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Late Prehistoric populations in the Ohio area: Biological affinities and stress indicators

Giesen, Myra Jayne, Ph.D.

The Ohio State University, 1992

UMI 300 N. Zeeb Rd. Ann Aibor, MI 48106

LATE PREHISTORIC POPULATIONS IN THE OHIO AREA: BIOLOGICAL AFFINITIES AND STRESS INDICATORS

DISSERTATION

Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University by Myra Jayne Giesen, B.A., M.A. The Ohio State university 1992

Dissertation Committee: Approved by Dr. Paul W. Sciulli Dr. William S. Dancey pjüuZüJ Adviser Dr. Richard W. Yerkes Department of Anthropology Copyright by Myra Jayne Giesen 1992 To my family

11 ACKNOWLEDGMENTS

The magnitude of th is d iss e rta tio n often became an overwhelming personal hell for me, however it could not have been accomplished without support from many directions. Thus, I wish to thank the following individuals for assistance in my times of need. I express sincere appreciation and admiration to Dr. Paul Sciulli, my mentor and friend, for his guidance, constructive criticisms, and support during all phases of my research. Thanks go to the other members of my committee Dr. William Dancey and Dr. Richard Yerkes fo r th e ir suggestions and comments. I thank the following for allowing access to materials in th e ir care: Lane Beck (Peabody Museum of Natural History), Jay Heilman (Dayton Museum of Natural History), Martha P o tter Otto (The Ohio H isto ric a l S o ciety ), Paul S c iu lli (The Ohio S tate U niversity) and David S tothers (University of Toledo). Gratitude is extended to the Department of Anthropology for providing research space and storage, in addition to financial assistance through GTA and GRA assignments throughout my tenure in the Department. I appreciate the

iii services and consultations provided by the Academic Computing Services of The Ohio State University, in addition to the funds which they furnished for mainframe operations. This research was partially supported by a Graduate Research Alumni Award granted by the Graduate School at The Ohio State University. I thank those who read and commented on this manuscript at various stages: Lane Beck, A Joanne Curtin, Annette Ericksen, Andrea Gorzitze, Lee Richardi, Michael Serra, Lori Sheeran, and James Wettstaed. Thanks also is due James Stewart for the illustrations. Last, but most certainly foremost, I wish to express my thankfulness, my indebtedness, and my love to my family who provided financial and moral support while I pursued a goal they never entirely understood. They never let me lose sight of myself or the "bigger picture" of life. To them my deepest gratitude!

IV VITA

December 30, 1962 ...... Born - W ichita, KS 1984 ...... B.A. in Anthropology, The Wichita State University, Wichita, KS 1986 ...... M.A. in Anthropology, The Wichita State University, Wichita, KS 1985-1986 ...... Teaching Assistant, Department of Anthropology, The W ichita S tate University, Wichita, KS 1987-1990 ...... Teaching Associate, Department of Anthropology, The Ohio State University, Columbus, OH 1989-1990 ...... S ta ff O steologist, The Ohio State University Isthmia Excavations, Isthmia, Greece 1990-1991 ...... Research Assistant, Department of Anthropology, The Ohio State University, Columbus, OH 1991-1992 ...... Teaching Associate, Department of Anthropology, The Ohio State University, Columbus, OH 1992 ...... Research Assistant, Department of Anthropology, The Ohio State University, Columbus, OH PUBLICATIONS Sciulli PW, Janini G, and Giesen MJ (1988) Phenotypic selection on the dentition in a Late Archaic population of Ohio. Am. J. Phys. Anthropol. 76:527-534. Giesen MJ (1988) Processual Analysis of Bone, Antler, and Shell Artifact Assemblage from House 2 Annie’s Site. In DJ Blakeslee (ed.): St. Helena Archaeology: New Data, New interpretations. Lincoln, NB: J & L Reprints. Giesen MJ and Sciulli PW (1988) Long bone growth in a Late Archaic skeletal sample. (Abstract) Am. J. Phys. Anthropol. 75:213-214. Giesen MJ and S c iu lli PW (1989) The Pearson Complex: cranial variation and biological affinities. (Abstract) Am. J, Phys. Anthropol. 78:228.

FIELDS OF STUDY Major Field: Anthropology Studies in Skeletal and Dental Variation. Professor PW S c iu lli. Studies in Nutrition. Professor PW Sciulli. Studies in Ohio Valley Prehistory. Professors WS Dancey and RW Yerkes.

VI TABLE OF CONTENTS

DEDICATION...... i i ACKNOWLEDGMENTS...... i i i

VITA ...... V

LIST OF TABLES...... X

LIST OF FIGURES...... XVÜ CHAPTER PAGE I. INTRODUCTION...... 1 Research Objectives ...... 8 H y p o th e s e s ...... 8 I I. MATERIALS...... 11 Fort Ancient T radition ...... 11 Previous Studies of Fort Ancient Skeletal M a t e r i a l ...... 16 Anderson Village Site (33WA4) ...... 22 Buffalo (46PU31) 28 M adisonville (33HA36) ...... 31 SunWatch (33MY57) ...... 38 Sandusky Tradition ...... 40 Indian H ills (33W04) 43 Pearson (33SA9) ...... 46 Petersen (330T9) 49 Summary ...... 50 I I I . OVERVIEW OF RELEVANT RESEARCH...... 54 Biological Distance ...... 54 Metric D ata ...... 58 Nonmetric D a ta ...... 60 Biocultural Stress Indicators ...... 63 A b s c e ss e s ...... 64 A t t r i t i o n ...... 65 Dental Caries ...... 68

vii Tooth L o s s ...... 75 s t a t u r e ...... 76 Long Bone G r o w t h ...... 76 Adult H eight ...... 79 IV. METHODS...... 85 Age Determination ...... 85 Subadult Age Determination ...... 85 Adult Age Determination ...... 86 SÏÏÀ Determination ...... 86 Metric D ata ...... 87 Cranial Metrics ...... 88 Adult Postcranial Metrics ...... 90 Subadult Postcranial Metrics ...... 90 Nonmetric D a ta ...... 91 Biocultural Stress Indicators ...... 95 A b sc e sse s...... 95 A t t r i t i o n ...... 96 C a r i e s ...... 97 Tooth L o s s ...... 98 S t a t u r e ...... 99 Long Bone G r o w t h ...... 99 Adult H eight ...... 100 V. RESULTS...... 101 Age and Sex E s tim a tio n s ...... 101 Biological Distance ...... 102 Cranial Metrics ...... 103 Cranial Discrete Traits ...... 113 Stature and Proportions ...... 122 Biocultural Stress Indicators ...... 128 Dental Pathologies ...... 128 Abscess ...... 154 A t t r i t i o n ...... 157 C a r i e s ...... 158 Tooth L o s s ...... 160 Lone Bone G r o w t h ...... 161 VI. DISCUSSION AND CONCLUSION...... 181 Biological Affinities ...... 181 Biocultural Stress Indicators ...... 184 Dental Pathologies ...... 184 S t a t u r e ...... 185 Long Bone G r o w t h ...... 185 Adult H eight ...... 189 Review of Research O bjectives ...... 198 Concluding Remarks ...... 202 BIBLIOGRAPHY ...... 207

viii APPENDIX A. CRANIAL METRIC DESCRIPTIONS ...... 226 B. POSTCRANIAL METRIC DESCRIPTION ...... 229 C. CRANIAL DISCRETE TRAIT DESCRIPTIONS ...... 232 D. VARIANCE-COVARIANCE MATRICES OF CRANIAL METRICS...... 238

IX LIST OF TABLES

TABLE PAGE 1. The environment’)nment’s effect on genotypically different andand genotypically genotypically similar similar populations. populs . 5 2. Number of burials excavated by early explorers at Madisonville ...... 35 3. Temporal placement of study sites ...... 52 4. Summary of site sample size ...... 53 5. List of cranial nonmetrics ...... 92 6. Data estimates for cranial metric analysis. . . 103 7. Summary of cranial metrics for males and females by s i t e ...... 104 8. Summary of cranial metrics for males by site. . 105 9. Summary of cranial metrics for females by site. 106 10. Mahalanobis’ values between samples with approximately equal numbers of males and females below diagonal"^ and geographical distance (Km)^ above diagonal ...... 108 11. Summary of the 1®^ and 2"° eigenvectors from the principal coordinate analysis for 0^ values and Km^ v alu es ...... 110 12. Distribution of the original seventeen discrete t r a i t s by s i t e ...... 114 13. Summary of traits affected by lack of variation between sites, intercorrelation between traits, age, or sex ...... 115 14. Mean Measure of Divergence values between samples below the diagonal and Harpending/Jenkins’ d® values between samples above diagonal ...... 117

X 15. Summary of the 1®^ and 2"“ eigenvectors from the principal coordinate analysis for MMD values and Harpending/Jenkins d® values ...... 117 16. Adult stature arranged from shortest to tallest for both sexes by site ...... 122 17. Analysis of variance for adult height ...... 123 18. Adult sta tu re proportions by sex ...... 125 19. Summary of Anderson maxillary permanent dental pathology by tooth ty p e ...... 129 20. Summary of Anderson mandibular permanent dental pathology by tooth ty p e ...... 130 21. Summary of Buffalo maxillary permanent dental pathology by tooth ty p e ...... 131 22. Summary of Buffalo mandibular permanent dental pathology by tooth ty p e ...... 132 23. Summary of Indian Hills maxillary permanent dental pathology by tooth type ...... 133 24. Summary of Indian Hills mandibular permanent dental pathology by tooth type ...... 134 25. Summary of Madisonville maxillary permanent dental pathology by tooth ty p e ...... 135 26. Summary of Madisonville mandibular permanent dental pathology tooth type ...... 136 27. Summary of Pearson maxillary permanent dental pathology by tooth type ...... 137 28. Summary of Pearson mandibular permanent dental pathology by tooth ty p e ...... 138 29. Summary of SunWatch maxillary permanent dental pathology by tooth type ...... 139 30. Summary of SunWatch mandibular permanent dental pathology by tooth ty p e ...... 140 31. Summary of Anderson permanent dental caries pathology by age and by tooth ty p e ...... 141 32. Summary of Buffalo permanent dental caries pathology by age and by tooth type ...... 142

x i 33. Summary of Madisonville permanent dental caries pathology by age and by tooth ty p e ...... 143 34. Summary of Pearson permanent dental caries pathology by age and by tooth ty p e ...... 144 35. Summary of SunWatch permanent dental carie s pathology by age and by tooth ty p e ...... 145 36. Anderson distribution of carious lesions by tooth by tooth surface and tooth ty p e ...... 146 37. Buffalo distribution of carious lesions by tooth by tooth surface and tooth ty p e ...... 147 38. Indian Hills distribution of carious lesions by tooth by tooth surface and tooth type ...... 148 39. Madisonville distribution of carious lesions by tooth by to oth surface and tooth ty p e ...... 149 40. Pearson distribution of carious lesions by tooth by tooth surface and tooth type ...... 150 41. SunWatch distribution of carious lesions by tooth by tooth surface and tooth type ...... 151 42. Age distribution for Total Caries Index ...... 153 43. Age distribution for Disease Index ...... 153 44. Kolmogorov-Smirnov test for age distribution, above diagonal are values for data in Table 42 and below diagonal are values for data in Table 43. 154 45. Age distribution by sample for Abscess Index. . 155 46. Age distribution by sample for Caries Index. . . 155 47. Age distribution by sample for AMTL Index. . . . 156 48. Age d istrib u tio n by sample fo r DM (decayed and missing) Index ...... 156 49. Correlations between chronological age estimates and the maximum diaphysial length of the humerus. 164 50. Correlations between chronological age estimates and the maximum diaphysial length of the radius. 165 51. Correlations between chronological age estimates and the maximum diaphysial length of the ulna. . 166

xii 52. Correlations between chronological age estimates and the maximum diaphysial length of the femur. 167 53. Correlations between chronological age estimates and the maximum diaphysial length of the tibia. 168 54. Correlations between chronological age estimates and the maximum diaphysial length of the fibula. 169 55. Correlations between chronological age estimates and the maximum length of th e c la v ic le ...... 170 56. Correlations between chronological age estimates and the maximum height of the scapula ...... 171 57. Correlations between chronological age estimates and the maximum breadth of the ilium ...... 172 58. Regression formulae for lone bones and irregular bones from Buffalo, Pearson, and SunWatch. . . . 173 59. Regression formulae for long bones and irregular bones from Buffalo, Pearson, and SunWatch combined ...... 174 60. Regression formulae for the femur and the tibia from a Late Archaic sample and the Denver growth study ...... 174 61. Variance-covariance matrix of cranial metrics for Anderson males and fem ales ...... 239 62. Variance-covariance matrix of cranial metrics for Anderson males ...... 240 63. Variance-covariance matrix of cranial metrics for Anderson females ...... 241 64. Variance-covariance matrix of cranial metrics for Buffalo males and fem ales ...... 242 65. Variance-covariance matrix of cranial metrics for Buffalo males ...... 243 66. Variance-covariance matrix of cranial metrics for Buffalo females ...... 244 67. Variance-covariance matrix of cranial metrics for Indian Hills males and females ...... 245 68. Variance-covariance matrix of cranial metrics for Madisonville males and females ...... 246

xiii 69. Variance-covariance matrix of cra n ia l m etrics fo r Madisonville males. . . . 247 70. Variance-covariance matrix of cranial metrics fo r Madisonville females. . . 248 71. Variance-covariance matrix of cranial metrics for Pearson males and females. 249 72. Variance-covariance matrix of c ra n ia l m etrics fo r Pearson males ...... 250 73. Variance-covariance matrix of cranial metrics for Pearson females...... 251 74. Variance-covariance matrix of cranial metrics for Petersen males and females. 252 75. Variance-covariance matrix of cranial metrics for SunWatch males and females, 253 76. Variance-covariance matrix of cranial metrics SunWatch m ales ...... 254 77. Variance-covariance matrix of cran ial m etrics fo r SunWatch fem ales ...... 255

XIV LIST OF FIGURES

FIGURES PAGE 1. Location of sites included in this study ...... 6 2. Chronologies for the Fort Ancient Tradition (after Henderson 1992) ...... 15 3. Chronologies for the Sandusky Tradition (after Bowen 1992) ...... 42 4. Three dimensional map of the first three eigenvectors of a principal coordinate analysis for Mahalanobis ' values ...... 109 5. Locations of the Mahalanobis’ (•) and the geographic Km® (■) after a Procrustes Rotation. 111 6. Three dimensional map of the first three eigenvectors of a principal coordinate analysis for Harpending/Jenkins d® values ...... 118 7. Locations of the Harpending/Jenkins’ d® (#) and the geographic Km® (■) after a Procrustes R otation ...... 120 8. Femur growth curves ...... 175 9. Tibia growth curves ...... 176 10. Femur acceleration curves ...... 177 11. Tibia acceleration curves ...... 178 12. Femur velocity curves ...... 179 13. T ibia v e lo city curves ...... 180

XV CHAPTER I

INTRODUCTION

understanding the dynamics of prehistoric populations is an interest shared by both biological anthropologists and archaeologists. Biological anthropologists base their interpretations of past human activities primarily on osteological and odontological data, while archaeologists base their interpretations on preserved material culture (e.g., artifacts and ecofacts). As the discipline of anthropology continues in its endeavor to be holistic, biocultural research into the prehistoric past has become more prominent, replacing single sub-disciplinary pursuits. Biological data are being implemented to test hypotheses based on cultural evidence and are being used in conjunction with cultural data to develop new interpretations through the relatively new subfield of bioarchaeology (Buikstra 1976). The intent of this research is to investigate biological measures, biocultural stress indicators, and growth patterns in two Late Prehistoric archaeologically designated cultural manifestations. Inquiries of this nature will broaden our current understanding of the

1 2 cultural/environmental relationship by introducing biological information to a field traditionally dominated by materialistic research. Biological affinity, nutritional data, and growth patterns will provide insight into genetic and environmental features influencing the populations. Ohio has a t le a s t two major m aterially defined archaeological traditions belonging to the Late Prehistoric period (A.D. 1000 to A.D. 1700): Fort Ancient in southern Ohio and Sandusky in northern Ohio. Archaeologists are divided as to the significance of the differences in material culture between these two local traditions. Questions such as the following frequently arise and have not as yet been adequately answered: Does each cultural group represent a biological population? Are they each indigenous groups or is one (or both) group(s) the result of a migration of peoples from other regions into Ohio? Do one or both represent fusion or fission between local and non­ local cultural or biological populations? Analysis of material culture provides some clues to these questions, but it does not provide a definitive answer. Biological analyses provide an independent form of data which may contribute to the clarification of some of these questions. Skeletal biodistance is a statistical method for measuring relative genetic affinity among and between populations. Biodistance measures are based on polygenic traits which reflect population diversity. Polygenic traits 3 have both environmental and genetic components. Because true genetic distance usually cannot be obtained from past populations, skeletal biodistance studies examine variation in those skeletal and dental measures which are thought to reflect genetic relatedness within and between past populations. In this research biodistance will facilitate our understanding of the genetic relationships among and between Fort Ancient and Sandusky populations. The nutrition of past populations is another issue of interest, the study of which can utilize both biological and cultural data. Paleonutritional data provide insight into a population’s health status and may reveal cultural behavior by identifying certain food stuffs in the diet. The inquiry into health and nutrition by assessing biological stress markers is of key interest in this research. First, the populations in question represent the earliest maize horticulturalists in the area. The adoption of maize would have brought about change in the material culture in terms of function. In addition, this major functional change would bring changes in diet, nutrition, and health status, and influence the direction of stylistic change. Secondly, since both pre- and post-contact populations are to be investigated, the idea that European contact had devastating effects on Native North American’s health can be evaluated. It is important to acknowledge that disease and malnutrition are influenced by both environmental and genetic parameters; 4 therefore one must control for the genetic structure of populations in an area when inquiring into nutritional and health data. Using the previously mentioned research topics from the archaeological record two lines of investigation will be pursued in this study: first, the measures of genetic affinity through biodistance and second, the measures of biocultural stress (short term biological responses to cultural or environmental pressures). These two lines of evidence allow fo r evaluation of 1) genetic closeness and 2) biocultural adjustments, particularly cultural patterns related to nutritional health. If samples of individuals within or between an archaeological manifestation (i.e.. Fort Ancient and Sandusky) are genotypically the same and show the same stress patterns, then the "environmental pressures" must be parallel. However, if samples which are genotypically similar show dissimilar nutritional and growth patterns, then the environmental pressures must be different for the archaeological manifestations. If the separate archaeological manifestations are genetically similar, then environmental pressure can best explain the biological variation. Alternatively, if the separate archaeological manifestations are genetically different, then the explanation for biological variation in terms of environmental pressures becomes less clear. Refer to Table 5 1 fo r a model of the environment’s influence on d iffe re n t genetic and phenotypic combinations.

TABLE 1. The environment’s effect on genotypically different and genotypically similar populations.

GENOTYPICALLY SIMILAR / STRESS INDICATORS SIMILAR genotype 1 stress 1

GENOTYPICALLY SIMILAR / STRESS INDICATORS DIFFERENT genotype 1 < 1 stress 1 genotype 1 stress 2

GENOTYPICALLY DIFFERENT / STRESS INDICATORS SIMILAR genotype 1 <-ssïlîS!aîaïJ_* stress 1 genotype 2 <-îEïi£a!BînîJ—* stress 2

GENOTYPICALLY DIFFERENT / STRESS INDICATORS DIFFERENT genotype 1 > stress 1 genotype 2 stress 2 genotype 1 stress 3

genotype 2 <-sasits 2ssaiJ_*. stress 4

Two archaeological manifestations suitable and available for analysis are the Fort Ancient Tradition and the Sandusky Tradition (Figure 1). Although it does not appear in the literature per se, it is a common (mis)conception that populations belonging to the same c u ltu ra l phenomena represent a c o lle c tiv e gene pool. Consequently, it has been inferred that populations within 6

Lake Erie

Indian Hills, Peters» off Pearson

Ohio

'Anderson

Madisonville West Virginia

iBuffalo Miles Kentucky Kilometers

FIGURE 1. Location of sites included in this study. 7 Fort Ancient, as well as populations within Sandusky are genetically similar. Graybill (1984:40), however, proposes that "Fort Ancient is not a cohesive cultural entity" and that phases (foci) within Fort Ancient represent different local tra d itio n s . Hence i t may be predicted th a t d iffe re n t lo cal populations comprised the Fort Ancient Tradition and that the different foci are instead comprised of genetically different populations. The same may hold true for the Sandusky Tradition. Since the Sandusky and Fort Ancient traditions are geographically separated and are recognized as distinct archaeclogical manifestations there may be some support for the idea they are different in terms of their biology (e.g. Sandusky is a separate and distinct gene pool from Fort Ancient). As indicated above, populations belonging to the same cultural phenomena are generally believed to represent a common gene pool. Biological examination of affinity within and between distinct groups can test the validity of this believed commonality. Data for analyses come from skeletal samples which have been identified as belonging to the same cultural tradition, as well as skeletal samples from a contemporary adjacent cultural tradition. Skeletal samples identified as belonging to the Fort Ancient Tradition procurable for examination include: Anderson Village (33WA4), Buffalo (46PU31), Madisonville 8 (33HA36), and SunWatch (33MY57) s ite s . An adjacent contemporary culture of the Fort Ancient Tradition is the Sandusky Tradition. Skeletal materials of this culture available for analysis are the Pearson Complex (the Middle Cemetery (33SA9)), the Petersen Site (330T9) and the Indian H ills S ite (33W04).

Research Objectives

Understanding the Late Prehistoric populations in the Ohio area requires both knowledge of a single Late Prehistoric tradition's expression in different regions within the area, and comparisons to adjacent distinct traditions. Much archaeological data exist for this period. Recent research centers on the interpretation of regional variation based on available archaeological data. There are two questions which are fundamental to the interpretation of Late Prehistoric populations, and these can best be answered with biological data. First, are archaeological sites that have been designated as the same cultural manifestation g en e tic a lly homogeneous? And second, are a l l maize horticulturalists under the same kinds of stress?

Hypotheses

#1 Are populations from archaeological sites which are designated as the same cultural manifestation genetically homogeneous? g Ho If skeletal samples representative of a particular archaeological culture are genetically homogeneous, then biological distance values will reveal no statistically significant difference between samples. Hi If skeletal samples representative of a particular archaeological culture are not genetically homogeneous, then biological distance will reveal statistically significant differences between samples. #2 Are maize horticulturalists under the same sorts of stress? Ho If indicators of stress are the same in magnitude and pattern among all the maize horticulturalists, then they are experiencing the same types of stress. Hi If indicators of stress are different in magnitude and pattern among the maize horticulturalists, then they are experiencing different types of stress.

To assess the first question cranial metric and nonmetric data will be employed. To assess the second question, the genotypical homogeneity of the populations must first be established. If the populations are shown to be g en etically homogeneous then b io cu ltu ral s tre s s indicators are evaluated for each site and then compared between sites and between Traditions. Biodistance analyses of the cranial metrics will include the analysis of covariance to establish shape and the Mahalanobis’ to establish size variation. Cranial discrete data are assessed using both the Mean Measure of Divergence and the Harpending/Jenkins’ d®. Adult stature is evaluated as a general size measure using the analysis of variance and overall shape is evaluated using comparisons of 10 proportions. These observations will establish whether adult stature is most useful as a biodistance or stress indicator for the sample populations. Biocultural stress is evaluated using subadult growth patterns and dental pathologies. This study also develops a framework upon which further research can be based. For example, if the samples are genetically the same, but the biocultural stress indicators are different, then what is happening at the different site areas to cause these differences? How does the culture under investigation compare to cultures which came before or after it? Would differences or similarities in biological features between these populations best be explained in terms of genetic factors or environmental factors? The results of this investigation provide a context for answering these questions. In sum, this research provides the first extensive survey and comparison of biological data of Late Prehistoric (1000-1700 A.D.) populations in and around Ohio. It furnishes information about the genetic affinity of paleopopulations and health data for populations experiencing a shift from previously hunting -gathering- fishing to maize horticulture. CHAPTER II

MATERIALS

This section provides a brief overview of the Fort Ancient and Sandusky traditions. Within each tradition’s description are site summaries for the samples used in this investigation.

Fort Ancient Tradition

The archaeological manifestation known as Fort Ancient has been characterized as consisting of archaeological complexes of the middle Ohio Valley covering a time span from around A.D. 1000 to about A.D. 1700. The area of th is manifestation encompasses south-central Ohio; north-central and northeastern Kentucky; western West V irginia; and southeastern Indiana. Fort Ancient sites are differentiated from contemporary sites in adjacent areas primarily on the basis of pottery vessels (i.e., shape, surface treatment, and decoration) (Griffin 1943). Fort Ancient society is thought to consist of village horticulturalists with an economy based on maize, beans, and squash with supplemental hunting and foraging (Wagner 1983). This horticultural society is assumed to be

11 12 adjusted to the varied environments of the middle Ohio Valley (Pollack and Henderson 1992). Fort Ancient also can be recognized archaeologically because of a distinct settlement type and a particular material culture. Pollack and Henderson (1992:291) suggest Fort Ancient “developed from a family/hamlet level of sociopolitical organization (early Fort Ancient) to that of a Big Man society (Madisonville horizon)". At the "family/hamlet" level "families cluster into a settlement group or hamlet (25-35 persons) on a (more) permanent basis. The subsistence economy continues to rely heavily on wild foods, sometimes in conjunction with the beginning of horticulture or herding. Storage is more prevalent. During the year individuals or families move out to exploit specific resources; from year to year, the hamlet reforms and fragments as households change locations to minimize resource procurement costs. The hamlet does not form a clearly demarcated political group, and leadership continues to be context specific and minimal. Ceremonialism is little developed" (Johnson and Earle 1987:19-20). While at the Big Man level has been characterized collectively as follows: "Subsistence is heavily focused on agriculture... The local community of perhaps 300-500 people is a territorial division, typically containing multiple clan or lineage segments that live together in a village... The local group is represented by a Big Man, a strong charismatic leader who is essential for maintaining internal group cohesion and for negotiating intergroup alliances. The Big Man is also important in risk management, trade, and internal dispute settlement, and represents his group in the major ceremonies that coordinate and formalize intergroup relationships. His power, however, is dependant on his personal initiative" (Johnson and Earle 1987:20). 13 Thus, Fort Ancient villages are thought to have undergone a transition which reflects this organizational change. Village configuration changes from dispersed hamlets to circular villages with a central plaza and circular zones of habitation, refuse pits, middens, and b u ria ls. Despite an acknowledged time depth of approximately 700 years, there is nonetheless a tendency to view Fort Ancient as an example of a c u ltu ra l "type". However, the boundaries of Fort Ancient are vague and too broadly defined, and according to some researchers, embrace too much variability to impose a uniform settlem ent model (G raybill 1984; Essenpreis 1978; Griffin 1978). Disagreement, as well as ingenious placement of phases by researchers, has l e f t the Fort Ancient lumped and at times split into numerous classification schemes. Generally, Fort Ancient phases are thought to reflect geographic differences rather than temporal differences (Essenpreis 1978; Griffin 1978). Prevalent in the literature are regional interpretations of the Fort Ancient cultural manifestation (Henderson 1992; Cowan 1987; Graybill 1984; Prufer and Shane 1970; and others). Generally these investigative reports are accompanied by their own classification scheme by which to order Fort Ancient subcultures. Many of these schemes result in competing 14 arguments for and against local cultural placement (Figure 2). Recent studies of Fort Ancient societies in the Ohio Valley can be placed into three different categories: 1) those concerned with documenting temporal change within different local traditions, 2) studies of subsistence patterns, and 3) those concerned with developing models of both subsistence and settlem ent (Mass 1987). Researchers within these categories are generally concerned with small scale local perspectives, thus infrequently addressing Fort Ancient as a whole. The cultural history of the Fort Ancient Tradition has been spatiotemporally delineated (Graybill 1984), as well as socioculturally reconstructed (Essenpreis 1978; Brose 1982). Griffin (1978) argues, and rightfully so, that as presently conceived Fort Ancient is too "gross" to be of much use. Graybill (1984), goes one step further and suggests that no such cohesive entity ex isted . The most reoent attempt to synthesize data pertaining to Fort Ancient is Fort Ancietit Cwltural Dvimmks In ike Mfbble Okîo

VaJletj edited by A Gwynne Henderson (1992), contributors provide the results of the Kentucky Fort Ancient Research Project. This report contributes much to our understanding of the organization of Fort Ancient through a regional assessment. It also presents a tentative model Fort Ancient Afchi0oIo(fad Rblorie m I I Qfooolotteal Chroeological fhMet A.D .1800 I m *------■S3SSSST Hbtorte iB dim A.D. 1700 ----- I Contact s Period nMottov hbtoric AD. 1600

A.D. 1500- -

A.D. MOO----- II Foert Ptchbiotle A.D. 1300- - I MlWk P e r M I A.Ü. 1200- -

A.D. 1100- - E aljr C rpfhan

A.U. 1000- - & Graybill 1981 Uunnell 1961 Orirnn 1978 A.D.900 Plufernnd Ess^rels l:hnMA 107(1 1978 Cowan 1987 Henderson 1992

FIGURE 2. Chronologies for the Fort Ancient Tradition (after Henderson 1992). Ol 16 cultural development in Kentucky which briefly is summarized in Figure 2.

Previous Studies of Fort Ancient Skeletai Materiai The research presented in this dissertation is not the first to utilize biological data in an investigation of the Fort Ancient culture. Biological studies pertaining to the sites in this investigation are introduced below, after the site description. More generalized studies of Fort Ancient populations and studies employing sites other than the ones discussed here are as follows.

In 1972, Louise Robbins published The Vrehisiorie of

Fort A»icient CultMre of Centré Oliio Valleii in collab o ratio n with

Georg Neumann, who had collected much of the data. This report examined cranial metrics and morphology from several Fort Ancient samples and historical samples in order to assess their biological affinities. Following Griffin, Robbins and Neumann used four archaeological foci (Baum, Feurt, Anderson, and Madisonville) to organize the Fort Ancient Tradition. In their analysis the Baum Focus is represented by the Baum village site (17

Focus is represented by the Anderson Village Site (46S and 399) (Anderson Museum and National Museum collections); the Taylor mound and village site (25<7 and 69) (Chicago Field Museum of Natural History collection; Fort Ancient Museum collection at Oregonia, Ohio; and from the Kercher collection at Cincinnati, Ohio); and the Stokes site (Id and 19) (Clark County Museum collection at Springfield, Ohio). The M adisonville Focus is represented by the Sand Ridge site (6d and 29) (Peabody Museum collection); the Hahn's Farm site (6d and 29) (Peabody Museum collection); the Turpin site (12d and 149) (Peabody Museum collection); the Campbell Island site (6d and 19) (National Museum and the Ohio State Museum collections); the Madisonville site (175d and 2169) (Peabody Museum, American Museum of Natural History, Cincinnati Art Museum and Cincinnati Museum of Natural History collections); and the Fox Farm site (38d and 259) (American Museum of Natural History collection; Blue Lick Museum collection at Blue Lick, Kentucky; University of Kentucky collection; and the Dodge collection at Lexington, Kentucky). Historical skeletal materials considered were 18 representative of the Seneca (313 and 339), the Shawnee (43), and h is to ric "Muskogid" (183, 39). Robbins and Neumann (1972) identify five North American physical "types" by which to compare Fort Ancient with the eastern United States (e.g., Lenid (453 and 59), Ilinid (173 and 199), Iswanid (333), Muskogid (483), and Dakota (583 and 69)). The Lenid type is "...the predominant physical form in the northeastern Woodland area, and is found in many of the Eastern Algonquian-speaking people, e.g., the Delaware" (1972:9). The Lenid "... display a gradual change in a number of traits, out of which evolved the Ilinid variety of the Late woodland and Upper M ississippi periods" (1972:12). The Ilinid type is represented by a collection from Oakwood Mound of the Fisher Focus of northern Illinois; while the Iswanid type is obtained from the Indian Knoll population on the Green River, Kentucky. The Dakotid (Lakotid) type was considered fo r comparative purposes. This type is thought "... to be of trihybrid origin, stemming from a mixture of Lenid, Walcoid (Muskogid), and Deneid characteristics" (1972:16) which results in a Plains group distribution pattern. The Muskogid (Walcoid), also used for comparative purposes, "... evolved during the Middle Archaic period from earlier Iswanid variety, (and) ... is more typically representative of the Middle Mississippian archaeological horizon during late prehistoric times" (1972:18). 19 Robbins and Neumann identified the Ilinid type for the two northern phases of Baum and Anderson and in the Feurt phase near the mouth of the Scioto River. Some I lin id types also are noted to occur in earlier sites within the Madisonville phase. The second distinct physical type associated with Fort Ancient sites was identified as Muskogid. This type was shown to be more prominent among the Madisonville phase populations. In this interfocus examination of Fort Ancient populations, Robbins and Neumann postulated a higher degree of genetic relatedness between Anderson, Baum, and Feurt foci. They also noted a greater population distance between these foci and the Madisonville focus. The validity of Robbins and Neumann's "types" has been challenged as being the "results of a subjective physiological evaluation" (Baker 1977:12). To Baker "the determination of cranial morphology seems to be observational, based on arbitrary classification of size (often of the "sm all", "medium", and "large" v ariety ) which are subjective ratings of continuous traits" (12). Baker also notes the small geographic radius (120 miles) from which the samples where selected for inquiry. The problems related to Robbins and Neumann’s work conveyed in Baker’s critique are concerns which must be addressed. Typologies are misleading and form an inaccurate approach to the study of human variation. The typological 20 approach used by Robbins and Neumann confines the amount of cranial variation to be observed in Fort Ancient populations by identifying only five possible "types". For Robbins and Neumann, cranial variation only could be identified and explained in fiv e d iffe re n t ways. However, in any so-called "types" or racial grouping there will be individuals who fall within the range of normal variation for another "type" or group. Typologies compress variation into restricted categories and do not allow new combinations of variation to be identified in terms of change; with the typological approach there can be no evolution, only "mixing" of types. In addition to those points just mentioned, other issues of concern include the retention of deformed skulls in the analyses and the inadequate sample size of the prehistoric and especially the historic samples. There is also the bias towards more male specimens in the study than females specimens. Another study incorporating biological data is that of Rodney Riggs. In 1977, Riggs wrote his Master's Thesis on the Turpin site. He evaluated human remains from two distinct mortuary groups from a single component of this multi-component site. He assessed the remains in terms of nonmetric traits from both the cranium and postcranium. Riggs concluded from his intrasite comparison that the two groups represent a single breeding unit. 21 To a limited extent, biological data also have been employed to evaluate subsistence strategies in Fort Ancient societies. Sciulli and Schneider (1986) examined dental caries among prehistorio Ohio populations and found that "while maize may have been available to Early and Middle Woodland populations in th is area (Ohio) i t was not a major contributor to the diet" (1986:21). Evidence for maize in the diet is limited to Late Prehistoric populations. Both Anderson Village, a Fort Ancient site, and Pearson, a Sandusky site, were included in their analysis. These Late Prehistoric populations showed an increase in caries frequencies corresponding with archaeobotanical studies of ratios from Anderson Village and Pearson which suggested a higher consumption of maize. Schneider's (1984; 1986) study of trace elements in tooth enamel from prehistoric skeletons from Ohio revealed that certain elements appear to correspond to specific subsistence strategies. For example, zinc, copper, and iron are elements which characterize hunting-gathering-fishing, while nickel and possibly phosphorus characterize horticulturist. She also found a correlation between elemental composition of the teeth and caries frequencies. Low frequencies of c a rie s and teeth with zinc, copper, and iron were enough to discriminate hunting-gathering-fishing societies from maize horticulturalist. 22 Broida’s (1984) study looking at the stable isotopes (i3c/i2c) in two Fort Ancient populations (Hardin V illage (15GP22) and the Slone site (15PI11)), suggests that these populations derived more than half their dietary carbon from maize, about 65% at Hardin Village and about 79% at Slone. The remainder of this section on Fort Ancient describes the sites used in this study. The archaeological attributes will be considered first. Next, information on the human skeletal remains from the site will be addressed, i.e., numbers of in d iv id u als recovered from the s it e , number of individuals assessed in this study, and existing studies which have utilized skeletal remains from the specific site.

