The Pennsylvania State University
The Graduate School
College of the Liberal Arts
THE CRANIAL MORPHOLOGY OF DWARF PRIMATE SPECIES
A Dissertation in
Anthropology
by
Brenda C. Frazier
2011 Brenda C. Frazier
Submitted in Partial Fulfillment of the Requirements for the Degree of
Doctor of Philosophy
May 2011
The dissertation of Brenda C. Frazier was reviewed and approved* by the following:
Joan T. Richtsmeier Professor of Anthropology Dissertation Advisor Chair of Committee
Timothy M. Ryan Assistant Professor of Anthropology
Russell W. Graham Associate Professor of Geosciences
Nina G. Jablonski Professor of Anthropology Head of the Department of Anthropology
*Signatures are on file in the Graduate School
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ABSTRACT
In 2004 a team of researchers announced the discovery of curious hominin skeletal material from Liang Bua cave on the small island of Flores, Indonesia. Several individuals assigned to a new taxon, Homo floresiensis , have been recovered, the most complete dating to only 18,000 years ago. This remarkable individual—the type specimen, LB1—is represented by the skull and skeleton of an adult hominin which stood just over a meter high, with a cranial capacity of ~400 cc. One hypothesis about the origin of this controversial material is that this creature evolved from a larger, known hominin that dwarfed over thousands of generations while in isolation on Flores. In this thesis, I seek to illuminate the debate over Homo floresiensis by informing our understanding of the cranial size and shape changes that accompany species level dwarfing in non human primates. To do this, I quantitatively compare the cranial morphology of three primate species that have evolved smaller bodies than their closest living relatives. Crania from a total of six species—three dwarfs and three relatives—were measured from museum skeletal collections. Cranial form, shape, and allometry were analyzed using an array of morphometric techniques, including traditional approaches as well as more recent innovations in quantitative morphology. I tested the null hypothesis that the dwarf primate species exhibit paedomorphic cranial features, as has been shown in some dwarf mammals (e.g., elephants and sloths), but not others (e.g., goats and hippos). My results reveal a unique pattern of cranial size and shape evolution in each of the three species. The dwarf guenon (Miopithecus ogouensis ) exhibits stereotypical ontogenetic scaling of the cranium. The simakobu monkey (Simias concolor ) of the Mentawai archipelago in Indonesia is paedomorphic in its large orbits, but its cranium has otherwise typically “adult” proportions. Finally, shape and cranial proportions in the small bodied Natuna Island leaf monkey (Presbytis natunae ) are essentially isometric relative to larger Presbytis . This research demonstrates the variety of possible outcomes of evolutionary dwarfing events. Based on these three case studies, I hypothesize two global models for dwarfing in primates which represent extremes along a spectrum of possible outcomes. The position of any given species along this spectrum is determined by its own unique natural history. In considering human and non human primates alike, these results encourage thoughtful skepticism of some common assumptions about evolutionary processes, particularly with regard to encephalization. As our knowledge of the Flores hominin grows, we must continually update our theoretical interpretations with information about its distinctive ecological and evolutionary context.
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TABLE OF CONTENTS
List of Figures………………………………………………………………………………..vii
List of Tables…………………………………………………………………………………xi
Acknowledgments……………………………………………………………………………xiv
Chapter 1 Introduction ...... 1
The Flores Hominin ...... 2 Evaluating the ‘LB1 as dwarf’ hypothesis ...... 5 Allometry ...... 6 Heterochrony ...... 6 Allometry ...... 8 Ontogeny of the primate cranium ...... 12 Encephalization ...... 12 Island Evolution & the Island Rule ...... 13
Chapter 2 Materials and Methods ...... 20
Samples ...... 20 Data Collection ...... 22 Landmark Data ...... 22 Endocranial Volume (ECV) ...... 27 Other metrics ...... 28 Data Processing ...... 31 Analysis: Landmark Data ...... 32 Distance methods: Euclidean Distance Matrix Analysis (EDMA) ...... 34 Superimposition methods: Generalized Procrustes Analysis (GPA) ...... 37 Analysis: Non Landmark Data ...... 48 Encephalization ...... 49
Chapter 3 A “classic” primate dwarf: the talapoin monkey ...... 52
Species background ...... 52 Hypotheses, approaches of this study ...... 57 Analysis of cranial morphology in the talapoin monkey compared to Cercopithecus nictitans ...... 58 Static allometry in Miopithecus ogouensis females ...... 59 Static allometry in Miopithecus ogouensis males ...... 62 Sexual dimorphism in Miopithecus ogouensis ...... 64 Static allometry in Cercopithecus nictitans females ...... 69 Static allometry in Cercopithecus nictitans males ...... 70 Sexual dimorphism in Cercopithecus nictitans ...... 73 Interspecific shape: M. ogouensis females compared to C. nictitans females ...... 76 Interspecific shape: M. ogouensis males compared to C. nictitans males ...... 79
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Overall cranial allometry in the species, sexes pooled ...... 81 Encephalization ...... 82 Conclusions ...... 84 Discussion ...... 86 Expectations for other dwarfed primates...... 88
Chapter 4 Size and cranial morphology in an odd nosed colobine lineage: Simias concolor and Nasalis larvatus ...... 89
Species background ...... 89 Hypotheses, approaches of this study ...... 94 Analysis of Nasalis & Simias morphology ...... 95 Static allometry in Simias females ...... 96 Static allometry in Simias males ...... 98 Simias static allometry & sexual dimorphism ...... 102 Static allometry in Nasalis females ...... 106 Static allometry in Nasalis males ...... 107 Nasalis static allometry & sexual dimorphism...... 112 Evolutionary allometry of the Nasalis Simias lineage ...... 114 Simias & Nasalis females ...... 114 Simias & Nasalis males ...... 117 Composite cranial allometry of the lineage ...... 121 Conclusions ...... 126 Discussion ...... 127
Chapter 5 Dwarfing in a dwarfed lineage: Presbytis leaf monkeys ...... 129
Species background ...... 129 Hypotheses, approaches of this study ...... 133 Analysis of cranial morphology in the Natuna leaf monkey ...... 134 Overview of comparative cranial shape in P. natunae , femoralis , and melalophos ...... 134 Static allometry in P. natunae ...... 137 Static allometry in Presbytis melalophos females ...... 145 Static allometry in Presbytis melalophos males ...... 146 Sexual dimorphism in Presbytis melalophos ...... 148 Interspecific shape: P. natunae females compared to P. femoralis females ...... 151 Interspecific shape: P. femoralis females compared to P. melalophos females ...... 154 Interspecific shape: P. melalophos compared to P. natunae ...... 155 Evolutionary allometry of Presbytis ...... 157 Encephalization across Presbytis ...... 163 Conclusions ...... 164 Discussion ...... 166
Chapter 6 Conclusions ...... 167
Methodological Approach ...... 167 Review of Species Comparisons ...... 168 Guenons ...... 168
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Simias/Nasalis ...... 171 Presbytis ...... 175 The Dwarf Phenotype ...... 177 Different paths to a dwarf phenotype: selective pressures ...... 177 Mechanisms of Dwarfing: Heterochrony as inferred from adult morphology ...... 180 Expectations for cranial morphology in a dwarf primate ...... 185 Dwarfing and Homo floresiensis ...... 186 Open questions and future directions ...... 188 Summary of Contributions ...... 190 Appendix: Glossary ...... 192 REFERENCES ...... 196
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LIST OF FIGURES
Figure 1.1. Island Southeast Asia, with the island of Flores highlighted...... 2
Figure 1.2. Relative brain size in Homo floresiensis and other hominins...... 3
Figure 1.3. Basic concepts of heterochrony employed in this dissertation...... 8
Figure 1.4. The relationship between ontogenetic and static allometry in a population...... 11
Figure 2.1. Cranial landmarks...... 23
Figure 2.2. Digital endocast of a male talapoin monkey...... 28
Figure 2.3. Interspecific PC1 extreme shapes in Presbytis ...... 40
Figure 2.4. Alternative hypotheses for the relationship between allometric trajectories: Divergent, Parallel, and Coincident...... 45
Figure 3.1. Approximate geographic distribution of Cercopithecus nictitans and the two talapoin species...... 54
Figure 3.2. Hypothesized phylogeny of the guenons (tribe Cercopithecini)...... 56
Figure 3.3. Static allometry in female talapoins...... 60
Figure 3.4. Visualization of predicted shapes for largest (red) and smallest (yellow) talapoin females...... 61
Figure 3.5. M. ogouensis adult male cranial allometry in the context of females and subadult males...... 63
Figure 3.6. Miopithecus ogouensis male (dark blue) and female (light blue) mean shapes. .. 66
Figure 3.7. Hypothetical male and female M. ogouensis shapes predicted at the mean cranial size of the opposite sex...... 68
Figure 3.8. Visualization of predicted shapes for largest (red) and smallest (yellow) C. nictitans females...... 70
Figure 3.9. Correlation between PCO2 score and cranial size (geometric mean) in C. nictitans males...... 72
Figure 3.10. Visualization of predicted shapes for largest (red) and smallest (yellow) C. nictitans males...... 72
Figure 3.11. The first principal component of shape variation in C. nictitans plotted against CS...... 73
Figure 3.12. Cercopithecus nictitans male (dark red) and female (pink) mean shapes...... 75
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Figure 3.13. Hypothetical male and female C. nictitans shapes predicted at the mean cranial size of the opposite sex...... 76
Figure 3.14. Visualization of C.nictitans (red) and M. ogouensis (blue) female mean shapes...... 77
Figure 3.15. PC1 plotted against CS from a PCA of all female guenons...... 79
Figure 3.16. PC1 plotted against centroid size from a PCA of all individuals, sexes pooled...... 81
Figure 3.17. Relative brain size in Miopithecus ogouensis compared to similarly sized anthropoids...... 83
Figure 3.18. Relative brain size in Cercopithecus nictitans compared to similarly sized anthropoids...... 84
Figure 4.1. Geographic ranges of the simakobu, Simias concolor , (in green) and the proboscis monkey, Nasalis larvatus , (in orange)...... 90
Figure 4.2. Hypothesized phylogeny of the Asian colobines...... 94
Figure 4.3. Visualization of predictions for Simias female large and small extremes...... 97
Figure 4.4. Visualization of predicted shapes for Simias male large (red) and small (yellow) extremes...... 99
Figure 4.5. Distribution of head and body length (HBL) in simakobu males, showing outlier...... 100
Figure 4.6. Cube root ECV plotted as a function of centroid size for female and male simakobus...... 101
Figure 4.7. Centroid size of the cranium in the complete Simias (Sc) and Nasalis (Nl) sample...... 102
Figure 4.8. The first two PCs of shape variation in Simias ...... 103
Figure 4.9. Male (darker green) and female (lighter green) simakobu mean shapes...... 103
Figure 4.10. The relationship between PC1 and CS in a pooled sex PCA of Simias ...... 105
Figure 4.11. Visualization of predicted shapes for largest and smallest female Nasalis ...... 106
Figure 4.12. Principal coordinates 1 and 2 of all Nasalis with outlier included (above) and removed (below)...... 109
Figure 4.13. Predicted shapes for largest and smallest male Nasalis ...... 110
Figure 4.14. Cube root ECV plotted as a function of CS for female and male proboscis...... 111
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Figure 4.15. Nasalis male and female mean shapes...... 112
Figure 4.16. The relationship between PC1 and CS in a pooled sex PCA of Nasalis ...... 113
Figure 4.17. Female mean shapes...... 115
Figure 4.18. The relationship between PC1 score and CS in females of the two species (from a pooled sample PCA)...... 116
Figure 4.19. Hypothetical Simias sized female Nasalis ...... 117
Figure 4.20. Male mean shapes...... 118
Figure 4.21. The relationship between PC1 score and CS in males of the two species (from a pooled sample PCA)...... 120
Figure 4.22. Hypothetical Simias sized male Nasalis ...... 121
Figure 4.23. The relationship between PC1 score and CS in the two species (from a pooled sample PCA)...... 122
Figure 4.24. Comparative encephalization among Asian colobines...... 124
Figure 4.25. ECV vs. body mass for anthropoids with sex specific mean body mass similar to Nasalis and Simias ...... 125
Figure 5.1. The approximate current geographic distribution of the three species of Presbytis considered in this chapter...... 130
Figure 5.2. Centroid size in the three Presbytis species (sexes pooled)...... 135
Figure 5.3. Principal components 1 & 2 of all Presbytis individuals...... 136
Figure 5.4. Distribution of female (n=10) and male (n=4) CS (above) and CBL (below) in the Natuna leaf monkey...... 137
Figure 5.5. Principal component analysis of P. natunae individuals...... 138
Figure 5.6. Principal component analysis of P. natunae individuals, using only 36 landmarks...... 139
Figure 5.7. Principal component analysis of all Presbytis individuals (Procrustes coordinates), with the three Singapore/ZRC P. natunae specimens circled...... 141
Figure 5.8. PCA of P. natunae , excluding the ZRC specimens...... 142
Figure 5.9. Visualization of positive and negative extremes of PC1 within non ZRC P. natunae ...... 143
Figure 5.10. PC1 score plotted against CS in all Natuna monkeys...... 144
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Figure 5.11. Visualization of predicted shapes for largest and smallest P. melalophos females...... 146
Figure 5.12. Visualization of predicted shapes for largest and smallest P. melalophos males...... 147
Figure 5.13. PCA of male and female P. melalophos ...... 149
Figure 5.14. Presbytis melalophos male (red) and female (pink) mean shapes...... 150
Figure 5.15. Principal components 1 & 2 of P. natunae and P. femoralis ...... 152
Figure 5.16. Visualization of P. natunae (blue) and P. femoralis (green) female mean shapes...... 153
Figure 5.17. Visualization of P. femoralis (green) and P. melalophos (pink) female mean shapes...... 154
Figure 5.18. Visualization of P. melalophos (red) and P. natunae (blue) mean shapes...... 156
Figure 5.19. Interspecific PC1 extreme shapes...... 158
Figure 5.20. Interspecific PC1 scores for all Presbytis individuals plotted against CS...... 159
Figure 5.21. Interspecific PCA of all Presbytis specimens...... 160
Figure 5.22. Phylogenetic tree of Presbytis species, based on craniometric dissimilaries. .... 162
Figure 6.1. Sexual dimorphism in ontogenetic and adult static allometric trajectories...... 171
Figure 6.2. The relationship between cranial size and brain size across Simias and Nasalis , showing “transpositional allometry.” ...... 174
Figure 6.3. Alternate paths to a dwarf phenotype...... 177
Figure 6.4. Potential mechanisms of size reduction...... 181
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LIST OF TABLES
Table 2.1. Museums curating specimens used in this dissertation...... 21
Table 2.2. Species and sample sizes used in this dissertation...... 22
Table 2.3. Landmark descriptions and abbreviations...... 24
Table 2.4. Non landmark based metrics...... 29
Table 2.5. Evidence for cranial allometry in Simias concolor males...... 41
Table 3.1. Evidence of cranial allometry in Miopithecus ogouensis females (n=22)...... 59
Table 3.2. Correlation between components of the cranium and body in female M. ogouensis ...... 61
Table 3.3. Evidence of cranial allometry in fully adult Miopithecus ogouensis males...... 62
Table 3.4. Correlation between components of cranium and body in adult male M. ogouensis ...... 63
Table 3.5. Sexual dimorphism in the cranium of Miopithecus ogouensis ...... 65
Table 3.6. Evidence of cranial allometry in Cercopithecus nictitans females (n=21)…….. .. 69
Table 3.7. Correlation between components of cranium and body in female C. nictitans ... .. 70
Table 3.8. Evidence of cranial allometry in C. nictitans males (n=24)...... 71
Table 3.9. Correlation between components of cranium and body in male C.nictitans ...... 73
Table 3.10. Sexual dimorphism in the cranium of Cercopithecus nictitans ...... 74
Table 3.11. Comparative statistics for female M. ogouensis and C. nictitans ...... 78
Table 3.12. Comparative statistics for male M. ogouensis (fully adult) vs. C. nictitans ...... 80
Table 3.13. Sex specific EQ values for representative guenon taxa...... 82
Table 3.14. Comparison of static allometry and sexual dimorphism in M. ogouensis and C. nictitans ...... 85
Table 4.1. Evidence for overall cranial allometry in simakobu females (n=15)...... 96
Table 4.2. Correlation between components of the cranium and body in Simias females...... 98
Table 4.3. Evidence for cranial allometry in Simias males (n=10)...... 98
Table 4.4. Correlations between components of the cranium in Simias males...... 100
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Table 4.5. Sexual dimorphism in the simakobu cranium...... 104
Table 4.6. Evidence of cranial allometry in Nasalis females...... 107
Table 4.7. Correlation between cranial components in Nasalis females...... 107
Table 4.8. Evidence of static allometry in the male proboscis cranium...... 110
Table 4.9. Correlation between cranial components in proboscis males...... 111
Table 4.10. Sexual dimorphism in the proboscis cranium...... 113
Table 4.11. Comparison statistics of females in the two species...... 114
Table 4.12. Comparison statistics for males of the two species...... 119
Table 4.13. EQ values for odd nosed monkeys and closely related species...... 123
Table 5.1. Mean body mass values for the Presbytis melalophos species group...... 132
Table 5.2. Cranial size in Presbytis natunae individuals...... 140
Table 5.3. Possible explanations for the size and shape differences between the ZRC specimens and other Natuna monkeys...... 140
Table 5.4. Evidence of cranial allometry in Presbytis natunae , excluding ZRC specimens...... 142
Table 5.5. Correlation between components of cranium and body in Natuna monkeys...... 143
Table 5.6. Evidence of cranial allometry in Presbytis natunae , including ZRC specimens. .. 144
Table 5.7. Correlation between components of cranium and body in all Natuna monkeys. ... 145
Table 5.8. Evidence of cranial allometry in Presbytis melalophos females (n=29)...... 145
Table 5.9. Correlation between components of cranium and body in female P. melalophos ...... 146
Table 5.10. Evidence of cranial allometry in Presbytis melalophos males (n=31)...... 147
Table 5.11. Correlation between components of cranium and body in male P. melalophos ...... 148
Table 5.12. Sexual dimorphism in the cranium of Presbytis melalophos ...... 149
Table 5.13. Comparative statistics for P. natunae (non ZRC) and femoralis females...... 153
Table 5.14. Comparative statistics for melalophos and femoralis females...... 155
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Table 5.15. Comparative statistics for all P. natunae (including ZRC specimens) vs. all P. melalophos ...... 156
Table 5.16. EQ values for members of the genera Presbytis and Trachypithecus ...... 163
Table 6.1. Factors influencing the dwarf phenotype...... 183
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ACKNOWLEDGMENTS
This dissertation would not have been possible without the support, guidance, and encouragement of many people. Direct financial support of this research came from an NSF Doctoral Dissertation Improvement Grant (#0824583) and a Dissertation Support Grant from the College of the Liberal Arts at Penn State. The Penn State Department of Anthropology funded the purchase of the MicroScribe digitizer (through the Hill Fund), as well as travel for my initial pilot study (through the Baker Fund). I was able to collect all of the data for this research thanks to the efforts and hospitality of many curators and collection managers: Richard Thorington and Linda Gordon at the Smithsonian (NMNH); Eileen Westwig at the American Museum of Natural History; Judy Chupasko (and her wonderful staff!) at the Harvard Museum of Comparative Zoology; Craig Hood at the Tulane Museum of Natural History; John Wible, Tim McCarthy and Sue McLaren at the Carnegie Museum of Natural History; Ned Gilmore at the Academy of Natural Sciences in Philadelphia; Susan Woodward and Judith Eger at the Royal Ontario Museum; Steve Hinshaw at the University of Michigan Museum of Zoology; and Peter Ng and Kelvin Lim at the Zoological Reference Collection (Raffles Museum, Singapore). The kind and generous efforts of Peter Lucas (George Washington University) and Barry Pereira (National University of Singapore) procured the beautiful micro CT scans of three specimens of the Natuna leaf monkey held at the ZRC. Eric Delson (Lehman College, AMNH) leant a MicroScribe digitizer for my initial pilot study, and shared surface scans of several AMNH specimens for used for visualizations throughout this thesis. Richard Kay (Duke) shared his micro CT scan of a male talapoin monkey. Matt Ravosa (University of Missouri) kindly shared data he collected from several proboscis monkey specimens. Members of the Penn State Department of Anthropology, past and present, have created a support system that allowed me to hatch the initial ideas for this research, and to see me through the long and tortuous evolutionary path to completion. In particular, I’d like to thank Betty Blair, Wendy Fultz, Faye Maring, Kim Miller, Diane Snyder and Melissa Strouse. Stephanie Rossman deserves special thanks for cheerfully handling all of my grant reimbursal requests in their many varied forms and currencies. Jasun Lego’s patience in dealing with all IT issues was unparalleled, and his expertise and support in creating a system that allowed me to work and
xv write remotely after moving abroad was critical to the completion of my PhD. At many times throughout my predoctoral career, the wisdom and advice of Anne Buchanan, Ken Weiss, Pat Shipman and Alan Walker have been indispensable. This work could never have been realized without the addition of Nina Jablonski to the Department and to my doctoral committee in 2006. Tim Ryan saved the day by taking the reins on my committee after Alan’s retirement. Russ Graham from the Department of Earth and Mineral Sciences brought a valuable and enjoyable perspective to the committee from beyond the hallowed walls of Carpenter Building. Graduate students and post docs during my lengthy tenure at Penn State gave me companionship, friendship, encouragement, and shared their knowledge and experience. In particular, I’d like to thank Nita Bharti, Abby Bigham, Jóhanna Gísladóttir Bissat, Holly Dunsworth, Sharon DeWitte, Kirk French, Craig Goralski, Denise Hsu, María Inclán, Heather Lawson, Denise Liberton, Dawn Miller, Heather Norton, Joe Orkin, Laurel Pearson, Ellen Quillen, Erick Rochette, Colin Shaw, Sam Sholtis, and Kirk Straight. Many people have generously made the fruits of their programming and statistics expertise available to me and to the larger morphometrics community: Chris Klingenberg, Tim Cole, Ryan Raaum, Dennis Slice, and Subhash Lele. I cannot offer enough thanks to my doctoral advisor, mentor, and role model throughout my graduate career, Joan Richtsmeier. Her patience over the last eight years is difficult to comprehend. Part of the nurturing environment she provides comes from the great people she keeps in her lab. For many years of friendship and personal and professional support, I thank Richtsmeier Lab members, past and present: Kristina Aldridge, Cheryl Hill, Peng Yan, Gail Krovitz, Valerie DeLeon, Machigar Ongtang, Satama Sirivunnabood, John Starbuck, Chris Percival, Trish Parsons, Jen Leszl, Lisa Gileskie Howell, Traci Haimowitz, Yann Heuzé and Neus Martínez Abadías. Kat Willmore has been a pillar of support and a vital source of comic relief since we scribbled the initial brainstorms of my thesis over beers together at Otto’s. The list of all the friends and colleagues outside of Penn State who have helped make this thesis a reality is too long to enumerate. I would be remiss, however, not to mention the support of Noreen von Cramon Taubadel and Stephen Lycett, Liz St. Clair, Mark Coleman, Will Harcourt Smith, Kieren McNulty, Sandi Olsen, Gabriel Marroig, Jeff Schoenebeck, Mary Silcox, David Begun, Chris Gilbert, Stephanie Kozakowski, and Sophie Pickford. Harry Merrick introduced me to the field of paleoanthropology and helped me pursue a graduate career in human origins. Emily Buchholtz and Sylvaine Égron Sparrow supported my graduate application long after I had left Wellesley.
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Finally, my family have provided steadfast support through all the vicissitudes of my long career as a student. My parents, Ron and Alice, have lovingly stood by me through even my most questionable of decisions. My sisters, Marian and Lisa, have cheered me on at every turn. My Aunts Joanne and Becky and my Uncle Mel have been particularly encouraging through my journey to doctorhood. John and Cathy Adams and all of my husband’s family have been ardent supporters. Our dearly departed dog, Simba, kept me sane through many months alone in State College while Ryan was away. And lastly, my strongest advocate, editor, coach, cheerleader, resident statistician and expert in all things technical or technology related (and much more) is my husband Ryan. He believed I could finish this even when I didn’t. This thesis is as much a testament to his strength and endurance as it is to mine.
Chapter 1
Introduction
Few discoveries in recent memory have sparked more controversy and bewilderment in the paleoanthropology community than the hominin finds at Liang Bua, Flores (Brown et al. 2004). The material from Flores—referred to a new taxon, Homo floresiensis —has highlighted not only the fact that there are still potentially paradigm shifting finds to be made in human paleontology, but also that there remain important aspects of basic human and primate biology that we do not yet adequately understand. One profound hypothesis is that the remains discovered on Flores may represent the result of endemic dwarfing in a hominin, thus putting into stark relief the relative lack of published findings regarding the changes in cranial form associated with species level dwarfing. As with the discovery of the original Neanderthal specimens, the Taung child and Java Man, the Flores remains have raised questions previously unasked and whose answers may bring controversy. These and other “big questions” include: What is Homo floresiensis ? One hypothesis is that the size of the Flores remains indicate an individual pathology; is it possible in this case to distinguish between pathology and species level dwarfism? Are tool making hominins subject to island dwarfing like many other big animals? The only H. floresiensis cranium yet known, the type specimen LB1, has a tiny braincase. Is a population of hominins with chimp sized brains capable of developing the type of stone tool technology we find on Flores? Could the brain of a thinking and culture bearing hominin (e.g., Homo erectus ) have shrunk in size so drastically, even in isolation? (i.e., Could a hominin become less encephalized?) If not Homo erectus , what species was ancestral to the Flores inhabitants? Could a hominin as primitive as this putative ancestor have successfully dispersed so far out of Africa? Could such a primitive creature and its descendants have persisted for nearly two million years in island Southeast Asia? How did they get to Flores in the first place? These high level questions are beyond the scope of this dissertation, but they are all driven to varying extents by the tiny size of LB1’s neurocranium. In this dissertation, I seek to illuminate the debate about the Flores hominin—particularly with regard to its small brain—by studying the morphological correlates of derived reduction in body size in the crania of three
2 primate taxa. Thus, I will address a related question that is more data driven and specific than the larger scale questions above. When compared to “full sized” relatives, what shape features characterize the crania of dwarfed primates? The answers to this question will lend insight into the various hypotheses regarding the origins of the Flores hominin remains.
Figure 1.1. Island Southeast Asia, with the island of Flores highlighted.
The Flores Hominin
In 2004, amid great fanfare, a team of researchers announced the discovery of curious skeletal material from Liang Bua cave on the small island of Flores, Indonesia (Figure 1.1) (Brown et al. 2004). The most complete individual (LB1) is represented by the skull and skeleton of an adult hominin which stood just over a meter high, had a brain size similar to that of a chimpanzee (est. 385 417 cm 3) (Brown et al. 2004; Falk et al. 2005; Holloway et al. 2006), and lived only 18,000 years ago. This material and more excavated subsequently have been assigned to a new taxon, Homo floresiensis . Fitting this new creature into our current understanding of human evolution has proven challenging and controversial. This is the first evidence for the persistence of a
3 hominin other than anatomically modern humans into the latest Pleistocene. By 18,000 years BP, modern humans had long since colonized most of the old world, including areas of island Southeast Asia and Australia (Barker 2002; Gillespie 2002; O’Connor 2007). Despite its apparently fairly derived cranial morphology (e.g., small canines, reduced supraorbital torus), the tiny braincase (Figure 1.2) and many primitive postcranial characters suggest affinities to pre H. erectus hominins, heretofore only known from Africa, and from over two million years earlier in time (Aiello 2010; Larson et al. 2009).
Figure 1.2. Relative brain size in Homo floresiensis and other hominins. The ranges of observed (or estimated) stature and brain volume for Homo sapiens , Homo erectus sensu lato (“Erectines”), and the Australopithecines are plotted against these estimates for the Flores hominin (LB1) (reproduced from Lahr and Foley 2004: Figure 2).
To account for this odd creature, various hypotheses have been suggested, none of which is extremely compelling. That initially favored by the discoverers is that Homo floresiensis is the descendant of Homo erectus who reached the island in the middle Pleistocene (based on stone tool finds) and subsequently underwent insular dwarfing. There are two primary weaknesses of this hypothesis based on the known skeletal remains. First, it is difficult to imagine the brain size shrinking so drastically in a dwarfing scenario (Martin et al. 2006); even the smallest brained H. erectus individuals from Dmanisi still have an endocranial capacity of ~600 cm3 (Rightmire et al. 2006). In addition, mounting evidence from studies of the postcrania indicate that the skeleton of
4 the Flores hominin is in many ways more primitive than what is known of Homo erectus (Jungers et al. 2009; Morwood et al. 2005; Tocheri et al. 2007). One alternative hypothesis regarding the Flores hominin is that the LB1 cranium represents a pathological microcephalic individual from a small statured anatomically modern human population. The most significant difficulty here is in accounting for the several other similarly sized postcranial remains in the cave. At least fourteen individuals are represented by the material published thus far, and all of them are consistent in size and morphology with the type specimen (Morwood et al. 2009). For this scenario to accommodate the available evidence, an entire group of individuals of stature well below the documented range for any modern human population, with markedly atavistic skeletal morphology, would have to be hypothesized. Alternatively, it would require an entire group of individuals sharing a common pathology resulting in these traits. At this point, the most parsimonious explanation may be the unlikely sounding hypothesis that the hominins at Liang Bua were the remnants of an early or pre H. erectus hominin dispersal out of Africa for which the Flores specimens are currently our only recognized evidence. This scenario may not be as implausible as it seems. There is little postcranial evidence for early H. erectus outside of Africa. It is known that Homo had reached Java by about 1.8 Ma (million years ago), but cranial capacity in the earliest estimable exemplar, Sangiran 4 (1.6 Ma), was over 900 cm 3—more than double the volume of the LB1 neurocranium (Holloway 1981; Rightmire 2004). Is it possible that this population, or an earlier one, was less derived postcranially than the Nariokotome boy, for example? Is it possible that a relatively small bodied and small brained early Homo began leaving Africa at around 2 Ma (before, or possibly in addition to, the more derived H. erectus ), spreading into parts of Southeast Asia? Even before the discovery of the Liang Bua fossils, there were suggestions of a pre H. erectus dispersal out of Africa, based on evidence at Dmanisi, Georgia (Rightmire et al. 2006) and, perhaps, the Sangiran Formation, Java (Kaifu et al. 2005). This hypothesis has a significant impact on our current understanding of human evolution, implying that a hominin morphologically less derived, and almost certainly less encephalized, than H. erectus successfully invaded the old world beyond the African continent. This scenario, plus the invocation of isolation on the island of Flores for some hundreds of thousands of years, might plausibly result in a creature such as Homo floresiensis . It is not within the scope of this dissertation to determine the origin of Homo floresiensis , however. Instead, the goal of the present study is to inform the debate with respect to the hypothesis of endemic dwarfing.
5 Evaluating the ‘LB1-as-dwarf’ hypothesis
The term dwarf suffers from the problem of colloquial as well as ill defined technical usage, with plenty of gray area in between (see discussion in Gould and MacFadden 2004). In this thesis, dwarfing refers to a derived, population or species level evolutionary phenomenon, whereby the range of body sizes typically attained by adults becomes substantially reduced in a descendant taxon relative to its ancestral form (Roth 1992). A dwarf refers to an individual or population of individuals belonging to such a taxon. Interpretation of the Flores hominin remains has been severely hampered by a lack of relevant comparative data from other putative dwarfed forms. It certainly contradicts the general picture of human evolution to envision a drastically less encephalized descendant of an ancestor with as large a brain as Homo erectus. For specific hypotheses involving brain size reduction as a correlate of insular body size reduction (i.e., island dwarfing), there are few obvious analogs among living primates to which we can look (Bromham and Cardillo 2007). For example, modern human populations with small average stature (so called “pygmies”) have brains that fall well within the normal range of size variation for our species (Beals et al. 1984), and thus do not come close to exhibiting the drastic type of species level difference in endocranial volume that distinguishes LB1 from Homo erectus . The purpose of this thesis is to use evidence from non human primate species to perform data driven analyses that are relevant to the Flores hominin debate and more broadly relevant to the evolutionary biology of living and extinct primates. To do this, I attempt to define and quantify the size related cranial shape changes—including those related to changes in brain size specifically—that have occurred in primates that have evolved smaller bodies than their ancestors. Put another way, I attempt to define features of cranial allometry associated with dwarfing in primates.
The next section of this chapter briefly introduces two core concepts in evolutionary biology: allometry and heterochrony. Allometry is an essential aspect of this thesis, because it concerns the relationship between size and shape. Heterochrony—differences in the rate and timing of development—is critical to the construction and investigation of allometric hypotheses. As such, these two areas of study form the theoretical framework on which this dissertation is built.
6 Allometry
Form, Shape & Size
Chapter 2 will cover the technical operational definitions of these terms, but a brief treatment is warranted before introducing the concepts of heterochrony and allometry. The word form describes all aspects of size and shape. Shape refers to a similar property, but it is invariant to scaling. For example, a model airplane will have the same shape as the real plane, but its form is different, due to scale. Of course the study of shape is not an end in itself, but a surrogate for the biology that underlies it. Size is the physical extent (magnitude) of an organism or part thereof. There is no single measure of size that is universally preferred for biological studies. In this thesis, local context defines the precise metric being employed for the quantification of size (e.g., volume, mass, length).
Heterochrony
Heterochrony is a large and complex field of inquiry based on the simple observation that adult morphology (and all phenotype) ultimately results from ontogenetic processes. Thus, differences in adult morphology must arise from differences in ontogenetic processes. Heterochrony refers to evolutionary differences ( hetero ) in rates and timing ( chron ) of development. Given that a major focus of this thesis is the relationship between size and cranial shape, this brief introduction to heterochrony is biased toward the study of these two variables. The theoretical intricacies and practical implications of heterochrony with respect to evolutionary biology are beyond the scope of this thesis. Klingenberg (1998) is recommended for a thorough introduction to the field, and many other authors have made important contributions to this area of study, dating back to Haeckel in the nineteenth century. The basic categorizations of heterochrony rely on descriptions of differences between ancestral and descendant forms. Thus, the terminology of heterochrony describes the rates and timing of developmental processes in a descendant taxon relative to an ancestral one. The discussion and study of heterochrony need not be restricted to the ancestor descendant case, however (Klingenberg 1998). “The evolutionary processes responsible for morphometric covariation along the branches of a phylogeny are the same, regardless of whether the taxa under study are linked by ancestor descendant or sister group relationships” (Klingenberg 1998:112). For this reason, I follow Klingenberg (1998) in
7 approaching the analysis of heterochrony between sister species in the same fashion as I would with true ancestor descendant cases. This differs from the approach and terminology favored by Gould (1966; 1975a), for example.
Basic terminology of heterochrony
Paedomorphosis describes the process by which the adult of a descendant taxon resembles the juvenile or subadult of an ancestral taxon. Peramorphosis describes the process by which the descendant at a given stage goes beyond the ancestor at the same stage, producing an exaggeration of the ancestral adult traits (Klingenberg 1998). Both of these phenomena can occur via a number of mechanisms—by altering rate and/or length of growth, shifting growth trajectories—but the discussion here will be limited to cases where ancestor and descendant reach different adult body sizes. The specific situation in which the descendant species is paedomorphic (juvenilized) in shape and also achieves smaller adult size than its ancestor is called hypomorphosis (Figure 1.3, left panel). In such a case, the direction of evolutionary change in the adult form is opposite the direction of ontogenetic change in an individual (Klingenberg 1998). The scenario in which the descendant is both peramorphic (hyper adult) in shape and is larger than its ancestor at adulthood is termed hypermorphosis (Figure 1.3, right panel). When a descendant species is hypermorphotic, the direction of evolution of adult forms is the same as the direction of ontogenetic change. Both diagrams in Figure 1.3 show ancestral (A) and descendant (D) taxa following similar size shape trajectories to adulthood (terminal points).
Because differences in the rate and timing of development are ultimately responsible for the differences in size and shape that we observe in organisms, the study of heterochrony is inherently tied to the study of allometry.
8
Figure 1.3. Basic concepts of heterochrony employed in this dissertation. Hypomorphosis (left) is a special case of paedomorphosis. In this case, the descendant creature (D) as an adult exhibits a shape and size corresponding to juveniles of its ancestor. Hypermorphosis (right) is a special case of peramorphosis. A = Ancestral taxon; D = Descendant taxon. Based on Figure 1 from Lieberman et al. (2007:650).
Allometry
As with heterochrony, the study of allometry by evolutionary biologists has a deep and rich history, Huxley’s Problems of Relative Growth (1932) being the foundational work. Allometry, broadly defined, concerns variation in virtually any biological trait associated with variation in overall size. Here, I focus especially on shape and size aspects of the cranium (and its components) and their relationship to body size. The definitions below are biased accordingly. Static allometry describes the variation in shape associated with size differences at a common ontogenetic stage within individuals of a single species , i.e., intraspecific allometry. Most commonly, static allometry pertains to adults, as it does in this thesis. Because sexual dimorphism is an important aspect of static allometry in most primates, this thesis often makes the distinction between female static allometry and male static allometry . Ontogenetic allometry deals with the shape changes associated with growth and development of an individual over the course of its life history. Finally, evolutionary allometry concerns the shape changes associated with size differences over evolutionary time and across species , i.e. interspecifically.
9 The allometric trajectory refers to the path through size and shape space that best describes the relationship between these variables in the sample under consideration. In the case of static allometry, this path is usually approximated by best fit linear regression between one or more shape variables and a size variable. The trajectory of ontogenetic allometry is the familiar concept of a “growth curve.” Similar to static allometry, the trajectory of evolutionary allometry is normally defined by a best fit regression through data points representing adult mean forms in the size shape space. Ontogenetic data and interspecific data are often close to log linear, and it is common in these cases to transform the variables using the natural logarithm.
Log transformation
Log transformation can also be convenient in that Huxley’s “Allometric Law,” represented by the power function Y = bX α, becomes linear in log space, and the “allometric exponent” ( α) becomes the slope of the bivariate regression line when the log of Y (trait of interest) is plotted against the log of size ( X). The variable b in this equation is just a scalar that becomes an added constant term after log transformation. In such a bivariate log log plot, a slope ( α) of 1 represents isometry between X and Y, with α > 1 indicating positive allometry , and α < 1 indicating negative allometry in the scaling of Y with X. Positive allometry means that as size ( X) gets larger, the trait of interest ( Y) increases even faster. Negative allometry indicates that the rate of increase in the trait of interest is outpaced by an increase in size. The classic example of negative allometry is the scaling of brain size with body size. I avoid log transformation of shape variables (including interlandmark distances) in this thesis for the simple reason that the data and analyses used herein do not appear to indicate the need for it. The shape variables that I use in most analyses do not have any interpretable meaning outside of the shape analysis, so log transforming them would not offer the benefit of interpretable slopes (in contrast to standard bivariate plots, as mentioned in the previous paragraph). Furthermore, the range of size considered in the static allometric analyses is not large enough to invoke an exponential scale. Smith (1980) offers a cogent explanation of why one should not log transform all variables without sound theoretical or methodological reasons.
Connecting the types of allometry
The central aim of this thesis is to describe the evolutionary allometry associated with three different primate lineages (sister species pairs), however the term evolutionary allometry itself
10 can be difficult to define, both conceptually and operationally. In that it concerns the size shape relationship among adults, evolutionary allometry is the logical extension of static allometry beyond the single species level (Cock 1966). Because differences in adult forms (within or between species) ultimately arise through differences in development, evolutionary allometry is also inherently connected to ontogenetic allometry. For example, to describe the evolutionary allometry that characterizes the ancestor descendant lineage depicted in the left panel of Figure 1.3 based on the species’ morphology, ontogenetic data would be necessary to definitively demonstrate that this is a case of hypomorphosis. First, we would need estimates for the average adult shape and size in each species to identify the endpoints of their ontogenetic trajectories in size and shape (red and blue dots in Figure 1.3). Second, we need information on the ontogenetic trajectory of the ancestral species. That is, we need to know its path through size and shape space during development (blue line in Figure 1.3, left). Ideally, we would also have ontogenetic data for the descendant species (red line in Figure 1.3) if we want to verify that its ontogenetic allometric trajectory actually coincides with that of the ancestral taxon, as depicted for these species. Thus, the positive identification of paedomorphosis or peramorphosis requires knowledge of (or, at least, assumptions about ) the ontogenetic allometry of both taxa. Unfortunately, ontogenetic data are not always readily available. Although the pattern of adult static allometry has empirically been found to approximate that of ontogenetic allometry in some cases (e.g., Shea 1982), this is not universally true, and need not be the case theoretically (Cheverud 1982; Cock 1966). Thus, the inferences that can justifiably be made about developmental processes are restricted in studies of adult static allometry such as this one (Shea 1983). To understand why this is the case, consider that the location of an individual in size and shape space is the result, or endpoint, of its own ontogenetic trajectory (Figure 1.4a b). Each individual’s path through size and shape will vary to some degree from that of others in the population, due to normal variation in genotype, environment, and stochastic processes during ontogeny. If we only measure the size and shape variation among the endpoints of these individual trajectories (i.e., adult morphology), this does not necessarily reflect the shape of the average trajectory during ontogeny (Shea 1983) (e.g., compare Figure 1.4c and d).
11
Figure 1.4. The relationship between ontogenetic and static allometry in a population. In any population, there is variation among individuals both in the starting points and ending points of ontogeny in size and shape space. (a) Individuals span a range of sizes ( Xb) and shapes ( Yb) at birth. (b) Individuals also vary in their ontogenetic trajectories, ultimately reaching a range of adult sizes ( Xa) and shapes ( Ya). (c) In this instance, the best fit line describing static adult allometry ( TS, dashed line) is very different from that describing the average ontogenetic trajectory of individuals ( TO, solid line). (d) With less variation in size and shape at birth and in slope of the ontogenetic trajectory, the position of adults in size and shape space ( TS, dashed line) may be a good approximation of the average ontogenetic trajectory (TO, solid line with arrow) of individuals in the population.
Genetic allometry
Before moving on from this discussion, one further point must be made about interpreting static allometry in terms of ontogeny and evolution. The phenotypic variance covariance structure of a population—indicated by its phenotypic static allometry (i.e., adult morphology)—does not necessarily coincide with its genetic variance covariance structure, which determines how a
12 population will respond to selection (or drift) (Cheverud 1982; Lande 1985). One possible null hypothesis for the study of allometry in closely related species is that shape change has occurred as the passive response to selection on size (Lande 1985). But we cannot actually know that selection on body size alone would induce these responses without first knowing about the structure of the underlying genetic variance covariance of these (size and shape) characters within the ancestral population (Lande 1985). As such, I explicitly avoid the temptation to either predict or postdict the trajectory (or magnitude) of response to selection on body size based only on phenotypic parameters (Cheverud 1982:146). Practically speaking, this means that I cannot conclude from morphological data alone that certain phenotypic changes in a dwarfed primate species happened as a passive correlated response to a change in body size. All I can say is that these phenotypic changes appear to be correlated with size in a certain way within adults of one species, and that the relationship within another species appears to be parallel or not.
The specific methods used to evaluate and compare allometry are detailed in Chapter 2.
Ontogeny of the primate cranium
In primates and other mammals, growth of the brain and the globes of the eyes is heavily biased toward the early stages of ontogeny, resulting in the early expansion of the hard tissue cranial structures housing these neural components. Particularly in Old World monkeys (as compared to hominoids and platyrrhines), a large portion of brain growth occurs prenatally, followed by slow growth after birth (Leigh 2004). Ontogenetic studies of primates as well as humans have amply demonstrated that postnatally, the magnitude of growth in the face (viscerocranium) is greater than that in the neurocranium (Leigh et al. 2003; Ravosa 1991b; Sperber 2001). This general pattern of early brain growth followed by later facial growth is fundamental to the evolutionary hypotheses on which the present research is based.
