Cultural Interaction and Biological Distance Among Postclassic Mexican Populations Corey Steven Ragsdale

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Corey Steven Ragsdale

Candidate

Anthropology

Department

This dissertation is approved, and it is acceptable in quality and form for publication:

Approved by the Dissertation Committee:

Heather JH Edgar, Chairperson

Osbjorn Pearson

Hillard Kaplan

Andrea Cucina

Frances Berdan ii

CULTURAL INTERACTION AND BIOLOGICAL DISTANCE

AMONG POSTCLASSIC MEXICAN POPULATIONS

COREY STEVEN RAGSDALE

B.A., Anthropology, California State University, San Bernardino 2009

M.S., Biological Anthropology, University of New Mexico, 2012

DISSERTATION

Submitted in Partial Fulfillment of the Requirements for the Degree of

Doctor of Philosophy Anthropology

The University of New Mexico Albuquerque, New Mexico

May, 2015 iii

CULTURAL INTERACTION AND BIOLOGICAL DISTANCE AMONG

POSTCLASSIC MEXICAN POPULATIONS

Corey Steven Ragsdale

B.A., Anthropology, California State University, San Bernardino 2009

M.S., Anthropology, University of New Mexico, 2012

Ph.D., Anthropology, University of New Mexico, 2015

ABSTRACT

Human population structure is influenced by cultural and biological interactions.

Little is known regarding to what extent cultural interactions effect biological processes such as migration and genetic exchange among prehistoric populations. In this study, I draw upon archaeological and ethnohistoric research to investigate the interaction of biology and culture among Postclassic period (AD 900-1519) Mexican populations. The central question for this project is: how did processes of economic exchange and political expansion affect genetic exchange among Postclassic period Mexican populations? To address this question, various biological distance analyses derived from dental morphological traits were employed to investigate inter- and intra-regional population interaction. These biological distances were further compared with distances inter- regionally, based on models of cultural interaction to evaluate the effects of geographic distances, political and economic interactions, shared migration history, and shared

iv cultural/linguistic group. Cultural effects on biological population structure were further evaluated at the regional and site level using both conventional and innovative statistical approaches.

My results show that shared migration and trade are correlated with biological distances, but geographic distance is not. Trade and political interaction are also correlated with biological distance when combined in a single variable. These results indicate that trade and political relationships affected population structure among

Postclassic Mexican populations. When viewed regionally, there is high similarity among groups in the Central Mexico and the Huasteca/Maya regions, and low similarity among groups in West and Northern Mexico. These results suggest high levels of gene flow among groups in these regions. Results of the analyses of individual sites indicate that important economic, political, or religious centers in Central Mexico and the

Huasteca/Maya regions have high variation among individuals, but not in West and

Northern Mexico. I conclude that differences in population structure exist among the regions throughout Mexico, and that population structures are affected by differences in economic, political, and/or religious structure. I further conclude that trade likely played a major role in shaping patterns of interaction between populations. This study also shows that the biological distance data support the migration histories described in ethnohistoric sources.

Table of Contents

Chapter 1: Introduction

Introduction 1

Theoretical approaches 3

Archaeological and ethnohistoric accounts of population interaction 7

Population interaction in biological anthropology 13

Statistical analyses 18

Dissertation outline 20

Chapter 2: Modeling cultural effects on phenetic distances among Postclassic Mexican and American Southwest populations.

Introduction 22

The archaeological and ethnohistoric records 23

Previous biological distance studies 28

Materials 30

Methods 33

Results 41

Discussion 45

Conclusion 48

Chapter 3: Cultural and biological distance in Postclassic period Mexico

Introduction 50

Previous biological distance studies 53

Materials and Methods 55

Results 68

Discussion 73

Conclusion 80

Chapter 4: Regional population structure in Postclassic Mexico

Introduction 83

Regional interaction in Postclassic Mexico 84

Previous research in Pre-contact Mexico population structure 90

Materials 91

Methods 94

Results 99

Discussion 109

Conclusion 112

Chapter 5: Conclusions 115

Bibliography 131

Appendices 148 1

CHAPTER 1: INTRODUCTION

Human population structure is influenced by cultural and biological interactions.

How do cultural interactions affect biological processes such as migration? This question is central to biocultural and bioarchaeological studies globally. In this study, I draw upon archaeological and ethnohistoric research to investigate the interaction of biology and culture among Postclassic period (AD 900-1519) Mexican populations. The central question for this project is: how did processes of economic exchange and political expansion affect genetic exchange among Postclassic period Mexican populations? To address this question, phenetic distances derived from dental morphological traits were compared with distances derived from political and economic relationships, geographic distances, shared migration history, and shared cultural/linguistic group. Phenetic similarity among groups approximates genetic similarity (Scott and Turner, 1997;

Hanihara, 2008; Ricaut et al. 2010), so phenetic distances are appropriate for determining dissimilarity among populations using morphological features.

