - <0.001 - - <0.001 0.002 <0.001 - - And <0.001 <0.001 - <0.001 <0.001 <0.001 - 0.008 Nic 0.002 <0.001 - - 0.042 <0.001 <0.001 Bor - <0.001 - <0.001 0.036 - Indo <0.001 0.009 <0.001 - - Mel 0.007 - <0.001 <0.001 Mic 0.001 <0.001 0.017 Aus <0.001 <0.001 Af - Cauc *significant p-values (p 0.05) only presented here

531 Glabellar Index: Male-Only H:95.75; p:1.32E-12

NA Sib Mon Jap Nchi Bur Lao Viet Thai Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA 0.0180.006------0.0050.046--<0.001-0.0040.048- Sib - 0.008 - - 0.047 - 0.007 - - <0.001 0.042 - <0.001 0.040 <0.001 - - Mon 0.003 - - 0.016 - 0.001 - - <0.001 0.013 0.030 <0.001 0.012 <0.001 - 0.028 Jap ------0.005 - - - 0.036 - 0.021 0.046 - Nchi ------0.007--<0.001-<0.001-- Bur -----0.002--<0.0010.048<0.001-- Lao - - - 0.016 0.046 - - 0.001 - 0.002 - - Viet - - - 0.012 - - <0.001 - <0.001 - - Thai 0.027 0.001 - - - 0.001 - 0.004 0.010 - Phi - <0.001 - - <0.001 0.039 <0.001 - - And <0.001 0.027 - <0.001 0.018 <0.001 - - Nic 0.022 0.004 - - - <0.001 0.017 Bor - <0.001 - <0.001 - - Indo <0.001 - <0.001 - - Mel - - <0.001 0.001 Mic --- Aus <0.001 <0.001 Af - Cauc *significant p-values (p 0.05) only presented here

532 Glabellar Index: Female-Only H:84.16; p:4.18E-10

NA Sib Mon Bur Lao Viet Thai Cam Phi And Bor Indo Mel Mic Aus Af Cauc NA ---0.028----0.003-<0.001<0.0010.002<0.0010.011- Sib --0.019------0.0020.013<0.001-- Mon ------0.0130.0080.0220.001-- Bur 0.018------<0.0010.001<0.001-- Lao ----0.002-0.005--<0.0010.035- Viet ------0.0050.016<0.001-- Thai ----0.0300.024-0.001-- Cam - 0.027 - 0.015 0.019 - 0.001 - - Phi - - - 0.010 0.016 0.002 - - And 0.019 - <0.001 <0.001 <0.001 - 0.012 Bor 0.009 0.013 - <0.001 - - Indo <0.001 0.001 0.001 - 0.003 Mel - 0.037 <0.001 0.001 Mic 0.001 0.002 0.006 Aus <0.001 <0.001 Af - Cauc *significant p-values (p 0.05) only presented here

533 Gnathic Index: Pooled Sex H:122.20; p:1.11E-16

NA Sib Mon Jap Schi Nchi Bur Lao Viet Thai Cam Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA - - - - 0.017 0.010 ------<0.001 - <0.001 - <0.001 Sib - - - 0.014 0.009 ------<0.001 - <0.001 - <0.001 Mon ------<0.001- <0.001 - <0.001 Jap - 0.033 0.047 ------<0.001 - <0.001 - <0.001 Schi ------0.027 - 0.034 - 0.010 Nchi - 0.002 - 0.008 - - 0.001 0.014 0.013 0.023 <0.001 0.002 <0.001 0.003 0.013 Bur 0.002 - 0.007 - - <0.001 0.008 0.005 0.009 <0.001 0.002 <0.001 <0.001 0.004 Lao 0.048 ------0.003 - 0.003 - <0.001 Viet - - - 0.013 - - - <0.001 0.022 <0.001 0.031 <0.001 Thai ------0.002 - 0.003 - <0.001 Cam - 0.023 - - - <0.001 - <0.001 0.042 0.007 Phi - - - - 0.001 - 0.001 - <0.001 And - - - 0.013 - 0.017 - <0.001 Nic - - 0.044 - - - <0.001 Bor - <0.001 - <0.001 - <0.001 Indo 0.001 - <0.001 - <0.001 Mel 0.001 - 0.013 <0.001 Mic 0.003 - <0.001 Aus 0.012 <0.001 Af <0.001 Cauc *significant p-values (p 0.05) only presented here

534 Gnathic Index: Male-Only H:61.02; p:1.40E-6

NA Sib Mon Jap Nchi Bur Lao Viet Thai Phi And Nic Bor Indo Mel Mic Aus Af Cauc NA ------0.037 Sib --0.018------0.009-0.030-<0.001 Mon -0.0080.015------0.034-----0.001 Jap ------0.018-0.022-0.042 Nchi -0.039-0.017----0.0480.001-0.002-- Bur ------<0.001-<0.001-0.023 Lao ------0.002-0.003-0.003 Viet ------0.006-0.012-0.011 Thai -----0.013-0.039-0.001 Phi - - - - <0.001 - 0.002 - 0.007 And - - - 0.026 - - - 0.001 Nic - - 0.027 - - - 0.006 Bor - <0.001 - <0.001 - <0.001 Indo 0.002 - 0.006 - 0.002 Mel - - 0.006 <0.001 Mic - - 0.045 Aus 0.018 <0.001 Af 0.008 Cauc *significant p-values (p 0.05) only presented here

535 Gnathic Index: Female-Only H:64.70; p:8.30E-8

NA Sib Mon Bur Lao Viet Thai Cam Phi And Bor Indo Mel Mic Aus Af Cauc NA --0.0180.021----0.007-0.0170.015-<0.0010.0280.012 Sib ------<0.001-0.050 Mon ------0.017-0.0260.041-0.0010.0330.035 Bur 0.008 - 0.033 - - <0.001 - 0.002 0.002 0.046 <0.001 0.001 - Lao 0.033-0.024------0.030-0.002 Viet - - - 0.026 - 0.028 0.026 - 0.002 0.045 - Thai ------0.039-0.012 Cam - 0.004 - 0.007 0.010 - 0.001 0.009 - Phi -----0.039-- And 0.029 - - 0.045 0.025 - <0.001 Bor ---<0.001-- Indo - 0.044 - - 0.003 Mel 0.030 - - 0.002 Mic <0.001 - 0.041 Aus - <0.001 Af 0.001 Cauc *significant p-values (p 0.05) only presented here

536 Appendix 7 Variable loadings* after principal component analysis of Linear variables (all samples): Pooled Sex

Pooled Sex: Log-transformed

Variable PC1 PC2 PC3 PC4 PC5 PC6 Ln-Transformed pr-ns 0.534 -0.142 0.623 0.145 -0.157 -0.010 NPH 0.269 0.089 -0.011 0.001 -0.105 0.179 pr-g 0.190 0.128 0.033 0.138 0.013 0.276 pr-b 0.121 0.012 -0.008 -0.029 0.052 -0.019 n-al 0.142 0.132 -0.108 -0.050 0.091 0.089 Rfmo-mf 0.078 -0.121 -0.033 0.055 0.151 0.093 Lfmo-mf 0.113 -0.095 -0.100 0.082 0.039 0.122 JUB 0.085 0.000 -0.106 0.075 -0.002 -0.045 mf-mf -0.028 -0.235 -0.136 0.441 -0.485 -0.400 fmo-fmo 0.097 -0.139 -0.117 0.130 -0.005 0.034 fmt-fmt 0.087 -0.132 -0.104 0.086 -0.014 0.012 ZMB 0.074 0.045 -0.065 0.117 0.091 -0.130 al-al 0.196 -0.317 -0.266 -0.585 -0.466 0.011 BBH 0.053 0.054 -0.098 -0.106 0.062 -0.146 PAC 0.057 -0.228 0.111 -0.144 0.275 -0.330 n-ns 0.142 0.201 -0.142 -0.138 0.065 0.042 FRC 0.091 -0.012 0.023 -0.061 0.093 -0.055 n-l 0.073 -0.161 0.085 -0.069 0.115 -0.108 n-o 0.115 -0.066 -0.038 -0.040 0.080 -0.113 * Highest two variables loadings for each axis in bold (continued)