Anderson Village Site (33WA4)

The Anderson Village Site is situated along the Little Miami River, one-fourth mile north of the Hopewellian earthwork of Fort Ancient, and one-fourth mile south of the confluence of the Little Miami River and Caesar's Creek in Washington Township, Warren County, Ohio. Anderson Village represents a permanent village site. Occupation of the site has been set at approximately A.D. 1275 (Nass 1987). Anderson Village’s close proximity to the Fort Ancient earthworks allowed early detection of the site. In 1810, a map of the Fort Ancient earthworks appeared in Tke Mapping of

Oldo to be followed by description by Atwater (1820), Squier and Davis (1848:18-21), and Hosea (1874). 23 The first known recorded reference to Anderson Village (then the Village Site) was by LM Hosea (1874). Warren K Moorehead, in his explorations at the earthworks at Fort Ancient became fa m ilia r with the V illage S ite . Moorehead made inquires of the area in 1887 through 1891. Moorehead's excavations in 1889 revealed three graves, while in his 1890 season he recovered 20 additional graves. Overall, between the years 1887 and 1891, Moorehead claimed to have exhumed a minimum of 132 b u ria ls (in Essenpreis (1982) from Moorehead (1891)). Moorehead's 1891 field report, which was conducted under the auspices of Fredric Ward Putnam, Director of the Peabody Museum, provides the best details of any of Moorehead’s work at the Village Site. Material recovered during the 1891 season at the Village Site were of special interest since they were to be considered for exhibit at the World’s Columbian Exposition 1892-1894. Clifford C Anderson, a researcher under Moorehead’s employment made frequent trips to the Village Site from 1892 to 1900 to establish a representative collection of artifacts from the site. From 1900 to 1906, Anderson maintained a continuous residence at Fort Ancient, at which time he added considerably to his artifact collection. Anderson left the site in 1906 to return again in 1924, whereupon he purchased the Village Site (the site thus became known as the Anderson V illage S ite or Anderson 24 Village). Anderson notes that during his absence, a flood (1913) washed away a fair quantity of the site. In 1925, a museum was erected at the site in order to exhibit Anderson’s collection. Returns from museum admissions supplied funds for a thorough excavation of the site in 1928. In a condensed version of his research at the s it e , Anderson (1936) makes reference to a t o ta l of 125 distinct burials encountered from the site. Anderson’s archaeological collection was purchased by the Ohio S tate A rchaeological and H isto rical Society in 1944. The Society also acquired the Anderson Village Site, including the museum and Anderson’s notes and maps. Later excavations at the site primarily have been of a salvage or restorative nature. Charles H Stout has performed salvage operations at Anderson Village in 1968, 1973, 1976, and 1978. Wright State University, Dayton, Ohio, also undertook salvage operations in 1976 and 1978. Patricia Essenpreis conducted excavations in 1976 "in an effort to synthesize available data into an overall description of the site" (Essenpreis 1982:18). Human remains from Anderson Village have been examined by Warren Moorehead, Georg Neumann, Louise Robbins, John Lallo, Paul Sciulli, Kim Schneider and this researcher. Moorehead made te n ta tiv e estim ates of age and sex fo r individuals which he excavated. It is believed that many of 2 5 the materials excavated by Moorehead’s explorations are located at the Peabody Museum and the National Museum. Neumann provided age and sex determinations for skeletons collected by CC Anderson in the late 1930s. Anderson (1936) incorporates these observations into his f ie ld notes. Neumann's main in te re s t was in evaluating biological relationships of prehistoric populations by assessing cranial metrics. Although Neumann was unable to elaborate upon his observations of the Anderson Village crania, his data were utilized by Louise Robbins, who continued the study of genetic relationships of Fort Ancient populations (Robbins and Neumann 1972). Robbins apparently made additional observations on the Anderson Village crania, as Neumann's original study included 50 individuals and Robbins presents data on 85 individuals in various publications. Lallo (1975) assessed the skeletal remains from the Anderson Village for his doctoral dissertation. He studied the remains in order to provide a detailed examination of the site's population. Lallo gave precise methodologies for establishing age, sex, stature, growth and development, paleodemography, and paleopathology. He used these sets of data to address both sociological behavior and ecological factors affecting individuals at Anderson Village. The "Anderson Collection" used by Lallo was much less complete than the original collection. Of the 125 known 26 burials (excavated by Anderson) from the site significantly fewer are present in the collection housed at the Ohio Historical Society. Lallo identified only 82 individuals, fo r which provenience was recorded fo r only 59. At the time of Lallo’s data collection the sample was assumed to represent a single occupation. Essenpreis (1982) points out that at least seven individuals of the 82 analyzed by Lallo are from a different component or site (the Taylor Site). She feels, too, that the integrity of the sample is further weakened by the lack of provenience data on 23 individuals. She notes that the paleodemographic data will be skewed because of the loss of data from Anderson’s original 125 burials. Essenpreis, however, does acknowledge the validity of Lallo’s other analyses as representative of an Anderson phase population in the Little Miami Valley in the vicinity of the Anderson Village and Taylor sites. This short review of Anderson Village demonstrates the amount of scholarly inquiry into this site. Also, it conveys some of the problems of many years of investigations. The current physical locations of many of the cultural and biological materials recovered in the early excavation by Moorehead a t Anderson V illage are unknown. The Peabody Museum at Harvard has many item s, yet i t was the common practice of early investigators to distribute artifacts to museums or to local collectors, or to trade 2 7 goods abroad. Consequently, many items cannot be evaluated in any systematic fashion today. It should be mentioned too, that during the late 1800s and early 1900s, most museums did not collect anything but intact crania. Such practices have thus lead to some serious sampling biases. As a re s u lt, the number of reported b u ria ls from early digs do not necessarily reflect the number of retrieved burials from sites. Inquiry of those human remains for the present study, pertaining to Anderson Village appear to be strictly from the remains excavated by Anderson in the 1930s. The "Anderson Collection" of human remains located at the Ohio Historical Society does include individuals from sites other than Anderson Village; however, for this study care was taken to include only individuals inventoried as being recovered from Anderson Village. Assessment of individuals in the "Anderson Collection" assigned to Anderson Village provided a sample size of 84. It is obvious these 84 individuals are significantly less than the 257 individuals (132 Moorehead and 125 Anderson) known from the s ite ; i t is believed however, that this sample will provide a representative portion of the whole by which to assess biological questions at Anderson Village. 28

Buffelat46EU3-1) The Buffalo site is located on a high terrace on the east bank of the Kanawha River, approximately fifteen miles upstream from i t s confluence with the Ohio River, in Putnam County, West Virginia. The site is thought to cover approximately 500,000 square feet, of which 67,000 square fe e t were excavated (Hanson 1975). The Buffalo s ite had at le a s t four components: one Archaic, one Woodland, and two Fort Ancient occupations represented by slightly overlapping v illa g e s (Hanson 1975). The Buffalo site was first mentioned in the literature by Thomas (1894:435). The archaeological presence of the Buffalo Site has been recognized since the 1930s when amateurs are known to have dug at the site (Griffin 1943; Mayer-Oakes 1955). Following these initial disturbances, some burials were excavated by the Kanawha Chapter of the West Virginia Archaeological Society (Metress 1971). The main excavation of the s ite was carried out by the Archaeological D ivision of the West V irginia Geological and Economic Survey in 1963-1965. Ed McMichael oversaw the excavation at Buffalo, by a crew from the West Virginia Department of Welfare's Work Training Program. The land was owned and made available for investigation by the Union Carbide Company. McMichael published b rie f d escrip tio n s of his excavations (1963; 1964). The final report was published by Hanson (1975). 29 McMichael (1963) speculates th a t the most recent occupation of the s ite was by the Shawnee. Olafson (1960) suggests the site could be the village visited by the trader Gabriel Arthur in 1674 during his captivity by the Tomahittan Indians. The villagers he visited identified themselves as the Monytons and as of yet, have not been identified among known Native American tribes (Metress 1971). The burials recovered from the Buffalo site belong to a single component (the Downstream Village) and are thought to represent an occupation of approximately 50 years which occurred some time between 1600 and 1650 A.D. (Metress 1971). Human remains recovered from Buffalo have been investigated by Louise Robbins, James Metress (1971), Lee Hanson J r . (1975), Paul S c iu lli, and th is author. Louise Robbins did incorporate cranial measures from Buffalo in her study of c ra n ia l types. However, much of her research was presented at professional meetings in oral form. Unfortunately most of these presentations did not fin d th e ir way in to p ublication and accounts of her work with Buffalo are not available. Metress (1971) used the Buffalo site human remains in his doctoral dissertation. He noted the range of intrasite skeletal and dental variation, and made comparisons with contemporary Iroquoian peoples in Western New York state and eastern Ontario. 30 Like Robbins and Neumann (1972), Metress too projects a physical "type" onto the Buffalo people. He describes the Buffalo populations as "gracile with medium sized skulls and medium to small faces, the cranial vault was oval in shape" (Metress 1971:120). In comparing his observations to those of Neumann (Neumann 1952, 1960 cited in Metress 1971), Metress places Buffalo into the Ilinid category. He concludes "the Buffalo site population is part of the Lenid- Illinid (Ilinid) microevolutionary line with very little contribution from the Iswanid-Muskogid line" (Metress 1971:122). Again, the typological approach to categorizing biological features is warned against as a means of understanding variation at the population level. Hanson (1975) notes the presence of a t le a s t 562 individuals from the site. The majority of the graves (71.5%) were recovered from the floor of houses, with the remaining graves found scattered about the village. No graves were recovered from the plaza. As was mentioned previously, archaeological materials which are used by numerous researchers risk minor losses of interpretable features because of physical deterioration through time. Old specimens also may be reinterpreted using new techniques and methodology providing new explanations. In a reassessment of the Buffalo collection by Paul Sciulli and th is researcher the sample count was increased from 565 (Metress 1971) and 562 (Hanson 1975) to 669 in d iv id u als. 31 Madisonville (33HA36)

Madisonville has been the site of organized archaeological activities for over a century. Charles Metz in the 1870s began his exploration of the Little Miami Valley and provided information on the prehistoric cemetery situated about one and one half miles southeast of the town of Madisonville, in Columbia township, Hamilton County, Ohio (Metz 1878). A b rie f note about M adisonville also appeared in JT S h o rt's, Norm AmerfcAtts of Anf{({Mitv( from 1879.

Metz began the excavation at the site in March of 1879. The L iterary and S c ie n tific Society of M adisonville, Ohio took on a supervisory role at the site in the spring of that year, maintaining Metz as the superintendent of excavations. Appropriations to defray excavation costs were provided by the Cincinnati Society of Natural History in exchange for a portion of excavated materials (Hooten and Willoughby 1920). In the early 1880s, Fredric Ward Putnam, the Director of Harvard University’s Peabody Museum of Archaeology and Ethnology, took interest in the Madisonville excavation. After a visit to the site, Putnam made arrangements with the Madisonville Literary and Scientific Society to fund p a rtia lly research a t the s ite . Between 1882 and 1911, the explorations at Madisonville were conducted under the auspices of the Peabody Museum by the following principal in v estig a to rs: CL Metz, FW Putnam, JR Swanton, RE Merwin, and BW Merwin. 3 2 Ms. Phoebe Ferris, the late owner of the land upon which Madisonville is situated, granted the archaeological exploration of the Peabody Museum to continue after her death. In 1897, the Museum learned that Ms. Ferris had bequeathed about twenty-five acres of land, upon which most of the Madisonville cemetery was situated, to the Museum. The extensive collections of cultural and biological remains, notes, maps, and photographs obtained during the Museum's involvement at the s ite cu rren tly reside a t the Peabody Museum in Cambridge. The majority of the human remains recovered from the cemetery near Madisonville are thought to be housed at the Peabody Museum. However, M adisonville s k e le ta l m aterials have been identified at other museums and research institutions, such as the American Museum of Natural History, the Cincinnati Art Museum, and the Cincinnati Museum of Natural History. No radiocarbon dates are available for dating the materials at Madisonville. European trade goods (glass beads and a few bits of iron and brass) found with some of the burials identify the recent temporal boundaries of the s ite . It is suggested the cemetery maintained a long continual usage through time (Hooten and Willoughby 1920). This assumption is supported by the number of individuals exhumed from the s ite and the amount of disturbances 33 recorded for late interments at the site. Hooten and Willoughby (1920:26) "... accept one hundred years as the approximate length of time during which the Madisonville village site was inhabited". The biological remains from Madisonville have had limited exposure in scientific inquiry in the past (Low 1880; Langdon 1881; Hooten and Willoughby 1920; Robbins and Neumann 1972). In 1880, Low, in a three part contribution to

E xploration» Vvj ih e Literary anb Scientific Society o f

Mabi»onvi11c, Oltio, supplied a chronological record of the

Society’s involvement in the exploration of Madisonville between the years 1878 and 1880. Mixed among the documentation of cultural materials is mention of the recovery of skeletal remains. Observations were made pertaining to the age and sex of individuals recovered, by (Dr.) Metz, who held a medical degree. Langdon’s (1881) paper in the above mentioned series of the Literary and Scientific Society of Madisonville, Ohio provides measurements of a lim ited number of crania and pathclogical assessment of individuals from Madisonville. Measures were taken by Metz and Langdon, with assistan ce from Low. On 83 adult crania, Langdon supplies the following types of data: cranial capacity (determined by dried peas and given in cubic centimeters), length, breadth, height. 34 index of breadth, index of height, index of frontal, zygomatic diameter, height of orbit, width of orbit, and sex. An additional 58 crania were included for other observations regarding the cranium (general contour, size, special characteristics of the various bones and cavities, sutural peculiarities, including wormian bones, and pathological features). Humeri of 34 individuals were examined for the presence of an olecranon fossa. Tibiae were evaluated for plactycneism and cnemeolordosis. At the time Langdon wrote his paper in 1881, a to ta l of 662 skeletons had been exhumed. A ll 662 indiv id u als were carefully examined for marks of disease or injury. Hooten and Willoughby (1920) provide information on M adisonville in a monograph e n title d ItibiAti vniA 5e Site Atib

Cemetenf ne^r MAbisoHvine. Oltio. In th is monograph, data are furnished on the b u ria ls from the excavations of Metz, Swanton, Merwin (RE), Merwin (BW), and Putnam. It also addressed depth of interments, forms of burial (horizontal or extended, contracted, and sitting posture), collective and disturbed burials, burials in cache pits, anomalous burials, grouping of burials, orientation of burials (direction of the head), objects associated with burials, and burials of special interest. After an extensive examination of the field notes of the principal excavators at Madisonville, a summary of the burials recovered from the site was provided (Hooten and 3 5 Willoughby 1920). Based on the fie ld notes, 1236 b u ria ls were exhumed from the cemetery between 1879 to 1911 (see Table 2).

TABLE 2. Number of burials excavated by early explorers at Madisonville.

Excavator Field Season # of Burials CL Metz 1879 360 CL Metz 1880 239 CL Metz 1881 58 FW Putnam 1882 6 JR Swanton 1897 230 RE Merwin 1907 85 RE Merwin 1908 176 BW Merwin 1911 82 Total 1236

Hooten and Willoughby noted th a t to the 1236 b u ria ls reported by the different excavators more burials should be added to account for burials washed away prior to the discovery of the site. In addition, burials unearthed by Metz’s intermittent excavations subsequent to August of 1882, at which time data entry on burials ended in his fie ld n o te s should be added. They conclude th a t " it is possible th a t the t o ta l number of b u ria ls made in the cemetery was not le ss than 1350" (Hooten and Willoughby 1920:20). 36 Hooten (from Hooten and Willoughby 1920) looked at the Peabody’s collection at Madisonville, comprising 86 crania and 112 postcranial remains. Hooten made all measurements except c ra n ia l capacity, which was assessed by George Schwab. Hooten noted a s lig h t degree of o c c ip ita l deformation in the Madisonville series, thought to be the result of cradle-boarding. Three fourths of the undeformed crania were identified as brachycephalic, with the remainder assessed as mesocephalic. Cranial observations included: deformation; length; breadth; height; cranial index; height- length index; menton-breadth index; alveon-nasion index; diameter bizygomatic maximum; facial index, total; facial index, upper; basion-alveon; basion-nasion; gnathic index; diameter frontal minimum; diameter bigonial; angle of lower jaw, mean; height of symphysis; orbit-height, right, left; orbit-breadth, right, left; orbital mean, nose height, nose breadth maximum; nasal index; palate, external length; palate, external breadth, maximum; palatal index; circumference, maximum; arc, nasion-opisthion; capacity (Hrdliôka’s method); and thickness of left parietal above tempoparietal suture. Hooten estimated male stature of the Madisonville population a t 167 cm and female sta tu re a t 155 cm from femur length. These estimates must be questioned as significant over estimates because they were derived from height standards based on R eliefs French cadaver sample and 3 7 regression formulae which apply to populations of much different shape than Native Americans. Since the time of Hooten and Willoughby’s monograph, the importance of using standard derived from a similar group of prehistoric Native Americans and using new regression formulae for stature estimates has been established (Sciulli et al. 1990). The Madisonville series when compared to the Tennessee Stone Grave group appeared to be gracile in most respects. Hooten's summary statement about pathologies was general, with a few case studies exemplifying the existence of specific disorders. Overall, he noted arthritis deformans, periostitis and osteoperiostitis. He noted the possibility of a tuberculous condition in one spine. Fractures and injuries were described to be rare in postcranial material, but crania appear to have numerous pathological and traumatic features. A total of 430 individuals from Madisonville were assessed for the current analyses. This sample size represents the t o t a l number of individuals recorded in a five week data collection trip to the Peabody Museum. Burials were selected by accession numbers. The smaller (or earliest) numbers were evaluated first. The majority of the burials evaluated came from the Metz Expeditions of the late 1800s. A reinventory of the Peabody collection is in progress. 38 SunWatch (33MY57)

Artifacts have been collected from the SunWatch site by local collectors for more than a century. Initially the lo catio n of the s ite was referred to as the Vance Farm S ite . In the early 1940s the land was acquired by the City of Dayton for the development of a sewage treatment facility (Heilman e t a l. 1990). The s i t e soon became known as the Incinerator Site with reference to the incinerator located to the north of the site. Archaeological attention developed at SunWatch in the 1960s when proposed sludge treatment pond construction jeopardized the site. John Allman and Charles Smith began excavation at the site which resulted in the discovery of the first known Anderson Focus house (Heilman et al. 1990). The f i r s t system atic survey of SunWatch began in 1969, with salvage excavations of the site to follow in 1971 by Jay Heilman under the auspices of the Dayton Museum of Natural History. Excavations at the site provided sufficient data to support designation of the village as an archaeological district on the National Register of Historic Places in 1975. In 1981, the City of Dayton turned to site over to the Dayton Museum of Natural History for construction of a museum and interpretive park facility. Seven radiocarbon dates from SunWatch establish the occupation of the site near the end of the twelfth century A.D. (Heilman and Hoefer 1980). SunWatch is located on the 39 floodplain on the west bank of the Great Miami River, just two miles south of downtown Dayton, Montgomery County, Ohio. The s ite is approximately 420 fe e t in diam eter, and was surrounded by a circular stockade. The site is known to represent an elaborate village site with a central plaza bordered f i r s t by b u ria ls and then by houses and storage/trash pits. More than 60% of the site has been systematically excavated by the Dayton Museum of Natural History (Heilman et al. 1990). More than 30% of the remainder of the has been "banked" for future research. Approximately 7% of the east side of the site has been destroyed through various construction activities over the years. Inv estig atio n s of the sk e le ta l m aterial from SunWatch has had limited exposure. The lack of published reports on the human remains at SunWatch has made acquiring copies of the works difficult. Pat Tench currently is evaluating biological data for a biodistance analysis. However, no results are available from Tench's work for discussion. Conard (1985) evaluated stable carbon isotopes in human remains from SunWatch for his Master’s Thesis. He found that 50% of the SunWatch villager’s diet could be attributed to the consumption of maize. Data from genetically related characteristics have been employed to test for patterns of post nuptial matrilocal residence fo r the In cin erato r s ite (renamed to SunWatch) 40 (Essenpreis 1978). Stanley Knick presented a paper and Steve Paquette wrote an unpublished manuscript on the paleopathologies found a t SunWatch. Louise Robbins also has presented data a t meetings on SunWatch. A t o ta l of 167 in d iv id u als from SunWatch were evaluated by Paul Sciulli and the author. This sample represents all known materials excavated from both the Smith and Heilman Excavations.

Sandusky Tradition

The northwestern portion of Ohio has been occupied by humans for at least 14,00 years. Beginning with the early Woodland period (ca 700 B.C.) data on settlem ents become available. For the next two millennia, two major regional cultural traditions are identified in northwestern Ohio: in the Maumee-Portage-Sandusky River area in the west is the Western Basin tradition (Stothers 1978; Pratt 1981), while in the Huron-Vermilion River area in the east is the Firelands tradition (Bowen 1992). Between A.D. 1300 and A.D. 1650 only a single regional cultural tradition, is identified in northwestern Ohio, the Sandusky tradition (Bowen 1980; Stothers and Pratt 1980). The origins of the Sandusky tradition have been the point of debate since 1980 when i t was f i r s t recognized. Over the past two decades the cultural placements within the Sandusky 41 Tradition have been continuously revised. Figure 3 summarizes proposed chronologies of the Sandusky Tradition. The location of the Sandusky Tradition is in the Huron River drainage system of north-central Ohio and the vicinity of Sandusky Bay. Sandusky populations resemble other Upper Mississippian populations in exhibition of "lithics, ceramics, bone-tools, biocultural, and settlement- subsistence configurations" (Stothers et al. 1984). According to Stothers and associates (1984) the Eiden phase populations utilized a combination hunting and gathering and maize horticulture subsistence system, with large year around village sites and peripheral seasonal camps. This pattern of subsistence is thought to have transformed into a settlement-subsistence system based almost exclusively on horticulture by the Wolf phase. Although the Wolf phase peoples probably also utilized seasonal fishing and gathering to some extent (Stothers and Bechtel 1987). This phase has been summarized as a "period of intense resource exploitation, geographic expansion, and demographic increase" (Stothers and Bechtel 1987:143). Bowen (1992:121) points out that around A.D. 1200-1300 "the long standing regional tradition with a dispersed settlement and a diffuse economy came to an end". He feels the change in the climate (cooler and wetter) drew the "nucleated, focused deer hunter, strongly corn horticultural Wolf phase people" (122) to the west out northwestern Ohio. CArottitfitgy Filling (1965) Sioihers (pre -1986) Stotliers (post-1986) Bowen (1992) Younge Western Basin Sandusky Western Basin Sandusky Western Basin Brelands Sandusky A O . 1600 Indian H«s IndanHib IndanHlla FodMalga FbrtMalga FoitMaIgs A .D. 1400 Wol Wol Wol Won Wol A.D. 1200 SpilngMta Springwab Eldan Sptkigmb Eldan Spitngmb

A.D. 1000 Younga Youiga Youipa Younga

A.D. 8 0 0 RhbraauVaaa RMaraauVaaa RbhrsauVaM QraanCreali Walteu

RMataauVaaa

A.D. 6 0 0

QiaanCiMlt

A O 4 0 0 Each tVntemBnIn Each MiddaWoodan)

A.D. 2 0 0 Waslam Basin Vflngjlon Each Wdjla Woodard

A D . 1

Wealarn Basin Lalmbach lalnbach

Eat(r Woodland 2 0 0 D .C . Providence Lelmbach

FIGURE 3. Chronologies for the Sandusky Tradition (after Bowen 1992) 43 The fisheries in the west supplied the attraction. Bowen believes the indigenous Springwells phase people of the Western Basin were "displaced and/or assimilated into the Wolf phase population (121)". By A.D. 1500, populations in northwestern Ohio are concentrated near productive fisheries due to the u n p red ic ta b ility of maize farming. Then by A.D. 1600 maize horticulture has a greater impact on subsistence as a "ridged-field" technique was employed for maize production. The region in known to have been near void of aboriginal people by A.D. 1650.

Indian Hills (33W04)

The Indian Hills site is located on a high plateau overlooking the juncture of the Grassy Creek and the Maumee River near Rossford in Wood County, Ohio (Stothers 1981). It is the type site for the Indian Hills phase (1500-1600 A.D.). This protohistoric site encompassed ten acres representing a permanent, fortified village surrounded by double and t r ip le p alisades (Stothers and Graves 1983). The village area had circular habitation structures around an occupied plaza-like area within the center of the village (Stothers 1981). Stothers and colleagues (1984) have suggested the inhabitants of the Indian Hills site would 44 have depended on an agricultural base supplemented with available aquatic resources. European trade goods were recovered from the site. Indian H ills has been radiocarbon dated a t 1610 ± 100 to 1760 ± 120 (S tothers and Abel 1989:129). S tothers and Abel (1989) use early historic accounts of Father LeJeune from 1640 (in Stothers and Abel 1989 from JR 1896-1901 18:227- 235) and the diary of Sieur de La S alle (in S tothers and Abel 1989 from Margry 1878-1886:243-245) to help document the Native population which once occupied the site. From these descriptions, they identify the site as a village occupied by the ethnic group known as the Totontaratonhrono/ A ssistaeronon. A ssistaeronon are id e n tifie d by Garrad and Heidenreich (1978) to be Algonquian speakers from the Michigan Lower Peninsula. The location of the Indian Hills site has been known to many lo c a l resid en ts of northwestern Ohio and Southeastern Michigan (Tucker 1980). In 1963, a professional interest in the site was expressed when an ossuary was discovered. Unfortunately, a controlled excavation was not possible at the site until 1967 (under the direction of Earl J Prahl), by which time the ossuary discovered in 1963 had been completely looted. Prahl continued excavations at Indian Hills through 1968. Stothers (1981), mentions four ossuaries (each containing 25 to 35 individuals) from Indian Hills. Three 45 Of the ossuaries were outside the palisade to the east, while the fourth was inside the palisade just south of the central village area. Indian Hills biological remains have been investigated by Paul S c iu lli, Kim Schneider, and th is author. Schneider (1984) included Indian Hills in her above mentioned doctoral dissertation which looked at trace elements and caries frequencies in prehistoric teeth from Ohio. Giesen and Sciulli (1989) used Indian Hills as a comparative sample in their assessment of cranial variation and b io lo g ical a f f in itie s of the Pearson Complex. The following section on the Pearson Complex contains the details of this investigation. The Indian Hills material evaluated in this study cannot be assigned to a specific ossuary. As of yet, the ossuary material has not undergone a thorough assessment in which a definitive sample size has been established. The material used in this investigation was excavated by Stothers and it is felt to be a representative sample of the inhabitants of Indian Hills. Since the elements are fragmentary and age or sex is unable to be determined in many cases, the Indian Hills sample cannot be used in all statistical procedures for this analysis. 46 Pearson (33SA9)

The Pearson Complex is located on a ridge, adjacent to Green Creek northeast of Fremont, in Sandusky county in north-central Ohio. Three partially overlapping habitation sites with cemeteries are represented in the complex. The Pearson Complex was f i r s t excavated in the la te 1960s to early 1970s by amateur archaeologist William Smith of St. Joseph Central High School, in Fremont, Ohio. In 1978, the first controlled excavations began at the site by Jonathan Bowen. Bowen continued work at the site under the auspices of Ohio State University and the Ohio Historical Society until 1985. In 1985, all cultural material and research data associated with the Pearson Complex were transferred to the Western Lake Erie Archaeological Research Program at the university of Toledo. As noted above, three occupation sites belonging to the Pearson Complex are known; these s ite s have been named Pearson North (Eiden phase), Pearson South (Wolf phase), and Pearson Middle (Fort Meigs phase)(S tothers and Abel 1989). Numerous human skeletal remains have been found at the site. Three separate cemeteries were identified for the complex, most probably representing the three different occupations at the site. The cemetery of interest to this research is the Pearson Middle Cemetery. The Pearson Middle Cemetery represents an Eiden phase cemetery, thus was presumably used 4 7 by the inhabitants of Pearson North. This cemetery is represented by a total of 546 excavated individuals. In the late 1980s, Stothers and Abel (1989) stated that all radiocarbon dates obtained for the Pearson Complex are thought to be erroneous. The ’^0 series obtained for the complex are consistently more recent than estimated by ceramic sériation. The factors involved in producing these unacceptable dates are not well understood, but a Chemical Waste Management facility which is not far from the site and the contaminants from intensive chemical use in farming could very well contribute to the problem. Sériation of the Pearson Complex ceramic assemblage with other acceptable radiocarbon dated Sandusky Tradition ceramic assemblages has produced some acceptable dates for temporal placement of the sites. Using this methodology Stothers and Abel (1989) place Pearson Middle a t about A.D. 1250. Of the Sandusky Tradition burial populations, the Middle cemetery has been exposed to the most scientific inquiry. Stable carbon "C/^^C calibrations for the Middle Cemetery indicate an intensive consumption maize, with possible minor contributions from chenopodium and amaranth (S tothers and Abel 1989). Schneider (1984) included Pearson in her trace element analysis of prehistoric teeth from Ohio. See the above section on Fort Ancient for a review of her work. The study of Sciulli and Schneider (1986) also appears in the Fort 48 Ancient section, they used Pearson in their evaluation of caries frequencies among prehistoric Ohio horticulturalists. Giesen and Sciulli (1989) assessed 43 crania from the Pearson Middle cemetery in order to understand cranial shape and size differences at the site, in addition to understanding how crania at Pearson would compare with the Fort Ancient Tradition, Anderson Village sample. Comparisons of the two s ite s revealed sig n ific a n t shape and size differences between the sites. They also noted that in addition to differing from each other, the Pearson sample and Anderson Village sample differ from earlier (Late Archaic, ca 100 B.C., to Middle Woodland ca A.D. 0) Ohio populations. Late Archaic and Hopewell samples were shown to be genetypically homogeneous with d ifferen ces re su ltin g only with the inclusion of Late Prehistoric samples in variation comparisons. Giesen and Sciulli (1991) suggest that evolutionary changes in the shape of the crania took place a fte r the Middle Woodland period in Ohio. The differences in cranial variation between the Pearson and Anderson Village samples were thought to be the result of mutual isolation due to geographic distances. When other Sandusky tradition samples were included (Indian Hills and a Late Archaic sample from Williams Cemetery) the observations of b io lo g ical iso la tio n due to geography seemed to be apparent. In conclusion, they suggested that because of small sample 49 size more populations should be assessed before any conclusive results can be submitted.

PgLecsen (33.019) The Petersen site is located on a clay ridge overlooking the south bank of the Portage River in Bay Township, Ottawa County, Ohio just west of the Pearson Complex. Petersen is id e n tifie d as a multi-component s it e (Stothers and Abel 1991), two components of which have been assigned to the Sandusky Tradition (Stothers and Graves 1983; Stothers and Abel 1989; 1990). The earliest of these components has been radiocarbon dated to the 14^" century A.D. (Stothers and Abel 1989). The other component has been radiocarbon dated between A.D. 1450 and 1550 (S tothers 1991). Much of the site has been destroyed by erosion and modern development, with a small portion of the site being salvaged prior to the land being sold and developed. In three field seasons, extensive excavations were carried on at Petersen by Western Basin Archaeological Research Program at the University of Toledo (Abel n.d.). The skeletal material from Petersen is fragmentary. The lack of identifiable burial plots at the site requires the remains to be assessed as an ossuary. Due to the fragmentary nature of the human remains from Petersen a d e fin itiv e number of in d iv id u als has not been sp ecified . 50 Like the Indian Hills materials, Petersen cannot be incorporated into all aspects of this investigation.

g Mtnmary The skeletal samples to be used in this investigation are from the Late Prehistoric period, the Fort Ancient Tradition in the middle Ohio Valley and the Sandusky Tradition in northwestern Ohio. Table 3 summarized the temporal placement of the sites used in this research and Table 4 provides the sample sizes of these sites. After a review of previous research on the Sandusky and Fort Ancient traditions skeletal collections, it appears that biological data in the past have been used to address a number of issues relevant to this dissertation. Fort Ancient Tradition skeletal samples are best known for their use in a typological approach to appraising biological affinities. This "type" method, however, was shown to lack validity as a means of discriminating and interpreting population variation. Thus, the demand for a population approach to understanding variation and biological affinity persists. Cranial shape and size analyses have been performed on a few of the samples from both traditions, however the investigators of these studies suggest more populations should be assessed before conclusive results could be put fo rth . 51 Dietary evaluations of both the Fort Ancient and Sandusky traditions have been done primarily on a site to site bases through ethnobotanical, biochemical, and dental pathology analyses. A comparative investigation of dietary stressors or any other biocultural stressors, as of yet, has not been completed for either of these traditions. In sum, it appears the samples available for inquiry adequately allow the problems set forth in the previous chapter to be addressed. The large sample sizes and the inclusion of two contemporary cultural traditions makes this comparative study one of the largest of its types. TABLE 3. Temporal placement of study sites.

FORT ANCIENT SANDUSKY A.D. SUNWATCH ANDERSON BUFFALO MADISONVILLE PEARSON PETERSEN INDIAN HILLS 1700

♦ 1600 ♦

♦ 1500 ♦

1400

1300

♦ ♦ 1200 ♦

1100

Cl ro TABLE 4. Summary of site sample size.

Ô 9 UNKNOWN SUBADULT TOTAL FORT ANCIENT ANDERSON 19 15 18 32 84 BUFFALO 102 130 189 248 669 MADISONVILLE 93 110 127 100 430 SUNWATCH 34 28 1 104 167 SANDUSKY

INDIAN HILLS - - - - ? PEARSON 108 118 96 224 546

PETERSEN - -- - ?

s CHAPTER III

OVERVIEW OF RELEVANT RESEARCH

This section provides a review of pertinent research concerning biological distance and biocultural stress indicators relevant to this study. A brief history of biological distance is provided, followed by a discussion of metric and nonmetric data collection techniques used in biodistance analyses. Following a review of nutritional stress indicators, the stress indicators (abscesses, attrition, caries, and tooth loss) employed in this evaluation are addressed. Finally, stature is examined (as both a distance measure and a s tr e s s in d icato r) and long bone growth is appraised as a stress response.

Biological Distance

Biological distance or biodistance is the measurement of the morphological affinities between two or more populations. It is based on the assumption that physical features of the skeleton are reflections of the underlying genetic structure of the individual. Biological distance analyses are commonly used for paleopopulations where true

54 5 5 genetic distances are usually unobtainable (Buikstra et al. 1990). In attempting to estimate a true genetic distance between populations there are at least four conditions that must be considered: 1) in the archaeological record, populations are often fragmentary and incomplete; 2) significant changes in gene pools of small populations may occur in a short amount of time; 3) traits must be selected for analysis which have a highly genetic component rather than a highly environmental component; and 4) cultural separation as well as geographic isolation may affect the pattern of between group biological distances by influencing the pattern of gene flow. Awareness of these limitations allows biological distance investigations to continue to develop and contribute to modern understanding of biological differences in the prehistoric record.

Karl Pearson’s (1926) publication of the C oefficient o f

R acial Likeneeo was the first attempt to calculate the rate of biological separation on statistical principles by use of metric measures. Pearson’s formula has been criticized as being weak on two accounts (Sjavoid 1977). First, it does not adequately consider the problem of correlation between v a riâ te s; and secondly, i t is not a m ea su re of divergence or 56 biological distance between populations, but rather it is a te st of divergence.