This dissertation is concerned with population variation, as interpreted through biological distance studies. Patterns of population variation in pre-contact Mexico were affected by migration associated with widespread trade networks, endemic warfare, imperial expansion, and rapid population growth. The archaeological and ethnohistoric records provide a wealth of information about migration history and population interaction from as early as the first known civilization in Mesoamerica, the Olmec

(1500-500 BC). For this project, migration refers to the movement of multiple individuals

2 to a different environment. These movements may occur as a small group of individuals acting based on common motives, or as large social groups whose actions are coordinated by a central authority (Cabana and Clark, 2011). Migrations throughout Mexico differed in scale: from the large and long-distance migrations of the nomadic Chichimec populations in the North, to settlements of several families within the Aztec Empire to the frontiers of the Gulf Coast, to the intentional resettlement of merchants to areas of high trade areas. By the Postclassic period (AD 900-1519), economic and political relationships connected virtually every population throughout Mexico. What is not known through the archaeological and ethnohistoric records is how these relationships shaped patterns of migration and genetic exchange among populations across the various regions of Mexico.

The results of this project can be used to build models for understanding relationships between culture and biology in regions around the world where the archaeological and ethnohistoric records are not as strong as in Mexico. This study blends biological distance data with models derived from cultural ecology, the study of human adaptations to their cultural and physical environments, including the distribution of wealth and power among cultural groups (Steward, 1990). A holistic approach to understanding population interaction and migration, such as that proposed here, is optimal for gaining a better understanding of the effects of imperial expansion, control of resources, intensified trade, and shared ideology on patterns of migration among prehistoric human populations.

Theoretical approaches

I am particularly interested in how political-economic processes affect population interaction and population structure. Political economy is a broad approach to investigating the relationships between people, economies and political structures (Gilpin and Gilpin 1987). From the perspective of biological anthropology, political economy theory can be used to understand how separate communities are connected through larger historical (or archaeological) political-economic processes that affect human biology

(Goodman and Letherman, 1998). One aspect of political economy relevant to this project is the relationship between biological variation and the social/cultural relationships associated with resource availability and labor. Populations around Mexico during the Postclassic period were politically organized into city-state cultures, small polities consisting of a single capital city or town that controlled a surrounding area of smaller settlements (Smith, 2003). Some powerful city-state cultures in the Late

Postclassic (1200-1519), such as the Aztecs and Tarascans formed empires, in which dominant imperial states maintained effective control of subordinate societies and resources (Doyle, 1986). The Aztecs in Central Mexico controlled provinces for access to food, labor, luxury and everyday items, and were constantly engaging in military campaigns to conquer more provinces (Berdan and Anawalt, 1997). Examples of military conquests and tribute payments recorded in the Codex Mendoza are provided in Figure

1.1. Other city-states outside the boundaries of empires relied on political alliances and economic relationships for access to resources and labor. Since the control, production, and exchange of resources often influences migration and genetic exchange, political

4 economic theory is complementary to my investigation of population structure among

Postclassic Mexican populations.

Figure 1.1. Pages from the Codex Mendoza. Some of the military campaigns of Axayacatl (AD 1469-1481) (left). Tributary requirements for the province of Tepequacuilco on the western frontier of the Aztec Empire (right). Courtesy of Frances Berdan (Berdan and Anawalt 1997, vol. 4, folios 10r and 37r, respectively).

Some of the early model-based approaches to studying migration were developed by demographers and geographers, and were focused on negative “push” and positive

“pull” factors among modern human groups (Herberle 1938; Lee, 1966). Push-pull models state that migration is most likely to occur when there are negative (push) stresses in the home region and positive (pull) attractions in the destination region, and the transportation costs between the two are acceptable (Lee, 1966). Push factors, such as a poor economy, drought or warfare influence a population to leave their home region; pull

5 factors, such as improved economic conditions, improved resource availability, or other social advantages attract migrants to a new destination. Push-pull models were first applied to archaeological populations by Anthony (1990), and typically apply only to long-distance migrations. Some problems with push-pull models include the inability to accurately define the decision-making unit (individual, family, or village) upon which pull factors operate (Anthony, 1990), they assume that migrants make considered decisions about whether to migrate and where (Chibnik, 2011; Cameron, 2013), and they do not typically distinguish between voluntary and forced migration (Cameron, 2013).

Push factors may be abrupt and sometimes violent, such as captive taking through raiding and warfare, and pull factors may be non-existent (Cameron, 2013). To accommodate such limitations in push-pull models, it is important to consider population movements facilitated through political and economic processes.