Encephalization
In general, encephalization refers to the size of the brain relative to the body size of an organism. There are different ways to quantify this relationship, one of the most popular being the
13 Encephalization Quotient (EQ). This term and the accompanying formula were introduced by Jerison (1973), although previous researchers had used similar approaches (e.g., the “progression index” of Bauchot and Stephan 1969). EQ is defined as the ratio of observed brain mass to the expected brain mass for a given body mass (Eisenberg 1981; Jerison 1973). By construction, the actual EQ value obtained depends on how one defines the “expected” brain mass. This is normally computed from the empirically derived regression line of log brain mass against log body mass for some group of species. This group could be a broad sampling of mammals (“mouse to elephant”), for example, or birds, or within an order, such as Carnivora. The most commonly cited equations for calculating EQ in mammals are based on regressions published by Jerison (1973), Eisenberg (1981), and Martin (1981). The exact parameters of this regression are debated: theoretically Jerison (1973) argued for a slope of 2/3 for this line based on the relationship between surface area and volume of a sphere, but empirically derived slopes have been found to differ significantly from this value. Using a broad spectrum of mammals, Eisenberg and Martin both calculate the slope at near ¾, which Martin (1981) argues is related to the comparable scaling of metabolic rate in mammals (the “maternal energy hypothesis”). Within a narrower set of mammals, such as an order, or within a narrower range of body masses, the regression parameters will differ. One potential alternative to the EQ style approach is to use a simple metric of relative brain size (RBS) that does not take any allometric regression into account. This ratio (brain mass ÷ body mass) does not attempt to make an allometric correction for the lack of isometric scaling between body mass and brain mass. As such, it does not rely on a choice of which allometric “criterion of subtraction” to employ. That is to say, all allometrically corrected measures of encephalization (such as the various definitions of EQ) are determined by the empirical or theoretical allometric relationship used to establish the expected brain body relationship. This relationship varies widely depending on the taxonomic level and range of body sizes considered.
Island Evolution & the Island Rule
Since the time of Darwin and Wallace, island evolution has been an inspiration and a model for investigating evolutionary theory. The seminal work of MacArthur and Wilson (1963; 1967) established the study of island biogeography as a field in and of itself. Islands offer unique
14 environments for natural experiments of evolution. When islands are remote and their biota isolated from larger gene pools, populations are especially vulnerable to founder effects (Mayr 1942; Mayr 1954) and genetic drift. Low diversity and small population sizes on islands necessarily make species more vulnerable to extinction than larger and more diverse ancestral populations. Rare but catastrophic events, such as hurricanes, earthquakes or droughts can have significant impacts on island biota. Volcanic islands are themselves products of catastrophic tectonic events, and are thus inherently ephemeral. Oceanic islands—those that have never been connected to a larger land mass—are only populated via what Simpson (1940) called “sweepstakes routes.” Such dispersal events would be highly improbable for most animals (Sondaar 1977). Barton (1989) coined the term faunal drift to describe this random sampling of species that reach an empty habitat. When such colonizing species reach a vacant habitat, this ecological release (Whittaker and Fernández Palacios 2007) allows them to evolve in ways that would be unlikely or impossible in their home environment with interacting competitors and predators. For example, the combination of a large landmass and isolation from mainland Africa permitted ancient members of the lemur and tenrec lineages to undergo huge radiations on Madagascar, in the absence of the predators and competition from other mammal lineages that existed on the mainland.
The Island Rule
It has been frequently observed that animals isolated from mainland populations for many generations undergo drastic increases or decreases in body size: giant island rodents and dwarf mammoths are two familiar examples. Although such evolutionary oddities have always interested researchers, they have recently risen to prominence in light of the Flores hominin discoveries. Although hypotheses abound, there has never been universal agreement as to the proximate and ultimate causes of body size trends often observed in island populations. These trends were first systematically described by Foster (1964), and termed the "island rule" by Van Valen (1973). This term describes the observation that isolated island populations of certain taxonomic groups often have drastically different body sizes than mainland populations. The pattern has come to be interpreted as a graded trend across and within taxa whereby large animals like ungulates tend to be smaller than mainland forms, while small animals like rodents tend to be larger (Heaney 1978; Lomolino 1985). Most hypotheses regarding island dwarfism involve some combination of selective pressures such as reduced threat of predation, reduced energetic
15 resources, and increased vulnerability to population crashes (Foster 1964; McNab 1994; Palombo 2007). Sondaar (1977) hypothesized that the frequent dwarfing of large mammals on islands is related to the potential for massive fluctuations in population size in such environments. For example, bone beds containing the remains of Pleistocene deer on the island of Crete suggest that the deer may have become overpopulated (perhaps due to predator release, e.g.) and subsequently suffered a mass starvation. Sondaar (1977) argues that such strong peaks and crashes in population size would be very strong selective events. Survivors of crashes would heavily skew genetic contribution to future generations (bottleneck effect). Individuals that survived a starvation event, Sondaar reasons, would have been those individuals that had a significant energetic advantage over their conspecifics. These pressures could result in traits such as (1) reduced allocation to neural tissue (i.e., smaller brains), (2) smaller overall body size, (3) reduced basal metabolism, (4) ability to exploit novel food and mineral resources. Sondaar’s scenario is supported by Marshall and Corruccini’s (1978) observation that extinction and dwarfing seem to be correlated in time, and thus, may be results of the same evolutionary forces. The exact mechanisms underlying island dwarfing are by no means settled, however, and recent studies have challenged the existence of any such general rule across mammalian clades (Meiri et al. 2008a; Meiri et al. 2004; Meiri et al. 2006). The present research does not attempt to prove, disprove, or otherwise test the validity of the island rule (Damuth 1993; Lomolino 1985; Van Valen 1973). Instead, given that there exist empirical examples of derived dwarfing on islands, I ask how cranial shape and proportions in such mammals differ from that of the non isolated population. It is hoped that this study will shed light on the potential mechanisms (selective, developmental, ecological) involved in such instances.
Anatomy of Island Dwarfs
Characteristic changes in postcranial anatomy accompany reduction in overall body size in many insular mammals. A tendency for reduced distal limb length and for fusion of limb bones— adaptations, presumably, to "low gear" locomotion—are particularly well documented, as are dental adaptations (Croft et al. 2006; Gould 1975b; Köhler and Moyà Solà 2001; Roth 1992; Sondaar 1977). Less well studied are changes in cranial form that may be correlates of island dwarfing. Köhler and Moyà Solà (2004) describe a Pleistocene goat (genus Myotragus ) from the Spanish island of Majorca with a small body size, and even smaller brain and orbits than would
16 be predicted for a bovid of comparable mass. The authors speculate that the relict population reduced its neurological components after being released from the predation pressure it experienced on the mainland. To investigate whether other insular artiodactyls lacking predators show a similar reduction in brain size, Palombo et al. (2008) consider the extinct Cretan deer Candiacervus . They find that the dwarfed deer exhibits only a slightly smaller brain than expected for a cervid of its body size. Orbit size in Candiacervus is more reduced than the brain, though not to the extent observed in Myotragus (Palombo et al. 2008). This finding raises intriguing questions about the causes, effects and mechanisms of island dwarfing. What kinds of changes in the central nervous system are associated with island dwarfing? Do predictable patterns of cranial form accompany cases of insular dwarfism in mammals, or is every case unique? How do these changes occur developmentally and evolutionarily? Gracile or paedomorphic cranial characters have been noted in insular mammals by several authors. The small insular canid Cynotherium from the Pleistocene of Sardinia retains hypercarnivorous teeth while lacking the cranial characters associated with this trait in all other canid taxa (Lyras et al. 2006). These authors conclude that the more gracile structures related to the masticatory apparatus are an adaptation to fast, small prey (such as the insular rabbit with which it shared the island) rather than the large, powerful prey of its mainland ancestors. Palombo and Giovinazzo (2004:44) find no “important brain change” in island Cynotherium , however. Paedomorphic cranial features are observed in the (extinct) dwarf elephant of Sicily, Elephas falconeri (Ambrosetti 1968). The skull is much reduced in size compared to its mainland ancestor, but the brain case is relatively expanded, and the placement of the respiratory axis is modified (Palombo 2001). This inflated neurocranium results in an adult skull that closely resembles juvenile specimens of other elephant species (Palombo 2001). Although the most impressive examples of endemic dwarfing in mammals are now extinct, there are some extant island dwarf species as well. Sloths endemic to the Bocas del Toro Islands, Panama, ( Bradypus pygmaeus ) exhibit the hallmark brachycephalic cranial shape of dwarfed mammals that accompanies a gracile facial skeleton and relatively inflated neurocranium (Anderson and Handley 2002). The Californian Channel Islands fox ( Urocyon littoralis ) differs from its mainland congeners in its smaller cranial size, relatively wide nasal bones, and less developed temporal ridges (Moore and Collins 1995). Wayne et al. (1991) studied morphological features of the Channel Islands fox, finding that variability in craniodental measures is lower in the island species than in the mainland gray fox. In a more recent study, Schauber (2007)
17 compared relative brain size (RBS = brain size÷body size) to that of the mainland gray fox, finding that RBS does not differ significantly between the two species. Because the brain scales with negative allometry (Armstrong 1985; Gould 1975a), the dwarf species would be expected to have a higher overall RBS, but this does not appear to be the case in the fox. These results bear on the issue of encephalization in island dwarf mammals.
Primate Models for Dwarfing
Although examples abound within the ungulates, there are few clear cut cases of island dwarfing within primates. Two extinct endemic forms are known from the Mediterranean region: the Miocene ape Oreopithecus , and a macaque from Sardinia, Macaca majori . Oreopithecus , endemic to a late Miocene island (Tuscany Sardinia, Italy) may not represent a dwarf form per se, but displays some very primitive cranial morphology, a relatively small brain and robust dentition, all of which have been attributed to a protracted period of evolution in isolation (Bilsborough and Rae 2007). Remains of Macaca majori suggest that, compared to modern macaques, it had reduced cranial dimensions relative to its body size (Rook and O'Higgins 2005). Its dentition, however, is relatively robust, and the facial skeleton exhibits lateral zygomatic expansion compared with extant species (Rook and O'Higgins 2005). Among extant primates, the Zanzibar red colobus ( Procolobus kirkii ) was studied by Nowak et al. (2008), who found that this island endemic has reduced cranial size and cranial sexual dimorphism compared to most mainland African colobus species. They concluded that this reduced sexual dimorphism is associated with smaller size and paedomorphic cranial traits in males, such as a short face, and enlarged neurocranium and orbits. Ideally, a comparative study of dwarfing in primates would include several endemic species that underwent dwarfing over many thousands of generations in isolation. Additionally, the optimal reference sample would include the last common ancestor of the dwarf and a non dwarf sister taxon in each case. As this is not feasible, extant close relatives of each dwarf taxon must be used as proxies for the ancestral forms. After a thorough review of the relevant literature, I identified two probable examples of island dwarfism in primates for which adequate museum samples exist in North America, both of the island taxon as well as a close mainland relative. The endemic leaf monkey ( Presbytis natunae ) of Greater Natuna Island, Indonesia, is compared to mainland (or very large island) populations of Presbytis melalophos . The simakobu monkey ( Simias concolor ) of the Mentawai
18 Islands, Indonesia, is compared to its closest living relative, the much larger proboscis monkey (Nasalis larvatus ) of Borneo. To contrast with endemic dwarfing in an island setting, a primate species which has evolved smaller body size in a non island setting will also be considered. The hylobatids in Asia and the South American callitrichids are two groups considered by many to be dwarfed lineages (e.g., Ford 1980; Ford and Nowak 2010; Martin 1992). In each of these cases, however, there is no obvious source for a comparative sample representing a putative ancestral form. In contrast, the talapoin monkey, or dwarf guenon (Miopithecus ogouensis ), of West Africa has long been recognized as a dwarf of the tribe Cercopithecini for which a radiation of closely related non dwarf species exist. For a comparison species, I examine the larger spot nosed guenon, Cercopithecus nictitans . For each dwarf species, cranial form and shape, proportion, and encephalization is compared to that in the non dwarf species, which is a best available model for the ancestral morphology. Three dimensional landmark coordinate data, endocranial volume, linear measures and body size indicators collected from museum specimens constitute the dataset upon which these comparisons are based. There may exist no common trends in cranial form among these island dwarfs. It may be the case that every island population represents the product of such unique ecological variables and evolutionary pressures that dwarfing affects the skull differently in each instance. Periods of isolation vary, and populations are not confined to equally sized islands with identical climates or terrains. Each species shares its environment with a different set of flora and fauna, meaning that resource availability and competition for resources are not equivalent. Small island populations are inherently vulnerable to extinction and tend to be relatively short lived (Alcover et al. 1998; Harcourt 1999; Harcourt and Schwartz 2001; MacArthur and Wilson 1967), biasing the extant populations available for study in any given era. Any study of a "natural experiment" is inevitably post hoc, and many variables are therefore out of our control. However, it would be an equally valuable result if there were documented evidence that no such trends exist. The only way to determine this is with a systematic study. Furthermore, there are enough putative cases of island dwarfing in mammals that it seems reasonable to hypothesize that common biological processes are at work. This thesis will use as its framework the null hypothesis that the cranial size and shape of derived dwarf primate species are consistent with ontogenetic scaling of the presumed ancestral form. In lieu of the actual ancestral morphology, the derived dwarf species is compared to
19 another species with which it shares a recent common ancestor. Thus the expectation of the null hypothesis is that the dwarf species exhibits paedomorphic or juvenilized cranial features. In comparison to the non-dwarf species, dwarfs will have smaller absolute cranial dimensions, but relatively large orbits and neurocranium, a reduced facial skeleton, and higher overall encephalization.
Overview of Thesis Organization
Chapter 2 will detail the materials and methods used in the dissertation research, including descriptions of the primate samples, data collected, and analyses performed. Chapters 3, 4 and 5 are devoted to three case studies of dwarfing in non human primates. Chapter 3 reports the comparison of the first species pair: the talapoin monkey ( Miopithecus ogouensis ) and the greater spot nosed guenon ( Cercopithecus nictitans ). Chapter 4 examines two closely related odd nosed colobines, the simakobu monkey and the proboscis monkey. Chapter 5 compares the rare Natuna leaf monkey ( Presbytis natunae ) to mainland forms of Presbytis leaf monkey. Chapter 6 summarizes the conclusions of these comparisons, and outlines a theoretical framework for classifying primate dwarf species. The Flores hominin remains are discussed with respect to this framework, as is human and non human evolution more broadly.
Chapter 2
Materials and Methods
This chapter will describe the samples used in this thesis, along with the data collection methods and approaches to data analysis. It is organized into five main sections: (1) Samples, (2) Data collection, (3) Data processing, (4) Analysis of landmark data, and (5) Analysis of non landmark data.
Samples
Three pairs of primate species are considered in this thesis: 1) the northern talapoin monkey ( Miopithecus ogouensis ) and the larger spot nosed guenon ( Cercopithecus nictitans ) of West Africa (Chapter 3); 2) the simakobu monkey ( Simias concolor ) of the Mentawai Islands and the proboscis monkey ( Nasalis larvatus ) of Borneo (Chapter 4); and 3) the Natuna Island leaf monkey ( Presbytis natunae ) and the Sumatran surili ( Presbytis melalophos ) (Chapter 5).
In each case, the choice of species is based on evidence for derived body size reduction in the smaller primate compared to its probable last common ancestor with the larger extant species. These species are described more fully in their respective chapters.
Museums
The specimens were measured at eight museums in North America (Table 2.1). In addition, the crania of three individuals of the rare endemic species Presbytis natunae held at the Raffles Museum Zoological Reference Collection (ZRC) at the National University of Singapore were micro CT scanned on site. A micro CT scan of one male Miopithecus ogouensis from a private collection was kindly provided by Professor Richard Kay.
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Table 2.1. Museums curating specimens used in this dissertation.
Museum Name Abbreviation Academy of Natural Sciences, Philadelphia ANSP American Museum of Natural History, New York AMNH Carnegie Museum of Natural History, Pittsburgh CARN Museum of Comparative Zoology, Harvard University, Cambridge MCZ National Museum of Natural History, Smithsonian Institution, Washington, D.C. NMNH Royal Ontario Museum, Toronto ROM Tulane Museum of Natural History, New Orleans TMNH University of Michigan Museum of Zoology UMMZ Zoological Reference Collection, Raffles Museum, National University of ZRC Singapore
Criteria for inclusion
The primate samples are composed mainly of wild shot museum specimens, which can introduce various statistical biases. In particular, animals were collected over a span of several years, and over varying geographic ranges. Biases in the collection process may over represent some individuals due to physical, behavioral, or ecological attributes. These factors reduce the extent to which the samples can be considered representative of true biological populations. Although captive animals were excluded as a rule, two male talapoin monkeys ( Miopithecus ogouensis ) that died in captivity were included to increase the small sample size. I attempted to include approximately equal numbers from both sexes. Generally, only adult individuals were considered, as determined by third molar eruption. Complete descent of the maxillary canines was not required for inclusion, although this condition was noted during data collection. Two female individuals with incomplete third molar eruption were included from the species Simias concolor (Chapter 4), due to the paucity of usable specimens. Individuals were excluded if the sex or provenience could not be determined, or if the cranium was incomplete or significantly damaged.
Phylogenetic considerations
In choosing which species to include in these comparisons, I referred to the most up to date molecular phylogenies published. Because all comparisons in this thesis are between closely related species—and not across species of differing degrees of relatedness—the issue of phylogenetic nonindependence (Felsenstein 1985) is moot.
22 Sample size
Sample sizes (Table 2.2) are limited to what is available in museum collections. Specimens are especially rare for the small island endemics due to their small population size. In any given analysis, the number of individuals may vary, depending upon the specific type of data under consideration. For example, endocranial volume is available for some individuals that lack landmark data, and for others, the converse is true. Body mass data are only available for approximately 24% of the individuals with landmark data.
Table 2.2. Species and sample sizes used in this dissertation. Included in this table are the sample sizes used in most morphometric analyses. Numbers used in any given analysis may differ somewhat, as indicated in the corresponding results section. (Abbreviations: N missL = number of specimens with missing landmarks; missL = average number of missing landmarks in specimens with missing landmarks) (following convention of Cardini and Elton (2008a)). Of 250 individuals listed below, 31 had at least one missing landmark.
Number of Individuals Species Male Female
total NmissL missL total NmissL missL Miopithecus ogouensis 18 2 2 22 - - Cercopithecus nictitans 24 3 1.7 21 4 1.8 Simias concolor 10 1 1 15 2 1.5 Nasalis larvatus 23 3 1 36 6 1.2 Presbytis natunae 4 1 2 10 2 1 Presbytis melalophos 31 5 1.4 29 1 1 Prebytis femoralis 0 - - 7 1 1 TOTAL 110 15 1.5 140 16 1.3
Data Collection
Landmark Data
Landmark choice
Landmarks for this study were chosen based on the following criteria: 1) correspondence and visibility across species, 2) minimization of observed measurement error, 3) biological relevance, and 4) maximum coverage of all areas of the cranium. Fifty nine anatomical landmarks were collected in total, although only 45 were used in most analyses (Figure 2.1, Table 2.3).
Figure 2.1. Cranial landmarks. See Table 2.3 for descriptions. Clockwise from upper left: basicranial view, superior view of an middle endocranial fossae, anterior view, posterior constructed from micro CT of male scan of female Presbytis melalophos
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Table 2.3. Landmark descriptions and abbreviations. Numbers correspond to those used in Figure 2.1.
Landmark Description Abbreviation 1 Basion. Most anterior midline point along anterior border of foramen magnum. BAS 2 Bregma. Point of intersection of the coronal and sagittal sutures on the exterior BRG surface of the cranial vault. 3 Incisive Foramen. Intersection of the posterior border of the incisive foramen with the ICVF palatal midline. 4 Interdentale Superior. Most anterior midline point on the alveolus between the IDS maxillary central incisors. 5 Lambda. Point of intersection of the lambdoid suture with the posterior sagittal LAM suture. 6 Maxillary-Palatine Suture at Midline. Intersection of the maxillary-palatine suture MPSM with the palatal midline. 7 Nasale. Most distal midline point on the nasal bones. NAL 8 Nasion. Intersection of the internasal suture with the nasal process of the frontal NAS bone. 9 Opisthion. Most posterior midline point along the posterior border of the foramen OPI magnum. 10 Posterior Nasal Spine. Most posterior midline point on the plane of the palate. PNS 11 Vomer-Sphenoid Junction. Most posterior midline point on the alae of the vomer. VSJ 12, 13 Asterion (bilateral). Intersection of the lambdoid suture with the parietotemporal and LAST, RAST occipitotemporal sutures. 14, 15 Basioccipital synchondrosis (bilateral). Lateral extreme of basioccipital synchondrosis. LBOS, RBOS 16, 17 Carotid Canal (bilateral). Most lateral point on rim of canal. LCAR, RCAR 18, 19 Condylar Intersection with Foramen Magnum (bilateral). Posterior intersection of LCIFM, RCIFM occipital condyle with border of foramen magnum. 20, 21 External Auditory Meatus (bilateral). Roof of external auditory canal, in approximate LEAM, REAM plane of tympanic membrane. 22, 23 Foramen Ovale (bilateral). Most anteromedial point on foramen ovale (external). LFO, RFO 24, 25 Frontal-Zygomatic Junction (bilateral). Fronto-zygomatic suture at the orbital rim. LFZJ, RFZJ 26, 27 Hypoglossal Canal (bilateral). Most posterior point on endocranial aperture of LHYP, RHYP hypoglossal canal (most posterior if multiple foramina). 28, 29 Infraorbital Foramen (bilateral). Inferolateral rim of infraorbital foramen (largest, LIF, RIF most superior if multiple foramina). 30, 31 Jugular Process (bilateral). Jugular process at antero-lateral extreme of LJUG, RJUG occipitomastoid suture. 32, 33 Maxillary Tuberosity (bilateral). Most posterior point on maxillary alveolus. LMXT, RMXT 34, 35 Temporal-Sphenoid Junction at Petrous (bilateral). Intersection of temporal-sphenoid LPET, RPET suture with petrous temporal. 36, 37 Premaxillary-Maxillary Suture (bilateral). Inferior extreme of premaxillary-maxillary LPMMX, RPMMX suture on anterior alveolus, medial to C 1. 38, 39 Temporal-Sphenoid Suture at Crest (bilateral). Most convex point along temporal- LTSCR, RTSCR sphenoid suture (or estimated position) on surface of temporal fossa. 40, 41 Temporal-Zygomatic Junction (bilateral). Inferior aspect of temporal-zygomatic suture LTZJ, RTZJ on zygomatic arch. 42, 43 Zygomaxillare Inferior (bilateral). Most inferior point on zygomaxillary suture. LZMI, RZMI 44, 45 Zygomaxillare Superior (bilateral). Intersection of zygomaxillary suture with inferior LZMS, RZMS border of orbit. 46 Sella Turcica. Deepest point on bone along midline of sella turcica. (Not normally SELLA accessible on intact crania.)
25
Digitizer
Three dimensional coordinate landmark data were collected directly from museum specimens using a handheld portable digitizer, the MicroScribe G2X. Polymer clay was used to secure the cranium in position while 23 anatomical landmarks were collected from the superior surface of the cranium and face. The cranium was then inverted and re secured to the table on its vertex, exposing the inferior (=ventral) surface for collection of the remaining 36 anatomical landmarks of the cranial base. In addition to the anatomical landmarks, four artificial points were marked with a pencil on each cranium, and recorded in both “superior” and “inferior” orientations. These four “shared” landmarks were then used to join the two separate landmark sets into a single configuration for each cranium (technique described below in Data Processing section). Landmarks were collected at least twice in each orientation before moving the specimen (see Landmark Error, below). The landmark SELLA was only collected in cases where the cranial vault had been physically detached (presumably to remove the brain; n=21), when the cranium had been bisected (n=3), and in the four individuals for which micro CT scan data were available. In such cases, the total number of “superior” orientation landmarks was 24.
Micro-CT scans
Three individuals from the extraordinarily rare species Presbytis natunae could not be readily digitized in person because they are curated in the Zoological Reference Collection of the Raffles Museum in Singapore. These three specimens were scanned by micro CT on site at the National University of Singapore. In addition, Professor R. Kay provided a scan of one male Miopithecus ogouensis specimen from his private collection. For these four individuals I was thus able to obtain micro CT scan data of the crania. The same landmarks were collected for these specimens, using the software Amira (Mercury Computer Systems 1995 2005) for reconstruction and landmark placement. Additionally, linear measures and endocranial volume were estimated using Amira. As an independent check on accuracy of the digitally collected data, for two of the Singapore Natuna monkeys, I was able to compare some linear measures that I recorded in Amira (e.g., orbital width, postorbital constriction) to those measured on the original specimens with
26 calipers by Professor N.G. Jablonski. The linear measures recorded in Amira differed from the caliper measures by an average of 1.3%.
Landmark Error
The measurement error associated with landmark collection depends on several factors. One contributor that is not directly quantified here is the biological variability among individuals in a sample (the issue of repeatability, Corner et al. 1992; Richtsmeier et al. 1995). One other potential source, interobserver error, is avoided in this thesis because all landmark data were collected by a single observer (BCF). Measurement error in landmark data collected using a hand held digitizer on original specimens arises from imperfection in the observer’s ability to locate a landmark accurately as well as limitations on the ability to physically record that location precisely. Included within this is error introduced by tiny movements in the specimen if it is not completely secured to the platform, and the error associated with the digitizing device itself (reported as ±0.23 mm by the manufacturer, Immersion Corporation). To maximize the precision with which landmark coordinates were recorded in practice, all landmark points were digitized twice with the cranium fixed in a single orientation. If the absolute difference between the two repeats was greater than 0.5 mm along any axis ( x, y, or z), that landmark was measured again, and repeated until the standard deviation among repeated measurements was ≤0.5 mm along all three axes. For the four artificial “shared” landmarks, the allowable imprecision was reduced to 0.2 mm from 0.5 mm. The maximum potential error associated with landmarks in the full configuration is somewhat higher than this, however, because each configuration is composed of landmarks collected in two separate orientations (superior and inferior). This process is explained under Data Processing. When landmarks are placed on surface reconstructions of micro CT scans, sources of potential error are somewhat different. The observer’s imperfect ability to accurately locate a point and precisely record it remains. The possibility for movement of the specimen with respect to the coordinate system of the digitizer during data collection is eliminated, but artifacts of the scanning and subsequent reconstruction process are introduced. Precision is limited by the resolution of the reconstruction, which is bounded by the resolution of the scan itself. The four scans used here were reconstructed at a resolution of <0.2 mm pixels and <0.15 mm slices. Even given this high resolution, some details of surface morphology are lost. Cranial sutures may be invisible, for example. The scan reconstruction lacks subtle variations in surface texture and color of the bone which may serve as cues to the observer. In this study, the maximum allowed
27 error (as standard error of the mean) associated with repeated measures (3+) of a landmark collected from the micro CTs was 0.5 mm along each axis. The standard error from repeated measurements of a given landmark location along each axis was considerably lower, on the order of 0.2 mm. No joining of landmark configurations was necessary with data collected from micro CT reconstructions, as the virtual cranium can be rotated within a fixed coordinate system to collect landmarks in any orientation. Repeated measurements were averaged to produce the final landmark coordinate configuration for each individual. Regardless of whether landmark coordinates are recorded directly from the specimens or from digital representations, anatomical landmarks may not be identifiable for a variety of reasons: injury or modification during life (e.g., tooth loss), peri or post mortem specimen damage (e.g., gunshot wounds; removal of brain via neurocranial vault or peri foramen magnum modification), artifacts of scanning procedure (e.g., scan did not cover entire cranium), and normal biological variation (e.g., natural obliteration of cranial sutures during ontogeny). In such cases, landmark location was either estimated during collection (e.g., approximating bregma from traces of coronal/sagittal sutures), estimated in data processing (via reflection or Thin Plate Splines, see Data Processing section), or the landmark was excluded from the configuration (and subsequent analysis) altogether. It is for this reason that sample sizes often differ in different analyses, as specimens missing particular landmarks had to be excluded. In addition to 3D coordinate landmark data, some traditional linear and volume biometrics were measured, such as cranial length (condylobasal length), head and body length, and endocranial volume.
Endocranial Volume (ECV)
For all museum specimens measured in person, cranial capacity was estimated by filling the neurocranium with glass “seed beads” (bead size 11/0; ~2.0 mm diameter × 1.0 mm deep) via the foramen magnum after plugging the other major cranial foramina with polymer clay (Sculpey®). The beads were then emptied from the cranium and poured into a graduated cylinder, agitated to ensure uniform packing, and a volume reading recorded. For volumes of ≤ 100 mL or less, a cylinder of 100 mL (=100 cm 3) capacity was used, and volume was estimated to the nearest 0.5 mL. For endocranial volumes exceeding 100 mL (which was the case in most male Nasalis larvatus individuals), a graduated cylinder of 250 mL capacity was used, and volume was
28 estimated to the nearest 1 mL. Small portions of damaged crania were reconstructed with polymer clay in order to obtain an ECV estimate when necessary, provided that the damage was not extensive. For most individuals, ECV was measured a single time. On a smaller sample of specimens, repeated estimates from the same individual were within ± 5% of the total estimated volume, similar to other published studies (e.g., Ravosa 1991b). In the four micro CT scans, endocranial volume was estimated using Amira. This was achieved by selecting the area enclosed within the endocranial cavity on each two dimensional slice of the scan, then using Amira’s surface generation function to compile these selected 2D areas into a 3D object, for which it then calculates the volume (Figure 2.2). On repeated measurement by a single observer (BCF), the precision associated with this process falls within 2% of the total estimated volume.
Figure 2.2. Digital endocast of a male talapoin monkey. Reconstruction and image created in Amira from micro CT scan data. Scan courtesy of Prof. R. Kay.
Other metrics
Linear measurements were recorded to the nearest 0.1 mm from each specimen using digital calipers (see Table 2.4 for definitions and abbreviations). Condylobasal length (CBL) was recorded as the distance between the most anterior midline point on the alveolar process of the maxilla (a.k.a. prosthion) and the posterior border of the occipital condyle (average of right and left side readings). Orbital height was recorded as the maximum interior distance between the
29 superior and inferior borders of the right orbit, parallel to the orbit’s vertical axis. Similarly, orbital width was measured between the lateral and medial borders of the right orbit, parallel to horizontal axis of the orbit. Orbital area, as approximated by multiplying orbital height by width, has been used in previous primate studies as an estimator of ocular size (e.g., Aiello and Wood 1994). The variable Orbital Diameter (OD) is the square root of this product, i.e., the geometric mean of the width and height. This results in a 1 dimensional estimator of orbital aperture size, making it easily comparable to other linear cranial dimensions. For the four specimens measured from micro CT scan data, these measuring techniques were mimicked with the linear measuring tool in Amira.
Table 2.4. Non-landmark-based metrics. Measures for all individuals available from the author upon request. Metric Definition Endocranial Volume (ECV) Volume of the endocranial cavity. (mL = cm 3) Orbital Diameter (OD) The square root of the product of Orbital Height and Orbital Width. (mm) Orbital Height The maximum interior distance between the superior and inferior borders of the right orbit, parallel to the orbit’s vertical axis. (mm) Orbital Width The maximum distance between the lateral and medial borders of the right orbit, parallel to horizontal axis of the orbit. (mm) Condylobasal Length (CBL) The distance between the most anterior midline point on the alveolar process of the maxilla and the posterior border of the occipital condyle (average of right- and left-side readings). (mm) Head-and-Body Length (HBL) Measured from the tip of the nose to the base of the tail (Schultz 1929). (mm) Mass Taken from collectors’ field notes, when available. (g) M2 Posterior Width (M2PW) The maximum buccolingual width of the crown of the distal loph of upper M2 (following Delson et al. 2000). (mm) Femoral length Measured from the superior surface of the femoral neck at its deepest point to the average projection of the distal condyles (following Ruff 2002). (mm) Femoral midshaft width The antero-posterior width of the femur at the midshaft (following Delson et al. 2000). (mm) Femoral head supero-inferior The maximum supero-inferior breadth of the joint surface (following breadth Ruff 1988). (mm) Femoral head antero-posterior The maximum antero-posterior breadth of the joint surface (following breadth Ruff 1988). (mm) Cranial Base Angle (CBA) Calculated as the angle between the landmarks nasion-SELLA-basion. (degrees)
For approximately 70% of individuals with landmark data, the head and body length (HBL) of the animal could be obtained either from the original specimen tags, or from the dried skin using a measuring tape. Although the HBL measures are prone to considerable error (from
30 differences in technique between observers, differences in condition of the animal at the time of measuring, and simple specimen/tag mix ups, e.g.), this information is nonetheless useful as an indicator of body size, particularly considering that body mass data were rarely available.
Other data
Accompanying information was typically available for the specimens. Museum records included the following information: species (and sometimes, subspecies) designation, sex, date and locale of collection, and collector’s name. These data were recorded, along with body mass and head and body length data, if listed in the records.
Supplementary metrics
Some measurements were recorded that were not used in any analyses in this thesis. For example, second molar posterior width (M2PW) is not immediately relevant to the analyses here. Femoral measures and cranial base angle, on the other hand, were available for so few specimens that they could not be readily incorporated into this study. These data are available from the author upon request, in the hopes that they may be useful to future researchers. When postcranial skeletal elements were available (n=43), calipers were used to record femoral midshaft width, and femoral head breadth (both supero inferior and antero posterior, as in Ruff (1988)). Femoral length—from the superior surface of the femoral neck at its deepest point to the average projection of the distal condyles (following Ruff 2002)—was measured in one of three ways. In the case of very small specimens ( Miopithecus ogouensis ), digital calipers were employed. For larger specimens, femoral length was measured on an osteological board, or by digitizing the two endpoints of the femoral measure using the Microscribe (and subsequently calculating the distance between the two points). Cranial base angle (CBA) was calculated for the 27 total individuals on which all three of the necessary landmarks could be collected (see note on SELLA under Digitizer, earlier). It was calculated as the angle between nasion, sella turcica (vertex), and basion.
31 Data Processing
Joining configurations
Landmark data collected using the Microscribe digitizer required an additional step of processing after averaging repeated measures, as the landmarks were collected in two separate orientations (superior and inferior) for each individual. The average landmark coordinates from both orientations were joined using four “shared” landmarks (a.k.a. “fiducial points,” Mitteroecker et al. (2004); “reference landmarks,” von Cramon Taubadel et al. (2007)), which were pencil points marked on each cranium and digitized in both orientations. The program DVLR (Reddy and Raaum 2006) was used to join the two orientations into a single landmark configuration. The program performs a least squares fit to the four landmarks shared by both orientations (“shared” points), rotating both configurations into a single coordinate system. Note that the measurement error associated with collecting the landmarks (limited in practice to ≤ 0.5 mm along each axis) is amplified during this joining process, as there is some error (≤ 0.2 mm) associated with recording the “shared” landmarks themselves.
Missing landmarks
In cases where a specimen was missing four or fewer bilateral landmarks on one side (due to breakage, etc.), the missing landmarks were estimated by reflecting the corresponding landmark from the opposite side (Mitteroecker and Gunz 2009). To do this, a least squares algorithm was used to fit a plane to the specimen’s midline landmarks, then the missing landmark was estimated by reflecting its antimere from the opposite side across the midline plane (this is similar the method used by Singleton (2002), among others). At least one lateral landmark was reconstructed on 29 specimens (Table 2.2). In a small number of cases (n=4), a single missing midline landmark would have required that an individual (with otherwise complete data) be dropped from all landmark analyses. In order to maximize sample size, these landmarks were reconstructed using thin plate splines (TPS). This was achieved by first creating a template landmark configuration, which was the mean shape (via Procrustes superimposition, described later) for all individuals in the species sex group. Then the TPS algorithm was applied to warp the template configuration (by minimizing bending energy) to the target with the missing landmark. Finally, the missing
32 landmark was imputed from the position of the warped template. This process was performed using Viewbox 4 software (Halazonetis 1995 2010). After processing, landmark coordinates were loaded into a Microsoft Access 2007 database linking landmark data with specimen ID, species, sex, museum location, and the other metrics collected (ECV, CBL, mass, etc.).
Sexual Dimorphism
The issue of sexual dimorphism complicates virtually any study of primate morphology. The species in this study span a wide range of body sizes, and the extent of their sexual dimorphism varies dramatically. For this reason, dimorphism must be considered separately for each taxon. In general, the model species belonging to the genus Presbytis exhibit low enough sexual dimorphism that pooling the data from both sexes is appropriate in some instances. In Cercopithecus , Simias , and Nasalis , strong dimorphism dictates that the sexes be treated as separate morphospecies in most analyses. The specific approach to sexual dimorphism in each analysis is presented with the results of that analysis.
Analysis: Landmark Data
Terminology
This thesis employs several different morphometric methods. Each of these uses morphological data to address biological form in a different way. Precision in terminology is important, because different methods use their own vocabulary, and to interpret the results, it is critical that the reader know exactly what analysis was done and how. For example, the term “size” in the context of an analysis based on interlandmark distances normally refers to the geometric mean of all possible distances for that individual, whereas in superimposition based analyses, “size” implies centroid size, which is a different quantity. As much as possible, critical terms are defined as they are introduced in the text. Additionally, a glossary of terms is located in the Appendix.
33 Definitions
The word form describes all aspects of size and shape. The definition of form employed in this thesis is “that characteristic which remains invariant under translation, rotation, and reflection of the object,” following Lele (1991:407). The word shape denotes a closely related property: form with the addition of invariance to scaling. It should be noted that the quantitative analyses in this thesis deal only with form and shape insofar as those properties may be captured by landmark coordinate data. Of course, much information about texture, curvature and other potentially important biological features of the specimens is lost when form is reduced to a configuration of a few points in space. This is a shortcoming shared by all studies using only biological landmarks. I attempt to mitigate this shortcoming to some extent by including other metrics that complement the landmark data, such as ECV and caliper measures not defined by biological landmarks. Another technical note on form and shape : These two properties are invariant to the parameters of translation, rotation, and reflection at the level of an individual object (such as a single skull), and as conceptual ideals (e.g., the species average skull, or “The Skull” in a Platonic/Socratic sort of way). However, the process of comparison of forms and shapes— including the practical estimation of mean forms or shapes from a sample—does not necessarily imply invariance to these parameters. Thus, individual objects (or landmark configurations) always preserve their own shape in any of the analyses described here. But for analyses that require registration of individuals for comparison—including the informal visual inspection of two individuals, or any type of superimposition—the observer must choose a single registration, and the comparison is no longer invariant to translation, rotation, and reflection, but rather associated with a single algorithm for fixing these parameters.
Distance-based vs. superimposition methods
Characteristics of size and shape in primate crania, as captured by 3D coordinate landmarks, were analyzed using two separate methodological approaches—one that is invariant to coordinate systems (EDMA), and one that superimposes all objects into a common coordinate system (Procrustes superimposition). As the approaches have differing strengths in the type of biological and geometric questions that may be addressed (see Adams et al. 2004; Richtsmeier et al. 2002, for differing perspectives), using the two in concert creates the potential for a more holistic interpretation of the data. It is hoped that together the results and conclusions will be accessible to researchers from a variety of morphometric backgrounds.
34 Distance methods: Euclidean Distance Matrix Analysis (EDMA)
The first approach used in this thesis to analyze form and shape is based on interlandmark distances. As mentioned above, it is invariant to coordinate system. This method is referred to as Euclidean Distance Matrix Analysis, or “EDMA.” Analyses are performed using the software WinEDMA (Cole 2002).
Form
The purpose of the EDMA Form procedure (Lele 1991) is to compare the form of two samples, leaving size (and its effects on shape) intact. Given two groups of individuals with landmark coordinate data for each, the Form function computes all possible pairwise interlandmark distances, creating a form matrix for each individual, composed of these distances. A mean form matrix is then estimated for each group, using an algorithm that creates, in essence, a matrix composed of the average distance between each landmark pair across the entire group (see Lele and Richtsmeier (1991) or (2001) for the full algorithm). To compare form in the two groups, all elements of the mean form matrix for the first group are divided by all of the homologous elements of the mean form matrix for the second group. These compose the estimated form difference matrix (FDM), in which each element represents the ratio of a given linear distance between the two groups. For distances in which the first group is larger, on average, the value of the corresponding element in the FDM will be greater than 1; it is less than 1 if the reverse is true; a ratio of 1 indicates that the estimated mean length of that linear distance is equal in the two groups. Form differences are localized through the estimation of confidence intervals. To establish confidence intervals on each individual ratio of the FDM (i.e., the relationship of each linear distance in the first compared to the second group), a non parametric bootstrapping algorithm is used. This procedure repeatedly resamples the original landmark coordinate data from each group (randomly and with replacement), then re estimates the FDM. When this is performed a large number of times (here, 1,000+ repeats are performed), it is possible to establish a range of values that each ratio could be expected to take for a group of individuals drawn from the same distribution as the actual samples. This range is bounded by confidence limits (here, a 90% confidence interval is used). If the range of ratios included in the confidence interval includes the value 1.0 for a given linear distance, then we cannot reject the null hypothesis of
35 similarity in that distance between the two groups. Thus, we have evidence of similarity (or difference) on a localized, distance by distance basis.
Shape
The purpose of the EDMA Shape procedure (Lele and Cole 1996) is to compare the shape of two samples, once their mean forms have been size standardized by a chosen scaling factor. That is, the Shape function differs from the Form procedure above in that it applies a scaling factor to the linear distance data before comparing the two groups. The user defines a size metric as a scaling factor for the data. There is no single “correct” measure of size in biology, so it is incumbent upon the researcher to choose a metric that is appropriate for the questions at hand, with the knowledge that this choice affects the results of the analysis (Mosimann 1970). In this thesis, the geometric mean of the distances composing the mean form matrix for each group is used as a size surrogate. The geometric mean is a member of the Mosimann family of size variables, and is commonly used in analyses of shape and allometry via distance data (Falsetti et al. 1993; Jungers et al. 1995; Lele and Richtsmeier 2001; Mosimann and James 1979). As before, a mean form matrix is estimated for each group. In the Shape procedure, all elements of the matrix are then divided by the chosen scaling factor, creating an estimated mean shape matrix. The two groups are then compared by calculating a shape difference matrix (SDM), in which each entry is the (arithmetic) difference between like linear distances in each groups’ shape matrix. Thus, a zero in the SDM indicates that the corresponding size standardized average interlandmark distance does not differ between the two groups. Positive values in the SDM indicate distances that are relatively larger in the first group, and negative values denote distances that are relatively smaller in the first group than in the second. Confidence intervals for the distance by distance elements of the SDM are produced in much the same way that the FDM confidence intervals are. Bootstrap samples (parametric, Monte Carlo) are generated from the original landmark coordinate data from each group, then the SDM is re estimated a specified number of times (here, 1,000+ repeats are performed). This establishes a range of values that each shape difference value could be expected to take for a group of individuals drawn from the same distribution as the actual samples, within the specified confidence limits (here, a 90% confidence interval is used). If the range of shape difference values included in the confidence interval includes the value zero for a given linear distance, then we cannot reject the null hypothesis of similarity in that size corrected distance between the two
36 groups. As before, this provides evidence of similarity (or difference) on a localized, distance by distance basis.