Mahalanobis f i r s t advanced his s t a t i s t i c in 1925 and later expounded on it (1930; 1936). It was Mahalanobis’ publication on the D* coefficient (Mahalanobis 1936) which firmly attached the term "distance" in the statistical literature. Initially, the complexity of computations made Mahalanobis’ analysis scarce in the literature, however with the advancements in computer technology such computations now have become routine. Currently, the main problem of distance studies involves defining and interpreting distance coefficients (Molto 1963). Since there are numerous methods of computing the distance between two points, a problem exists with the definition of "real" distance. This suggests that biological distance is not an objectively defined quantity, but ra th e r, a value dependent on the method used (Constandse-Westermann 1972). In the area of data collection, metric and nonmetric data are commonly used in biological distance analyses. Both types of data are necessary to insure a more accurate comparison since both theoretically are independent of each other; reflecting distinct patterns of inheritance. Metric data may be affected by biocultural factors (e.g., artificial cranial deformation and nutrition). Discrete 5 7 traits overcome many of the limitations of other genetic markers because they can be scored on incomplete elements and are easily recorded. In addition, many epigenetic traits appear to be unaffected by the age or sex of the individual, but this assumption must be tested in each population. The potential of skeletal and dental analyses for resolving archaeological problems involving biological hypothesis cannot be fully appreciated until more is known about the genetics of bone and tooth development. In the meantime, there are several approaches which do address biological distances in prehistory. Comparing prehistoric and historic groups is one approach (Molto 1983; Turner 1976; Robbins and Neumann 1972). Recognizing interbreeding between groups is yet another (S c iu lli and Schneider 1985; Buikstra 1984; Ossenberg 1977). Still other avenues of investigation include: inference of matrilocal and p a trilo c a l residence p a tte rn s (Konigsberg 1988; Lane and Sublett 1972), and questions of biological variation in terms of isolation by geographic and temporal distances (Konigsberg 1990b). The validity of these approaches is witness by the symposium organized by B uikstra and Konigsberg at the 1986 annual meeting of the American Association of Physical Anthropologists in Albuquerque, New Mexico, entitled Skelcul 58 BiologkÀl DfftAMce: A Sywposlww. The papers derived from th a t symposium la te r appeared in the 82"“ volume of the American Journal of Physical Anthropology (Buikstra et al. 1990; Connor 1990; Key and Jantz 1990; Konigsberg 1990a; Rothhammer and S ilva 1990; and S c iu lli 1990).

Metric Data

Osteometry is the measurement of the skeleton and its components. Standardized measurements of various dimensions of the skeleton are well established. Useful reviews of osteometric measures are found in Stewart (1947), Comas (1960), Montague (1960), Olivier (1969), Krogman and i§can (1986), and Bass (1987). Conventionally, craniometries (measurement of the skull) appear more often in the literature than do post- cranial measures (Howells 1973; 1989; Brothwell 1981). The explanations Brothwell (1981:77) submits are: 1) crania excite more interest due to their close association to the brain; 2) differences in cranium shape tend to be more obvious than those in other parts of the body; 3) the configuration of the cranium’s form enables definite points from which measurements can be obtained; and 4) retention of the crania is more common in museum collections than are other elements of the skeleton. Nevertheless, postcranial 5 9 metrics are as valuable as cranial metrics since both are know to be heritable to some degree. When postcranial metric data are collected they are routinely comprised of long bone measures. Several different approaches view metric data as essential (Jantz 1970; Carpenter 1976). Metric data can be used as raw measures of size and robusticity (i.e., diameter of head of femur or humerus). A number of measurements can be used in discriminant function analysis allowing estimations of sex, age, cultural status, or ethnic affiliation. Shape determinations are established by using various indices or ratios (i.e ., cephalic index, ischiopubic index, femur-shaft index, tibia shaft-index). Multivariate analyses also can aid in identifying dimensions that contribute to or are correlated with shape (Howells 1973). Multivariate analyses also have provided insights about which measures are useful. Discriminant functions help select measurements that distinguish between populations or sexes. Metric data also are used to determine distance coefficients, thus supplying information on biological a ffin ity . Osteometric data have various applications in anthropology, both for forensic anthropologists and bioarchaeologists (Howells 1973; 1989; Krogman 1962; S teele and Bramblett 1988). As was noted above, s k e le ta l measures 60 are used by investigators to establish estimates of age, sex, ethnic affiliation, activity level or musculature, and stature for extant and extinct populations. This basis of inquiry is often necessary in forensic anthropology where individuals are represented by only skeletal remains. The metric data can be a good source of evidence used to make a positive identification of the deceased.

Nonmetric Data

The use of nonmetric epigenetic features (i.e., discrete, discrete, discontinuous morphological traits, quasi-continuous, or epigenetic variants) as biological distance markers can be traced back to the research of Laughlin and Jorgensen (1956). While others preceded them in description and experimental studies, it was these workers who first convincingly demonstrated the applicability of nonmetric traits for use as measures of biological or genetic distance in paleopopulations. Hauser and De Stefano (1989), Saunders (1989), and El- N ajjar and McWilliams (1978) provide reviews of work on nonmetric traits in human osteology. Over 200 variants have been described for the skull (Ossenberg 1976), as well as for the postcranial skeleton (Saunders 1978; Winder 1981). Rosing (1984) provides a concise, critical review of the use 6 1 of nonmetric skeletal traits, concluding that standards for their determination are poor or lacking. It is noted that nonmetric traits are polygenic and have underlying continuity which is both genetic and environmental in origin (Dempster and Lerner 1950; Hauser and De Stefano 1989; van Vark and Schaafsma 1992). Typically, researchers endorse the use of nonmetric traits because these features are not markedly influenced by environmental factors or individual characters (e.g. sex, age, nutritional status). Hauser and De Stefano (1989:5) note the difficulty of "elucidation of the genetic basis of each (discrete) characters ...". The evidence for genetic identification is indirect and is supported by three types of inquiry: 1) trait frequencies in human populations (e.g., different "genetic" populations produce different trait frequencies); 2) data from animal experiments; and 3) trait correlation with inherited syndromes (Hauser and De Stefano 1989). Another reason for using nonmetric traits is that they are easily scored and are usable on fragmentary material(s). According to Berry and Berry (1967), simple trait frequencies in skeletal samples could act as "genetic markers" to assess biological variability in prehistoric populations. 62 Through the years, the sentiments for the usefulness of nonmetric traits have been divided into three factions (Saunders 1989; van Vark and Schaafsma 1992). One factio n suggests that nonmetric traits do not satisfactorily distinguish skeletal populations when compared to metric traits. Another faction states that nonmetric traits are better discriminators than are metric. The other faction supports the use of nonmetric traits with the use of metric data. This debate has generated concern about nonmetric studies and their relation to methodological problems and theoretical considerations (Saunders 1989; van Vark and Schaafsma 1992). The methodological problems which most often emerge in the literature are the assumptions made pertaining to side independence of bilateral traits, the absence of age and sex influence on trait incidence, and the lack of significant correlations between traits. These assumptions have been tested (Korey 1970; Corruccini 1974; Suchey 1975; Berry 1975), and from a statistical perspective the assumptions have not been supported. As a result, researchers have developed two models for inquiry (Molto 1983): the inclusive model, which pools the data with respect to side, age, and sex; and the re d u c tio n ist, model which supports the elimination of traits that are influenced by these factors. 63 In practice, however, most research designs are a compromise between the two approaches.

Biocultural Stress Indicators

Stress can broadly be defined as "... the friction between an individual and his social, physical, nutritional, and disease environment". Stressors are then assumed to invoke "a stereotypic, nonspecific physiological response for adaptive activities in the body" (Simpson et al. 1990:72-73). It is through extrapolations from material remains and from data on contemporary or historic human populations sharing similar geographical, cultural, and technological characteristics, that the patterns of a prehistoric population's stress emerge. Many times, nutrition has been identified as being a important contributor to stress in paleopopulations. Extrapolations from prehistoric diet patterns, compared with established nutrient requirements or recommendations, can be used to generate hypotheses regarding potential nutrient imbalances which may result in nutritional disorders. These hypotheses can then be tested by examination of skeletal remains of archaeological populations for signs of deficient or excessive nutrient intake, and/or other indicators of dietary stress. 64 The interdisciplinary nature of paleonutritional research is well illustrated by the numerous techniques utilized in dietary reconstructions (i.e., skeletal and dental analysis, paleoethnobotany, bone chemistry, zooarchaeology, cultural analysis through archaeological recovery). Dental health is known to be influenced by several aspects of diet, both during childhood development and throughout adult life. This study will utilize dental abscesses, attrition, caries, and tooth loss as biocultural markers of stress.

Abscesses

Alveolar abscessing is a pathological condition distinguished by periapical destruction of alveolar bone caused by various infectious conditions. Brothwell (1963) attributes abscessing as one of the leading causes of antemortem tooth loss in a population. An abscess may result from a number of circumstances, including caries, occlusal attrition, traumatic injury, and periodontal disease (Patterson 1984). Abscesses usually arise as a result of infection following carious involvement of the tooth and pulp infection (Shafer et al. 1983). Typically, the abscess originates in an area of chronic infection (the periapical granuloma) or may develop directly as an acute apical 65 periodontitis following an acute pulpitis (Shafer et al. 1983). Patterson (1984) discusses four types of lesions identified with alveolar abscess. They include apical periodontitis, apical abscess, apical granuloma, and apical periodontal (radicular) cyst. All four lesions are characteristic of chronic inflammatory reaction in the alveolus. These lesions only can be distinguished from each other with certainty through histological examination, thus they cannot be absolutely identified in skeletal materials. Traditionally, alveolar abscessing has been investigated in studies of dental pathology (Hooten and Willoughby 1920; Fisher et al. 1931; Snow 1948; Goldstein 1948). However, more recent stu d ies have provided more complete data on frequency, incidence, and distribution of alveolar abscesses in the dentition (Patterson 1984; Clarke and Hirsch 1991; Hartnady and Rose 1991; Kelley e t a l. 1991).

Attrition

Dental attrition, the wearing away of the enamel and dentin, is now accepted as a n atural b io lo g ical phenomenon. Attrition begins as a small circular or oval area of wear on the surface of a tooth, usually the cusp tip. As the 6 6 process progresses the facet grows larger, with dentin eventually becoming exposed as the enamel is worn away. In cases of severe wear the pulp of the tooth becomes exposed, which may result in periodontal disease or tooth loss. Attrition can best be explained as the result of a complex set of interactions among teeth, their supporting structures, and the functioning of the chewing apparatus. The types and amount of a t t r i t i o n in a population may be influenced by any or all of the following factors: eruption pattern of teeth; tooth morphology; hardness of enamel and dentin; enamel thickness; dental occlusion; dental pathologies (including caries); bone inflammation; antemortem tooth loss; masticatory patterns; dietary and non-dietary functions of the teeth; and chronological age (Murphy 1959; Lavelle 1970; Molnar 1971a; 1971b; 1972; Patterson 1984). The amount and rate of dental attrition may "directly affect the prevalence and severity of dental pathologies" (Powell 1985:309). Attrition, when slow and gradual may be beneficial, since it removes potential caries loci by smoothing fissures and pits on the occlusal surface. Interproximal surfaces may become grooved because of wear associated with mastication allowing the entrapment of food particles thus promoting tooth decay. 6 7 Dental attrition has been studied intensively in several ways. Molnar (1971b; 1972) provides a literature review of the various studies using dental attrition among anthropologists. Studies of attrition in the past have been concerned with both degree of wear and rate of wear. Broca proposed a system for recording attrition as early as 1879. Hrdliôka also developed a system which was applied by Goldstein (1932). While studying skeletal remains of several Native American groups, Leigh (1925) devised yet another classificatory system. Other such schemes for quantifying attrition followed (e.g., Klatsky 1939; Murphy 1959; Lysell 1958; Brothwell 1981; Molnar 1971b; Scott 1979; Lovejoy 1985). Diet, food preparation technique, and dental wear have been observed to be correlated by many researcher for both historic and prehistoric populations. The use of stone grinders fo r food preparation was a ttrib u te d to heavy amount of attrition in Mesolithic and Neolithic populations from Jarmo (Dahlberg 1960), Kish (Carbonell 1966), Nubia (Greene e t a l. 1967) and Isra e l (Smith 1972). Diachronic stu d ie s of archaeological samples from Egypt (Buffer 1920), Nubia (Armelagos and Rose 1972), Greece (Angel 1944) and Europe (Lavelle 1970) have shown th a t lig h te r amounts of a t t r i t i o n has been associated with improved food processing techniques. Using prehistoric Native American dentitions 68 has revealed similar observations concerning the effects of differing subsistence technologies on attrition (Leigh 1925; G oldstein 1932; Molnar 1971b; S cott 1979; Powell 1985).

Dental Caries

Dental caries are a microbial disease of the calcified tissue of the teeth, characterized by demineralization of the inorganic portion and destruction of the organic substance of the tooth (Shafer et al, 1983:406). As a disease it is both infectious and transmissible (Pindborg 1970:256). Dental caries manifest itself in a variety of manners: pit and fissure caries, smooth surface caries, root c a rie s, and deep d en tin al c a rie s. Advancement of the disease may lead to pulp exposure which may cause necrosis of the pulp and the formation of a periapical abscess (Pindborg 1970). General features of the early progression of the carious process have been established, but, the exact etiology and chemical pathways involved in caries formation are still uncertain (Shafer et al. 1983). It is generally agreed to be a complex problem complicated by many indirect factors which obscure the direct cause or causes. Three principal theories on the etiology of dental caries have emerged after numerous years of research. These include the acidogenic theory (Miller’s chemico-parasitic 69 theory), the proteolytic theory and the proteolysis- chelation theory (Shafer e t a l. 1983). Shafer, Mine, and Levy (1983) will be used to explain these ideologies of caries etiology. The acidogenic theory was established in the late 1880s by WD Miller. Miller states that "dental decay is a chemico-parasitic process consisting of two stages, the décalcification of enamel, which results in its total destruction and the décalcification of dentin, as a preliminary stage, followed by dissolution of the softened residue. The acid which affects the primary décalcification is derived from the fermentation of starches and sugars lodged in the retaining centers of the teeth" (in Shafer et al. 1983:410). The proteolytic theory rests on the idea that the organic portion of the tooth renders a salient role in the carious process. Enamel structures (i.e., enamel lamellae and enamel rods) which are made up of organic material are known pathways for microorganisms through enamel. Thus, when microorganisms invade these structures the acids produced by these bacteria are capable of destroying portions of the enamel. Microorganism invasion of dentin also has been demonstrated with caries as the end product. Schatz and co-workers (in Shafer et al. 1983) founded the proteolysis-chelation theory. They maintain that 7 0 keratinolytic bacteria initiate a bacterial attack on the enamel. This assault results in a breakdown of the protein and other organic constituents of enamel, especially keratin. The outcome is the formation of substances which may form soluble chelates with the mineralized component of the tooth, whereupon the enamel will be decalcified at a neutral or even alkaline pH. This latter theory resolves the dispute as to whether the initial attack is organic or inorganic by alleging both may be attacked at the same time. Nonetheless, Pindborg (1970) feels that most available evidence supports the acidogenic theory. The complexity of caries investigations is accentuated as one evaluates the variability of caries frequencies in individuals and populations. Shafer and associates (1983) state that differences exist between persons of the same sex, age, ethnic group, and geographic area subsisting on similar diets under the same living conditions. With no consensus on etiology of caries formationi it appears that a number of p o ssible in d ire c t or co n tributing fa c to rs must be considered. Epidemiological studies of extant populations have identified several of these factors. Caries frequencies have been identified in association with the following: composition of the tooth; morphologic characteristic of the 71 tooth; tooth position; composition of the saliva; Ph of the saliva; viscosity of the saliva; quantity of saliva; antibacterial properties of saliva; buffer capacity of saliva; physical nature of the diet; carbohydrate content of the diet; vitamin content of the diet; calcium and phosphorus dietary intake; fluorine content of the diet; and heredity (Pindborg 1970; Heloe and Haugejorden 1981; Krasse 1985; Shafer et al. 1983; Newbrun 1982; Bhaskar 1986). However carbohydrate content of the diet is the principal attribute associated with caries. Most studies regarding the tooth’s role in caries development are focused on the inorganic portion of the tooth. Different levels of chemical elements found in surface enamel apparently contribute to caries resistance. Morphological features (e.g., fissures and pits) are thought to predispose the tooth to caries development by providing an area for food entrapment. Attritional advancement tends to obliterate morphologic characteristics reducing an area for food to accrue, hence individuals with advanced a t t r i t i o n are in clin ed to have fewer crown c a rie s. Improperly aligned teeth have a tendency to allow food debris to collect in difficult to reach areas in the mouth, creating a climate conducive to caries formation. Saliva is considered the "environmental" agent which influences the state of oral health in a person (Shafer et 7 2 al. 1983:419). As such, everything about saliva must be considered with respect to caries formation. Both the quality and quantity of saliva have a relationship to the incidence of dental caries. For an excellent review of saliva as a factor of caries formation see Shafer and colleagues (1983). Caries formation and diet are of particular interest. Diet may influence dental decay by either inhibiting or promoting it (Naylor 1984). The cariogenic nature of a food item is associated with its carbohydrate and acid content, as w ell as the i t s adhesiveness in the mouth (Krasse 1985; Newbrun 1982). Carbohydrate content of diet is recognized as the most important factor in the process of caries form ation. D iets in which sugars and starch es are consumed alter the composition of the saliva. Microflora production in the oral cavity is facilitated by the appearance of carbohydrates in the diet. From these food types bacteria form two extracellular polysaccharides: w ater-soluble and insoluble glucans. The w ater-soluble glucans serve two purposes: 1) to adhere the microorganisms to the smooth surfaces of the tooth and 2) as a n u trien t supply. The insoluble glucans assist in cell-to-cell adhesion and creates the structural bases for colony formation. Together, the glucans secure other substances (i.e., lipoteichoic acid) to form a covering (plaque) over 73 the tooth. Beneath the plaque acid accumulates. Since the Ph of carbohydrates is considered to be acidogentic; acid build-up will be intensified, resulting in the demineralization of the enamel by the acids (Krasse 1985). Dental caries commonly are considered a disease of a "civilized " d ie t (P atterson 1984:69). However, c a rie s research documents their antiquity among australopithecines (Brothwell 1963). Research of the Upper Paleolithic and Mesolithic periods have revealed low incidence rate for caries (less than eight percent), with an increase from 5 to 14 percent by the end of the Neolithic (Patterson 1984). Studies in British populations from the Iron Age to approximately late Medieval times demonstrate little change in caries expression (Kerr et al. 1988). Beginning around the 17th century, the pattern of caries starts to change from a pattern of low frequency to a pattern of increasing frequency (Kerr et al. 1988). Caries rates often are used by bioarchaeologists as indicators of carbohydrate consumption where archaeological evidence for diet is in s u ffic ie n t (Schneider 1984; S c iu lli and Schneider 1986). Some use the rate of 2 carious lesions per person as the dividing point between high- and low-carbohydrate diets (Rose et al. 1984; Turner 1979). Extensive surveys of the occurrence of c a rie s in modern populations have been undertaken. Mallanby in 1934 (in 74 Shafer et al. 1983) reviewed the literature on caries in existing cultures which subsisted on diets low in carbohydrates. In his survey he noted the incidence of caries. Marthaler, in a series of cross-sectional surveys of selected age groups in extant people of Tristan da Cunha, revealed a rapid increase in caries over time. He explains th is ris e in frequency due to a change to modern d ie t and eating habits dominated by imported industrial sugar- containing products (Heloe and Haugejorden 1981). Other similar trends have been reported from Greenland, Canada, Alaska, Africa, and Asia (Heloe and Haugejorden 1981; Shafer et al. 1983; Patterson 1984). Heloe and Haugejorden (1981) hypothesize that dietary habits are the major determinants for "the rise and fall" of dental caries at the global level. They present information co llected by the World Health Organization (WHO) on the geographic distribution of caries in 12-year-olds in the early and middle 1970s to substantiate their claim. High to moderate caries levels are found in industrial countries, with very low to low levels in developing countries. Other factors that affect the distribution of dental caries are demographic, genetic, and socioeconomic status. 7 5 Tooth Loss

Teeth in archaeological collections may be lost either before or after death. Antemortem tooth loss (AMTL) is the loss of teeth prior to an individual’s death. This condition is identifiable by progressive resorptive destruction of the alveolus. Tooth loss which occurs immediately before death w ill be confused with postmortem tooth loss. It is often difficult to successfully assess specific AMTL in specimens with advanced attrition and inordinate AMTL. Antemortem tooth lo ss may o rig in ate from several different etiological pathways: 1) caries ■» pulp exposure -* abscess •» resorption + tooth loss; 2) calculus accumulation

■* periodontal disease ■» resorption ■» tooth loss; or 3) attrition pulp exposure ■> abscess ■* resorption -» tooth loss (Lukacs 1989:265). Thus, depending on the etiology, AMTL can be classified as either infections or degenerative. In addition to the etiological pathways just mentioned, dental trauma (either accidental or intentional) can result in AMTL. Interpreting the prevalence of AMTL is difficult because of differing reports on the changing frequency of this pathology with the appearance of horticulture. Smith et al. (1984) for the Levant; and Cook (1984) for the Lower Illinois Valley report an increase in AMTL with an increase 76 reliance on horticulture. High frequencies of AMTL also are noted by Meilkejohn and colleagues (1984) for Mesolithic Europeans and by Rathbun (1981) for Paleolithic Southwest Asians. Anderson (1965), however, found a decrease in AMTL from pre-horticulturalist (41.6) to horticulturalist (6.2) at Tehuacân.

Stature

Stature estimates reflect both intrinsic (biological) and extrinsic (environmental) conditions influencing past populations, interpretations based on stature estimates must be done with comprehension of both these causal agents.

Umg Bone Growth

The growth of linear dimensions of individuals in contemporary human populations has been shown to be the result of hereditary and environmental variation (Malina 1975; Johnson et al. 1980). The hereditary component of variation in growth potential, both at the individual and interdemic level, however, has been found to have only minor e ffe c ts compared to environmental circum stances. Growth processes are, in general, plastic and readily modified by environmental variation. Factors such as climate, disease load, nutrition, and hygiene play important roles in determining variation in growth processes and final 7 7 phenotypic expression. Populations known to have been exposed to extremes of environmental variation exhibit, for example, slowed growth rates, delayed maturation, an extended growth period, smaller adult stature, and increased variability in adult stature compared to genetically similar populations not exposed to extreme environmental variation. Investigations of linear growth of long bones in contemporary populations have determined that bone growth to be an accurate estimator of population's general growth response to extreme environmental variation (Eveleth and Tanner 1976). These findings in contemporary populations have led to the appreciation of linear long bone growth as a potential source of information concerning the environmental circumstances of prehistoric populations particularly their health and nutritional status (Mensforth et al. 1976; Jantz and Owsley 1984; Mensforth 1985). Variations in growth velocity of particular skeletal elements produce many of the fetal, childhood, and adult differences in morphology seen between and among species and genera (Harrison et al. 1988). The growth process is characterized by differential growth rates for various tissues and separate areas of the body. The process is a highly organized interdependent system, whereupon one process depends on the achievement of a single or multitude of other stage(s). How this complex organization network 78 functions is said to be on of the "most fundamental problem of growth" (Harrison et al. 1988:352). Understanding the differential growth rates in the human skeleton will allow a better assessment of adult stature. The organization of growth manifests itself through the emergence of maturity "gradients" (Harrison et al. 1988). To assess an element or group of elements (e.g. lower leg) in terms of its maturity, the items are compared to the percentage of the adult value. Gradients of maturity change through time, with some elements reaching adult values earlier than other elements. The head grows first, and approaches its adult status much earlier than the torso; the torso, in turn, grows earlier than the legs (Meredith 1939). Simmons (1944) notes that hands reach adult values sooner than the forearm, and forearm reaches adult values sooner than upper arms at all ages. Tanner (1962) states that there is a growth gradient from lower to upper portions, as well as in anteroposterior depth, transverse width and height. He also asserts arms are in their upper two segments advanced over the corresponding segments of the leg s. Bergman and Gorqcy (1984) suggest a re la tio n sh ip between the time of appearance of growth spurts in some body dimensions and the recency of their phylogenetic origins. Even with a theoretically "clear" understanding of the organization of growth, one must be aware of the dynamics of 79 growth processes. In ideal circumstances, the pattern of growth appears to be quite regular and stable with little or no v a ria tio n . However, the p attern of growth can be altered greatly as extrinsic forces interact with the process of growth. An individual is able to respond rather flexibly to alterations in the environment. The short term physiological response to these alterations is observed at the individual level. For example, during a period of starvation an individual’s growth will slow down to adjust to the stress of inadequate nutrition. This pattern will be followed, in most cases, by prompt catch-up growth to a previous growth curve when food (again) becomes readily available to the individual. The capability to achieve catch-up growth depends on the timing and severity of the stress. The property of returning to the original growth curve after being pushed off trajectory has been called canalization by Waddington (1957). The unusually large velocity occurring during this process has been termed "catch-up" by Prader, Tanner, and Von Harnack (1963).

AduH Height

The long term selective or evolutionary response to environmental alteration is observed at the population level. This type of change is termed an adaptation and is 80 thought to provide an adaptive advantage. Many times this pattern is observed as secular trends. Investigations of linear growth of long bones in contemporary populations have determined that long bone growth is an accurate estimator of a population’s response to extreme environmental variation (Eveleth and Tanner 1976). These findings in contemporary populations have led to the appreciation of linear long bone growth as a potential source of information concerning the environmental circumstances of earlier human populations, particularly their health and nutritional status (Mensforth et al. 1978; Jantz and Owsley 1984; Mensforth 1985). Studies of linear long bone growth in human skeletal populations, generally, have taken two approaches in understanding environmental influences. In the first approach, an attempt is made to assess the sufficiency of growth in a previous population by comparing it to a contemporary "control" population with optimum or close to optimum environmental conditions. In the second approach, growth variation is assessed among or between previous populations differing in environmental conditions usually as the result of a major shift in subsistence. An approach used to assess the potentiality of biological relatedness between the populations would look at growth status between populations under similar environmental pressures. 8 1 Besides the climatic-morphological conditions which are associated with zoological rules, nutritional inadequacy is the other environmental factor which can have a strong impact on growth. Reduction in body size or "growth failure" is commonly considered the major index of nutritional stress (Harrison et al. 1988). Borgin (1988) recognizes evolution by natural selection to be caused by environmental changes (i.e., variation in food availability and temperature) which test the ability of organisms to "adapt" to the change. Viewed in this evolutionary framework, he feels variation in growth, development, and adult size of living populations is a biological adaptive response to fitness (i.e., Darwinian). Others have suggested the selective forces of natural selection have favored those individuals with a genetic potential to be smaller in situations where food is scarce (see Borgin 1988 for a review of these articles). Greene (1977), and others, have introduced the hypothesis that malnutrition creates selective pressures against children with the genetic potential for greater growth. Greater nutritional requirement would be necessary for larger children to account for the added metabolic cost of growth, as well as increased needs associated with maintenance of their large body mass. 82 These researchers propose that in times of starvation, larger children and adults will be at a higher risk of dying. It is through this mechanism, they suggest, that populations subjected to long extensive bouts of chronic u ndernutrition w ill be comprised of sm all indiv id u als and therefore the reason for the smallness would be genetic (i.e., adaptation). In other words, the hypothesis states that reduced body size within a human population constitutes a genetic adaptation to limited food resources by lowering the nutritional requirements for physical growth and body maintenance. According to this hypothesis, where malnutrition is endemic, children with high protein requirements are more likely to develop kwashiorkor and th erefo re d ie. However, as M artorell (1984) points out, i f this was true, then the mean protein requirements would be lower in populations with a very long history of malnutrition. It has been demonstrated that this is not the case. In an earlier investigation of malnourished Guatemalans, Martorell and co-workers revealed that taller women had a higher fitness value (i.e., they contributed more offspring to the next generation) than shorter women. Thus, the preceding hypothesis which states there is differential fertility in favor of short mothers in malnourished populations must be rejected because of 83 constraints imposed by childbirth so males and females are under different selectional pressures. Martorell (1984) suggests genetic changes in terms of growth at the population level is unnecessary. He feels children are capable of.modifying their growth to cope with malnutrition (i.e., adjustment). Waterlow (1984:8) clearly states growth failure is not a genetic adaptation, but rather a response to a particular environment. He su b sta n tia te s th is claim by commenting on catch-up growth and an individual's full genetic potential. Waterlow suggests that since catch-up growth is possible during childhood in these short populations, then these short individuals are not meeting their full genetic potential. In other words, they are not adjusted to their environmental s tre s s . Seckler (1980; 1982) proposed the "small but healthy" hypotheses which argues that children who are stunted but not wasted are healthy. Thus, stature of past populations would not satisfactorily reveal the effects of environmental conditions. Martorell (1989:15) argues against the “small but healthy" approach. He makes four points:

1. adults in developing countries have small body sizes largely as a result of poor diets and in fe c tio n during childhood 84 2. growth retardation, rather than an innocuous response to environmental stimuli, is a warning signal of increased risk of morbidity and mortality 3. the conditions which give rise to stunted children also affect other aspects such as cognitive development 4. stunted girls who survive to be short women are at a greater risk of delivering growth retarded infants with a greater probability of dying in infancy.

From these points he concludes small is not healthy. Using Martorell’s argument, monitoring growth patterns is a good indicator of health from which environmental processes may be assessed. CHAPTER IV

METHODS

This chapter will provide the methodological framework for the investigation of biological affinity and environmental stress sim ilarities and differences between and within Fort Ancient and Sandusky populations. Each procedure and technique used in data collection will be explained, as will statistical analyses used in data manipulation. Techniques for age and sex determinations also are addressed in this section.

Age Determination

Estimating age from the skeleton is equal in difficulty to estimating age from a living person (El-Najjar and McWilliams 1978). Accuracy and certainty in establishing age are reduced with increasing age for both living and dead individuals. Numerous techniques have been established in order to determine age at death for skeletal populations.

Subadult Age Determination

Age determination in immature individuals is straightforward. Criteria employed in this study were 85 86 dental development patterns (Moorrees et al. 1963a; 1963b).

Adult Age Determination

Age determination for adults is more problematic. In the adult, morphological variation is much more subtle and the sequence of chronological development is not as exact. The reliability of an age determination is largely dependent on the preservation of the skeleton. Whenever possible multiple lines of evidence were implemented in age determination. Age estimates are based on the gross morphological examinations of the following regions: metamorphosis of the pubic symphysis (Meindle et al. 1985; Suchey et al. 1988) and the auricular surface of the ilium (Lovejoy et al. 1985), epiphyseal union of the clavicle, and suture closure of the cranium (Meindle and Lovejoy 1985). Sériation of dental attrition, the pubis synthesis and auricular surfaces was possible for the Pearson collection.

Sex Determination

Data from males and females were treated separately in the biodistance analysis so as to exclude within-group variability contributed by sexual dimorphism. Sex assessments for Madisonville were made exclusively by this 87 researcher. Assessment of the other sites were made by this researcher and Paul Sciulli. Pubic bone characteristics were used as the primary indicator of sex (Phenice 1969), while ancillary indicators (Appendix B) included discriminant functions based on maximum vertical diameter of the head of the humerus, minimum circumference of the humerus, maximum diameter of the head of the femur, femur midshaft circumference, and foot height, or sériation based on robusticity and size/shape variations of cranial morphological characteristics (Acsédi and Nemeskeri 1970). The metrics for the discriminant functions were based on measures from individuals sexed by the Phenice method. BMDP7M and BMDP2D were used for determining discriminant functions and allocating individuals to sex (Dixion et al. 1990). No effort was made to appraise the sex of subadults since sex indicators in juveniles are generally unreliable.

Metric Data

This study will use cranial metric data for distance analysis, because complete crania are available and because the cranium is thought to be the part of the skeleton which shows the clearest genetic attributes. Studies of patterns of growth and nutritional conditions indicate measures of long bone length and stature are more plastic in response to 88 such conditions as opposed to cranial measures (Hooten 1930; Benfer 1968; Bennett 1973). However, as mentioned in the previous chapter, adult height most definitely has a genetic component which may be assessed in terms of biodistance. In addition to using adult height to assess biological affinities, adult height and subadult measures of long bone lengths will be used to evaluate environmental (nutritional/ stress) questions.

Cranial Metrics

The ensuing research began with thirteen metric traits from the cranium: biasterionic breadth, frontal arc, frontal chord, maximum breadth, maximum length, minimum fro n ta l breadth, occipital arc, occipital chord, parietal arc, parietal chord, porion to bregma, porion to lambda, and porion to nasion. A brief description of these traits is offered in Appendix A. The original set of measures represents measurements traditionally considered to be important in distinguishing skeletal populations. Cranial deformation can introduce serious bias into biodistance comparisons (Verano 1987), thus crania identified as being deformed were eliminated from this study. All measures were taken using standard craniometric instruments. 89 In cases where three or fewer of the total traits were missing, the missing values were estimated by the multiple regression option of BMDPAM (Dixion et al. 1990) using cases with complete data. This procedure was applied separately to each sample using all individuals in the sample with complete data. In order to assess whether traits should be discarded, a principal component analysis of the 13 x 13 variance covariance matrix in each sample was assessed using BMDP4R (Dixion et al. 1990). The traits with the largest absolute values for a coefficient in the eigenvectors of the smallest eigenvalues were discarded since these traits are either of less importance or are redundant (Mardia et al. 1979:242). The remaining variance covariance matrices were examined for homogeneity using Box’s (1949) F-test (using Speakeasy, Cohen and Pieper 1979). Mahalanobis’ Generalized Distance (Df) was the m u ltiv ariate method used on the remaining c ra n ia l measures, because this multivariate measure of between-group differences takes into account correlations between variables and differences in sample size (Mahalanobis 1936). The D® statistic is generally recognized as the most useful overall measure of morphological sim ilarity between populations (Talbot and Mulhall 1962; Howells 1966; Rightmire 1969; Hiernaux 1972) and has been used extensively 90 as a measure of biological relationships between skeletal populations. Principal coordinate analysis was preformed on the resulting distance matrix of the Mahalanobis’ scores. The geographical distances also were assessed using principal coordinate analysis. Biological and geographical distances then were compared to each other by employing Procrustes Rotation (Mardia et al. 1979:416). Procrustes Rotation allows for the best fit between the two distance m atrices.

Adult Postcranlai Metrics

Descriptions of the eleven postcranial metrics gathered for adults in this study are outlined in Appendix B. Measures were collected from non-diseased skeletal elements using standard osteological instruments. The adult post- cranial metrics for this study are described further in the succeeding section on stature under the heading adult height.

Subadult Postcranial Metrics

Metrics gathered for subadults in this study included the maximum diaphysial lengths for the humerus, radius, ulna, femur, tibia, and fibula. In addition, the length of the clavicle, the height of the scapula, and the breadth of the ilium were recorded. These measures were taken prior to 91 epiphyseal union with either sliding calipers or an osteometric board. Only non-pathologic bones were included in this analysis. A description of these measures is located in Appendix B. Application of the subadult post­ cranial metrics gathered for this study is elucidated in the ensuing section on stature under the heading long bone growth.

Nonmetric Data

Data were collected on seventeen discrete traits from non-deformed crania (see Table 5). Descriptions of these traits are found in Appendix C. These variables were selected for three reasons: 1) they are biologically interpretable, generally reflecting a portion of the hereditary makeup of a population; 2) they were thought to vary among the samples; and 3) they have the largest sample sizes over the sites. Trait scores were translated into numbers where 0 = t r a i t absent, 1 = t r a i t , and 9 = no data. Bilateral traits were appraised with the assumption that unilateral occurrences are randomly "equal" to both bilateral presence and bilateral absence, or in other words that fluctuating asymmetry causes random distribution of t r a i t s by sid e. Following the method outlined by Konigsberg (1987), random side scoring was applied. Both sides were scored when possible, and if scoring for the two sides 92 differed, then one side was randomly selected to represent an individual. After data collection traits were assessed to see if variation in trait expression did in fact exist among the sites. Significant age and sex differences have been reported to exist in the expression of nonmetric variants (Corruccini 1974), subsequently the influence of both age and sex on the m aterial was appraised.