537 Pooled Sex: Log-transformed

Variable PC1 PC2 PC3 PC4 PC5 PC6 Ln-Transformed BNL 0.100 -0.056 -0.048 -0.117 0.148 -0.072 BPL 0.060 -0.212 -0.121 0.003 0.277 0.079 OCC 0.050 0.052 0.016 -0.059 0.092 -0.173 STB 0.063 0.175 0.088 0.127 -0.066 -0.126 Bipterionic breadth 0.174 0.129 0.126 -0.041 -0.087 -0.005 AUB 0.190 0.190 -0.087 0.026 -0.007 0.131 Biporionic breadth 0.181 0.170 -0.091 0.029 -0.029 0.035 ASB 0.124 0.018 -0.041 -0.049 -0.007 0.101 ju-au 0.207 -0.134 -0.080 -0.158 0.086 -0.034 zm-au 0.142 -0.128 -0.109 0.102 0.034 -0.061 Biparietal breadth 0.010 0.064 0.039 -0.069 0.030 -0.190 Bi-superior zygomatic 0.124 -0.018 -0.041 0.064 0.025 -0.152 Bi-inferior zygomatic 0.138 0.039 -0.044 0.060 -0.001 -0.038 Bimastoidale 0.190 0.141 -0.086 -0.015 -0.054 0.111 ms-po 0.104 0.148 -0.326 0.032 0.026 -0.368 zm-infzyg -0.012 -0.382 -0.248 0.337 0.009 0.299 zm-fmo 0.154 0.059 -0.090 -0.067 0.069 -0.006 zm-fmt 0.147 0.066 -0.258 0.040 -0.017 0.046 zyo-supzyg 0.172 -0.016 -0.103 0.034 0.028 0.034 FOL 0.128 -0.041 0.002 0.164 0.068 -0.017 ba-sphba 0.094 0.170 -0.090 0.202 0.252 -0.204 sphba-sta 0.100 0.071 -0.210 0.110 0.129 -0.022 sta-ol 0.032 -0.342 0.004 0.040 0.270 0.171 enm-enm 0.174 0.068 -0.048 0.038 -0.126 -0.108 g-l 0.099 -0.196 0.103 -0.119 0.206 -0.213 * Highest two variables loadings for each axis in bold 538 Pooled Sex: Mosimann Shape

Variable PC1 PC2 PC3 PC4 PC5 PC6 Size-corrected pr-ns -0.008 -0.045 0.222 0.085 0.184 0.038 NPH -0.141 -0.058 0.254 -0.074 0.067 0.075 pr-g -0.161 -0.008 0.151 0.031 0.333 0.506 pr-b 0.001 -0.155 -0.028 -0.190 0.114 0.170 n-al -0.070 -0.045 -0.015 -0.105 -0.155 0.001 Rfmo-mf 0.043 0.044 -0.005 0.044 -0.055 0.137 Lfmo-mf 0.013 0.091 0.008 0.023 -0.048 0.014 JUB -0.029 0.077 -0.174 0.093 -0.038 -0.135 mf-mf 0.025 0.078 -0.069 0.181 0.005 -0.021 fmo-fmo 0.049 0.237 -0.035 0.172 -0.143 0.034 fmt-fmt 0.071 0.218 -0.092 0.164 -0.152 0.090 ZMB -0.038 0.026 -0.261 0.066 0.464 0.112 al-al 0.021 0.023 0.048 -0.106 -0.076 -0.168 BBH -0.005 -0.170 -0.410 -0.413 -0.193 0.085 PAC 0.415 -0.201 -0.030 -0.058 0.264 -0.188 n-ns -0.094 -0.077 -0.036 -0.162 -0.064 -0.066 FRC 0.055 -0.180 -0.023 -0.087 -0.049 0.059 n-l 0.387 -0.170 0.195 0.099 -0.198 0.238 n-o 0.101 -0.070 0.042 0.011 -0.077 -0.165 BNL 0.099 -0.065 0.031 -0.204 -0.179 -0.017 * Highest two variables loadings for each axis in bold (continued)

539 Pooled Sex: Mosimann Shape

Variable PC1 PC2 PC3 PC4 PC5 PC6 Size-corrected BPL 0.210 0.251 -0.089 -0.137 -0.141 0.235 OCC 0.026 -0.229 -0.212 -0.071 0.006 0.259 STB -0.142 -0.313 -0.245 0.538 -0.264 0.095 Bipterionic breadth -0.123 -0.399 0.257 0.233 -0.059 -0.029 AUB -0.308 -0.097 0.113 -0.164 0.036 0.114 Biporionic breadth -0.268 -0.111 0.087 -0.105 -0.048 -0.076 ASB -0.037 -0.079 0.085 0.008 -0.281 -0.005 ju-au 0.047 0.010 0.144 -0.075 -0.024 -0.209 zm-au 0.026 0.152 0.011 0.085 0.101 -0.096 Biparietal breadth 0.053 -0.335 -0.429 0.109 0.080 -0.015 Bi-superior zyg. -0.008 0.014 -0.074 0.177 0.149 -0.372 Bi-inferior zyg. -0.088 -0.029 -0.006 0.165 0.046 -0.106 Bimastoidale -0.196 -0.115 0.167 -0.027 -0.259 0.011 ms-po -0.053 0.019 -0.159 -0.111 -0.028 -0.182 zm-infzyg 0.076 0.235 -0.047 0.113 -0.087 0.135 zm-fmo -0.028 -0.035 0.014 -0.118 0.031 -0.006 zm-fmt -0.074 0.062 -0.031 -0.117 -0.043 -0.095 zyo-supzyg -0.014 0.031 0.070 -0.023 0.012 -0.056 FOL 0.002 0.008 0.044 0.110 0.067 0.085 ba-sphba -0.038 -0.005 -0.082 -0.036 0.131 0.004 sphba-sta -0.039 0.056 -0.069 -0.045 0.010 0.077 sta-ol 0.152 0.134 -0.010 0.053 -0.170 0.207 enm-enm -0.047 0.001 0.030 -0.045 -0.012 -0.116 g-l 0.489 -0.251 0.208 -0.033 0.072 -0.026 * Highest two variables loadings for each axis in bold

540 Appendix 8 Variable loadings* after principal component analysis of Linear variables (excluding samples of n < 5): Pooled Sex

Pooled Sex: Log-transformed

Variable PC1 PC2 PC3 PC4 PC5 PC6 Ln-Transformed pr-ns 0.523 -0.001 0.666 0.088 -0.032 -0.089 NPH 0.270 0.072 0.037 -0.036 -0.052 0.156 pr-g 0.217 0.175 0.017 -0.051 -0.091 0.210 pr-b 0.110 0.010 -0.022 -0.021 0.051 0.019 n-al 0.134 0.107 -0.132 -0.088 0.054 0.147 Rfmo-mf 0.095 -0.100 -0.029 -0.021 0.149 0.091 Lfmo-mf 0.128 -0.098 -0.068 0.063 0.089 0.179 JUB 0.093 -0.010 -0.097 0.097 0.029 -0.011 mf-mf 0.019 -0.222 -0.013 0.687 -0.303 -0.198 fmo-fmo 0.121 -0.134 -0.077 0.128 0.036 0.086 fmt-fmt 0.106 -0.134 -0.065 0.092 0.015 0.037 ZMB 0.088 0.077 -0.118 0.063 -0.012 -0.174 al-al 0.156 -0.473 -0.122 -0.383 -0.597 -0.166 BBH 0.038 0.019 -0.117 -0.070 0.045 -0.206 PAC 0.021 -0.197 0.040 -0.068 0.257 -0.272 n-ns 0.124 0.153 -0.178 -0.164 -0.012 0.032 FRC 0.069 -0.013 -0.005 -0.023 0.103 0.053 n-l 0.069 -0.149 0.099 -0.073 0.157 -0.181 n-o 0.108 -0.065 -0.054 -0.027 0.051 -0.106 * Highest two variables loadings for each axis in bold (continued)