Assumptions
Any statistical procedure requires some set of assumptions by the user. Two of the salient assumptions involved in EDMA procedures are enumerated here. First, use of the Monte Carlo approach to creating bootstrap samples (to obtain confidence intervals) in both Form and Shape procedures assumes that the underlying Gaussian perturbation model is correct (Lele and Richtsmeier 2001:212). The nonparametric bootstrap requires fewer assumptions about the underlying perturbation model, but because of the “curse of dimensionality” in this type of data (i.e. the glut of dimensions compared to the number of individuals in the sample), confidence intervals obtained through this type of resampling may not be very reliable, especially with small samples (for n < ~15). The statistical power can be increased in such cases by using “subsets” using fewer landmarks. Second, as mentioned above, the Shape procedure requires the user to define the scaling factor to be applied. If the choice of size metric is not biologically well founded, the results of the procedure will lose their relevance ( ibid :161).
Principal coordinates analysis and allometry
Form and shape within a sample (or between multiple samples pooled together) can be further explored using principal coordinates analysis (Gower 1966). The WinEDMA implementation of principal coordinates analysis (PCOORD) calculates a generalized similarity metric between every possible pair of individuals in the sample, based on either scaled (“shape”) or unscaled (“form”) interlandmark distance data (see Richtsmeier et al. (1998) for details). (In all of the PCOORD analyses reported in this thesis, only scaled interlandmark distances are considered, restricting us to the “shape” case.) These pairwise distances between individuals are collected into a matrix, which is then decomposed into eigenvectors and eigenvalues. This produces principal coordinate axes describing the dimensions that account for the majority of variation among individuals. The proportion of total variation associated with each coordinate axis (based on the eigenvalue of the axis) is reported, as well as the contribution of each linear distance to the loading on that axis. The utility of this procedure is that a lower dimensional representation of the individuals may reveal natural clusters of data, and the separation between these clusters can be traced back
37 to specific morphological traits (i.e., linear distances that correlate most strongly with that axis). Allometry can be explored by calculating the correlation between an axis score of interest (e.g., the first principal coordinate axis, PCO1) for each individual and its size (geometric mean), providing the proportion of variance in axis score attributable to size ( R2). A standard p value of this correlation indicates whether a statistically significant association exists between that axis score and size (see last row of Table 2.5, later in this chapter). Principal Coordinates Analysis is an example of a so called “Q Mode” statistical procedure, in that it concerns the relationship among members of sample. This is in contrast to “R Mode” procedures, such as Principal Component Analysis (PCA; discussed later), which concerns the variation in individual variables.
Reporting EDMA results
To reduce the effects of landmark error, in each chapter’s comparisons all linear distances with an average magnitude of less than 10.0 mm in the group with the smallest cranial size (i.e., Miopithecus ogouensis females in Chapter 3, Simias concolor females in Chapter 4, and Presbytis natunae in Chapter 5) were excluded from the results.
Superimposition methods: Generalized Procrustes Analysis (GPA)
The second approach to landmark analysis in this thesis involves placing individual landmark configurations into a common coordinate system using a fitting criterion. Several computer programs have been developed to implement this group of “superimposition” methods, but in this thesis, the discussion will be restricted to the specific implementation of the software package MorphoJ (Klingenberg 2011). Size of objects in the context of these analyses is known in the geometric morphometrics literature as centroid size : the square root of the sum of the squared distances of all landmarks from the configuration centroid (Bookstein 1991). It is a scaling factor designed to measure the degree of dispersion of landmarks around the centroid. Like the geometric mean calculated from all interlandmark distances, the centroid size will also be dependent on the number of landmarks included. For this reason, the size of objects as defined by the geometric mean or the centroid size is only comparable to the size of other objects with exactly corresponding landmark configurations. Although geometric mean and centroid size are calculated differently, the two
38 measures in a given individual are highly correlated ( r > 0.99) for the landmark configurations used in this thesis.
Generalized Procrustes Analysis (GPA)
Generalized Procrustes Analysis (GPA) involves controlling for the “nuisance” parameters of rotation, translation and scale using a predetermined fitting algorithm. The procedure can be summarized in three basic steps. (1) All individual landmark configurations (that is, all individuals in the sample) are translated so that they share a common centroid—each object’s center of mass is now superimposed onto a single point. (2) Each configuration is scaled to the same centroid size (or close to it; the scaling is actually somewhat more complex—see Full Procrustes Fit in Glossary for details.). (3) The configurations are iteratively rotated until the sum of the squared Euclidean distances between corresponding landmarks has been minimized. The new landmark coordinates of each individual after this translation, rotation, and scaling are known as Procrustes shape coordinates. For 3D landmark data, each individual will thus have 3 k (where k = the number of landmarks) shape coordinates. The average position of each landmark in the sample now composes a consensus configuration, or mean shape, for the sample. Although different in its assumptions and computation, this mean shape configuration is conceptually analogous to the mean shape matrix calculated in EDMA. The Procrustes mean shape requires a coordinate system for its expression (which facilitates visualization), whereas a mean shape matrix is invariant to any coordinate system (which entirely eliminates translation and rotation).
Tangent projection
After GPA is performed, the “shape space” describing the variations in landmark data is actually a multidimensional curved space (Kendall 1984), whereas visualizations and statistical analyses are performed in a standard Euclidean space (Zelditch et al. 2004). For this reason, the registered landmark configurations after GPA are projected into a tangent Euclidean space, which has the same number of dimensions as the original curved space (Rohlf 1998). To do this, the location of the mean shape (defined above) in the curved shape space is chosen as a point of tangency for orthogonal projection (Dryden and Mardia 1998) of all Procrustes coordinates into a Euclidean space. We can think of this as analogous to the projection of small areas of the Earth’s (curved) surface onto 2 dimensional maps (Rohlf 1998). Thus, all Procrustes shape coordinates, including
39 mean shape coordinates, used in all visualizations and statistical analyses (e.g., PCA, multivariate regressions, MANCOVA) are really tangent space coordinates, produced by the orthogonal projection implemented in MorphoJ (Klingenberg 2011). These coordinates are thus estimates of the original Procrustes coordinates from the curved space, but the difference between the two is minimal in most biological data sets (e.g., Lockwood et al. 2004).
Principal Components Analysis (PCA)
In contrast to principal coordinates analysis (PCOORD) performed on interlandmark distance data, principal components analysis (PCA) is the exploratory technique of choice in most superimposition based morphometric studies. First, a covariance matrix (rather than the correlation matrix , often used in other applications of PCA) is generated from the Procrustes coordinates of all individuals in the sample, based on the post superimposition estimate of variance around each landmark (discussed further under Assumptions, below). The PCA performs an eigen structure decomposition on the elements of this matrix, reducing the original 3k variables (i.e., the Procrustes coordinates) to a (usually) smaller number of uncorrelated variables, known as principal components. The principal components (PCs) are typically ordered according to the proportion of variance they explain in the shape variables. In this thesis, the first principal component, referred to as PC1, is the component which explains the largest portion of the variance. After applying PCA, each individual in the sample now has a corresponding “score” along each PC axis.
Mean shape & PC extreme Visualizations
Most superimposition based results reported in this thesis come from interpreting visualizations of various configurations. Cranial shape in different groups (e.g., species, sexes) can be compared by using the group consensus landmark configuration to reconstruct a hypothetical mean shape for that group. The visualizations in this thesis were constructed in the software Amira by taking a surface scan of a “holotype” individual specimen and warping its surface to the mean shape configuration for a given sample. In all such visualizations, the viewer must bear in mind that only landmark points “anchor” the surface warps, whereas the surface in between landmarks is interpolated. By superimposing these hypothetical “mean shapes” for different samples, we see how these shapes differ.
40 Using the shape of the sample mean as a starting point, other hypothetical shapes can be visualized. A common application of this is visualization of the variation in shape associated with a particular principal component. For example, to explore the shape variation captured by the first principal component (PC1), the mean shape coordinates for the sample are modified to represent different points (usually, positive and negative extremes) along that axis. This is accomplished by projecting the PC1 eigenvector onto each Procrustes coordinate by multiplying the eigenvector by a scaling factor (depending on what PC1 “score” is desired), and adding this product to the corresponding Procrustes coordinate value of the mean shape configuration. Figure 2.3, for example, illustrates the hypothetical shapes associated with positive and negative extreme positions along PC1 from a PCA of the complete sample of Presbytis individuals considered in Chapter 5.
Figure 2.3. Interspecific PC1 extreme shapes in Presbytis . (Copy of Figure 5.19.) The shape associated with the extreme negative end of PC1 (score of 0.06) is represented in light violet. The dark violet shape represents the positive extreme of PC1 (score of 0.04). Reconstructions made using the female P. melalophos surface scan (courtesy Prof. E. Delson).
Allometry: the relationship between shape and size
In this study, the quantitative relationship between shape and size, as determined via regression of Procrustes coordinates onto size, are reported in tables such as Table 2.5, reproduced below from Chapter 4. The results presented in these tables are produced as follows. For the first row, a multivariate regression is performed in MorphoJ using all Procrustes coordinates for all individuals in the sample as the response (= dependent) variables, against CS as the single predictor (= independent) variable. In aggregate, all Procrustes coordinates account for 100% of the total shape variation in the sample (Table 2.5, first numeric entry). The next column reports
41 the proportion of total variance in Procrustes coordinates which is attributable to variation in size. Statistically, this is the “explained variance”—the proportion of total shape variance predicted by size in the regression. It is important to note here that in all regressions where the proportion of variance “explained by,” “predicted by,” or “attributable to” size is reported, this is a statistical statement and not a biological one. As in any such study, correlation does not imply causation, and we cannot say that changes in size cause changes in shape (or the converse), only that they are statistically associated. The next column of the table reports the p value from a permutation test in MorphoJ. This permutation test performs 10,000 random assignments of sizes to individual shapes, to assess the probability of obtaining an equivalently strong shape size association by chance. A large p value indicates that we cannot reject the null hypothesis that size and shape are independent.
Table 2.5. Evidence for cranial allometry in Simias concolor males. This is a copy of Table 4.3. See text for explanation. Shape component Proportion of total Proportion of variance Associated p-value variance explained in component against null hypothesis by component explained by size of no allometry
All Procrustes coordinates 100% 22.3% 0.0090* PC1 of Procrustes PCA 31.4% 61.7% 0.0076* PCO1 of EDMA PCOORD 33.1% 43.3% 0.0387* Analysis * Significant at the p < 0.05 level.
The next two rows of the table report the results of simple linear regressions testing the association of a principal component (PC) or principal coordinate (PCO) score with size in the sample. In these cases, the first numeric entry reports the eigenvalue of the given principal axis as a proportion of the sum of all eigenvalues. The next column reports the proportion of variance in the PC or PCO score that is “explained by” size—this is the R2 value or square of the correlation coefficient ( r) of the bivariate regression. This is followed in the right most column by the p value associated with the regression. Again, a high p value indicates that we cannot reject the null hypothesis that the shape component (here, PC or PCO score) is independent of size in the sample.
42 Predicted shapes: Large and small extremes
Results such as those in Table 2.5 present statistical evidence of association between cranial shape and size in a sample. In many of the samples examined in this thesis, this association— a.k.a., cranial allometry—is weak. As a primary aim of this thesis is to characterize the relationship between size and shape in different primates, visualizations are used to explore cranial allometry, even when it is subtle. The major criterion for including species in this study is that they differ in size, and so it is critical to identify how shapes differ with respect to those size differences. To visualize the differences in shape associated with cranial size variation within each sample, large and small predicted shapes were created. This was accomplished in the following way. First, multivariate regression of all Procrustes coordinates on CS was performed in MorphoJ, as described in the previous section. Predicted shape coordinates for any given size can be computed by solving the multidimensional regression equation. That is, although all actual specimens will deviate to a greater or lesser extent from this “best fit” equation, we can find the expected shape (as Procrustes coordinates) for any CS within the sample range. This enables us to focus on those components of shape which are statistically correlated with size in the sample, ignoring all the other shape variation that exists. The stronger the relationship between size and shape in the sample, the more meaningful such predicted shapes are. Of course, if the association between size and shape is not statistically significant, any differences between large and small predicted shapes are only tentative and could be artifacts of the data set. Even with relatively weak cranial allometry, however, this technique allows us to visualize how larger individuals tend to differ from smaller ones in the sample. This is visualized in a similar fashion to the hypothetical PC extreme shapes described above. The regression coefficient calculated between each Procrustes coordinate and CS is multiplied by a scaling factor (how large or small the desired CS relative to the mean) and then added to the mean shape coordinate, producing a predicted value for that coordinate. Here, one predicted shape is calculated at the CS corresponding to the largest cranium in the sample and another is calculated for the smallest cranium. These predicted Procrustes coordinates are imported into Amira to create a surface warp of the sample mean shape for both the large and small predictions. The two predicted surfaces (in contrasting colors) are then superimposed to facilitate visual comparison.
43 Hypothetical shape-size extrapolation
Just as the multivariate regression of Procrustes coordinates on CS can be used to predict the shape of actual specimens (i.e., at centroid sizes which exist in the sample), hypothetical shapes can also be predicted outside the normal size range of a sample (Baab and McNulty 2009; McNulty et al. 2006). As with any regression, extrapolation of the regression line beyond the range of the actual data is of limited statistical value. Here, I use this extrapolation in some instances as another tool for qualitative visualization of allometric trends. It permits us to hypothesize the cranial shape of a given species at the size of a smaller or larger relative, given the static allometry of that species.
Assumptions/Limitations
It must be kept in mind that the act of placing objects in a coordinate system means that we cannot know the “true” variance local to any given landmark. The superimposition algorithm distributes variance around all landmarks in order to minimize the summed squared distances between corresponding landmarks across the configuration. Thus, the precise distribution of variance around each landmark ultimately depends on the criteria used to superimpose the configurations. When we consider (co)variance in this context, we rely on the assumption that the biological (morphological) variability in the sample concentrates more around some landmarks than others, to the extent that this differential variability is detectable even after the superimposition attempts to equalize it. Following from this issue, the conclusions we draw about shape after superimposition depend on which landmarks are included in the analysis, because there is no absolute variance associated with a given landmark. A related issue in interpreting shape comparisons using GPA is that localized shape differences are only “suggestive” in some sense, because there is no test of statistical significance associated with local differences between landmark configurations. This is in contrast to EDMA results, where each interlandmark distance is associated with a confidence interval to indicate the magnitude and statistical significance of localized differences between samples. On the other hand, GPA does produce quantifiable distances between configurations in shape space. Pairwise distances (Procrustes distances, Mahalanobis distances) between individual specimen configurations or between mean shape configurations can be readily calculated and compared.
44 Testing for similarity in static allometry
It is challenging to answer the question of whether two groups share a common relationship between cranial size and shape. To help clarify this subject, I employ specific operational definitions for allometric relationships within and between groups. Note that in the following discussion, and throughout this dissertation, linear regression refers to standard least squares regression, either bivariate or multivariate. Static allometry refers to the relationship between shape and size among individuals of a species at the same age or developmental stage. In this thesis, the term static allometry always refers to adult individuals. I divide the concept of static allometry into two subtypes for the analyses presented. With no specific qualifier, the term refers to all adults of a species, with males and females pooled into a single group. When referring to the allometry within adult females only, I specify female static allometry, and male static allometry for adult males only. The trajectory of static allometry refers to the best fit linear regression between one or more shape variables and a size variable (either CS or geometric mean) within either a single sex or pooled sex group. Thus, in the case where a single shape variable (such as a PC or PCO score) is compared to cranial size, the allometric trajectory is easily visualized with a simple two dimensional plot. When multiple shape variables (such as all Procrustes coordinates or multiple PC scores) are regressed against cranial size, the resulting allometric trajectory is a multidimensional vector field that cannot be easily represented in a two dimensional figure. When static allometries are compared between two groups, their trajectories may be either divergent (i.e., their slopes are significantly different) or parallel (Figure 2.4a c). Divergent allometries mean that size and shape do not have the same relationship in one group as in the other (Figure 2.4a). Parallel allometries imply that shape is related to size in the same way in the two groups. If two allometric trajectories are parallel, they may either be coincident or not. If they are coincident, not only do the groups share similar (parallel) size shape relationships, but their trajectories are collinear —the two groups fall along a common path in size shape space (Figure 2.4c). If the trajectories are parallel but not coincident, they have different “starting” shapes, such that even at the same size, the shape predicted by the regression model is different for each group: the trajectories have the same slope but different intercepts, or elevations (Figure 2.4b). This general phenomenon is sometimes called “transpositional allometry” or “grade shifting” (e.g., Gould 1971; Martin 1990; Steudel 1982).
45
Figure 2.4. Alternative hypotheses for the relationship between allometric trajectories: Divergent, Parallel, and Coincident. Plots depict the static allometry within two groups of individuals, red and blue, with shape represented as a 1 dimensional variable for simplicity. (a.) The static allometries of the red and blue groups have different slopes and are thus divergent . (b.) The two static allometries have equal slopes—they are parallel —but have different intercepts on the shape axis. Although size X 1 falls within range of both groups, the shape predicted for a red individual at size X1 is different than that for a blue individual. (c.) Red and blue static allometries overlap, so the groups can be said to share a common or coincident static allometry.
To determine which of these three models best fits the cranial shape data, I use the multivariate analysis of covariance (MANCOVA) (or its univariate counterpart, the ANCOVA) in a two step procedure. This test allows us, first, to determine whether the size shape relationship in two groups is (not significantly different from) parallel, and if so, to partition shape variation into distinct size related and group related components (Rosas and Bastir 2002). Group membership (i.e., species or sex) is the categorical covariate (a.k.a. “factor”) in the analysis, the continuous predictor variable is size (CS), and the multiple response variables are shape variables (PC scores from a pooled group PCA of Procrustes coordinates). PC scores, as opposed to raw Procrustes coordinates, are used in the MANCOVA test to reduce the number of variables needed to capture significant portions of shape variance in the sample. In the first step, this is formalized as a “full factorial model,” which includes a constant offset term, c:
shape = c +α × group+ β × size+γ × group× size
This step determines whether the interaction between group membership and size (the “interaction term,” group×size) has a significant effect on shape in the linear model. If the (group×size) coefficient ( γ) is statistically significant, this indicates that the association between shape and size is not parallel in the two species—their static allometries are divergent . If the interaction term is not significant, then we do not have evidence that group membership changes the way shape and size are associated. That is, we cannot reject the null hypothesis that the
46 groups have parallel static allometries. If the null hypothesis of parallel slopes is not rejected in the first step, we continue to the second step, now dropping the interaction term from the model. The MANCOVA is repeated with the simplified model:
shape = c +α × group+ β × size
This step partitions shape variation into a portion attributable to the group factor ( α) and another attributable to size ( β). If the group coefficient, α, is significant, this indicates that the position of the two allometric trajectories in space is not the same, although their slopes do not differ significantly. Thus, they are not coincident. Alternatively, if the group coefficient is not significant, then group membership does not change the shape predicted by the model at a given size. In other words, the groups can be said to fall along a common or coincident allometric trajectory.
Reporting of MANCOVA results
Each MANCOVA was repeated multiple times using different proportions of the total shape variance—that is, using PCs 1 through m, where m varies from 1 to n 1, the total number of PCs. This repetition ensured that the significance of the test was consistent. If the significance changed with the proportion of total shape variance considered, this is reported in the results. For each test, I report the number of PCs included, the F statistic, the degrees of freedom (effect df, error df), and p value. The number of PCs required to account for 95% of shape variance was the default for reporting. For example, the results of the first step of a MANCOVA testing male and female static allometries for divergent slopes might be (PCs 1 29, F=1.49; df=29,13; p=0.225). As this is step 1, the results pertain to the coefficient of the interaction term group×size, γ. Unless stated otherwise, this indicates that 95% of shape variance is accounted for by including scores from the first 29 PCs; the F statistic is 1.49, the effect degrees of freedom is 29, the error degrees of freedom is 13, and the p value is not significant (≥ 0.05), indicating that the slopes are not significantly different from parallel.
Limitations of MANCOVA testing
Importantly, multivariate shape can only be tested using this method by pooling individuals from both groups into a single PCA (otherwise their PC scores would not be comparable). This means that the shape variables under consideration are defined by the principal axes of shape variation
47 of the pooled sample, which may not reflect the axes of greatest variation within each sample independently. Secondly, it is an undesirable feature of the MANCOVA that if the investigator’s objective is to test hypotheses about parallel allometry, the null hypothesis of the test is that the trajectories are parallel. This means that the MANCOVA never provides evidence of parallelism, strictly speaking, but only a lack of evidence of divergence. If the null hypothesis is not rejected, it could be that the test was merely indeterminate. If there are insufficient data to reliably determine the allometric slopes, the test will not be able to reject the null hypothesis. This limitation stems from the same issues that plague any evaluation of allometry. The weaker the association between size and shape within a sample, the less meaningful any comparisons of that trajectory become, due to lack of statistical power. The same issue arises in a simple bivariate regression between any two metrics. If the relationship is strong, the various types of regression techniques (e.g., least squares, major axis, reduced major axis) will return similar results. The weaker the relationship, the more the results of different regression methods will vary (Lande 1985; Steudel 1982). If one were to use all Procrustes coordinates in the MANCOVA so as to avoid the potential biases of a pooled PCA, the issue of statistical power is only exacerbated, because the number of shape variables is now three times the number of (3D) landmarks being used.
Qualitative evaluation of allometry
To complement the information provided by MANCOVA testing, static allometry is also qualitatively assessed by comparing the large and small “extreme” predicted shapes (described earlier) between groups. This simply involves comparing the large and small superimposed predictions for one group (species or sex) with the analogous predicted shapes for the other group. By comparing and contrasting the types of shape features associated with size in the two samples, we can infer how their static allometries may be similar (or different).
Evolutionary allometry
As discussed in Chapter 1, evolutionary allometry is difficult to define. In this thesis, evolutionary allometry is discussed in two ways, one strictly delineated, and one more informal and intuitive. The often discussed issue of whether two species share a “common” static allometry, or “parallel” allometric trajectories is a natural extension of static allometry into an interspecific, and therefore evolutionary, context (Cock 1966). Here these concepts are
48 operationalized as discussed in the static allometry section above, by determining whether the static allometry of two species is divergent, parallel, or coincident. The second approach to evolutionary allometry in the following chapters is a comparative one, based on quantitative measures, but lacking in strict statistical definitions. This approach includes the comparison of RBS and EQ values between species, as well as the qualitative interpretations of (quantitatively derived) shape visualizations.
Analysis: Non-Landmark Data
Dimensionality
The issue of data dimensionality is a persistent one in studies of allometry. In this study, it is often the case that the unit of one quantity of interest is a mass or volume (e.g., grams or milliliters), while another is a linear dimension (e.g., millimeters). How we deal with this discrepancy depends on the type of quantitative comparison being employed. Ratios are dimensionless values, and as such, their components must be of comparable units in order to produce a meaningful ratio value. Thus, when ECV (in cubed linear units) is compared to a linear dimension such as CS via a ratio, the cube root of ECV is used to create an artificial one dimensional proxy for volume. Similarly, correlation values are unitless and are intended to capture linear relationships, so ECV is also reduced to one dimension for calculating correlations with one dimensional metrics.
Correlations
Variables were tested for normality using a Shapiro Wilk test. If the variables in question are normally distributed, then a Pearson’s product moment correlation was computed. If one or both variables fail the Shapiro Wilk test, then two rank correlation methods—Spearman’s and Kendall’s tests—were performed. All of these analyses were performed using the statistical computing language R.
Ratios
Several authors (Albrecht et al. 1993; 1995; Jasieński and Bazzaz 1999) have pointed out potential pitfalls in using ratios of biological variables for morphometric comparisons. Indeed,
49 ratios have some undesirable statistical properties (Atchley et al. 1976): they typically do not have normal distributions and can have infinite variance if the denominator takes values near zero. Tests on two variables expressed as a ratio also have reduced statistical power compared to testing the variables directly, meaning that lower variance and/or larger sample sizes are required to achieve a given confidence level (Jasieński and Bazzaz 1999). Albrecht et al. (1993) warn in particular that variables that are “size corrected” by dividing by a size measure (and are thus ratios) are not necessarily uncorrelated with size (“size free,” in their terminology). However, this is simply equivalent to the observation that when isometric scaling effects are removed by dividing by a scalar, any allometric effects on variables remain intact. In a study designed to identify and examine these allometric effects, then, use of ratios remains a convenient and effective way to remove isometric scaling from variables. This is how ratios of multiple variables are used in this thesis and, indeed, the basis of how size correction is performed in both superimposition and distance based shape analysis. Like other raw variables, the ratios examined and compared in this thesis (e.g., OD/CS, CBL/HBL, etc.) have been tested for normality of distribution. Non parametric tests are employed when the normality criterion is not met. All ratios of metric values used here are biological measurements which are not near zero (essentially eliminating the infinite variance issue). Finally, ratios are used in concert with other data exploration techniques (e.g., correlations), representing just one of the angles from which the relationship between variables is evaluated.
Encephalization
The term encephalization generally refers to the size of the brain relative to the size of the body (or some part of the body). Brain size is variably defined by mass or volume by different researchers, and is evaluated here using multiple approaches. A limitation of using ECV for these analyses is that ECV is not precisely equal to brain mass, and cranial capacity and brain mass do not necessarily scale isometrically (Palombo 2007; Röhrs and Ebinger 2001). However, given the degree of error involved in the measurement of endocranial volume, the relatively small body size of the species considered, and the fact that brain tissue has a specific gravity close to that of water (1.036 g/cm 3, (Ebinger 1974; cited in Köhler and Moyà Solà 2004)), I follow other authors (e.g., Eisenberg and Wilson 1981; Gingerich and Gunnell 2005; Isler et al. 2008) in using
50 endocranial volume (in cm 3 = mL) interchangeably with brain mass (in g) for the purposes of calculating encephalization. (For further discussion of this issue, see Isler et al. 2008.)
Brain size relative to cranial size
This is quantified with the ratio of cube root ECV to CS. Rather than using a 1 dimensional proxy for volume of the entire cranium (such as CS or geometric mean), a potentially preferable method would avoid the discrepancy in dimensionality by calculating a 3D volume directly from the cranial landmark configuration. Ratios of volume to volume could then be compared without conversion between 1 and 3 dimensional quantities. For example, Weston and Lister (2009) estimated cranial volume in hippos as a cuboid (rectangular box) with sides corresponding to length, height and width measures of the cranium. Because CS is a measure of dispersion of landmarks around their centroid, it implicitly models cranial volume as proportional to a sphere, which seems reasonable for globular primate crania. A better volumetric approximation might result from more sophisticated estimation of the polyhedron associated with the landmark configuration. Choosing the most appropriate model from among possible polyhedra is beyond the scope of this thesis, however. Such a model would need to be both computationally feasible and also biologically relevant. This could be a fruitful area for future research.
Brain size relative to orbit size
In this thesis, brain to orbit size is also calculated with a simple ratio by dividing cube root ECV by OD (orbital diameter). Again, a ratio using the actual volume or mass of the globes of the eyes would yield a more accurate size comparison of these organs. Several allometric studies (Kay and Cartmill 1977; Ravosa 1991a; Schultz 1940; Todd et al. 1940) suggest that the volume of the bony orbits themselves depends more on overall facial size (or depth) than on the volume of the soft tissue globes. For this reason, calculation of orbital volume was not attempted.
Brain size relative to head and body length
This quantity is another ratio composed of cube root ECV divided by a linear dimension, HBL. Ideally, HBL would be converted to a body mass estimate based on empirical regression equations for the species and sex under consideration (assuming that the actual body mass was not available, of course). Then RBS and EQ could be calculated (as below). For most of the species in this thesis, such empirical data were not available, however. In most samples, there
51 were so few specimens with both HBL and body mass data available that I did not feel regression equations derived from them would offer a significant improvement in estimating body size over the raw HBL measure itself.
Brain size relative to body mass (RBS; no allometric correction)
When mass data were available, relative brain size (RBS) was calculated as ECV (as an approximation to brain mass) divided by mass (in g).
Actual vs. expected brain size: Encephalization Quotient (EQ)
Encephalization Quotient (EQ) is defined as the ratio of observed brain mass to the expected brain mass for a given body mass (Eisenberg 1981; Jerison 1973). In this thesis, I report EQ calculated using Eisenberg’s (1981) equation, which is based on brain and body weight data across mammalia (Eisenberg 1981; Eisenberg and Wilson 1978; 1981):
brain mass in g 0.055 body mass in g .
The interpretation of EQ is “how big is the brain compared to a ‘typical mammal’ of the same body mass?” In this definition, “typical mammal” is determined by the species data used in Eisenberg’s studies. Jerison’s (1973) formula, which is less influenced by small bodied mammals, would result in slightly lower EQ values for the primate species considered here.
Other approaches to encephalization
Comparative encephalization is also assessed in some cases by considering absolute brain volume in other primates of similar body mass. This “narrow allometry” approach (Smith 1980) eliminates the need to correct for body size by simply examining other animals of similar size.
Chapter 3
A “classic” primate dwarf: the talapoin monkey
The first of the three interspecific primate comparisons in this thesis considers the talapoin monkey or dwarf guenon, Miopithecus ogouensis . The talapoin has been recognized as a dwarfed lineage and studied by researchers in that context for many decades. It is compared to another arboreal guenon of much larger body size, the greater putty nosed monkey, Cercopithecus nictitans .
Species background
Taxonomy
Although traditionally referred to a single taxon, Miopithecus talapoin Schreber 1774, the two populations of talapoin monkey in west Africa are now recognized as distinct species with non overlapping ranges (Figure 3.1). The distinction between northern and southern populations was first suggested in print by Machado (1969), and formalized by Kingdon (1997). Besides differences in behavior and morphology, mitochondrial ribosomal RNA sequencing (van der Kuyl et al. 2000) also supports a species level separation between the northern or Gabon talapoin, Miopithecus ogouensis , and the southern variant, Miopithecus talapoin . The species considered in this study is the better known variant, and the one more widely represented in museum collections: the northern talapoin, Miopithecus ogouensis (Kingdon 1997). Here, I refer to it using this species name interchangeably with the common name, the talapoin monkey.
Geographic range
The northern talapoin is a strictly equatorial, riverine species found from Cabinda (disputed northern enclave of Angola) in the south to north of the River Sanaga in Cameroon (Figure 3.1) (Kingdon 1997; Maisels et al. 2006). The River Ogooué (Gabon) is the center of its distribution, and it is never found more than 500 m from a waterway (Kingdon 1997).
53 The geographic range of Cercopithecus nictitans begins north of the River Congo, including all of the range of M. ogouensis , and extending west to Nigeria. There also exist sparsely distributed populations continuing west all the way to Liberia (Kingdon 1997).
Biogeography
Miopithecus ogouensis lives in the dense undergrowth of riverbanks. Kingdon (1997) postulates that the eastern extent of its geographic range is restricted by the presence of its relative, Allenopithecus , which has similar habits. There is at least some degree of sympatry between the northern talapoin and other arboreal guenons—Cercopithecus nictitans , C. cephus , C. pogonias , and C. neglectus—in Gabon (Gautier Hion and Gautier 1985). This overlap in habitat between the talapoin and C. nictitans is appealing for this comparison of cranial morphology and body size, as it offers some degree of constancy of potentially confounding ecological variables. Cercopithecus nictitans is a member of the C. mitis or “gentle monkeys” superspecies (also occasionally called C. nictitans superspecies), which also includes C. albogularis . These species inhabit tropical forest, although Kingdon (1997) argues that they are largely limited to “periphery” forest areas. Generalists in feeding habits, these monkeys may be outcompeted by more specialized primates in the most productive forests and thus forced to marginal areas. Their persistence across a large portion of Africa is probably due in part to two significant adaptations: the ability to live at a wide range of altitudes, and the ability to survive long fruitless periods by relying on fallback foods such as insects and foliage (Kingdon 1997). Sympatry of Cercopithecus nictitans with C. pogonias and C. cephus at sites in Gabon is well documented (Gautier Hion 1980; Tutin et al. 1997). Furthermore, Tutin (1999) records an instance of a polyspecific (multiple species) C. cephus C.nictitans troop, as well as a hybrid individual.
54
Figure 3.1. Approximate geographic distribution of Cercopithecus nictitans and the two talapoin species. Based on Kingdon (1997).
Diet
In northern Gabon, the talapoin’s diet is nearly 80% fruits. It is known to forage terrestrially, and consumes invertebrates opportunist ically. Talapoins also take advantage of human cultivation near rivers for foraging fruits and vegetables (Kingdon 1997). As mentioned above, C. nictitans can subsist on foliage and insects when necessary, although fruits are its preferred food source. Its diet also includes some seeds and flowers (Kingdon 1997).
Sociality & Reproduction
Like the papionins, but unlike any other species in the guenon clade, Miopithecus and Allenopithecus exhibit female sexual swellings. Male and females both reach sexual maturity around four years of age (Enstam and Isbell 2007; Gautier Hion and Gautier 1976) . Like most other guenons, including C. nictitans , talapoins give birth seasonally (Enstam and Isbell 2007; Kingdon 1997). There is a larger gap in age at sexual mat urity between male and female Cercopithecus nictitans, with females maturing at around four years, and males at five or six years of age (Gautier Hion and Gautier 1976). Talapoins live in multimale/multifemale groups (during breeding season), while C. nictitans exhibits the more typical guenon social system of the single male/multifemale group (Enstam and Isbell 2007).
55 Predation
The talapoin depends on dense evergreen cover, presumably because its small size makes it vulnerable to predation from carnivores, snakes, and birds of prey (Kingdon 1997). It will dive and swim if disturbed in vegetation overhanging a waterway (Kingdon 1997). Crowned eagles are known to prey upon Cercopithecus nictitans , and other potential predators include the python, golden cat, and leopard (Gautier Hion et al. 1983).
Anatomy
Miopithecus is the smallest of the Old World monkey genera, and M. ogouensis is the smaller of the two talapoin species (Kingdon 1997). Adult male body mass is typically around 1.4 kg; 1.1 kg for females (Gautier Hion and Gautier 1976). In his volume on comparative cranial morphology of the guenons, Verheyen (1962:109) concluded that the talapoin is the “most aberrant and mos t specialized of the genus sensu lato ,” noting especially its juvenile characters. The (adult) talapoin cranium is strikingly paedomorphic in appearance, with large orbits and a bulbous neurocranium, a small, gracile face, and persistently visible cranial sutures. In his craniometric comparisons of the guenons, Verheyen concluded that the talapoin is cranially most similar to Cercopithecus ascanius and C. mona , which are also the two smallest species he examined, after the talapoin. “It is evident without any doubt that allometric growth has strongly influenced these facts” (Verheyen 1962:111). Many subsequent studies have recognized the talapoin as a neotenous or dwarfed lineage (e.g., Napier and Napier 1967; Strasser and Delson 1987). Cercopithecus nictitans is one of the larger guenons in terms of cranial size (Verheyen 1962) and body mass, with a species mean of over 5 kg (Smith and Jungers 1997). It is almost exclusively arboreal in behavior, and primarily moves quadrupedally in the trees (McGraw 2002).
Phylogeny
Phylogeny, as well as taxonomy, within the guenons (tribe Cercopithecini) is still a subject of debate (Butynski 2002; Grubb et al. 2003). Part of the issue stems from conflicting phylogenetic relationships obtained from different types of molecular data (X and Y chromosome, Alu insertions, karyotypes, protein sequences) (Xing et al. 2007). It has long been thought that Allenopithecus and Miopithecus represent the most basal lineages of the tribe (Figure 3.2), which is consistent with evidence from behavioral, morphological, and genetic data (Groves 2001).
56 Mounting molecular evidence supports a terrestrial clade, including the Cercopithecus lhoesti species group, Chlorocebus (formerly Cercopithecus ) aethiops , and Erythrocebus patas (Moulin et al. 2008; Tosi et al. 2005; Tosi et al. 2004; Xing et al. 2007). The most recent published study using Alu insertions differs in that there is statistically significant support for Miopithecus grouping with the other “arboreal guenons,” to the exclusion of the terrestrial clade (Xing et al. 2007).
Figure 3.2. Hypothesized phylogeny of the guenons (tribe Cercopithecini). Divergence dates in millions of years (Ma), based on X chromosome data. Molecular clock calibrated by fossil estimate of Theropithecus/Lophocebus/Papio last common ancestor at 4 Ma (star). Based on Tosi et al. (2005) (X chromosome data), and Xing et al. (2007) (Alu insertion polymorphisms). *Two possible branching positions of Miopithecus are shown, as well as the uncertain position of the C. diana species group (dotted lines).
The choice to use Cercopithecus nictitans as a comparative taxon for Miopithecus was thus an arbitrary one, based primarily on the availability of museum specimens. Allenopithecus nigroviridis may well represent the closest extant approximation to the last common ancestor of the talapoin with the rest of the guenons, but Allenopithecus specimens are scarce. Based on ecology (and, perhaps, genetics, see above), any of the arboreal Cercopithecus taxa seem equivalently appropriate as a comparative species for Miopithecus .
57 Fossil record
Fossil material that can be confidently attributed to tribe Cercopithecini is scarce. The oldest Cecopithecus specimens are jaw fragments from the Omo Basin, Ethiopia dated at 2.9 Ma (Eck and Howell 1972; Jablonski 2002). A single Miopithecus sized mandible is known from Koobi Fora at 2.6 Ma (Leakey 1988).
Hypotheses, approaches of this study
A broad picture of cranial variation—including allometry and sexual dimorphism—across the guenons has recently been published by Cardini and Elton (2008a; 2008b). The present study has a different focus, however. Its primary aims are (1) to further examine cranial form in the particular case of Miopithecus as a dwarfed lineage by comparing it to a larger guenon taxon, (2) to address relative encephalization in the talapoin, about which there is a substantial literature, and (3) to establish a baseline expectation for the size related changes in cranial shape that correspond to an evolutionary reduction in body size. The first aim is achieved via cranial morphometric analysis, using landmark data, caliper measures, and volume estimates to characterize adult cranial form and allometry within the species Miopithecus ogouensis and between M. ogouensis and a large bodied arboreal guenon, Cercopithecus nictitans . In so doing I also validate the conclusions of Cardini & Elton (2008a; 2008b) regarding cranial allometry and morphology in these two species, using an independent dataset and differing methodologies. The second aim is addressed both indirectly via shape analysis and more directly by comparing endocranial volume (ECV) in the talapoin to C. nictitans and other anthropoid primates. Lastly, the third aim follows naturally from the results of the first two. Because the talapoin has thriving wild and captive populations as well as an array of extant (“non dwarf”) relatives, its comparative morphology is well studied. This has made it a canonical example of body size reduction in primates. In contrast, Chapters 4 and 5 examine two less common and rarely studied monkeys. The findings of this chapter establish expectations for dwarfing using the same methodology as is used throughout this thesis, providing null hypotheses for cranial shape differences in smaller primates compared to close relatives of larger body mass.
58 The null hypotheses of the present chapter’s study are drawn from the findings of previous work on Miopithecus and Cercopithecus cranial morphology. It is well documented that the talapoin cranium is characterized by a relatively short face, large orbits, and large neurocranium. I test the following hypotheses: 1. Within each of the two guenon species examined, the trajectory of male cranial static allometry is coincident with that of female static allometry. This hypothesis is drawn from Cardini & Elton’s conclusion that “[w]ithin species, sexual dimorphism in skull shape follows the direction of size related shape variation of adults…” (2008b:638). 2. The cranial static allometry of M. ogouensis is parallel to that of C. nictitans (or nearly so). This stems from Cardini & Elton’s (2008b) finding that the static allometric trajectories of most guenon species are “nearly parallel.” 3. Sexual dimorphism in cranial shape and size is less pronounced in the dwarf species, M. ogouensis , than in the larger species, C. nictitans . This is predicted by Rensch’s rule (Smith and Cheverud 2002), but was not supported for this particular pair of species by the results of Cardini & Elton (2008b). 4. The relative size of the neurocranium of M. ogouensis is not only large for its skull, but large for its overall body size when compared to other primates. This finding has been published multiple times (e.g., Bauchot and Stephan 1969; Holloway and Post 1982), but was recently contradicted by the results of Isler et al. (2008).
Finally, I interpret the results of this chapter’s analyses in light of Shea’s (1992:305) conclusion that “…the paedomorphic morphology of talapoins as compared to their larger relatives results from the heterochronic process of rate hypomorphosis…” Although the data collected for this thesis do not allow testing of this hypothesis directly (because only adults are considered), I evaluate whether or not the results of the present study are consistent with Shea’s hypothesis.
Analysis of cranial morphology in the talapoin monkey compared to Cercopithecus nictitans
This study begins by examining static allometry within females, then males, of M. ogouensis , followed by a treatment of allometry and sexual dimorphism. Next, females and males of C.
59 nictitans are likewise evaluated. Shape and allometry are then compared between females of the two species, followed by males of the species. Finally, cranial allometry and encephalization in the species are considered in the context of other anthropoid primates.
Static allometry in Miopithecus ogouensis females
Within female talapoins, a statistically significant proportion (just below 10%) of variation in cranial shape is correlated with cranial size (Table 3.1).
Table 3.1. Evidence of cranial allometry in Miopithecus ogouensis females (n=22).
Proportion of total Proportion of variance Associated p-value Shape component variance explained in component against null hypothesis by component explained by size of no allometry All Procrustes coordinates 100% 9.50% 0.002* PC1 of Procrustes PCA 16.4% 36.9% 0.003* PCO1 of EDMA PCOORD 17.8% 48.6% <0.001* Analysis * Significant at the p < 0.05 level.
The first principal axis of shape variation is strongly size related, both when defined through a PCA of Procrustes superimposed coordinates and through a PCOORD of scaled interlandmark distances (920 distances in total, after removing those < 10.0 mm). Figure 3.3 illustrates the relationship between cranial size and PCO1 score from a PCOORD analysis. Higher PCO1 scores (associated with larger cranial size) are correlated with relatively longer distances between ZMS and other facial landmarks (especially IDS, PMMX, nasale, opposite ZMS), indicating a relatively larger maxillary region (landmarks defined in Table 2.3, Figure 2.1). Lower PCO1 scores—associated with smaller individuals—are correlated with relatively longer distances from asterion to other cranial base landmarks, in particular, PET, TSCR, BOS, and CAR.
60
1
0.5
0 R² = 0.486 -0.5
PCO1 PCO1 score -1
-1.5
-2 22 22.5 23 23.5 24 24.5 25 25.5 Geometric Mean
Figure 3.3. Static allometry in female talapoins. First principal coordinate axis (PCO1) score in Miopithecus ogouensis females (n=22), plotted against cranial size (as geometric mean of all possible interlandmark distances).
An alternative way of investigating the shape differences associated with cranial size is through predicted landmark configurations for the largest and smallest individuals in the sample (Figure 3.4). Smaller females have a relatively foreshortened maxilla/lower face (in accordance with PCO1 indications, above). Relative inflation of the neurocranium in smaller individuals is also evident. Larger individuals have relatively short nasal bones (a more superior position of nasale on the face) and a relatively deep palate. The relative breadth of the zygomatic arches is also greater in larger females.
61
Figure 3.4. Visualization of predicted shapes for largest (red) and smallest (yellow) talapoin females. Predicted landmark locations are derived from the multivariate regression of all Procrustes coordinates on centroid size. The landmarks used to perform the warping of a “holotype” surface scan to each predicted shape are shown in green for the yellow (small) shape, in purple for the red (large) shape. In all such visualizations, the viewer must bear in mind that only landmark points “anchor” the surface warps, whereas the surface in between landmarks is interpolated. For example, in the above representation, the “true” relationship between the yellow and red shapes just posterior to opisthion on the occiput cannot be known from the data collected, because there is no landmark in that location. All surface reconstructions of M. ogouensis in this chapter are based on a micro CT scan of a male specimen from the collection of Prof. R. Kay.
Centroid size (CS) of the cranium is significantly correlated with brain size (as cube root ECV) and with orbit size (OD) in this sample (Table 3.2). As in all the samples considered in this thesis, there is a strong correlation between CS and condylobasal length (CBL). Head and body length (HBL) is also correlated with CS in the talapoin females.