Table 5. List of cranial nonmetrics.

TRAIT EXPRESSION SCORED

Accessory Mental Foramen present Asterionic Ossicles present Coronal Ossicles present Foramen Huschke present Foramen Ovale Configuration complete Foramen Spinosum Configuration complete Hypoglossal Canal Configuration double Lingula Bridge present Mastoid Foramen Locus exsutural Mylohyoid Bridge present Occipital Condyle Form double Parietal Foramen present Parietal Notch Bone present Postcondylar Canal Configuration canal present Precondylar Tubercle present Superior Sulcus Direction right Supraorbital Foramen Configuration notch 93 Next, the trait frequencies of each sample were obtained for traits showing variation between sites and having no correlation between age and sex. These frequencies were generated using a program in BASICA. The chi-square test was used to test the hypothesis that each trait was not correlated. The independent traits were retained for analysis. The chi-square was used again to test for associations between sex and trait expression and age and tra it expression (BMDP4F (Dixion et al. 1990)). The Mean Measure of Divergence (MMD) (de Souza and Houghton 1977) then was calculated for the noncorrelated (e.g., age, sex, and by trait) traits using BASICA. The MMD, is a test of the statistical significance of d ifferen ces in t r a i t frequencies fo r a number of t r a i t s considered simultaneously, and is thus a general measure of "distance" between two population samples. The MMD equation can be w ritten as:

MMD = 1/T * Zi_, [(6,1-021)" - (1/n,i+l/nji)] (1)

Where T = the number of t r a i t s and 0 = s i n ’(1-2P) and P is an estimate of the percentage of the population having the t r a i t (i) in question. Sample sizes from the two populations are n, and ng. A Monte Carlo procedure in the smaller samples was applied using BASICA to evaluate if the MMD values could 94 occur by chance. The observed MMD values are used to predict the expected proportion of cases in each cell, under a null hypcthesis of trait independence. For each sample’s ta b le of t r a i t s , uniform random numbers are generated up to the number of cases observed in the table. Permuted cases then are placed into the relevant cells of the trait table based on the new proportions. A MMD was then calculated for each permuted table. This process was repeated for a total of 200, which resulted in a suitable continuous distribution. In the larger samples the MMD’s were calculated using the known trait frequencies and sample size per trait for each population. The trait significance levels were evaluated using a chi square. Using trait frequencies and sample size per trait per population the Harpending and Jenkins’ d^ (1973) statistic also was applied to the discrete data. The d^ equation can be written as:

d' = fu + n, - 2r\,. (2 )

Where

Pi and Pj refer to the trait frequencies in the samples i and j being compared; and P i s the average of the two 95 matrices being compared. The is the squared Euclidean distance between the populations under consideration. A p rin c ip a l coordinate an aly sis was preformed on the resulting distance matrix of the MMD values and of the Harpending and Jenkins’ d^ values. Both biological distances for discrete data and geographical distance then were compared to each other by employing Procrustes Rotation.

BioputtHral Stre?? Indl.catp.rg Of particular interest here are the use of dental pathologies as indicators of nutritional disease or nutritional stress. Abscesses, attrition, caries, and tooth loss were observed by a tooth count method, thus allowing an evaluation of a pathology’s distribution by jaw, tooth class, or location on a tooth crown.

Abscesses

A macroscopic diagnosis of abscessing was performed on the alveolus for the presence or absence of abscesses. An abscess was judged present if a cloacae or an inflammatory bone reaction was observable. The Abscess Index was calculated as:

total # abscess total # loci X 100 (4) 96 Where the to ta l number of lo c i was determined by counting (anteraortem tooth loss) + (postmortem tooth loss) + (teeth with supporting alveolus).

Attrition Only those dentitions that were thought to represent a state of normal health and that were at a completed developmental stage (i.e., in full occlusion) were analyzed for attrition. Attritional status was assessed using a scale developed by Molnar (1971a). His technique assigns various degrees of wear to different categories based upon the criterion of dentin exposure. Categories range from unworn te e th (category 1) to te e th with roots functioning in occlusion (category 8). For this study, category 1 (typically unerupted teeth) was not evaluated. Categories 3 and 4, 5 and 6, and 7 and 8 were combined, thus resu ltin g in a total of four wear categories (e.g., 2, 3-4, 5-6, and 7- 8). Side and type of tooth, as w ell as age and sex of an individual, were factors suspected of having an effect upon attrition. With this in mind, the data were separated into age, sex, side, and type categories to determine their e ffe c ts upon one another. 97 Caries

Caries are commonly classified by their size and lo catio n on the to o th . However, in th is research no size gradation was employed. Each tooth was examined fo r the presence or absence of caries. Small caries were confirmed as caries by use of a probe to identify the presence of demineralization of the enamel surface. Care was taken not to count the morphological trait “buccal pit" or "foramen caecum hypoplasia" as d en tal c a rie s. The locations of recorded caries lesions include: occlusal, mesial, buccal, distal, lingual, mesial cementoenamel junction, buccal cementoenamel junction, distal cementoenamel junction, lingual cementoenamel junction, and totally rotten. In cases where multiple c a rie s were present, the t o ta l number of c a rie s was recorded. In addition to location of the caries by tooth and by jaw, teeth were assessed in conjunction to age. The Caries Index (Kelley e t a l. 1991) was calculated fo r each s it e . The C aries Index was calculated as:

total # carious teeth x 100 . (5) t o ta l # te e th

A Total C aries Index (Kelley et a l. 1991) also was calculated for each individual from each site. The Total Caries Index was calculated as: 98 to ta l # c a rie s per mouth x 100 . (6) # te e th per mouth

Tooth Loss

Tooth loss was identified as either antemortem tooth loss (AMTL) or postmortem tooth loss (PMTL), by a gross examination of the alveolus. AMTL was ascertained when a tooth was absent and the socket had overt alv eo lar bone resorption. PMTL was concluded when a tooth was absent and the tooth socket had no obvious remodeling. The AMTL Index was calculated as:

■to t al # AMTL total # loci X 100. (7)

The DM (D, decayed: M, antemortem tooth loss)(Kelley et al. 1991) was calculated as:

total # carious teeth + total # AMTL total # loci X 100. (8)

The Disease Index was calculated as:

total # caries + total » AMTL + total # abscess total # teeth X 100. (9) 99 Stature

This section uses metrics obtained from subadult and adult skeletons (as proposed in the above sections on post­ cranial measures, respectively) in order to assess health stressors (subadult) and health stressors and biodistance (adult). Data on stature will be considered only if the genetic aspect of stature is understood.

Long Bone Growth

The primary aims of assessing long bone growth are to evaluate the growth processes in the Late Prehistoric samples to the extent to which these processes are concordant with findings concerning the biocultural stress of each sample. The maximum length of subadult bones was measured according to the procedures described in the above section on subadult postcranial metrics. Correlations of dental age estim ates (Moorrees et a l. 1963a; 1963b) and maximum diaphyseal length of each subadult bone were calculated from each site. Next, generalized growth curves were reconstructed for each site. Linear growth was analyzed from birth to adulthood using the Count Regression Model (Count 1943). This equations is as follows:

length = bo + b, (age) + bg (log age) + e. (10) 100 The Count Regression Model has been used on various occasions to model lo n g itu d in al growth (Giesen and S c iu lli 1988; Jan tz and Owsley 1984; Berkey 1982). Depending on how the samples compare with respect to genetic affinities, growth will be assessed in terms of velocity and acceleration by sample or grouped together. The correlation between chronological age and the maximum diaphyseal length (without epiphyses) of each long bone and the maximum width of the scapula and ilium will be examined.

Adult Height

Regression equations developed by Sciulli and colleagues (1990) after Fully's (1956) anatomical method were used to estimate skeletal height. Measures used in the equations include skull height, vertebral column length (02 to SI), the bicondylar length of the femur, the standard length of the tibia, and the foot height. Depending on the outcome of the analysis of variance for the cranial data, stature will be assessed for homogeneity using the F-test. If the metric statistics for the samples are shown to be homogeneous, then the stature should be homogeneous i f environmental pressures are the same between the samples. If after a test for variance is performed the samples vary for stature, then environmental pressure suspect of influencing the samples stature will be evaluated. CHAPTER V

RESULTS

This chapter presents the results of age and sex estimates, biological distance analyses, and of the analysis of biocultural stress status.

Age and Sex Estimations

Criteria employed in this study to age subadults were dental development patterns (Moorrees et al. 1963a; 1963b). The total numbers of subadult age estimates made by this technique per site are as follows: Anderson = 19, Buffalo = 140, Madisonville = 56, Pearson = 136, and Sunwatch = 85. Whenever possible multiple lines of evidence were implemented in adult age determination. Age estimates are based on the gross morphological examinations of the following regions: metamorphosis of the pubic symphysis (Meindle et al. 1985; Suchey et al. 1988) and the auricular surface of the ilium (Lovejoy et al. 1985), epiphyseal union of the clavicle, and suture closure of the cranium (Meindle and Lovejoy 1985). Averaging the difference estimates per individual resulted in a single age estimate for that in d iv id u al. The to t a l numbers of ad u lt age estim ates made

101 102 by this technique per site are as follows: Anderson = 29, Buffalo = 245, M adisonville = 113, Pearson = 153, and SunWatch = 60. Pubic bone characteristics were used as the primary indicator of sex (Phenice 1969). The total numbers of sex estimates made by pubic bone assessment per site are as follows : Anderson =

Madisonville = d63 and 983, Pearson = 3 5 0 and 959, and

Sunwatch = 3 9 and 913.

Biological Distance

Genetic affinity among the seven Late Prehistoric samples is estimated by using cranial metrics, cranial d isc re te t r a i t s , and adult s ta tu re . 10 3 Cranial Metrics

Table 6 presents the number of individuals for which missing cranial estimates were made and the number of estimates that were made per sample. Compared to the total number of indiv id u als measured and the to ta l number of cranial measures taken, the number of estimated measures is small. Estimated measures were obtained for 16.7% of the total number of individuals but only 2.2% of the total number of c ra n ia l measurements were estim ated.

TABLE 6. Data estimates for cranial metric analysis.

SITE Sample Size # of individuals # of measures for which estimated estimates were made

ANDERSON 36 10 14 BUFFALO 29 3 4 INDIAN HILLS 11 3 6 MADISONVILLE 95 19 34 PEARSON 41 2 5 PETERSEN 12 0 0 SUNWATCH 46 8 14

Tables 7 through 9 presents metric trait descriptive statistics for each sample. Multivariate analysis of the cranial metric data began with a principal component analysis of the 13 x 13 variance-covariance matrices (see Appendix D). Parietal chord, porion to basion, and TABLE 7. Summary of cranial metrics for males and females by site.

ANDERSON BUFFALO INDIAN HILLS MADISONVILLE PEARSON PETERSEN SUNWATCH

XSXSX 3 X S X 8 X S XS

Biasterionic Breadth 107.4 5.1 109.2 4.7 107.7 5.4 109.5 5.5 109.0 4 .9 109.6 4.9 107.8 3 .9

Frontal Arc 11S.9 6.1 122.7 7.6 125.6 5.1 124.3 5.6 127.7 8.8 125.6 4.1 128.4 6 .8

Frontal Chord 104.8 5.8 109.8 5.7 111.5 3.7 110.5 4.3 112.9 5.7 111.3 4.1 114.4 5.3

Maximum Droadth 134.1 5 .6 147.1 7.4 139.9 7.2 147.4 6.0 140.9 7.1 140.3 5.9 139.1 5.4

Maximum Length 175.8 9.6 174.3 6.5 173.1 6.2 176.0 6.9 182.7 7.9 174.6 6.2 181.6 7.2

Minimum F ro n ta l B readth 94.1 6.4 94.1 5.2 97.3 2.8 95.1 3 .8 95.8 5.0 93.7 2.1 93.3 5.1

Occipital Arc 114.7 9.9 116.0 8.8 110.8 9.6 111.5 6.3 120.1 7.5 116.7 6.7 119.7 8.1

Occipital Chord 95.9 7 .0 98.2 6.5 95.4 5.2 94.9 5.3 100.8 5 .5 97.6 4.7 100.9 5.9

Parietal Arc 121.9 8 .8 120.5 6 .3 119.4 4.2 119.3 7.1 125.6 9.0 121.8 4.6 123.5 8.7

Parietal Chord 105.7 7.4 107.6 4 .8 105.9 7.6 105.7 5.2 111.5 7.2 109.0 6 .0 109.8 7 .4

P orion to Bregma 129.2 4.4 132.8 4.8 128.4 5.3 131.5 4.7 130.9 6.3 127.7 3 .7 132.5 5.4

P o rio n to Lambda 113.6 6.0 116.1 4 .8 111.2 5.3 114.6 4.8 117.6 5.4 115.2 5.9 117.0 4.4

Porion to Naslon 109.6 6 .2 108.3 6.1 108.8 6.3 113.4 4.6 108.3 7.3 108.3 4.3 111.1 6.8

o 1 0 5 TABLE 8. Summary of cranial metrics for males by site.

ANDERSON BUFFALO MADISONVILLE PEARSON SUNWATCH â (19) (15) (47) (18) (26) X S X S X S X S X S Biasterionic Breadth 108.6 4 .6 109.94.6 111.55.5 111.64.8 108.54.5 Frontal Arc 120.4 5.8 124.38.0 126.05.5 130.98.2 131.35.7 Frontal Chord 106.6 5 .8 110.55.4 112.24.3 115.76.0 117.14.2 Maximum Breadth 136.7 4.9 148.48.1 148.85.4 143.15.9 141.35.3 Maximum Length 180.0 8.7 174.87.0 178.66.9 186.18.6 184.75.7 Minimum Frontal Breadth 96.5 7.6 93.45.6 9 6 .7 3 .9 9 5 .4 4 .3 95.04 Occipital Arc 117.311.4 117.78.5 111.16.6 124.16.8 119.96 Occipital Chord 97.5 7 .8 98.97.1 94.95.7 102.65.1 100.86.1 Parietal Arc 124.6 8.1 120.06.5 121.36.4 128 .9 7 .3 126.58.9 Parietal chord 107.5 6.8 106.94.7 107.35.0 113.36.3 111.57.4 Porion to Bregma 131.9 3.8 132.94.9 133.14.9 134.47.1 132.54.9 Porion to Lambda 117.2 5.1 116.35.7 115.75.0 120.35.2 118.34.2 Porion to Naeion 112.5 5.5 109.46.0 116.04.0 112 .4 6 .9 113.35.8 106 TABLE 9. Summary of cranial metrics for females by site.

ANDERSON BUFFALO MADISONVILLE PEARSON SUNWATCH 9 (17) (29) (95) (41) (46) X S X 8 X S X S X 3 Biastsrionie Breadth 105.95.3 108.44.9 107.64.9 107.04.1 106.82.9 Frontal Arc 117.46.3 121.07.2 122.65.2 125.18.6 124.66.4 Frontal Chord 102.75.2 109.16.2 108.83.7 110.64.4 110.94.6 Maximum Breadth 1 31.24.9 145.76.6 146.16.2 139.37.6 136.14.1 Maximum Length 171.28.5 173.76.1 173.55.9 180.16.4 177.67.2 Minimum Frontal Breadth 91.43.0 94.94.9 93.52.9 96.05,6 91.04.6 Occipital Arc 111.97.3 114.19.1 111.86.1 117.06.7 119.37.6 Occipital Chord 94.25.8 97.56.0 94.94.9 99.35.5 101.05.7 Parietal Are 118.98.7 121.16.2 117.27.2 123.19.5 119.77.0 Parietal Chord 103.67.7 1 08.34.9 104.15.0 110.17.6 107.77.0 Porion to Bregma 126.12.9 1 32.84.7 129.94.0 128.14.0 129.04.0 Porion to Lambda 109.54.3 115.93.8 113.54.3 115.54.6 115.24.0 Porion to Naeion 106.35.4 107.26.3 110.93.6 105.05.9 108.17.0 1 0 7 occipital chord measures had the largest absolute values for coefficients in the eigenvectors of the smallest eigenvalues throughout the samples. These traits were discarded from each of the samples since they can be considered to be either of less relevance or of a redundant nature (Mardia et al. 1979:242). A test for homogeneity of the resulting (10 X 10) variance-covariance matrices was preformed for the seven samples. This test, = 1.51, P>0.05, could not reject the hypothesis of homogeneity. Thus, the seven samples could be, at least, descended from the same parent population with respect to general cranial shape that these measures represent and can be pooled to yield a common variance-covariance matrix. Table 10 presents the matrix of Mahalanobis’ values and geographic distances between samples in Km®. Using an F test at P>0.05, all between sample comparisons for D® were significant except for comparisons of Petersen and the following sites: Buffalo, Indian Hills, Pearson, and SunWatch. In these cases, the lack of sig n ifican ce is probably due to the small sample size of Petersen. To envision how the sites compare to each other for mean cranial size, the first three eigenvectors of a principal coordinate analysis for D® were used to produce a 3-dimensional map of their distribution (Figure 4). The sites separate into three clusters: cluster 1, Anderson, 1 0 8 Pearson, and SunWatch; c lu s te r 2, Petersen and Indian H ills; and c lu s te r 3, Buffalo and M adisonville. In te re stin g ly , the clusters appear to reflect a temporal distribution of the Late Prehistoric sites. Cluster 1 contains precontact samples; cluster 2 contains samples dating to approximately A.D. 1550; and c lu ste r 3 contains samples known to have European trade goods recovered with them.

TABLE 10. Mahalanobis’ values between samples with approximately equal numbers of males and females below diagonal'*' and geographical distance (Km)^ above diagonal.

ANDERSON BUFFALO INDIAN MADISON- PEARSON PETERSEN SUNWATCH HILLS VILLE

ANDERSON - 39134.7 61752.3 1490.0 53638.6 61752.3 1140.8

BUFFALO 7.1 4 ’ - 124256.3 43056.3 101410.4 110024.9 49261.8

INDIAN HILLS 5.09' 5.69’ - 81054.1 1584.0 1310.4 46612.8

MADISONVILLE 7.04" 1.89’ 4 .2 6 ’ - 71716.8 81054.1 4733.4

PEARSON 4.7 3 ’ 3.62’ 4 .7 7 ’ 5 .54’ - 327.6 41067.0

PETERSEN 3 .30’ 3.00 2.78 4 .5 0 ’ 2.13 - 47654.9

SUNWATCH 5 .2 0 ’ 4 .50’ 4.67’ 5.46’ 1.23' 1.78 -

O’ value* reflect ell cranial metrica except parietal chcrd, porion to baelon, and occipital chord. = elgnifioance at 0.05»

To visualize the fit between biological distance based on c ra n ia l m etrics (Of) and geographical distance (Km’), the first two eigenvectors of the principal coordinates analysis (Table 11) of the D’ matrix and the geographical distance matrix were plotted against each other by means of 109

2

1 PEARSON BUFFALO MADISONVILLE ■■ 0 g -1 ANDERSON

3 PETERSEN I INDIAN HILLS

SECOND FIRST

FIGURE 4. Three dimensional map of the first three eigenvectors of a principal coordinate analysis for Mahalanobis’ values. 110 Procrustes Rotation (Figure 5). The first two eigenvectors of the matrix account fo r 84.2% of the v a ria tio n . The D® and Km^ m atrices were transformed to a s im ila rity m atrix and centroids adjusted, the principal coordinates analysis then provided the normalized eigenvectors of the matrix. Figure 5 shows that no relationship exists between geographic distance and biological distance (R^ = 1.89).

TABLE 11. Summary of the l®’^ and 2"“ eigenvectors from the principal coordinate analysis for D® values and Km® values.

SITE Cranial D® Values Geographic Km® Values 1ST gNO 18T gND

ANDERSON -.51834 -.43608 -.43642 -.38378

BUFFALO .51414 .18948 -.82443 1.02280

INDIAN HILLS -.04205 -.51202 .76201 -.04550

MADISONVILLE .60089 -.24514 -.59114 -.54009

PEARSON -.18659 .47463 .63841 .17962

PETERSEN -.15577 .05671 .71611 .21904

SUNWATCH -.21228 .47242 -.26455 -.45207

To measure the significance of the association between the D® and Km® matrices, a permutation test between these 111

■ INDIAN HILLS ■ PliTl-RSEN SUNWATCH##: PEÀRSONX

ANDERSON

■ SUNWATCH

mClANDCRSON MADISONVILLE INDIAN HILLS

MADISONVILLE

FIGURE 5. Locations of the Mahalanobis’ (•) and the geographic Km® (■) after a Procrustes Rotation, 112 matrices was performed. The test statistic is based on Kendall’s tau:

Kc = Ej^^.,sign( [Xi, - X,*] [Yi, - Y^]), (11)

where X^, and Y^j are distances between points i and j for distance measures (Isi^jsn). Kc is the sum of the n(n-1) (n-2)/2 terms involving pairs of distances with a point in common. The P value of the observed statistic is the proportion of the n! permutations for which T is greater than or equal to the observed value. Each value of T, T[ (Xi2Y^(1)^(2)] . . . (X„_i and (1 ) .. .0 (n) ] is a permutation of the integers (1...n), and corresponds to a relabeling of the n points for the Y distance measure (Dietz 1983). The observed Kendall correlation statistic between the and the Km^ m atrices was 2.0. Using 2000 random permutations the estimated statistic exceeded the observed statistic 1121 times resulting in a P value = .5605. This permutation test is unable to reject the hypothesis of independence between the Mahalanobis’ distances and the geographical distances. In this sample of Late Prehistoric populations, cranial size is not structured by geographic distances between populations. Returning to the observation of the cluster distribution of values, the Dietz permutation test also was performed on the D^ and temporal difference matrices. 113 This procedure was executed in order to see if the distribution could be explained in terms of time since geographic distance did not appear to explain the distribution. The observed Kendell correlation statistic between metrics and time was 31.0. The estimated statistic exceeded the observed statistic 95 times in a 2000 permutation run resulting in a P value = .0475. This permutation test is able to reject the hypothesis of independence between Mahalanobis’ distances and temporal distances. Thus, it appears that cranial size for these Late Prehistoric populations is patterned by time between populations.

Cranial Discrete Traits

The analysis of cranial variation among the samples also considers the frequencies of seventeen discrete trait expressions (Table 12). Lack of variation within samples resulted in the deletion of three traits: foramen ovale configuration, lingula bridge, and occipital condyle form (see Table 13). Of the remaining fourteen traits, six were eliminated due to intercorrelations in one or more of the samples (Table 13). These eliminated traits include: coronal ossicles, foramen Huschke, foramen spinosum configuration, postcondylar canal configuration, precondylar tuberole, and supraorbital foramen configuration. Testing for age and sex association revealed that asterionic TABLE 12. Distribution of the original seventeen discrete traits by site.

TRAITS ANDERSON BUFFALO INDIAN H ILLS MADISONVILLE PEARSON PETERSEN SUNWATCH

Acceitory Itontal Forawn (♦} R 6/44 11.4 9/172 5 .2 0/11 0 18/129 14.6 4/66 6.1 0/11 0 7/51 13.7 L 4/47 8 .5 12/172 7 .0 0 /2 0 16/135 11.9 2/73 2 .7 0/11 0 4/51 7 .8 atterionlc otticist (+) R 18/35 50.0 57/124 46.0 0 /6 0 19/104 18.3 6/43 14.0 1/9 11,1 16/48 33.3 L 11/37 29.7 49/110 44.5 0 /6 0 21/101 20.8 8/44 18.2 2/9 22.2 18/66 32.1 Coronal Oaalclea (+) 25/37 67.6 32/83 38.6 12/14 85.7 2/122 1.6 22/36 61.1 6 /9 66.7 20/41 48.8 Foramen Huichke («■) R 14/47 29.8 36/205 17.6 5/13 38.5 12/122 9.8 13/85 15.3 2/10 20.0 9/51 17.6 L 14/50 28.0 38/201 18.9 4/15 26.7 19/122 15.6 14/85 16.4 4/9 44.4 9/53 17.0 Foramen Ovale (complete) R 30/30 100.0 83/83 100.0 7 /7 100.0 74/77 96.1 27/27 100.0 2 /2 100.0 34/37 91 .9 L 31/31 100.0 93/35 97.9 9/9 100.0 74/78 94.9 30/31 96.8 36/38 94 ,7 Foramen Splnoaun (complete) R 29/32 9 0.6 79/117 66.1 6 /7 85.7 61/70 87.1 21/29 7 2 .4 1/2 50.0 34/38 89.5 L 27/28 9 6.4 77/92 83.7 8/8 100.0 65/76 85.5 29/32 90.6 35/40 8 7 .5 Hypogloaaal Canal (double) R 6/39 15.4 28/143 19.6 1/17 5.9 9/77 11.7 3/51 5 .9 1/3 33.3 6/45 13.3 L 6/37 10.2 36/138 26.1 1/18 5.6 12/74 16.2 11/55 2 .0 0 /2 0 7/47 14.9 Lingula Bridge (+) R 9/45 20.0 2/131 1 .5 0 /14 0 0/129 0 0/44 0 2/8 25.0 1/50 2 .0 L 14/48 29 2 3/123 2 .4 0/16 0 0/131 0 0/48 0 1/7 14.3 2/51 3 .9 Haatold Foramen (ex eu tu ral) R 17/29 58.6 89/127 70.1 3/4 75.0 66/90 7 3 .3 36/52 6 9 .2 3 /8 37.1 36/46 76 .3 L 21/36 58.3 79/117 67.5 8/9 68.9 61/90 6 7 .8 27/44 61.4 4 /7 57.1 35/48 72 .9 Vylonyold Bridge (*) A 14/41 34.1 34/150 22.7 1/13 7.7 26/121 21.5 15/68 22.1 2/8 25.0 7/49 14.3 L 12/42 28.6 31/152 20.4 1/13 7 .7 24/123 10.5 12/61 19.7 1/7 14.3 7/50 14.0 Occipital Condyle (double) R 0/27 0 0/156 0 1/12 8 .3 0/89 0 3 /70 4 .3 #• 1/34 2 .9 L 1/37 2.7 1/128 0.8 0 /1 2 0 0 /90 0 5 /62 8.1 ** 2/35 5 .7 R 15/25 60.0 75/170 44.1 11/15 73.3 49/111 44.1 28/68 4 1 .2 4 /12 3 3.3 23/51 45.1 L 24/35 66.8 53/159 33.3 11/15 73.3 43/110 39.1 28/63 44.4 3/10 3 0 .0 19/51 37.3 p a r ie ta l eotcb Bene (*) R 6/34 23.5 8/118 6 .8 1 /7 14.3 10/102 9 .8 14/50 28.0 0 /8 0 7/49 14.3 L 13/33 3 9.4 10/109 9 .2 4 /9 44.4 9/102 8 .8 10/47 21.3 0/8 0 6 /50 12.0 Foatcondylar Canal (■>) R 17/23 7 3 .9 88/105 8 3.8 6 /9 6 6.7 62/67 9 2 .5 31/34 9 1 .2 2 /2 100.0 29/36 6 0.6 L 17/28 6 0 .7 86/99 86.9 10/13 76.9 61/69 88.4 26/30 86.7 2/2 100.0 30/35 65.7 precondylar Tubercle (*) 11/36 30.6 100/137 72.3 2 /1 6 13.3 49/86 57.0 18/42 42.9 0/1 0 22/46 47.8 Superior Sulcut (rlgnt) 17/43 3 9 .5 150/207 72.5 16/16 100.0 93/105 88.6 61/84 72.6 8/13 61.5 47/53 88.7 Supraorbital (notch) R 27/48 5 6.3 82/146 56.2 10/17 5 8 .8 72/124 58.1 32/59 54.2 2/6 33.3 31/50 62.0 L 27/48 5 6.3 78/129 60.5 14/18 7 7 .8 74/123 6 0 .2 45/62 72.6 2/4 50.0 34/50 6 8 .0

(* skeletal material was such that no observations whore made regarding the tra it in question.) TABLE 13. Summary of traits affected by lack of variation between sites, intercorrelation between traits, age, or sex.

TRAITS ANDERSON BUFFALO INDIAN HILLS MADISONVILLE PEARSON SUNWATCH

Accetvory Mantel rorasen (+)

Aitarionlc Oaalclea (+)

Coronal oaalclea (*) 17 16 15 Foramen Muacnke (+) 9 14 Foramen Ovale < co ^)lete)

Foramen Spinoaum (complete) 2 Hypogloaaal Canal (double) 17 Lingula Bridge (+)

9. Maatold Foramen (exautural) 4 10. Mylohyoid Bridge (+) 14 It. Occipital Condyle (double)

12. P a rie ta l Foremen {♦) 15 . P a rie ta l Notch Bone (■») 17 14. Poatcondyler Canal (*) IS 10,17 4 18. Precondylar Tubercle (♦) 14 16 3 ,1 0 ,1 6 10. Superior Sulcua (right) 3,15 15 17. Supraorbital (notch) 14 13

• Zndicatea no variation betaken the aemplea; numbera under the intercorralated colum indicate artilch trait(e) the given trait la/ere correlated with; algnlficant et P<0.05; end*= algnifleant at F<0.05.

VI 116 ossicles and hypoglossal canal configuration are correlated with age and th a t hypoglossal canal configuration and mastoid foramen location are correlated with sex in one or more samples. Asterionic ossicles and mastoid foramen thus were removed from fu rth e r consideration. Although, both age and sex correlations for the hypoglossal canal configuration were found to be significant at P= 0.05, th is t r a i t was retained because the r values just exceed the level of significance. The mean measure of divergence (MMD) (de Souza and Houghton 1977) and the H arpending/Jenkins’ (1973) distance (d®) were employed for assessing biological distance between samples for discrete traits. These distances were calculated using the frequencies of accessory mental foramen, hypoglossal canal, mylohyoid bridge, parietal foramen, parietal notch bone, and superior sulcus direction, which were shown to be independent traits. The Petersen site was not used in discrete trait distance analysis because of its small sample size. Table 14 presents the matrix of MMD values and Harpending/Jenkins’ d® values between samples. The MMD values and the Harpending/Jenkins’ d® values are highly correlated, r = 0.88 and thus contain virtually the same information. The Harpending/Jenkins’ d® was used in the remaining procedures because it is an Euclidean measure. 117 TABLE 14. Mean Measure of Divergence values between samples below the diagonal and Harpending/Jenkins’ d^ values between samples above diagonal.*

ANDERSON BUFFALO INDIAN HILLS MADISONVILLE PEARSON SUNWATCH

ANDERSON 0 .170 .373 .254 .124 .286

BUFFALO .122 0 .288 .049 .057 .050

INDIAN HILLS .574 .478 0 .199 .244 .176

MADISONVILLE .202 .018 .315 0 .078 .006

PEARSON .078 .033 .421 .048 0 .086

SUNWATCH .224 .021 .250 0 .059 0

Values derived from tra its shown to have variation among the samples studied and have no correlation between traits,tra age. or sex. These traits include: accessory mental foramen, * hypoglossal canal configuration,configurât! mylohyoid bridge, parietal foramen, parietal notch bone, and superior sulcus d ire c tio n .

TABLE 15. Summary of the 1®^ and 2® eigenvectors from the principal coordinate analysis for MMD values and Harpending/Jenkins d^ values.

SITE Harpending/ Geographic Km® Jenkins’ Values values ^ ST 2^ .jST 2*®

ANDERSON -.58343 -.51722 -.43642 -.38378 BUFFALO -.22324 .48327 -.82443 1.02280 INDIAN HILLS .71512 -.37019 .76201 -.04550 MADISONVILLE .06684 .41143 -.59114 -.54009 PEARSON -.26464 .08695 .63841 .17962 SUNWATCH .15432 .43018 -.26455 -.45207 118

THIRD

1.0 ■ PEARSON

0.5 BUFFALO iSUNWATCH ■ INDIAN HILLS ' iISONVILLE 0.0

0.5

ANDERSON 1.0 0.0 0.5 -0.5 0.0 SECOND -0.5 FIRST 1.0 . 1.0

FIGURE 6. Three dimensional map of the first three eigenvectors of a principal coordinate analysis for Harpending/Jenkins d^ values. 119 The first three eigenvectors of the principal coordinate analysis for Harpending/Jenkins’ d^ matrix (Table 15) were plotted to see how similar the sites were in reference to cranial discrete traits. Figure 6 reveals that Buffalo, Madisonville, and SunWatch cluster together, while the remaining sites (Anderson, Indian Hills, and Pearson) separate out as isolated entities. A visual comparison of the d® distribution and the distribution reveals few similarities. At first glance, the outcome appears to yield contradictory results, with metric data providing a different representation of biodistance than nonmetric data. However, these re s u lts are not unanticipated or c o n flic tin g since two different types of data are being considered in this analysis. Cranial measures and cranial discrete observations may segregate differently simply because of the independence of their genetic basis. Consequently, these results suggest the alleles that control metric appearance have little or no effect on the alleles that control nonmetric trait appearance. Again the principal coordinates technique was selected to best demonstrate the fit between biological distance and geographical distance (Figure 7). Using the matrix of Harpending/Jenkins’ d^ values the principal coordinates analysis provided the normalized eigenvectors of the matrix. As with the metric D^, the first two eigenvectors were 120

INDIAN HILLS ■•ANDERSON

/ PEARSON

BLTFALO

SUN\VAT(

./• madisonville

■ madisonville SUNWATCH /

• INDIAN HILLS g BUFFALO

FIGURE 7. Locations of the Harpending/Jenkins’ d* (•) and the geographic Km^ (■) after a Procrustes Rotation. 121 plotted after they were pivoted using Procrustes Rotation to best correspond with their geographic position. The geographic positions were arrived at in the same fashion described in the previous section on cranial metrics. The analyses of discrete traits resulted in an = 1.64. This value is smaller than the 1.89 R^ value obtained from the metric analysis, however this 1.64 value is relatively large making it unlikely that geographical distance between populations plays a role in patterning biological diversity. To test the association between the distance matrices, the permutation t e s t (Dietz 1983) was performed between the Harpending/Jenkins’ distance matrix and the geographic distance matrix and the temporal matrix. Using 720 permutations (based on 61), the observed Kendell correlation between the d® and Km^ m atrices was -4.0. The estim ated statistic surpassed the observed statistic 478 times, resulting in a P value = .6689. Again, this permutation test is unable to reject the hypothesis ofindependence between biological distance and geographical distance. The observed Kendell correlation between the d^ and the temporal m atrices a f te r using 720 perm utations was -17.0. The estimated statistic was greater than the observed statistic 712 times resulting in a P value = .9889. This test is unable to reject the hypothesis ofindependence between cranial discrete traits and time. Thus, cranial discrete variation between these Late Prehistoric 1 2 2 populations is not patterned by either geographic distances or temporal distances between populations.

Stature and Proportions

Table 16 contains the stature estimates for the seven samples calculated using the regression equations developed by Sciulli and associates (1990). These data show that significant sexual dimorphism exists for adult heights for a l l s ite s .

TABLE 16. Adult stature* arranged from shortest to tallest for both sexes by site.

â N X ± SO 9 N X ± SD PETERSEN 7 157.8 ± 2.7 PETERSEN 5 147.0 ± 7.2 MADISONVILLE 78 160.7 ± 7.1 MADISONVILLE 95 151.2 ± 6.8 INDIAN HILLS 26 163.8 ± 3.5 INDIAN HILLS 25 153.2 ± 4.1 ANDERSON 15 165.2 ± 6.9 SUNWATCH 30 153.7 ± 4.2 PEARSON 52 165.3 ± 5.3 BUFFALO 108 154.4 ± 4.1 BUFFALO 99 165.3 ± 6.0 PEARSON 52 154.5 ± 4.5 SUNWATCH 30 166.8 ± 4.4 ANDERSON 15 154.9 ± 4.6

* measures in centimeters.