541 Pooled Sex: Log-transformed

Variable PC1 PC2 PC3 PC4 PC5 PC6 Ln-Transformed BNL 0.090 -0.073 -0.058 -0.126 0.137 -0.140 BPL 0.079 -0.198 -0.133 -0.094 0.221 0.028 OCC 0.040 0.061 -0.034 -0.076 0.006 -0.235 STB 0.061 0.200 0.065 0.142 -0.035 -0.053 Bipterionic breadth 0.156 0.129 0.135 -0.030 -0.034 -0.005 AUB 0.199 0.178 -0.092 -0.068 -0.064 0.068 Biporionic breadth 0.188 0.155 -0.096 -0.024 -0.070 -0.011 ASB 0.124 0.000 -0.019 -0.082 -0.007 0.075 ju-au 0.193 -0.150 -0.089 -0.158 -0.007 -0.045 zm-au 0.158 -0.110 -0.110 0.091 -0.014 -0.027 Biparietal breadth -0.013 0.073 -0.026 -0.024 -0.060 -0.134 Bi-superior zygomatic 0.119 -0.010 -0.058 0.115 0.044 -0.074 Bi-inferior zygomatic 0.141 0.046 -0.056 0.053 -0.024 0.000 Bimastoidale 0.197 0.112 -0.059 -0.072 -0.058 0.046 ms-po 0.105 0.098 -0.369 0.110 -0.050 -0.356 zm-infzyg 0.060 -0.361 -0.143 0.276 0.111 0.405 zm-fmo 0.141 0.043 -0.124 -0.072 -0.011 0.073 zm-fmt 0.159 0.016 -0.230 0.049 0.007 0.080 zyo-supzyg 0.175 -0.037 -0.073 0.053 0.129 0.078 FOL 0.152 0.005 -0.011 0.086 0.033 0.007 ba-sphba 0.111 0.190 -0.142 0.145 0.341 -0.314 sphba-sta 0.115 0.074 -0.266 0.060 -0.006 0.125 sta-ol 0.062 -0.309 0.045 -0.080 0.330 0.055 enm-enm 0.167 0.051 -0.029 0.112 -0.073 -0.061 g-l 0.076 -0.174 0.073 -0.086 0.211 -0.211 * Highest two variables loadings for each axis in bold

542 Pooled Sex: Mosimann Shape

Variable PC1 PC2 PC3 PC4 PC5 PC6 Size-corrected pr-ns -0.032 0.026 0.227 0.048 0.160 0.079 NPH -0.135 0.037 0.240 -0.089 0.198 0.131 pr-g -0.198 -0.018 0.206 -0.154 0.255 0.191 pr-b -0.012 -0.104 -0.033 -0.178 0.250 0.382 n-al -0.062 -0.027 -0.024 -0.084 -0.190 0.134 Rfmo-mf 0.043 0.016 0.006 0.016 -0.037 0.133 Lfmo-mf 0.021 0.086 -0.014 0.042 0.004 0.074 JUB -0.013 0.024 -0.187 0.157 0.041 -0.101 mf-mf 0.033 0.030 -0.062 0.201 0.147 -0.031 fmo-fmo 0.066 0.185 -0.068 0.211 0.019 0.148 fmt-fmt 0.097 0.145 -0.115 0.203 0.077 0.136 ZMB -0.081 -0.074 -0.221 -0.018 0.277 -0.332 al-al 0.035 0.064 0.008 -0.050 -0.029 -0.100 BBH 0.039 -0.251 -0.394 -0.358 0.139 0.059 PAC 0.377 -0.172 -0.003 -0.061 0.078 -0.232 n-ns -0.089 -0.052 -0.045 -0.140 -0.124 -0.042 FRC 0.046 -0.138 -0.011 -0.063 -0.025 0.323 n-l 0.421 -0.190 0.289 0.013 0.098 -0.060 n-o 0.099 -0.052 0.055 0.016 -0.224 -0.205 BNL 0.114 -0.050 0.031 -0.213 -0.268 -0.087 * Highest two variables loadings for each axis in bold (continued)

543 Pooled Sex: Mosimann Shape

Variable PC1 PC2 PC3 PC4 PC5 PC6 Size-corrected BPL 0.211 0.191 -0.139 -0.162 -0.378 0.231 OCC 0.020 -0.316 -0.112 -0.163 0.094 -0.043 STB -0.153 -0.445 -0.063 0.483 -0.215 0.193 Bipterionic breadth -0.125 -0.317 0.368 0.186 -0.010 0.007 AUB -0.315 -0.053 0.129 -0.240 -0.152 -0.045 Biporionic breadth -0.264 -0.074 0.107 -0.140 -0.183 -0.189 ASB -0.014 -0.067 0.110 0.005 -0.235 0.075 ju-au 0.038 0.079 0.108 -0.055 -0.239 -0.197 zm-au 0.008 0.146 -0.021 0.089 -0.072 -0.127 Biparietal breadth 0.018 -0.444 -0.309 0.087 -0.119 0.071 Bi-superior zyg. -0.025 0.037 -0.102 0.272 0.034 -0.198 Bi-inferior zyg. -0.103 -0.023 0.007 0.175 -0.076 -0.069 Bimastoidale -0.167 -0.080 0.200 -0.052 -0.108 -0.107 ms-po -0.048 0.003 -0.186 -0.053 -0.050 -0.123 zm-infzyg 0.091 0.166 -0.069 0.110 0.002 0.113 zm-fmo -0.036 0.000 -0.004 -0.109 -0.060 0.076 zm-fmt -0.056 0.071 -0.070 -0.073 -0.015 -0.088 zyo-supzyg -0.003 0.061 0.046 0.004 0.094 -0.019 FOL -0.007 -0.012 0.073 0.058 0.060 -0.046 ba-sphba -0.037 -0.031 -0.075 -0.049 0.123 -0.141 sphba-sta -0.046 0.033 -0.079 -0.060 -0.083 0.060 sta-ol 0.160 0.075 -0.005 0.015 -0.207 0.211 enm-enm -0.040 0.038 0.002 0.002 0.037 0.033 g-l 0.468 -0.175 0.253 -0.069 0.028 -0.038 * Highest two variables loadings for each axis in bold

544 Appendix 9 Variable loadings* after principal component analysis of Linear variables (all samples): Male-Only

Male-Only: Log-Transformed

Variable PC1 PC2 PC3 PC4 PC5 PC6 Ln-transformed pr-ns 0.513 0.000 0.608 0.189 0.158 0.185 NPH 0.273 0.084 -0.042 0.086 0.099 0.078 pr-g 0.239 0.153 -0.124 0.151 0.036 0.053 pr-b 0.107 0.001 -0.011 0.001 -0.061 0.015 n-al 0.151 0.078 -0.173 0.018 0.170 0.040 Rfmo-mf 0.092 -0.160 -0.088 0.079 0.124 -0.075 Lfmo-mf 0.117 -0.138 -0.110 0.034 -0.021 0.021 JUB 0.101 -0.033 -0.069 0.062 -0.035 -0.087 mf-mf -0.021 -0.480 0.213 0.264 -0.529 0.157 fmo-fmo 0.102 -0.173 -0.072 0.081 -0.050 0.044 fmt-fmt 0.067 -0.166 -0.068 0.063 -0.055 -0.089 ZMB 0.079 0.051 -0.126 0.120 -0.013 -0.133 al-al 0.213 -0.113 0.033 -0.686 -0.061 0.381 BBH 0.024 0.063 -0.086 -0.050 -0.152 -0.128 PAC 0.036 -0.107 0.162 -0.177 -0.190 -0.263 n-ns 0.157 0.109 -0.215 -0.011 0.093 -0.055 FRC 0.084 -0.008 0.042 0.016 -0.103 -0.080 n-l 0.067 -0.125 0.095 -0.097 0.052 -0.012 n-o 0.116 -0.067 0.001 -0.069 0.029 -0.143 BNL 0.079 -0.068 -0.014 -0.177 0.058 -0.180 * Highest two variables loadings for each axis in bold (continued)

545 Male-Only: Log-Transformed

Variable PC1 PC2 PC3 PC4 PC5 PC6 Ln-transformed BPL 0.029 -0.211 -0.181 -0.134 0.132 -0.161 OCC 0.060 0.100 -0.005 -0.102 -0.114 -0.146 STB 0.048 0.119 -0.018 0.155 -0.289 -0.188 Bipterionic breadth 0.146 0.178 0.063 0.053 -0.173 -0.071 AUB 0.170 0.084 -0.118 0.087 -0.005 -0.020 Biporionic breadth 0.186 0.055 -0.093 0.085 -0.050 0.030 ASB 0.119 -0.006 0.034 -0.010 -0.134 0.059 ju-au 0.199 -0.051 0.012 -0.214 0.052 -0.190 zm-au 0.174 -0.149 -0.070 -0.011 0.049 -0.142 Biparietal breadth 0.008 0.120 0.064 -0.087 -0.270 -0.086 Bi-superior zygomatic 0.128 -0.031 -0.043 0.063 -0.006 -0.121 Bi-inferior zygomatic 0.117 -0.035 -0.040 0.024 -0.042 -0.111 Bimastoidale 0.169 0.069 -0.072 0.104 0.014 -0.086 ms-po 0.068 0.068 -0.173 -0.178 -0.411 -0.181 zm-infzyg 0.037 -0.505 -0.249 0.094 0.045 0.067 zm-fmo 0.156 0.099 -0.086 -0.155 -0.098 0.166 zm-fmt 0.194 0.027 -0.169 -0.021 -0.205 0.152 zyo-supzyg 0.174 -0.038 0.057 -0.041 -0.036 -0.140 FOL 0.153 -0.047 0.011 0.095 0.083 -0.100 ba-sphba 0.039 0.058 0.111 0.069 0.029 -0.358 sphba-sta 0.157 0.057 -0.342 0.089 -0.121 0.240 sta-ol 0.065 -0.338 -0.119 0.008 0.205 -0.119 enm-enm 0.150 0.057 -0.087 -0.001 -0.045 -0.006 g-l 0.068 -0.091 0.187 -0.225 0.069 -0.298 * Highest two variables loadings for each axis in bold