Table 3.2. Correlation between components of the cranium and body in female M. ogouensis . For correlations with r < 0.2 or p > 0.2, table entry is “not significant” (n.s.). cbrt(ECV) = cube root ECV.
cbrt( ECV ) OD CS CBL OD n.s. - - - CS r= 0.599*, r=0.483*, - - p=0.003 p=0.023 CBL n.s. n.s. r=0.859 *, - p<0.001 HBL n.s. n.s. ρ=0.568†, τ=0.224‡, p=0.017 p=0.183 * Denotes that correlation value is significant at the p < 0.05 level. † Standard r value and Kendall’s rank correlation τ are also significant. ‡ Similar result for Spearman’s rank correlation ρ.
62 Static allometry in Miopithecus ogouensis males
In contrast to females, there is little static allometry in the crania of adult talapoin males (Table 3.3). At least with this sample size, there is no statistically significant association between shape and CS among the males. For this reason, large and small extreme shape visualizations were not created.
Table 3.3. Evidence of cranial allometry in fully adult Miopithecus ogouensis males. Sample of 16 individuals; subadults not included (see text below).
Proportion of total Proportion of variance Associated p-value Shape component variance explained in component against null hypothesis by component explained by size of no allometry All Procrustes coordin ates 100% 4.94% 0.883 PC1 of Procrustes PCA 18.8% 5.56% 0.384 PCO1 of EDMA PCOORD 15.9% 0.710% 0.756 Analysis
We can gain insight into the terminal end of the male talapoin growth trajectory (ontogenetic allometry) by considering two subadult males—both with M3s in place but upper canines not fully descended. It is clear from their shape and size that these two individuals are not fully grown adults (Figure 3.5), but they add relevant information about the relationship between ontogenetic allometry and sexual dimorphism in talapoins.
63
1.5
1
0.5
0
-0.5
PCO1 PCO1 score adult males -1 females -1.5 subadult males -2 22 23 24 25 26 27 28 Geometric Mean
Figure 3.5. M. ogouensis adult male cranial allometry in the context of females and subadult males. The first principal coordinate score from a PCOORD of all talapoins (accounting for 21% of total variation among individuals), including two subadult males, plotted against cranial size (as geometric mean).
In accordance with ontogenetic studies of other cercopithecoids (e.g., Ravosa 1991b; Richtsmeier et al. 1993), the cranial size and the position of the two subadult males along PCO1 (Figure 3.5) is consistent with the hypothesis that male talapoins achieve their adult cranial form largely through hypermorphosis of a growth trajectory shared by both sexes. Clearly, a much larger ontogenetic dataset would be necessary to verify this hypothesis. This lack of static allometry in the adult male sample suggests, however, that once adult size and shape is reached, variation in male cranial shape is not significantly associated with cranial size.
Table 3.4. Correlation between components of cranium and body in adult male M. ogouensis . Fully adult males only (n=16).
cbrt( ECV ) OD CS CBL OD r=0.435, - - - p=0.081 CS r= 0.754*, r=0.472, - - p<0.001 p=0.065 CBL r=0.672*, r=0.573*, r=0.889*, - p=0.003 p=0.016 p<0.001 HBL n.s. n.s. n.s. n.s. * Denotes that correlation value is significant at the p < 0.05 level.
64 Correlations between metrics of the cranium and body in adult male M. ogouensis are similar to those in females (Table 3.4). As in females, there is a significant correlation of both orbital size (OD) and brain size (cube root ECV) with overall cranial size (CS). In contrast to the female sample, these correlations are significant whether CS or CBL is used as the cranial size metric.
Sexual dimorphism in Miopithecus ogouensis
As is visible in Figure 3.5, summary statistics of the female and adult male talapoin samples indicate that the sexes do not generally overlap in cranial size (Table 3.5). Adult males are about 8% larger than females, but females vary more in size (standard deviation in CS = 3.9 in females, 3.0 in males). The sexes overlap appreciably in ECV, with males having the larger mean volume. Endocranial volume and orbital size are larger relative to overall cranial size in females, however. This is typical for dimorphic species, as neural structures tend to differ less in size between the sexes than does the cranium as a whole (Plavcan 2003; Ravosa and Ross 1994). Brain size (ECV) is also larger relative to body length (HBL) in females than in males. The range of relative brain size (RBS = ECV ÷ body mass) values within the female sample is strikingly large, varying by almost a factor of two. This is a function of the wide range of body masses within this small sample. Such variation in RBS may or may not reflect the “norm” for this group. The species mean value reported below is based on published ECV and mass data of additional individuals, and should be reliable.
65
Table 3.5. Sexual dimorphism in the cranium of Miopithecus ogouensis . (Subadult males excluded.) The range and mean values for each variable are given for females and males. For ease of display in the table, several ratios were multiplied by 100, as indicated. Mean values that differ significantly between the sexes (as determined by t tests) are denoted by indicating in which sex the mean is larger. Otherwise, lack of significance is indicated by “no.” Mean RBS values are reported as the species mean estimate for each sex (based on published mass figures), as the dataset collected for this thesis did not contain enough individual mass values to compare RBS ranges within the samples. Miopithecus ogouensis Range Mean Significant Female Male Female Male CS 130 -145 148 -159 139.1 151.3 M > F OD (mm) 15.3 -17.4 16.2 -17.9 16.3 17.0 M > F ECV (mL) 32.5 -42.5 34.0 -48.0 37.1 40.4 M > F cbrt(ECV)/CS ratio (x 100) 2. 34 -2.54 2.17 -2.33 2.40 2.27 F > M OD/cbrt(ECV) ratio 4.57 -5.22 4.64 -5.24 4.90 4.97 no OD/CS ratio (x 100) 11.0 -12.4 10.6 -11.9 11.8 11.3 F > M RBS (ECV/Mass) (x 100) 2.60 -5.12 2.60 -3.14 3.28 2.71 F > M cbrt(ECV)/HBL ratio (x 100) 0.93 -1.17 0.91 -1.12 1.0 8 0.998 F > M CBL/HBL ratio (x 100) 12.8 -17.1 13.8 -17.9 15.3 15.4 no
An EDMA Shape comparison indicates that the sexes are distinguished by relative inflation of the neurocranium in females versus relative projection of the lower maxilla and premaxilla in males. Distances connecting lambda and bregma to landmarks on all regions of the cranium except the lower face are relatively long in the female sample. Distances that are relatively long in the adult male sample connect landmarks on the lower face and palate (i.e., IDS, PMMX, ICVF, MPSM, MXT) to the zygomatic arches (TZJ) and to cranial base landmarks. The distance between the right and left zygomatic arches is also relatively wide in males. The visualizations of superimposed Procrustes mean shapes (Figure 3.6) reinforce the results above. The male mean shape is characterized by localized projection of the maxillary alveolus and more flaring zygomatic arches. This lower facial expansion corresponds to a neurocranium that is smaller relative to overall cranial size than is the case in smaller faced females.
66
Figure 3.6. Miopithecus ogouensis male (dark blue) and female (light blue) mean shapes.
We can put these results in the context of the relationships illustrated in Figure 3.5, showing the grouping of the two subadult male specimens with the female specimens along PCO1 (PCO1 accounts for 21% of total variation among all talapoin individuals). The distances with strongest positive correlations to the PCO1 score connect the maxillary alveolus and palate to locations on the cranial base. That is, the distances that are relatively long in adult males. Distances between lambda and the rest of the cranium (except for the maxillary/palatal region) are negatively correlated with PCO1 score. In terms of these PCO1 related shape differences, Figure 3.5 suggests that across this sample (which is not exclusively “static,” due to the subadult males), variation in cranial shape in both sexes approximately follows a common allometric trajectory.
Parallel static allometry in the sexes
As mentioned earlier, there are not sufficient non adult specimens to test any hypotheses about ontogenetic allometry. To formally determine whether static allometry across adults follows a common allometric trajectory, we must show that the two within sex static trajectories are not significantly different from parallel and coincident (see Chapter 2). This was done in a two step MANCOVA. First, there is no evidence using any proportion of the shape variance (as represented by PC scores from a pooled sexes PCA) that the relationship between size and shape differs between the sexes in Miopithecus ogouensis (for 95% of shape variance, PCs1 28: F=0.597; df=28,7; p=0.844). That is, we cannot reject the null hypothesis that their static allometries are parallel . The results of the second step of the test show that the two trajectories are not coincident , however, as the sex factor has a significant effect on shape (PCs1 28:
67 F=4.31; df=28,8; p=0.018). This means that adding information about sex to the size shape regression changes the position of the allometric line, even if it does not significantly affect its slope. Thus, the MANCOVA results indicate that the sexes do not share a common static allometry , although their slopes do not differ significantly from parallel. This finding would seem to be at odds with two earlier observations: (1) adult female cranial shape is significantly size correlated whereas no significant allometry was detected in adult male shape; and (2) the impression from Figure 3.5 that the whole talapoin sample follows a common allometric trajectory. In regards to the first item above, the most likely explanation is that the size shape relationship within males is so weak that the MANCOVA does not have the statistical power to determine that the male slope is significantly different from the female slope. One caveat of this test is that failure to reject the null hypothesis happens both when two slopes are genuinely parallel, but also when there are not sufficient data to determine how close the slopes are, i.e., the test is inconclusive. More data are needed to resolve this. As for the second item, the impression of a common allometry is fueled in part by the presence of the two subadult males. A species’ static allometric trajectory need not coincide with its ontogenetic allometry (Cheverud 1982; Cock 1966), so we cannot consider the subadults in our evaluation of adult allometry. The other phenomenon at work is probably our human tendency to see trends in data that may not exist statistically. Figure 3.7 shows the plot of PC1 score against CS, with regression lines added to show the statistical best fit to the adult male and adult female data. These trendlines help to clarify why the sex covariate is significant in part 2 of the MANCOVA.
68
0.06
0.04 y = 0.0003x - 0.0189 R² = 0.0072
0.02
adult males 0 females PC1 score PC1
-0.02 subadult males
hypo M @ F CS -0.04 y = 0.0025x - 0.3625 R² = 0.4877 hypo F @ M CS -0.06 125 130 135 140 145 150 155 160 165 CS
Figure 3.7. Hypothetical male and female M. ogouensis shapes predicted at the mean cranial size of the opposite sex. Predicted shapes are extrapolated from the regression of Procrustes coordinates on CS within each sex. The first principal component score is reported from a PCA of all talapoins (Procrustes coordinates), including two subadult males, and two hypothetical shapes. This is similar to but not the same as the plot in Figure 3.5, which shows results from a PCOORD analysis plotted against geometric mean. ‘hypo M @ F CS’ = hypothetical male at female mean CS; ‘hypo F @ M CS’ = hypothetical female at male mean CS.
As another approach to exploring the relationship between adult male and female allometry in the talapoin, hypothetical male and female shapes were created. The multivariate regression of Procrustes coordinates on CS within females was used to predict a “hypermorphic” female at the mean CS of the male sample. Likewise, the adult male size shape regression was used to predict a “hypomorphic” male at the mean CS of the female sample. These two hypothetical shapes were then included in the PCA of all talapoins for comparison with the actual specimens (Figure 3.7). Notice that the female sized hypothetical male remains at a male like position along PC1. The male sized female, however, moves out of the female range of PC1 and into the male range. This result lends support to the hypothesis that male talapoins may achieve adult size and shape through extension of an ontogenetic growth trajectory that is shared with (or very similar to) that of females. If this is the case, it appears that adult female static allometry may retain more of the signature of this ontogenetic allometry in terms of slope than does adult male static allometry. Again, only ontogenetic data can directly address these hypotheses.
69 I now replicate these analyses of cranial shape in C. nictitans , a larger bodied guenon cousin of the talapoin monkey.
Static allometry in Cercopithecus nictitans females
About 7% of total shape variation in the cranium of female C. nictitans is statistically correlated with size variation (Table 3.6).
Table 3.6. Evidence of cranial allometry in Cercopithecus nictitans females (n=21) . Proportion of total Proportion of variance Associated p-value Shape component variance explained in component against null hypothesis by component explained by size of no allometry All Procrustes coordinates 100% 7.38% 0.043* PC1 of Procrustes PCA 16.2% 27.3% 0.014* PCO1 of EDMA PCOORD 15.7% 24.6% 0.022* Analysis * Significant at the p < 0.05 level.
Over 25% of variation in PCO1 score is associated with size in C. nictitans females. The distances most positively correlated with PCO1 score—associated with larger crania—are connections between the cranial base and the palate. This is somewhat different from the case among female talapoins, where the whole maxilla is relatively large in larger individuals, rather than only the lower maxilla/premaxilla and palate. Distances most negatively correlated with PCO1 score in C. nictitans females are measures of length and breadth of the cranial base (posterior to the palatal region). In visualizations comparing the largest and smallest predicted shapes, the projecting lower maxilla and palate in the large shape are evident (Figure 3.8). The relatively large lower face in larger females is associated with reduced relative size of the neurocranium, as in the talapoin sample.
70
Figure 3.8. Visualization of predicted shapes for largest (red) and smallest (yellow) C. nictitans females. Purple landmark points correspond to the red (large) predicted shape, and green points correspond to the yellow shape. Because no digital surface data of C. nictitans were available, all surface reconstructions of C. nictitans in this chapter are based on the micro CT scan of a male M. ogouensis , For this reason, reconstructions show considerable distortion.
Correlations between cranial and body metrics in female C. nictitans contrast with those in Miopithecus ogouensis in that brain size (cube root ECV) is not significantly correlated with any of the other measures ( Table 3.7). Orbit size (OD) is correlated with CBL and, as in all samples used in this thesis, CS is strongly correlated with CBL. Table 3.7. Correlation between components of cranium and body in female C. nictitans . cbrt( ECV ) OD CS CBL OD n.s . - - - CS n.s. r=0.400, - - p=0.073 CBL n.s. r=0.488*, r=0.944*, - p=0.018 p<0.001 HBL n.s. n.s. n.s. n.s. * Denotes that correlation value is significant at the p < 0.05 level.
Static allometry in Cercopithecus nictitans males
In the sample of C. nictitans males, cranial allometry is comparable in strength to that in females—with about 7% of overall shape variance associated with size variance (Table 3.8). Unlike in females, however, the first principal axes of shape variation (in both PCOORD and
71 PCA) are not significantly correlated with cranial size. Allometric shape is not detectable until the 3 rd principal component (or the second principal coordinate) of shape variation for the males.
Table 3.8. Evidence of cranial allometry in C. nictitans males (n=24).
Proportion of total Proportion of variance Associated p-value Shape component variance explained in component against null hypothesis by component explained by size of no allometry All Procrustes coordinates 100% 7.03% 0.014* PC1 of Procrustes PCA 14.5% 9.60% 0.136 PC3 of Procrustes PCA 10.6% 24.4% 0.014* PCO1 of EDMA PCOORD 13.8% <0.001% 0.991 Analysis PCO2 of EDMA PCOORD 13.0% 45.9% <0.001* * Significant at the p < 0.05 level.
The interlandmark distances correlating positively with PCO2 score (Figure 3.9) are not related to lower maxillary/alveolar projection per se , but to the relative distance between landmarks on the posterior palate (PNS, MXT) and landmarks on the cranial base, posterior to VSJ (e.g., CIFM, FO, OPI, JUG, CAR, etc.). Distances that are negatively correlated with PCO2 score (i.e., distances that tend to be relatively long in smaller individuals) include the connections between the palate and the upper face. This pattern is surprising in that it appears that the palate is relatively short compared to the rest of the cranial base in larger individuals. The maxillary alveolus does not appear to be more projecting in larger males. Nasale is more projecting, however. In smaller individuals, the distance between the orbital rims at FZJ is relatively wide, and bregma is relatively more superior (relatively tall neurocranium). Normally, we expect larger individuals to have a longer, more projecting palate, but that is not the case in this sample.
72
1.5
1 R² = 0.459 0.5
0
PCO2 PCO2 score -0.5
-1
-1.5 37 37.5 38 38.5 39 39.5 40 40.5 41 41.5 42 Geometric Mean
Figure 3.9. Correlation between PCO2 score and cranial size (geometric mean) in C. nictitans males. Although PCO2 accounts for only 13% of total variance among individuals (Table 3.8), a large portion of PCO2 related variance is attributable to size (high R2 value).
The unexpected results of the PCOORD analysis (i.e., with respect to palatal projection) are confirmed by visualizations of large and small extreme shapes extrapolated from Procrustes coordinates (Figure 3.10). The large predicted shape (in red) does not appear to have more premaxillary prognathism than the small predicted male C. nictitans (in yellow).
Figure 3.10. Visualization of predicted shapes for largest (red) and smallest (yellow) C. nictitans males.
Brain size (cube root ECV) and cranial size (CS) are more strongly correlated in the male sample of C. nicititans than in the female sample, but the correlations are still not statistically significant (Table 3.9). The relationship between OD and cranial size (as CS and CBL) in males
73 is of similar magnitude to that in females. Counterintuitively, the relationship between OD and HBL is negative within the male sample, although this correlation is not statistically significant.
Table 3.9. Correlation between components of cranium and body in male C.nictitans .
cbrt( ECV ) OD CS CBL OD n.s. - - - CS ρ= 0.377†, r=0.442*, - - p=0.069 p=0.031 CBL ρ= 0.256†, r=0.332, r=0.894*, - p=0.198 p=0.084 p<0.001 HBL n.s. r=-0.411, n.s. n.s. p=0.128 * Denotes that correlation value is significant at the p < 0.05 level. † Results similar for Kendall’s rank correlation (τ).
Sexual dimorphism in Cercopithecus nictitans
Shape comparisons between the sexes in C. nictitans —via EDMA or GPA—reveal a continuous spectrum of size and shape variation across the sexes, such that the largest females overlap with the smallest males in terms of cranial size and the major component of shape variation (Figure 3.11).
0.05 0.04 0.03 0.02 0.01 0 -0.01 PC1 score PC1 males -0.02 females -0.03 -0.04 -0.05 190 200 210 220 230 240 250 CS
Figure 3.11. The first principal component of shape variation in C. nictitans plotted against CS. From a PCA of all Procrustes coordinates. The analogous PCOORD analysis yields a nearly identical plot.
74 Summary statistics (Table 3.10) show that the male mean cranial size, orbital size and ECV are significantly larger than females, but overlapping in range. As expected by the increased relative size of the face in males, female ECV and orbital size are higher relative to overall cranial size. Based on body length (HBL), females are also significantly more encephalized than males (cube root ECV/HBL), although there are not adequate mass data available in this sample to confirm this (i.e., via RBS).
Table 3.10. Sexual dimorphism in the cranium of Cercopithecus nictitans . For explanation of table, see Table 3.5. RBS values are reported as the species mean estimate for each sex (based on published mass figures), as the dataset collected for this thesis did not contain enough individual mass values to compare RBS ranges within the samples (1 of 21 females and 3 of 24 males).
Cercopithecus nictitans Range Mean Significant Female Male Female Male CS 194 -217 218 -243 204.6 229.9 M > F OD (mm) 19.0 -22.9 19.4 -23.3 20.8 21.7 M > F ECV (mL) 57.0 -83.5 64.5 -95.0 70.9 80.7 M > F cbrt(ECV)/CS ratio (x 100) 1.92 -2.13 1.75 -1.92 2.02 1.88 F > M OD/cbrt(ECV) ratio 4.62 -5.77 4.36 -5.45 5.04 5.03 no OD/CS r atio (x 100) 9.40 -11.1 8.75 -10.1 10.2 9.42 F > M RBS (ECV/Mass) (x 100) - 1.19 -1.33 1.67 1.21 F > M cbrt(ECV)/HBL ratio (x 100) 0.76 -0.95 0.65 -0.84 0.861 0.748 F > M CBL/HBL ratio (x 100) 15.0 -18.7 13.7 -17.4 16.6 15.7 no
A comparison of shape between the sexes using EDMA reveals limited and well defined differences. The interlandmark distances that are relatively long in females have lambda or bregma as endpoints. All of the most significantly (relatively) long distances in males are connected to landmarks on the palate and maxillary alveolus. These straightforward shape differences are corroborated by the mean shape visualizations (Figure 3.12). The lower face of the male mean shape projects more anteriorly, including the premaxilla and lower maxilla as well as the nasal bones. This increased male prognathism results in a concomitant reduction in relative size of the neurocranium. The relative breadth of the zygomatic arches does not differ between the sexes, both in mean shape visualizations and in linear distance comparisons (i.e. distance between right and left TZJ).
75
Figure 3.12. Cercopithecus nictitans male (dark red) and female (pink) mean shapes.
Parallel static allometry in the sexes
The relationship between size and shape in the two sexes is not statistically distinguishable via MANCOVA (PCs1 29: F=1.49; df=29,13; p=0.225). That is, the static allometries of the sexes are not significantly different from parallel . This is despite the observations made earlier regarding small and large predicted shapes in the two sexes—cranial shape in males does not appear to be related to size in the same way as in females. Nonetheless, the slopes of the static allometric trajectories do not diverge sufficiently between the sexes to be detectable with these sample sizes. Step 2 of the MANCOVA procedure indicates that the effect of sex on shape is significant, independent of size (PCs1 29: F=4.32; df=29,14; p=0.003). This indicates that—as in talapoins—male and female static allometries in C. nictitans adults are not coincident . A different angle for exploring static allometry in each sex is to predict a “male sized” female based on the within sex allometry of female C. nictitans . Likewise, a “female sized” male was produced, as done earlier in this chapter with male and female Miopithecus ogouensis (Figure 3.7). When included in a PCA with the entire actual C.nictitans sample (Figure 3.13), both the hypothetical male sized female and female sized male fall closer to the average PC1 score for males rather than females. Both are in a range of PC1 values that includes both male and female C. nictitans , however. The positions of the two hypothecial shapes along the first two PC axes suggest that there is some difference in static allometric trajectory between the sexes, in that the oversized female is closer to the center of the male distribution on PC1 than the undersized male is to the female PC1 mean. These results are similar to those from the comparison of hypothetical talapoin shapes. As such, they are consistent with an analogous hypothesis (again, untestable here) regarding the role of ontogenetic scaling to produce cranial
76 sexual dimorphism in C. nictitans . That is to say, male cranial shape is consistent with hypermorphosis along an ontogenetic shape trajectory similar to that describing static allometry within adult females.
0.05 0.04 0.03 0.02 0.01 0 -0.01 males PC1 score PC1 -0.02 -0.03 females -0.04 -0.05 hypo M @ F CS -0.06 190 200 210 220 230 240 250 CS
Figure 3.13. Hypothetical male and female C. nictitans shapes predicted at the mean cranial size of the opposite sex. Predicted shapes are extrapolated from the regression of Procrustes coordinates on CS within each sex. Shown here is PC1 of a PCA of all Procrustes coordinates plotted against CS, using the 45 actual specimens plus two hypothetical shapes. (‘hypo M @ F CS’ = hypothetical male shape at the mean CS of female C. nictitans ; ‘hypo F @ M CS’ = hypothetical female shape at the mean CS of males)
Next, I move from shape comparisons within the two guenon species to the investigation of cranial shape and allometry between them. As such, I extend static allometry into the realm of evolutionary allometry.
Interspecific shape: M. ogouensis females compared to C. nictitans females
In an EDMA Shape comparison, the largest differences between females in the two species are related to the relative inflation of the neurocranium in the talapoin vs. the relative premaxillary maxillary projection in C. nictitans . Distances connecting to lambda and bregma from everywhere on the cranium (except the anterior palate) are relatively long in M. ogouensis . The
77 relative length of distances connecting the premaxilla (PMMX, IDS, ICVF) to the cranial base account for all of the most significant shape differences in female C. nictitans . A visual comparison of the superimposed mean female shapes of each species (Figure 3.14) conforms to the EDMA findings above. The neurocranium and orbits of the talapoin are relatively prominent, in contrast to the marked prognathism of the female C. nictitans .
Figure 3.14. Visualization of C.nictitans (red) and M. ogouensis (blue) female mean shapes.
Given the results of shape comparisons, it is not surprising that the ratios of orbital and ECV size to cranial size are greater in talapoins (Table 3.11). Although ECV is greater in relation to HBL in the female talapoin, the ratio of cranial length (CBL) to HBL is larger in C. nictitans . The scarcity of body mass data for the larger guenon prevents a comparison of RBS or encephalization quotient (EQ) directly from the samples analyzed here.
78
Table 3.11. Comparative statistics for female M. ogouensis and C. nictitans . Mean RBS values are reported as the species estimate for females (based on published mass data). In this study’s samples, body mass data are available for 14 of 22 M. ogouensis, and 1 of 21 C. nictitans . Range Mean Significant Mo Cn Mo Cn CS 130 -145 194 -217 139.1 204.6 Cn > Mo OD (mm) 15.3 -17.4 19.0 -22.9 16.3 20.8 Cn > Mo ECV (mL) 32.5 -42.5 57.0 -83.5 37.1 70.9 Cn > Mo cbrt(ECV)/CS ratio (x 100) 2.34 -2.54 1.92 -2. 13 2.40 2.02 Mo > Cn OD /cbrt(ECV) ratio 4.57 -5.22 4.62 -5.77 4.90 5.04 no OD /CS ratio (x 100) 11.0 -12.4 9.40 -11.1 11.8 10.2 Mo > Cn RBS (ECV/Mass) (x 100) 2.60 -5.12 - 3.28 1.67 Mo > Cn cbrt(ECV)/HBL ratio (x 100) 0.93 -1.17 0.76 -0.95 1.08 0.861 Mo > Cn CBL/HBL ratio (x 100) 12.8 -17.1 15.0 -18.7 15.3 16.6 Cn > Mo
Parallel static allometry in females
The first step of a MANCOVA tests for differences in size effects on shape in females of the two species. This procedure indicates that the slopes of static allometry do not differ significantly from parallel (for 95% of shape variance, PCs1 21: F=1.12; df=21,19; p=0.406). In the second step of the MANCOVA, the relationship becomes more complex. When only shape variation captured by PCs 1 and 2 are considered (69.9% of total variance in shape), species membership does not significantly affect the position of the allometric trajectory, meaning the two lines are coincident (PCs1 2: F=2.95; df=2,39; p=0.064). When more cumulative variance (73% or more) is included by adding more PCs to the analysis, the best fit lines of static allometry no longer coincide. This phenomenon is easily explained, however. In terms of the major axes of cranial shape variation, females of M. ogouensis and C. nictitans share static allometric trajectories that are not significantly different from coincident (see Figure 3.15). This means that if the top ≈70% of shape variation is considered, a talapoin female “scaled up” to the size of a C. nictitans female should look like a C. nictitans female. But the third PC of shape variation and beyond picks up species specific shape traits in the two samples. As such, including species information in the linear model predicts shape better than including only size (for 95% of variance, PCs1 21: F=6.39; df=21,20; p<0.001). That is to say that when more than ≈70% of shape variation is included, the two static allometries are not coincident .
79
0.1 0.08 y = 0.0011x - 0.1647 0.06 R² = 0.1824 0.04 0.02 0 -0.02 PC1 PC1 score -0.04 M. ogouensis F -0.06 y = 0.0017x - 0.2952 C. nictitans F -0.08 R² = 0.3375 -0.1 125 135 145 155 165 175 185 195 205 215 225 CS
Figure 3.15. PC1 plotted against CS from a PCA of all female guenons.
Less formally, we can compare within sample allometry for females based on their respective large and small predicted shapes (Figure 3.4 & Figure 3.8). These visualizations suggest some divergence in allometric trajectories in that larger female talapoins appear to have a more projecting face overall (including the position of nasion and FZJ) than smaller individuals. In C. nictitans , however, facial projection in the larger predicted shape is more localized to the lower face only. This is consistent with the MANCOVA (step 2) results, suggesting that there are some shape differences between females of the species that cannot be explained by size alone.
Interspecific shape: M. ogouensis males compared to C. nictitans males
The shape differences between males of the two species (including only fully adult talapoin males) are similar to those between females. An EDMA Shape comparison identifies, again, the relative importance of distances connecting to lambda and bregma as characterizing the talapoin cranium. In the C. nictitans males, the relative length of distances connecting the premaxilla to the cranial base is particularly salient. The superimposed mean shape visualizations of the male samples are nearly identical to their female counterparts (not shown). Interspecific shape differences are dominated by the
80 relatively large orbits and inflated neurocranium of the talapoin in contrast to the marked naso alveolar projection of the male C. nictitans . Summary statistics and ratio comparisons for males of the two species (Table 3.12) follow the same pattern as in the females, with the exception that the ratio of CBL to HBL does not differ significantly between males of the species (this ratio is higher in C. nictitans vs. talapoin females, Table 3.11).
Table 3.12. Comparative statistics for male M. ogouensis (fully adult) vs. C. nictitans . Because body mass data are only available for 2 of 16 adult M. ogouensis, and 3 of 24 C. nictitans in the sample, mean RBS values are reported as the species estimates for males, based on published mass data.
Range Mean Significant Mo Cn Mo Cn CS 148 -159 218 -243 151.3 229.9 Cn > Mo OD (mm) 16.2 -17.9 19.4 -23.3 17.0 21.7 Cn > Mo ECV (mL) 34. 0-48.0 64.5 -95.0 40.4 80.7 Cn > Mo cbrt(ECV)/CS ratio (x 100) 2.17 -2.33 1.75 -1.92 2.27 1.88 Mo > Cn OD /cbrt(ECV) ratio 4.64 -5.24 4.36 -5.45 4.97 5.03 no OD /CS ratio (x 100) 10.6 -11.9 8.75 -10.1 11.3 9.42 Mo > Cn RBS (ECV/Mass) (x 100) 2.60 -3.14 1.19 -1. 33 2.71 1.21 Mo > Cn cbrt(ECV)/HBL ratio (x 100) 0.91 -1.12 0.65 -0.84 0.998 0.748 Mo > Cn CBL/HBL ratio (x 100) 13.8 -17.9 13.7 -17.4 15.4 15.7 no
Parallel static allometry in males
Testing with a MANCOVA for the difference of size effects on shape in males of the two species, there is no indication of divergence in slopes between their allometric trajectories. This result holds for any included proportion of total shape variance (for 95% of shape variance, PCs1 20: F=0.553; df=20,17; p=0.897). This statistical comparison is of limited meaning, however, as the statistically insignificant cranial allometry in talapoin males limits the power to reject the null hypothesis of parallel allometries. Larger sample sizes are needed to obtain a biologically and statistically meaningful comparison of static allometry in these male guenons. In the second phase of the MANCOVA, the species factor is significant, implying that even if the static allometries are parallel, they are not coincident (PCs1 20: F=2.97; df=18,20; p=0.012).
81 Overall cranial allometry in the species, sexes pooled
The results of a MANCOVA that includes all individuals are, at least superficially, incongruent with the results of the all male and all female tests for parallel allometry between the species— which indicated trajectories not significantly different from parallel. With any proportion of shape variance included (PC1+), the relationship between cranial size and shape is not parallel in the two species (for 95% of shape variance, PCs1 29: F=3.11; df=29,53; p<0.001). This may simply be a reflection of the larger sample sizes that result from pooling the sexes. Larger sample sizes increase the statistical power of the MANCOVA to reject the null hypothesis, whereas there were perhaps too few individuals in the single sex groups. Separate regression lines in Figure 3.16 demonstrate the difference in allometric slopes associated with PC1. It would appear that although they are statistically divergent from parallel, the species have very similar static allometries with respect to this first principal component of cranial shape variation.
0.15 y = 0.0013x - 0.2183 0.1 R² = 0.696
0.05
y = 0.002x - 0.3527 0 R² = 0.6701 PC1 score PC1 -0.05
-0.1 Mo Cn -0.15 125 145 165 185 205 225 245 CS
Figure 3.16. PC1 plotted against centroid size from a PCA of all individuals, sexes pooled. (Procrustes coordinates) Although the PC1 related allometric trajectories are quite similar in Miopithecus ogouensis (“Mo”) and Cercopithecus nictitans (“Cn”), the slopes of their overall allometric trajectories are significantly different from parallel.
82 Encephalization
There are conflicting conclusions in the literature regarding encephalization in the talapoin monkey. Because Miopithecus is an outlier among Old World monkeys in terms of body size, its level of comparative encephalization is difficult to assess. Seminal research on comparative encephalization in primates by Bauchot and Stephan (1969) and Jerison (1973), as well as subsequent work (e.g., Holloway and Post 1982), has consistently ranked Miopithecus among the most highly encephalized primates. Using the equations for EQ, which are based on brain/body relationships across mammals, they are highly encephalized (Table 3.13). In contrast, Isler and colleagues (2008) found that when compared to the brain/body regression line among cercopithecines, Miopithecus is below average in brain size. This discrepancy appears to be due to vastly different estimates for species mean body mass by different authors—Bauchot and Stephan (1969) used 1000g for the talapoin, whereas Isler et al. (2008) used 1750g. (The Isler et al. (2008) dataset contains a mathematical error when including two exceptionally heavy individuals reported in Smith and Jungers (1997), skewing the species mean dramatically.)
Table 3.13. Sex-specific EQ values for representative guenon taxa. EQ calculated using Eisenberg’s (1981) formula. Values for M. ogouensis and C. nictitans from this study (using additional published mass data); other values from Isler et al. (2008). Brackets at left indicate “arboreal Cercopithecus ” clade ( A) and “terrestrial guenon” clade ( T) (phylogeny in Figure 3.2).
Species ECV (mL) Mass (g) EQ M F M F M F Miopithecus ogouensis 40.4 37.1 1490 1130 3.30 3.71 Cercopithecus nictitans 80.7 70.9 6670 4240 2.17 2.67 Cercopithecus cephus 68.8 61.7 4290 2880 2.57 3.09 Cercopithecus petaurista 58.1 52.1 4300 2918 2.16 2.58 A Cercopithecus diana 70. 1 55.2 5200 3900 2.27 2.21 Cercopithecus mitis 77.4 65.2 7591 4628 1.89 2.30 Cercopithecus mona 65.9 57.8 4705 2733 2.30 3.01 Cercopithecus neglectus 71.1 60.9 7350 4130 1.78 2.33 Cercopithecus lhoesti 81.1 67.3 5970 3450 2.37 2.95 T Chlorocebus aethiop s 71.0 59.0 4400 3039 2.60 2.84 Erythrocebus patas 107 88.9 12400 6500 1.81 2.44 Allenopithecus nigroviridis 62.4 53.7 6130 3180 1.79 2.50
83 The only other anthropoids with body mass comparable to Miopithecus are among the platyrrhines: the squirrel monkeys, Saimiri ; the titi monkeys, Callicebus ; the owl monkeys, Aotus ; and the sakis, Pithecia and Chiropotes . Mean species body mass and ECV values for these species suggest that the female talapoin, at least, has a comparatively large relative brain size (Figure 3.17), assuming that such phylogenetically distant taxa can reasonably be compared in this way. As modern levels of encephalization likely evolved independently in platyrrhines and catarrhines, comparability between the talapoin and the New World monkeys is debatable. The mass range of the talapoin male is void of comparators among other male anthropoids.
60
50
M. ogouensis (f) 40 Saimiri (f) Callicebus (f) 30 Aotus (f) ECV (mL) ECV 20 M. ogouensis (m) Callicebus (m) 10 Pithecia (m) Chiropotes (m) 0 500 1000 1500 2000 2500 Body Mass (g)
Figure 3.17. Relative brain size in Miopithecus ogouensis compared to similarly-sized anthropoids. Each point represents the mean values for a given sex and species within the indicated genus. Values for M. ogouensis from this study (using additional published mass data); other values from Isler et al. (2008).
There are many other anthropoid primates with similar body mass range to C. nictitans , however. The mean ECV estimates for male and female C. nictitans place it squarely among other cercopithecines and papionins of similar body size (Figure 3.18).
84
130
120 C. nictitans (f) 110 platyrrhines (f) 100 cercopithecines (f) 90 papionins (f) 80 colobines (f)
ECV (mL) ECV 70 C. nictitans (m)
60 platyrrhines (m) cercopithecines (m) 50 papionins (m) 40 colobines (m) 30 hylobatids (m) 3000 4000 5000 6000 7000 8000 Body Mass (g)
Figure 3.18. Relative brain size in Cercopithecus nictitans compared to similarly-sized anthropoids. Each point represents the mean values for a given sex and species. Values for C. nictitans from this study (using additional published mass data); other values from Isler et al. (2008).
Conclusions
The results of this suite of comparative analyses allow some conclusions to be drawn with respect to the null hypotheses outlined earlier in the chapter. Hypothesis 1: Within each species, the trajectory of male cranial static allometry is coincident with that of female static allometry. I did not find support for this hypothesis. Male and female trajectories are not significantly different from parallel within the two species, although this may be due to a lack of statistical power, at least in the case of talapoins. It does not appear to be the case that male and female cranial shapes within species are simply different points along a common static allometric trajectory. That is, sex affects the distribution of cranial shape in these samples, independent of size. This does not exclude the possibility that male and female ontogenetic allometries are coincident, however.
85 Hypothesis 2: The cranial static allometry of M. ogouensis is parallel to that of C. nictitans . I found some support for this hypothesis. Sex specific static allometries are not statistically significantly different from parallel between the species (that is, in male male and female female comparisons). Interspecific results presented here suggest that female static allometric trajectories between the two species are closer than are male static allometries, being coincident in terms of the first two principal axes of shape variation. With the sexes pooled, the multivariate slope of static allometry in M. ogouensis is significantly different than that of C. nictitans (see Figure 3.16). Hypothesis 3: Sexual dimorphism in cranial shape and size is lower in M. ogouensis than in the larger guenon. The data presented here support this hypothesis (Table 3.14). Sexual dimorphism of CS as a percentage of male CS is 8.06% in M. ogouensis and 11.0% in C.nictitans . The Procrustes distance and the Mahalanobis distance between mean male and female shapes are also lower in the talapoin than in C. nictitans . It should be said that the discrepancy between the magnitudes of sexual dimorphism in the two species is less than one would expect given the trend across other guenons (Cardini and Elton 2008b).
Table 3.14. Comparison of static allometry and sexual dimorphism in M. ogouensis and C. nictitans . For this table, allometry and sexual dimorphism ( SD ) were calculated using the same methods as in Cardini and Elton 2008b ( C&E ). SD of cranial size is the difference between male and female mean CS as a percentage of male CS. Static allometry is calculated as the percentage of shape variation predicted by a multivariate regression of all PC scores against natural log CS. The distances between male and female mean shapes ( Shape distance, M-F) in each species are reported from this study only. PRD = Procrustes distance; Mah = Mahalanobis distance. Species Allometry % (pooled sexes) SD of cranial size (%) Shape distance, M-F This study C&E This study C&E PRD Mah M. ogouensis 15.5 21.1 8.06 9.8 0.0375 4.55 C. nictitans 16.7 14.4 11.0 9.3 0.0419 5.07
Nonetheless, these results differ from those obtained by Cardini and Elton (2008b:Table 1), in that they found sexual size and shape dimorphism to be slightly lower in C. nictitans compared to M. ogouensis (Table 3.14). Cardini and Elton also found that the magnitude of static allometry was higher in M. ogouensis than in C. nictitans , whereas this study found the magnitude of allometry to be nearly equal in the two species. These inconsistencies are probably due to methodological differences in data collection between the studies. Cardini and Elton (2008b) included 86 midline and left side landmarks on the cranium and mandible, compared to
86 45 midline and bilateral (cranium only) landmarks in this study. In addition, the two studies used different individual specimens, albeit with some overlap in sampling between them. Hypothesis 4: M. ogouensis has an unusually large endocranial volume for its body mass compared to other non human primates. I find support for this hypothesis. The EQ of the next most encephalized guenon, Cercopithecus cephus , is 2.83 (average of male and female EQ values in Table 3.13), compared to 3.50 in the talapoin. Among the few anthropoids closer to its body mass, the talapoin also appears to have an above average brain volume (Figure 3.17).
Discussion
Ultimately, the analyses of shape and static allometry in this chapter have little direct bearing on Shea’s (1992) hypothesis that the talapoin’s paedomorphic morphology results from rate hypomorphosis relative to larger guenons. That said, these results are consistent with Shea’s conclusion. The cranial size and shape of female and subadult male talapoins suggest that the static adult male allometric trajectory (or lack thereof) probably differs substantially from the ontogenetic trajectory of talapoins. In addition, the static allometry of female talapoins coincides with that of female C. nictitans in the major aspects of cranial shape variation. If adult female static allometry is a reasonable indicator of the trajectory of ontogenetic allometry in these species, then growth truncation or hypomorphosis of some variety would be consistent with the observed adult morphologies. Miopithecus is clearly an outlier taxon among Old World monkeys. A hypothesis of ontogenetic scaling from an early ancestral guenon has considerable explanatory power, as shown by Shea (1992). As Shea points out, disproportionately large neural structures are expected in an animal that has slowed and/or shortened its postnatal growth, because most neural growth happens early in ontogeny. With respect to encephalization in the talapoin, Shea concludes (1992:303): “Thus, we basically end up with a monkey dwarfed predominantly or exclusively via postnatal growth mechanisms, which therefore results in a creature with a large relative brain size.” Bauchot and Stephan (1969) hypothesized that a derived decrease in body size tends to result in a relatively large brain, both in terms of brain to body mass ratio and in terms of interspecific allometry. That is, they hypothesize that brain volume in dwarf species tends to
87 follow an intra specific rather than inter specific regression coefficient: closer to 0.23 (within species) than to 0.63 (between species). They suggest that this “intraspecific scaling” phenomenon is the most likely explanation for the talapoin monkey’s large brain, noting a similar trend in small breeds of domestic dogs. The result of evolutionary dwarfing, posit the authors, is that dwarf forms end up with encephalization indices closer to juveniles of a typical species than to adults. This phenomenon should not be mistaken for a “superior level of brain evolution” in the dwarf (Bauchot and Stephan 1969:268), as adult dwarfs are not directly comparable to adults of non dwarf species. With respect to this aspect of the hypothesis, it is notable that Deaner et al. (2006) found that in published studies of non human primate “domain general” cognition, Miopithecus tends to score significantly below members of Cercopithecus . Besides the talapoin, Bauchot and Stephan (1969) hypothesize that a similar scenario may also apply to the genus Cebus . Both Shea’s and Bauchot and Stephan’s explanations share an element of the “evolutionary lag” hypothesis. So called evolutionary lag refers to a situation in which a biological trait defies theoretical expectation because it is still in the process of responding to a recent selective pressure on a different trait (or traits) (Deaner and Nunn 1999). This phenomenon is frequently invoked to explain larger than expected relative brain size in an organism as the result of a recent decrease in body size (or recently increased body size resulting in a relatively small brain). Although the evolutionary lag hypothesis is appealing and often cited (Lande 1979; Martin and Harvey 1985), Deaner and Nunn (1999:687) contend that it does not hold up to testing in primates, concluding that “relative brain size should not be used to infer recent evolutionary changes in body size.” According to Deaner and Nunn, the frequently observed taxon level effect (TLE) is the only line of evidence to support the evolutionary lag hypothesis. The TLE describes the finding—ubiquitous in brain:body scaling studies—that the slope of the log log brain body size regression equation is steeper at higher taxonomic levels, and flatter at lower taxonomic levels. Bauchot and Stephan (1969), for example, calculated an intraspecific slope of 0.23, whereas their intraspecific regression line had a slope of 0.63, as alluded to earlier. Shea (1992) found that Verheyen’s (1962) species mean craniometric values for other guenon species fall nicely along the extension of the common growth trajectory of talapoin and moustached monkey ( Cercopithecus cephus ) individuals. This result, in concert with the results of the present study and those by Cardini and Elton (2008a; 2008b) suggest to me that the species mean shapes across guenons will tend to fall close to a common ontogenetic allometric trajectory
88 shared by all species, whereas the static adult allometry within any given species (particularly that of males, it would appear) is not parallel to this line. Adults within a species vary in shape in ways that are much less size related than individuals along a growth trajectory. Despite the fact that evolutionary allometry is the logical extension of static allometry, the shape trajectory of species level evolutionary change seems to approximate an ontogenetic curve more closely than a static one. It would seem that this phenomenon, the TLE (introduced above), and “transpositional allometry” (introduced in Chapter 2) are all related: ontogenetic and evolutionary (i.e., interspecific) allometric slopes tend to be steep, while static (intraspecific) slopes are more moderate.