In order to assess adult height in terms of population similarity, the homogeneity of the samples was tested. In a two-way analysis of variance, the F-values for adult height were significant for both site (Fg g^g = 11.6) and sex (F, gig = TABLE 17. Analysis of variance for adult height,

W ithout W ithout w ith o u t W ithout W ithout W ithout TEST A ll S ite s P e te rse n P e tersen P e tersen Petersen & Petersen & Petersen & 5+9 5 9 Madisonville Madisonville Madisonville 5+9 5 9 Pooled variance

S ite F,.,,,= 11.6 F;.ao«- 11.1 Fs,2M- 7 .7 F».3h“ 3 .9 F«.437- 0 .9 F4.217" 1 • 3 F4.220" 3 .4

Sex 239.4 Fi.ooe” 338.6 Fi .«7= 315.5 Interaction 0 .7 Fj.mb” 0 .9 F,.,37= 0 .6

Welch F ia.ir“ 49.2 Fti.i«= 59.4 F,.B,= 6 .7 Fs.7«- 3 .2 F».ioo“ 58.5 F4.32- 2 .0 F4.M- 3 .6

Brown-Forsythe

S ite F.,.7= 11.5 Fs.ioa” 6.9 Fs.im” 8 .6 Fs.213" 3 • 2 F,.k,= 1 .2 F4.78” 1 • 1 F4.12»“ 3.5 Sex F |.« = 312.7 F|,toe= 443.8 F ^ w = 367.7

Interaction F.,.7= 0 .6 Fs.,m= 0 .8 F«,m= 0 .7

Levene’ s

S ite F«.«(a~ 4 .7 Fs.k»" 5 .5 F 2.9 Fs.314® 3 .3 F«,437- 4 .4 F4.217- 2 .7 F4.220” 2 .9

Sex F,.„>= 0.1 F|.«(»“ 2 .5 F i .437= 2 .8

Interaction F«.«tt“ 0 .9 Fj.iot* 0 .7 F4.437= 1.1

8 124 239.5). These F-values reject the hypothesis the samples have been drawn from the same parent population. The test of the samples was repeated without the Petersen sample due to i t ’s low sample size. The variance between the samples was s till significant for site (Fs^eos = 11.1) and sex (Fi ^g = 338.6). However, i t was noted th a t the most divergent d ifferen ce in s ta tu re was the Madisonville sample and that the Madisonville sample was shorter, on average than any of the remaining samples. The te s t was repeated without both the Petersen and M adisonville samples. Without Petersen and Madisonville there were no significant differences for site (F^ = 0.9), but sex differences were significant (F^ ^gy = 315.5). The results obtained in all the analyses of variance appear in Table 17. Overall, it appears adult height (as a measure of size) is variable among the study samples. Differences between the samples are evident when Madisonville and Petersen is included, however there are no differences when these two samples are removed from the an aly sis. Thus size appears to be le s s sta b le fo r both c ra n ia l and p o stcran ial data fo r these late Prehistoric populations. Adult proportions were assessed in order to establish i f p o stcran ial shape is homogeneous as is the c ra n ia l shape for the samples. Table 18 contains the average measures of each element of the body needed to obtain a skeletal height, plus the average skeletal height by sex and by site (only TABLE 18. Adult Stature proportions by sex.

s E SITE SKULL HEIGHT VERTEBRAL COLUMN BICONOYLAR FEMUR STANDARD TIBIA FOOT HEIGHT SKELETAL X HEIGHT

H XS %X S %XS % XS %XS%X

ANDERSON 8 14.5 0.72 9.3 51.0 2.71 32.7 46.0 2.46 29.4 38.5 1.98 24.6 6.1 0.32 4 .0 156.2 BUFFALO 7 14.0 0.71 9.2 50.0 1.20 32.6 45.2 2.53 29.5 37.8 2.93 24.7 6.1 0.18 4 .0 153.3 e MADISONVILLE 3 14.1 - 9 .6 49.2 - 33.4 42.7 - 29.0 35.2 - 23.9 6.0 - 4.1 147.2 PEARSON 12 14.1 0.3B 9.2 50.7 3.13 33.2 44.4 1.87 29.6 38.0 1.71 25.5 . 5.8 0.33 3.8 152.9 SUNWATCH 18 14.6 0.43 9.3 51.9 3.31 32.9 46.1 2.02 29.3 38.3 1.86 24.3 6 .5 0.36 4.1 157.1

ANDERSON 4 14.0 - 9 .6 47.7 - 32.9 43.0 - 29.6 35.1 - 24.2 5 .6 - 3 .9 145.3 BUFFALO 6 13.7 0.55 9.2 49.9 2.71 33.4 44.4 1.17 29.7 35.9 1.63 24.0 5.6 0.40 3.7 149.5 9 MADISONVILLE 4 13.7 - 9.4 49.3 - 33.9 42.3 - 29.1 34.4 - 23.7 5 .7 - 3 .9 145.4 PEARSON 13 13.5 0.35 9.4 46.4 2.10 32.9 41.2 1.60 29.5 35.3 1.51 24.5 5.3 0.36 3 .9 144.3 SUNWATCH 10 13.8 0.43 9.5 48.1 2.44 33.2 42.1 1.71 29.1 35.1 1.43 24.2 5.6 0.33 3 .9 144.7

tVJ Ü 1 126 sites with a large enough sample size). This table provides data from only individuals which possessed every element necessary to obtain a complete skeletal height. The skeletal heights very among and between the samples, which is not surprising since size differences in stature have already been shown for the samples. Noteworthy is the fact that little or no difference is detected when a comparison of the percentages of each of the elements for skeletal height by sex is made for the samples. Adult height proportions are virtually identical, so it appears shape in the postcranial elements also maintains a certain amount of stability through time. These appear to be no shape differences these Late Prehistoric populations for either cranial or postcranial elements. Since stature is affected by both biological and environmental factors, in order to understand stature expression in populations, biological relatedness must first be established between the samples under investigation. The analyses of variance for the metric data revealed homogeneity between the samples for shape, thus it would appear to allow the biological control needed to interpret adult s ta tu re . However, the re s u lts obtained in the analyses of cra n ia l and p o stcran ial size and c ra n ia l discrete traits revealed variation among and between samples for these features suggesting that a degree of biological diversity exists for the samples. 127 Assuming th a t th ere is an in h e rita b le property to the appearance of shape, size, and discrete traits, then the c ra n ia l data provides a number of in te rp re ta tiv e approaches by which to assess adult height. The cranial data from the Late Prehistoric samples of this study show that: 1) cranial shape is being held constant through time for the Late Prehistoric populations; 2) geographic location of samples does not explain differences in the size and discrete trait distribution of the cranium; 3) cranial size is experiencing a small, but noticeable change through time; and 4) discrete traits distribution has no recognizable pattern. The postcranial data from these samples show the same patterns for size and shape diversity as does the cranial data - shape is constant, but size is less constant for all samples. The variation in cranial and to a certain degree postcranial size, may represent a microevolutionary response to some environmental or biocultural stress. Both shape and size are the result of a complex of interacting environmental forces and the products of several genes. However, size parameters would be more lik e ly to be fle x ib le in response to environmental forces as opposed to shape parameters. A g re a te r number of fo rces e ffe c t size than effects shape. For example, in terms of pressures, shape variation is most often associated with climate, while size is associated with many stresses: nutrition, disease, 128 socioeconomic status. Discrete traits variation also may be reflecting similar responses to environmental pressures. The variation observed in adult postcranial size (e.g., stature) most probably can be explained by extrinsic environmental forces. Hence, adult height would best be utilized in appraising the environment's effect upon the different samples. The results of stature analysis will be discussed in terms of biocultural stress in the final chapter.

Biocultural Stress Indicators

This section first will examine the results of the analysis of dental pathologies (abscesses, attrition, dental caries, and tooth loss) as stress indicators. Next, results from the subadults growth analyses will be supplied.

Dental Pathologies

Tables 19 through 30 have a general summary of dental pathologies of the permanent dentition for caries by wear category, AMTL, PMTL, and abscess. The distribution of pathologies in these tables are by sample, jaw, and tooth class. In Tables 31 through 35 caries distribution by age is provided, while in Tables 36-41 caries distribution by location is furnished. Petersen and Indian Hills were eliminated from this portion of the analysis because of low sample size. Samples 129 TABLE 19. Summary of Anderson maxillary permanent dental pathology by tooth type.

ANDERSON WEAR AMTL PMTL ABSCESS LOCI «AXILLARY 2 3-4 5-6 7-8 TOTAL

I’ # of teeth 11 36 15 11 73 15 12 2 100 c ario u s 0 0 0 0 0 I' # o f te e th 16 33 18 10 77 10 12 c ario u s 0 0 0 2 2 c * of teeth 9 33 18 10 85 7 3 6 98 c ario u s 0 2 2 4 8 p’ # of te e th 25 29 14 4 72 14 cario u s 1 4 2 3 10 p* # of teeth 32 32 14 1 79 11 2 93 cario u s 1 4 2 0 7 H< # of teeth 17 42 6 4 69 17 13 90 ca rio u s 2 13 2 2 18 II* # o f te e th 42 17 4 3 66 14 2 8 83 ca rio u s 9 3 4 1 17 M* # o f te e th 36 11 3 0 50 14 70 cario u s 2 3 4 1 5 T # o f te e th 0 188 242 97 44 571 102 41 37 730 A 15 29 12 16 67 L c ario u s 130 TABLE 20. Summary of Anderson mandibular permanent dental pathology by tooth type.

ANDERSON WEAR AMTL PMTL ABSCESS LOCI MANDIBULAR 2 3-4 5-6 7-8 TOTAL

I, # O f te e th a 31 12 13 64 11 19 3 96 cario u s 0 0 0 0 0 h # of teeth 11 33 13 14 71 5 16 95 c ario u s 0 1 1 1 3 C # o f te e th 6 36 25 10 77 4 8 4 93 c ario u s 0 1 0 1 2

P, # o f te e th 23 38 18 4 83 6 0 94 cario u s 3 1 1 0 5

P, # o f te e th 27 41 4 1 73 13 4 5 93 cario u s 1 7 2 0 10

", # o f te e th 11 32 10 4 57 35 14 98 ca rio u s 4 10 2 1 17 u. # o f te e th 28 13 5 3 49 41 0 2 94 ca rio u s 5 4 1 0 10

", # of teeth 36 13 2 1 52 29 0 2 83 ca rio u s 7 2 0 0 9 T # o f te e th 150 237 89 50 526 0 144 49 34 745 A 20 26 7 3 56 L c ario u s 131 TABLE 21 Summary of Buffalo maxillary permanent dental pathology by tooth type.

BUFFALO WEAR AHTL PHTL ABSCESS LOCI MAXILLARY 2 3 4 5-6 7-8 TOTAL

I' # O f te e th 9 140 54 9 212 52 100 18 308 cario u s 3 29 5 1 38 I* # o f te e th 19 134 40 4 197 39 112 13 cario u s 1 20 10 0 31 C # o f te e th 22 199 47 8 276 28 76 14 317 c ario u s 5 24 15 4 48 P’ # o f te e th 100 146 20 1 267 43 46 20 319 ca rio u s 20 39 13 0 72 P* # o f te e th 136 120 12 1 269 50 35 15 314 c ario u s 26 36 4 1 67 H' # o f te e th 118 157 5 1 261 70 16 44 311 ca rio u s 27 69 4 0 100 If # of te e th 203 61 2 1 267 60 14 22 276 cario u s 61 25 1 1 88

If # o f te e th 134 27 2 1 164 61 41 cario u s 40 11 0 1 52 T « o f te e th 741 984 182 26 1933 0 403 443 163 2371 A c ario u s 183 253 52 a 496 L 132 TABLE 22. Summary of Buffalo mandibular permanent dental pathology by tooth type.

BUFFALO WEAF AUTL PMTL ABSCESS LOCI MANDIBULAR 2 3-4 5-6 7-8 TOTAL

1 , # Of te e th IB 156 50 20 244 46 183 6 425 cario u s 0 9 5 1 15 h # of teeth 20 196 28 16 260 29 183 8 426 cario u s 0 10 3 3 16

C # of teeth 13 229 59 9 310 28 131 16 431 cario u s 1 26 12 3 42

P, # of teeth 94 208 127 6 435 54 90 16 440 c ario u s 8 45 11 3 67

P, # of teeth 139 126 16 6 287 78 103 27 442 c ario u s 23 46 8 2 79

M, # o f te e th 54 163 9 2 228 238 28 46 475 cario u s 21 91 3 0 115

M, # of teeth 131 70 4 0 205 230 37 24 452 cario u s 48 36 2 0 86

", # o f te e th 111 47 3 0 161 188 47 19 393 c ario u s 32 26 0 0 58 T # of teeth 580 1195 296 59 0 2130 T 891 808 162 3484 A 133 L cario u s 289 44 12 478 133 TABLE 23. Summary of Indian Hills maxillary permanent dental pathology by tooth type.

I»IDIAN HILLS WEAf AHTL PMTL ABSCESS LOCI yiAXILLARY 2 3-4 5-6 7-8 TOTAL

I’ # of teeth 1 9 2 0 12 44 54 c ario u s 0 0 0 0 0 I‘ # of teeth 1 13 1 0 15 3 46 c ario u s 0 0 0 0 0 c # o f te e th 3 19 5 0 27 2 34 2 55 c ario u s 0 0 0 0 0 p* # of te e th 10 17 4 0 31 28 c a rio u s 1 1 2 0 4 p’ # o f te e th 17 15 4 0 36 21 57 c a rio u s 2 2 2 0 6 M* # o f te e th 20 31 3 0 54 12 10 52 c ario u s 1 5 0 0 8

If # o f te e th 21 10 0 0 31 7 9 41 c ario u s 2 4 0 0 6

II* # o f te e th 19 2 0 0 0 3 9 1 c ario u s 1 0 0 0 0 T # o f te e th 92 116 19 0 227 0 37 201 22 395 A 7 12 4 0 L ca rio u s 23 134 TABLE 24. Summary of Indian Hills mandibular permanent dental pathology by tooth type.

I»DIAN HILLS WEAI AHTL PMTL ABSCESS LOCI MANDIBULAR 2 3-4 5-6 7-8 TOTAL

I| # o f te e th 2 6 9 0 17 5 49 3 68 c a rio u s 0 0 0 0 0 " h # o f te e th 3 15 5 0 23 3 43 3 65 c ario u s 0 0 0 0 0 c # of teeth 2 17 7 1 27 1 41 1 66 c ario u s 0 0 2 1 3

p. # o f te e th 9 14 1 0 24 7 33 5 62 ca rio u s 1 2 0 0 3

p. # o f te e th 7 19 0 1 27 11 24 5 36 ca rio u s 0 1 0 0 1

M, # o f te e th 12 29 4 0 45 18 6 6 58 cario u s 0 6 1 0 7

«2 # o f te e th 22 14 0 0 36 20 6 6 57 c ario u s 6 0 0 0 6

«2 # of teeth 13 5 0 0 18 19 13 4 46 c ario u s 3 0 0 0 3 T # o f te e th 70 119 26 2 217 0 T 84 215 33 478 A 10 9 3 1 23 L cario u s 135 TABLE 25. Summary of Madisonville maxillary permanent dental pathology by tooth type.

wU3IS0NVILLE WEAI AUTL PHTL ABSCESS LOCI MAXILLARY 2 3-4 5-6 7-8 TOTAL

I' # of teeth 3 33 49 6 91 12 160 3 252 cario u s 0 3 4 0 7 I» # o f te e th 7 60 33 6 106 16 139 3 256 cario u s 0 3 2 0 5 c # of teeth 10 86 49 3 148 6 115 10 263 c ario u s 0 3 8 0 11

p ' # of te e th 50 94 17 3 164 18 80 16 262 c ario u s 4 15 6 0 25

p’ # o f te e th 75 80 12 2 169 23 70 16 265 c ario u s 5 17 3 0 25 u' # o f te e th 58 151 23 5 237 28 18 19 270 c ario u s 11 32 7 2 52

I f # of te e th 116 60 3 1 180 34 37 14 251 cario u s 17 11 0 1 29 H* # o f te e th 77 10 1 0 88 35 93 18 215 c ario u s 16 1 0 0 17 T # o f te e th 396 574 187 26 1183 0 174 712 99 2034 A 53 85 30 3 171 L c ario u s 136 TABLE 26. Summary of Madisonville mandibular permanent dental pathology tooth type.

w U3IS0NVILLE WEAI1 AUTL PHTL ABSCESS LOCI MANDIBULAR 2 3-4 5-6 7-8 TOTAL

Ï, # O f te e th 1 73 47 11 132 8 189 2 332 c ario u s 0 0 0 0 0

I, # o f te e th 10 91 50 12 163 6 160 5 327 c ario u s 0 1 2 2 5 C # o f te e th 7 112 52 7 178 4 146 0 324 c ario u s 0 3 3 0 6

P» # o f te e th 52 137 22 3 214 12 104 5 328 c ario u s 1 13 6 0 20

P, # o f te e th 59 105 8 2 174 34 86 14 326 c ario u s 9 21 2 0 32

«1 # o f te e th 47 138 22 0 207 115 22 35 336 ca rio u s 11 39 5 0 55

", # o f te e th 81 90 11 0 182 103 42 18 323 c ario u s 24 26 5 0 55

", # o f te e th 95 43 1 0 182 75 55 14 268 c ario u s 32 16 0 0 48 T # o f te e th 352 789 213 35 1389 0 357 804 83 2554 A 77 119 23 2 L c a rio u s 221 137 TABLE 27. Summary of Pearson maxillary permanent dental pathology by tooth type.

PEARSON WEAF AUTL PMTL ABSCESS LOCI MAXIllAHY 2 3-4 5-6 7-8 TOTAL

I’ # O f teeth 23 81 30 11 145 37 51 4 224 c ario u s 0 4 1 1 6 I' # o f te e th 33 77 28 145 33 43 2 209 c ario u s 0 5 6 0 11

C # o f te e th 23 90 27 10 150 30 30 15 209 cario u s 1 7 8 2 18 P® » o f te e th 57 79 12 3 151 36 25 210 cario u s 3 15 6 1 25 P* # of te e th 69 61 13 5 148 38 22 16 206 c ario u s 6 17 4 4 31

M' # of te e th 61 98 18 1 178 48 15 16 229 c ario u s 6 25 8 0 39

II* # of teeth 94 45 7 2 148 47 17 12 199 c ario u s 16 19 0 0 35

H’ # of teeth 84 30 2 0 116 43 11 17 152 c ario u s 21 11 0 0 32 T * of teeth 444 561 137 39 1181 0 307 214 85 1638 A 53 103 33 L cario u s 8 197 138 TABLE 28. Summary of Pearson mandibular permanent dental pathology by tooth type.

PEARSON WEAR AUTL PUTL ABSCESS LOCI MlANDIBULAR 2 3-4 5-6 7-8 TOTAL

I, # o f te e th 17 84 23 20 144 50 70 3 255 c a rio u s 0 2 2 0 4

Is # o f te e th 22 91 23 20 156 29 74 11 255 c ario u s 0 2 1 1 4

C # o f te e th 21 89 64 18 192 15 58 8 256 cario u s 0 4 11 1 16

P. # o f te e th 54 103 34 7 198 27 37 9 254 c ario u s 1 16 4 0 21

P4 # of te e th 74 78 24 4 180 45 28 6 256 c ario u s 7 15 4 1 27

«. # o f te e th 47 119 21 2 189 102 5 21 290 c a rio u s 4 26 8 2 40

“s # of teeth 84 67 7 1 159 101 10 15 270 c a rio u s 16 21 2 0 39

Ms # of teeth 78 41 4 0 123 91 11 219 c ario u s 16 21 1 0 23

T # of teeth 397 672 200 72 1341 0 460 293 74 2055 A 36 100 174 L ca rio u s 33 5 139 TABLE 29. Summary of SunWatch maxillary permanent dental pathology by tooth type.

SUNWATCH WEAI AHTL PHTL ABSCESS LOCI MAXILLARY 2 3 4 5-6 7-8 TOTAL

I ' # Of te e th 8 59 90 70 83 32 10 6 123 cario u s 0 2 2 0 4

I* # of te e th 17 54 t 2 2 85 22 13 119 c ario u s 0 2 1 0 3

C # of te e th 10 51 15 8 84 19 11 10 116 c ario u s 1 3 1 5 10 P» # o f te e th 21 44 6 5 76 26 7 10 114 cario u s 6 8 1 0 15

P* # of te e th 31 39 7 2 79 24 108 c ario u s 5 17 1 0 17

H' # of te e th 26 41 9 2 78 30 22 116 ca rio u s 8 14 5 0 27

H‘ * of teeth 48 26 0 0 74 26 15 105 c ario u s 6 6 0 0 12

H’ # of teeth 33 13 0 0 46 13 5 9 62 c ario u s 7 4 0 0 11 T # of teeth 194 327 58 26 60S 0 196 55 81 863 A 33 50 11 5 99 L c ario u s 140 TABLE 30. Summary of SunWatch mandibular permanent dental pathology by tooth type.

SUNWATCH WEAR AUTL PUTL ABSCESS LOCI MANDIBULAR 2 3-4 5-6 7-8 TOTAL

I. # o f te e th 6 62 3 10 81 27 14 2 123 c ario u s 0 1 0 0 1

I» # of teeth 9 61 6 14 90 18 15 c ario u s 0 1 1 1 3 C # o f te e th 5 65 13 4 87 8 12 118 ca rio u s 0 5 4 1 10

P, # o f te e th 13 69 11 3 96 5 14 117 c a rio u s 0 6 3 1 10

P4 # o f te e th 27 46 6 1 80 18 15 115 c ario u s 3 5 1 0 9 H, # o f te e th 16 42 10 4 72 42 12 123 c ario u s 6 19 4 1 30

# of teeth 33 25 3 0 61 46 2 111 c a rio u s 9 10 2 0 21 # o f te e th 32 8 1 0 41 28 84 c a rio u s S 5 1 0 11

T # o f te e th 141 378 53 36 608 0 192 77 45 914 A 23 52 16 4 95 L c a rio u s TABLE 31. Summary of Anderson permanent dental caries pathology by age and by tooth type.

ANDERSON Maxillary Mandibular p3 p . I' I' C M' II* M* I, I. C P, P, M, H. M, i 18-20 21-30 1 3 1 0 5 3 1 1 1 4 2 3 3 31-40 1 1 1 1 1 2 41-50 +50 ■ ■ ■ subtotals 0/24 0/27 1/30 4/25 2/29 9/24 5/24 3 /18 1/25 2/24 1/26 2/28 6/27 2/18 3/22 3/20 ? 18-20 1 2 21-30 2 2 1 31-40 2 2 1 2 1 2 41-50 1 1 1 2 2 1 +50 1 1 1 1 1 ■ ■ ■ ■ s u b to ta ls 0 /1 2 0/13 1/15 0/14 2/14 4/11 6/13 0 /1 2 0 /1 2 1/15 0/13 0/18 1/17 8/13 4/8 4/13 Sex ? 18-20 21-30 31-40 41-50 +50 ■ s u b to ta ls 0 /0 0 /0 0 /0 0 /0 0/0 0/0 0/0 0/0 0 /0 0 /0 0 /0 0 /0 0 /0 0 /0 0 /0 0 /0 S ubadult 6-18 0/14 0/13 0/11 0 /1 0 0 /1 0 1/14 0 /1 0 0/1 0 /1 2 0/11 0 /8 0 /8 0 /8 1 /1 2 2 /8 0/3

TOTALS 0/50 0/53 2/56 4/49 4/53 14/49 11/47 3/31 1/49 3 /5 0 1/47 2/54 7/52 11/43 9/38 7/35 TABLE 32. Summary of Buffalo permanent dental caries pathology by age and by tooth type,

BUFFALO Maxillary Mandibular

I'I'C P’ P‘ M' W’ I, I, C P,P4 «, M, i 18-20 2 1 1 3 2 1 1 21-30 5 4 2 6 8 10 7 5 1 a 15 9 9 31-40 3 4 8 10 13 15 12 7 1 2 6 9 13 11 10 11 41-50 1 3 2 2 1 2 2 1 1 4 6 2 3 1 +50 2 1 1 1 s u b to ta ls 10/51 9/54 10/69 2 2 /6 6 25/69 30/62 30/54 14/36 4/64 4/68 7/85 14/89 29/75 29/52 22/42 22/48 9 18-20 1 1 1 1 5 7 1 21-30 8 5 5 9 7 18 15 9 1 1 7 7 9 22 14 13 31-40 11 6 12 11 8 12 11 5 2 3 10 13 8 9 9 10 41-50 2 1 3 3 4 7 9 1 1 1 4 5 4 4 2 2 +50 1 1 1 ■ ■ ■ ■ subtotals 21/73 12/62 22/93 24/92 19/88 37/86 37/93 15/52 4/71 5 /90 21/104 25/110 21/69 41/66 32/69 26/59 Sex 7 18-20 1 1 1 1 1 5 4 21-30 2 3 2 3 1 1 1 1 1 31-40 2 1 2 1 2 1 1 2 1 41-50 +50 1 1 1 - 1 s u b to ta ls 3/15 1/14 0 /1 2 3 /17 6 /2 0 5/18 6 /2 0 2/16 0 /1 2 1/11 1/19 2 /2 2 0/18 8/16 5/13 3/13 S ubadult 6-18 1/26 1/23 2/24 2/23 0 /2 2 3/57 1/26 1/26 1/34 0/32 0/26 0/26 2/27 15/56 8/26 0 /3

TOTALS 35/165 23/153 34/198 51/200 50/199 75/223 74/193 31/130 9/181 10/201 29/234 41/247 52/189 93/190 67/150 51/123

-u to TABLE 33. Summary of Madisonville permanent dental caries pathology by age and by tooth type.

MADISONVILLE Maxillary Mandibular

18 20 21-30 31-40 41-50 +50 s u b to ta ls 1/15 0/0 4/24 6/31 7/30 7/34 9/31 3/17 0/23 4/28 4 /32 3/34 2/32 6/28 6/26 7/25

18-20 21-30 31-40 41-50 +50 subtotals 3/25 3/28 3/41 6/42 7/48 20/53 8/43 9/25 0/32 1/42 1/44 6/51 9/53 15/38 11/35 16/33 Sex ? 18-20 21-30 31-40 41-50 +50 s u b to ta ls 0/2 0/3 0/40/3 0/4 2/4 2/4 1/3 0/1 0/4 0/4 0/4 1/4 0/0 4 /4 1/3 Subadult 6-18 0/9 0 /5 0/11 1/12 0/11 2/36 2/16 0/1 0/12 0/19 0/16 0/23 1/23 10/46 11/24 0/2

TOTALS 4/51 3/36 7/79 13/89 14/93 31/127 21/94 13/46 0/78 5/93 5/96 9/112 13/112 31/112 32/89 24/63

- b 0» TABLE 34. Summary of Pearson permanent dental caries pathology by age and by tooth type.

PEARSON Maxillary

18-20 21-30 31-40 13 41-50 +50 s u b to ta ls 3/44 4/47 10/54 13/60 12/58 14/58 18/55 17/55 2/51 2/54 10/75 9/75 12/62 16/56 10/50 7/45

18-20 21-30 31-40 13 41-50 +50 s u b to ta ls 3/47 6/52 7/62 11/54 17/61 21 /54 17/53 14/50 2/37 2/49 6/69 10/78 13/71 12/57 23/65 15/64 Sex 7 18-20 21-30 31-40 41-50 +50 s u b to ta ls 0/6 1/8 1/7 0/8 1/7 3 /10 1/7 1/8 0/7 0/8 0/13 1/13 1/13 1/11 2 /8 1/10 S ubadult 6-18 0/48 0/41 0/36 1/38 1/36 1/61 1/39 0/4 0/50 0/47 1/390/37 1/42 11/70 4/43 0/8

TOTALS 6/145 11/148 18/159 25/160 31/162 39/183 35/154 32/117 4/145 4/158 16/194 21/205 27/188 40/194 39/166 23/127 TABLE 35. Summary of SunWatch permanent dental caries pathology by age and by tooth type.

SUNWATCH Maxillary Mandibular pS p4 I ' I" C M' H» H’ I, I, 0 P. P, M, ", a 18-20 21-30 1 31-40 1 2 4 8 12 5 4 1 2 2 9 8 6 41-50 6 3 3 3 4 4 1 3 3 5 4 3 +50 1 2 1 1 1 ■ ■ ■ subtotals 1/34 3/41 8/46 7/42 11/43 16/35 9/32 8/21 0/32 2/39 5/46 2/44 5/36 15/35 12/28 9/35 9 18-20 21-30 - - - 1 2 -_ .. 4 1 31-40 1 - 2 1 2 4 3 2 1 4 7 3 2 2 2 41-50 1 2 1 1 1 1 1 2 1 2 2 +50 ■ ‘ ■ ■ ■ ■ subtotals 1/27 0/26 2/27 3/27 6/31 5/25 4/28 3/22 1/26 1/29 5/35 9/37 4/30 8/19 5/20 2/20 sex 7 18-20 21-30 _ _ 31-40 41-50 +50 -- s u b to ta ls 0 /0 0 /0 0 /0 0 /0 0 /0 0 /0 0 /0 0 /0 0 /0 0 /0 0 /0 0 /0 0 /0 0 /0 0 /0 0 /0 S ubadult 6-18 0/18 0/18 0/13 5/14 0/10 2/23 0/14 1/3 0/20 0/19 0/14 0/12 0/12 8/26 4/17 0 /3

TOTALS 2/45 3/85 10/86 15/83 17/84 23/83 13/74 12/46 1/78 3/87 10/95 11/93 9/78 31/80 21/65 11/58

A cn TABLE 36. Anderson distribution of carious lesions by tooth by tooth surface and tooth type.

ANDERSON MAXILLARY MANDIBULAR TYPE CROWN ROOT ROT N=2 N=3 TOTAL TYPE CROWN ROOT ROT N=2 N=3 TOTAL

I ' 0 0 0 0 0 0 I, 0 0 1 0 0 1 I* 1 0 1 0 0 2 I, 0 0 3 0 0 3 C 2 0 4 2 0 8 C 0 0 2 0 0 2 P’ 2 1 5 2 0 10 P. 1 2 2 0 0 5 P‘ 2 3 1 1 0 7 P. 3 3 3 1 0 10 M' 6 6 5 3 0 20 M, 7 4 4 2 0 17 5 3 1 2 0 11 M, 4 1 1 3 0 9 M’ 0 3 0 0 0 3 M, 5 0 0 2 0 7

o> TABLE 37. Buffalo distribution of carious lesions by tooth by tooth surface and tooth type,

BUFFALO MAXILLARY MANDIBULAR TYPE CROWN ROOT ROT N=2 N=3 TOTAL TYPE CROWN ROOT ROT N=2 N=3 TOTAL

I ’ 16 6 10 6 0 38 6 9 0 0 0 15 I ' 12 7 11 1 0 31 h 6 8 2 0 0 16 C 19 18 7 4 0 48 C 17 18 3 4 1 43 P’ 25 25 14 8 0 72 P. 22 28 8 8 1 67 P* 22 24 17 4 2 69 P, 23 40 12 4 0 79 M' 38 30 15 17 3 103 M, 62 17 14 22 2 117 M' 24 19 6 12 3 64 M, 37 8 9 11 2 67 M' 15 9 1 6 0 31 M, 32 2 7 9 1 51 TABLE 38. Indian Hills distribution of carious lesions by tooth by tooth surface and tooth type.

INDIAN HILLS MAXILLARY MANDIBULAR TYPE CROWN ROOT ROT N=Z N=3 TOTAL TYPE CROWN ROOT ROT N=2 N=3 TOTAL

I ’ 0 0 0 0 0 0 I, 0 0 0 0 0 0 I* 0 0 0 0 0 0 h 0 0 0 0 0 0 C 0 0 2 0 0 2 0 0 3 0 0 0 3 P' 1 1 3 1 1 7 P. 0 0 2 0 0 2 P* 1 5 4 0 0 10 P4 0 0 0 1 0 1 M' 5 0 0 1 0 6 «1, 3 2 1 1 0 7 M' 0 0 0 0 0 0 M, 0 0 0 0 0 0 If 0 0 0 0 0 0 M, 0 0 0 0 0 0 TABLE 39. Madisonville distribution of carious lesions by tooth by tooth surface and tooth type.

MADISONVILLE MAXILLARY MANDIBULAR TYPE CROWN ROOT ROT N=2 N=3 TOTAL TYPE CROWN ROOT ROT N=2 N=3 TOTAL

I' 6 0 0 0 0 6 I. 0 0 0 0 0 0 I ' 3 0 0 2 0 5 I. 2 2 1 0 0 5 C 4 4 2 1 0 11 C 3 3 0 0 0 6 P' 3 9 6 4 1 23 P, 4 11 3 2 0 20 P* 3 13 8 1 1 26 P. 4 18 6 4 2 34 U' 12 19 3 18 2 54 M, 23 18 4 10 3 58 M' 6 7 4 3 1 21 M, 16 7 1 4 4 32 N' 9 4 0 0 0 13 M, 16 3 2 1 2 24

(O TABLE 40. Pearson distribution of carious lesions by tooth by tooth surface and tooth type.

PEARSON MAXILLAHY MANDIBULAR TYPE CROWN HOOT ROT N=2 N=3 TOTAL TYPE CROWN ROOT ROT N=2 N=3 TOTAL

I ’ 3 3 0 0 0 6 I, 1 2 1 0 0 4 I' 1 7 3 0 0 11 I, 0 2 2 0 0 4 C 1 8 9 0 0 18 0 2 10 2 2 0 16 P' 5 12 a 0 0 25 P. 4 11 6 0 0 21 P* 6 9 15 1 0 31 P. 5 11 8 3 0 27 M’ 10 19 6 4 0 39 M, 11 18 5 5 1 40 M' 4 18 7 6 0 35 M, 8 17 8 6 0 39 If a 19 2 3 0 32 M, 8 11 4 0 0 23 TABLE 41. SunWatch distribution of carious lesions by tooth by tooth surface and tooth type.

SUNWATCH MAXILLARY MANDIBULAR TYPE CROWN ROOT ROT N=2 N=3 TOTAL TYPE CROWN ROOT ROT N=2 TOTAL

10 15 10

27 10 10 30

oi 152 from Anderson and SunWatch were combined fo r the indices analysis, to insure adequate sample representation for the different age classes. The merging of these samples is believed to be valid because these sites are temporally and geographically similar and the summary of dental pathology appears to be comparable. The previous D® analysis for cranial metrics also clusters these sites relatively close to each other. To better address dental disease with a shift in subsistence an Archaic sample was added to the analysis. Observations of dental pathologies on this sample were made by Paul Sciulli (1992). The Archaic sample represent prepottery, hunting-gathering-fishing groups in Ohio. Table 42 contains the age distributions of individuals for the Total Caries Index and Table 43 contains the age distribution of individuals for the Disease Index. In these ta b le s N is the number of in d iv id u als, 0% is the cumulative percent. Mean is the average age in years, and Variance is the variance in years^. The samples are arranged from left to right in a temporal fashion, with the Archaic representing the earliest sample and Madisonville representing the most recent sample. The mean age of males and females varied from site to site for the six samples with the mean age observed between th e samples averaging between 26 and 30 years of age. Using the Kolmogorov-Smirnov test. Table 44 indicates that pair- 153 TABLE 42. Age distribution for Total Caries index*.

Age ARCHAIC ANDERSON PEARSON BUFFALO MADISONVILLE Class and (years) SUNWATCH N C% N 1 C% N C% N C% N 1 e t 6-10 0 90.6 3 96.2 2 97.9 2 98.2 3 95.0 11-15 6 84.4 8 86.2 13 84.5 7 92.1 5 86.7 16-20 e 76.0 8 76.2 13 71.1 17 77.2 8 73.3 21-25 15 60.4 12 61.2 17 53.6 19 60.5 5 65.0 26-30 16 43.8 8 51.2 11 42.3 15 47.4 8 51.7 31-35 16 27.1 16 31.2 17 24.7 21 28.9 16 25.0 36-40 18 8.3 11 17.5 16 8.2 22 9.6 7 13.3 41-45 6 2.1 5 11.2 4 4.1 6 4.4 5 5.0 46-50 2 0.0 6 3.8 4 0.0 1 3.5 3 0.0 50+ 0 0.0 3 0.0 0 0.0 4 0.0 0 0.0 TOTAL 96 80 97 114 60 MEAN 27.8 29.9 27.0 29.2 28.7 VARIANCE 108.9 135. 1 103.8 99.2 112.4

* m - Mb.r .f IMlvUMl.. C\ • ....lâtlV. BMi - .g. i. yMr*. ... V .rU iw . - v irto M t lu yMr«*.