546 Male-Only: Mosimann Shape

Variable PC1 PC2 PC3 PC4 PC5 PC6 Size-corrected pr-ns -0.023 0.028 0.210 0.080 -0.047 0.065 NPH -0.155 0.075 0.224 -0.016 0.017 0.204 pr-g -0.256 0.014 0.140 0.074 0.051 0.124 pr-b -0.041 -0.072 -0.081 0.100 -0.081 0.362 n-al -0.077 0.039 0.073 -0.158 0.017 -0.030 Rfmo-mf 0.030 0.089 -0.045 -0.002 -0.067 -0.021 Lfmo-mf 0.015 0.064 -0.060 0.032 -0.071 0.060 JUB -0.015 0.023 -0.162 0.162 -0.031 -0.099 mf-mf 0.067 0.029 -0.075 0.061 -0.197 -0.074 fmo-fmo 0.063 0.182 -0.168 0.045 -0.211 0.007 fmt-fmt 0.111 0.134 -0.232 0.008 -0.145 -0.034 ZMB -0.104 -0.047 -0.263 0.159 0.158 -0.211 al-al 0.025 0.006 0.060 -0.011 0.040 0.072 BBH 0.017 -0.285 -0.359 -0.384 0.012 0.237 PAC 0.328 -0.272 -0.069 0.487 0.046 0.243 n-ns -0.090 -0.005 0.035 -0.158 0.049 0.030 FRC 0.033 -0.158 -0.063 0.151 -0.149 0.051 n-l 0.346 -0.020 0.247 -0.192 -0.558 -0.178 n-o 0.106 0.024 0.042 -0.049 0.062 -0.173 BNL 0.140 -0.011 0.004 -0.318 0.186 -0.078 * Highest two variables loadings for each axis in bold (continued)

547 Male-Only: Mosimann Shape

Variable PC1 PC2 PC3 PC4 PC5 PC6 Size-corrected BPL 0.199 0.210 -0.304 -0.058 0.335 -0.078 OCC -0.013 -0.242 -0.029 -0.204 0.140 -0.110 STB -0.148 -0.318 -0.257 -0.099 -0.158 -0.380 Bipterionic breadth -0.219 -0.346 0.256 0.133 -0.133 -0.127 AUB -0.261 -0.003 0.060 0.010 0.147 -0.151 Biporionic breadth -0.220 -0.010 0.083 0.053 0.068 -0.161 ASB -0.023 -0.078 0.080 0.084 -0.153 -0.022 ju-au 0.027 0.014 0.171 0.026 0.219 -0.115 zm-au 0.034 0.140 0.052 0.148 0.104 -0.146 Biparietal breadth -0.007 -0.499 -0.161 0.061 -0.030 -0.039 Bi-superior zygomatic -0.030 0.035 -0.020 0.252 0.025 -0.156 Bi-inferior zygomatic -0.022 -0.003 -0.054 0.282 0.202 -0.157 Bimastoidale -0.158 0.004 0.123 -0.147 -0.004 -0.203 ms-po -0.008 -0.065 -0.080 -0.077 0.048 0.138 zm-infzyg 0.091 0.200 -0.161 0.085 -0.142 -0.064 zm-fmo -0.036 -0.047 0.052 -0.162 0.073 0.253 zm-fmt -0.073 0.047 0.005 -0.042 0.032 0.201 zyo-supzyg 0.019 0.015 0.100 0.037 -0.019 0.066 FOL -0.005 0.026 0.062 0.013 0.000 -0.103 ba-sphba 0.015 -0.059 -0.015 -0.032 0.023 -0.051 sphba-sta -0.078 0.055 -0.070 -0.018 0.012 0.109 sta-ol 0.107 0.174 -0.093 -0.059 -0.050 -0.163 enm-enm -0.042 -0.013 -0.031 -0.008 0.063 0.070 g-l 0.557 -0.229 0.315 -0.040 0.329 -0.091 * Highest two variables loadings for each axis in bold

548 Appendix 10 Variable loadings* after principal component analysis of Linear variables (excluding samples of n < 5): Male-Only

Male-Only: Log-transformed

Variable PC1 PC2 PC3 PC4 PC5 PC6 Ln-transformed pr-ns 0.519 0.091 0.629 -0.252 0.201 0.083 NPH 0.267 0.134 -0.004 0.014 0.066 0.036 pr-g 0.224 0.240 -0.073 0.034 -0.054 0.041 pr-b 0.094 0.005 -0.006 -0.004 0.047 0.015 n-al 0.153 0.100 -0.163 0.089 0.074 0.067 Rfmo-mf 0.125 -0.101 -0.046 0.081 0.189 -0.106 Lfmo-mf 0.128 -0.107 -0.076 0.058 0.110 -0.021 JUB 0.101 0.000 -0.055 0.130 0.058 0.018 mf-mf 0.024 -0.463 0.395 0.347 -0.447 0.332 fmo-fmo 0.125 -0.130 0.002 0.051 0.074 0.012 fmt-fmt 0.088 -0.144 -0.016 0.157 0.090 0.001 ZMB 0.072 0.123 -0.126 0.170 -0.050 0.082 al-al 0.187 -0.267 -0.233 -0.673 -0.437 -0.026 BBH 0.008 0.022 -0.070 0.111 -0.111 -0.091 PAC 0.015 -0.173 0.064 -0.027 0.191 -0.269 n-ns 0.145 0.116 -0.209 0.110 0.021 -0.085 FRC 0.070 -0.006 0.041 0.044 0.010 -0.124 n-l 0.079 -0.154 0.057 -0.047 0.025 -0.234 n-o 0.124 -0.064 -0.039 0.012 -0.003 -0.155 * Highest two variables loadings for each axis in bold (continued)

549 Male-Only: Log-transformed

Variable PC1 PC2 PC3 PC4 PC5 PC6 Ln-transformed BNL 0.097 -0.110 -0.070 -0.006 -0.046 -0.158 BPL 0.073 -0.195 -0.237 0.026 0.105 0.114 OCC 0.039 0.064 -0.058 0.033 -0.178 -0.111 STB 0.023 0.134 0.058 0.255 -0.330 -0.184 Bipterionic breadth 0.102 0.166 0.065 0.111 -0.244 -0.157 AUB 0.164 0.149 -0.103 0.069 -0.153 0.040 Biporionic breadth 0.181 0.118 -0.066 0.039 -0.161 0.041 ASB 0.107 -0.006 0.045 -0.053 -0.128 -0.085 ju-au 0.203 -0.066 -0.123 -0.057 -0.144 -0.135 zm-au 0.197 -0.093 -0.096 0.043 0.000 -0.114 Biparietal breadth -0.033 0.064 0.025 0.004 -0.229 -0.108 Bi-superior zygomatic 0.127 0.012 -0.046 0.118 0.056 -0.051 Bi-inferior zygomatic 0.119 0.006 -0.065 0.079 -0.051 0.051 Bimastoidale 0.173 0.123 -0.029 0.119 -0.137 -0.091 ms-po 0.032 -0.034 -0.146 0.085 -0.072 -0.143 zm-infzyg 0.104 -0.427 -0.185 0.202 0.111 0.075 zm-fmo 0.135 0.020 -0.075 -0.055 -0.037 0.342 zm-fmt 0.172 -0.002 -0.103 0.070 -0.023 0.331 zyo-supzyg 0.168 -0.064 0.047 0.098 0.090 -0.150 FOL 0.175 0.014 0.039 0.082 -0.008 0.024 ba-sphba 0.044 0.079 0.101 0.169 -0.046 -0.266 sphba-sta 0.144 0.103 -0.214 -0.022 0.122 0.290 sta-ol 0.135 -0.271 -0.115 0.090 0.074 -0.116 enm-enm 0.133 0.076 -0.083 -0.014 0.026 0.018 g-l 0.081 -0.148 0.062 -0.063 0.096 -0.233 * Highest two variables loadings for each axis in bold 550 Male-Only: Mosimann Shape