Expectations for other dwarfed primates
The talapoin model of reduced body size in primates helps to establish the baseline predictions for dwarf primate morphology. The hypotheses that are tested in the following two chapters are derived from a null expectation of pure ontogenetic scaling in the dwarf taxon relative to its non dwarf kindred. As stressed in this chapter and in Chapter 1, the hypothesis of ontogenetic scaling in the dwarf cannot be tested directly with only static adult data. Beginning with a model of ontogenetic scaling, however, we can derive null hypotheses about adult morphology that can be tested. Thus, in the two remaining groups of analyses in this dissertation, I address the following null hypotheses: 1) The dwarf species has relatively large neural components for the size of its cranium. These components are quantified in this study via the hard tissue orbits and endocranial cavity. 2) In the cranium of the dwarf species, the facial skeleton is less prominent than in the cranium of the larger bodied species. 3) The dwarf species shares a coincident static adult cranial allometry with its non dwarf relative. As defined in Chapter 2, coincident allometric trajectories are both parallel and collinear . 4) Encephalization in the dwarf species is higher than in the non dwarf taxon. Encephalization is assessed using a combination of approaches in each case, based on the data available.
Chapter 4
Size and cranial morphology in an odd-nosed colobine lineage: Simias concolor and Nasalis larvatus
The objective of this chapter is to identify and describe the differences in cranial form and shape between two sister species of odd nosed colobine monkeys which have diverged considerably in body size since their last common ancestor. The smaller species, Simias concolor , is known variously as the snub nosed langur, the pig tailed langur, or locally as the “simakobu.” The proboscis monkey, Nasalis larvatus , is a larger bodied and highly dimorphic colobine. These species are informative models for studying the morphological correlates of body size evolution because they are closely related and share many ecological variables, but have entirely non overlapping geographic ranges. This holistic cranial morphometric comparison of these two species is the first of its kind.
Species background
Geographic range
The simakobu, Simias concolor , is found in the forests of the four largest islands of the Mentawai archipelago: Siberut, Sipora, and North and South Pagai (Figure 4.1). The total land area of these islands amounts to less than 8,000 km 2 (roughly 10% smaller than Puerto Rico, for comparison). Simias is sympatric with three other endemic primates on the islands: the Kloss’s gibbon (Hylobates klossii ), the Mentawai Islands leaf monkey ( Presbytis potenziani ), and the Pagai macaque ( Macaca pagensis ). The proboscis monkey, Nasalis larvatus , inhabits swamp and mangrove forest bordering coastline and waterways on the island of Borneo (Meijaard and Nijman 2000). With a land area approaching 750,000 km 2, Borneo is one of the world’s largest islands, surpassing Madagascar in size. Nasalis shares the island with multiple other non human primates, including other Asian colobines from the genera Presbytis and Trachypithecus , macaques, gibbons, orangutans, tarsiers, and the slow loris.
90
Figure 4.1. Geographic ranges of the simakobu, Simias concolor , (in green) and the proboscis monkey, Nasalis larvatus (in orange).
Biogeography
The most obvious biogeographic issue raised by the current distribution of Simias and Nasalis concerns why they have no living relatives in between these two separate ranges (Harrison et al. 2006; Meijaard 2004). Virtually any biogeographic scenario must hypothesize that ancestral members of the lineage inhabited Sumatra and/or the Malay Peninsula at some point. Brandon Jones (1996; 1998) contends that at least two major glacial related aridity events occurred in Pleistocene island Southeast Asia: one about 190 thousand years ago (kya) and one about 80 kya. He hypothesizes that during these aridity crises, rainforest cover was reduced to only a few refugia on the Mentawai Islands, parts of Borneo, and to a lesser extent, northern Sumatra. It was during the first and most severe of these droughts that the Nasalis Simias last common ancestor went extinct in Sumatra and across the region, leaving only relict populations on the Mentawai Islands and Borneo (Brandon Jones 1996). Subsequent members of the lineage were never able to successfully reinvade Sundaland. Some insight into possible paleobiogeographic scenarios for the colonization of the Mentawai Islands by Simias may be provided by work done on the macaques of the islands (Roos et al. 2003). This does not present a simple scenario for colonization, however, as the authors
91 found that the Mentawai macaques are not monophyletic, but represent two separate divergence events from other Asian macaques, beginning about 2.2 million years ago (Ma). In contrast to the Mentawai macaques, Whittaker (2005) found that the Kloss’s gibbon ( Hylobates klossii ) on the islands represents a single lineage. She also notes that the four islands may have been united into a single landmass as recently as 7 kya. Brandon Jones (1996; 1998) stresses that many cranial and, especially, postcranial features of the proboscis and simakobu (which he considers congeneric) indicate that they evolved in a more open, terrestrial environment, rather than the lush rainforest to which they are presently confined. Their postcranial morphology he considers very macaque like, and notes that their dedication to folivory indicates an evolutionary history where seasonal climatic change would have favored the ability to eat mature (toxic) leaves, rather than depending on seasonal fruits and young leaves.
Diet
Both Simias and Nasalis are primarily arboreal leaf eaters. Little data are available on the specific dietary habits of the simakobu. The proboscis monkey is typical among the Asian colobines in that it prefers fruits and seeds when available, followed by young leaves, and resorts to mature leaves only when necessary (Kirkpatrick 2007).
Sociality
Both species generally live in social groups consisting of one male plus multiple females with their offspring (one male units), although Simias social units—particularly in areas of human habitat encroachment—have been observed containing only one adult female in addition to the male (Hadi et al. 2009; Kirkpatrick 2007; Tenaza and Fuentes 1995). All male bands have been observed in both taxa (Bennett and Sebastian 1988; Hadi et al. 2009), which is an expected consequence when polygynous groups are heavily sex biased.
Predation
The major predatory threat to the simakobu and to all Mentawai primates now is from humans, who first colonized the largest of the islands, Siberut, 2 3 kya (Nooy Palm 1968; cited in Whittaker 2005). There are currently no large felid predators on the Mentawais, although simakobu ancestors presumably faced this predation threat at some point (Yorzinski and Ziegler
92 2007). Despite their predominantly arborial lifestyle, behavioral studies document that the simakobu may flee on the ground when disturbed (Tilson 1977; Wilson and Wilson 1976). There is a relative paucity of large predators on the island of Borneo compared to Sumatra, Java and Peninsular Malaysia, which are (or were until recently) inhabited by tigers, leopards and wild dogs (Meiri et al. 2008b). Predation on juvenile proboscis by the clouded leopard has recently been documented, however (Matsuda et al. 2008). Its frequent river crossings also expose it to predation by crocodiles (Yeager 1991). Nonetheless, the greatest threats to the survival of the proboscis monkey are anthropogenic (Meijaard and Nijman 2000), as with the simakobu.
Reproduction
Simias is unique among Asian colobines in that receptivity is indicated by sexual swellings (Tenaza 1989). There is weak, if any, birth seasonality (Hadi et al. 2009), and gestation time is unknown for Simias . Based on data from young infants, neonatal mass is estimated at approximately 500 g (Hadi et al. 2009). The proboscis apparently has only weak birth seasonality, and gestation length is not well established (Gorzitze 1996; Kirkpatrick 2007). Neonatal mass in a single captive born male was reported by Rüedi (1981) as 600 g. Alloparental care is common (Kirkpatrick 2007).
Anatomy
Combining the few available mass data from museum records with masses collected from more recently wild shot animals (Hadi et al. 2009) yields mass estimates of 8.6 kg for adult simakobu males, and 6.4 kg for females. The proboscis monkey is substantially larger in body mass than the insular simakobu, with females averaging about 9.7 kg and males close to 20 kg. Because of these pronounced body size differences, along with the small island range of the simakobu monkey, I consider Simias concolor to be an example of derived island dwarfism, as suggested by Jablonski (1998:25). In all skeletal features except its tail and in its limb proportions, the simakobu can be seen as a smaller or dwarfed form of the proboscis monkey. The accumulation within Nasalis and Simias of uniquely derived states resulting from their apparently lengthy geographical separation and considerable independent evolution may have, effectively, “overprinted” the synapomorphies that may have united them to each other and to the other odd nosed colobines.
93 Brandon Jones (1996; 1998) stresses that many cranial and, especially, postcranial features of the proboscis and simakobu (which he considers congeneric) indicate that they evolved in a more open, terrestrial environment, rather than the lush rainforest to which they are presently confined. Their postcranial morphology he considers very macaque like, and notes that their dedication to folivory indicates an evolutionary history where seasonal climatic change would have favored the ability to eat mature (toxic) leaves (rather than depending on seasonal fruits and young leaves).
Phylogeny
The precise taxonomy of the genera Nasalis and Simias and their proper phylogenetic position have been the subject of considerable debate (Bigoni et al. 2003). Recent molecular studies confirm their close relationship (Sterner et al. 2006; Whittaker et al. 2006), which is also supported by morphological (Groves 1970) and ecological data (Bennett and Davies 1994). The simakobu monkey is usually classified in its own genus, Simias , although it is sometimes referred to as Nasalis concolor (e.g., Brandon Jones 1996), sharing a genus with the proboscis monkey. For the sake of clarity, I use the unique genus name ( Simias ) throughout this dissertation interchangeably with the common name, “simakobu.” Sterner et al. (2006) show molecular (mitochondrial DNA) support for a so called “odd nosed colobine” clade that includes the genera Nasalis (including Simias ), Rhinopithecus , and Pygathrix . They estimate that the divergence of the odd nosed monkeys from other Asian colobines occurred around 8.8 Ma, and that the three aforementioned odd nosed genera diverged from each other around 6.9 Ma (Figure 4.2). Whittaker et al. (2006) use mitochondrial data to demonstrate a sister taxon relationship between Nasalis and Simias . In other Asian colobines, species with a pairwise distance of 10% or less are considered congeneric. With a pairwise distance of about 6%, Simias and Nasalis could easily be combined into Nasalis on molecular grounds (Whittaker et al. 2006). The authors do not give an estimate of divergence time for the two species.
Fossil record
The fossil record for Nasalis and Simias is entirely lacking (Meijaard 2004). The most recent fossil primate that is likely to be relevant to this clade is Mesopithecus from Late Miocene Europe and Asia, which may be a sister group to the living odd nosed colobines (Jablonski 1998; Pan et
94 al. 2004). Jablonski argues for a Nasalis Mesopithecus Pygathrix Rhinopithecus clade based on the unique character combination of “primitive terrestrial limb proportions and highly derived, brachiator like characters of the pectoral girdle” (Jablonski 1998:27). Body mass is estimated for the genus Mesopithecus (European samples) at 6.5 12.5 kg for females, and 8.5 16 kg for males (Delson et al. 2000). Fossil postcrania attributed to Mesopithecus pentelicus are interpreted by Delson (1994) as indicative of locomotor adaptations similar to the semi terrestrial Hanuman langur ( Semnopithecus entellus ). The Miocene Pliocene colobine Dolichopithecus has been likened to extant Nasalis phenetically, in its long muzzle and narrow interorbital pillar (Delson 1994; Pan and Groves 2004).
Figure 4.2. Hypothesized phylogeny of the Asian colobines. Divergence dates (in millions of years ago) are estimates from Sterner et al. (2006), based on mitochondrial DNA sequence. Mesopithecus (extinct) has been inserted in its hypothesized position as a sister group to the living odd nosed genera (in bold ). Adapted from Sterner et al. (2006).
Hypotheses, approaches of this study
As outlined at the end of Chapter 3, the null hypotheses for interspecific comparisons in this chapter and the next derive from a model of ontogenetic scaling of the cranium in the dwarf
95 species. Thus, the null hypotheses being tested with respect to Simias and Nasalis are the following: 1) The simakobu (Simias ) has a larger neurocranium and orbits relative to its cranial size than does the proboscis monkey ( Nasalis ). 2) For its cranial size, the simakobu has a less prominent facial skeleton than the proboscis. 3) The two species share a coincident static cranial allometry. Stated otherwise, adult cranial shape is associated with size in a way common to both Simias and Nasalis . 4) The simakobu is more encephalized than the proboscis monkey.
To address these subjects, I begin by characterizing the static cranial allometry within each sex of each species, then examine the static allometry across adults of each species (this includes elements of both size related and sex related shape). Finally I assess the evolutionary allometry of adults across the two species by defining the shape differences between the taxa, and comparing their levels of encephalization. One issue that bears mentioning is the degree of uncertainty surrounding the polarity of various character states in the Nasalis Simias lineage, including ancestral body size. For instance, even if the simakobu has a smaller body mass than its forebears, it is possible that the proboscis—as the largest living colobine—may be larger in body mass than the Nasalis Simias last common ancestor (LCA). Nevertheless, “… the nature of the morphological transformations determined through these studies of allometry and heterochrony remains unaltered” by the as yet unknown ancestral character states (Shea 1992:286). The evolutionary processes responsible for phenotypic variation among related species are the same, independent of which traits are primitive or derived (Klingenberg 1998).
Analysis of Nasalis & Simias morphology
Before considering in detail the static and evolutionary allometries related to this lineage, it is useful to point out the basic physical differences between the species that are visible to the naked eye. The most striking aspects of cranial morphology in this branch of the odd nosed monkeys are (1) Nasalis is considerably larger than Simias , (2) Nasalis is much more sexually dimorphic in size and soft tissue shape than Simias , and (3) the most obvious component of shape
96 distinguishing adult male Nasalis from juvenile and female Nasalis , and from all Simias , is the pendulous nose.
Static allometry in Simias females
There is a general lack of cranial allometry in Simias females, as summarized in Table 4.1. The null hypothesis of independence between shape (as all Procrustes shape coordinates) and (centroid) size cannot be rejected. The first and second principal components of shape variation in the sample (representing about 45% of total shape variation, combined) are not correlated with size. Similarly, separation of individuals along the first principal coordinate (PCO1) in a Principal Coordinates (PCOORD) Analysis of scaled linear distances (using geometric mean) is also uncorrelated with size (as geometric mean). For all EDMA analyses of Simias and Nasalis , distances with a mean less than 10 mm in the smallest group ( Simias females) were not considered, to reduce the effects of measurement error. This reduced the number of pairwise linear distances from 990 to 966 distances.
Table 4.1. Evidence for overall cranial allometry in simakobu females (n=15).
Proportion of total Proportion of variance Associated p-value Shape component variance explained in component against null hypothesis by component explained by size of no allometry All Procrustes coordinates 100% 7.51% 0.336 PC1 of Procrustes PCA 30.8% 2.92% 0.546 PC3 of Procrustes PCA 10.0% 30.0% 0.0374* PCO1 of EDMA PCOORD 26.6% 0.860% 0. 742 Analysis * Significant at the p < 0.05 level.
Weak cranial allometry in Simias females is detectable in PC3 of a Procrustes PCA. Thirty percent of variance along this axis can be explained by size, and a permutation test confirms the size dependence of PC3 score. To visualize the differences in shape associated with cranial size in this sample, the predicted shapes from a multivariate regression of all Procrustes coordinates on centroid size were used to create 3D surfaces. The predicted landmark configurations for the largest and smallest individuals in the sample, scaled to equal centroid size, are compared in Figure 4.3. Larger individuals appear to have more projecting premaxillae than
97 smaller individuals. The palate of larger females is slightly deeper posteriorly, creating a subtly more airorhynch facial profile compared to smaller individuals—that is, the plane of the palate is inclined such that the posterior nasal spine is more inferior relative to the anterior nasal spine. Width of the lateral orbital pillars (between left and right fronto zygomatic junction) is somewhat narrower in larger relative to smaller simakobu females.
Figure 4.3. Visualization of predictions for Simias female large and small extremes. Shown in red is the predicted shape for the cranium with largest centroid size in the sample. In yellow is the shape predicted for the smallest cranium in the sample. All visualizations of the simakobu were created from a surface scan of AMNH 103371 (female), kindly provided by Prof. E. Delson.
Within Simias females, endocranial volume (ECV) is not significantly correlated with centroid size of the whole cranium, nor with CBL (Table 4.2). As for head body allometry, the correlation between HBL and cranial size (as CS or as CBL) is only of borderline significance. Orbital size (OD) and ECV are not significantly correlated. There is a stronger relationship between orbital size and CS, but it is not statistically significant.
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Table 4.2. Correlation between components of the cranium and body in Simias females. Centroid size calculated from a 43 landmark configuration (rather than the 45 used in morphometric analyses) is used for correlation tests throughout this chapter to maximize sample sizes. For correlations with r values < 0.2 or p values > 0.2, table entry is “not significant” (n.s.). cbrt(ECV) = cube root ECV. cbrt( ECV ) OD CS CBL OD n.s. - - - CS r=0.377, r=0.433, - - p=0.166 p=0.107 CBL n.s. n.s. r=0.835*, - p<0.001 HBL n.s. r=0.511 †, ρ=0.632* ‡, ρ=0.599* ‡, p=0.0741 p=0.0230 p=0.0331 * Denotes that correlation value is significant at the p < 0.05 level. † Spearman’s ρ=0.555, p=0.0512; Kendall’s τ =0.436, p=0.0422. ‡ Standard r value not significant; Kendall’s τ =0.410, p=0.0573.
Static allometry in Simias males
In contrast to females of the species, significant cranial allometry was found within the sample of Simias males. Over 20% of shape variance is explained by size in a multivariate regression of all Procrustes coordinates on centroid size (Table 4.3). The first Principal Component of a Procrustes PCA is also significantly correlated with size. Similarly, the first Principal Coordinate in an EDMA ordination procedure (distances scaled by geometric mean) is correlated with geometric mean at the p < 0.05 level.
Table 4.3. Evidence for cranial allometry in Simias males (n=10).
Proportion of total Proportion of variance Associated p-value Shape component variance explained in component against null hypothesis by component explained by size of no allometry All Procrustes coordinates 100% 22.3% 0.0090* PC1 of Procrustes PCA 31.4% 61.7% 0.0076* PCO1 of EDMA PCOORD 33.1% 43.3% 0.0387* Analysis * Significant at the p < 0.05 level.
In a visualization of shapes predicted for the largest and smallest Simias male crania (Figure 4.4), we see that larger individuals have more projecting premaxillae, similar to the case in females. In profile, the palate appears to be deeper and more airorhynch in larger individuals relative to smaller ones, and the nasal bones longer. The difference in relative breadth of the
99 zygomatic arches, orbital margins and neurocranium is pronounced, with larger individuals having an overall narrower cranium than smaller ones.
Figure 4.4. Visualization of predicted shapes for Simias male large (red) and small (yellow) extremes. Because no surface scan of a male simakobu was available, all Simias visualizations are based on the female scan in Figure 4.3.
In a (scaled) distance based principal coordinate analysis, the distances most correlated with separation along the first principal coordinate axis are those connecting VSJ and PNS with other landmarks and with each other. This is consistent with the increased palatal depth of larger males indicated by the regression prediction, suggesting a relatively elongated connection between the cranial base and the posterior palate.
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Figure 4.5. Distribution of head-and-body length (HBL) in simakobu males, showing outlier. Boxplot indicates median and 1 st and 3 rd quartiles for the sample, with whiskers extending to maximum and minimum values (outliers excepted).
The largest male in terms of size of the cranium (AMNH 103367) is an outlier in this sample in terms of head and body length (Figure 4.5). As this individual was wild shot at the same time and location as seven of the other nine male Simias , and the sample size is already small, I do not see a justifiable reason to exclude this specimen from the analyses (very few of which include the HBL variable, anyway). Furthermore, this individual is not an outlier in any other metric considered here.
Table 4.4. Correlations between components of the cranium in Simias males. See Table 4.2 caption for explanation. HBL had no significant correlation with any other variable. cbrt( ECV ) OD CS OD r=0.501, - - p=0.140 CS r=0.917*, r=0.532, - p<0.001 p=0.113 CBL r=0.923*, r=0.513, r=0.987*, p<0.001 p=0.107 p<0.001 * Significant at the p < 0.05 level.
101 In surprising contrast to the statistical independence of brain size and overall cranial size in females, brain size (as cube root ECV) correlates tightly with cranial size (as CS and CBL) in simakobu males (Table 4.4, Figure 4.6). This is the opposite pattern from what is expected in species with significant cranial dimorphism. Typically, the most dimorphic areas of the male primate cranium are related to facial length and robusticity, (often) flaring of the zygomatic arches, and in larger species, cresting/ridging of muscle attachment areas. Neurocranial size tends to be less dimorphic, resulting in a relatively smaller neurocranium in males compared to overall cranial size. Thus, we would predict that ECV should be less closely correlated with overall cranial size in males than in females of a dimorphic species. In Simias , we find that even though ECV is smaller relative to cranial size in males than in females (Table 4.5), ECV and cranial size are tightly correlated in males and only loosely correlated (not statistically significant) in this sample of females.
4.1
4.05
4 R² = 0.8418 3.95
3.9
3.85 cbrt(ECV) 3.8 R² = 0.1422 3.75 Simias M 3.7 Simias F 3.65
3.6 180 185 190 195 200 205 210 215 CS (43 landmarks)
Figure 4.6. Cube root ECV plotted as a function of centroid size for female and male simakobus. Notice the discrepancy in how tightly the male sample fits the corresponding ordinary least squares regression line compared to the female sample.
As in female simakobu, orbital diameter and ECV are not significantly correlated in males. The relationship between orbital size and CS is comparable between the sexes. HBL is
102 not significantly correlated with any cranial metric considered (with or without the above mentioned outlier (Figure 4.5) included).
Simias static allometry & sexual dimorphism
Despite their typical body mass differences, male and female Simias overlap to some extent in size and shape of the cranium (Figure 4.7, Figure 4.8). The mean size and shape for males and females differ significantly, however (Figure 4.7, Table 4.5). The average interlandmark distance in males is only about 7.64% larger than the corresponding distance in females. centroid size centroid 180 200 220 240 260 Sc F Sc M Nl F Nl M
Figure 4.7. Centroid size of the cranium in the complete Simias (Sc) and Nasalis (Nl) sample. To maximize sample size, CS is based on a 43 landmark configuration, as opposed to the 45 landmarks used in form and shape analyses. Note the Nasalis male outlier (arrow), discussed in the text.
103
0.045
0.025
0.005
PC 2 2 (13.1%) PC -0.015
-0.035 Simias M Simias F -0.055 -0.05 -0.04 -0.03 -0.02 -0.01 0 0.01 0.02 0.03 0.04 0.05 PC1 (22.2%)
Figure 4.8. The first two PCs of shape variation in Simias .
The male simakobu cranium differs in shape from females in its more projecting premaxilla, slightly wider zygomatic arches, and relatively less inflated neurocranium (Figure 4.9). These features are evident both in EDMA Shape tests and in Procrustes superimposition of mean forms. Interestingly, the nasal bones (nasion to nasale) are not significantly longer in males than in females, on average.
Figure 4.9. Male (darker green) and female (lighter green) simakobu mean shapes. Representations of the mean shapes for the male and female Simias samples, warped from the female surface scan, and scaled to equal centroid size.
104 As expected, the orbits account for a larger proportion of cranial size in females than in males (Table 4.5), which is visible in the mean shape visualizations. The relative size of the orbits compared to brain size (cube root ECV) is about equal in the two sexes, however.
Table 4.5. Sexual dimorphism in the simakobu cranium. The range and mean values for each variable are given for females and males. For ease of display in the table, the two ratios involving CS were multiplied by 100. Mean values that differ significantly between the sexes (as determined by t tests) are denoted by indicating the sex with the larger mean size. Otherwise, lack of significance is indicated by “no.” Simias concolor Range Mean Significant Female Male Female Male CS (43 landmarks) 182 -198 196 -213 190 204 M > F OD (mm) 19.9 -22.1 20.7 -22.5 20.9 21.7 M > F ECV (mL) 48.0 -58.0 53.0 -66.0 53.2 60.0 M > F cbrt(ECV)/CS ratio (x 100) 1.88 -2.06 1.88 -1.96 1.98 1.91 F > M OD/cbrt(ECV) ratio 5.17 -5.86 5.36 -5.75 5.57 5.55 no OD/CS ratio (x 100) 10.4 -11.6 10.0 -11.0 11.0 10.6 F > M
Static allometry within Simias
A MANCOVA does not detect a significant difference in slopes between the male and female samples (for 95% of shape variance, PCs1 18: F=2.450; df=18,4 ; p=0.200). Thus, we cannot reject the hypothesis that the sexes have parallel static allometries. Given the small samples (n=10 males, 15 females), and that independent regressions of Procrustes coordinates on CS within each sample show that static allometry is not significant within females and is significant within males, this MANCOVA result should be viewed with caution. Figure 4.10 illustrates the “messiness” of the PC1 CS relationship in the simakobu.
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0.05 0.04 0.03 0.02 0.01 0 -0.01 PC 1 1 score PC -0.02 -0.03 Simias M -0.04 Simias F -0.05 185 190 195 200 205 210 215 220 225 230 CS
Figure 4.10. The relationship between PC1 and CS in a pooled-sex PCA of Simias .
Nonetheless, in the absence of significantly different slopes, we can test for coincident slopes. That is, we seek to determine whether sex has a significant effect on cranial shape independent of size. The results of this step of testing are difficult to interpret. When including 95% of total shape variance, a MANCOVA cannot reject the null hypothesis of coincident allometric trajectories (PCs1 18: F=3.637; df=18,5; p=0.0791). Note, however, that the p value here approaches significance at the 0.05 level. Depending upon what proportion of the total variance (i.e., number of PCs) is included in the analysis, the p value fluctuates above and below the significance cut off. I suspect that the combination of small sample sizes and weak overall size shape correlations are responsible for the inconsistent results. Thus, in the general linear model used for the MANCOVA, the inclusion of the “sex” covariate sometimes produces a better shape prediction, and sometimes not, depending on the number of shape variables included.
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Figure 4.11. Visualization of predicted shapes for largest and smallest female Nasalis . The large size extreme shape is shown in red, and the small size extreme in yellow. All visualizations of the proboscis were created from a surface scan of AMNH 103669 (female), kindly provided by Prof. E. Delson.
Static allometry in Nasalis females
The female proboscis cranium displays relatively weak overall allometry. A multivariate regression of all Procrustes coordinates on CS is significant, but size only explains about 5% of variance in shape coordinates (Table 4.6). Regression of the first two PCs of a Procrustes PCA on CS does not yield significant evidence of dependence, although 13.7% of variance in PC3 can be explained by size variation. None of the first three PCOs of a PCOORD of scaled linear distances was correlated with geometric mean. To visualize which aspects of cranial shape are influenced by size, predicted shapes representing the largest and smallest female Nasalis crania are presented (Figure 4.11). Here we see that larger individuals have slightly shorter nasal bones relative to their overall cranial size, and narrower orbital pillars and zygomatic arches. As with simakobu females (Figure 4.3), smaller proboscis females have a more orthognathic facial profile than larger individuals.
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Table 4.6. Evidence of cranial allometry in Nasalis females.
Proportion of total Proportion of variance Associated p-value Shape component variance explained in component against null hypothesis by component explained by size of no allometry All Procrustes coordinates 100% 5.12% 0.0031* PC1 of Procrustes PCA 11.2% 2.70% 0.330 PC3 of Procrustes PCA 8.89% 13.7% 0.0253* PCO1 of EDMA PCOORD 12.9% 0.608% 0.651 Analysis * Significant at the p < 0.05 level.
Endocranial volume shows some correlation with CS and CBL in proboscis females, but the association does not reach statistical significance (Table 4.7). Centroid size and CBL are tightly correlated with each other. Orbital diameter and cranial size are correlated, but the statistical significance of this association is quite weak, depending on the correlation measure and size measures employed. Orbital diameter and ECV are not significantly correlated. HBL is not significantly correlated with any cranial measures considered (i.e., CS, CBL, ECV).
Table 4.7. Correlation between cranial components in Nasalis females.
cbrt( ECV ) OD CS OD n.s. - - CS r=0.307 †, r=0.344* ‡, - p=0.0687 p=0.0371 CBL r=0.307 †, r=0.404* †, r=0.947* †, p=0.0687 p=0.0131 p<0.001 † Correlation and p values similar using Spearman’s and Kendall’s rank correlation methods. ‡ Correlation not significant using Spearman’s and Kendall’s rank correlation methods, p≈0.08.
Static allometry in Nasalis males
Outlier
A boxplot of centroid size in the Nasalis Simias samples indicates a clear outlier in cranial size among proboscis males (Figure 4.7). Specimen notes taken at the time of data collection do not indicate that this individual (AMNH 103471) appeared abnormal in any way, nor that it had anything other than fully adult male dentition. Plots from a PCA of Procrustes coordinates and from PCOORD of linear distances (Figure 4.12) reveal that this individual groups squarely within
108 female proboscis in terms of cranial shape. It has been shown that the proboscis male achieves cranial size dimorphism primarily through an extended growth period relative to females (sexual bimaturism) along a common ontogenetic trajectory (Ravosa 1991b). Additionally, subadult proboscis males of adult size but lacking fully developed secondary sexual characteristics have been observed in the wild (Bennett and Sebastian 1988). Given this evidence, I conclude that the most likely reason for the small overall cranial size of this individual is that it had not yet completed its cranial growth (despite its adult dentition) or, less plausibly (considering the striking canine size dimorphism in Nasalis ), that its sex was misidentified in museum records and by myself. For these reasons, I exclude it from all analyses.
109
1.5
1
0.5
0
PCO Axis Axis PCO 2 (8%) -0.5
-1 Nasalis M Nasalis F -1.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5 2 PCO Axis 1 (27%)
1.5
1
0.5
0
-0.5 PCO Axis Axis PCO 2 (8%)
-1 Nasalis M Nasalis F -1.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5 2 PCO Axis 1 (28%)
Figure 4.12. Principal coordinates 1 and 2 of all Nasalis with outlier included (above) and removed (below). Linear distances for each individual are scaled by the geometric mean. Arrow indicates male outlier.
Despite their strikingly dimorphic cranial morphology, cranial allometry within Nasalis males is relatively weak, consistent with results in the simakobu and proboscis female samples. Less than 6% of variance in the aggregate of Procrustes coordinates is explained by size (Table 4.8). Visualization of the predicted shapes at the large and small ends of the size range indicates
110 that the plane of the face is rotated in larger proboscis males relative to smaller ones such that the orbits are more posteriorly positioned and the premaxilla is more projecting (Figure 4.13). In contrast to the case in Simias , this prognathism does not apparently correspond to increased airorhynchy in larger individuals. Indeed, the palate is shallower posteriorly in larger compared to smaller males. Although the orbital pillars are relatively narrower in larger individuals, proboscis males depart from the pattern seen in the other three groups in that larger individuals have relatively wider zygomatic arches than smaller individuals.
Table 4.8. Evidence of static allometry in the male proboscis cranium.
Proportion of total Proportion of variance Associated p-value Shape component variance explained in component against null hypothesis by component explained by size of no allometry All Procrustes coordinates 100% 5.84% 0.146 PC1 of Procrustes PCA 16.9% 13.8% 0.0798 PC3 of Procrustes PCA 9.54% 15.2% 0.0649 PCO1 of EDMA PCOORD 16.7% 1.37% 0.594 Analysis PCO2 of EDMA PCOORD 11.3% 14.4% 0.0739 Analysis PCO3 of EDMA PCOORD 9.27% 14.7% 0.0714* Analysis * A Kendall’s rank correlation test yields a significant τ =0.296, p=0.0498.
Figure 4.13. Predicted shapes for largest and smallest male Nasalis . Large size extreme in red; small extreme in yellow. Because no surface scan of a male proboscis was available, all Nasalis visualizations are based on the female scan in Figure 4.11.
111 Although the correlation is not as strong as in simakobu males, ECV and CS are significantly correlated in proboscis males (Table 4.9). This finding mimics the counterintuitive situation described earlier for the simakobu, where the volume of the endocranial cavity is strongly correlated with overall cranial size in males, despite the fact that this volume represents a significantly smaller proportion of the cranium in males than in females. The discrepancy between males and females in terms of this ECV CS correlation is less pronounced in Nasalis than in Simias , however (Figure 4.14). Orbital diameter and CS are significantly correlated (Table 4.9). As reported for the previous groups, orbital diameter and ECV are not significantly correlated in proboscis males. HBL is not significantly correlated with any cranial metric considered.
Table 4.9. Correlation between cranial components in proboscis males.
cbrt( ECV ) OD CS OD n.s. - - CS r=0.644*, r=0.532*, - p<0.001 p<0.001 CBL r=0.636*, r=0.211, r=0.932*, p<0.001 p=0.246 p<0.001 * Significant at the p < 0.05 level.
5
4.9 R² = 0.4319 4.8 4.7 4.6
cbrt(ECV) 4.5 4.4 R² = 0.0965 Nasalis M 4.3 Nasalis F 4.2 200 210 220 230 240 250 260 270 CS (43 landmarks)
Figure 4.14. Cube root ECV plotted as a function of CS for female and male proboscis. Compared to the same plot for Simias (Figure 4.6), male and female Nasalis have more similar correlation values. Even with sample sizes more than double what is available for the simakobu, there is nonetheless evidence for a discrepancy between proboscis males and females in terms of the ECV CS association.
112 Nasalis static allometry & sexual dimorphism
In contrast to Simias , the sexes of adult Nasalis overlap neither in body mass nor cranial size, differing by an average of 17.6% in linear dimensions of the cranium. As is typical in highly dimorphic cercopithecoids, Nasalis males differ most from females in projection of the lower facial skeleton, resulting in a more prognathic male face (Figure 4.15). Compared to males, the female proboscis has a more domed cranial vault, relatively large orbits, and a relatively wider cranium.
Figure 4.15. Nasalis male and female mean shapes. Female mean shape is depicted in light orange, and male mean shape in darker orange.
Proboscis males are significantly larger than females in all but two of 966 linear distances considered, in absolute terms. Distances within the neurocranium differ the least in absolute length, while distances connecting the maxillary alveolus to the face and cranial base differ the most—up to over 35% larger in males. The nasal bones are also among the most dimorphic features, at about 31% longer in males than females. As suggested by shape comparisons, the orbits and ECV are larger relative to cranial size in females than in males (Table 4.10). The relative size of the orbits compared to ECV does not differ significantly between the two sexes.
113
Table 4.10. Sexual dimorphism in the proboscis cranium. Variables and notation as in Table 4.5. Nasalis larvatus Range Mean Significant Female Male Female Male CS (43 landmarks) 205 -228 238 -263 215 254 M > F OD (mm) 21.1 -23.8 22.8 -27.0 22.7 24.4 M > F ECV (mL) 77.5 -97.0 95.0 -120 86.5 105 M > F cbrt(ECV)/CS ratio (x 100) 1.96 -2.14 1.76 -1.96 2.06 1.86 F > M OD/cbrt(ECV) ratio 4.87 -5.45 4.80 -5.89 5.12 5.17 no OD/CS ratio (x 100) 9.91 -11.4 8.86 -10.1 10.5 9.57 F > M
Coincident static allometry in the sexes
Sex specific static allometries do not differ significantly in slope (for 95% of shape variance, PCs 1 34: F=0.798; df=34,22; p=0.729). Furthermore, their trajectories are coincident, regardless of what proportion of shape variation is included in the analysis (PCs 1 34: F=1.254; df=34,23; p=0.286). This implies that Nasalis individuals, insofar as cranial landmark data and these sample sizes can capture, all follow a common static adult allometry. PC1 allometric trajectories are illustrated in Figure 4.16.
0.06
0.04
0.02
0 PC1 PC1 score -0.02
-0.04 Nasalis M Nasalis F -0.06 210 220 230 240 250 260 270 280 290 CS (45 landmarks)
Figure 4.16. The relationship between PC1 and CS in a pooled-sex PCA of Nasalis .
114 Evolutionary allometry of the Nasalis-Simias lineage
I now attempt to build upon what has been established in terms of cranial allometry within each sex and species to construct a basic outline of allometry through this branch of the odd nosed monkeys. As cranial shape and proportion differ significantly between the sexes of both species, this construction begins with female female comparisons, then male male comparisons, and finally attempts to identify common threads that characterize this Nasalis Simias clade.
Simias & Nasalis females
Form
Females of the two species are more similar in form (= size and shape aspects) than are males of the two species, although they do not overlap in range of cranial size (Figure 4.7). The crania of female Nasalis are absolutely larger than Simias by about 13% in linear measures, on average (Table 4.11). The largest absolute differences are in distances within the cranial base and those projecting to nasale (tip of nasal bones). Mainly these give the impression of an expanded floor of the neurocranium in Nasalis relative to Simias . Distances that are not significantly larger in Nasalis (in absolute terms) are zygomatic height (ZMI ZMS), and upper face height (nasion infraorbital foramen).
Table 4.11. Comparison statistics of females in the two species. Statistics 1 through 6 are as defined in Table 4.5. RBS (relative brain size) is calculated as ECV (mL) divided by body mass (g) (where available). Range Mean Significant Simias Nasalis Simias Nasalis CS (43 landmarks) 182 -198 205 -228 190 215 Nl > Sc OD (mm) 19.9 -22.1 21.1 -23.8 20.9 22.7 Nl > Sc ECV (mL) 48.0 -58.0 77.5 -97.0 53.2 86.5 Nl > Sc cbrt( ECV )/CS ratio (x 100) 1.88 -2.06 1.96 -2.14 1.98 2.06 Nl > Sc OD / cbrt( ECV ) ratio 5.17 -5.86 4.87 -5.45 5.57 5.12 Sc > Nl OD /CS ratio (x 100) 10.4 -11.6 9.91 -11.4 11.0 10.5 Sc > Nl RBS (ECV/Mass) (x 100) 0.81 -0.82 0.79 -0.11 0.814 0.907 Nl > Sc cbrt (ECV )/HBL ratio (x 100) 0.68 -0.82 0.69 -0.92 0.727 0.772 Nl > Sc CBL/HBL ratio (x 100) 13.4 -15.9 13.1 -17.0 14.2 14.7 Nl > Sc
115 Shape
Most of the distances in which Simias females are relatively larger than Nasalis females are related to the landmark zygomaxillare inferior (ZMI). Distances connecting this point to many cranial base landmarks (vomer sphenoid junction, basion, foramen ovale, carotid canal, opisthion, hypoglossal canal) are relatively longer in Simias , as is the bilateral ZMI width. As suggested by the prominence of the simakobu’s orbits in mean form visualizations (Figure 4.17), biorbital width (between the frontozygomatic junction on the lateral orbital rim) is relatively larger in Simias females. Distances that are not significantly different in length relative to cranial size (measured as geometric mean) between females of the two species include nasale to ZMI and to vomer spenoid junction (VSJ), height from ZMI to fronto zygomatic junction (on the ipsilateral side), and incisive foramen to carotid canal.
Figure 4.17. Female mean shapes. Simias female mean in green, and Nasalis in orange.
Nasalis is relatively larger in many distances with an endpoint at bregma (bregma to nasion, nasale, posterior nasal spine, interdentale superior, incisive foramen, VSJ, lambda). Interestingly, distances related to premaxillary projection are not heavily implicated in shape differences between females of the two species, which is consistent with the only slight projection of the proboscis premaxilla beyond the simakobu in the mean form visualizations. The width between right and left TSCR is relatively larger in Nasalis , and the TSCR TZJ distance relatively smaller, indicating a shallower temporal fossa in Nasalis than Simias . This same pattern holds for males of the two species, and is discussed further below.
116 Ratios
The ratios presented in Table 4.11 reinforce and extend the results of the form and shape analyses. Orbital diameter in Simias females is clearly larger relative to both cranial size (CS) and ECV than in Nasalis . Endocranial volume is relatively smaller in Simias , compared to cranial size, to body mass, and to HBL.
Parallel static allometry in females
A MANCOVA did not detect a significant difference in the slopes of static allometry between females of the two species (for 95% of shape variance, PCs1 31: F=1.029; df=31,17; p=0.490). That is to say, the relationship between shape and size was not affected by species affiliation in a significant way—the hypothesis of parallel static cranial allometry in females of the two species cannot be rejected. The second step of MANCOVA testing confirmed what is implied by the PC1 CS plot in Figure 4.18–the two allometric trajectories are not coincident (PCs1 31: F=6.026; df=31,18; p<0.001). Furthermore, Figure 4.18 illustrates that the major axis of shape variation in the interspecific female sample is not size related.
0.08
0.06
0.04
0.02
0 PC1 score PC1
-0.02 Nasalis F -0.04 Simias F
-0.06 190 195 200 205 210 215 220 225 230 235 240 CS (45 landmarks)
Figure 4.18. The relationship between PC1 score and CS in females of the two species (from a pooled-sample PCA).
The fact that female static allometries are not coincident in these species means that the female Simias cranium is not just a “scaled down” Nasalis cranium. Size correlated shape in females of the two species is similar, as their slopes do not differ significantly, but the trajectories
117 have different y intercepts. This phenomenon—sometimes called transpositional allometry or grade shifting—has often been noted in allometric studies (Martin 1990; Steudel 1982; Weston and Lister 2009) (see also page 44). Figure 4.19 represents the predicted (hypothetical) shape of a Nasalis female at the mean size of Simias females, following the static allometric trajectory of Nasalis adult females (see Chapter 2, page 43, for details). This visualization serves two purposes. First, to emphasize that even though females of the two species seem to have parallel static allometric slopes, they nonetheless do not share a coincident allometric path. The allometric trajectories have different y intercepts, reflecting basic differences in cranial shape between the species. The second purpose is to use this extreme size extrapolation to highlight what these basic shape differences are. Female Nasalis at a Simias size has an extremely inflated neurocranium, short face, but still prominent nose, relative to the Simias mean shape.
Figure 4.19. Hypothetical Simias -sized female Nasalis . Hypothetical Nasalis shape in orange compared to Simias mean shape in green.
Simias & Nasalis males
Form
Male Nasalis are significantly larger than male Simias in virtually every dimension of the cranium (962/966 distances considered). The crania of male Nasalis are absolutely larger than male Simias by about 24% in linear measures, on average. Distances not significantly larger in male Nasalis are TSCR TZJ (a measure of lateral projection of the zygomatic arch from the temporal fossa, discussed later) and lambda to asterion. Many of the largest absolute differences share endpoints at nasale and zygomaxillare superior, indicating nasomaxillary expansion in
118 Nasalis , unsurprisingly. Length of the nasal bones (nasion to nasale) is over 50% larger in male Nasalis . The distance from bregma to lambda is about 35% larger in Nasalis than Simias males, comparable to the difference between females of the two species ( Nasalis 30% larger).
Figure 4.20. Male mean shapes. Simias male in green, and Nasalis male in orange.
Shape
Simias males are relatively larger in many distances connecting to the frontozygomatic junction (FJZ) (e.g., FZJ basion, FJZ to contralateral EAM and TZJ), including biorbital width, as seen in the female comparison above. The Simias male cranium is more brachycephalic overall, with relatively wider set zygomatic arches and auditory meatuses, while the Nasalis male is more dolichocephalic in comparison (Figure 4.20). The palate of Nasalis males projects further forward on the cranial base, and is slightly more airorhynch than in Simias , as evidenced by relatively longer distances connecting PNS to VSJ, to FO, to BOS, and to TSCR. Several within palate distances are similar in proportion in males of the two species, such as the distance between the premaxillary maxillary sutures (PMMX), and the length from intradentale superior (IDS) to VSJ. Nasalis males are relatively larger in distances connecting nasale to bregma, to lambda, to foramen ovale, and to nasion. As noted for females, Nasalis males have a relatively broader cranial base between right and left TSCR, and a relatively short distance between TSCR and TZJ, so that the temporal fossa is shallower compared to Simias (although this is not obvious in the mean shape visualizations).