TABLE 4 3 .

Age d istrib u tio n fo r Disease Index* ■

Age ARCHAIC ANDERSON PEARSON BUFFALO MADISONVILLE Class and (years) SUNWATCH C% N 1 e t e t e t e t 6-10 9 90.8 3 96.7 2 98.5 2 98.7 4 95.1 11-15 6 84.7 8 87.9 13 88.6 7 94.0 9 84.1 16-20 8 76.5 8 79.1 15 77.3 19 81.4 10 72.0 21-25 15 61.2 12 65.9 19 62.9 20 68.2 5 65.9 26-30 16 44.9 8 57.1 15 51.5 21 54.3 11 52.4 31-35 17 27.6 19 36.3 26 31.8 28 35.8 19 29.3 36-40 18 9.2 12 23.1 24 13.6 33 13.9 8 19.5 41-45 7 7.1 9 9.9 8 7.6 12 6.0 8 9.8 46-50 2 0.0 8 4.4 8 1.5 3 4.0 7 1.2 +50 0 0.0 4 0.0 2 0.0 6 0.0 1 0.0 TOTAL 98 91 132 151 82 MEAN 28.0 31. 4 29.5 30.9 29.3 VARIANCE 109.5 140. 0 116.7 104.0 136.2

M ■ or IMlvldttlt, 0% - c w o U tiv t fOMomt, mw# • Ivtrot* #0* 1» yooro. aM variaae# ■ variaae* ia yaara*. 154 TABLE 44. Kolmogorov-Smirnov test for age distribution, above diagonal are values for data in Table 42 and below diagonal are values for data in Table 43.

ARCHAIC ANDERSON PEARSON BUFFM.0 MADISONVILLE and SUNWATCH ARCHAIC - 0.60 0.51 0.55 0.48

AND/SUNWATCH 0.95 • 0.62 0.54 0.36

PEARSON 0.58 0.70 - 0.55 0.69

BUFFALO 0.72 0.69 0.45 - 0.34

MADISONVILLE 0.69 0.47 0.45 0.72 -

* critical value at P = 0.05 ia 1.36. wise comparisons between the samples reveal no significant differences for age distribution (critical value at P = 0.05 is 1.36). The general trends for dental health are presented by sample for the Abscess Index (Table 45), the Caries Index (Table 46), the AMTL Index (Table 47), and DM (decayed and missing) Index (Table 48). Results obtained from the Caries, AMTL, and DM indices provide sensitive indicators by which dietary generalizations can be made about these samples. As mentioned previously, patterns of dental disease closely reflect diet and health.

Absgess.

The abscess indices reported in Table 45 do not reveal any distinctive pattern with respect to subsistence. A 5.3 155 TABLE 45. Age distribution by sample for Abscess Index.

Age Class ARCHAIC ANDERSON PEARSON BUFFALO MADISONVILLE (years) and SUNWATCH

6-10 0.0 0.0 0.0 0.0 0.0 11-15 0.0 0.9 0.3 0.0 0.0 16-20 0.0 2.0 2.2 4.0 1.3 21-25 0.4 3.0 2.9 5.4 4.1 26-30 3.9 2.8 6.7 5.0 4.8 31-35 7.3 7.6 7.9 6.6 6.1 36-40 12.3 5.7 6.2 6.2 8.4 41-45 11.1 9.7 1.2 7.2 6.4 46-50 13.8 15.8 7.7 7.9 3.8 +50 0.0 5.8 0.0 2.6 6.2 MEAN 5.3 6.0 4.7 5.3 4.3 VARIANCE 53.9 63.3 39.8 47.0 51.5

TABLE 46, Age distribution by sample for Caries Index.

Age Class ARCHAIC ANDERSON PEARSON BUFFALO MADISONVILLE (years) and SUNWATCH

6-10 0.0 0.0 0.0 0.0 13.9 11-15 0.0 5.0 3.6 10.7 9.7 16-20 1.6 7.2 5.7 20.2 6.9 21-25 3.9 9.0 8.3 26.7 11.6 26-30 9.1 10.5 19.6 15.1 10.1 31-35 9.1 19.2 20.8 28.6 18.4 36-40 13.7 21.2 25.7 23.9 25.8 41-45 7.2 30.5 30.5 44.0 15.4 46-50 15.8 18.5 49.3 0.0 29.2 +50 - 33.6 - 25.4 - MEAN 7.1 15.0 16.1 23.2 15.4 VARIANCE 103.5 207.6 306.3 299.3 194.6 156 TABLE 47. Age distribution by sample for AMTL Index.

Age Class ARCHAIC ANDERSON PEARSON BUFFALO HADISONVILLE (years) and SUNWATCH

6-10 0.0 0 .0 0.0 0.0 0.0 11-15 0 .0 0 .0 0.0 0.0 0.0 16-20 0.0 1.6 2 .6 8.6 1.3 21-25 0.0 5.4 4.3 8.8 0.6 26-30 4.0 7.4 14.5 9.3 7.9 31-35 15.0 22.2 22.4 29.1 13.4 36-40 18.2 18.8 34.0 35.7 11.2 41-45 28.5 49.7 59.2 34.8 31.3 46-50 41.8 28.3 55.1 49.7 34.2 +50 - 60.8 81.2 43.0 37.5 MEAN 9 .5 18.8 21.3 22.2 12.0 VARIANCE 328.0 611.1 739.6 697.5 371.4

TABLE 48. Age distribution by sample for DM (decayed and missing) Index.

Age Class ARCHAIC ANDERSON PEARSON BUFFALO MADISONVILLE (years) and SUNWATCH

6-10 0.0 0.0 0.0 0.0 6.2 11-15 0.0 4 .2 3.3 10.1 11.5 16-20 1.6 8.6 9.0 21.2 7.7 21-25 3.8 12.9 13.1 31.4 8.8 26-30 12.4 15.8 25.6 23.8 15.3 31-35 23.3 35.0 36.2 43.6 24.9 36-40 28.5 33.4 44.7 49.2 27.8 41-45 32.8 61.0 68.1 53.0 38.8 46-50 52.6 40.1 66.9 64.8 42.2 +50 - 69.8 81.2 48.4 37.5 MEAN 15.4 28.6 30.8 36.9 21.4 VARIANCE 392.6 664.1 822.5 681.2 425.2 157 value was reported for the hunting-gathering-fishing Archaic sample, as well as for the much later horticultural Buffalo sample. The Anderson/SunWatch samples have the highest value, 6.0, while the Pearson sample, with a corresponding date, has a 4.7 value. Madisonville, the most recent site, has the lowest value, 4.3. One trend that is clear from assessing Tables 19 through 30 is the correlation of age and abscess frequencies. As an individual increases in age it appears the likelihood of them having an abscess is greater, it also appears from the summary table of permanent pathology by tooth type that the tooth most likely to be affected by an abscess is the first molar.

Attrition.

Again, using the summary tables for permanent dental pathologies, a number of notable observations about attrition can be made for the Late Prehistoric samples. All samples have the most teeth present represented in the 3-4 wear category (42.4 to 62.1%). Less than 10% of the teeth present per site appear in the 7-8 wear category. The precontact sites had the highest frequencies for the 7-8 wear category (Anderson: maxilla = 7.7 and mandible =9.5; Pearson: maxilla =3.3 and mandible = 5.3; and Sunwatch: maxilla = 4.3 and mandible = 5.9). All other sites had frequencies less than 2.8. Hence, higher wear scores appear 158 more often associated with the precontact samples (transitional horticulturalist) than with the postcontact (horticulturalist) samples. Examination of wear category and caries lesions revealed that for most sites the trend was to have an increase in caries in the 7-8 wear category. The only exception to this observation is the mandibular dentition from Anderson which shows a decrease in caries as the wear scores increase.

Caries.

The overall prevalence of carious lesions, shown in Table 46, concurs with expectations of caries distribution for hunting-gathering-fishing subsistence to transitional horticulturalists to horticulturalists. Turner (1979:624) notes that "the variability of caries as assessed by the range of frequencies of caries teeth increase from hunting and gathering economies (0.0-5.3%), through the mixed economies (0.44-10.3%), to agricultural ones (2.3-26.9%)". The Archaic sample has the lowest caries frequency (7.1), which however is higher than Turner's range for hunting and gathering economies. The Archaic sample is followed by Anderson/SunWatch (15.0), Madisonville (15.4), Pearson (16.1), and Buffalo (23.2); all which have frequencies high enough to place them in Turner’s agricultural economies. The earlier Late Prehistoric sites 159 (Anderson/SunWatch and Pearson) are not easily identified as tra n s itio n a l or from a mixed economy by T urner's method. The only unexplained placement in the above sequence is Madisonville. Since Madisonville is known to be a more recent site dependent on maize it seems odd that the percent of carious teeth is so low. Nevertheless, the Archaic populations which practice hunting-gathering-fishing subsistence separate nicely from the horticultural populations. Although no correlation test was made between attrition and carious lesions, a comparison of the trends between these two v ariab les shows th a t the samples with the higher wear scores (Anderson, Pearson, and SunWatch), also have the lower percentage of caries. Attrition, for these samples, may provide some protection against carious invasion by removing the natural food traps on the occlusal surface. The ra te s of a t t r i t i o n would need to be examined in more detail to establish a more definitive statement about the interaction of caries and attrition. The predominant pattern observed for caries location on most teeth is on the root or cementoenamel junction for all sites (Tables 19 through 30). Overall molars appear to be affected most often by caries activities. This observation of high caries frequency for molars may be influenced by molars size and morphology. Molars are the largest, most complex te e th ; in addition to being the most numerous tooth 16 0 type found in the dental arcade. The permanent first molars also experience a longer amount of time in the o ral cavity due to their time of eruption allowing for more exposure to carious invasion.

Tcpth Lqsæ.

Antemortem to oth lo ss, represented by the AMTL ind ices, coincides well with the results obtained from both the C aries indices and the DM (decayed and missing) ind ices. The mean AMTL values in ascending order by sample are: Archaic (9.5); Madisonville (12.0); Anderson/SunWatch (18.8); Pearson (21.3); and Buffalo (22.2). This sample sequence is the same as that found for the DM values: 15.4, 21.4, 28.6, 30.8, and 36.9 respectively. Frequencies increase in a fashion similar to the Caries indices, with the only difference being a reversal between Madisonville and Anderson/SunWatch samples. Again, these sequences of increased disease can best be explained by diet. The shift to maize horticulture provides a high carbohydrate diet that is known to jeopardize the quality of dental health. In all samples, AMTL is highest for molars than any other tooth type. The increase of a carbohydrate diet which is more likely to impact the most morphologically complex teeth may best explain the pattern of molar tooth loss. 161 Une Bang. Qiowth The results obtained by correlating chronological age and maximum diaphyseal length (without epiphyses) of each long bone and maximum length of the clavicle, height of the scapula, and breadth of the ilium are presented by site in Tables 49 through 57. Indian Hills and Petersen were not considered for this analysis because of their low sample s iz e s. The ALL category contains the means fo r Anderson, Buffalo, Madisonville, Pearson, and Sunwatch. Pooling of these samples is justified since the adult stature is virtually the same for all samples except Madisonville and Madisonville is represented in the analysis by a small sample size. Thus, the ALL category should provide a generalized standard for age estimates for Late Prehistoric samples from the Ohio area. The subadult bone measures were fitted to the Count model (or human growth equation) according to an in d iv id u a l’s ages (up to age 18) by s ite using BMDPAR (Dixion et al. 1990). Buffalo, Pearson, and Sunwatch were used for this assessment since they possessed adequate sample sizes. Buffalo, Pearson, and SunWatch initially were assessed independently of each other (Table 58) to see how their growth equations would compare to each other. The coefficient for age (b,) reflects the linear component of child growth while the coefficient for the log of age (bg) reflects the rapid growth of early childhood. 162 The values shown a t the rig h t in d icate a good f i t to the equation. These three sites were then combined to produce a single growth equation for each element (Table 59) when the equations between the sites were observed to be similar. Again, the R* values describing the proportion in bone length accounted for by the model were high. A comparison of the bg values to the b, values per elements by sample and then a l l samples grouped togeth er shows th a t growth is more rapid during early development than during later development. To better assess whether the Buffalo, Pearson, and Sunwatch samples should be combined in this analysis, the growth curves, velocities, and accelerations for the femur and tibia (the two element showing the greatest amount of variation) were plotted. Comparisons also were made with a Late Archaic sample (Giesen and S c iu lli 1988) and an environm entally optimum sample from the Denver growth study of modern Euro-Americans by Maresh (1955). Table 59 provides the femur and tibia growth values for the Late Archaic and the Denver samples as they fit to the Count model. Figures 8 and 9 shows the long bone growth curves modeled by the Count equation for Buffalo, Pearson, Sunwatch, the Late Archaic, and the Denver samples. In both these figures the Late Prehistoric samples cluster relatively close together. The femur curves for the Late 163 Prehistoric samples are slightly lower than the Late Archaic and Denver samples, while the tibia curves for the Late Prehistoric samples fall between the Late Archaic and Denver samples. Figures 10 through 13 shows the velocity and acceleration of the femur and tibia. Again, the Late Prehistoric samples group together relatively well. These figures also reveal a slightly reduced rate for both acceleration and velocity for most of the Late Prehistoric samples. Giesen and Sciulli (1988) concluded from their study that sim ilarities observed in the growth curves between the Late Archaic sample and the Denver sample suggest little environmental stress was being displayed in the Late Archaic population. They f e l t th is was a f a i r assessment since the Denver sample represents a population with optimal nutrition and minimal stress from chronic and acute illness. The results obtained here are mixed, the tibia data suggest compatible results to those of Giesen and Sciulli, while the femur results show a slightly lower growth curve than either the Late Archaic or Denver samples. The reduced acceleration and velocity for the Late Prehistoric samples when compared to the other two samples suggest a more stressed environment. The dental pathologies and short adult stature identified earlier in this study also support a higher stress environment for these Late Prehistoric populations. TABLE 49. Correlations between chronological age estimates and the maximum diaphysial length* of the humerus.

HUMERUS ALL ATCERSON BUFFALO MADISONVILLE PEARSON SUNWATCH

N X range N X range NX range N X range N X range N X range

NB-0.49 4 0 4 .4 5 4 .5 -7 2 .0 3 63.5 5 4 .5 -7 2 .0 1 67.0

0.5*0.09 30 03.0 48.0-80.0 11 62.8 53.0-69.0 1 6 3 .0 3 61.7 4 8 .0 -7 3 .0 15 6 5 .2 5 8 .0 -8 0 .0 1 .0 -1 .4 9 22 86.4 01.0-103.0 1 67.0 3 102.7 102.0-103.0 3 67.7 6 1 .0 -7 4 .0 15 88.2 68 .0 -1 0 0 .5 1 .5 -1 .9 9 15 110.9 9 6 .0 -1 3 4 .0 2 109.7 104.5-115.0 2 123.0 110.0-130.0 1 101.0 3 119.3 106.0-134.0 7 105.5 96.0-115.0 2 .0 -2 .9 9

3 .0 -3 .9 9 12 138.7 114.0-230.0 3 133.0 129.0-139.5 3 134.7 130.0-140.0 2 128.2 115.5-141.0 2 122.0 114.0-130.0 2 180.5 131.0-230.0 4 .0 -4 .9 9 G 150.4 145,0-158.5 1 145.0 3 151.3 147.0-158.0 1 145.0 1 158.5 5 .0 -5 .9 9 4 177.9 169.0-214.5 2 180.8 159.0-214.5 1 159.0 1 179.0

0 .0 -0 .9 9 8 178.5 101.0-197.5 1 190.0 3 181.2 171.0-197.5 1 184.0 3 170.0 164.0-175.0

7.0-7.99 5 190.2 101.0-207.0 1 207.0 2 196.0 192.0-200.0 2 176.0 161.0-192.5 8 .0 -8 .9 9 2201.5193.0-210.0 1210.0 1 193.0

9 .0 -9 .9 9 1 201.0 1 201.0 10.0-10.99 4 227.5 215.0-244.0 1 223.0 2 236.0 228.0-244.0 1 215.0

11.0-11.09 5 233.3 210.0-261.0 1 245.0 1 201.0 2 210.0 210.0-210.0 1 240.5 12.0 -1 2 .9 9 0 253.7 233.0-298.0 1 250.0 1 298.0 1 256.0 3 239.3 233.0-245.0 13.0-13.99 4 243.6 227.0-207.0 1 267.0 3 236.0 227.0-244.0 14.0-14.99 1 270.0 1 276.0

15.0-15.09 3 271.7 253.0-301.0 2 257.0 253.0-261.0 1 301.0 10.0 -1 0 .9 9 1 267.0 1 267.0 in»n langth glvan in nilllnatars.

o> TABLE 50. Correlations between chronological age estimates and the maximum diaphysial length* of the radius.

RADIUS ALL ANDERSON BUFFALO MADISOWILLE PEARSON SÜNNATCH

H X range N X range N X range N X range N X range N X range

NB-0.49 13 49.0 44.5-54.0 2 46.5 44.5-48.5 1 54.0 0.5-0.99 29 52.8 39.0-66.5 10 51.6 47.5-56.0 1 50.5 2 46.5 3 9 .0 -5 4 .0 16 54.5 48.0-66.5 1.0-1.49 12 73.5 63.5-84.0 2 82.8 81.5-84.0 1 81.5 9 70.6 63.5-77.0

1 .5 -1 .9 9 16 8 7 .7 7 8 .0 -1 0 5 .0 2 86.0 80.5-91.5 3 92.7 80.0-105.0 5 91.4 65.0-101.0 6 82.6 78.0-87.0 2 .0 -2 .9 9

3 .0 -3 .9 9 11 108.3 7 1 .0 -1 8 4 .0 3 106.7 100.0-111.0 2 108.0 106.0-110.0 2 100.8 92.0-109.6 1 100.0 3 11B.0 71.0-184.0 4 .0 -4 .9 9 2 115.3108.0-122.5 1 108.0 1 122.5 5 .0 -5 .9 9 4 138.8 127.0-162.0 2 146.0 130.0-162.0 1 127.0 1 136.0 6 .0 -6 .9 9 1 131.0 1 131.0

7.0-7.99 4 146.5 138.0-163.5 2 155.0 146.5-163.5 2 138.0 138.0-138.0 8 .0 -8 .9 9 1 145.0 1 145.0 9 .0 -9 .9 9

10.0-10.99 3 168.7 152.0-180.0 2 177.0 174.0-180.0 1 152.0

11.0-11.99 2 141.0 117.0-162.0 1 165.0 1 117.0 1 2.0 -1 2 .9 9 5 182.4 148.0-197.0 4 191.0 185.0-197.0 1 148.0 1 3.0 -1 3 .9 9 3 189.7 181.0-194.0 3 189.7 181.0-194.0 1 4.0 -1 4 .9 9

1 5.0 -1 5 .9 9 2 213.8 199.0-228.5 1 199.0 1 228.5 16.0-16.99 1 254.0 1 254.0

' mean length given in millimetere. TABLE 51. Correlations between chronological age estimates and the maximum diaphysial length* of the ulna.

ULNA ALL ANDERSON BUFFALO MADtSOmiLLE PEARSON SUNWATCH

N X range N X range N X range N X range N X range N X range

NB-0.49 3 5 7.5 4 9 .5 -6 2 .0 2 55.3 49.5-61.0 1 6 2.0

0 .5 -0 .9 9 29 6 0 .2 4 0 .0 -7 5 .0 10 57.6 40.0-65.0 1 59.5 4 5 6.5 4 6 .0 -6 8 .0 14 62.5 55.5-75.0 1.0-1.49 12 78.4 55.0-94.0 2 93.0 92.0-94.0 10 7 5.5 5 5 .0 -8 7 .0

1 .5 -1 .9 9 15 9 9.8 85.0-118.0 2 96.5 90.0-103.0 2 115.0 112.0-118.0 1 102.0 4 103.5 95.0 -1 1 5 .0 6 93.0 85.0-99.0 2 .0 -2 .9 9

3.0-3.99 12 131.0 94.0-203.0 3 118.7 114,0-123.0 2 159.5 141.0-178.0 1 121.5 3 122.3 100.0-152.0 3 136.3 94.0-203.0

4 .0 -4 .9 9 4 129.5 122.0-135.0 2 130.5 128.0-133.0 1 122.0 1 135.0 5 .0 -5 .9 9 2 137.0 134.0-140.0 1 134.0 1 140.0 0 .0 -6 .9 9 4 151.3 141.0-163.0 1 163.0 1 157.0 2 142.5 141.0-144.0

7 .0 -7 .9 9 3 169.5 161.0-180.0 1 180.0 1 161.0 1 167.5 8 .0 -0 .9 9 1 161.0 1 161.0 0 .0 -9 .9 9

10.0-10.99 4 187.8 162.0-201.0 1 184.0 2 194.5 188.0-201.0 1 162.0 11 .0 -1 1 .9 9 2 209.5 192.5-227.0 1227.0 1192.5 12.0-12.99 4 220.3 204.0-219.0 1 242.0 3 213.0 204.0-224.0

13.0-13.99 3 211.3 200.0-219.0 3 211.3 200.0-219.0

14.0-14.99 1 227.0 1 227.0

15.0-16.90 2 238.0 220.0-256.0 1 220.0 1 256.0 16.0-16.99

■ Man length given in millimetere.

o>O) TABLE 52, Correlations between chronological age estimates and the maximum diaphysial length* of the femur.

FEMUR ALL ANDERSON BUFFALO MADISONVILLE PEARSON SUNWATCH N X range N X range N X range N X range N X range NX range

NB-0.49 3 69.0 62.0-76.0 2 69.0 62.0-76.0 1 69.0 0 .5 -0 .9 9 34 71.3 62.0-113.5 12 73.0 59.0-81.0 3 87.8 73.0-113.5 4 6 9.8 5 2 .0 -8 0 .0 15 67.0 60.0-79.5 1 .0 -1 .4 9 16 94.0 69.0-134.0 2 104.5 7 5 .0 -1 3 4 .0 1 132.0 4 89.2 69.0-118.0 9 89.6 7 5 ,0 -1 0 2 .0 1 .5 -1 .9 9 20 135.5 9 7 .0 -1 7 0 .0 2 138.0 135.0-141.0 5 158.5 137.5-170.0 1 129.0 6 143.3 110.0-169.0 6 108.7 97.0-126.0 2 .0 -2 .9 9

3 .0 -3 .9 9 15 192.5 143.5-330.0 3 183.3 171.0-193.0 4 198.8 185.0-225.0 2 171.2 150.0-192.5 2 182.0 171.0-193.0 4 208.9 143.5-330.0 4 .0 -4 .9 9 S 204.1 190.0-221.0 1 197.0 1 193.0 2 205.5 190.0-221.0 1 219.5 5 .0 -6 .9 9 8 234.3 200.0-309.5 4 249.8 221.0-309.5 1 200.0 2 220.5 220.0-221.0 1 234.0 0 .0 -6 .9 9 16 240.2 210.0-278.0 1 267.0 7 251.9 235.0-278.0 2 232.0 210.0-254.0 6 240.7 220.0-249.0

7 .0 -7 .9 9 12 277.6 221.0-356.0 1 281.0 2 313.5 271.0-356.0 7 276.1 248.0-348.0 2 245.5 221.0-270.0 8.0-8.99 4 285.3 266.0-315.0 1 294.0 2 290.5 266.0-315.0 1 266.0 9 .0 -9 .9 9

10.0-10.99 5 303.6 285.0-330.0 1 305.5 2 321.0 312.0-330.0 2 285.6 285.0-286.0

11.0-11.99 8 324.0 274.0-379.0 2 333.2 323.6-343.0 3 308.5 274.0-359.5 2 337.0 295.0-379.0 1 333.0 12.0-12.99 8 339.9 272.0-408.5 1 345.0 2 379.8 351.0-408.6 1 314.5 3 342.7 330.0-359.0 1 272.0 13.0-13.99 6 355.0 324.0-404.0 2 389.5 375.0-404.0 4 337.8 324.0-362.0

14.0 -1 4 .9 9 1 380.0 1 380.0 15.0-15.99 2 396.5 377.0-416.0 1 377.0 1 416.0 16.0-10.99 1 367.5 1 367.5 17.0-17.99 1 400.0 1 400.0

«••n l«ngth *r« given in miUimetere.

O) - s TABLE 53. Correlations between chronological age estimates and the maximum diaphysial length* of the tibia.

TIBIA ALL ANDERSON BUFFALO MADISONVILLE PEARSON SUNWATCH

N X range N X range N X range N X range N X range N X range

NB-0.4Q 4 6 3,8 5 4 ,5 -6 9 .0 3 62.0 64.5-67.5 1 6 9 .0 0 .5 -0 .0 0 25 6 5 .2 4 6 .0 -7 9 .5 8 64.4 61.0-67.5 1 64.0 2 5 6 .0 46.0-66.0 15 67.0 60.0-79.5

1 .0 -1 .4 9 14 87.1 63.0-108.5 1 63.0 1 108.5 3 80 .7 62.0-94.0 9 89.6 76.0 -1 0 2 .0 1.5-1.09 16 117.9 97.0-150.0 2 112.8 111.5-114.0 1 143.0 1 105.0 6 126.8 113.0-150.0 6 108.7 97.0-126.0 2 .0 -2 .0 9

3 .0 -3 .9 9 13 160.0 118.0-278.5 3 156.0 149.0-165.0 2 174.0 163.0-185.0 2 136.5 120.0-153.0 3 151.7 130.0-168.0 3 176.5 118.0-278.5

4 .0 -4 .9 9 5 171.0 162.0-181.5 1 165.5 1 162.0 2 172.0 167.0-177.0 1 181.5 5 .0 -5 .9 9 7 202.6 175.0-250.0 3 215.7 195.0-250.0 3 192.3 175.0-217.0 1 194.0 OeO-0.99 13 200.6 178.0-216,0 1 216.0 5 206.4 195.0-215.5 2 183.5 178.0-189.0 5 198.6 186.0-208.0

7 .0 -7 .9 9 8 230.0 183.0-292.0 1 239.0 5 240.0 220.0-292.0 2 199.0 183.0-215.0 8.0-8.09 1 220.0 1 220.0 0.0-9.09 1 225.0 1 225.0 10.0-10.99 5 261.6 238.0-283.0 1 260.0 3 270.0 256.5-283.0 1 238.0

11.0-11.90 5 291.7 245.0-320.0 1 305.0 1 306.5 2 287.0 245.0-329.0 1 273.0 12.0-12.99 7 205.7 245.0-329.0 1 274.5 2 314.8 287.0-342.5 4 291.0 270.0-307.0 13.0-13.09 3 290.0 284.0-301.0 3 290.0 284.0-301.0 14.0-14.99 1 325.0 1 3 25.0

16.0-15.90 2 319.5 289.0-350.0 1 289.0 1 350.0 15,0-10.99 2 336.8 314.5-359.0 1 314.5 1 359.0 17.0-17.99 1309.0 1300.0

* msan length given in niUinetera.

0> 00 TABLE 54. Correlations between chronological age estimates and the maximum diaphysial length* of the fibula.

FIBULA ALL ANDERSON BUFFALO MADISONVILLE PEARSON SUNWATCH

N X range N X range N X range N X range NX range N X range

NB-0.49 2 58.0 5 1 .0 -6 5 .0 1 5 1.0 1 65.0

0 .5 -0 .9 9 20 63.1 56.0-67.0 4 61.5 56.5-65.0 1 6 2 .0 1 62.0 14 6 3 .7 5 6 .0 -8 7 .0

1.0-1.49 9 84.4 6 6 .0 -9 7 .0 1 68.0 8 86.5 71.0-97.0

1 .5 -1 .9 9 10 112.4 95 .0 -1 3 8 .0 4 124.2 115.0-138.0 6 104.5 95.0-121.0 2 .0 -2 .9 9

3.0-3.99 4 137,5 113.0-162.0 1 150.0 2 132.5 113.0-152.0 1 135.0 4 .0 -4 .9 9 4 167.8 161.5-176.5 1 169.0 1161.5 1164.0 1 176.5

5.0-6.99 4 207.3 180.0-246.5 2 216.0 189.5-242.5 2 198.5 180.0-217.0

6 .0 -5 .9 9 6 205.4 191.0-231.0 1 216.6 2 215.0 199.0-231.0 3 195.3 191.0-198.0

7 .0 -7 .9 9 5 216.7 167.6-233.0 1 230.0 2 228.0 223.0-233.0 2 198.8 187.5-210.0 8 .0 -8 .9 9 2 240.0 212.0-268.0 1 268.0 1 212.0 9 .0 -9 .9 9

10.0-10.99 2 237.5 225.0-250.0 1 250.0 1 225.0

11.0-11.99 2 288.3 264.0-312.0 1 312.0 1 264.5 1 2 .0-12.99 4 262.0 226.0-280.0 3 274.0 269.0-280.0 1 226.0

13.0-13.99 3 289.0 283.0-296.0 3 289.0 283.0-296.0 1 4 .0-14.99

15.0-16.99 1 341.0 1 341.0 1 6 .0-15.99 1 300.0 1 306.0 1 7 ,0-17.99

18.0-18.99 1 370.0 1 370.0

* mean length given in millimetere. TABLE 55. Correlations between chronological age estimates and the maximum length* of the clavicle.

CLAVICLE ALL ANDERSON BUFFALO MADISONVILLE PEARSON SUNWATCH N X range X range N X range N X range NX range H X range

W -0 .4 9 1 4 4 .0 1 4 4.0 0 .6 -0 .9 9 23 43.7 34.0-55.6 9 42.2 34.0-47.0 1 43.0 2 48.0 4 5 .0 -5 1 .0 11 44.2 38.0-55.5

1.0-1.49 10 55.7 44.0-66.0 1 44.0 2 65.5 65.0-66.0 7 54.5 50.5-57.0 1 .5 -1 .9 9 14 6 4 .5 5 6 .0 -7 5 .0 2 64.8 62.0-67.5 1 56.0 1 6 3 .0 5 67.4 5 6 .0 -7 5 .0 6 63.5 59.0-68.0 2 .0 -2 .9 9

3 .0 -3 .9 9 8 7 1 .6 6 5 .0 -7 6 .0 1 7 2 .0 3 73a0 71.0-76.0 1 76.0 2 69.0 65.0-73.0 1 68.0

4 .0 -4 .9 9 3 6 1 .0 73.0-63.0 2 80.0 78.0-82.0 1 83.0 5 .0 -5 .9 9 4 9 0 .2 63.0-102.0 2 95.8 89.5-102.0 1 83.0 1 86.0

6 .0 -6 .9 9 2 8 6 .0 64.0-88.0 1 84.0 1 88.0

7.0-7.99 4 91.8 87.0-98.0 2 92.5 8 7 .0 -9 8 .0 2 91.0 87.0-95.0 8 .0 -6 .9 9 3 9 7 .3 8 8.0 -1 1 2 ,0 1 88.0 2 102.0 102.0-102.0 9 .0 -9 .9 9 1 9 0 .0 1 9 0 .0

10.0 -1 0 .9 9 2 9 5 .0 7 8 .0 -1 0 2 .0 1 76.0 1 112.0

11.0-11.99 4 117.9 113.0-125.0 1 113.5 1 120.0 1 125.0 1 113.0 12.0-12.99 2 116.0 116.0-120.0 2 118.0 116.0-120.0

13.0-13.99 4 115.5 103.0-131.0 1 131.0 3 110.3 103.0-118.0 1 4.0 -1 4 .9 9

15.0-16.99 1 133.0 1 133.0

16.0-16.99 1 150.0 1 150.0 17.0 -1 7 .9 9

16.0-16.99 1 132.0 1 132.0

* naan langth givan In n lU iaatars. TABLE 56. Correlations between chronological age estimates and the maximum height* of the scapula.

SCAPULA ALL BUFFALO UADXSONVILLE PEARSON SUNWATCH NX range N X range N X range N X range N X range

NB-0.49 3 28.0 25.0-30.0 2 27.0 2 5 .0 -2 9 .0 1 3 0.0

0 .5 -0 .0 9 24 31.7 26.0-40.5 8 30.4 2 6 .0 -3 4 .0 2 30.5 30.0-31.0 1 32.0 13 3 2 .6 2 8 .5 -4 0 .5

1 .0 -1 .4 9 13 42.0 3 2 .0 -5 5 .0 2 4 7 .5 4 0 .0 -5 5 .0 11 41.2 3 2 .0 -5 1 .0 1.5-1.99 11 52.9 45.0-68.0 2 57.0 46.0-68.0 1 51.0 1 58.0 7 51.2 4 5 .0 -5 8 .0 2 .0 -2 .9 9

3 .0 -3 .9 9 4 01.0 56.0-70.0 1 61.0 1 70.0 2 5 6 .0 5 6 .0 -5 6 .0 4 .0 -4 .9 9 3 72.3 72.0-73.0 1 72.0 1 73.0 1 7 2 .0 5 .0 -5 .9 9 1 60.0 1 8 0 .0 6.0-0.99 1 73.0 1 7 3 .0

7 .0 -7 .9 9 2 88.0 8 3 .0 -9 3 .0 2 8 8 .0 8 3 .0 -9 3 .0 8 .0 -8 .9 9 9 .0 -9 .9 9

10.0-10.99 1 101.0 1 101.0

11.0 -1 1 .9 9 1 104.0 1 104,0 12.0-12.99 13.0-13.99 14.0-14.99 15.0 -1 5 .9 9 16.0-16.99

* nom height given in millimetere. TABLE 57. Correlations between chronological age estimates and the maximum breadth* of the ilium.

ILIUM ALL BUFFALO MADISONVILLE PEARSON SUNWATCH NX range N X range N X range N X range N X range

fC-0.49 4 27.1 18.0-33.5 2 28.5 26.0-31.0 1 18.0 1 3 3.5

0.5*0.09 34 35.0 23.0-00.0 11 33.1 2 9 .5 -3 5 .0 2 3 2 .2 3 2 .0 -3 2 .5 5 40.2 2 3 .0 -5 9 .0 16 36.3 31.0-49.0

1 .0 -1 .4 9 20 44.2 30.0-03.0 2 51.0 39.0-63.0 6 36.8 30.0-56.0 12 46.8 41.0-57.0

1 .5 -1 .0 9 18 5 8.5 4 2 .0 -7 0 .0 4 6 1 .2 53.0-70.0 1 52.5 4 63.5 58.0-66.0 9 55.7 42.0-68.0 2 .0 -2 .9 9

3 .0 -0 .9 9 9 08.8 55.0-78.0 3 6 9 .8 6 6 .5 -7 3 .0 1 77.5 4 67.5 5 5 .0 -7 8 .0 1 6 2.5 4 .0 -4 .9 9 5 78.0 09.0-84.0 1 60.0 2 81.0 79.0-83.0 1 75.0 1 8 4 .0

5 .0 -5 .9 9 7 8 5 .8 70 .0 -1 0 8 .0 2 9 2.5 77.0-108.0 1 83.0 3 60.0 76.0-84.0 1 9 2 .5 0.0-0.99 10 89.3 75.0-101.0 4 83.4 7 5 .0 -9 1 .0 2 90.5 88.0-93.0 4 94.5 90.0-101.0

7 .0 -7 .9 9 0 9 4 .9 80 .0 -1 1 8 .0 8 94.9 60 .0 -1 1 8 .0 1 9 5.0 8 .0 -8 .9 9 1 101.0 1 101.0 0 .0 -9 .9 9 1 9 4 .5 1 94.5

10.0-10.90 7 108.9 100.0-115.0 2 100.8 108.0-111.5 3 109.2 108.0-111.5 2 107.5 100.0-115.0

11.0-11.90 5 112.3 0 9 .0 -1 2 0 .0 2 109.5 99.0-120.0 2 114.5 110.0-119.0 1 113.5 12.0-12.09 4 103.7 90.0-111.0 3 108.3 105.0-111.0 1 9 0 .0 13.0-13.99 4 118.9 110.0-123.0 1 110.5 3 121.7 120.0-123.0 14.0-14.99 1 128.0 1 128.0

15.0-15.99 3 120.2 115.0-123.0 1 115.0 1 122.5 1 123.0 10.0-10.99

• mean b read th given in m illim e te re .