Variable PC1 PC2 PC3 PC4 PC5 PC6 Size-corrected pr-ns -0.023 0.028 0.210 0.080 -0.047 0.065 NPH -0.155 0.075 0.224 -0.016 0.017 0.204 pr-g -0.256 0.014 0.140 0.074 0.051 0.124 pr-b -0.041 -0.072 -0.081 0.100 -0.081 0.362 n-al -0.077 0.039 0.073 -0.158 0.017 -0.030 Rfmo-mf 0.030 0.089 -0.045 -0.002 -0.067 -0.021 Lfmo-mf 0.015 0.064 -0.060 0.032 -0.071 0.060 JUB -0.015 0.023 -0.162 0.162 -0.031 -0.099 mf-mf 0.067 0.029 -0.075 0.061 -0.197 -0.074 fmo-fmo 0.063 0.182 -0.168 0.045 -0.211 0.007 fmt-fmt 0.111 0.134 -0.232 0.008 -0.145 -0.034 ZMB -0.104 -0.047 -0.263 0.159 0.158 -0.211 al-al 0.025 0.006 0.060 -0.011 0.040 0.072 BBH 0.017 -0.285 -0.359 -0.384 0.012 0.237 PAC 0.328 -0.272 -0.069 0.487 0.046 0.243 n-ns -0.090 -0.005 0.035 -0.158 0.049 0.030 FRC 0.033 -0.158 -0.063 0.151 -0.149 0.051 n-l 0.346 -0.020 0.247 -0.192 -0.558 -0.178 n-o 0.106 0.024 0.042 -0.049 0.062 -0.173 BNL 0.140 -0.011 0.004 -0.318 0.186 -0.078 * Highest two variables loadings for each axis in bold (continued)

551 Male-Only: Mosimann Shape

Variable PC1 PC2 PC3 PC4 PC5 PC6 Size-corrected BPL 0.199 0.210 -0.304 -0.058 0.335 -0.078 OCC -0.013 -0.242 -0.029 -0.204 0.140 -0.110 STB -0.148 -0.318 -0.257 -0.099 -0.158 -0.380 Bipterionic breadth -0.219 -0.346 0.256 0.133 -0.133 -0.127 AUB -0.261 -0.003 0.060 0.010 0.147 -0.151 Biporionic breadth -0.220 -0.010 0.083 0.053 0.068 -0.161 ASB -0.023 -0.078 0.080 0.084 -0.153 -0.022 ju-au 0.027 0.014 0.171 0.026 0.219 -0.115 zm-au 0.034 0.140 0.052 0.148 0.104 -0.146 Biparietal breadth -0.007 -0.499 -0.161 0.061 -0.030 -0.039 Bi-superior zygomatic -0.030 0.035 -0.020 0.252 0.025 -0.156 Bi-inferior zygomatic -0.022 -0.003 -0.054 0.282 0.202 -0.157 Bimastoidale -0.158 0.004 0.123 -0.147 -0.004 -0.203 ms-po -0.008 -0.065 -0.080 -0.077 0.048 0.138 zm-infzyg 0.091 0.200 -0.161 0.085 -0.142 -0.064 zm-fmo -0.036 -0.047 0.052 -0.162 0.073 0.253 zm-fmt -0.073 0.047 0.005 -0.042 0.032 0.201 zyo-supzyg 0.019 0.015 0.100 0.037 -0.019 0.066 FOL -0.005 0.026 0.062 0.013 0.000 -0.103 ba-sphba 0.015 -0.059 -0.015 -0.032 0.023 -0.051 sphba-sta -0.078 0.055 -0.070 -0.018 0.012 0.109 sta-ol 0.107 0.174 -0.093 -0.059 -0.050 -0.163 enm-enm -0.042 -0.013 -0.031 -0.008 0.063 0.070 g-l 0.557 -0.229 0.315 -0.040 0.329 -0.091 * Highest two variables loadings for each axis in bold

552 Appendix 11 Variable loadings* after principal component analysis of Linear variables (all samples): Female-Only

Female-Only: Log-transformed Variable PC1 PC2 PC3 PC4 PC5 PC6 Ln-transformed pr-ns 0.663 -0.426 -0.256 0.029 -0.260 0.306 NPH 0.274 0.065 -0.054 0.028 -0.020 -0.074 pr-g 0.225 -0.003 -0.065 -0.202 0.034 0.097 pr-b 0.111 0.039 0.062 0.037 0.016 -0.148 n-al 0.194 0.062 -0.021 -0.003 0.045 -0.207 Rfmo-mf 0.104 -0.009 0.108 -0.054 0.088 0.064 Lfmo-mf 0.124 -0.004 0.098 -0.028 0.123 0.090 JUB 0.071 0.114 0.080 -0.079 0.119 0.007 mf-mf -0.042 0.059 0.383 -0.509 -0.392 -0.078 fmo-fmo 0.094 0.044 0.093 -0.132 -0.012 0.066 fmt-fmt 0.106 0.044 0.117 -0.166 -0.035 0.053 ZMB 0.103 0.147 0.049 -0.157 -0.014 -0.130 al-al 0.071 0.136 0.346 0.670 -0.323 0.057 BBH 0.027 0.072 0.034 0.058 -0.008 -0.205 PAC 0.076 -0.153 0.288 0.009 -0.026 -0.146 n-ns 0.151 0.113 -0.055 0.068 -0.036 -0.237 FRC 0.056 0.043 0.037 0.024 0.072 -0.141 n-l 0.109 -0.090 0.194 -0.023 0.018 -0.068 n-o 0.136 0.059 0.092 0.006 0.114 -0.119 BNL 0.137 0.062 0.054 0.052 0.103 -0.204 * Highest two variables loadings for each axis in bold (continued)

553 Female-Only: Log-transformed

Variable PC1 PC2 PC3 PC4 PC5 PC6 Ln-transformed BPL 0.126 -0.083 0.176 -0.001 0.023 -0.162 OCC 0.029 0.038 -0.020 -0.069 0.054 0.041 STB 0.090 0.078 -0.164 -0.180 0.092 -0.006 Bipterionic breadth 0.131 0.077 -0.100 -0.016 0.151 -0.022 AUB 0.103 0.209 -0.067 0.013 0.126 0.017 Biporionic breadth 0.094 0.199 -0.038 -0.026 0.149 -0.031 ASB 0.079 0.041 -0.051 0.054 0.121 -0.064 ju-au 0.179 0.116 0.236 0.174 0.067 0.057 zm-au 0.107 0.126 0.181 -0.020 0.084 0.109 Biparietal breadth 0.001 -0.041 -0.028 -0.082 -0.062 -0.107 Bi-superior zygomatic 0.089 0.152 0.061 -0.025 0.084 0.010 Bi-inferior zygomatic 0.067 0.140 0.063 -0.015 0.151 0.012 Bimastoidale 0.092 0.235 -0.056 0.107 0.141 -0.016 ms-po 0.068 0.344 -0.181 -0.068 -0.441 -0.100 zm-infzyg -0.038 0.134 0.314 -0.075 0.165 0.592 zm-fmo 0.142 0.148 -0.064 0.002 -0.080 0.033 zm-fmt 0.045 0.160 -0.026 -0.024 0.110 0.014 zyo-supzyg 0.080 0.254 -0.015 0.057 -0.111 0.254 FOL 0.099 0.086 0.103 -0.106 0.124 0.066 ba-sphba 0.040 0.324 -0.052 -0.155 -0.308 0.051 sphba-sta 0.114 0.043 0.088 0.036 -0.041 -0.231 sta-ol 0.141 -0.241 0.233 -0.112 0.133 -0.178 enm-enm 0.108 0.156 -0.121 0.006 0.257 -0.021 g-l 0.109 -0.103 0.253 -0.050 0.010 -0.034 * Highest two variables loadings for each axis in bold