119
Table 4.12. Comparison statistics for males of the two species. Definitions as in Table 4.11. Range Mean Significant Simias Nasalis Simia s Nasalis CS (43 landmarks) 196 -213 238 -263 204 254 Nl > Sc OD (mm) 20.7 -22.5 22.8 -27.0 21.7 24.4 Nl > Sc ECV (mL) 53.0 -66.0 95.0 -120 60.0 105 Nl > Sc cbrt( ECV )/CS ratio (x 100) 1.88 -1.96 1.76 -1.96 1.91 1.86 Sc > Nl OD / cbrt( ECV ) ratio 5.36 -5.75 4.80 -5.89 5.55 5.17 Sc > Nl OD /CS ratio (x 100) 10.0 -11.0 8.86 -10.1 10.6 9.57 Sc > Nl RBS (ECV/Mass) (x 100) 0.74 -0.75 0.40 -0.59 0.742 0.518 Sc > Nl cbrt( ECV )/HBL ratio (x 100) 0.63 -0.77 0.59 -0.80 0.706 0.667 Sc > Nl CBL/HBL ratio (x 100) 13.3 -16.2 12.5 -17.3 14.6 14.8 no
Ratios
The comparative statistics in Table 4.12 reinforce the above results, but differ from the female comparisons in some significant ways. The orbits in Simias males remain consistently large relative to CS and to ECV, as in females. However, the relative size of the endocrinal cavity in male Simias is larger than in male Nasalis (see ECV/CS and ECV/HBL ratios, RBS), reversing the case in females of the species. This finding is in accordance with encephalization comparisons (discussed below), where Simias males have small ECV for their body mass, but Nasalis males have even smaller ECV for their bulky bodies.
Parallel static allometry in males?
The MANCOVA results are more difficult to interpret than was the case for the females, as the significance of the interaction term (size × species) depends on the proportion of shape variance included in the analysis. When more than the first six PCs are included (i.e., PCs 1 7+, ~72%+ of shape variance), there is no statistically significant affect of species affiliation on the size shape relationship (for 95% of shape variance, PCs1 22: F=2.643; df=22,8; p=0.0792). This is also the result when less than 59% of shape variation is included (PCs 1 3: F=2.390; df=3,27; p=0.0908), indicating no significant difference in slope of the static allometries. However, within the window of ~60 70% of shape variation included (corresponding to the first four, five or six PCs), the MANCOVA does detect a significant affect of species membership on the cranial size shape relationship (i.e., the null hypothesis of parallel allometry is rejected at the p<0.05 level) (PCs1 6: F=2.541; df=6,24; p=0.0477).
120
0.08 0.06 0.04 0.02 0
PC1 score PC1 -0.02
-0.04 Nasalis M -0.06 Simias M -0.08 200 210 220 230 240 250 260 270 280 CS (45 landmarks)
Figure 4.21. The relationship between PC1 score and CS in males of the two species (from a pooled- sample PCA).
I suspect that the inconclusive results arise not only from the small simakobu male sample size (n=10), but also from the lack of statistically significant overall cranial allometry in the male proboscis. Considering up to ~59% of shape variance, the allometric slope of proboscis males is too weak to be well defined (see relationship of PC1, 37% of shape variance, with CS in Figure 4.21). By adding some of the less important components of shape variation (captured by PCs 4 6), statistically significant species differences in static allometry become detectable. The power of this type of test is limited by sample size relative to the number of response (shape) variables, and so the ability to reject the null hypothesis of parallel size effects on shape is lost as more variables (and, consequently, more cumulative shape variance) are included in the analysis. That the MANCOVA results are consistent in females regardless of how many PCs are included suggests that the test is not strongly affected by sample size in that instance. With only ten male Simias individuals, sample size is a limiting factor in testing allometry between males of the two species, however. Insofar as results of the first MANCOVA indicate allometries not significantly different in slope, we can test for coincident allometric trajectories. Over most of the regions of shape variance where the null hypothesis of parallel allometries is not rejected, the second MANCOVA indicates that the trajectories are not coincident (PCs1 3: F=4.067; df=3,28; p=0.0162; PCs1 7: F=2.985; df=7,24; p=0.0211; PCs1 18: F=2.632; df=18,13; p=0.0405). When more than 92% of the total shape variance is included, however, the null hypothesis of coincident allometries cannot be rejected (for 95% of variance, PCs1 22: F=2.513; df=22,9; p=0.0772).
121 Figure 4.22 represents the predicted (hypothetical) shape of a Nasalis male at the mean size of Simias males, following the static allometric trajectory of Nasalis adult males. As with the hypothetical small Nasalis female, this visualization demonstrates that males in the two species do not share a coincident allometric path, even if the slopes of their static allometries are similar. In contrast to the female version of this rendering, the hypothetical male Nasalis has a very prominent upper face and orbits, while the neurocranium is not drastically inflated relative to the Simias mean shape.
Figure 4.22. Hypothetical Simias -sized male Nasalis .
Composite cranial allometry of the lineage
There are few cranial shape traits that show a consistent allometric trend relative to cranial size within this lineage as a whole. The orbits are consistently more prominent in smaller individuals across the two genera—as would be expected for a neural component—while the neurocranium is not, due to the peculiarly small endocranial volume of the smaller species, Simias . Larger individuals tend to be more prognathic consistently across the lineage, although this prognathism does not appear to be consistently associated with palatal angulation (airorhynchy/ klinorhynchy).
Parallel static allometry
Formal testing of static allometry between the species using MANCOVA is inconclusive. The (pooled sex) species static allometries are not significantly different from parallel for up to 78% of shape variance (PCs1 14: F=1.750; df=14,67; p=0.0659). Beyond 78%, the results oscillate between significant or not with increasing proportions of the shape variance included. For this
122 top 78% of the shape variance, the second MANCOVA clearly rejects the null hypothesis that the allometric trajectories of the two species are coincident (PCs1 14: F=57.44; df=14,68; p=0.00). Indeed, the plot of PC1 score on CS (Figure 4.23) suggests that the main axis of shape variation among individuals in the Nasalis Simias clade represents a classic case of transpositional allometry—their trajectories are not coincident .
0.08
0.06
0.04
0.02
0
PC1 score PC1 -0.02
-0.04 Nasalis -0.06 Simias -0.08 180 190 200 210 220 230 240 250 260 270 280 CS (45 landmarks)
Figure 4.23. The relationship between PC1 score and CS in the two species (from a pooled-sample PCA).
Encephalization
The unusual neurocranial proportions of this lineage in concert with the discrepancy in degree of sexual dimorphism in the two species make comparing encephalization especially difficult. The encephalization quotient (EQ, using Eisenberg’s equation) calculated for male Nasalis (~1.23) is somewhat lower than for male Simias (EQ ≈ 1.34), but for females of the two
species, Nasalis is unquestionably more encephalized (EQ Nasalis ≈ 1.76; EQ Simias ≈ 1.48). The confidence we can have in evolutionary hypotheses regarding cranial morphology and encephalization are severely hampered when we only have evidence from two species in a lineage. Categorizing features (such as relative brain size) as primitive or derived for the clade is difficult (or impossible), without looking to other related species for clues. Fossil evidence for the group since its divergence from other Asian colobines would be extraordinarily informative in
123 this regard, but no such evidence has yet been recovered. The best available evidence for ancestral character states comes from the extinct possible sister group to the living odd nosed clade, Mesopithecus (Jablonski 1998; Pan et al. 2004), and from the living odd nosed monkeys and a closely related genus, Semnopithecus . The average ECV and body mass data available for these taxa are presented in Table 4.13. Male Nasalis are the least encephalized within this group, followed by Simias males. (Even with a smaller body mass estimate for male Nasalis of 19,760 g (Delson et al. 2000), its EQ is only 1.26.) The situation differs in females in that Simias females occupy the extreme low end of the EQ spectrum, while Nasalis females are comparable to estimates for extant Semnopithecus dussumieri and Late Miocene Mesopithecus pentelicus from Europe. Of course, the EQ estimate for Mesopithecus is necessarily low confidence, as an ECV estimate for only a single individual is available, and body mass estimations in any extinct taxon are also uncertain.
Table 4.13. EQ values for odd-nosed monkeys and closely-related species. Sources for ECV and mass data are as follows: 1 = this study; 2 = Isler et al. (2008); 3 = Delson et al. (2000); 4 = Hadi et al. (2009); 5 = Radinsky (1974). ECV (mL) Mass (g) EQ Species Source M F M F M F Nasalis larvatus 105 86.5 20563 § 9730 1.23 1.76 1,2,3 Simias concolor 60 53.2 8588 6395 1.34 1.48 1,4 Pygathrix nemaeus 93.3* 89.5* 11000* 8440* 1.73 2.02 2 Rhinopithecus rox ellana 123* 113 17900 11600* 1.59 2.02 2 Semnopithecus entellus 117* 105* 18144* 11340* 1.50 1.91 2 Semnopithecus ajax 132* 133* 19959* 12701* 1.58 2.22 2 Semnopithecus schistaceus 130* 128* 19200 14800 1.60 1.91 2 Semnopithecus dussumieri 91.9* 88.3 11198* 10130 1.68 1.74 2 Mesopithecus pentelicus† - 72.5 - 8000 - 1.70 3,5 §This value is larger than most published estimates of male Nasalis body mass. I suspect that at least a few individuals included in the average values published in Delson et al. (2000) and Isler et al. (2008) were not fully adult. To prevent the potential bias of subadult specimens, this average value excludes specimen values from other studies, using only specimens for which I verified M3 eruption (n=9 with associated mass data). * Indicates that n < 5 individuals used to calculate this average value. † Fossil species. ECV estimated from single endocast from Pikermi, Greece by Radinsky (1974). Body mass estimated from multiple craniodental and postcranial remains by Delson et al. (2000).
Figure 4.24 presents the same data from Table 4.13 in a more visual format. In the top panel, the sex specific mean RBS (ECV ÷ body mass)—which does not make any allometric correction for the nonlinearity of brain body scaling—is illustrated for the odd nosed monkeys and their relatives. The sex specific mean EQ—which “corrects for” the negative allometry in brain scaling—is depicted in the bottom panel for the same species.
124
Nasalis
F Simias Rhinopithecus roxellana Pygathrix nemaeus Semnopithecus entellus M Semnopithecus dussumieri Semnopithecus schistaceus 0 2 4 6 8 10 12 Semnopithecus ajax RBS (x 1000) Mesopithecus
F
M
0 0.5 1 1.5 2 2.5 EQ
Figure 4.24. Comparative encephalization among Asian colobines. Top panel: Sex specific relative brain size (RBS) in Nasalis , Simias and related species—females above (F) and males below ( M). Bottom panel: EQ for the same species. Explanation of data and sources in Table 4.13.
Thus, based on ECV in related colobines, it is plausible that Nasalis females retain a level of encephalization similar to ancestral odd nosed colobines, and extensive somatic growth in males results in their especially low EQ. In such a scenario, Simias exhibits a derived reduction in encephalization. Alternatively, the most recent common ancestor of the living odd nosed colobines may have already been more encephalized than Nasalis (closer to extant Pygathrix and Rhinopithecus ), and both Nasalis and Simias have diminished in EQ since their divergence from the other genera (estimated at 6.9 +/ 0.65 Ma, Sterner et al. 2006) (Figure 4.2). In keeping with the “narrow allometry” approach advocated by Smith (1980) and others, Figure 4.25 compares the average ECV of Nasalis and Simias males and females to anthropoids
125 of similar sex specific average body mass. At the high end of the body mass spectrum, there are few other anthropoids (for which body mass is documented) of similar average mass to male proboscis monkeys—only males of Papio cynocephalis (with the largest ECV), geladas, and three species of Semnopithecus . Males in all of these species have a higher ECV than Nasalis , reinforcing the placement of Nasalis at the bottom end of the anthropoid encephalization spectrum in classic studies by Bauchot and Stephan (1969) and Holloway and Post (1982). Simias males fare similarly in comparison to other male anthropoids of equivalent body mass. Closest to them in ECV are the western red colobus ( Piliocolobus badius ) and another endemic island primate, Macaca fascicularis umbrosa from the Nicobar Islands, India.
180
160
140
males 120 females
100 Simias M Simias F Average ECV Average ECV (mL) 80 Nasalis M Nasalis F 60
40 2000 7000 12000 17000 22000 27000 Average Body Mass (g)
Figure 4.25. ECV vs. body mass for anthropoids with sex-specific mean body mass similar to Nasalis and Simias . ECV and body mass data for all other species come from Isler et al. (2008). Data points (yellow circles for females; blue squares for males) were included if the sex specific body mass average is within +/ 10% of that for the same sex in Nasalis or Simias .
Females of the two species are not the least encephalized among similarly sized anthropoid females. Trachypithecus auratus and Colobus guereza kikuyuensis females both have lower average ECV than female Nasalis . Comparably sized species of spider monkey, macaque,
126 baboon and siamang have considerably larger braincases than the female proboscis. Simias females fall into a body size range occupied by females of many anthropoid species. The least encephalized in this group is the black howler monkey (howler monkeys are recognized to have especially low encephalization, in general). Notably, the point just above the howler in this group represents Presbytis siamensis rhionis , another island endemic monkey from Indonesia (Riau Islands). In a similar range of ECV are multiple species and subspecies of Presbytis (the subject of Chapter 5) and Trachypithecus . These two genera are, along with Semnopithecus , the closest living relatives of the odd nosed monkey clade.
Conclusions
In terms of the hypotheses outlined at the beginning of the chapter, my analyses yielded some unexpected results. Hypothesis 1 : The simakobu ( Simias ) has a larger neurocranium and orbits relative to its cranial size than does the proboscis monkey (Nasalis ). This study shows that relative orbit size in Simias is significantly larger than relative orbit size in Nasalis , consistent with the null hypothesis. The results for relative neurocranial size, however, depend on how sexual dimorphism is taken into account. Relative neurocranial size is smaller in female Simias than in female Nasalis (regardless of whether neurocranial size is quantified via external landmarks or volume of the endocranial cavity, ECV). In contrast, male Simias have slightly larger neurocrania than do Nasalis males, relative to their cranial size— more in keeping with allometric expectation. Hypothesis 2 : For its cranial size, the simakobu has a less prominent facial skeleton than the proboscis . This hypothesis is not supported. One species does not have a distinctly more prominent face than the other: in both sexes, the orbits are more prominent in Simias , while the nasal region is more prominent in Nasalis . Hypothesis 3 : The two species share a coincident static cranial allometry . Although sample sizes limit the ability to formally test the relationship between the trajectory of static allometry in the two species, there is strong evidence for rejecting a null hypothesis of coincident trajectories. In this dataset, there is not sufficient evidence to reject a hypothesis of parallel slopes, however. The aggregate of quantitative and qualitative
127 comparisons of static allometry presented here suggests that cranial size and shape have a similar relationship in the two species (i.e., similar slopes), despite the fact that their cranial shapes are different (i.e., different intercepts). Hypothesis 4 : The simakobu is more encephalized than the proboscis monkey. As with relative neurocranial size, the interpretation of relative encephalization depends on how one accounts for sexual dimorphism in Simias and Nasalis . The null hypothesis of higher encephalization (measured by RBS or EQ) in the dwarf species, Simias , is clearly rejected when only females are considered. In males, however, Simias is more encephalized than the large bodied Nasalis . The proboscis monkey’s extreme body mass dimorphism results in an overall (sexes pooled) species mean EQ identical to that for Simias , to three significant digits (EQ = 1.40, using ECV and mass figures from Table 4.13).
Discussion
This study presents evidence that relative brain size has decreased in Simias since its last common ancestor with Nasalis . This appears to be a novel finding among anthropoid primates, in that the smaller bodied of two sister species is less encephalized than the larger bodied one. Montgomery et al. (2010) demonstrate several examples of absolute reduction in brain size within Primates (e.g., within callitrichids, lemuroids, Cercocebus ), as well as examples of reduced relative brain size in larger bodied taxa than in smaller bodied relatives (e.g., gorillas vs. chimpanzees, Mandrillus vs. Cercocebus ). None of these cases mimic the curious pattern of encephalization in the Nasalis Simias lineage, however. Taylor and van Schaik (2007) document what may be an analogous case among subspecies of the orangutan ( Pongo pygmaeus ), although the lack of associated postcranial or body mass data in their sample prevents direct comparison with the findings of this study. Given evidence for derived reduction in relative brain size in Simias , how might this reduction have occurred developmentally and evolutionarily? I hypothesize that selective pressure imposed by energetic constraints in an isolated environment at some point in the ancestry of the simakobu is responsible for its relatively small brain. Limited nutritional resources are commonly hypothesized as an explanation for reduction in body size in insular mammals. As brain tissue is energetically expensive, several researchers have argued that energetic constraints may disproportionately affect brain size in periods of low habitat
128 productivity (Prof. N.G. Jablonski, pers. comm.; Köhler and Moyà Solà 2004; Taylor and van Schaik 2007). This hypothesis is explored further in Chapter 6.
Chapter 5
Dwarfing in a dwarfed lineage: Presbytis leaf monkeys
Thus far, this thesis has considered a pair of African guenons and a pair of colobines from island Southeast Asia. This chapter compares cranial morphology in another set of Asian colobines: the Natuna leaf monkey (or Natuna pale thighed surili), Presbytis natunae , and the black crested leaf monkey (or Sumatran surili), Presbytis melalophos . The precise placement of P. natunae is unresolved within the melalophos group, which includes P. melalophos , femoralis , siamensis , and natunae . For this study, P. melalophos was chosen as a comparative species to the insular Natuna monkey because the largest sample sizes were available. A small sample of the banded surili, P. femoralis , was opportunistically measured as well, and these data are considered here when informative.
Species background
Geographic range
The current range of P. natunae is restricted to Bunguran Island (a.k.a. Natuna Besar or Greater Natuna Island). Bunguran is the largest of the Natuna Islands of Indonesia, situated on the Sunda Shelf between Borneo to the east and the Malay Peninsula to the west (Figure 5.1). The island has a land area of 1,700 km 2. (For comparison, the smallest U.S. state, Rhode Island, has a land area of about 2,700 km 2.) P. melalophos occurs only on Sumatra (and some offshore islands), where it has many geographic variants south of the Lake Toba region (Figure 5.1) (Groves 2001). Sumatra has a land area of 443,000 km 2, which is over twice the size of the island of Great Britain. The seven P. femoralis specimens measured in this study were collected variously from locations in northeastern Sumatra (n=4; Presbytis femoralis percura ) and peninsular Thailand (n=3; P. f. robinsoni ). Although these P. femoralis specimens will not be examined as a group by themselves, they are included in inter species shape comparisons and genus level analyses to provide a broader perspective.
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Figure 5.1. The approximate current geographic distribution of the three species of Presbytis considered in this chapter. Distributions based on Groves (2001) and Meijaard and Groves (2004).
Biogeography
It is presumed that Presbytis natunae has been isolated geographically from the mainland at least since sea levels rose at the end of the last glacial maximum (LGM), circa 10,000 years ago (Meijaard and Groves 2 004; Meijaard and Nijman 2003) . Bunguran Island shares close biogeographic affinities with both the Malay Peninsula, 475 km to the west, and Borneo, 225 km to the south east (Lammertink et al. 2003) . During periods of low sea level, this land was located on the west bank—the Malay side —of the Great Sunda River (Lammertink et al. 2003). The other non human primates inhabiting Bunguran today are the slow loris ( Nycticebus coucang ) and the long tailed macaque ( Macaca fascicularis ) (Lammertink et al. 2003). Lake Toba (in the crater of the massive Toba volcano ) approximately divides Sumatra into two primary biogeographic zones (Whitten et al. 2000) . The southern portion is home to multiple subspecies of P. melalophos , as well as pockets of P. siamensis and P. femoralis (see Figure 5.1), while only Presbytis thomasi occupies the most northern extent of the island. It is
131 important to recognize that because the taxonomy of Presbytis is unstable, and because P. melalophos , femoralis , and siamensis have adjacent ranges on Sumatra (possibly overlapping, Groves 2001; Wilson and Wilson 1977), taxonomic classifications in museums are often uncertain.
Diet
All Presbytis species are leaf specialists, although some populations obtain 50% or more of their diet from fruits and seeds, when available (Kirkpatrick 2007). Young leaves constitute a larger portion of the diet than mature leaves, which may be associated with niche separation from other sympatric colobines (Kirkpatrick 2007).
Sociality & Reproduction
Average mixed sex group size for P. femoralis and P. siamensis is reported as 11 16 individuals (Kirkpatrick 2007). Behavioral studies have not detected birth seasonality for Presbytis (femoralis and thomasi have been studied, specifically; Kirkpatrick 2007). Alloparental care during the first months of life has been recorded for some groups (Kirkpatrick 2007).
Predation
Predation rates for Presbytis are not well documented. On the island of Bunguran, Lammertink et al. (2003) report no evidence of hunting of Natuna leaf monkeys by humans, although they are frequently kept as pets by the locals. Bunguran lacks the feline predators that threaten Presbytis in other areas (Lammertink et al. 2003). On Sumatra, potential non human predators of leaf monkeys include the Sumatran tiger, the clouded leopard, and the Asian golden cat.
Anatomy
Presbytis species in general are small bodied relative to most other Asian colobines—no species has a mean body mass estimated above 7 kg (Smith and Jungers 1997). For this reason, as well as some dental features (Willis and Swindler 2004), it has been suggested that the entire genus may represent a dwarfed lineage derived from Trachypithecus like ancestors (Jablonski 1998). Presbytis continues to be sympatric with Trachypithcus over much of its geographic range (Kirkpatrick 2007).
132 Linear measures previously collected from museum specimens suggest that P. natunae is a "probable dwarf" within this potentially dwarfed lineage (Prof. N.G. Jablonski, pers. comm.). The sparse body mass data available for the Natuna leaf monkey indicate that its mean mass is approximately 80% of that recorded for Presbytis melalophos (Table 5.1). The reduced body size of P. natunae compared to its mainland congeners, along with the small size of Bunguran Island, permits its classification as a derived island dwarf species.
Table 5.1. Mean body mass values for the Presbytis melalophos species group. Although the white thighed surili (Presbytis siamensis ) is not considered in this chapter, it is included below for comparison. Samples sizes (in parentheses) indicate the number of specimens with mass records used to calculate each average (not the number measured in this study, specifically).
Mean Body Mass, in grams Species Male ( n) Female ( n) Presbytis natunae 5217 (2) 544 3 (4) Presbytis melalophos* 6554 (10) 6567 (11) Presbytis femoralis* 6892 (9) 6804 (5) Presbytis siamensis† 5879 (7) 6520 (10) * Data from Isler et al. (2008), including all subspecies. † Data combined from Delson et al. (2000) and Isler et al. (2008).
Members of the genus Presbytis generally have low body mass dimorphism (possibly even “reverse dimorphism” in P. siamensis ) (Table 5.1), and minimal dimorphism in cranial shape and size (Pan and Groves 2004). Canine dimorphism is not strong (Groves 2001).
Phylogeny
The taxonomic status of the Natuna leaf monkey is contested, considered variously as a subspecies of P. femoralis (Weitzel et al. 1988), P. melalophos (Oates et al. 1994), or P. siamensis (Brandon Jones et al. 2004). For simplicity, I follow Groves (2001) in referring to it at the species level. Zain (2001) published the most detailed molecular research on the genus Presbytis to date. He estimated that P. natunae diverged from the melalophos femoralis clade of the Malay Peninsula between 800,000 and 1.4 million years ago (Zain 2001). This entire melalophos species group diverged from other Presbytis species (e.g., rubicunda , comata , thomasi ) considerably earlier, 2.1 to 2.9 million years ago (Zain 2001). The precise position of the Presbytis genus within the Asian colobines is by no means agreed upon (Osterholz et al. 2008). Mitochondrial studies tend to support a Presbytis +
133 Trachypithecus clade to the exclusion of Semnopithecus (as shown in Figure 4.2) or, alternatively, an unresolved polytomy between these three genera (Osterholz et al. 2008; Sterner et al. 2006; Ting et al. 2008). Data from the X chromosome, in contrast, place Semnopithecus and Trachypithecus as sister taxa (Ting et al. 2008), as do analyses of retroposon integrations (Osterholz et al. 2008).
Fossil record
A small colobine is known from the Early Pliocene of Pakistan which has been assigned to the genus Presbytis , based primarily on size: Presbytis sivalensis (Conroy 1990; Jablonski 2002). Nothing is known of Presbytis from island southeast Asia earlier than a Middle Pleistocene partial palate from Java that is indistinguishable from modern Javan P. comata (Jablonski 2002). More recent craniodental remains of Presbytis (of indeterminate species) are known from caves in central Sumatra and along the northern coast of Borneo. These specimens are typical of Late Pleistocene Holocene mammals in this region (e.g., orangutan, macaque, tapir, rhinoceros) in being slightly larger than their living counterparts, despite morphological similarity (Jablonski 2002; Whitten et al. 2000). Reduced body size in the modern species is thought to be linked to the warmer prevailing temperatures now than in the past, in accordance with Bergmann’s Rule (Whitten et al. 2000).
Hypotheses, approaches of this study
The objective of this chapter is to identify cranial shape traits associated with isolation and dwarfing in Presbytis natunae by comparing it to a larger and more widespread species. P. melalophos was chosen over other closely related taxa as the primary reference species, because of specimen availability. When the opportunity arose to measure several Presbytis femoralis individuals (all females), these were included to increase the within genus variation considered in the analyses. As for the previous chapter’s comparisons, the null hypotheses for this study are those outlined in the conclusions of Chapter 3. Hypothesis 1 : The smaller bodied insular form, Presbytis natunae , has a larger neurocranium and orbits relative to cranial size than do larger Presbytis.
134 Hypothesis 2 : For its cranial size, the Natuna Island leaf monkey has a less prominent facial skeleton than do its larger relatives . Hypothesis 3 : Presbytis natunae shares a coincident static adult cranial allometry with the other Presbytis species . Hypothesis 4 : Encephalization in the dwarf taxon, Presbytis natunae , is higher than in the larger bodied taxa. The inclusion of three species rather than two dictated that the structure of this chapter deviate somewhat from the preceding ones. First, context is established by presenting the principal components of shape variation across the combined samples. A treatment of allometry and shape in the two primary species of interest follows. Then pairwise shape differences between species are examined. Finally, allometry and encephalization in the genus Presbytis are discussed.
Analysis of cranial morphology in the Natuna leaf monkey
Overview of comparative cranial shape in P. natunae , femoralis , and melalophos
Before addressing specific hypotheses, it is useful to establish the morphological context in which comparative shape and allometry will be explored in this genus. As indicated by the mass values in Table 5.1, P. natunae is considerably smaller in body size than either P. melalophos or femoralis . This is also true of their average cranial size, although there is some overlap in CS between P. natunae and the other two species (Figure 5.2).
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Figure 5.2. Centroid size in the three Presbytis species (sexes pooled). Centroid size calculated using the 45 cranial landmark configuration used for all subsequent analyses in this chapter. Boxplots indicate median and 1 st and 3 rd quartiles for each sample, with whiskers extending to maximum and minimum values. (Pf = Presbytis femoralis (n=7); Pm = Presbytis melalophos (n=60); Pn = Presbytis natunae (n=14)).
An initial impression of comparative cranial shape is obtained from a standard PCA of Procrustes coordinates from all specimens of all three species pooled (Figure 5.3).
136
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PC 2 2 (7.4%) PC -0.01
-0.02 P. melalophos M P. melalophos F -0.03 P. femoralis F -0.04 P. natunae M P. natunae F -0.05 -0.06 -0.04 -0.02 0 0.02 0.04 0.06
PC 1 (17.6%)
Figure 5.3. Principal components 1 & 2 of all Presbytis individuals. PCA of Procrustes coordinates.
The most striking feature of this plot is the strong grouping of P. melalophos at the higher end of PC1, while P. femoralis females and P. natunae cluster at the lower end of PC1. This raises interesting questions: 1. When all specimens are considered together, the position of the Natuna monkeys along the major axis (PC1) of cranial shape variation is more similar to that of P. femoralis than P. melalophos , despite the more similar size of the latter two species. Does this mean that P. natunae are isometrically scaled P. femoralis , in terms of cranial shape? 2. What kind of shape variation is captured by PC1? Is this variation size related?
These will be addressed in the proceeding analyses of intra and interspecific shape and allometry.
137 Static allometry in P. natunae
Because the sample size for this species is small, and sexual dimorphism is minimal (see cranial size comparisons, Figure 5.4), the sexes are pooled for analysis.
Figure 5.4. Distribution of female (n=10) and male (n=4) CS (above) and CBL (below) in the Natuna leaf monkey.
A different, and unexpected, variable appears to be important in terms of shape and size in this in this sample. The three P. natunae individuals from the Zoological Reference Collection (ZRC) at the National University of Singapore—for which only micro CT data are available (i.e., no data collected from the physical specimens)—cluster on the fringe of the sample distribution in both size and shape (Figure 5.5,
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Table 5.2).
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0.01 ZRC M 0 ZRC F -0.01 other M PC 2 2 (15.7%) PC -0.02 other F
-0.03
-0.04 -0.06 -0.04 -0.02 0 0.02 0.04 0.06 PC 1 (25.3%)
Figure 5.5. Principal component analysis of P. natunae individuals. Procrustes coordinates. Singapore (ZRC) specimens in orange. PCOORD analysis of scaled linear distances yields a similar separation of the ZRC specimens from the others.
This separation is potentially problematic, because these landmark data were collected by the author at a different time (many months later) and using different tools (virtual reconstructions of micro CT scans) than the rest of the P. natunae (and, indeed, all of the Presbytis ) individuals. Inspection of shape differences associated with PC1, as well as visual comparisons of the landmark configurations of the three ZRC specimens alongside the mean configuration of the non ZRC P. natunae specimens, revealed that major landmarks influencing this separation in shape space included ZMS, TSCR, AST, PET, and LAM. All of these landmarks (nine total, including bilateral) are especially challenging to measure from CT scan reconstructions, because the relevant cranial sutures often are not visible. Indeed, they are often challenging even with the original specimen in hand for the same reason, and are heavily influenced by the observer’s decision about how to record the landmarks in question. To see if these nine potentially less reliable landmarks were driving the isolation of the ZRC specimens from the others along PC1, the GPA superimposition and PCA of aligned Procrustes coordinates were repeated with all nine landmarks removed from the analysis (Figure 5.6).
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0.04 0.03 0.02 0.01 0 ZRC M -0.01 ZRC F PC 2 2 (16.5%) PC -0.02 other M -0.03 other F -0.04 -0.04 -0.03 -0.02 -0.01 0 0.01 0.02 0.03 0.04
PC 1 (22.2%)
Figure 5.6. Principal component analysis of P. natunae individuals, using only 36 landmarks. Procrustes coordinates.
Although less drastic, the separation in shape space persists with the reduced landmark set. Given that the shape differences in the ZRC specimens appear to be robust to removal of many of the most error prone landmarks, and that these are also the three largest individuals in the sample (Table 5.2), I do not feel confident that the ZRC monkeys are drawn from the same distribution, statistically speaking, as the other eleven P. natunae individuals. When size is measured by geometric mean rather than CS, male ANSP 6686 is the second largest, with the other three top spots occupied by the ZRC specimens. This could be for purely technical/methodological reasons relating to data collection from CT scans (Williams and Richtsmeier 2003), or it could be reflecting “real” biological (morphological) differences, perhaps due to random or directional change in the population over time (the ZRC specimens were collected approximately 30 years later than the others). It could also simply reflect natural variation in the population that, by chance, was not captured in the specimens collected earlier in time. The odds of three randomly chosen individuals from this sample being the three largest are 1 in 364 (via the binomial coefficient, 14 choose 3). Then again, the ANSP 6686 male is the same size as ZRC 4.256 and 4.258 to three significant figures.
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Table 5.2. Cranial size in Presbytis natunae individuals. Based on a 45 landmark configuration. Specimens are ranked by CS from smallest to largest. The corresponding geometric mean of all possible linear distances for each individual is also listed. Museum Catalog # Sex Centroid Size Geometric Mean NMNH 104843 F 179.1 30.94 NMNH 104848 M 179.3 30.88 NMNH 104847 M 182.6 31.53 NMNH 104849 F 184.3 31.88 ANSP 6687 F 184.5 32.09 NMNH 1048 45 F 184.7 32.04 NMNH 104842 F 188.0 32.64 NMNH 104846 F 189.5 32.90 ANSP 14030 F 190.4 32.98 NMNH 104850 F 191.4 33.22 ANSP 6686 M 194.5 33.62 ZRC 4.258 F 194.8 33.58 ZRC 4.256 M 194.8 33.60 ZRC 4.257 F 196.6 33.99
Whatever the reason(s) for the discrepancy in size and shape (summarized in Table 5.3), the within species analyses of P. natunae were run both with and without the three ZRC specimens included. In the context of the entire Presbytis sample, interspecific shape and size differences are large enough relative to this within species natunae variation (Figure 5.7), that the ZRC specimens were included in interspecific analyses, unless otherwise noted.
Table 5.3. Possible explanations for the size and shape differences between the ZRC specimens and other Natuna monkeys. Not all of the possibilities are mutually exclusive. In items 1 and 2, apparent differences are merely artifacts of data collection. Items 3 5 represent “real” morphological differences between specimens. Possibility 1 Observer (the author) systematically collected the data differently due to temporal gap between landmarking of CT scans and landmarking of all other physical specimens in person. 2 Observer systematically collected the data differently due to different specimen/observer interface and different measuring tools (virtual reconstruction + on-screen tools vs. actual crania + hand- held digitizer). 3 The population of Presbytis on Bunguran Island changed in size and shape between the collection of the non-ZRC specimens (1894-1900) and the collection of the ZRC individuals (1928). 4 The specimens represent two morphologically distinctive sub-populations on the island. 5 All specimens represent the normal range of variation in the population, and it is only by chance that the three ZRC individuals happen to be morphologically similar to each other and different from the rest of the P. natunae sample.
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0 PC 2 PC -0.01
-0.02 P. melalophos M P. melalophos F -0.03 P. femoralis F -0.04 P. natunae M P. natunae F -0.05 -0.06 -0.04 -0.02 0 0.02 0.04 0.06
PC 1
Figure 5.7. Principal component analysis of all Presbytis individuals (Procrustes coordinates), with the three Singapore/ZRC P. natunae specimens circled.
With the ZRC specimens excluded, a new GPA fit and PCA of the re maining P. natunae individuals separates males and females along the first PC axis ( Figure 5.8). This axis is not, however, correlated with size ( Table 5.4), only sex. For example, specimen NMNH 104848 —a subadult male included because samples were so scarce —still groups with the other males on PC1, despite its small cranial size (equal to that of the smallest female , Table 5.2). In fact, at least within this sample, there is no significant correlation between cranial size and shape (as all Procrustes coordinates) in the Natuna monkey.
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0.05 0.04 0.03 0.02 0.01 0 -0.01 males PC 2 2 (15.6%) PC -0.02 females -0.03 -0.04 -0.05 -0.05 -0.03 -0.01 0.01 0.03 0.05 PC 1 (24.6%)
Figure 5.8. PCA of P. natunae , excluding the ZRC specimens. Procrustes coordinates. Note the separa tion of the sexes along PC1, including the grouping of subadult male NMNH 104848 (arrow) with the two adult males.
Because the sexes separate along the first principal axis of both a PCA (Procrustes coordinates; Figure 5.8) and a PCOORD (scaled linear distances; not shown) , we can make inferences about sexual shape dimorphism, even with only a few available specimens. Principal component 1 of the superimposition based PCA is associated with differences in the landmarks ZMS , LZMI, FZJ, RFO, and ICVF. Separation along the first principal coordinate axis is driven by distances connecting to RFO, RZMS, and LFZJ, especially.
Table 5.4. Evidence of cranial allometry in Presbytis natunae , excluding ZRC specimens . Sample size of three males and eight females. Proportion of total Proportion of variance Associated p -value Shape component variance explained in component against null hypothesis by component explained by size of no allomet ry All Procrustes coordinates 100% 9.08% 0.607 PC1 of Procrustes PCA 24.6% 0.006% 0.983 PCO1 of EDMA PCoord 30.0% 0.001% 0.931 Analysis
To better visualize the shape differences associated with the PC1 axis, positive and negative extreme shapes were c onstructed. I chose this approach rather than a superimposition of male and female mean shapes, because the sample size for males is so small and the mean shapes of the two sexes will be quite close in shape, whereas the PC1 extremes will exaggerate the probably small differences that contribute to the male female shape separation. In Figure 5.9, we
143 see that the female like shape has relatively wider zygomatic arches and wider orbits than the male like shape. Foramen ovale is pushed posteriorly in males relative to females. Males have a more antero superiorly oriented premaxilla (probably related to the maxillary canines, which are noticeably dimorphic), more vertically oriented orbits, and a more inflated cranial vault.
Figure 5.9. Visualization of positive and negative extremes of PC1 within non-ZRC P. natunae . The first principal component axis is not correlated with CS, i.e., it is non allometric—but sex related— shape variation. The positive end of PC1 is associated with a female like shape (light aqua), whereas the negative end represents a more male like shape (darker aqua). All surface reconstructions of P. natunae in this chapter are based on the micro CT scan of male specimen ZRC 4.256.
There are no significant correlations between ECV and orbit or cranial size in the P. natunae sample (Table 5.5). As expected, CS and CBL are strongly correlated. Interestingly, CBL and HBL are also strongly correlated.
Table 5.5. Correlation between components of cranium and body in Natuna monkeys. (ZRC specimens excluded.) For correlations with r < |0.2| or p > 0.2, the precise values are replaced in the table with “n.s.” (not significant).
cbrt( ECV ) OD CS CBL OD n.s. - - - CS n.s. r=0.507, - - p=0.112 CBL n.s. n.s. r=0.845*, - p=0.001 HBL r=-0.459, n.s. r=0.571, r=0.813*, p=0.156 p=0.067 p=0.002 * Denotes that correlation value is significant at the p < 0.05 level.
If we include the three crania from the ZRC in Singapore, the picture of static allometry within P. natunae changes (Table 5.6). The sexes no longer separate along either of the first two
144 PC axes of shape variation (see Figure 5.5), so any inferences about sexual dimorphism in the sample are dubious.
Table 5.6. Evidence of cranial allometry in Presbytis natunae , including ZRC specimens. Sample size of four males and ten females. Proportion of total Proportion of variance Associated p-value Shape component variance explained in component against null hypothesis by component explained by size of no allometry All Procrustes coordinates 100% 13.6% 0.0246* PC1 of Procrustes PCA 25.3% 32.6% 0.0363* PCO1 of EDMA PCoord 28.0% 28.9% 0.0474* Analysis * Significant at the p < 0.05 level.
With these individuals included, static allometry in the sample becomes statistically strong. However, the hypothesis of a genuine relationship between size and shape is not compelling, as this correlation is primarily driven by the three ZRC specimens, which are both larger and differently shaped than the others (Figure 5.10).
0.05 0.04 0.03 0.02 ZRC M 0.01 ZRC F 0 other M other F
PC 1 1 score PC -0.01 -0.02 -0.03 -0.04 -0.05 178 180 182 184 186 188 190 192 194 196 198 Centroid Size
Figure 5.10. PC1 score plotted against CS in all Natuna monkeys.
Correlations between cranial and body metrics within the P. natunae sample change somewhat with the addition of the three ZRC specimens (Table 5.7), but the statistically significant correlations from Table 5.5 remain: CBL CS and CBL HBL.
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Table 5.7. Correlation between components of cranium and body in all Natuna monkeys. ZRC specimens included. cbrt( ECV ) OD CS CBL OD n.s. - - - CS n.s. r=0.457, - - p=0.101 CBL n.s. r=0.321, r=0.880*, - p=0.263 p<0.001 HBL r=-0.526, n.s. r=0.385, r=0.668*, p=0.053 p=0.174 p=0.009 * Denotes that correlation value is significant at the p < 0.05 level.
Static allometry in Presbytis melalophos females
Sufficiently large samples were obtained for both sexes in P. melalophos that their static allometries may be considered separately. Table 5.8 attests to the weak static allometry in P. melalophos females. Only 5% of total variation in shape (Procrustes coordinates) can be attributed to size variation. The first principal component of shape variation is correlated with size to some extent, although the first two (distance based) principal coordinate axes are not.
Table 5.8. Evidence of cranial allometry in Presbytis melalophos females (n=29).
Proportion of total Proportion of variance Associated p-value Shape component variance explained in component against null hypothesis by component explained by size of no allometry All Procrustes coordinates 100% 5.29% 0.049* PC1 of Procrustes PCA 16.0% 13.7% 0.050 PCO1 of EDMA PCoord 14.2% 1.25 % 0.564 Analysis PCO3 of EDMA PCoord 8.25% 26.8% 0.004* * Significant at the p < 0.05 level.
Comparing the predicted shapes for the largest and smallest individuals in the sample reveals the shape correlates of size in P. melalophos females (Figure 5.11). This visualization suggests that the facial aspect of the zygomatic bone is taller in larger individuals, and maxillary alveolar complex is taller/deeper. Nasion is positioned more anteriorly relative to nasale, making the nasal profile more vertically oriented in larger than in smaller individuals. Smaller
146 individuals have a relatively inflated neurocranium, as a smaller proportion of their cranial size appears to be devoted to the facial skeleton than in larger individuals.
Figure 5.11. Visualization of predicted shapes for largest and smallest P. melalophos females. All surface reconstructions of P. melalophos in this chapter are based on a surface scan of female specimen AMNH 102208. The correlation between ECV and CS approaches statistical significance in the P. melalophos female sample (Table 5.9). Unlike in other samples, orbit size (OD) is significantly correlated with cranial size (both CS and CBL). There is also statistically significant correlation between ECV and HBL, which has not been observed in other samples.
Table 5.9. Correlation between components of cranium and body in female P. melalophos
cbrt( ECV ) OD CS CBL OD n.s. - - - CS r=0.323, r=0.624*, - - p=0.088 p<0.001 CBL n.s. r=0.606*, r=0.825*, - p<0.001 p<0.001 HBL r=0.556*, r=0.223, r=0.200, n.s. p=0.002 p=0.255 p=0.307 * Denotes that correlation value is significant at the p < 0.05 level.
Static allometry in Presbytis melalophos males
This sample of male P. melalophos displays even weaker cranial shape allometry than females. With a strict p < 0.05 significance requirement, we cannot reject the null hypothesis of no
147 association between size and shape (Table 5.10). The major axis of shape variation is associated with size in neither a PCA nor a PCOORD analysis.
Table 5.10. Evidence of cranial allometry in Presbytis melalophos males (n=31).
Proportion of total Proportion of variance Associated p-value Shape component variance explained in component against null hypothesis by component explained by size of no allometry All Procrustes coordinates 100% 4.72% 0.058 PC1 of Procrustes PCA 12.9% 0.927% 0.602 PCO1 of EDMA PCoord 12.6% 0.029% 0.928 Analysis PCO2 of EDMA PCoord 9.36% 14.3% 0.036* * Significant at the p < 0.05 level.
By visualizing the predicted shapes for the smallest and largest individuals in the sample (Figure 5.12), we see that larger melalophos males tend to have wider zygomatic arches and wider crania in the region of EAM and asterion. Larger males also have a more anteriorly projecting premaxilla and naso alveolar region, which does not incorporate the zygomatic bones. Opposite the allometric trend in female melalophos , the smaller male predicted shape has the more anterior position of nasion, and more vertically oriented nasal bones. The small predicted shape has a noticeably inflated cranium, all the way from nasion to lambda, as well as wider orbits. In addition, smaller males appear to have a shallower palate than larger individuals.
Figure 5.12. Visualization of predicted shapes for largest and smallest P. melalophos males.