>1 lu 173 TABLE 58. Regression formulae for lone bones and irregular bones from Buffalo, Pearson, and SunWatch.

COEFFICIENT FOR COEFFICIENT FOR CORRELATION ELEMENT SITE N INTERCEPT AGE THE LOG OF AGE R* (b.) (b.)

HUMERUS BUFFALO 36 94.18t5.36 10.6011.06 27.0715.72 .9415

PEARSON 29 8 6 .3 8 t3 .9 6 7.5911.17 55.3719.44 .9687

SUNWATCH 48 67.82t4.22 11.4911.41 31.0910.24 .8930

RADIUS BUFFALO 25 72.70t3.91 8.1110.99 21.0914.38 .9410

PEARSON 23 77.5 7 t3 .2 4 6.7410.96 42.6818.54 .9695

SUNWATCH 43 7 1 .5 1 t4 .6 7 6.4611.41 23.6117.68 .7842

ULNA BUFFALO 23 63.9414.96 8.2911.29 24.6515.40 .9214

PEARSON 26 62.6314.23 6.9411.16 39.4719.58 .9519 SUNWATCH 40 75.9414.16 10.5311.39 20.8717.12 .6587

FEMUR BUFFALO 49 124.4116.71 15.1411.50 51.6018.08 .9398

PEARSON 46 115.0915.63 10.4911.61 95.72114.36 .9437

SUNWATCH 47 1 1 4 .2 * 7 0 .3 14.3712.24 52.32112.22 .8658

TIBIA BUFFALO 26 105.1316.07 13.5611.69 33.1917.42 .9413

PEARSON 42 96.2415.43 9 .8411.63 77.20115.10 .9365 SUNWATCH 41 90.0516.24 14.7912.03 33.16110.37 .8725

FIBULA BUFFALO 13 116.79113.71 9.2612.81 52.07113.60 .9311

SUNWATCH 36 62.3014.16 13.7911.18 25.6916.65 .9512

CLAVICLE BUFFALO 22 56.4612.60 3 .6210.77 16.6214.01 .9424

PEARSON 24 57.9612.73 3 .4110.70 17.7516.93 .9234

SUNWATCH 33 53.7611.43 4.4410.44 11.7112.99 .9469

SCAPULA SUNWATCH 40 40.7311.46 5.3910.60 11.4612.39 .9236

ILIUM BUFFALO 34 49.2212.47 3.9010,63 16.4012.90 .9116

PEARSON 48 49.7912.61 3.9910.64 21.4614.07 .8984

SUNWATCH 46 46.6111.60 3.5910.57 17.7313.22 .8818 174 TABLE 59. Regression formulae for long bones and irregular bones from B uffalo, Pearson, and SunWatch combined.

COEFFICIENT FOR COEFFICIENT FOR CORRELATION ELEMENT N INTERCEPT AGE THE LOG OF AGE R* (b.) (b«)

HUMERUS 113 69.5412.66 10.6010.66 28.92*3.88 .0362

RADIUS 01 71.6812.65 7.47*0.66 23.01*3.76 .9055

ULNA 88 80.00t2.54 8.9010.67 24.23*3.77 .0210 FEMUR 142 117.5813.81 14.7510.09 54.0915.94 .0281 TIBIA 111 95.4013.58 14.0010.88 35.55*5.04 .9294

FIBULA 74 93.1613.55 12.49*0.88 40.32*5.59 .9525

CLAVICLE 70 65.8611.16 3.8210.30 15.72*1,06 .9484 SCAPULA 60 40.5611.77 5.27*0.78 9.09*2.28 .8257

ILIUM 128 49.11*1.28 4.0410.34 18.20*1.92 .9093

TABLE 60. Regression formulae for the femur and the tibia from a Late Archaic sample and the Denver growth study.

COEFFICIENT FOR COEFFICIENT FOR ELEMENT SITE N INTERCEPT THE LOG OF AGE (M (b.)

FEMUR LATE ARCHAIC 114.57 13.47 1 0.09 75.48 * 7.66 45

DENVER 120.70 17.54 * 0.30 54.02 1 2.03

TIBIA LATE ARCHAIC 31 89.52 13.67 1 0.08 36.53 * 7.62

DENVER 05.08 13.83 1 0.10 50.88 * 1.02 1 7 5

* DENVER * ARCHAIC 0 SUNWATCH A PEARSON * BUFFALO

500

400

300

200

100

AGE IN YEARS

FIGURE 8. Femur growth curves. 176

« DENVER ■Ar ARCHAIC a SUNWATCH A PEARSON • BUFFALO

400

300

ICO 0 5 10 15

AGE IN YEARS

FIGURE 9. Tibia growth curves. 177

DENVER ARCHAIC

SUNWATCH

PEARSON BUFFALO

-10

-15

-20

-25

AGE IN YEARS

FIGURE 10. Femur acceleration curves. 178

• DENVER * ARCHAIC a SUNWATCH ^ PEARSON # BUFFALO

-10

-20

-30

-40 10 15 20

AGE IN YEARS

FIGURE 11. Tibia acceleration curves. 179

• DENVER •A- ARCHAIC Q SUNWATCH A PEARSON

• BUFFALO

100

80

60 zI 40

20

0 0 5 10 15 20

AGE IN YEARS

FIGURE 12. Femur velocity curves. 180

« DENVER * ARCHAIC

B SUNWATCH

A PEARSON

• BUFFALO

80

70

60

50

40

30

20

10 0 5 10 15 20

AGE IN YEARS

FIGURE 13. Tibia velocity curves. CHAPTER VI

DISCUSSION AND CONCLUSION

In this chapter the results will be discussed with respect to how the Late Prehistoric populations compare in terms of biological affinities and for the distribution of stress indicators. Next, the research objectives delineated in Chapter I will be addressed in light of the results. Finally, some concluding thoughts about this project will be advanced.

Biological Affinities

The data investigated here indicate that all of the samples considered are ultimately related with respect to shape, but with respect to size appear to be virtually independent. If geography plays a role in structuring biological cranial diversity it is a minor role. In this respect, the Late Prehistoric populations differ from earlier populations in Ohio. Using similar cranial data for Late Archaic in Ohio, Sciulli (1990) found that all samples investigated were biologically related (size and shape virtually identical), and that geographically neighboring samples were more closely related

181 182 than distant ones, for the discrete traits. These observations are in accord with the findings of Sciulli and Schneider (1985) for the Late Archaic and for the Early Woodland Adena complex, and Reichs (1974; 1984) fo r the Middle Woodland Hopewell. S c iu lli and Schneider (1985:441) summarize these observations well in saying that "in each of these periods osteological evidence indicates little long­ distance interaction among populations within a complex and that local population interaction, even among complexes, best accounts for the observed variability". As previously mentioned, the Late Prehistoric samples most probably shared a common heritage. Thus, the cultural differences evident between the Fort Ancient and Sandusky traditions are not clearly paralleled in their biological makeup. The c lu s te rs fo r size and d isc re te t r a i t s shown in Figures 5 and 7 respectively, are not reflective of cultural affiliation or geographic distribution. The pattern which materializes, at least for cranial size, is best explained as a function of time. This is to say, cranial shape is the same for the samples studied through time, but cranial size is changing through time. The pattern of cranial shape stability may have continued through long-distance interaction or gene flow among and between these cultural entities. However, since these populations are separated by rather long distances the most parsimonious explanation would be that shape has not changed from its shared 183 ancestral state in any of the populations. Isolation by distance in the Late Prehistoric no longer appears to be contributing to the structure of cranial diversity in Ohio populations. The question then arises: Are the samples experiencing more or less restrictions on gene flow? If distance within this area is no longer an issue in mate selection for the Late Prehistoric samples, then less variation would be expected for all samples. There would be less variation since a common gene pool would have been created for all groups in the Ohio area considered here. However, because variation was found to exist between the samples using size and discrete trait data analyses, it appears the samples are experiencing more re s tric te d gene flow and gene flow is not structured by simple geographic distance between populations. Restricted gene flow may have been due to the stationary horticultural lifestyle, which required the inhabitants to stay "close to home" in order to protect the crops and the village. The variation observed between these more sedentary populations then would best be explained by differences in the separate local environments, thus stature variation will be dealt with in more detail in the following sectio n . 184 Biocultural Stress Indicators

Dental Pathologies

This study, like many other studies, shows a strong association between subsistence patterns and overall dental health. In order to better elucidate changes in dental health due to a shift in subsistence a Late Archaic sample (i.e., hunting-gathering-fishing base) was included for a comparison to the Late Prehistoric samples (i.e., h o rtic u ltu ra l b a se). The number and percent of carious teeth increase from hunting-gathering-fishing through the horticulturalist, as do the rates of antemortem tooth loss. Dental abscess does not reflect a particular pattern with respect to a shift in subsistence. The fluctuation in the abscess pattern is not unexpected since abscesses may result from either carious activities or increased occlusal attrition and the hunting-gathering-fishing economies are known to have severe attrition, where the horticultural economies are known to have a tendency for high carious frequencies. The general trend which emerges from these pathologies suggest poorer dental health with the advent of horticulture. The amount of carbohydrates would have increased as the reliance on maize increased in the diet. As mentioned earlier, carbohydrate content of diet is recognized as the most important factor in the process of 185 caries formation. Therefore, it may be concluded that dental pathologies are good indicators of nutritional s tre s s .

The results of the subadult growth analyses will be discussed first. Since the results obtained for adult heights do not lend themselves to biological affinity assessment, the results will be dealt with in light of biocultural pressures.

kong Bone gjrpwth-

A generalized standard was produced for aging Late Prehistoric samples from the study area. Standards of this type are important since growth patterns between populations are known to vary making it unsatisfactory to use any generalized standard of growth, especially a standard from a "racially" distinct population. At this point a possible source of error should be mentioned which may have influenced the determination of dental age. It has been shown that both dental eruption and development are to a varying degree advanced in Native Americans when compared to Euro-American standards (Owsley and Jantz 1983). The p o te n tia l e ffe c t to th is study would be the possible overestimation of age which would lead to underestimate of growth rates. 186 This potential for error is unlikely to make a great amount of difference in this study sinoe all the samples are representative of prehistoric Native American populations. Thus, the relative ages will be comparable between the prehistoric samples. Topics of interest specific to tables 49 through 57, which contain the age correlations between chronological age and subadult bone measures, include the following. First, the noticeable outlier for SunWatch in the 3.00 to 3.99 year age class whose measurements approximate a 10 to 11 year old is of interest. This individual was reassessed for both dental and skeletal measures and the teeth do reflect the young age. The most likely explanation would be that the cranial (e.g., dental) material and the postcranial material do not belong to each other. Hence, this large upper limit for the 3.00 to 3.99 class for SunWatch should be ignored. When the range of measures for a single element are compared fo r an age c la ss, i t becomes apparent th a t some ranges are large. In a few cases, the range may exceed the age class mean directly above or below the age class in question. Variation of this type simply may be due to the age range of the age class. Age classes of one year interval will have individuals who just turned that age, plus individuals who are almost ready to advance to the next age class. This potential one year difference in the ages of individuals assigned to a single class make reflect this 187 range of diversity. Also, this variability in measures may be a re fle c tio n of growth d ifferen ces between males and females who are assigned to the same age. Differences in rates of growth are known to occur between the sexes (Harrison et al. 1988), but since sex determination can not be accomplished for subadult skeletons it is impossible to make this distinction. Subadult long bone measures may assist in our understanding of Late Prehistoric health, since the rate of growth has been identified as a better reflection of health in some case than the height attained as an adult (Harrison e t a l. 1988). Using the Count model or human growth equation, generalized growth equations were produced for skeletal elements using the Buffalo, Pearson, and SunWatch samples. In this model, the coefficient for age (b,) reflects the linear component of child growth while the coefficient for the log of age (bg) reflects the rapid growth of early childhood. A comparison of the bg values to the b, values per elements by sample (Table 58) and then all samples grouped tog eth er (Table 59) shows th a t growth is more rapid during early development than during later development for the Late Prehistoric Samples. The Buffalo, Pearson, and SunWatch samples were pooled together because these samples overall appear to be similar for the growth equation. 188 The s im ila r itie s and d ifferen ces seen between the different skeletal elements also needs to be addressed. Pearson, when assessed sep arately , showed a s lig h t increase in early childhood growth and a slight decrease in linear growth for most elements present when compared to Buffalo and SunWatch. The d ifferen ce between the b, and bg values is not consistent between skeletal elements for Pearson or fo r Buffalo and SunWatch fo r th a t m atter, thus ra te s of change for specific elements are variable for all samples. The greatest difference noted among the three samples was for the femur and tibia. The growth, velocity, and acceleration curves were plotted for femur and tibia growth. Buffalo, Pearson, and SunWatch appear to have l i t t l e difference between plotted curves. When the Late Prehistoric samples were compared to a Late Archaic population and the Denver growth study the Late Prehistoric samples were found to be similar; especially the tibia. The femur had slightly lower velocity and acceleration curves in the Late Prehistoric samples. The upper or proximal elements of the extremities (e.g., the humerus and the femur) show greater values for b^ and bg than do the lower or distal elements (e.g., radius, ulna, tibia, and fibula). This observation is not in support of maturity gradients for different elements of the skeleton. Harrison et al. (1988:355) have observed "a maturity gradient ... running from advanced maturity 189 distally to delayed maturity proximally". The results of the velocity and acceleration also shows disagreement with this generality about maturity gradients. The maturity gradient observed by Harrison and associates (1988) may not have been seen for these Late Prehistoric populations since these populations are believed to have been experiencing nutritional stress. It is probable that the normal (healthy) pattern of growth was disrupted and that the pattern which resulted then was further altered by any "catch-up" growth they may have been experienced.

Adult Height.

In Chapter III the arguments for using overall stature as an indicator of environmental conditions were presented. Some researchers feel overall stature, in terms of "small but healthy", is a suitable indicator of environment, while others disagree. For this research, evidence is presented to show that overall stature satisfactorily reveals the effects of environmental conditions. Climatic-morphological conditions, social status, disease, and nutritional inadequacies are among the most influential biocultural factors influencing the attainment of adult stature. Reduction in body size or "growth reduction" is commonly considered the major index of nutritional stress (Harrison et al, 1988). 190 The clim ate in the Ohio Valley and the Lake Erie area became cooler and w etter from A.D. 1300 to A.D. 1700 (Bowen 1992). Using the zoological rules (Bergmann’s and Allen’s) one would predict a decrease in the surface area and an increase in the volume for fauna in the region (Harrison et al, 1988). A compact body of this type would be relative short with respect to trunk and limbs. Using the climate as a factor, differences in stature would be expected to be gradual, with samples from earlier sites being taller than samples from later sites. Ordering of the sites from earliest to most recent results in the following site habitation sequence: SunWatch (ca A.D. 1200), Pearson (ca A.D. 1250), Anderson (ca A.D. 1275), Petersen (ca A.D. 1500), Indian Hills (ca A.D. 1550), Buffalo (ca A.D. 1625), and M adisonville (ca A.D. 1650). Comparison of the habitation sequence to the stature sequences in Table 16 (for either of the males or the females) does not support a gradual change in stature through time. Thus, the change in climate does not appear to have been of a magnitude to provoke an adaptive response in the Late Prehistoric samples. Adult stature has been used to identify variation within a population in terms of social status (Powell 1991). High status individuals are believed to have access to more and better nutritional food stuffs and are better able to fight disease. Consequently, these individuals would have a 191 greater chance of obtaining their full genetic potential. Thus, taller individuals are interpreted as belonging to a high status group, while shorter individuals are interpreted as belonging to a low status group. For this study, individual social status was not assessed in terras of stature. However a look at the variances for stature for the different samples shows the highest within sex variance to be for the Madisonville sample. This variation within the sex grouping may be a reflection of class differentiation, however before such a inference can be accepted more information about Madisonville cultural and skeletal collections is needed. It is possible the Big Man society, which has been purposed for the late Fort Ancient c u ltu re s (Pollack and Henderson 1992:291), would have recognized more class distinctions and could have resulted in greater variation within males and within females. For the Late Prehistoric samples stature variation among samples is manifest as sexual dimorphism. Humans are moderately sexual dimorphic, a phenomenon of body size variation between the sexes which is "complex, with behavioral, physiological, and anatomical dimensions" (White 1991:320). As with most human populations, all the Late Prehistoric sample males are taller than the Late Prehistoric females (Table 16). Some of the most important aspects of sexual dimorphism involve so ft tis s u e , making i t hard to reconstruct th is 192 phenomena from the hard tis s u e of a skeleton (S tin i 1985). The occurrence of muscular hypertrophy (rigidity) is one of the most common ways of assessing sexual dimorphism in prehistoric populations. This biomechanical approach to activity also is used to evaluate adaptation to shifts in subsistence patterns (Ruff and Larsen 1990; Bridges 1991 ; Larsen and Ruff 1991). However, since many b io lo g ical properties (i.e., weight, stature, lean body cells) represent "size" assessment for sexual dimorphism, stature also can be used to evaluate sexual dimorphism if one realizes its limitations. A comparison of the differences between the mean stature of males and females was made for each of the Late Prehistoric samples. The differences (in cm) observed are as follows: Anderson 10.3, Buffalo 10.9, Indian Hills 10.6, M adisonville 9.5, Pearson and Petersen 10.8, and SunWatch 13.1. The majority of the sites appear to center around a 10.7 cm difference. The greatest difference, 13.1 cm, occurs fo r SunWatch which is the e a r lie s t s it e , and the least difference, 9.5 cm, occurs for Madisonville which is the latest or most recent site. The differences between the mean stature of males and females from European Early Upper Paleolithic, Late Upper P a le o lith ic and M esolithic populations (Frayer 1981) and an Ohio Late Archaic (S c iu lli e t a l 1991) population were obtained. These populations utilized a hunting-gathering- 1 9 3 (fishing) economy, thus permitting a subsistence shift comparison to be made between these populations and the Late Prehistoric horticulturalists. The differences (in cm) observed for the hunting-gathering-(fishing) populations are as follows: Early Upper Paleolithic 12.9, Late Upper Paleolithic 17.7, Mesolithic 10.9, and Ohio Late Archaic 14.4. This supplementary comparison provides a larger time depth from which the pattern of sexual dimorphism can be evaluated. The general pattern which emerges is a trend from a higher degree of sexual dimorphism in hunting- gathering -fishing societies to a lower degree of sexual dimorphism in horticulturalist. Sexual dimorphism in size often is associated with sexual division of labor (Bridges 1991 ; Larsen and Ruff 1991). Hence, the greater the size difference between the sexes, the greater the difference in the types of activities or stresses between the sexes. Shifts in subsistence, in terms of hunting and gathering-horticultural comparisons, have shown many transformation in biocultural expression between the sexes. Modern hunting and gathering societies typically are shown to have adequate food supplies and a balance in nutrients resulting in a healthy lifestyle (Cassidy 1980). Horticultural/agricultural societies, in contrast, experience poorer health because of their inferior diet 1 9 4 (Cassidy 1980). The transition from hunting and gathering to horticulture results in a reduction in dietary proteins and fats, but an increase consumption of carbohydrates. Although the latter provides an adequate caloric intake, a low protein diet is an imbalanced diet which may lead to impaired disease resistance. Sexual dimorphism would be expected to be greater in hunting and gathering societies where the differences in activities between the sexes are greater. Males typically are the hunters and females are typically the gatherers; these tasks require d iffe re n t work loads on the body. A shift from hunting and gathering to horticulture could bring about a change in the work load between the males and females, where activities between the males and females possibly would be more a lik e . The more sim ila r work load would put the same type of stresses on both males and fem ales. The greater variation between males and females seen at SunWatch may represents a greater degree of the division of labor between the sexes at that site. Stable Carbon Isotope Ratio Analysis (SIRA) of human bone from SunWatch in d icates that maize constituted over 50% of the village population's d ie t (Conard 1985). Thus, the mixed economy of maize horticulture and hunting and gathering, and/or other activities which constitute distinction between male and female activity roles could potentially explain the high 195 level of sexual dimorphism. The reduction in the degree of sexual dimorphism for Madisonville, using the division of labor as a causal agent, could imply a less diverse activity schedule between males and females. Overall, a shift to a horticultural lifestyle would create less of a change in females since their daily activities would not be as dramatically altered as the male’s daily activities. Thus in looking at both early and late sites, female height would be expected to be more constant through time than male height. There is 3.7 cm difference in female height compared to a 6.1 cm difference in male height from the early to the late Late Prehistoric samples. These values were obtained by excluding the Petersen samples because of low sample size, but including Madisonville data which are known to contain individuals of short stature from both sexes. When Madisonville is excluded, females exhibit a 1.7 cm difference in height compared to a 3 cm difference in height in males. Either way, this stature comparison implies a greater difference in male stature when compared to female stature through time. Nutrition, outside of a change in subsistence, also has been identified as an evolutionary cause for sexual dimorphism (S tin i 1982). The anatom ical, physiological, and metabolic demands of pregnancy and la c ta tio n have been identified as triggering hormonal mechanisms to mediate the influence of nutritional stress on body size (Stini 1975). 196 These constraints placed on female growth and development have resulted in the "canalization" of size variability (Stini 1985). The hormonal mechanisms found in females are assumed to be lacking in males, thus allowing for a greater fluctuation in body size (Stini 1975). Stini (1985:221-222) notes that "virtually every measurable value (continuous traits) shows a higher frequency of extreme values occurring in m ales". Stini (1985:222) goes on to say "it appears that environmental stressors have a greater impact on male growth, development, and survival". Stini (1969:425), in an earlier study of morphological effect of protein deficiency, concluded that "the long-term effects of protein deprivation are more pronounced in males" than fem ales. The p attern of greater reduced height in the more recent Late Prehistoric populations may be a reflection of nutritional stress. Although both male and females may have experienced the same nutritional deficiencies, the consequences would have been more visible in the males’ stature which is known to be more fluctuating in times of stress. Some possible explanations beyond those just mentioned for male verses female stature differences would be the added stress of European contact. The effects of contact were negative and disruptive. Settled villages suffered high levels of mortality and morbidity, population losses from disease and warfare, and social deterioration 197 (Ramenofsky 1987). A common feature of the Late Prehistoric settlements considered in this study is the presence of stockades which are interpreted as a form of defense for the villages. The conflict endured may have had a greater impact on males as their responsibility for defending the village against raids would have increased with the sedentary lifestyle (Krause 1972). Disease is known to influence adult height. The healthier an individual is, the better the chances are that that individual will obtain his or her full genetic potential for stature. Disease conditions must be assessed to better understand stature variation between the samples. Levels of disease are known to have increased with European contract (Dobyns 1983; Ramenofsky 1987). A higher disease load would be expected for the postcontact, Late Prehistoric populations; thus shorter, less healthy individuals. Anderson, Pearson, and SunWatch are precontact sites while Buffalo, Indian Hills, Madisonville and Petersen are postcontact sites. Examination of Table 16 reveals that the precontact sites exhibit the taller stature, while the postcontact sites exhibit the shortest stature. Noticeably, Petersen and Madisonville are 2 to 6 cm on average shorter for males and females than the other samples. The results obtained from Petersen should be considered in light of the small sample. 198 Review of Research Objectives

The research objectives described in Chapter I now will be examined. An attempt will be made to answer the questions which were presented throughout that chapter. Does each cultural group (tradition) represent a distinct biological population? Distinct biological groups are not easily identified from the biological data. In fact the sim ilarities between the Fort Ancient and Sandusky samples are strong enough to allow all samples to be identified as descendants of one ancestral population, which has diversified to some degree over time and as a result of what appears as random fa c to rs . Is each tra d itio n an indigenous group or is one (or both) group(s) the result of a migration of peoples from other regions into Ohio? The results of shape analyses suggest a common ancestry, thus at one time the forebears of these groups probably were in closer proximity to one another. Do one or both represent fusion or fission between local and non-local cultural or biological populations? The biology suggests fusion in terms of shape data, but suggests fission in terms of size, discrete traits, and dental disease, A comparative investigation on samples predating the Late Prehistoric and on samples with the same dates but from different regions would aid in answering questions of origins of these traditions. 199 The inquiry in to health and n u tritio n was another interest of this research. Since the populations in question represent the earliest maize horticulturalists in the area information about dietary change was available. This major cultural shift would be expected to be reflected in changes in diet, nutrition, and health status. The results of this study clearly show a pattern of stress which correlated to a high dependency on maize for the Late Prehistoric samples studied. Antemortem tooth loss and caries frequencies increase through time, catchup growth is cut sh o rt, and adult s ta tu re i s reduced. The idea that European contact had devastating effects on Native North American’s health was appraised, since both pre- and post-contact populations were investigated in this study. Differences in pre- and post-contact were identified for cranial and postcranial data, as well as dental pathologies. The patterns observed for pre- and post- contact populations mirror the transitions seen in the hunting-gathering-fishing societies to mixed economies to horticulturalists. Since the study populations were experiencing both a shift in subsistence and the European contact it is difficult to separate the effects each had on the populations. The hypotheses to be addressed in the research were:

#1 Are populations from archaeological sites which are designated as the same cultural manifestation genetically homogeneous. 200 Ho If skeletal samples representative of a particular archaeological culture are genetically homogeneous, then biological distance values will reveal no statistically significant difference between samples. Hi If skeletal samples representative of a particular archaeological culture are not genetically homogeneous, then biological distance will reveal statistically significant differences between samples. #2 Are maize horticulturalists under the same sorts of stress?

H q If indicators of stress are the same in magnitude and pattern among all the maize horticulturalists, then they are experiencing the same types of stress. Hi If indicators of stress are different in magnitude and pattern among the maize horticulturalists, then they are experiencing different types of stress.

For the first question, the null hypothesis can be either accepted or rejected depending on the data used to test the hypotheses. All the study populations were found to be genetically homogeneous at a level which would suggest a common ancestry using cranial shape comparison. Thus, the hypothesis that populations from archaeological sites which are designated as the same cultural manifestation are g en etically homogeneous must be accepted. In te re stin g , too, is the observation that different cultural manifestations (i.e., Sandusky and Fort Ancient) were found to be genetically homogeneous. These same populations were found to be genetically heterogeneous using the cranial size and discrete trait comparison results, even within and between the traditions. 201 It appears then that the Fort Ancient and Sandusky traditions represent diversified descendants from a common ancestral stock. The structure of the biological diversity between Late Prehistoric samples using cranial size and cranial discrete traits appears to be associated with time for size and to have no association with geography for either size or trait expression. One may ask: So what do these results really tell use about biological diversity? The use of both cranial metric and nonmetric data in this investigation allows for a more thorough understanding of biological diversity. A common biological affinity was established, yet variation in the biological makeup also was detected for the Late Prehistoric populations. The microevolutionary difference in size, for both cranial metrics and adult stature, probably reflect stress changes to environmental pressures. Size would have a greater response to biocultural pressures than would shape. The second question: Are maize horticulturalist under the same sorts of stress? No, but. The pattern and magnitude of stress indicators was not the same for all the samples, strictly speaking. However, a consistent pattern of health emerges which best can be explained as a reflection of change in cultural values and identities with a shift towards a more intensive subsistence strategy based on maize and an increased amount of dissension due to 202 European contact. Moving from early to late Late Prehistoric samples there is an increase in the magnitude of dental disease and a reduction in attained adult height. These patterns of poor health are in accord with other investigations of biocultural modifications during economic change. The only exception to these disease-health patterns is the pattern seen for the Madisonville sample. Madisonville is significantly shorter than the other samples and has what appears to be a better pattern of dental health. It is possible that the adult height difference which separates Madisonville from the other samples is more of an indicator of inheritance rather than of nutrition.

Concluding Remarks

This research has provided one of the first extensive surveys and comparisons of biological data of Late P re h isto ric populations in the Ohio area. Over 1900 individuals were assessed for data collection (Anderson = 84, Buffalo = 669, Madisonville = 430, Pearson = 546, and SunWatch = 167; w ith Indian H ills and Petersen to ta ls varying because of their ossuary state). In addition to the immense number of indiv id u als investigated, many of the samples used in this investigation have qualities which are noteworthy. The Buffalo and Madisonville sites contain two of the largest known Fort 203 Ancient burial populations, while Pearson is the largest burial population known to the Sandusky tradition. SunWatch is especially remarkable since it is one of the best preserved and most completely excavated and analyzed Late Prehistoric archaeological village sites in the Eastern Woodlands. The information provided in Chapter II, about the history of the different skeletal samples, made obvious a number of items of concern. First, the lack of acquirable published reports on the skeletal populations studied made assembling a comprehensive review of the sites difficult. Being familiar with the site and previous studies on the collection under investigation is important. Next, the discrepancies noticed between observation made in this study verses observations made in published reports is another concern. Upon finishing this project, it has become apparent that the cultural and biological data from a single site should be investigated in their totality before parts of the whole are used in large collective studies. Or that, a comprehensive study of a sites resources would eliminate confusion about such thing as number of individuals excavated verse number of individuals encountered during excavation but not excavated verse number of indiv id u als in a collection. Information about where archaeological materials are archived also would become evident. 204 In a time when reburial is a issue for both cultural and biological collections many of these details will be brought to light though reinventorying, but unfortunately many more details will be lost once items are reburied. It is important that skilled anthropologist take the time to investigate the vast quantities of resources before they are gone forever through reburial or before the details of the excavation notes and collections are lost in the bowels of an archive facility. The Madisonville site is a case in point. The Madisonville collection currently is not at risk for reburial, but currently is unusable except for generalization. This is in no way the fault of the museums which house the Madisonville collections. The volume of data available for both cultural and biological research is overwhelming. Researchers are involved with different aspect of the information from Madisonville, however a group effort is necessary to decipher the decades worth of fieldnotes and hundred of thousands of artifacts and thousands of burials. An individual is simply unable to manage all the details, such an effort would require a team of researchers. The goals of this project were not compromised because the problem just mentioned, however problems of this type are in need of being addressed in the anthropological literature. Whenever bioarchaeologists begin to investigate 205 a skeletal population they realize the limitations of dealing with an archaeological collection. Developing a demographic profile for the population represented in a cemetery depends on a series of assumptions, from duration of use of the cemetery to the idea that the cemetery represent all soci-economic classes which made up the living population. Recovery of a complete cemetery is rare, in many investigations, the researcher must be satisfied with small samples which they then assume to be representative of the population. The sample sizes use in this research fortunately were large and hopefully were representative of the populations from which they came. Now that the appeal for more and thorough data recovery of existing collections has been made, justification for this study of multiple sites almost seem necessary. Comparative studies has long been the an intricate part of anthropology. In order to understand cultural and b io lo g ic a l d iv e rsity , the element fo r and of change must be identified and what other way is there but to have a number of items (containing the elements) with which to compare each other. The research problems identified in Chapter I would not have been possible w ithout a number of s ite s with which to compare each other. So, although single site description are important, it is equally as meaningful to have comparative studies of numerous sites and complexes. 206 The impact of this research would not have been as significant had only Fort Ancient Tradition cultural manifestations been considered. By including both Fort Ancient and Sandusky cultural manifestations the obvious cultural differences were lost when the biological data were employed. This is not to say the biological data are better and tell you more, but rather that biological data are equally as important as cultural data in our reconstruction of the past. Both cultural and biological data provide independent forms of information which can be used to clarify question regarding antiquity. Thus, a biocultural approach to prehistory is superior to either an exclusively cultural or biological approach. To disregard either cultural or biological data obscures the reality of the symbiotic relationship that exists between culture and biology. 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CRANIAL METRIC DESCRIPTIONS

226 227 Biasterionic Breadth The distance from asterion to asterion taken with sliding calipers. Frontal Arc The distance from nasion to bregma taken in the midsagittal plane with tape measure. Frontal Chord The distance from nasion to bregma taken in the midsagittal plane with sliding calipers. Maximum Cranial Breadth The maximum width of the skull perpendicular to the midsagittal plane. This measure is taken with spreading c a lip e rs. Maximum Cranial Length The distance from glabella to opisthocranion (the most posteriorly protruding point on the back of the braincase, which usually f a l l s on the superior squama of the o c c ip ita l) in the midsagittal plane. This is measured in a straight line with spreading calipers. Minimum Frontal Breadth The least distance between the two frontotemporale. This measure is taken with sliding c a lip e rs. Occipital Arc The distance from lambda to opisthion taken in the midsagittal plane with a tape measure. Occipital Chord The distance from lambda to opisthion taken in the midsagittal plane with sliding calipers. Parietal Arc The distance from bregma to lambda taken in the midsagittal plane with tape measure. Parietal Chord The distance from bregma to lambda taken in the midsagittal plane with sliding calipers. Porlon to Bregma The distance from porion to bregma taken with sliding c a lip e rs. 228 Porion to Lambda The distance from porion to lambda taken with sliding c a lip e rs. Porion to Nasion The distance from porion to nasion taken with sliding c a lip e rs. Skull Height The distance from basion to bregma taken with spreading c a lip e rs. APPENDIX B

POSTCRANIAL METRIC DESCRIPTION

229 230 Maximum Length of the Humerus The distance from the most superior point on the head of the humerus to the mostinferior point on the trochlea taken with an osteometric board. Maximum Vertlcai Diameter of the Head of the Humerus The distance between the most superior and inferior points on the border of the articular surface of the humerus head. This distance is taken with sliding calipers. Minimum Circumference of the Humerus The minimum circumference measured towards the distal end of the shaft using a tape measure. Maximum Lei^th of the Femur The distance from the most superior point on the head of the femur to the most inferior point on the distal condyles taken with an osteometric board. Bfcondylar iength of the Femur The distance from the most superior point on the head of the femur to a plane drawn along the inferior surface of the distal condyles taken with an osteometric board. Maximum Diameter of the Head of the Fémur The maximum diameter of the femur head measured on the border of the articular surface using a sliding caliper. Femur Midshaft Circumference The circumference measured at the midpoint on the diaphysis using a tape measure. Maximum Lei^th of the Tibia The distance from the most superior point of the intercondylar eminence of the tibia to the tip of the medial malleolus taken with an osteometric board. Standard Tibia The distance from the superior articular surface of the lateral condyle of the tibia to the tip of the medial malleolus taken with an osteometric board. Fbot Height The distance obtained by placing the talus on top of the calcaneus and measuring from the superior surface of the talus to the inferior surface of the calcaneus. This measure is taken with an osteometric board. 231 Vertebral Column The distance from midpoint of the superior border of the vertebral body to the midpoint of the inferior border of the vertebral body taken in the anterior dimension (this measure is taken for cervical 3-7, thoracic 1-12, and lumbar 1-5). The axis measurement is taken from the superior margin of the dens epistrophei to the midpoint of the inferior body border. The first sacral body is measured from the midpoint of the promontory to the midpoint of the first transverse line. These measures are taken with sliding calipers. Maximum Diaphysial Lengths The distance from the most superior point of the metaphysis on the proximal end to the most inferior point of the metaphysis on the distal end of a long bone taken prior to epiphyseal union. Height of the Scapula The maximum distance from the superior to the inferior border of the scapula. Breadth of the Ilium The distance between the anteriosuperior iliac spine to the posterosuperior iliac spine of the ilium prior to fusion with the ischium or pubis. APPENDIX C