554 Female-Only: Mosimann Shape

Variable PC1 PC2 PC3 PC4 PC5 PC6 Size-corrected pr-ns 0.026 0.231 -0.064 -0.152 -0.016 -0.012 NPH -0.045 0.259 -0.058 -0.243 -0.128 -0.107 pr-g 0.009 0.414 -0.223 -0.052 -0.004 -0.049 pr-b 0.053 -0.107 -0.041 -0.166 -0.346 0.073 n-al -0.025 0.093 -0.051 -0.172 -0.175 0.031 Rfmo-mf 0.045 0.042 -0.016 0.014 0.043 -0.019 Lfmo-mf 0.043 0.047 0.014 0.036 0.017 0.000 JUB -0.046 -0.097 0.077 0.164 0.076 0.304 mf-mf 0.033 -0.019 -0.011 0.095 0.081 0.076 fmo-fmo 0.048 0.089 -0.039 0.180 0.115 0.161 fmt-fmt 0.039 0.125 -0.029 0.227 0.132 0.214 ZMB -0.059 -0.041 -0.004 0.080 -0.083 0.088 al-al 0.011 -0.043 0.117 -0.029 -0.051 -0.115 BBH -0.020 -0.505 -0.097 -0.018 -0.251 -0.102 PAC 0.404 -0.199 -0.007 -0.178 0.083 -0.119 n-ns -0.035 0.021 -0.028 -0.113 -0.190 -0.050 FRC 0.000 -0.286 -0.066 -0.114 -0.033 0.095 n-l 0.421 -0.063 0.040 -0.181 0.218 -0.002 n-o 0.063 -0.051 0.132 -0.227 0.010 0.046 BNL 0.030 -0.100 0.112 -0.241 -0.137 0.052 * Highest two variables loadings for each axis in bold (continued)

555 Female-Only: Mosimann Shape

Variable PC1 PC2 PC3 PC4 PC5 PC6 Size-corrected BPL 0.191 -0.001 0.058 -0.014 -0.305 0.372 OCC 0.004 -0.202 -0.275 0.140 0.215 -0.219 STB -0.168 0.009 -0.425 -0.206 0.320 0.133 Bipterionic breadth -0.186 0.031 -0.105 -0.428 0.285 0.327 AUB -0.252 -0.090 0.048 -0.158 0.141 -0.126 Biporionic breadth -0.231 -0.116 0.056 -0.049 0.112 0.037 ASB -0.044 -0.165 -0.152 -0.151 0.005 0.018 ju-au 0.032 -0.010 0.257 -0.059 -0.003 -0.095 zm-au -0.005 0.031 0.177 0.079 0.130 -0.005 Biparietal breadth 0.088 -0.209 -0.599 0.210 -0.078 0.048 Bi-superior zygomatic -0.106 -0.097 0.153 0.142 0.068 0.198 Bi-inferior zygomatic -0.105 -0.205 0.158 0.106 0.095 0.210 Bimastoidale -0.256 -0.224 0.187 -0.165 0.142 -0.121 ms-po -0.089 0.039 -0.061 0.145 -0.166 -0.178 zm-infzyg 0.016 -0.007 0.134 0.238 0.160 0.014 zm-fmo -0.045 0.087 -0.041 0.024 -0.093 -0.128 zm-fmt -0.047 -0.074 -0.001 0.068 0.020 -0.010 zyo-supzyg -0.079 0.017 0.029 0.120 0.074 -0.205 FOL 0.011 0.012 0.009 0.033 0.105 -0.006 ba-sphba -0.055 -0.004 -0.001 0.120 -0.018 -0.144 sphba-sta 0.015 -0.018 -0.014 -0.004 -0.113 0.015 sta-ol 0.167 0.019 -0.034 0.049 -0.112 0.398 enm-enm -0.078 -0.007 0.056 -0.057 0.040 0.160 g-l 0.512 -0.044 0.049 -0.064 0.296 -0.122 * Highest two variables loadings for each axis in bold

556 Appendix 12 Variable loadings* after principal component analysis of Linear variables (excluding samples of n < 5): Female-Only Female-Only: Log-transformed

Variable PC1 PC2 PC3 PC4 PC5 PC6 Ln-transformed pr-ns 0.533 -0.384 -0.627 -0.037 -0.049 -0.017 NPH 0.241 0.051 -0.043 0.078 0.012 0.048 pr-g 0.196 0.115 -0.069 -0.011 0.104 0.068 pr-b 0.103 -0.015 0.087 0.082 0.006 0.042 n-al 0.150 0.068 0.044 0.064 -0.021 0.100 Rfmo-mf 0.100 -0.044 0.096 -0.043 0.164 -0.027 Lfmo-mf 0.133 -0.043 0.071 0.060 0.199 0.014 JUB 0.114 0.030 0.094 -0.111 0.085 0.040 mf-mf 0.023 -0.171 0.178 -0.600 -0.592 0.135 fmo-fmo 0.117 -0.022 0.050 -0.082 0.069 0.087 fmt-fmt 0.131 -0.050 0.043 -0.076 0.035 0.114 ZMB 0.155 0.115 0.103 -0.114 -0.079 0.055 al-al 0.078 -0.391 0.327 0.522 -0.266 0.048 BBH 0.034 0.047 0.102 0.093 -0.059 -0.118 PAC 0.031 -0.257 0.148 -0.018 -0.086 -0.388 n-ns 0.140 0.109 0.085 0.070 -0.055 0.103 FRC 0.067 0.010 0.046 0.034 -0.041 -0.116 n-l 0.533 -0.384 -0.627 -0.037 -0.049 -0.017 n-o 0.241 0.051 -0.043 0.078 0.012 0.048 BNL 0.196 0.115 -0.069 -0.011 0.104 0.068 * Highest two variables loadings for each axis in bold (continued)

557 Female-Only: Log-transformed

Variable PC1 PC2 PC3 PC4 PC5 PC6 Ln-transformed BPL 0.085 -0.170 0.097 -0.065 -0.003 -0.241 OCC 0.144 -0.007 0.108 -0.049 0.006 -0.151 STB 0.143 0.022 0.101 0.009 -0.045 -0.025 Bipterionic breadth 0.107 -0.151 0.121 -0.003 0.112 0.272 AUB 0.036 0.079 -0.007 0.053 0.004 -0.365 Biporionic breadth 0.120 0.165 -0.162 -0.075 -0.111 -0.154 ASB 0.138 0.070 -0.146 -0.026 -0.208 0.052 ju-au 0.161 0.164 0.016 0.019 -0.070 -0.090 zm-au 0.153 0.148 0.036 0.025 -0.054 -0.030 Biparietal breadth 0.099 0.060 -0.038 0.149 0.126 -0.079 Bi-superior zygomatic 0.180 -0.134 0.215 0.041 -0.006 -0.081 Bi-inferior zygomatic 0.143 -0.049 0.147 0.046 0.065 0.071 Bimastoidale -0.047 0.036 -0.014 -0.045 0.141 -0.124 ms-po 0.135 0.047 0.091 -0.076 0.031 0.065 zm-infzyg 0.111 0.045 0.078 -0.086 0.057 0.014 zm-fmo 0.183 0.118 0.027 0.125 -0.052 -0.118 zm-fmt 0.177 0.306 0.181 0.165 -0.249 0.201 zyo-supzyg 0.025 -0.149 0.272 -0.288 0.336 0.015 FOL 0.148 0.121 0.122 0.013 0.018 -0.029 ba-sphba 0.136 0.129 0.070 0.063 0.106 -0.004 sphba-sta 0.130 0.086 0.046 -0.041 0.089 -0.164 sta-ol 0.108 0.014 0.092 -0.125 0.026 -0.224 enm-enm 0.149 0.263 0.139 -0.245 0.158 -0.109 g-l 0.092 -0.012 0.127 0.122 -0.076 0.121 * Highest two variables loadings for each axis in bold

558 Female-Only Mosimann Shape

Variable PC1 PC2 PC3 PC4 PC5 PC6 Size-corrected pr-ns -0.017 0.083 0.205 0.137 0.001 -0.091 NPH -0.115 0.126 0.179 0.016 0.030 -0.193 pr-g -0.162 0.070 0.123 0.137 0.020 -0.143 pr-b 0.025 0.001 -0.109 -0.127 -0.365 -0.178 n-al -0.052 0.058 0.060 -0.080 -0.140 0.016 Rfmo-mf 0.032 -0.013 0.010 0.046 0.062 -0.086 Lfmo-mf 0.025 0.026 -0.029 0.045 0.031 -0.172 JUB -0.018 0.032 -0.165 0.157 0.167 0.174 mf-mf 0.042 0.001 0.010 0.007 -0.005 0.167 fmo-fmo 0.022 0.047 -0.014 0.219 0.053 -0.075 fmt-fmt 0.027 0.080 -0.018 0.202 0.008 0.000 ZMB -0.117 0.048 -0.164 -0.105 -0.019 0.395 al-al 0.061 0.046 -0.011 -0.081 -0.062 -0.146 BBH -0.004 -0.319 -0.320 -0.346 -0.206 0.008 PAC 0.411 -0.162 0.163 -0.271 -0.222 0.091 n-ns -0.049 0.031 0.000 -0.047 -0.068 0.007 FRC 0.007 -0.184 -0.040 -0.121 -0.139 -0.009 n-l 0.418 -0.084 0.237 0.011 0.218 0.133 n-o 0.061 0.081 0.098 -0.153 0.173 0.203 BNL 0.018 0.066 0.011 -0.132 0.013 0.158 * Highest two variables loadings for each axis in bold (continued)