As in female P. melalophos , orbit size is significantly correlated with cranial size (CS and CBL) in males (Table 5.11). The atypical correlation between ECV and HBL seen in the female sample is not detectable in the males. Centroid size and CBL have the usual strong correlation.
148
Table 5.11. Correlation between components of cranium and body in male P. melalophos .
cbr t( ECV )† OD CS CBL OD n.s. - - - CS ρ=0.231 ‡, r=0.392 ‡*, - - p=0.212 p=0.029 CBL n.s. r=0.451*, r=0.853*, - p=0.011 p<0.001 HBL n.s. n.s. r=0.282 ‡, r=0.281, p=0.131 p=0.132 * Denotes that correlation value is significant at the p < 0.05 level. † Because this variable is not normally distributed, non parametric rank correlations were performed. ‡ Neither Spearman’s rho nor Kendall’s tau is statistically significant.
Sexual dimorphism in Presbytis melalophos
A PCA plot gives a good impression of the shape similarity between males and females (Figure 5.13). Yet the sexes are statistically different in the mean value of most variables considered (Table 5.12). Although the range of CS overlaps nearly completely between the sexes, males have a larger average CS than females. Endocranial volume, notably, is significantly larger in males, absolutely and also compared to CS, to body mass, and to HBL. (This finding was unexpected and will be discussed later in the chapter. This does not fit the pattern for primates, at least dimorphic ones.) When we compare male and female mean shapes (Figure 5.14), the differences are few and subtle. Males display a slight forward projection of the premaxilla (similar to natunae males, certainly related to canine development), and posterior projection of lambda. The female cranium is more brachycephalic and the orbits wider, relative to the male.
149
Table 5.12. Sexual dimorphism in the cranium of Presbytis melalophos . The range and mean values for each variable are given for females and males. For ease of display in the table, several ratios were multiplied by 100, as indicated. Mean values that differ significantly between the sexes (as determined by t tests) are denoted by indicating in which sex the mean is larger. Otherwise, lack of significance is indicated by “no.” Mass data are only available for five of 29 females and eight of 31 males. Preb ytis melalophos Range Mean Significant Female Male Female Male CS 192 -212 192 -215 202 206 M > F OD (mm) 22.4 -24.6 22.0 -24.7 23.5 23.2 no ECV (mL) 63.0 -81.0 67.0 -88.5 72.4 79.7 M > F ECV/CS ratio (x 100) 1.95 -2.21 1.97 -2.20 2.06 2.09 M > F OD/ECV ra tio 5.33 -6.02 5.07 -5.93 5.64 5.40 F > M OD/CS ratio (x 100) 11.2 -12.3 10.6 -11.9 11.6 11.3 F > M RBS (ECV/Mass) (x 100) 0.84 -1.2 0.92 -1.53 0.983 1.18 M > F ECV/HBL ratio (x 100) 0.71 -0.87 0.74 -0.94 0.779 0.811 M > F CBL/HBL ratio (x 100) 11.2 -14.7 12.3 -15.1 13.0 13.5 M > F
0.04
0.03
0.02
0.01
0
PC 2 2 (9.2%) PC -0.01
-0.02 males -0.03 females -0.04 -0.05 -0.04 -0.03 -0.02 -0.01 0 0.01 0.02 0.03 0.04 0.05 PC 1 (11.9%)
Figure 5.13. PCA of male and female P. melalophos . Using Procrustes coordinates.
When male and female shape are compared using EDMA, distances connecting landmarks on the premaxilla (i.e., IDS and PMMX) to the rest of the cranium are relatively longer
150 in males. Distances involving lambda are also relatively longer in males, consistent with the results from superimposing male and female mean shapes. The relative prominence of the zygomae in females contributes heavily to shape differences, as seemed to be the case in P. natunae visualizations. Females are relatively larger in distances connecting ZMI to virtually all areas of the cranium, except the premaxilla. To a lesser extent, distances connecting FZJ to landmarks on the face (IF, ZMS, ZMI, opposite FZJ) as well as to MXT are also longer in females.
Figure 5.14. Presbytis melalophos male (red) and female (pink) mean shapes.
Parallel static allometry in the sexes
The extreme large and small predicted shapes in Figure 5.11and Figure 5.12 indicate that the relationship between size and shape may differ between male and female P. melalophos . For instance (as mentioned earlier), the relative antero posterior position of nasion may not be associated with size in the same way in males and females. All in all, however, these differences do not amount to much statistically when we test variation in the PC scores of all P. melalophos individuals against size with a size by sex interaction term. A MANCOVA verifies that the interaction between size and sex does not have a significant effect on shape, no matter what proportion of shape variation (i.e., number of PC scores) is included in the analysis (for 95% of shape variance, PCs1 36: F=1.458; df=36,21; p=0.181). In other words, the static cranial allometries of male and female melalophos are not statistically distinguishable from parallel. This is not surprising, given that cranial allometry is only barely statistically significant in the samples to begin with. The second step of the MANCOVA reports that although the slopes of static allometry do not differ significantly between the sexes, they are not coincident when considering 50% or more
151 of the shape variance within the pooled sample (PCs1 36: F=4.973; df=36,22; p<0.001). When only approximately 46% or less of shape variance is analyzed, their trajectories are not distinguishable from coincident (for 45.8% of shape variance, PCs1 6: F=1.374; df=6,52; p=0.242). I interpret this to mean that the features of shape distinguishing the sexes are not the most important axes of shape variation within the pooled sex sample. Indeed, none of the top six PCs (or top 7 PCOs) is significantly correlated with sex. Some statistically weaker axes of shape variation do separate by sex, however, causing the MANCOVA to reject the null hypothesis of coincident allometric trajectories when more than about 50% of shape variation is considered in the analysis. Below this threshold, their allometric trajectories coincide. Now that within species allometry and dimorphism have been characterized, interspecific shape differences are examined.
Interspecific shape: P. natunae females compared to P. femoralis females
In comparing these two species, I chose to consider only females, because all P. femoralis individuals in the sample are female, and because the results of a PCA (Procrustes coordinates) suggested that this approach would produce two cohesive species groups (Figure 5.15).
0.04 0.03 0.02 0.01 P. femoralis 0 P. natunae M (ZRC) -0.01
PC 2 2 (13.1%) PC P. natunae F (ZRC) -0.02 P. natunae M (non -ZRC) -0.03 P. natunae F (non -ZRC) -0.04 -0.05 -0.03 -0.01 0.01 0.03 0.05 PC 1 (18.2%)
152
0.05 0.04 0.03 0.02 0.01 0 -0.01
PC 2 2 (13.7%) PC P. femoralis -0.02 -0.03 P. natunae F (non -ZRC) -0.04 -0.05 -0.04 -0.02 0 0.02 0.04 PC 1 (17.6%)
Figure 5.15. Principal components 1 & 2 of P. natunae and P. femoralis . Procrustes coordinates. (Upper) All individuals from both samples (ZRC specimens indicated). (Lower) Males and ZRC females removed from P. natunae sample, showing clear grouping of P. femoralis and P. natunae along PC1.
The species differences indicated by an EDMA Shape comparison confirm those visible in the mean shape visualizations via superimposition (Figure 5.16). A more projecting nasion in P. femoralis results in relatively longer distances connecting to nasion, from cranial base landmarks, in particular. This positioning of nasion is also associated with more vertically oriented nasals in P. femoralis than P. natunae . The distance from bregma to lambda is relatively longer in P. femoralis . The mean P. femoralis shape has relatively wider zygomatic arches, and a relatively longer palate (IDS to PNS) (both also seen in visualizations). Note from the visualizations that the premaxilla does not project more anteriorly in P. femoralis , despite its longer palate. The occiput is relatively taller in P. natunae females, as indicated by a longer lambda opisthion distance. Vomer sphenoid junction is positioned more anteriorly in P. natunae , as evidenced by relatively longer distances between VSJ and landmarks posterior to it on the cranial base (e.g., JUG, HYP, PET, CIFM, BAS). This is also visible in the visualization upon close inspection. The relative height of the facial aspect of the zygomatic bone (from FZJ to ZMI) is longer in P. natunae (also suggested by the relative inferior extension of zygoma in shape visualizations).
153
Figure 5.16. Visualization of P. natunae (blue) and P. femoralis (green) female mean shapes. ZRC specimens are excluded. As a digital scan of P. femoralis was not available, the P. natunae male micro CT is used for visualization of P. femoralis , because femoralis females are closer in shape space to natunae than to melalophos (based on PCA).
Although Presbytis femoralis is absolutely larger than P. natunae in average CS and ECV, the sparse data collected on these species do not indicate significant differences in the size of the brain relative to the rest of the cranium, to body mass, or to body length (Table 5.13). The mean ratios between cranial length and body length do not differ in these samples either.
Table 5.13. Comparative statistics for P. natunae (non-ZRC) and femoralis females. Variables as described for Table 5.12. Note that HBL and body mass are only available for four out of seven femoralis females; mass is available for four of eight natunae females. Orbital dimensions were not collected for P. femoralis .
Range Mean Significant Pn Pf Pn Pf CS 179 -191 194 -209 187 200 Pf > Pn ECV (mL) 55.0 -62.5 66.0 -76.0 58.5 72.0 Pf > Pn ECV/CS ratio (x 100) 2.00 -2.14 2.02 -2.17 2.08 2.08 no RBS (ECV/Mass) (x 100) 0.93 -1.2 0.98 -1.1 1.07 1.04 no ECV/HBL ratio (x 100) 0.70 -0.89 0.80 -0.84 0.845 0.827 no CBL/HBL ratio (x 100 ) 12.6 -15.0 13.6 -14.4 14.2 14.1 no
154 Interspecific shape: P. femoralis females compared to P. melalophos females
Because only female P. femoralis were sampled, and because detailed information on shape dimorphism within P. femoralis was lacking, I chose to use only females from the melalophos sample for comparing shape between these two species. When we compare shape in femoralis and melalophos females via scaled linear distances (EDMA), P. femoralis females have a wider biorbital distance (between right and left FZJ; also between ZMS bilaterally). P. femoralis individuals also have a taller and more anteriorly projecting premaxilla, with relatively longer distances between IDS and other facial landmarks such as ZMS, IF, ZMI, and FZJ. Correspondingly, nasion and nasale are more distant from premaxillary landmarks (IDS, PMMX, ICVF) in P. femoralis . Distances involving ZMI are responsible for most of the areas in which P. melalophos females are relatively larger than femoralis . In particular, the connections between ZMI and AST, EAM, JUG, HYP, foramen ovale, CIFM, and lambda are all important in differentiating shape between the species. The more antero inferior position of ZMI in P. melalophos is visible to some extent in the mean shape (GPA based) visualizations (Figure 5.17). The wider orbits of P. femoralis are clearly visible, as is the longer distance from the tip of the nasal bones (nasale) to the anterior alveolus. This latter distance may indicate shorter nasal bones in P. femoralis , which is one of the only hard tissue features cited in the literature (Groves 2001) as distinguishing these two species.
Figure 5.17. Visualization of P. femoralis (green) and P. melalophos (pink) female mean shapes.
The average size of the cranium and ECV do not differ significantly between the samples of P. melalophos and P. femoralis females (Table 5.14). Nor do the ratios of ECV to cranial size
155 or to body mass. In contrast, P. femoralis females appear to have larger ECV and skull length for their body length than do P. melalophos , although all of these results are tentative, given the few mass and HBL data collected for P. femoralis .
Table 5.14. Comparative statistics for melalophos and femoralis females. Note that HBL and body mass are only available for four out of seven femoralis females. Range Mean Significant Pm Pf Pm Pf CS 192 -212 194 -209 202 200 no EC V (mL) 63.0 -81.0 66.0 -76.0 72.4 72.0 no ECV/CS ratio (x 100) 1.95 -2.21 2.02 -2.17 2.06 2.08 no RBS (ECV/Mass) (x 100) 0.84 -1.2 0.98 -1.1 0.983 1.05 no ECV/HBL ratio (x 100) 0.71 -0.87 0.80 -0.84 0.779 0.827 Pf > Pm CBL/HBL ratio (x 100) 11.2 -14.7 13.6 -14.4 13.0 14.1 Pf > Pm
Interspecific shape: P. melalophos compared to P. natunae
In comparing P. natunae cranial shape against that in P. melalophos I pooled specimens of both sexes, as the sample of male Natuna monkeys is too small to consider separately. In an EDMA Shape analysis, relatively longer distances connecting to bregma in P. natunae are responsible for many of the largest shape differences. From examination of the mean shape (GPA based) visualization (Figure 5.18) in 3D (not easily reproducible here, unfortunately), it is evident that bregma is more supero posteriorly positioned along the cranial vault in P. natunae than in P. melalophos , creating a relatively shorter distance between bregma and lambda in the Natuna monkey. The P. natunae mean shape has more widely spaced EAMs relative to cranial size than P. melalophos , and wider orbits (between FZJ bilaterally) as well. These differences are evident both from linear distance (EDMA) comparison and from the mean shape superimposition (GPA). In addition, both methods indicate a relatively longer distance from nasale to the lower face/alveolus in P. natunae , which appears to be a result of shorter nasal bones and a more forwardly projecting premaxilla in the dwarf species. It was noted earlier that P. natunae has less vertically oriented nasal bones than femoralis (Figure 5.16), and this is also true when comparing natunae to melalophos . Besides a longer distance from bregma to lambda, P. melalophos show a
156 relatively more posterior positioning of PNS, VSJ, and foramen ovale. The palate of P. melalophos (ICVF – PNS) is also relatively longer than that of P. natunae .
Figure 5.18. Visualization of P. melalophos (red) and P. natunae (blue) mean shapes. Pooled sex samples.
The absolutely smaller species, P. natunae , has relatively larger orbits, compared to ECV and to CS, than P. melalophos (note similarity to Simias Nasalis comparison) (Table 5.15). The two species do not differ significantly in RBS, based on the few body mass records available. Compared to P. melalophos , both P. natunae (Table 5.15) and P. femoralis (Table 5.14) appear to have larger ECV and longer CBL for their body length. This could be an indication of, for instance, a slightly more elongate body in P. melalophos compared to the others. At any rate, the relationship of cranial size to body size appears to be roughly similar among these species of Presbytis .
Table 5.15. Comparative statistics for all P. natunae (including ZRC specimens) vs. all P. melalophos . Body mass data are available for six of 14 P. natunae, and 13 of 60 P. melalophos . Range Mean Significant Pn Pm Pn Pm CS 179 -197 192 -215 188 204 Pm > Pn OD (mm) 21.0 -24.1 22.0 -24.7 22.3 23.4 Pm > Pn ECV (mL) 55.0 -70.0 63.0 -88.5 60.6 76.2 Pm > Pn ECV/CS ratio (x 100) 1.95 -2.28 1.95 -2.21 2. 09 2.08 no OD /ECV ratio 5.19 -6.13 5.07 -6.02 5.67 5.52 Pn > Pm OD /CS ratio (x 100) 11.2 -12.7 10.6 -12.3 11.8 11.5 Pn > Pm RBS (ECV/Mass) (x 100) 0.93 -1.35 0.84 -1.53 1.14 1.10 no ECV/HBL ratio (x 100) 0.70 -1.04 0.71 -0.94 0.872 0.796 Pn > Pm CBL/HBL rat io (x 100) 12.6 -16.1 11.2 -15.2 14.5 13.2 Pn > Pm
157 Evolutionary allometry of Presbytis
To synthesize evolutionary allometry in Presbytis , I refer back to the interspecific PCA initially presented in Figure 5.3 (reproduced with new notations in Figure 5.21), and to the questions it raised. In considering this PCA, we should keep in mind that the pattern of shape variation in melalophos probably contributes disproportionately to the establishment of these principal axes, because of the larger sample size. Of course, the picture of interspecific variation could change with larger samples of P. natunae and P. femoralis . The first question posed earlier was, Is the Natuna monkey an isometrically “scaled down” femoralis ? Yes, with respect to the major shape differences that distinguish these two species from melalophos , which are captured by PC1. By virtue of the Procrustes superimposition method, any isometrically scaled version of any individual will occupy the same place in shape space, so such scaling would not affect the grouping of natunae and femoralis together at the lower end of PC1, away from melalophos . That is not to say that natunae and femoralis have the same mean shape, however. Based on the few female specimens considered here there are indeed shape differences between the species (see Figure 5.16 and accompanying text). P. femoralis has a more anterior position of nasion than natunae , and correspondingly more vertical nasals. The P. femoralis mean shape also displays relatively wider zygomatic arches, and a relatively longer palate (ICVF PNS) than the Natuna monkey female mean shape. P. natunae has a relatively taller occiput (lambda opisthion distance), and a taller facial aspect of zygomatic bone (FZJ to ZMI) than femoralis . Despite those shape differences, P. femoralis and P. natunae should, however, share shape characteristics that distinguish both of them from melalophos . These should match up when we consider (1) the shape associated with PC1 in the overall PCA, as well as (2) the differences between the mean shape of melalophos compared to those of femoralis and natunae .
158
Figure 5.19. Interspecific PC1 extreme shapes. The shape associated with the extreme negative end of PC1 (score of 0.06) is represented in light violet. The dark violet shape represents the positive extreme of PC1 (score of 0.04). Reconstructions made using the female P. melalophos surface scan.
Interspecific PC1 shape
The second question posed earlier in the chapter was, What is the nature of PC1 related shape variation? The most notable shape features associated with a positive position along the PC1 axis (the “ melalophos end”) are a relatively long, low braincase, and narrow, orbits. The face is flat with a nearly vertical facial profile, “retracted” premaxilla, and relatively long nasal bones (Figure 5.19). At the negative end of PC1 (the “ femoralis natunae end”), the neurocranium is more brachycephalic, with a higher position of lambda. The orbits are relatively wider, and the facial profile markedly prognathic, with an anteriorly protruding premaxilla. Are these the same features that tend to distinguish femoralis and natunae from melalophos ? Yes. Compared to melalophos mean shape, both natunae and femoralis are more brachycephalic (relatively wider distances between bilateral asterion and EAM), have relatively wider orbits, relatively shorter nasals, and a more projecting premaxilla (see Figure 5.17 & Figure 5.18). These PC1 related characters cannot be tightly correlated with size across these species, because the two larger species ( femoralis and melalophos ) are at opposite ends of the axis. Yet a correlation test between interspecific PC1 score and CS is highly significant ( r=0.53, p<0.001). This contradiction is only understood by considering the data more carefully. Figure 5.20 illustrates several phenomena worth noting. As we already know, the melalophos and femoralis individuals cover a similar size range, but there are many more specimens in the melalophos
159 sample, which fall toward the positive end of PC1. So even though the femoralis specimens have negative PC1 scores, they have little effect on the overall PC1 CS “trend.”
0.05
0.04 P. melalophos M P. melalophos F 0.03 P. femoralis F 0.02 P. natunae M 0.01 P. natunae F 0
-0.01 PC 1 1 Score PC
-0.02
-0.03
-0.04
-0.05
-0.06 175 180 185 190 195 200 205 210 215 220 Centroid Size
Figure 5.20. Interspecific PC1 scores for all Presbytis individuals plotted against CS.
Looking at the scatter of melalophos individuals only (Figure 5.20), there is no clear correlation between CS and position along PC1 (nor is there within the few femoralis individuals). This point is further illustrated by using the multivariate regression of Procrustes shape coordinates on CS within melalophos to create a hypothetical natunae sized melalophos individual (Figure 5.21). Such an individual falls well within the range of variation along PC1 for P. melalophos (and specifically, not near the low end). The P. natunae individuals cluster at the low end of both the interspecific CS and PC1 score range (Figure 5.20), such that a trendline through the two main clusters of data points on a CS PC1 plot (representing natunae and melalophos ) forcibly indicates a positive correlation between CS and PC1. Within the natunae sample itself, we see that the four largest individuals (the three Singapore specimens plus one additional male) have the highest (least negative) PC1 scores. Only a larger sample size would allow us to determine whether this PC1 position is likely
160 to be genuinely associated with CS throughout the whole species, or whether this is a spurious correlation because these larger natunae indivi duals also happen to approximate more closely the P. melalophos condition in terms of PC1 related cranial shape.
0.04
0.03
0.02 * 0.01
0 * PC 2 2 (7.5%) PC -0.01 *
-0.02 P melalophos M * P melalophos F -0.03 predicted melalophos P femoralis F -0.04 P natunae M P natunae F -0.05 -0.06 -0.04 -0.02 0 0.02 0.04 0.06 PC 1 (17.6%)
Figure 5.21. Interspecific PCA of all Presbytis specimens. Plot of PC1 vs. PC2 scores for a ll individuals, with the addition of a hypothetical P. melalophos configuration (yellow triangle) at the mean size (CS) of P. natunae . The predicted shape of a P. melalophos individual at a size that is 8% smaller than the species average (about 2% smalle r than the smallest melalophos in the actual sample) falls well within the normal variation for the species. The three circled individuals were collected at localities on or near Rupat Island, Sumatra (from upper left: NMNH 143546, 143547, 143548). The four P. femoralis individuals marked with a star (*) are classified in the subspecies P. f. percura , and were collected in eastern Sumatra (see text for discussion).
This brings up another question: Why do the Singapore specimens come closer to P. melalophos along PC1 than do any of the other natunae individuals (Figure 5.7)? Two possible explanations for this are that (1) there is a genuine correlation between larger size and more melalophos like cranial shape within P. natunae , or that (2) there was gene flow from P. melalophos (or another Presbytis population with similar cranial shape characters) into the P. natunae population between the time when the non Singapore specimens were collected and
161 when the three Singapore individuals were shot, about three decades later. The gene flow scenario is plausible considering reported trade of Natuna monkeys to other parts of Indonesia (for zoos and as personal pets; Lammertink et al. 2003), although this practice would seem to be unlikely to bring outside Presbytis species to Bunguran Island. An important conclusion of these results is that the main shape differences distinguishing natunae from melalophos are unlikely to be related to isolation and dwarfing in the Natuna monkey, because natunae shares these shape characters with the melalophos sized femoralis . Based on this, it is probable that natunae and femoralis share these traits due to phylogeny, although it is also possible that these features respresent homoplasies (convergent evolution of these traits independently). We cannot, however, say whether these traits represent the primitive state for this branch of Presbytis monkeys (and the melalophos morphology is derived), or whether the salient shape features of melalophos represent the primitive state, and femoralis and natunae share a derived condition. A more recent common ancestry of P. natunae with P. femoralis than with P. melalophos is predicted by Meijaard and Groves (2004) in their thorough synthesis of Presbytis biogeography and phylogeny. The authors hypothesize that the ancestors of P. femoralis retreated to a wet forest refugium located on present day Bunguran Island during the driest periods of the LGM, before migrating west as vegetation conditions improved. In such a scenario, those paleo femoralis individuals remaining in the Bunguran forest were ancestral to modern P. natunae . If molecular divergence times estimated by Zain (2001) are accurate, however, P. natunae diverged from P. femoralis and the rest of the melalophos species group long before the LGM (i.e., on the order of one million years ago, rather than 10 to 20 thousand years). Meijaard and Groves (2004) also use craniometric data from all species of Presbytis to construct a phylogenetic tree based on dissimilarities (Figure 5.22). In this analysis, they found that P. natunae is cranially more similar to Presbytis (hosei ) canicrus and Presbytis hosei from northern and eastern Borneo than to P. femoralis . Even so, their results are in accordance with those presented in the current study, in that P. natunae has closer affinities with P. femoralis than with P. melalophos .
162
Figure 5.22. Phylogenetic tree of Presbytis species, based on craniometric dissimilaries. The dissimilarity matrix was constructed using measurements from 277 colobine skulls, including Trachypithecus cristatus and T. obscurus as outgroups to Presbytis (Source: Meijaard and Groves 2004:79).
Although the major shape differences across the three species considered here are not associated with the endemic evolution of the Natuna monkey, there are nonetheless some cranial shape traits in P. natunae that could potentially be related to isolation and dwarfing—in particular, those shape features that distinguish it from both melalophos and femoralis . These include (1) a shorter relative distance between bregma and lambda in natunae , (2) a more posterior position of nasion and less vertical nasal bones, and (3) a relatively shorter palate (ICVF PNS) in natunae compared to femoralis and melalophos .
Species-level and geographic trends in craniometric data
Whereas species of Presbytis are defined almost exclusively on the basis of skin and pelage features and coloration, the morphometric data presented here suggest that cranial morphometrics could also be useful for systematics. For example, locality information listed for the three individuals circled in Figure 5.21 indicates “Rupat Strait” (for two of them) and “Rupat Island” (for the third). Rupat Island lies just off the Eastern shore of Sumatra, adjacent to an area inhabited by Presbytis femoralis (Figure 5.1). Although these three specimens are classified in NMNH records as Presbytis melalophos , based on their position in the interspecific PCA it is
163 plausible that they could actually be members of P. femoralis . Alternatively, they could be from an admixed population with recent genetic contributions from both femoralis and melalophos . Notably, a meticulous description of “the langurs of the Presbytis femoralis group,” published by Miller (1934) lists these three Rupat specimens as Presbytis percura —a taxon that was eventually subsumed as a subspecies of Presbytis femoralis , and that is represented in the present study by four female specimens (marked with a * in Figure 5.21).
Encephalization across Presbytis
In comparing the island isolate Simias to its relative Nasalis , it became evident that both absolute and relative brain size have probably decreased in the dwarfed Simias . The same does not appear to be true of the dwarfed Natuna leaf monkey, which has similar RBS and EQ values to its congeners (Table 5.13, Table 5.15, and Table 5.16). As a genus, it would seem that Presbytis tends to be more encephalized than Trachypithecus , which would fit with general expectation if Presbytis is indeed a dwarfed form of a Trachypithecus like ancestor.
Table 5.16. EQ values for members of the genera Presbytis and Trachypithecus . Mass and ECV data from Isler et al. (2008), except for ECV values of Presbytis natunae and P. melalophos , which are from this study. EQ calculated using Eisenberg’s (1981) equation. ECV (mL) Mass (g) EQ Species M F M F M F Presbytis natunae 65.8* 58.5 5217* 5443* 2.12 1.83 Presbytis melalophos 79.7 72.4 6554 6567 2.17 1.97 Presbytis femoralis 77.2 70.2 6892 6804 2.03 1.86 Presbytis siamensis 64.7 57.2 5879† 6520† 1.91 1.56 Presbytis chrysomelas 78.3 65.9* 6520 6917* 2.14 1.73 Presbytis rubicunda 74.4 67.7 6310 6221 2.09 1.92 Presbytis frontata 83.7* 78.4* 5560* 5670 2.58 2.38 Presbytis thomasi 76.7* 69.1* 6770* 6690 2.04 1.85 Trachypithecus obscurus 64.3 60.0 7347 6765 1.61 1.60 Trachypithecus cristatus 60.7 55.0 6728 6060 1.62 1.59 Trachypithecus phayrei 76.5 69.2* 7768 7182* 1.84 1.76 Trachypithecus vetulus 62.2* 60.4* 7371* 5103* 1.55 1.98 Trachypithecus pileatus 116* 91.4* 12247* 11340* 1.99 1.66 * Indicates that n < 5 individuals were used to calculate this average value. † Mean mass values from Isler et al. (2008) combined with those from Delson et al. (2000).
164 What is unexpected about encephalization in Presbytis is that males tend to have absolutely larger brains than females, even in species where females have a greater average body mass (Table 5.16). In all species and subspecies of Presbytis included in the dataset compiled by Isler et al. (2008), males have a larger mean ECV than females, both in absolute terms and relative to mean body mass. Is this typical for relatively monomorphic primates? In 37 of 57 anthropoid species and subspecies with a mass dimorphism < 1.10 included in the Isler et al. (2008) dataset, males have a larger mean RBS than females. The species which do not follow the trend (i.e., in which female RBS is larger or equal to male RBS) are mostly either callitrichids or hylobatids. The rule among dimorphic primates is that females are virtually always more encephalized than males (Bilsborough and Rae 2007; Isler et al. 2008). This is particularly expected when males achieve larger body size via an extension of a common growth trajectory with females, as the brain completes most of its growth early in ontogeny, and thus its adult size is not strongly affected by extended or accelerated growth later in ontogeny (hypermorphosis). One mechanism of routinely producing a larger brain size in males of a monomorphic species would be via an increased rate of brain growth prenatally.
Conclusions
Returning to the null hypotheses enumerated earlier in the chapter, the results of these analyses offer the following insights: Hypothesis 1 : The smaller bodied insular form, Presbytis natunae , has a larger neurocranium and orbits relative to cranial size than do larger Presbytis. This hypothesis is not supported. Although P. natunae has relatively larger orbits for its cranium than does P. melalophos , relative orbital size in natunae and femoralis appear comparable, so this is not a trait unique to the dwarf species, P. natunae . Based on these samples, neurocranial size (ECV) is equivalent relative to cranial size (CS) in all three Presbytis species. Hypothesis 2 : For its cranial size, the Natuna Island leaf monkey has a less prominent facial skeleton than do its larger relatives . Again, this hypothesis is not supported, as the Natuna monkey has a more projecting premaxilla than P. melalophos and more prominent orbits—both traits that natunae shares with femoralis . P. natunae does have a relatively short palate compared to melalophos and femoralis ,
165 although this does not appear to be directly associated with premaxillary projection or retraction in a whole cranium superimposition. This impression could be somewhat altered if the facial landmark configurations were superimposed independently from the rest of the cranium. This is an unavoidable issue when using superimposition methods, because the “best fit” of a superimposition always depends on which landmarks are included (see Chapter 2). Hypothesis 3 : Presbytis natunae shares a coincident static adult cranial allometry with the other Presbytis species . Cranial allometry is so weak in P. natunae that it is virtually undetectable in this small sample, making this question difficult to address. Formal testing for coincident allometry (via MANCOVA) was forgone for this reason. The only feature noted in these visualizations is that both larger P. natunae individuals and larger P. melalophos males tend to have relatively wider zygomatic arches than smaller individuals. Generally speaking, the issue of parallel static adult allometry may be essentially moot among Presbytis , due to the insignificant size shape association in the adult cranium. Ontogenetic data have the potential for interesting comparisons with respect to cranial allometry in these taxa, however. Hypothesis 4 : Encephalization in the dwarf taxon, Presbytis natunae , is higher than in the larger bodied taxa. This also is not supported by the data presented here. Encephalization (EQ) and RBS in the Natuna monkey are similar to that in P. melalophos and other species of Presbytis .
Apart from the specific null hypotheses, the results of this chapter permit some general conclusions about cranial shape and allometry in the genus Presbytis . The endemic species Presbytis natunae is closer in cranial shape to P. femoralis (females, at least) than to P. melalophos , despite the fact that the latter two species are more similar to each other in cranial size. We cannot draw conclusions about phylogenetic affinities based on shape features without first verifying their validity as phylogenetic characters, and then determining the polarity (primitive vs. derived) of these characters. The entire issue of using quantitative shape features as characters for phylogenetic inference is frought with controversy (e.g., Felsenstein 2002), and is beyond the scope of this thesis. There is little to no static allometry of adult cranial shape within the species of Presbytis considered here, similar to the findings in Simias (males excepted) and Nasalis (Chapter 4). Geographic, specific, and subspecific variants traditionally classified based only on vocalizations and soft tissue characters (skin and pelage coloration and features) may be
166 distinguished by cranial morphometrics, to various degrees. This could be due to different environmental factors, genetic drift, or adaptation. This phenomenon has been documented among Cercopithecus species (Cardini and Elton 2008a; 2008b), and is well documented among human populations from different geographic climatic areas (e.g., von Cramon Taubadel 2009). Males in this monomorphic genus appear to be more encephalized than females, on average. That is, males have a larger mean ECV than females, even though the sexes do not differ substantially in body size. Nowak et al. (2008) found some evidence for cranial shape change over time (~50 years) in the insular dwarf colobine, Procolobus kirkii (Zanzibar Island). It is possible that the discrepancy in cranial shape and size found here between the three Presbytis natunae specimens from Singapore (ZRC) and the other individuals (collected ~30 years earlier) indicates a similar phenomenon.
Discussion
It is an important cautionary lesson to realize that if the few sundry Presbytis femoralis specimens had not been considered in these analyses, it would have been easy to conclude that the major shape differences distinguishing natunae from melalophos were indeed derived traits associated with natunae ’s isolation and/or dwarfing. This point and a similar phenomenon mentioned above—the spurious but statistically significant correlation between CS and interspecific PC1 score—underscore the danger of drawing conclusions about evolutionary relationships (allometric or otherwise) based on only two species (Garland and Adolph 1994). Such comparisons, including those in this thesis, are a fruitful means of generating evolutionary hypotheses that can only be tested by incorporating data from additional species.
Chapter 6
Conclusions
In this thesis I have presented three case studies of dwarfing in primates. Each of these comparisons examined the adult cranial morphology of a small bodied dwarf species relative to a larger, related species. Quantitative analyses revealed that each species pair exhibits unique differences in cranial form. Based on these results, I hypothesize that dwarfing in primates may be conceptualized as a spectrum connecting two global types of dwarfing, determined by the prevailing selective regime. I outline the expectations for cranial morphology associated with each extreme type, and discuss potential evolutionary developmental mechanisms for dwarfing with respect to the model species studied in Chapters 3 through 5. The case of Homo floresiensis is then discussed in light of the empirical results of these species comparisons and the evolutionary hypotheses proposed. Finally, directions for future research and testing of such hypotheses are suggested.
Methodological Approach
As this research is predominantly concerned with the relationship between body size and cranial shape, its focus is necessarily on allometry. To address questions regarding size related shape in dwarf species, it was necessary to adapt existing methods for the study of cranial allometry. In particular, it is clear that sex related shape and size differences in sexually dimorphic species may confound the analysis of allometry at the species level: static allometry at the species level may be as indicative of sex related shape differences as it is of genuinely size related shape differences. For this reason, Chapter 2 defined formal tests for comparing static allometry between two groups (i.e., testing for parallel slopes, then coincident trajectories). These tests were applied within species to compare male and female static allometry, as well as between species. Within each sex, adult cranial allometry was also evaluated qualitatively by creating predicted shapes at the large and small extremes of the size range spanned by the sample. Using
168 the regression of all Procrustes coordinates on centroid size (CS), predicted configurations were computed and visualized by warping a digital 3D surface. Superimposition of the large and small shape predictions allowed visualization of the most salient size related shape differences within a given sample. This study also considered encephalization of the sexes separately. This was particularly important when evaluating relative brain size in the Nasalis Simias lineage, where the two species have similar mean EQ values. When the confounding effects of sexual dimorphism were removed by examining the sexes separately, however, it became clear that Simias females are less encephalized than their Nasalis counterparts, even though male encephalization in the two species is similar. Although the primary focus of this research is on cranial form and shape, much attention is paid to the analysis and discussion of encephalization. This is a necessary consequence of two factors. First, more than any other single issue, the controversy surrounding Homo floresiensis is driven by the tiny braincase of the LB1 specimen. If the endocranial volume of LB1 were estimated at 600 cm 3 rather than 400 cm 3, the hypotheses needed to account for this creature would be much less disruptive to our current understanding of hominin evolution. Second, relative to most mammals, anthropoid primates have large brains. Therefore, when considering the whole cranium morphology of any anthropoid, neurocranial shape and proportion are necessarily major components of overall morphology. If this study were to include other mammals for which the neurocranium is less significant to overall cranial morphology, encephalization might have taken a back seat to other more prominent features, such as the masticatory apparatus or olfaction, for example. Because brain evolution is so important to our definition of Primates—and Anthropoidea, in particular—it becomes a principal focus of any study of cranial shape.
Review of Species Comparisons
Guenons
Adult cranial shape in the talapoin monkey is generally consistent with ontogenetic scaling from a Cercopithecus like ancestor. The talapoin’s inflated neurocranium, large orbits, and gracile
169 face are all paedomorphic characters, both within primates and across mammals. Thus, as has been suggested by previous studies (Shea 1992), Miopithecus morphology fits an expectation of reduced rate and/or length of growth relative to its Cercopithecus relatives. Cranial allometry is not statistically significant within adult male talapoins, indicating that size is not a major determinant of cranial shape for adult males. The magnitude of cranial allometry among adult females is stronger, and may be a closer approximation to the trajectory of ontogenetic allometry in the species. This can only be verified by the analysis of ontogenetic craniometric data, however. In Cercopithecus nictitans adults, cranial allometry is statistically significant but not strong among both males and females—less than 8% of shape variance within each sex specific sample is correlated with variation in cranial size. Although males and females differ from each other in size and shape, the vast majority of shape differences among adults within each sex is not statistically associated with cranial size. Within each of the two guenon species, we cannot reject the hypothesis of parallelism for the slopes of male static allometry and female static allometry. Male and female static allometries are not coincident in either species, however, implying that there exist sex specific cranial shape differences that cannot be attributed to allometric effects alone. Consistent with the predictions of Rensch’s rule (e.g., Smith and Cheverud 2002), the magnitude of sexual dimorphism of cranial size and shape is lower in the smaller bodied talapoin than in C. nictitans (Table 3.14). This finding is also consistent with the expectations of ontogenetic scaling: because the sexes tend to diverge most markedly in shape and size late in ontogeny (particularly in species where sexual dimorphism is achieved primarily through hypermorphosis of males), a truncation or slowing of late growth should reduce these differences between the sexes. This appears to be the case in the talapoin relative to larger bodied guenons, according to my results. Cardini and Elton’s (2008b) study of skull shape across all living guenon species is broadly consistent with these results, although in the particular case of C. nictitans , they report slightly lower magnitudes of sexual size and shape dimorphism in C. nictitans than in the talapoin (see Chapter 3 conclusions). This discrepancy with my results is probably due to differences in methodology between the studies. A comparison of cranial allometry between M. ogouensis and C. nictitans with the sexes pooled indicates that the species’ static allometric trajectories are statistically different in slope (i.e., not parallel). This means that although larger cranial size is associated in both species with some similar shape features, like increased prognathism, the relationship between cranial size and
170 shape differs significantly in these two species. This analysis of encephalization concurs with previous studies that have placed M. ogouensis among the most encephalized non hominoid primates. The present study differs from previous work on guenon static allometry in that it examines male and female samples separately. In so doing, I show that sex related shape differences are relevant to allometric judgments, and that variation in shape is not explained by static allometry exclusively. In the talapoin, for instance, centroid size (CS) accounts for 15.5% of shape variation when the sexes are pooled. When we remove the sex related shape differences by calculating static allometry within each sex separately, however, size related shape variance falls to about 9.5% in female talapoins and does not reach statistical significance in males, as mentioned above. The talapoins exemplify the situation where, in a size and shape dimorphic species, allometry appears stronger with the sexes pooled than separated. Whether or not the differences in adult shape between the sexes are truly allometric, rather than purely sex related, is an empirical question that depends on the ontogenetic shape trajectories of the sexes (Figure 6.1a b). If the male ontogenetic shape trajectory is an extension of the female trajectory, then sex related shape differences in adults can be said to be allometric (Figure 6.1a). It is at least theoretically possible, however, that the sexes have significantly different ontogenetic shape trajectories, such that the larger sex never exhibits the shape of the smaller sex during its ontogeny, but follows a different path through size and shape space (Figure 6.1b). In such a case, a regression line fitted to shape across adults could show apparently strong allometry when, in fact, adult shape might not be correlated with size at all, once sex is taken into account (Figure 6.1c). It seems probable that in a case where the sexes share a common ontogenetic allometry (Figure 6.1a), static adult allometry will tend to resemble the situation depicted in Figure 6.1d more closely than 6.1c. Here, there is a statistically significant association between size and shape in adult females, but not in adult males (Figure 6.1d). Such a pattern seems to fit the adult size and shape data collected in this study for talapoins (see Figure 3.7) and, at least with respect to PC1 related shape, C. nictitans as well (Figure 3.13). Furthermore, the relationship between cranial size and shape among Nasalis adults (Figure 4.16) is suggestive of a similar situation (discussed below). I hypothesize that in these three species—and probably in many other dimorphic primates—the trajectory of adult female static allometry is more similar to the sexes’ shared ontogenetic allometry than is the trajectory of adult males.
171
Figure 6.1. Sexual dimorphism in ontogenetic and adult static allometric trajectories. See text for explanation. O M, O F = trajectory of ontogenetic allometry for males and females, respectively; XM, X F = mean adult size for males and females; S M, S F = best fit line describing static adult allometry for males and females, and (S M+F ) for the sexes combined.
Simias/Nasalis
The comparative cranial morphology of Simias concolor and Nasalis larvatus is consistent with the expectations of ontogenetic scaling in that the smaller animal, the simakobu, has more prominent orbits than the larger proboscis. Additionally, within each of the two species, larger individuals tend to be more prognathic—as in talapoin monkeys and female C. nictitans . The Simias Nasalis comparison departs from a model of ontogenetic scaling in that prominence of the facial skeleton is not reduced in the smaller species.
172 This case appears to be unique among documented cases in anthropoid primates in that the female of the smaller bodied species ( Simias ) has a smaller relative brain size than female Nasalis . In each of the two species, females are more encephalized than males (quantified as EQ or as relative brain size, RBS)—this is what we expect in a sexually dimorphic primate. When species average brain vs. body sizes are compared, the two species are about equivalent in EQ. This is also unremarkable in two species of different body sizes. What makes this comparison unique is the fact that females in the large bodied proboscis are more encephalized (as EQ or RBS) than the smaller simakobu. It is possible that a Simias level of encephalization represents the primitive condition for this lineage, and that Nasalis has increased the size of its brain since their divergence. Two lines of evidence refute this explanation however. First, the only available fossil evidence of brain size with probable relevance to Asian colobine evolution suggests a level of encephalization at 10 12 Ma ( Mesopithecus pentelicus ) that is already comparable to that of the living odd nosed monkeys. Second, the other extant members of the odd nosed monkey clade ( Pygathrix and Rhinopithecus ), as well as the related genus, Semnopithecus , have similar or greater EQ values than Nasalis (Figure 4.24), suggesting that encephalization has probably not increased in Nasalis since its last common ancestor with these taxa. Given the smaller overall body size of the simakobu, and the relatively small size of its neurocranium, I hypothesize that Simias represents a case of island dwarfing with reduced encephalization, similar to the findings of Weston and Lister (2009) in Malagasy dwarf hippos. This reduced encephalization makes the Nasalis Simias model of interspecific allometry the most relevant of the three comparisons with respect to the small brained endemic primate, Homo floresiensis . Another potential explanation for the simakobu female’s low encephalization could be derived from life history theory in an energy constrained or high mortality environment. That is, if female simakobu must terminate brain growth earlier than males in order to divert energy to reproduction, encephalization in females could be lower than we might otherwise predict. Leigh (2004) concluded that brain growth in baboons ( Papio hamadryas ) and macaques ( Macaca mulatta ) is concentrated disproportionately on the fetal period, compared to the New World monkeys and apes in his study. Such prenatally focused brain growth reflects a heavy metabolic investment on the part of baboon and macaque mothers during gestation, Leigh (2004) argues. Postnatally, these cercopithecoids displayed minimal and slow increases in brain volume. Do colobines adhere to a similar pattern of brain growth? Ravosa’s (1991) ontogenetic sample indicated no statistically significant sexual dimorphism in endocranial volume (ECV) among
173 proboscis monkeys until (dental) adulthood, implying that significant brain expansion occurs during late subadult ontogeny in males of this colobine species. Although Ravosa (1991) did not explicitly consider prenatal vs. postnatal allocation of brain growth, his cross sectional ECV data indicate that the vast majority of total adult brain volume (75% or more) in the proboscis (both sexes) has been achieved by the earliest dental age in his study (Prof. M.J. Ravosa, pers. comm.). In the case of the proboscis, then, Ravosa’s data suggest while postnatal brain expansion is minimal in both sexes, there is nonetheless significantly more brain growth occurring in the latest stage of subadult ontogeny in males compared to females. Turning back to the case of the simakobu, I argue that the low encephalization of simakobu females relative to proboscis females is evidence of severe selective pressure (in the form of energy restriction) in its evolutionary past, which necessitated a significant reduction in prenatal brain growth. Is it instead possible that late ontogenetic brain expansion in males but not females—such as the proboscis apparently undergoes—accounts for the peculiarly low encephalization of simakobu females? Such a phenomenon could be predicted by life history theory (e.g., Charnov 1991), if female simakobu must sacrifice late ontogenetic brain growth in favor of reproduction. I believe this is unlikely, for two reasons. Although it may be the case that postnatal brain growth in simakobu males outpaces (or outlasts) that in females (ontogenetic data are clearly needed to test this hypothesis), a postnatal discrepancy in brain growth between the sexes cannot explain the simakobu female’s low encephalization relative to the female proboscis. First, despite lacking the late brain expansion of proboscis males, proboscis females are far more encephalized than males because their body mass is substantially lower. If the ancestral simakobu shared the proboscis pattern of brain growth and overall encephalization, then early truncation (or slowing) of brain growth in females should not be expected to result in anomalously low encephalization in the simakobu female but not the proboscis. Also, female simakobu are still more encephalized than males—female brain size in the simakobu is only small when compared to females of other species (see Table 4.13, Figure 4.24). Second, even if ECV in female simakobu reached the same average adult volume as males (through faster and/or extended growth), female simakobu encephalization would still be lower than in other Asian colobine females. An increase in female average ECV from 53.2 mL to 60 mL (the male mean) would only bring the EQ value in simakobu females from 1.48 to 1.67. Although closer to the other species’ values, this still falls short of EQ estimates for the other extant Asian colobine females. Rather than a significant postnatal change (that is, reduction) in brain growth, it seems more plausible that the ancestral simakobu was already locked into what may be the typical
174 pattern for Old World monkeys: concentrated investment in brain development by mothers during gestation (Leigh 2004). As Leigh (2004) suggests, this metabolic strategy may reflect the “metabolic risk profile” faced by a species—in the case of high brain investment during gestation, we would expect a relatively low risk of energy shortage prenatally compared to postnatally. Once established, this “early brain investment” strategy may be difficult to reverse, even in the face of a changing metabolic risk profile. I suggest that the ancestral simakobu inherited the prenatal brain investment strategy from its forebears, only to incur periods of severe energy shortage in isolation on the Mentawai Islands. The survivors of the energy crisis were animals that managed to reproduce successfully with reduced energetic input during gestation (and, probably, throughout ontogeny), resulting in reduced encephalization.