Among the early approaches to studying population interaction through economic processes was Karl Polanyi’s “port of trade” model (Polanyi et al. 1957; Polanyi 1963), which did not include pre-capitalist states such as those found throughout Postclassic period Mexico. According to this model, all merchants are portrayed as sponsored and controlled by the political leadership, and that long-distance trade was independent from local and regional trade systems. Ports of trade were trade centers located along political borders, often in politically neutral zones so trade may occur between merchants from hostile polities (Polanyi 1957). The port of trade model was first applied to Postclassic

Mesoamerica by Chapman (1957), where she suggested ports of trade accounted for long-distance exchange. These ports of trade were located in politically neutral areas, trade was limited to luxury items and thus was separate from local and regional exchange

6 systems, and that merchants that interacted at these ports of trade were members of a particular social group whose activities were sponsored by the state (Chapman 1957).

Several criticisms have since arose for applying the ports of trade model to Postclassic

Mesoamerica (Berdan 1978; Freidel and Sabloff 1984; Voorhees 1989; Gasco and

Berdan 2003).

In summary, these criticisms include the presence of long-distance trade centers in non-politically neutral areas, more variation and long-distance trade centers than accounted for by Chapman, the relationships between merchants and states, the existence of utilitarian goods as well as luxury items at major trade centers, the existence of politically independent merchant organizations, and the connection between long- distance, regional, and local market exchange systems. Because of these criticisms, the port of trade model is no longer utilized by most Mesoamerican scholars to investigate population interaction through trade.

The most recent approaches to studying cultural interaction among Postclassic

Mexican groups using ethnohistoric or archaeological materials have revolved around the

Mesoamerican world system theory (Blanton and Feinman, 1984). Mesoamerica is a term that refers to the cultural area encompassing most of Mexico, and extending down to

Central America. A world system, a concept originally developed by Wallerstein (1974) to explain the origins of modern capitalism, is an economic zone of core and peripheral societies that extends beyond a single geographic region in which exchange benefits the core.

The major criticism of applying this theory to Mesoamerica is that it is composed of too many competing cores distinguished by socioeconomic organization rather than core domination (Smith and Berdan, 2000; Kepecs and Kohl, 2003). To account for this, the Mesoamerican world system extends cores and peripheries to international trade centers, affluent production zones, resource extraction zones, and unspecialized peripheries (Smith and Berdan, 2003). For this study, economic exchange networks incorporate sites of varying socioeconomic structures, each contributing to the greater

Mesoamerican world system. Another criticism of the Mesoamerican world system is that it underestimates the contributions of frontier provinces, or areas outside of the known core zones of Mesoamerica such as Northern Mexico and parts of the Maya region

(Wells, 2006). To address this issue, populations in these regions were considered as economic exchange networks as a part of the Mexican world system, as it is assumed these populations contributed to population interactions. To date, no body of theory exists that replaces the Mesoamerican world system when viewed at an interregional scale (Balkansky, 2006).

Archaeological and ethnohistoric accounts of population interaction

Political and economic processes among Postclassic Mexican populations varied across geographic regions. For this reason, I tested the effects of cultural relationships on phenetic distances among groups at the regional and inter-regional level. A brief overview of each geographic region considered in this study is provided below. The location of samples and major geographic regions are provided in Figure 1.2.

Figure 1.2. (1) Hawiku; (2) Pueblo Bonito; (3) Otowi Cliffs; (4) Puye Cliffs; (5) Paquime; (6) Tayopa; (7) Nararachic; (8) Copper Canyon; (9) Guasave; (10) Cuatro Cienegas; (11) Candelaria Cave; (12) Paila Cave; (13) Chalpa; (14) Tecualilla; (15) Huejuquilla; (16) Autlan-Tuxcacuesco; (17) Zacapu; (18) Tzintzuntzan; (19) Texcaltitlan; (20) Teotenango; (21) Azcapotzalco; (22) Coyoacan; (23) Tenayuca; (24) Tlatelolco-Tenochtitlan; (25) Culhuacan; (26) Huexotla; (27) Xochimilco; (28) Mixquic; (29) Teopanzolco; (30) Cholula; (31) Zaachila; (32) Yagul; (33) Zapotal; (34) Vista Hermosa; (35) Tamtok; (36) Chicoasen; (37) Jaina Island; (38) Coba; (39) Playa del Carmen; (40) San Gervasio; (41) Cozumel; and (42) Tulum.

Central Mexico

Central Mexico is considered the center for widespread trade and political expansion during the Postclassic period (Hodge and Smith 1994; Smith 2001; LópezLujan 2005;

Melgar and Ciriaco 2009). During much of the Middle-Late Postclassic period (AD 1200-

1519), the Aztec Triple Alliance, led by the Mexica in the Valley of Mexico, grew in power and achieved dominance over much of Mexico (Evans 2004; LópezAustin and LópezLujan

2005). The Aztecs expanded their political control and trade networks extensively, and by the time the Spanish arrived in AD 1519, controlled provinces stretching from the Gulf Coast, to the Pacific, and to the Chiapas Highlands in southern Mexico. The Aztecs maintained the center for economic exchange with a large inter-regional market at Tlatelolco. The market served an estimated 20,000 to 25,000 people daily (Anonymous Conquerer 1971). Along with the Aztecs, the Tlaxcallans and various Chichimec groups also inhabited Central

Mexico. The term Chichimec does not imply a particular ethnic, linguistic, or technological identity, but refers to a large number of nomadic groups that inhabited much of Northern

Mexico, the Gulf Coast, and parts of Central Mexico (Lopéz Austin and Lopéz Luján 2001).