559 Female-Only Mosimann Shape

Variable PC1 PC2 PC3 PC4 PC5 PC6 Size-corrected BPL 0.150 0.161 -0.161 0.191 -0.452 -0.060 OCC -0.034 -0.432 -0.106 -0.050 0.310 -0.200 STB -0.256 -0.313 0.410 0.019 -0.191 0.248 Bipterionic breadth -0.184 -0.096 0.479 0.167 -0.202 0.175 AUB -0.245 -0.057 0.088 -0.233 0.081 -0.058 Biporionic breadth -0.215 -0.022 -0.017 -0.146 0.194 -0.059 ASB -0.102 -0.193 0.037 0.084 -0.019 -0.438 ju-au 0.106 0.114 -0.036 -0.126 0.001 0.019 zm-au 0.045 0.097 -0.026 -0.061 0.006 -0.044 Biparietal breadth 0.048 -0.606 -0.158 0.396 -0.042 0.105 Bi-superior zygomatic -0.048 0.064 -0.159 0.111 0.142 0.112 Bi-inferior zygomatic -0.034 -0.022 -0.191 0.093 0.172 0.124 Bimastoidale -0.167 -0.004 0.101 -0.253 0.057 -0.268 ms-po -0.099 0.030 -0.107 -0.129 -0.011 0.133 zm-infzyg 0.091 0.014 -0.121 0.059 0.021 0.020 zm-fmo -0.050 0.019 -0.021 -0.046 0.085 0.033 zm-fmt -0.058 -0.027 -0.072 -0.007 0.043 -0.090 zyo-supzyg -0.022 -0.035 -0.016 0.033 0.136 -0.049 FOL 0.024 -0.024 0.023 -0.008 0.101 0.083 ba-sphba -0.058 0.009 -0.072 -0.060 0.108 0.104 sphba-sta 0.005 0.001 -0.070 -0.034 -0.113 0.035 sta-ol 0.132 0.071 -0.082 0.315 -0.121 -0.082 enm-enm -0.081 0.073 0.044 0.080 0.109 0.084 g-l 0.496 -0.070 0.223 -0.092 0.215 -0.151 * Highest two variables loadings for each axis in bold

560 Appendix 13 Variable loadings* after principal component analysis of Angular variables (all samples): Pooled Sex Pooled Sex: Raw Data

Angle PC 1 PC 2 PC 3 PC4 Raw NAA -0.349 0.195 -0.051 0.120 PRA 0.131 -0.034 0.147 -0.180 BBA 0.170 -0.158 0.015 -0.024 NBA -0.080 -0.212 0.200 -0.206 BBA 0.069 0.112 -0.086 0.132 NFA 0.047 -0.271 -0.051 0.081 SSA 0.092 -0.578 -0.291 0.649 FRA 0.016 0.107 0.210 0.118 PAA1 -0.112 0.155 -0.345 -0.143 PAA2 -0.011 0.174 -0.407 0.135 OCA -0.191 -0.059 0.673 0.317 NS -0.624 -0.282 -0.011 -0.177 PR 0.468 0.287 0.149 0.130 mf-n-zyo -0.057 0.072 -0.168 -0.071 ns-n-zyo -0.241 0.146 0.037 0.246 ns-n-ba -0.220 0.300 -0.070 0.192 n-ns-zyo -0.071 0.294 0.051 0.387 n-ns-ba 0.193 -0.194 0.022 -0.110 * Highest two variables loadings for each axis in bold

561

Pooled Sex: Log-transformed

Angle PC 1 PC 2 PC 3 PC4 Ln-transformed NAA -0.318 0.203 -0.107 0.238 PRA 0.119 -0.039 -0.035 -0.265 BBA 0.293 -0.145 0.241 0.099 NBA 0.010 0.140 0.184 0.004 BBA 0.047 -0.066 -0.184 0.034 NFA 0.028 0.009 0.116 0.077 SSA 0.066 0.011 0.226 -0.102 FRA 0.009 0.011 -0.056 0.092 PAA1 -0.144 -0.078 -0.025 -0.014 PAA2 -0.057 -0.083 -0.076 0.003 OCA -0.049 0.124 -0.006 -0.052 NS -0.272 0.307 0.275 -0.120 PR 0.375 -0.360 -0.500 0.279 mf-n-zyo -0.565 -0.769 0.196 -0.055 ns-n-zyo -0.330 0.239 -0.247 0.182 ns-n-ba -0.272 0.064 -0.274 0.359 n-ns-zyo -0.160 0.044 -0.530 -0.696 n-ns-ba 0.151 -0.071 0.085 -0.303 * Highest two variables loadings for each axis in bold

562 Appendix 14 Variable loadings* after principal component analysis of Angular variables (excluding samples of n < 5): Pooled Sex

Pooled Sex: Raw Data

Angle PC 1 PC 2 PC 3 PC4 Raw NAA -0.299 0.200 0.002 0.117 PRA 0.113 0.003 -0.072 -0.215 BBA 0.146 -0.196 0.038 0.142 NBA -0.115 -0.156 -0.146 0.069 BBA 0.087 0.077 0.063 0.002 NFA 0.004 -0.367 0.006 0.227 SSA 0.011 -0.670 0.233 -0.380 FRA 0.046 0.054 -0.229 0.200 PAA1 -0.090 0.219 0.379 -0.135 PAA2 0.023 0.167 0.394 -0.137 OCA -0.179 -0.094 -0.695 -0.235 NS -0.677 -0.113 0.044 -0.010 PR 0.526 0.151 -0.182 0.014 mf-n-zyo -0.037 0.084 0.169 -0.026 ns-n-zyo -0.185 0.128 -0.084 -0.155 ns-n-ba -0.147 0.233 -0.016 0.133 n-ns-zyo -0.024 0.299 -0.098 -0.650 n-ns-ba 0.144 -0.132 0.011 -0.350 * Highest two variables loadings for each axis in bold

563 Pooled Sex: Log-transformed

Angle PC 1 PC 2 PC 3 PC4 Ln-transformed NAA -0.289 0.178 -0.077 0.249 PRA -0.284 0.183 -0.073 0.255 BBA 0.087 -0.066 -0.093 -0.201 NBA 0.279 -0.128 0.320 -0.032 BBA -0.058 0.064 0.188 -0.086 NFA 0.095 0.001 -0.156 0.118 SSA 0.016 0.000 0.191 -0.033 FRA 0.061 0.026 0.280 -0.330 PAA1 -0.146 -0.091 -0.131 0.125 PAA2 -0.030 -0.075 -0.109 0.072 OCA -0.063 0.089 0.044 -0.229 NS -0.364 0.185 0.217 -0.137 PR 0.523 -0.190 -0.383 0.246 mf-n-zyo -0.449 -0.863 -0.006 -0.011 ns-n-zyo -0.233 0.221 -0.176 -0.103 ns-n-ba -0.170 0.104 -0.190 0.336 n-ns-zyo -0.100 0.063 -0.642 -0.576 n-ns-ba 0.087 -0.095 0.011 -0.305 * Highest two variables loadings for each axis in bold

564 Appendix 15 Variable loadings* after principal component analysis of Angular variables (all samples): Male-Only Male-Only: Raw Data

Angle PC 1 PC 2 PC 3 PC4 Raw NAA -0.261 0.238 -0.156 0.229 PRA 0.163 -0.024 0.146 0.018 BBA 0.101 -0.195 -0.004 -0.145 NBA -0.059 -0.090 0.233 -0.182 BBA 0.046 0.024 -0.119 0.182 NFA -0.025 -0.323 -0.047 0.154 SSA -0.015 -0.577 -0.100 0.651 FRA 0.061 0.116 -0.021 -0.172 PAA1 -0.053 0.141 -0.310 -0.066 PAA2 0.010 0.163 -0.305 -0.042 OCA -0.172 0.208 0.762 0.190 NS -0.701 -0.155 0.029 -0.183 PR 0.535 0.205 0.098 0.155 mf-n-zyo 0.006 0.081 -0.193 -0.061 ns-n-zyo -0.198 0.252 0.012 0.311 ns-n-ba -0.128 0.298 -0.190 0.219 n-ns-zyo -0.023 0.305 0.029 0.364 n-ns-ba 0.137 -0.194 0.136 -0.049 * Highest two variables loadings for each axis in bold