5.5
5
4.5
cbrt(ECV) 4 Simias M Simias F 3.5 Nasalis M Nasalis F 3 180 190 200 210 220 230 240 250 260 270 CS (43 landmarks)
Figure 6.2. The relationship between cranial size and brain size across Simias and Nasalis , showing “transpositional allometry.” The intraspecific relationship between CS and cube root endocranial volume (cbrt(ECV)) is similar (close to parallel) in the two species. However, the intercepts of these allometric trajectories are notably different. As a result, even at the same cranial size (i.e., centroid sizes in the 205 215 range), the simakobu has a smaller ECV than the proboscis. Explanation in text.
As is typical in allometric studies of closely related species, the trajectories of static cranial allometry within Simias and within Nasalis are similar in slope, but not coincident. The association between cranial size and shape in the two species is thus similar, but they have fundamental differences in cranial shape to begin with. It is easy to see evidence of this shape
175 difference in allometric plots such as that in Figure 6.2, for example: although Simias males overlap with Nasalis females in cranial size and PC1 score (Figure 4.23), ECV in even the largest Simias male is substantially smaller than in the smallest Nasalis female. As other authors have noted, this pattern can be interpreted as a case of transpositional allometry (a.k.a. grade shifts or intercept shifts) between species. In adult Nasalis , it appears from the relationship between (pooled sex) PC1 score and CS (Figure 4.16) that the two smallest adult males in the sample may be hypomorphic with respect to the rest of the adult males. Although there were no gross morphological features of these two crania to suggest that they were subadult, it seems plausible that they, like the small “outlier” male (which was dropped from the analysis due to its size; see Chapter 4) had not fully completed their adult cranial growth. Similar to the situation in two subadult talapoin males (Figure 3.7), the size shape relationship across the Nasalis sample suggests that (1) the sexes share a common ontogenetic trajectory, with the rate and/or duration of growth extended in males relative to females; (2) adult female cranial allometry may retain a stronger signal of this ontogenetic path through size and shape than does adult male allometry (Figure 6.1). Given that this kind of size shape relationship is suggested by my analyses of both guenon species as well as the distantly related Nasalis , it seems likely that it is a common pattern among dimorphic Old World monkeys. Thus, I hypothesize that in sexually dimorphic cercopithecoids, the trajectory of adult female cranial (static) allometry more closely approximates the shared ontogenetic trajectory of both sexes than does adult male static allometry. This hypothesis can be readily tested using ontogenetic craniometric data from other dimorphic Old World monkeys. Surprisingly, males exhibit much higher correlation between cranial size and endocranial volume than do females. I discuss this discrepancy in more detail later in this chapter.
Presbytis
The hypotheses based on a model of ontogenetic scaling in the endemic Natuna Island leaf monkey ( Presbytis natunae )—the dwarf species—and related Presbytis were not supported by the data analyzed here. Specifically, there is no significant difference in neurocranial size relative to overall cranial size among the three species of Presbytis (P. natunae , femoralis , and melalophos ). Relative orbital size is larger in both P. natunae and P. femoralis than in P. melalophos , so this is not a feature unique to the dwarf species, P. natunae . Furthermore, the
176 prominence of the facial skeleton is not reduced in P. natunae compared to the other two Presbytis species. Although the palate is relatively shorter in the Natuna monkey than in the others, this shortening does not appear to be associated with a difference in premaxillary projection or retraction in P. natunae . Static adult cranial allometry is statistically insignificant in all of the Presbytis samples considered, obviating any formal testing for parallel or coincident allometric trajectories. Potential differences in ontogenetic allometric trajectories between the various species remain an interesting subject for future investigation. Such ontogenetic studies could reveal how subtle species level reductions in overall body size occur developmentally, without significant changes in relative brain size. Similar to Cardini and Elton’s (2008a) recent study of guenons, the comparison of cranial morphology in three species of Presbytis suggests that species variants traditionally classified on the basis of pelage and vocalizations are also distinguishable craniometrically. There is little or no cranial sexual dimorphism within each of the species. Overall cranial shape in the island dwarf species, Presbytis natunae , was found to be more similar to that in the (small) sample of Presbytis femoralis than in Presbytis melalophos . In order to soundly hypothesize a closer phylogenetic relationship between P. natunae and P. femoralis , this common cranial shape must represent discrete characters which are derived (synapomorphic) rather than primitive (symplesiomorphic), however. Additionally, the mean EQ value in the Presbytis samples analyzed here is higher for males than for females. These data, along with published endocranial volume data from other species, suggest that males in monomorphic anthropoid species may tend to be more encephalized than females. This is in strong contrast to the trend among dimorphic species, in which females are consistently more encephalized. It is unclear whether a male female disparity in EQ indicates functional significance in any species (indeed, the significance of EQ itself is debatable (Deaner et al. 2007)), but the apparent reversal of the typical primate pattern is notable.
177 The Dwarf Phenotype
Different paths to a dwarf phenotype: selective pressures
I hypothesize that two of the three dwarf species examined in this thesis represent two globally different evolutionary paths to derived body size reduction in primates (Figure 6.3). In one scenario, reduced body size is only incidental, a byproduct of targeting a niche or resource base that is most effectively exploited with a smaller body size. I hypothesize that the talapoin monkey exemplifies this niche-separation dwarfing . The second path to dwarfing is induced by severe resource limitation, such that the fittest individuals in a population are those which require the least energy to survive and reproduce. I use the term energy-restriction dwarfing to describe this scenario, which I argue applies to the simakobu monkey ( Simias concolor ).
Figure 6.3. Alternate paths to a dwarf phenotype.
Niche separation
The talapoin represents a classic case of dwarfing in a rich, mainland environment. It remains broadly sympatric in the forests of West Africa with several other guenons, and it seems likely that its ancestors evolved under similar circumstances. This habitat accommodates multiple guenon species of moderate body size (2.5 10 kg). By reducing its size below this range, ancestral Miopithecus was able to exploit areas of the African riverine forest environment that were not being ‘harvested’ by other, larger guenons. This increased their reliance on energy dense food sources like invertebrates and ripe fruits, probably in part via more terrestrial foraging
178 in the dense vegetation that surrounds waterways. The increased vulnerability to predation due to a smaller body was counterbalanced by the elusiveness of a small, agile mammal living under cover of thick foliage. Other potential cases of niche separation dwarfing in primates are gibbons, callitrichids, and cheirogaleids (dwarf lemurs). Importantly, dwarfing in a pure niche separation scenario is only incidental. The evolutionary path of the species is tied to body size only to the extent that it is advantageous for exploiting an ecological niche. If the available ecological space is conducive to larger body size, we would expect ‘niche separation giantism’ to evolve instead. The gorilla may represent just such a case of giantism in the hominoids, for example.
Energy restriction
The other major path to reduced body size is not driven by exploitation , but by the characteristics necessary to survive in a resource scarce environment. The simakobu monkey (Simias concolor ) is a probable instance of this energy restriction dwarfing. It has survived prolonged isolation on the Mentawai Islands, which offer limited land area and few endemic predators. In cases such as this, energy limitation can easily become a strong selective pressure during periods of climatic stress, favoring phenotypic changes that permit survival with minimal energetic input. Any number of physiological parameters might thus be altered for energy conservation: overall body size, size of specific costly organs (e.g., brain, gastrointestinal system), basal metabolic rate (BMR), behavior, reproductive parameters, growth patterns, etc. The simakobu has an unusually small brain volume compared to related species (Figure 4.24), suggesting that its ancestors were subjected to energy restriction dwarfing. Of course, the physiological changes that minimize metabolic expenditure—such as decreased brain size—will have their own fitness trade offs. As discussed in Chapter 1, however, survivors of a severe population crash need only reproduce successfully to have their offspring dominate the post crash lineage. Whatever the expected relative fitness of such survivors under a pre crash selective regime is not relevant once the new regime is in place. Energy restriction dwarfing may be the legacy of a species that came back from the brink of extinction (Marshall and Corruccini 1978; Sondaar 1977). The prototypical energy constrained environment is a small, oceanic island isolated from contact with larger biotic pools. As many researchers have discussed, however, an “island environment” need not refer to a literal island, but may denote virtual islands: pockets of resources and biota that are isolated by biogeographic barriers other than ocean, such as desert,
179 human settlement, or drastic changes in elevation. The phenomenon of a climatic refugium during a severe glacial event is one example of a non water bounded ecological island. As primate habitats suffer fragmentation as a result of deforestation and other anthropogenic forces, “island ecology” becomes increasingly relevant to conservation biology.
Here I have described two extremes along a spectrum of possible evolutionary paths to reduced body size. At one extreme, the talapoin’s ancestors may have been under little direct energetic constraint, but smaller individuals simply had higher fitness due to their abilities to exploit a small bodied niche. Researchers have suggested parallels between the talapoin and the radiation of squirrel monkeys in rainforests of the New World (Kingdon 1997). There would appear to be a genuine small bodied primate (600 g 1.5 kg) niche to be exploited in the rainforest that has been filled in the New World by Saimiri , and in the Old World by Miopithecus . At the other “evolutionary extreme” with respect to body size reduction, one or more periods of extreme resource deficiency may eliminate all but the most energetically conservative members of a population. I hypothesize that such a period was a defining feature in the evolutionary history of the simakobu monkey. Based on its cranial form and overall body size compared to its closest living relative (the proboscis), the simakobu likely represents an island endemic species that has persisted through energetic crises by reducing its energy requirements. A diminution in body mass is part of a suite of adaptations, which also includes reduced relative (and absolute) brain size, permitting members of the ancestral simakobu population to survive extinction during climatic crises. Although in these examples, niche separation dwarfing applies to a mainland species, and energy restriction to an island species, these scenarios are not necessarily tied to mainland and island environments, respectively. Niche separation could be a strong force for body size change in an island setting as well: if two species that normally share a similar diet were to be isolated in a highly constrained environment, they might diverge in body size as each became adapted to less overlapping food resources. Alternatively, a severe shortage in a (mainland) species’ primary source of energy could favor individuals who were able to exploit a novel food source. In both of these cases, elements of both energy restriction and niche separation would be implicated in body size evolution.
I have thus far discussed the natural history of the talapoin and the simakobu monkeys, but where does the third dwarf species, the Natuna monkey, fit into this framework? The Natuna
180 Island leaf monkey presents an interesting case with respect to these dwarfing scenarios, in that neither model is an obvious fit. As Presbytis natunae is endemic to a tiny island with eminently finite resources, the hypothesis of energy restriction dwarfing is immediately attractive. Unlike the simakobu, however, the Natuna monkey does not exhibit evidence in the cranium of unusually small neural components compared to its relatives. What sorts of cranial shape features should we expect to see in an energy restriction dwarf as opposed to a niche separation dwarf? To answer this question, I must first elaborate on the potential mechanisms of dwarfing in primates.
Mechanisms of Dwarfing: Heterochrony as inferred from adult morphology
The comparisons of adult cranial form presented here, along with what is already known of primate ontogeny, lead to some testable hypotheses regarding the probable evolutionary and developmental mechanisms of body size reduction in these and other primate species. The analyses in this thesis tested dwarf cranial morphologies against the expectations of ontogenetic scaling relative to a non dwarf morphology. Ontogenetic scaling generally implies that postnatal development has been modified, via a change in the rate or timing of postnatal growth . Alternatively, modifications to development during the gestational period may be responsible for morphological differences. Such changes to prenatal growth have the potential to result in fundamental structural differences, because cell migrations and condensations may be affected. As an extreme hypothetical example, we can imagine that changes in postnatal growth of the nose would result in either a juvenilized or hyper adult nasal morphology. In contrast, a prenatal change in cell migration and proliferation into the median nasal prominences, for example, could result in the failure of major parts of the nose to form.
181
Figure 6.4. Potential mechanisms of size reduction. See text for explanation.
I hypothesize that changes in postnatal growth are more likely to be the primary mechanism of shape change in primates that have undergone niche separation dwarfing, as less severe selective pressure should be required to effect postnatal changes in growth. In contrast, prenatal changes are more likely to accompany energy restriction dwarfing, in scenarios where severe selective pressure has altered prenatal ontogeny. This would be expected if prenatal ontogeny is more difficult to alter evolutionarily, whereas postnatal growth is more labile (although this assumption may not be universally true!). As such, in the absence of exceptionally severe selective pressure, heterochronic changes in postnatal ontogeny will be favored over alterations to prenatal development. Such is likely to be the case with so called niche separation dwarfing. Only under an austere selective regime that likely eliminates a large portion of a population will prenatal developmental reorganization be favored. Energy restriction dwarfing may result from this type of regime, as fundamental changes in the way an organism allocates energy will be required.
182 As cercopithecoids in particular (as compared to haplorrhines and hominoids) complete most of their total brain growth prenatally (Leigh 2004), a reduction in postnatal growth (via any mechanism) is expected to have comparatively little effect on adult brain size. A significant change to the proliferation of neural cells prenatally , however, could dramatically affect the size of the brain at birth. This would substantially affect the adult brain size as well. Thus, we would predict that primates that have evolved smaller body size via changes in postnatal growth will exhibit signs of ontogenetic scaling. Those which have evolved smaller body size via prenatal growth modifications are expected to exhibit differences that cannot be easily effected by alterations of postnatal ontogeny. For example, a significant reduction in the size of the eyes and brain, which develop primarily prenatally, would be a strong indication of prenatal developmental reorganization. Must these hypothesized connections between selective pressure and mechanism of dwarfing hold? That is, must niche separation dwarfing occur exclusively via postnatal ontogenetic changes, and energy restriction dwarfing occur solely by prenatal changes? Based on the case of the talapoin monkey, I hypothesize that when exploitation of a relatively open trophic niche is primarily responsible for a reduction in body size, postnatal ontogenetic scaling will typically be the path of least evolutionary resistance (Schluter 1996). We can think of one scenario as an evolutionary opportunity (niche availability), and the other as an evolutionary constraint (energy restriction). If ontogenetic scaling does indeed represent the path of least evolutionary resistance, it will probably occur initially in either the “constrained” or “opportunistic” cases (Figure 6.4). Given the combination of strong enough selective pressure and adequate time, less easily accomplished reorganizations of prenatal development can occur. This probably will not happen in a purely opportunistic niche separation scenario (left hand path in Figure 6.4), but requires an evolutionary constraint (energetic or otherwise) to force these prenatal changes (right hand path in Figure 6.4). In sum, dwarfing via (postnatal) ontogenetic scaling could result from either niche separation or energy restriction, but dwarfing via prenatal growth alterations will require energetic restriction or an equivalently strong constraint. Is one of these paths more robust to future changes in the selective regime? In other words, is one evolutionary path to smaller body size more easily reversible? Just as changes in prenatal growth are more difficult to effect, once they have occurred, they may be more difficult to reverse than are postnatal changes. For this reason, I hypothesize that dwarf primates which have undergone more involved developmental changes than simple ontogenetic scaling will also be more vulnerable to extinction than an ontogenetically scaled dwarf. Again, this accords with
183 the observation that dwarfing and extinction events appear to be correlated in time, and probably share evolutionary influences (Marshall and Corruccini 1978).
Multiple parameters beyond the simplified “niche availability vs. energy restriction” dichotomy have the potential to influence how (or whether) dwarfing proceeds in a given situation (Table 6.1). To varying degrees, many of these factors are related to phylogeny. For example, colobines are generally less encephalized than cercopithecines, and some evolutionary reduction in encephalization may actually characterize the colobine lineage as a group (Isler et al. 2008). Perhaps this implies that colobines are already physiologically or evolutionarily pre adapted to brain size reduction (largely a prenatal phenomenon), such that further reduction in this direction would evolve more easily than in a cercopithecine under the same selective regime, for example. Alternatively, it could be that colobines already occupy the lower limits of relative brain size without incurring significant fitness disadvantages. For this reason, we might predict that further reduction in brain size would actually be less likely in a colobine than in a cercopithecine, given equivalent selective pressures.
Table 6.1. Factors influencing the dwarf phenotype. * These factors have an especially strong phylogenetic component, whereas the others will be independent of (or only indirectly related to) phylogenetic affinities. Ancestral (starting) morphology* Ancestral (starting) growth pattern* Genetic and genotype-phenotype Ancestral life-history parameters* correlation structure* Dietary physiology* Locomotor adaptations* Timescale of dwarfing “event” Nature of founding population (# of individuals and their genetic diversity) Selective regime Degree of isolation (biogeographic, genetic) Competition for resources Resource/energy abundance Predation pressure Climate and climatic (in)stability
Fundamental dietary physiology likely places constraints on how dwarfing proceeds in a primate lineage. A dietary generalist may be in a position to reduce its body size while preserving metabolically expensive neural tissue by exploiting energy dense foods. This model would seem to fit the talapoin monkey well. In contrast, a dedicated folivore (such as the simakobu monkey) will tend to begin with a lower metabolism than an omnivore of similar mass, and will be size limited by the minimum volume of gut tissue necessary to process its low quality diet. Thus, the diets of colobine monkeys may limit their potential phenotypic responses to reduced body size. Offspring brain size, for instance, may bear a particular burden in animals
184 with a low metabolism, as predicted by the maternal energy hypothesis (Martin 1981, 1996). Comparative studies of the scaling of encephalization in other primate “dwarfs” can shed light on the relationship between dietary physiology and brain size. The small bodied kinda baboon (Papio cynocephalus kindae ) is an appealing subject among cercopithecines for such a study. Basic parameters of an animal’s life history could also influence the evolutionary effects of dwarfing on adult phenotype. I have made a distinction between pre and post natal growth trajectories in discussing how dwarfing proceeds developmentally. Importantly, the precise allocation of growth to the gestational period vs. postnatal ontogeny also varies among primates (Leigh 2004). For example, a change in exclusively postnatal brain growth patterns has more potential to impact the eventual adult encephalization value in a taxon like Saimiri (which undergoes significant postnatal brain expansion) than in Papio (which achieves most brain mass prenatally) (Leigh 2004). Locomotor adaptations may influence how primates respond to a dwarfing scenario. Faced with scarce, more widely dispersed food resources, a large bodied suspensory primate might adapt differently than a mid sized arboreal or terrestrial quadruped. The Miocene hominoids of Asia that gave rise to modern gibbons became reliant on brachiation to move between foraging points in the forest (Ford and Nowak 2010), whereas talapoin ancestors in Africa did not have the locomotor apparatus to adopt such a strategy (Prof N.G. Jablonski pers. comm.). Climate and climatic stability present another variable that may affect an animal’s phenotypic options. Few non human primate species live outside the tropics, and those that do (Macaca fuscata in Japan, Rhinopithecus in China) are mid to large bodied (8 18 kg range). A seasonal or cold environment may present a physiological barrier to a large brained primate with a high surface area to volume ratio (Prof. N.G. Jablonski, pers. comm.). Whereas many other mammals have adapted to hibernate or enter torpor seasonally, such a metabolic strategy may not be available to a small bodied animal with an energy hungry brain.
185 Expectations for cranial morphology in a dwarf primate
We can formulate several expectations for cranial morphology in a dwarf primate, depending on the type of selective pressures (i.e., energy restriction or niche separation) and the evolutionary developmental mechanisms of dwarfing involved (i.e., prenatal and/or postnatal growth modifications). Based on the comparisons in this thesis, few cranial features were identified that may potentially be common to all dwarf primates. A relatively short palate appears to characterize the cranium of the talapoin and the Natuna monkey, but not the simakobu. The simakobu and talapoin have larger orbits relative to their cranial size than their non dwarf relatives, but this is not true for the Natuna monkey. With respect to the bony orbits, we can only say that none of the dwarf primates has relatively small orbits compared to its larger bodied relative. In a primate that has evolved reduced body size via ontogenetic scaling, we expect the standard cranial traits that were used to build the null hypotheses in this thesis: relatively large orbits and brain, small face, and higher encephalization. As discussed in the previous section, ontogenetic scaling is probably the “easiest” way to reduce body size, so almost any selection that favors smaller size could result in ontogenetic scaling. This makes it a poor indicator of the specific selective forces involved in any given instance, only suggesting that the ancestral growth pattern was probably altered post natally. Thus, morphological signs of ontogenetic scaling, rather than providing evidence for a specific selective regime, only reduce the likelihood that the primate is the product of extreme energy restriction dwarfing. Energy restriction dwarfing is expected to disproportionately affect the size of energetically costly organs, in addition to reducing overall metabolic requirements. To best exploit the scarce energetic resources available, other specific features may evolve, such as dental adaptations for processing fallback foods more efficiently (Lambert et al. 2004). In the cranium, the brain (and, possibly, eyes) would be likely targets for size reduction, due to the metabolic costs of neural tissue. Reductions in brain size will be especially salient in the primate cranium, because neurocranial expansion is a defining feature of the Order. These expectations lead us back to the question of dwarfing in the Natuna monkey. Its cranial morphology does not fit at either extreme of the selective and mechanistic dwarfing spectrum outlined here. Overall cranial shape in Presbytis natunae does not fit the expectations of ontogenetic scaling from an ancestral form similar to P. femoralis or P. melalophos . Nor is the reduction in overall cranial size, or in ECV specifically, drastic enough to detect any substantial
186 difference in encephalization in the Natuna monkey compared to its congeners. Based on the few specimens available for analysis in this thesis, P. natunae ’s cranium is close to an isometrically scaled version of P. femoralis for the major components of cranial shape variation. The extent and nature of cranial size reduction in P. natunae does not provide strong evidence for either niche separation dwarfing via ontogenetic scaling or energy restriction dwarfing via reorganization of prenatal development. More data regarding cranial morphology in the Natuna monkey are needed to better resolve its position along the primate dwarfing spectrum.
Dwarfing and Homo floresiensis
What do these results mean for our understanding of Homo floresiensis ? Although LB1 is not the subject of this thesis, it is nonetheless a key motivation behind it. Each case study has relevance to the hypothesis that LB1 represents a dwarfed lineage. A Miopithecus like model (i.e., ontogenetic scaling) of dwarfing from our current definition of a Homo erectus like morphology is clearly incompatible with the LB1 cranium. The expectation of such a model would be a paedomorphic cranium with a relatively large braincase, whereas LB1’s neurocranium is relatively small compared to a Homo erectus . This implies that a “niche separation dwarfing” scenario applied to a Homo erectus like ancestor can be rejected for Homo floresiensis . Of the three comparisons in this thesis, that of the simakobu and proboscis monkeys may be the most relevant to the issue of LB1 in that the putative dwarf species, Simias concolor , is less encephalized than its larger relative, Nasalis larvatus . Although the magnitude of size difference between these two colobines is not as pronounced as the difference between the Flores hominin and Homo erectus , the Nasalis Simias example nonetheless provides an empirical example of both absolutely and relatively smaller brain size in the smaller bodied of two closely related primate taxa. At least qualitatively, the apparently significant reduction in brain size in an island isolate such as H. floresiensis is compatible with an event approaching the “energy restriction dwarfing” extreme of the primate dwarfing spectrum. Comparison of the Natuna Island leaf monkey with Presbytis melalophos and P. femoralis provides a case of dwarfing that is less drastic than either of the other two pairs. As a result, the differences in cranial shape that distinguish P. natunae from the other species are less pronounced. Thus, a P. natunae like model of dwarfing is not directly relevant to Homo
187 floresiensis , except as an example of moderate body size reduction that does not appear to entail a significant change in neurocranial proportions or encephalization relative to larger related species.
LB1 cranial morphology
A handful of studies have examined the cranial shape and allometry of the LB1 skull directly. Gordon et al. (2008) assessed the external shape of the cranial vault using linear dimensions from the original H. floresiensis publication (Brown et al. 2004). They concluded that size adjusted variables from LB1 cannot be accommodated within the cranial variation of a large and diverse modern human sample, and that the LB1 cranium more closely resembles Homo erectus sensu lato and Homo habilis . Falk et al. (2009; 2005) reported that the endocast of LB1 (constructed using CT scan images) shows evidence of global brain reorganization, which may help to explain the combination of human like behaviors and an ape sized brain attributed to Homo floresiensis . Baab and McNulty (2009) examined LB1 cranial size and shape in the context of hominin cranial allometry, concluding that LB1 is most compatible with predictions for a small archaic Homo rather than a small modern human.
Is the cranial morphology (shape, size, proportions) of LB1 consistent with island dwarfing? Based on the case studies in this thesis, dwarfing cannot be ruled out as an explanation for the origin of Homo floresiensis . Importantly, the comparisons presented here emphasize that cranial form in island dwarfing need not conform to the expectations of ontogenetic scaling. While this finding has been previously reported in studies of ungulates (Malagasy hippos, Weston and Lister 2009; Mediterranean goat, Köhler and Moyà Solà 2004) it is a novel result for primates. To fit the LB1 cranium into the conceptual framework outlined in this chapter, I hypothesize either (1) drastic developmental reorganization of a Homo erectus like ancestor— i.e., an energy restriction dwarfing event; or (2) a less extreme dwarfing scenario from an ancestral hominin which was smaller bodied and less encephalized than Homo erectus . The latter situation could entail elements of both niche separation and energy restriction dwarfing, depending on the nature of the ancestral form and on the many other evolutionary variables involved (e.g., those in Table 6.1). Notably, the drastically small adult brain size of LB1 does not necessarily require a drastic change in prenatal brain growth relative to Homo erectus . In contrast to the gestationally biased brain growth strategy of Old World monkeys, chimpanzees and humans save a large portion of total brain growth for the postnatal period (Leigh 2004). Both parsimony and available
188 evidence (from the Mojokerto child specimen, in particular) suggest that the Homo erectus brain also underwent substantial postnatal expansion (Coqueugniot et al. 2004; Leigh 2006; Walker and Ruff 1993). Although the LB1 specimen itself can tell us little about the pattern of brain ontogeny in H. floresiensis , we can at least say that with an ECV of 400 cm 3, the adult brain of LB1 is substantially larger than published mass estimates for H. erectus neonates, which range from 200 g to 323 g (Leigh 2006; Walker and Ruff 1993). Therefore, a significant decrease in prenatal brain growth need not strictly be postulated if H. floresiensis evolved from an erectus like ancestor—changes in the rate and duration of brain growth could theoretically be limited to postnatal ontogeny. Significantly, based on his analysis of brain ontogeny and life history in Homo erectus , Leigh (2006:107) concluded, “…these results strongly suggest that evolutionary changes in patterns of early development are decoupled from changes in late development, and thus human life history evolution cannot be seen as a tightly integrated suite of characteristics.”
Open questions and future directions
The research presented in this thesis leaves many questions unanswered and has generated several hypotheses regarding cranial allometry and the evolution of brain size associated with reduced body size in primates.
Magnitude of static cranial allometry
In both guenon species, I found evidence that adult female static (cranial) allometry is stronger than in adult males. This result is counterintuitive in that “male like” cranial features—increased prognathism, zygomatic flaring, and smaller relative size of the neurocranium—are typically associated with larger size in guenons and primates in general. Is the apparently stronger association between cranial size and shape in female guenons merely a statistical artifact of small sample sizes? If not, is it a phenomenon that is common to other guenon species? What would cause such a phenomenon, developmentally? One hypothesis is that, in these species at least, female adult static allometry may better reflect the late ontogenetic trajectory (possibly shared by males and females) than does male adult static allometry (Figure 6.1). With access to adequate ontogenetic data, this hypothesis can be tested.
189 Correlation between brain and cranial size
In the male samples of both Nasalis and Simias , I found that brain size (as ECV) and cranial size (CS) were highly correlated, whereas in females they were not. As discussed in Chapter 4, this is counterintuitive in that males of these two species have a smaller proportion of cranial size devoted to the neurocranium than do females. Why would this be? There is a wider range of ECV and CS values among males of these species compared to females, so the higher correlation may be a statistical artifact. In allometric studies, larger size variation within samples tends to result in higher correlations (e.g., Steudel 1982). In addition, correlations within the Simias male sample are particularly prone to statistical artifacts because the sample is so small (n=10). Thus, although we might hypothesize biological explanations for the discrepancy between male and female correlations, statistical issues provide the most likely explanation. Further biological hypotheses would be warranted if this result were obtained using larger sample sizes and/or more species.
Encephalization and energetic constraints
What is the best approach to evaluating encephalization in sexually dimorphic species? When explicitly reproductive parameters are at issue, restricting the analysis to females is logical (Isler et al. 2008). In the comparison of encephalization, it is less clear that female data should always be preferred. However, Martin (1996) has argued convincingly for the unique role of the mother in the evolution of mammalian brain size, due to metabolic constraints during gestation (the “maternal energy hypothesis”). The choice of female only as opposed to pooled sex mean values for brain and body size can significantly alter the picture of comparative encephalization between species (as in the case of Nasalis and Simias , Chapter 4). In most primate species, using only female brain and body size data yields higher encephalization estimates than would male only, or pooled sex data. Should the approach be altered when dealing with monomorphic, or even “reverse dimorphic,” species? As discussed in Chapter 5, it appears that Presbytis melalophos and P. natunae males have larger ECVs than females of equal or larger body mass. Does this have any biological significance? Brain tissue is energetically expensive (Aiello and Wheeler 1995; Mink et al. 1981), and the significant correlation between basal metabolic rate (BMR) and adult brain mass is not surprising (Isler and Van Schaik 2006). In times of nutritional shortage, there could be an advantage to reducing the energy allocated to neural tissue, provided that the energetic benefit
190 outweighed any costs associated with a smaller brain (e.g., reduced cognitive or sensory capabilities). Köhler and Moyà Solà (2004) suggest that this explains the apparently drastic decrease in both ocular and brain size in the insular goat Myotragus . Indeed, lower BMR is associated with extant small island endemic birds and mammals compared to their mainland counterparts (McNab 1994; 2002). The Maternal Energy Hypothesis (Martin 1981; 1996) states that primate brain size is tied to maternal metabolic turnover. Therefore, large brained primates tend to have high metabolic rates. This also implies that in primates with a low BMR, fetal brain growth will be constrained by the mother’s available metabolic resources (Martin 1996). Martin’s hypothesis is therefore consistent with the idea that scarcity of energetic resources might disproportionately affect brain size. As discussed earlier in this chapter and in Chapter 4, I suggest that this effect may explain reduced relative brain size in Simias concolor . Lande (1979:414) hypothesized “…that encephalization in primates decreased the genetic correlation between brain size and body size within populations, which facilitated further encephalization in the human lineage by avoiding antagonistic selection on brain and body sizes.” Although Lande proposed this genetic decoupling of brain and body size in terms of allowing further increases in relative brain size, it should likewise allow decreases in relative brain size. The simakobu (and possibly, Homo floresiensis ) may provide examples of this phenomenon, which is compatible with energy restriction dwarfing, as discussed in this chapter. How could we test the hypothesis that selection for reduced energy requirements led to reduced absolute and relative brain size in the ancestors of Simias concolor ? One approach would be to compare the BMR of the simakobu to the expected value for an “average” colobine of its body mass. Similarly, the degree of encephalization and BMR in the other Mentawai Islands primates could be compared to their mainland counterparts. One caveat to this approach is that the other Mentawai primates probably reached the islands more recently than the simakobu, so they may not share influential periods of its evolutionary history on the islands (Harrison et al. 2006).
Summary of Contributions
This thesis addressed the cranial morphology of dwarf primates using empirical data from extant species. A suite of quantitative methods were employed to analyze and compare cranial form and
191 allometry. The results of this research indicate that no single model for evolutionary reduction in body size can account for the variation in cranial form exhibited by modern primate dwarf species. Instead, a theoretical framework for interpreting instances of dwarfing in primates is proposed. This work sheds light on the debate over the evolutionary affinities of Homo floresiensis , questioning some assumptions that have been made with respect to the island dwarfing hypothesis in particular. While this thesis has improved our understanding of cranial allometry in primate evolution, it has also raised new questions and highlighted fruitful directions for future research.
Appendix
Glossary
Airorhynchy – An attribute of facial profile in which the plane of the palate is inclined such that the posterior nasal spine is more inferior relative to the anterior nasal spine. Considered a defining character of the Asian great apes Pongo and Sivapithecus (cf. klinorhynchy). Allometry – Variation in a biological trait associated with variation in overall size. Centroid size – The square root of the sum of the squared distances of all landmarks from the configuration centroid. This is a one-dimensional measure of the degree of dispersion around the centroid, and is the scaling factor of choice for superimposition based morphometric analysis. Correlation – Unless otherwise stated, Pearson’s product moment correlation. Euclidean Distance Matrix Analysis (EDMA) – A suite of analysis techniques for comparing form, shape and growth in a way that is invariant to coordinate system. Analyses are based on full matrices of all possible interlandmark distances . Encephalization Quotient (EQ) – A metric that expresses relative brain size as a ratio between observed and expected brain mass, based on an allometric regression equation. Here, the equation published by Eisenberg (1981) is used for EQ calculations. Encephalization – A general term referring to the size of the brain relative to the body or to some part of the body. (cf. EQ, RBS) Evolutionary allometry – Concerns the shape changes associated with size differences over evolutionary time and across species (interspecifically). Form – All aspects of size and shape . “That characteristic which remains invariant under translation, rotation, and reflection of the object.” (Lele 1991:407) Form difference – In this thesis, a feature (such as an interlandmark distance ) which is significantly larger or smaller in one sample than in the other, in absolute terms. That is, the interlandmark distances in the analysis have not been scaled (cf. shape difference ). Full Procrustes Fit – Although some superimposition algorithms force all configurations to have a centroid size of exactly 1.0, a slightly closer least squares fit can be obtained by forcing only the consensus configuration to have unit centroid size, and allowing the centroid size of each specimen configuration to vary with the cosine of the angle between the vector of shape
193 coordinates of that specimen and the vector of the mean shape. This “full Procrustes fit” (Rohlf 1999) algorithm is the method implemented in the software MorphoJ (Klingenberg 2011), and thus, pertains to the superimpositions used in this thesis. Generalized Procrustes Analysis (GPA) – A procedure for analyzing landmark configurations that involves superimposing configurations to control for rotation, translation and scale using a predetermined fitting algorithm. Geometric mean – The nth root of the product of n distances. This is a one-dimensional measure of central tendency, and is the scaling factor used here for all scaled analyses based on interlandmark distances . Heterochrony – Evolutionary differences in the rate and timing of development. Hypermorphosis – The scenario in which a descendant taxon achieves a hyper adult morphology (peramorphosis) at larger adult body size than the ancestral taxon. Hypomorphosis – The situation in which a descendant taxon is juvenilized in shape (paedomorphic) and also achieves smaller adult body size than the ancestral taxon. Interlandmark distance – The linear distance between two landmarks in a configuration. (In the context of EDMA , synonymous with linear distance .) Kendall’s rank correlation τ – A non parametric rank correlation test, used here when samples under consideration are not normally distributed (as determined by a Shapiro Wilk Test ). Klinorhynchy – An attribute of facial profile in which the plane of the palate is inclined such that the posterior nasal spine is more superior relative to the anterior nasal spine. Considered a defining character of the African (great) apes (cf. airorhynchy). Linear distance – The length of a line segment connecting two points in Euclidean space. (In the context of EDMA, used interchangeably with interlandmark distance .) Mahalanobis’ distance (D) – A generalized statistical distance metric that adjusts for correlation among variables. Computed as the squared distance between two means divided by the pooled sample variance covariance matrices (Zelditch et al. 2004). Mean form – The form represented by a matrix composed of the average distance between each landmark pair across the entire group. Mean shape – In the context of distance based analyses, the shape represented by the matrix of interlandmark distances composed of each element of the mean form matrix divided by the geometric mean of those elements. In superimposition based analyses, the sample average position of each landmark now composes a consensus configuration or mean shape for the
194 sample, which is roughly analogous to the configuration represented by the mean shape matrix calculated using EDMA (although they will differ in their particulars). Ontogenetic allometry – Shape changes associated with growth and development of an individual over the course of its life history. Paedomorphosis – The process by which the adult of a descendant taxon resembles the juvenile or subadult of an ancestral taxon (cf. peramorphosis ). Parallel allometry – Two groups display parallel allometry if shape is related to size in the same way in both groups. In such a case, the allometric trajectories may either be collinear (coincident ) or not. Pearson’s rank correlation ρ – A non paramentric rank correlation test, used here when samples under consideration are not normally distributed (as determined by a Shapiro Wilk Test ). Peramorphosis – The process by which a descendant taxon at a given ontogenetic stage goes beyond the ancestral taxon at the same stage, producing an exaggeration of the ancestral adult traits (cf. paedomorphosis ). Principal coordinates analysis (PCOORD), PCO – As implemented in WinEDMA, a procedure for dimensionality reduction that projects individuals onto principal coordinate (PCO) axes describing the dimensions that account for the majority of variation between individuals. Procrustes coordinates – The new landmark coordinates of each individual after translation, scaling, and rotation in Generalized Procrustes Analysis (GPA). That is, each Procrustes coordinate is the x, y, or z position of a given landmark in the superimposed space. Procrustes distance – A measure of shape distance, approximately equal to the Euclidean distance between two configurations after Procrustes superimposition and projection into the tangent space. That is, the square root of the sum of squared distances between corresponding landmarks in two configurations. Configurations may represent single individuals or group mean shapes. Shape – A property closely related to form , but it is additionally invariant to scaling. Objects have the same shape if they are geometrically similar, even if they are different in size. In this thesis, all references to an object’s shape imply that the interlandmark distances or landmark configurations involved have been scaled . In terms of analyses, a specimen’s or a sample’s shape means a collection of shape variables . Depending on the analysis, this will be one of three things: 1) the aggregate of Procrustes shape coordinates for the sample, 2) one or more PC scores from a PCA of all Procrustes coordinates, 3) one or more PCO scores from a PCOORD of interlandmark distances using EDMA. Shape coordinates – See Procrustes coordinates .
195 Shape difference – In distance based analyses in this thesis, a feature (such as an interlandmark distance ) which is significantly larger or smaller in one sample than in the other, relative to the overall size (geometric mean) of the sample mean form. That is, the interlandmark distances in the analysis have been scaled (cf. form difference ). In superimposition based analyses, a shape difference simply refers to the difference between Procrustes shape coordinates after superimposition. Shape space – A space in which the shape of an object is represented by a single point (rather than a configuration of points). This can be the curved shape space, or a tangent (Euclidean) space. Shapiro Wilk Test – A test for normality distribution. A significant p value (here p < 0.05 is used) indicates that the null hypothesis of a normal distribution can be rejected for the sample under consideration. Size – Generally, the physical extent of an organism or part thereof. Local context defines the precise metric being employed for the quantification of size (e.g., volume, mass, length). In distance based morphometric analyses (EDMA) in this thesis, size refers to the geometric mean of all possible interlandmark distances for an individual. In superimposition based morphometric analyses (Generalized Procrustes Analysis, GPA), size refers to the centroid size of a configuration. Static allometry – Variation in shape associated with variation in size among individuals of a single species at a common ontogenetic stage (usually adulthood). Tangent space – The tangent Euclidean space will have the same number of dimensions as the curved shape space that it approximates (Rohlf 1998).
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VITA Brenda C. Frazier
EDUCATION 2011 Ph.D., Anthropology, Pennsylvania State University 2005 M.A., Anthropology, Pennsylvania State University 1999 B.A., French, Wellesley College
SELECTED FELLOWSHIPS AND AWARDS 2008 NSF Doctoral Dissertation Improvement Grant 2008 Research & Graduate Studies Office Dissertation Support Grant, Penn State 2008 Hill Foundation Dissertation Support Grant, Penn State 2005 2008 National Science Foundation Graduate Research Fellowship 2003 2004 University Fellowship, Department of Anthropology, Penn State
FIELDWORK 2009 Crew member, Rusinga Island, Kenya (early Miocene). Team led by H.M. Dunsworth, W.E.H. Harcourt Smith and K.P. McNulty. 2006 Crew member, Fayum, Egypt (late Eocene early Oligocene). Team led by E.L. Simons and E.R. Seiffert. 2004 Crew member, Crazy Mountains Basin, Montana, and Big Horn Basin, Wyoming (late Paleocene early Eocene). Team led by J.I. Bloch, D.M. Boyer and M.T. Silcox.
SELECTED PUBLICATIONS 2010 Frazier BC. The influence of sexual dimorphism on allometric interpretations in sister colobine species. American Journal of Physical Anthropology Supplement 50:107. 2009 Frazier BC, Richtsmeier JT. Craniofacial shape and allometry in sister taxa of disparate body sizes: Nasalis larvatus and Simias concolor . American Journal of Physical Anthropology Supplement 48:129. 2008 Frazier BC, Willmore KE, Richtsmeier JT. Characterizing neurocranial shape in microcephalic children. American Journal of Physical Anthropology Supplement 46:99. 2008 Frazier BC, Mooney MP, Losken HW, Barbano T, Moursi A, Siegel MI, Richtsmeier JT. Comparison of craniofacial phenotype in craniosynostotic rabbits treated with anti Tgf β2 at suturectomy site. Cleft Palate Craniofacial Journal 45(6):571 582. 2007 von Cramon Taubadel N, Frazier BC, Mirazón Lahr M. The Problem of Assessing Landmark Error in Geometric Morphometrics: Methods and Modifications. American Journal of Physical Anthropology 134(1):24 35. 2005 Frazier B, Aldridge K, Richtsmeier JT. Sexual dimorphism and morphological integration in baboons. American Journal of Physical Anthropology Supplement 40:103.