CRANIAL DISCRETE TRAIT DESCRIPTIONS

232 233 Accessory Mental Foramen The mental foramen is the large, sometimes multiple foramen located on the lateral corpus surface, near midcorpus, below the premolar region. This foramen transmits the mental vessels and nerves. (From White 1991). When multiple foramina are present the trait of accessory foramen is scored as present. This trait is assessed on both right and left sides. Asterionic Ossicles The junction of the temporoparietal suture and the lambdoid suture is termed asterion. An ossicle (wormian bone) may occur bilaterally or unilaterally in the asterionic region superior to the parietomastoid suture. These ossicles vary in size but are normally triangular in shape and approximately 1 cm on a sid e. (Modified from El- Najjar and McWilliams 1978). Hauser and De Stefano (1989) report in their review of epigenetic traits that asterionic ossicles tend to be reported in males more often than females, decline in their occurrence with age, and do not appear to have a side preference in cases of asymmetrical expression. In this study ossicles at asterion are scored as present or absent, by side. Coronal Ossicles The coronal suture traverses the skull from one side to the other and connects the posterior edge of the frontal and the anterior borders of the parietal bones. Ossicles may occur in the coronal suture. The bones themselves are usually small and may be single or multiple. (Modified from Hauser and De Stefano 1989). Sex differences in the occurrence of coronal ossicles are not consistently reported; some report higher frequencies in males, while other report higher frequencies in females (Hauser and De Stefano 1989). Coronal ossicles were scoreo as present if any ossicle was observed along the coronal suture. This trait is scored only in crania with a complete coronal su tu re. Foramen Huschke Foramen Huschke also is synonymous with tympanic dehiscence and foramen tympanicum. The floor of the external acoustic meatus is formed by the tympanic plate, whose lateral free margin is an irregular dentate shaped. Very rarely there may be complete absence of the tympanic plate. More frequently a dehiscence in the medial third occurs that may vary from a pinhole-size aperture to large defects. All these conditions are summarized in the term tympanic dehiscence. (From Hauser and De Stefano 1989:143). Hauser and De Stefano also state that no consistent sexual dimorphism or age specific data are reported for the 234 expression of foreman Huschke, and that asymmetrical expression of the t r a i t is predominately reported. Foramen Huschke in this study is scored as either present or absent, by side. Foramen Ovale Configuration Foramen ovale is located p o sterio r to the foramen rotundum on each side of the greater wing of the sphenoid. The foramina transmit the mandibular nerves, accessory meningeal arteries and a vein which connects the cavernous sinus with the pterygoid plexus. (Modified from Hauser and De Stefano 1989). On occasion, foramen ovale is incomplete on the posterolateral wall so that it is continuous with foramen spinosum. Hauser and De Stefano (1989) found that in the majority of investigations there is no difference in incidence between sexes for incomplete ovale foramina. The tra it also appeared highly asymmetrical, although some reported symmetric occurrences. Age dependence was similarly reported variable in the literature, in this study, the foramen ovale is scored as complete or incomplete, by side. Foramen Spinosum Configuration Foramen spinosum is located on the g re a te r wing of the sphenoid just posterolateral to foramen ovale. The foramina spinosa are set in the posteroinferior spines of the sphenoid, very close to the temporal bones. They transmit the middle meningeal vessels and branches from the mandibular nerves. The posterior wall of foramen spinosum is sometimes lacking. (Modified from Hauser and De Stefano, 1989). Hauser and De Stefano found that most authors agree that there is a significantly higher frequency of incomplete foramen spinosa for females. They found variable results for both the asymmetrical occurrence and the age dependence of the t r a i t . Foramen spinosum is thus scored as e ith e r complete or incomplete, by side. Hypoglossal Canal Configuration The hypoglossal canals are tunnels through the base of the occipital, anterior to and beneath the occipital condyles. These canals give exit to the hypoglossal nerves and entrance to arteries. The canal may be a single foramen, or it may be bifurcated giving the appearance of a double foramen. (Modified from El-Najjar and MoWilliams 1978). Generally, no sexual dimorphism in the expression of the bridging is noted. The foramen is scored as either sin g le or double, by side. Ungula Bridge The lingula is a sharp, variable shaped projection at the edge of the mandibular foramen. It is the attachment 235 point for the sphenotnandibular ligament. (From White 1991). On occasion, the lingula will cross over and connect to the ramus forming a bridge or arch. The lingula bridge is scored by side as either present or absent. Mastoid Foramen Locus The mastoid foramen is located near the posterior edge of the mastoid process along the occipitomastoid suture. These foramina transmit a small branch of the occipital artery, which supplies the dura mater, the diploe, and the mastoid air cells. The foramen may be single or multiple and may be located in the occipitomastoid suture or exsutural on either the mastoid portion of the temporal or the occipital. It also may be absent. (Modified from El- Najjar and McWilliams 1978). For this study the mastoid is scored as either sutural or exsutural. Mylohyoid Bridge The mylohyoid groove crosses the medial ramus surface, running anteroinferiorly from the edge of the mandibular foramen. It lodges the mylohyoid vessels and nerves. (From White 1991). On occasion, a bony bridge will cross over the groove. The mylohyoid bridge is scored by side as either present or absent. The bridge must be complete to be scored as present. Occipital Condyle Form The occipital condyles are located on either side of the foramen magnum on the occipital. The articular surface fits into the facets of the atlas vertebra. The condyles vary in size and form. Occasionally, the articular surface is divided into two distinct facets. Condyle form in this study is scored as either a single or double facet, by side. Parietal Foramen The parietal or obelionin foramina are located on the parietal bones lateral to the sagittal suture and slightly anterior to lambda. They transmit an emissary vein (Santorini’s vein) through the parietal which connects the occipital veins with the nearby superior sagittal sinus. (Modified from Hauser and De Stefano 1989). According to Hauser and De Stefano, sex differences in the expression of parietal foramina show negative results, with both male and females being reported as having high frequencies. They also report the tendency in the literature to report no change in appearance between young and old ad u lts. Hauser and De Stefano note symmetry is significant according to most authors. Parietal foramina are scored by side as present or absent. 236 Parietal Notch Bone In the fe tu s the temporal bone i s composed of two parts, the petrous portion and the squamous portion or fan like superior part of the bone. Where the squamosal suture meets the temporoparietal suture a notch may be formed. This notch apparently represents advancement of the parietal bone into the temporosquamosal suture before the union of the two parts of the temporal at approximately the sixth month in utero. The notch may be absent or i t may p e rs is t in varying depths. It also may contain a ossicle. (From El-Najjar and McWilliams 1978). The appearance of an ossicle in the notch is scored as present or absent, by sid e. Postcondylar Canal Configuration Posterior to the occipital condyles are fossae. These ectocranial depressions receive the posterior margin of the superior facet of the atlas vertebra when the head is bent backwards. (Modified from White 1991). A canal transmitting an emissary vein from the sigmoid sinus usually pierces the condylar fossa. (Modified from El-Najjar and McWilliams 1978). The appearance of the canal is scored as present or absent, by sid e. Precondylar Tubercle Immediately anterior and medial to the occipital condyle and posterior to the site of the pharyngeal fossa, a bony tubercle my occur. A precondylar tubercle is scored as present or absent. Superior Sagittal Sulcus Direction The occipital sagittal sulcus passes superiorly from the internal occipital protuberance. It is a deep endocranial groove marking the posterior extension of the sagittal sinus, a major blood drainage pathway from the brain. (From White 1991). The direction of the sulcus is scored as right, left, equal (both directions) or straight. Supraorbital Foramen Configuration The su p ra o rb ita l foramen or notch is located on the medial one third of the superior margin of the orbit. It permits passage of fibers of the corrugator supercilius nerve exiting from the roof of the orbit to the external surface of the frontal bone. The passage may take the form of a broad shallow notch, a narrow deep notch approaching a closed foramen, or a foramen. The passage is formed by ossification of a "supraorbital ligament" crossing the notch. Variations include an absence of supraorbital osseous structures, a notch, a foramen plus a notch, or multiple notches plus a foramen. The complex occurring above one eye is often different from that found above the 237 Other. (Modified from El-Najjar and McWilliams 1978). Hauser and De Stefano (1989) report no significant d ifferen ces between the two sexes and the two sid es, nor did they note any tendency for preferential side combinations. The su p ra o rb ita l configuration was scored by side as e ith e r a foramen or a notch. If both a foramen and a notch occurs, the trait is scored as a foramen. APPENDIX D

VARIANCE-COVARIANCE MATRICES OF CRANIAL METRICS

238 TABLE 61. Variance-covariance matrix of cranial metrics for Anderson males and females.

ANDERSON Biaster- Frontal Frontal Maximum Maximum Minimum occipital occipital Parietal Parietal Porion Porion Porion ionio Arc Chord Breadth Length Frontal Arc Chord Arc Chord to to to 1 9 f & 175 Breadth Breadth Bregma Lambda Nasion Bl«st

8 CD TABLE 62. Variance-covariance matrix of cranial metrics for Anderson males.

ANDERSON Biaater- Frontal Frontal Maximum Maximum Minimum Occipital Occipital Parietal Parietal Porion Porion Porion ionic Arc Chord Breadth Length Frontal Arc Chord Arc Chord to to to 195 Breadth Breadth Bregma Lambda Nasion Blasttrlonlc Breadth 20.92 Frontal Arc 5 .3 9 33 .47 Frontal Chord 2 .4 9 3 0 .03 3 3 .59 NaxiiMm Breadth -2 .0 5 -2 .9 3 -0 .1 8 23.67 Maximum Length 13.44 35.33 36.00 -13.67 76.33 Minimum Frontal Breadth 9.14 11.35 12.32 3.73 30.22 57.60 occipital Are 1.27 31.45 24.21 -16.80 46.78 -0.98 130.43 occipital Chord 0 .5 8 14.09 9.41 -7 .3 4 22.33 -4.71 85.98 60.71 Parietal Arc -3 .2 4 6.89 10.73 9.58 22.83 31.40 -33.11 -28.23 66.26 Parietal Chord -4 .8 8 8.07 10.70 5.40 24.17 25.99 -13.48 -15.10 52.34 46.04 Porion to Bregma 4.82 8.76 90.1 1.13 22.50 7.23 18.81 11.55 7.34 7 .1 7 14.32 Porion to Lambda 4.14 19.44 17.28 4 .2 7 25.78 6.75 42.62 27.37 4.96 6 .6 9 13.02 25,47 Porion to Nation 9.02 5.09 9.96 -1.29 27.22 11.68 -10.24 -11.40 22.49 17.51 11.39 2.98 30.60

ro Ê TABLE 63. Variance-covariance matrix of cranial metrics for Anderson females.

Blatter. Frontal Frontal Maximum Maximum Minimum Oooipltal Occipital Parietal Parietal Porion Porion ANDERSON ionic Arc Chord Breadth Length Frontal Arc Chord Arc Chord to to to 179 Breadth Breadth Bregma Lambda Nation Blasterlonlo Breadth 27.74 Frontal Arc 11.79 39.24 Frontal Chord 6 .0 3 23.92 27.22 Maximum Breadth 7.90 -4.25 3.08 24.40 Maximum Length 0 .3 3 10.06 1.24 -21.60 71.53 Minimum Frontal Breadth 2 .8 0 5 .7 8 3 .8 8 -6 .2 6 12.55 9.01 occipital Are -6 .7 0 7.67 -3.41 -9.54 12.90 8.87 52.99 occipital Chord -2 .4 7 16.04 2.51 -4.54 -1.04 4 .8 3 31.78 3 3.82 Parietal Arc 9.11 21.54 15.78 -9.67 50.21 11.18 2.11 -4 .6 0 75.11 Parietal Chord 9 .8 9 17.09 9.12 -8.80 45.58 9.62 6.64 -2.08 62.76 59.01 Porion to Bregma 1.20 7.64 4 .1 0 -1.27 10.60 2.89 4.70 3.9 7 2.51 2.36 8.2 4 Porion to Lambda 1.13 -6.51 -4.71 1.15 9 .5 3 0 .7 7 5 .5 7 -0.63 -2.56 -2.08 4 .1 2 18.34 Porion to Nation -7 .5 3 7.76 5.40 -10.56 31.19 9.00 16.47 9.86 15.35 15.00 7.59 3.27 29.10

lO 4 k TABLE 64. Variance-covariance matrix of cranial metrics for Buffalo males and females.

BUFFALO Blaster- Frontal Frontal Maximum Maximum Minimum occipital Occipital Parietal Parietal Porion Porion Porion Ionic Arc Chord Breadth Length Frontal Arc Chord Arc Chord to to to â & 9 - 29 Breadth Breadth Bregma Lambda Haslon Blasterlonlo Breadth 22.15 Frontal Arc 18.06 58.22 Frontal Chord 14.14 38.83 32.93 Maxliaun Breadth 26.12 32.48 25.27 54.95 Maximum Length 9 .6 6 16.55 14.37 9.90 43.35 Minimum Frontal Breadth 12.02 16.71 11.34 23.85 10.36 27.45 occipital Arch 19.32 21.06 18.07 19.50 16.87 24.72 77.39 Occipital Chord 13.96 21.36 31.69 19.37 13.18 23.30 31.69 42.69 Parietal Arc -1.02 0.24 -21.41 5.00 1.28 -3.27 -21.41 -12.92 39.12 Parietal Chord -1 .6 4 4 .4 0 -17.76 7.04 1.26 1 .4 7 -17.76 -4.18 22.08 22.82 Porion to Bregma 5 .9 2 22.55 4 .5 3 18.77 13.62 7.1 6 4.53 8.08 7.13 6 .8 2 22.58 Porion to Lambda 9.13 16.41 19.79 14.96 12.19 14.71 19.79 20.02 -7 .8 9 -1 .1 5 10.37 23.14 Porion to Naelon 0 .5 8 5 .5 4 -1.81 5.32 22.51 -3.25 -1.81 -2.60 -7 .8 3 -0 .5 0 7.42 1.33 37.59

ro to TABLE 65. Variance-covariance matrix of cranial metrics for Buffalo males.

BUFFALO Blaater- Frontal Frontal Maximum Maximum Minimum Occipital Occipital Parietal Parietal Porion Porion Porion lonlc Arc Chord Breadth Length Frontal Arc Chord Arc Chord to to to 133 Breadth Breadth Bregma Lambda Nasion Biastarlonic Breadth 21.27 Frontal Are 18.82 16.02 Frontal Chord 14.57 3 7.08 2 8.98 uaxlmum Breadth 26.27 45.17 34.09 6 5.97 MaxUaun Length 4.11 14.56 7.81 7.44 49.60 Mlnlenan Frontal Breadth 14.77 28.53 19.94 35.81 17.30 31.83 Occipital Are 22.10 15.08 14.49 29.97 14.51 3 0.40 7 1.78 Occipital Chord 18.56 22.66 47.05 22.96 19.13 26.17 4 7 .05 50.64 Parietal Arc 2 .43 13.36 -19.36 7.71 5 .0 7 2 .3 0 -8 .6 4 -19.36 42.43 Parietal Chord 4.13 20.52 13.10 12.10 6 .7 7 6 .8 9 -10.30 -8.50 20.86 22.35 Porion to Bregma 6 .2 0 25.61 19.07 22.13 15.54 11.91 6 .3 2 5 .7 8 8.14 4.92 24.41 Porion to Lambda 18.11 21.50 138.37 28.31 10.91 24.03 27.14 28.59 -12.07 -1 .2 0 11.04 32.50 Porion to Nation -12.94 -7 .6 9 -9 .49 -8 .1 7 19.73 -2.10 -11.53 -5.33 -13.43 1.10 -3 .2 6 -3 .2 6 36.26

& TABLE 66. Variance-covariance matrix of cranial metrics for Buffalo females.

BUFFALO Blaster- Front.l Frontal Maximum Maximum Minimum Occipital occipital Parietal Parietal Porion Porion Porion ionic Arc Chord Breadth Length Frontal Aro Chord Arc Chord to to to 149 Breadth Breadth Bregma Lambda Naelon Blasterlonlo Breadth 23.65 Frontal Arc 16.00 51.69 Frontal Chord 13.70 41.31 38.75 Maximum Breadth 25.82 16.38 15.74 43.30 Maximum Length 15.52 18.00 21.74 11.68 37.14 Minimum Frontal Breadth 11.14 7.92 4 .0 2 15.19 4 .5 7 23.67 Occipital Aro 14.89 22.46 20.60 4.25 18.48 23.47 81.92 occipital Chord 8.92 19.00 10.92 14.85 6 .9 2 23.15 14.65 3 6.27 Parietal Arc -3 .9 6 -11.92 -6 .2 4 4 .2 5 -2 .0 6 -11.14 -34.62 -6.12 37.92 Parietal Chord -6 .9 0 -10.15 -5.35 4.16 -3.76 -5.34 -24.41 1.23 24.29 24.07 Porion to Bregma 6.02 20.85 22.65 16.47 12.55 2.66 2.79 11.12 6 .6 3 9 .4 5 22.34 Porion to Lambda 1.99 11.46 13.25 1.11 14.26 6 .1 3 12.55 12.00 -3.76 -0.88 10.43 14.75 Porion to Naelon 13.44 16.23 20.43 16,99 25.91 2.97 4.06 -1.81 -1.09 -0.06 14.05 5 .8 8 39.26 TABLE 67. Variance-covariance matrix of cranial metrics for Indian Hills males and females,

INDIAN HILLS B laster- Frontal Frontal Maximum Maximum Minimum O ccipital O ccip ital P a rie ta l P a rie ta l Porion Porion Porion lonlo Arc Chord Breadth Length Frontal Arc Chord Arc Chord to to to df + 9 = 11 Breadth Breadth Bregma Lambda Naelon Bl»terlonlo Breadth 26.65 Frontal Arc -4.51 26.45 Fro n tal Chord ■0.06 12.08 13.87 Haxinua Breadth 19.17 7.86 13.45 51.89 Haxlnu* Length 6 .5 3 15.14 14.55 1.41 37.89 Klnimua F rontal Breadth 5.3 2 6.91 4.46 5 .0 3 2.8 7 7.62 o c c ip ita l Arc 17.85 -20.17 7.69 8 .4 8 16.02 3.7 5 92.16 O ccip ital Chord 11.81 6.85 6.72 7.54 23.06 2.59 21.47 26.65 F a rle ta l Are 0.81 -4.55 -4.98 -10.16 1 .8 6 -4.01 -8.53 -4.05 18.05 P a rie ta l Chord 5.77 2.06 -9.25 -27.41 19.21 -5 .4 7 -15.42 14.14 20.94 58.09

Porion to Bregma 2 .9 0 16.25 17.82 19.44 21.96 4.99 10.67 12.95 -3 .6 5 - 8 .6 6 27.85 Porion to Laaibda 13.95 2.77 4.81 14.82 16.08 -0.65 11.54 20.53 -1.87 9.32 13.83 28.56 Porion to Naelon 13.15 17.13 17.39 20.28 23.32 3.15 17.66 22.57 -14.13 -4.02 23.27 20.34 39.76

Ü 1 TABLE 68. Variance-covariance matrix of cranial metrics for Madisonville males and females.

MADISONVILLE Blaster- Frontal Frontal Maximum Maximum Minimum Occipital Occipital Parietal Parietal Porion Porion 1 Porion Ionic Arc Chord Breadth Length Frontal Aro Chord Arc Chord to to 1 to A7S & 489 Breadth Breadth Bregma Lambda 1 Naelon Blaittrlonlo Breadth 30.40 Frontal Arc 10.11 31.21 Frontal Chord 10.88 21.40 18.89 Maximum Breadth 23.42 16.00 13.53 35.70 Maximum Length 16.42 17.79 18.19 12.08 4 7 .0 7 Minimum Frontal Breadth 9.7 0 7 .5 0 6 .3 0 8.78 10.44 14.38 Occipital Arc 12.58 5 .4 2 7.40 11.86 27.18 10.30 39.78 Occipital Chord 10.33 4.30 4.70 8.74 12 .87 5 .2 8 22.31 27.81 Parietal Aro 2.92 11.10 9.61 1.12 24.15 2.89 3.82 -0.86 49.89 Parietal Chord 4 .1 3 6 .8 4 7.21 1.19 20.85 4.09 7.11 2 .0 8 3 2.78 27.54 Porion to Bregma 13.89 15.28 13.28 16.64 16.04 8.22 9 .9 5 9 .3 0 13.64 10.25 22.25 Porion to Lambda 16.95 9 .3 0 9 .8 0 14.64 20.34 6.71 19.01 13.34 7.80 7.83 13.76 22.73 Porion to Naelon 11.67 12.53 11.42 14.65 17.95 7.64 10.69 9.52 8.48 6.87 14.38 10.24 20.93

ro o> TABLE 69. Variance-covariance matrix of cranial metrics for Madisonville males.

Blaster- Front.l Frontal Uulmm Uaxlnun uininjn occipital Occipital Parietal Parietal Porion Porion Porion MADISONVILLE Ionic ATO Chord Brtadth Langth Frontal Arc Chord Arc Chord to to to 4 7 a Breadth Brtadth Bregiea Lambda Nation Blasterlonle Breadth 3 0.17 Frontal Arc 0 .6 9 30.15 Frontal Chord 0 ,5 6 20.68 18.41 Maximum Breadth 2.86 14.19 12.75 29.45 Maximum Length 3.51 18.14 16.92 12.65 47.86 Minimum Frontal Breadth -1 .6 8 5 .2 8 3 .5 0 6 .6 9 8.76 15.11 Occipital Arc 2 .8 5 8.09 7 .8 7 12.44 3 2.07 14.19 43.03 Occipital Chord 30.1 4 .93 4 .0 9 5 .5 2 13.76 5 .5 3 22.11 32.61 Parietal Aro -2 .3 7 3 .8 6 4 ,3 8 0 .2 9 18.81 -0 .4 2 4 .0 0 -1 .8 0 40.92 Parietal Chord -0,85 -0 ,5 8 2.86 0.47 19.36 1.32 9 .4 8 1 .96 27.53 25.43 Porion to Bregma 15.29 11.57 11.42 15.10 15.29 7.71 13.27 9.81 11.24 8 .98 23.80 Porion to Lambda 17.55 10.04 9 .3 3 14.73 21.64 7.14 22.82 12.13 8 .45 9.18 13.98 24.82 Porion to Naelon 10.60 9.61 8.56 10.81 18.20 5 .8 3 13.65 8.63 4.41 4.10 12.63 8.94 15.89 TABLE 70. Variance-covariance matrix of cranial metrics for Madisonville females.

MADISONVILLE Blaster- Frontal Frontal Maximum Maximum Minimum o c c ip ita l Occipital Parietal Parietal Porion Porion ienie Are Chord Breadth Length Frontal Arc Chord Arc Chord to to to 4 8 ? Breadth Breadth Bregma Lambda Naelon Bla.ttrlDnlo 23.64 Frontal Arc 2.79 2 7.22 Frontal Chord 4.09 16.83 14.00 Haxtiawi Breadth 19.32 13.43 9 .8 6 38.70 Haxtnia length 6.03 9.22 11.15 4.69 34.30 Minimum Frontal Breadth 4 .1 8 4.31 3.59 6.44 3 .9 4 38.70 Occipital Arc 9.81 4.02 8.21 12.44 24.61 7.77 37.24 occipital Chord 10.07 3 .8 5 5 .4 7 12.13 12.37 5.22 22.98 23.71 Parietal Arc -2 .4 9 11.49 7.94 -3 .7 6 19.41 -0 .5 6 5 .0 5 0 .1 3 51.28 Parietal Chord -1 .6 4 8 .7 7 6.10 -2.60 14.46 3 .5 9 5 .9 9 2 .3 3 31.92 24.91 Porion to Bregma 6.60 13.87 9.98 14.07 8.99 3 .6 7 7.93 9 .0 7 9 .3 6 6.5 4 16.14 Porion to Lambda 12.40 5.04 6.70 11.48 13.86 2.80 16.39 14.86 2.78 3 .0 7 10.31 18.72 Porion to Naelon 2 .9 5 7.01 5.75 11.58 5 .0 0 1.15 9 .6 6 10.71 2.10 1.39 6.60 6 .0 4 13.14

00 TABLE 71. Variance-covariance matrix of cranial metrics for Pearson males and females.

PEARSON Biacter- Frontal Frontal Maximum Maximum Minimum Occipital occipital parietal Parietal Porion Porion Porion ionio Arc Chord Breadth Length Frontal Arc Chord Arc Chord to to to W & 239 Breadth Breadth Bregma Lambda Naelon Blasterlonlc Brtadth 24.00 Frontal Arc 9 .1 7 78.18 Frontal Chord 4 .3 0 40.95 3 2.58 HaaliMini Breadth 18.70 22.02 5.01 50.22 Maximum Length 19.09 28.07 15.41 12.40 62.96 Minimum Frontal Breadth 6.34 -0.91 -5.11 18.61 2 .1 8 25.19 Occipital Arc 22.10 11.15 7.99 3 .6 3 4 2 .6 7 -0 .2 3 56.82 occipital Chord 9 .6 4 9 .59 8 .99 -4 .7 9 2 3.88 -8 .2 4 31.04 30.39 Parietal Arc 14.47 11.47 8.92 19.62 34.74 9 .3 8 18.88 -0.99 80.69 Parietal Chord 8.90 5.44 8.03 11.09 24.61 7.93 16.41 -2 .0 7 57.83 51.25 Porion to Bregma 12.28 22.68 13.36 22.12 24.79 7 .99 15.01 8.34 31.35 18.62 40.16 Porion to Lambda 12.04 9 .2 0 10.62 9 .5 5 25.14 4 .2 6 21.33 12.18 19.29 17.13 14.88 29.14 Porion to Nation 12.01 9 .2 7 9.94 10.29 24.88 -0.36 26.00 11.79 17.68 11.03 26.86 10.78 53.60

I TABLE 72. Variance-covariance matrix of cranial metrics for Pearson males.

PEARSON B la ste r. Frontal Frontal Maximum Maximum Minimum Occipital occipital Parietal Parietal Porion Porion Porion lonlo Aro Chord Breadth Length Frontal Arc Chord Arc Chord _ to to to iaj Breadth Breadth Bregma lambda Naelon Blasterlonlo Breadth 22.60 Frontal Arc 0.4 5 67 .4 7 Frontal Chord 4.64 37.69 36.45 Maximum Breadth 11.85 17.77 -3.34 34.53 Maximum Length 22.43 13.94 -2 .4 0 11.88 73.94 Minimum Frontal Breadth 8.40 -9.51 -12.36 11.27 2.74 18.49 occipital Arc 21.26 5.94 -6 .2 8 2 .0 6 42.41 3 .3 3 4 5 .58 Occipital Chord 8.78 7 .0 9 7 .5 9 5.45 23.79 -3.55 22.49 25.66 Parietal Aro 9 .1 3 -1.71 -8.15 6 .7 7 28.54 2.63 17.94 -0.16 53.63 Parietal Chord 7 .2 6 -8.51 •1.84 -1.67 22.63 -3.14 22.04 1.67 37.16 39.41 Porion to Bregma 7.04 13.85 4 .2 9 13.04 22.45 2.66 10.09 13.16 29.10 11.80 50.49 Porion to Lambda 7.4 3 -4 .2 2 4 .1 6 -8.31 16.80 -5.43 16.45 14.43 5.33 13.88 1.33 27.18 Porion to Naelon 4.83 15.56 8.72 3 .3 3 27.33 -6 .1 8 17.27 14.59 17.76 9.1 4 29.82 1.14 47.56 TABLE 73. Variance-covariance matrix of cranial metrics for Pearson females.

PEARSON Blatter- Frontal Frontal Haxlmn Maxliauai lUninuai Occipital Occipital Parietal Parietal Porion Porion Porion Ionic Arc Chord Breadth Length Frontal Arc Chord Arc Chord to to 239 Breaotn Breadth Bregma- Lambda Nasion Blasterlonlo Breadth 16.59 Frontal Arc 4 .0 4 74.26 Frontal chord 0 .7 0 3 1.58 19.07 Maximum Breadth 16.90 16.11 2.79 58.02 Maximum Length 4 .8 6 24.22 15.85 2.98 4 0.99 Minimum Frontal Breadth 6.41 7.45 1.79 26.26 3 .6 3 31.32 Occipital Arc 8.87 5.78 2.71 -7 .3 5 2 5.37 -0 .8 6 44.95 Occipital Chord 3 .8 0 3 .0 6 2.72 -10.26 15.97 -11.24 28.29 30.40 Parietal Aro 7.09 6.58 8.90 20.34 25.22 16.77 1.55 -10.48 89.81 Parietal Chord 3.86 7.85 8.51 15.87 18.49 17.81 2 .3 7 -9.91 67.90 58.03 Porion to Bregma 3.77 13.72 6 .2 8 19.24 10.58 14.36 -0.90 -4 .5 0 17.85 15.53 16.03 Porion to Lambda 6 .0 7 7.04 4.80 15.40 19.54 6.36 10.39 3.70 18.13 13.34 12.20 21.35 Porion to Naelon 2.50 -15.18 -6.14 3.18 3 .7 3 13.39 9 .6 8 -1 .14 -1.41 2.05 4.41 2.27 3 5.27 TABLE 74. Variance-covariance matrix of cranial metrics for Petersen males and females.

PETERSEN B iaater» F rontal F rontal Maximum Maximum Minimum O ccipital O ccipital P a rie ta l p a rie ta l Porion Fcrlon Porion ionic Arc Chord Breadth Length Frontal Arc Chord Arc Chord to to to <î & 9 = 12 Breadth Breadth Bregma lambda Naelon Blatterlonlc Breadth 23.72 F rontal Arc 7 .7 7 18.45 F rontal Chord 9,45 13.33 16,61 Maximum Breadth 18.18 17.70 17.97 34.42 Maximum Length 0 .1 4 12.54 17.80 7.97 38.81 Minimum Frontal Breadth 1.89 ■0.39 2.38 3.45 0.34 4.57 o c c ip ita l Arc 6 .5 9 12.61 14.18 15.27 1 7.80 2 .0 2 45.30 O cc ip ita l Chord 8 .86 4.81 6.15 2.88 9.27 -2.30 20.25 21.72 P a rie ta l Aro -4.55 4.29 4.33 -0 .5 8 17.38 •1.05 -5.41 -3.35 21.24 p a r ie ta l Chord -8.73 1.27 10.82 -2 .3 8 24.01 2 .0 0 1.45 1.36 15.55 3 5.82 Porion to Bregma 9 .32 3 .4 3 9 .0 9 4 .2 7 12.43 1.66 13.20 12.43 1.59 10.09 14.02 Porion to Lambda 5.91 7.28 14.94 2.94 24.17 1.59 13.14 13.82 0.48 18.91 14.59 34.52 Porion to Naelon 14.45 10.70 13.42 14.33 13.42 2.36 10.00 10.06 6 .7 0 6 .6 4 11.00 12.58 18.79

s TABLE 75. Variance-covariance matrix of cranial metrics for SunWatch males and females.

SUNWATCH B laeter- F rontal F rontal Maximum Maximum Minimum O ccipital o c c ip ita l P a rie ta l P a rie ta l Porion Porion Porion lo n lc Arc Chord Breadth Length Frontal Arc Chord Arc Chord p to to to 2 6 d & 209 Breadth Breadth LonMa Nasion Blattarlonio Brtadth 15.45 F ro n tal Bro 6.63 46.44 F ro n tal Chord 8.70 32.39 28.56 Mtxlnun Brtadth 1.46 17.78 13.19 29.53 uaxlaua Length 13.05 31.81 22.91 5 .1 8 52.25 Minimum Frontal Breadth 2.23 18.73 14.04 10.27 18.96 25.85

Occipital Arc 7.84 17.03 12.61 -0 .6 4 2 1 .8 8 1 2 .8 8 65.88 O ccip ital Chord 3.0 4 5.64 1.62 1.87 0.78 3.16 27.83 34.59 P a rie ta l Arc 5.3 5 22.46 -18.68 8.37 29.46 11.54 -21.37 -18.68 75.90 P a rie ta l Chord 7 .8 8 20.76 15.87 1.79 27.42 7.74 -12.46 -13.00 51.89 54.55 Porion to Bregma 4 .1 7 28.37 2 0 .2 0 14.92 21.33 16.83 9 .3 0 6.90 23.57 20.23 29.54 Porion to Lambda 8 .7 7 19.20 15.60 5.78 18.20 8 .4 8 15.96 7.77 9.65 9.66 12.38 19.06 Porion to Naelon 3.32 17.64 11.55 11.80 23.65 12.38 - 2 .2 0 2.74 15.61 15.41 20.72 4.2 9 45.88

s TABLE 76. V ariance-covariance m atrix of c ra n ia l m etrics SunWatch males.

SUNWATCH B latter* F rontal F rontal Maxima# Maximum Minimum O ccip ital O coipital P a rie ta l P a rie ta l Porion Porion Porion lonlo Arc Chord Breadth length F rontal Arc Chord Arc Chord to to to 2Gd Breadth Breadth Bregma Lambda Nation Blut.rlonio Breadth 20.26 F ro n tal Arc 5 .2 7 32.86 F ro n tal Chord 7.74 2 2.72 17.22 Mulaiu. Breadth -2.21 16.70 10.56 28.22 Uexiann Length 14.63 12.99 12.64 -1.81 32.72 Hiniieum Frontal Breadth -1 .4 6 9 .7 5 7.40 6 .9 9 4 .3 7 23.08 O c cip ital Arc 16.86 10.48 11.41 -2 .2 8 19.88 9 .6 0 74.99 o c c ip ita l Chord 9.11 11.34 8.74 -0.78 9.05 6.37 38.98 37.60 P a rie ta l Arc 4 .02 4.21 3 .3 8 8.73 13.69 6.38 -29.38 -21.27 78.98 P a rie ta l Chord 6 .SO 10.37 7.78 1.97 17.13 2.02 -16.34 -4.95 52.50 54.90 Porion to Bregma 3.1 3 17.50 12.58 12.14 6.11 12.63 5.42 9.48 15.71 18.47 23.68 Porion to Lambda 10.85 17.23 14.89 4.71 14.62 6.71 19.27 12.09 4 .8 7 8.23 11.27 17.96 Porion to Naelon -0 .3 9 6 .8 5 3 .8 4 5 .8 9 4 .6 4 -0 .7 7 -1 8 .8 8 -0 .7 3 15.03 16.19 11.09 *2.62 33.04 TABLE 77. Variance-covariance matrix of cranial metrics for SunWatch females.

SUNWATCH Blaater- Frontal Frontal Maximum Maximum Minimum Occipital Occipital Parietal Parietal Porion Porion Porion lonlc Are Chord Breadth Length Frontal Arc Chord Are Chord to to to 20? Breadth Breadth Bregma Lambda Naelon Blutarionle Breadth 8.24 Frontal Are 2 .04 40.46 Frontal chord 4.19 22.01 21.57 Waxlaam Breadth 1.18 -0 .4 6 -1.72 16.98 Maximum Length 4 .5 7 30.09 11.54 -6 .9 9 5 1.09 Minimum Frontal Breadth 3 .1 6 15.42 8.58 2.74 22.21 21.16 Occipital Arc -4 .1 6 24.41 12.88 -0.16 23.41 16.58 5 7.18 Occipital Chord -4 .5 8 -0 .7 9 -6 .9 5 6 .0 5 -9 .2 6 -0 .4 2 14.68 3 2.42 Parietal Aro 0 .5 8 20.66 7.97 -9.79 23.40 2 .6 8 -14.10 -1 5 .4 7 48.64 parietal Chord 6 .3 2 20.51 13.44 -9.90 26.61 6.63 14.68 -23.84 38.69 48.54 Porion to Bregma -0.41 19.65 8.58 0.52 16.71 8.47 12.93 4.58 10.44 9.86 16.37 Porion to Lambda 3.46 10.74 6.18 -1.78 11.21 4 .0 0 11.49 2.84 4 .2 9 5 .2 9 3.46 16.09 Porion to Nation 3 .1 2 11.83 2.91 4 .0 9 2 7.88 17.74 17.96 8.05 -3 .0 2 3 .4 5 15.31 4 .4 5 48.83

K Ol