565 Male-Only: Log-transformed

Angle PC 1 PC 2 PC 3 PC4 Ln-transformed NAA -0.176 0.294 -0.163 0.175 PRA 0.071 -0.145 -0.065 -0.407 BBA 0.153 -0.206 0.310 0.309 NBA 0.055 0.064 0.093 -0.166 BBA -0.005 -0.055 -0.077 0.142 NFA 0.026 0.004 0.126 0.063 SSA 0.059 -0.016 0.212 -0.035 FRA -0.035 -0.049 -0.031 0.066 PAA1 -0.113 0.017 -0.036 0.049 PAA2 -0.093 -0.033 -0.039 0.148 OCA -0.017 0.115 -0.099 -0.238 NS -0.118 0.425 0.275 -0.135 PR 0.195 -0.554 -0.498 0.154 mf-n-zyo -0.864 -0.427 0.208 -0.051 ns-n-zyo -0.211 0.334 -0.335 0.191 ns-n-ba -0.175 0.158 -0.265 0.366 n-ns-zyo -0.171 0.072 -0.477 -0.491 n-ns-ba 0.087 -0.119 0.091 -0.338 * Highest two variables loadings for each axis in bold

566 Appendix 16 Variable loadings* after principal component analysis of Angular variables (excluding samples of n < 5): Male-Only Male-Only: Raw data

Angle PC 1 PC 2 PC 3 PC4 Raw NAA -0.225 0.263 -0.011 0.069 PRA 0.134 -0.014 0.132 -0.290 BBA 0.085 -0.233 -0.077 0.143 NBA -0.100 -0.100 0.173 -0.044 BBA 0.087 0.023 -0.073 -0.050 NFA -0.028 -0.393 -0.077 0.122 SSA -0.088 -0.613 -0.154 -0.361 FRA 0.038 0.039 0.072 0.410 PAA1 -0.072 0.255 -0.281 -0.060 PAA2 -0.007 0.174 -0.342 -0.117 OCA -0.124 -0.059 0.730 -0.048 NS -0.721 -0.017 0.038 0.047 PR 0.571 0.102 0.152 0.023 mf-n-zyo -0.043 0.050 -0.319 -0.280 ns-n-zyo -0.142 0.206 0.146 -0.161 ns-n-ba -0.049 0.260 -0.043 0.122 n-ns-zyo -0.004 0.306 0.148 -0.580 n-ns-ba 0.075 -0.137 0.075 -0.309 * Highest two variables loadings for each axis in bold

567 Male-Only: Log-transformed

Angle PC 1 PC 2 PC 3 PC4 Ln-transformed NAA -0.077 0.298 -0.166 0.270 PRA 0.056 -0.113 -0.095 -0.299 BBA 0.065 -0.237 0.423 -0.041 NBA -0.001 0.102 0.108 -0.202 BBA 0.030 -0.111 -0.072 0.084 NFA 0.018 -0.011 0.197 -0.049 SSA -0.018 -0.007 0.288 -0.188 FRA 0.012 -0.011 0.014 0.049 PAA1 -0.116 0.040 -0.153 0.316 PAA2 -0.075 -0.022 -0.086 0.183 OCA 0.059 0.133 0.028 -0.304 NS -0.192 0.454 0.185 -0.071 PR 0.341 -0.569 -0.342 0.062 mf-n-zyo -0.896 -0.389 -0.049 -0.039 ns-n-zyo -0.059 0.300 -0.300 -0.085 ns-n-ba -0.005 0.108 -0.232 0.357 n-ns-zyo -0.058 0.098 -0.563 -0.527 n-ns-ba 0.003 -0.086 0.031 -0.317 * Highest two variables loadings for each axis in bold

568 Appendix 17 Variable loadings* after principal component analysis of Angular variables (all samples): Female-Only Female-Only: Raw Data

Angle PC 1 PC 2 PC 3 PC 4 Raw NAA -0.297 0.210 -0.126 0.170 PRA 0.109 -0.140 0.099 -0.257 BBA 0.129 -0.120 0.009 0.057 NBA -0.068 -0.212 -0.162 -0.083 BBA 0.060 0.092 0.014 0.089 NFA -0.012 -0.223 -0.068 0.094 SSA 0.073 -0.569 0.493 0.259 FRA 0.000 0.029 0.051 0.633 PAA1 -0.015 0.251 0.204 -0.336 PAA2 0.059 0.113 0.272 -0.122 OCA -0.172 -0.214 -0.205 0.262 NS -0.673 -0.143 0.077 -0.145 PR 0.578 0.150 -0.160 0.073 mf-n-zyo -0.056 0.041 -0.127 -0.134 ns-n-zyo -0.138 0.231 0.113 -0.033 ns-n-ba -0.129 0.276 -0.210 0.180 n-ns-zyo -0.067 0.417 0.611 0.244 n-ns-ba 0.082 -0.157 0.248 -0.278 * Highest two variables loadings for each axis in bold

569 Female-Only: Log-transformed

Angle PC 1 PC 2 PC 3 PC 4 Ln-transformed NAA -0.271 0.135 -0.068 0.314 PRA 0.101 -0.056 0.037 -0.141 BBA 0.188 -0.175 0.149 -0.327 NBA -0.057 -0.058 0.177 0.026 BBA 0.071 0.004 -0.118 0.012 NFA -0.001 -0.014 0.095 -0.010 SSA 0.063 0.011 0.166 -0.324 FRA 0.000 0.007 -0.036 0.006 PAA1 -0.028 0.030 -0.177 0.144 PAA2 0.007 -0.030 -0.085 -0.105 OCA -0.066 0.047 0.131 0.020 NS -0.338 0.204 0.179 -0.021 PR 0.612 -0.395 -0.353 0.278 mf-n-zyo -0.536 -0.819 -0.104 -0.125 ns-n-zyo -0.229 0.097 -0.322 0.139 ns-n-ba -0.143 0.017 -0.181 0.415 n-ns-zyo -0.109 0.250 -0.726 -0.505 n-ns-ba 0.064 -0.020 0.056 -0.310 * Highest two variables loadings for each axis in bold

570 Appendix 18 Variable loadings* after principal component analysis of Angular variables (excluding samples of n < 5): Female-Only Female-Only: Raw Data

Angle PC 1 PC 2 PC 3 PC 4 Raw NAA -0.278 0.230 -0.027 0.201 PRA 0.140 -0.136 -0.103 -0.240 BBA 0.097 -0.141 -0.024 0.075 NBA -0.106 -0.166 -0.254 -0.248 BBA 0.083 0.071 0.014 0.202 NFA -0.043 -0.199 -0.201 0.045 SSA 0.048 -0.744 0.286 -0.010 FRA -0.059 -0.057 0.255 0.324 PAA1 0.057 0.222 0.242 -0.541 PAA2 0.108 0.065 0.220 -0.118 OCA -0.233 -0.114 -0.131 0.261 NS -0.655 -0.077 0.074 -0.155 PR 0.570 0.117 -0.204 0.065 mf-n-zyo -0.097 0.055 -0.184 -0.395 ns-n-zyo -0.081 0.162 0.137 -0.257 ns-n-ba -0.120 0.303 -0.131 0.156 n-ns-zyo 0.048 0.190 0.692 0.097 n-ns-ba 0.112 -0.189 0.130 -0.168 * Highest two variables loadings for each axis in bold

571

Female-Only: Log-transformed

Angle PC 1 PC 2 PC 3 PC 4 Ln-transformed NAA -0.158 0.205 -0.170 0.304 PRA 0.046 -0.173 0.070 -0.127 BBA 0.089 -0.175 0.358 -0.118 NBA -0.090 -0.013 0.125 0.030 BBA 0.070 -0.055 0.006 0.058 NFA -0.042 -0.039 0.147 0.069 SSA 0.052 0.015 0.371 -0.223 FRA 0.005 0.044 -0.010 -0.053 PAA1 0.001 -0.024 -0.295 -0.091 PAA2 0.015 -0.078 -0.039 -0.110 OCA -0.055 0.109 0.098 0.035 NS -0.248 0.335 0.111 -0.023 PR 0.428 -0.635 -0.297 0.192 mf-n-zyo -0.814 -0.527 -0.101 -0.145 ns-n-zyo -0.114 0.176 -0.406 -0.059 ns-n-ba -0.065 0.124 -0.307 0.395 n-ns-zyo 0.133 0.159 -0.427 -0.719 n-ns-ba 0.040 -0.088 0.117 -0.245 * Highest two variables loadings for each axis in bold

572