These groups were a consistent problem for the Aztecs, and wars with the Tlaxcallans lasted until Spanish contact. Tlaxcallans and Chichimecs also participated in widespread trade during the Postclassic period. In the Oaxaca valley, Zapotec and Mixtec civilizations continued to thrive after the fall of Monte Alban (Joyce 2010). Much of this region fell under the control of the Aztecs during the fifteenth century, but maintained important trade centers until Spanish contact.

West Mexico

The Tarascans in West Mexico were the major political entity in West Mexico during the Postclassic period. In addition to archaeological data, information about the Tarascans is provided by written sources from the colonial period, such as the Relación de Michoacán.

Like the Aztecs, the Tarascans maintained a large empire, extracting tribute of minerals and luxury items from cities within their range of control (Pollard and Vogel 1994; Beekman

2010). Unlike the Aztecs, the Tarascan elite maintained firm political and economic control within their domain, controlled by a major political capital at Tzintzuntzan. Additionally, the

Tarascan elite controlled specific raw materials such as copper, and land, remaining unchallenged until the arrival of the Spanish in AD 1525 (Pollard 2003). Beyond the

Tarascan Empire, many city-states in West Mexico were highly active in trade, particularly in metals and marine goods (Beekman 2010). The Aztitlan trade route was located along the

Pacific coast of West Mexico, and was home to several small, densely populated cities and towns that were often fortified with defensive structures and high walls. This area was also a major extraction zone for metal throughout the Postclassic period. Populations in West

Mexico were likely in constant contact with each other, as well as with groups from other nearby regions such as Northern Mexico (Wilcox et al. 2008; Kelley et al. 2012).

Northern Mexico

The Coahuila-Chichimec groups in Northern Mexico occupied caves and open areas that had access to water and desert plains (Turpin 1997). These nomadic groups traveled great distances to participate in trade, and settlements were primarily located near available resources. People of the Casas Grandes culture, centered at Paquimé, traded with both

Mesoamerican and American Southwest populations (DiPeso 1974; Weigand 2008).

Paquimé served as a sort of economic gateway between these two major cultural regions, importing goods such as cacao and macaws from southern Mexico and turquoise from the

American Southwest (Woosley and Olinger 1993; Weigand 2008; Crown and Hurst 2009).

The dating of Paquimé is continually debated, but it is likely the site experienced a large

11 amount of migrants from the American Southwest around the time of a great drought around

AD 1130-1150, and was abandoned around AD 1300 (DiPeso 1974; Kelley et al. 2012). It is possible that Paquimé facilitated migration from the American Southwest into other regions of Mexico, as well as served as a venue for economic exchange (Walker 2006; Weigand

2008) and inter-group warfare (Walker 2006; Anderson et al. 2012) for various groups around Northern Mexico.

The Gulf Coast

The diverse environment of the Gulf Coast provided a wealth of land, food, and luxury and other trade goods that were known throughout Mexico in pre-contact times (Pool

2006). The Gulf Coast is a large region extending from the modern Mexican state of

Tamaulipas, to the Maya region of the Yucatan Peninsula. Much of the Gulf Coast was inhabited by Totonac and Epi-Olmec groups, whi;e the Huastecs occupied the area of

Northern Veracruz state, and the modern states of Tamaulipas and San Luis Potosi. The

Huastec populations inhabited the northern Gulf Coast in settlements that were scattered and relatively low density, with larger concentrations of sites near the major rivers of the region

(LópezAustin and LópezLujan 2005). Groups in this area participated in widespread trade networks reaching from the Maya region to as far as the Mississippian Valley in North

America (Lopéz Austin and Lopéz Luján 2008; Dávila 2009). The Aztecs thought the

Huastecs were savage barbarians (Sahagun 1982), and their strong resistance to Aztec political expansion during the Late Postclassic period highlights their political/military organization (Hassig 1988). The Totonacs in the southern Gulf Coast were politically

12 organized into small independent states with capital cities, which began to appear around the thirteenth century (Ochoa 2001; Lopéz Austin and Lopéz Luján 2008). Many of these states were occupied during the Late Classic period (AD 600-900), and were either re-occupied, replaced, or maintained continuous population growth over time (Daneels 1997; Stark and

Chance 2008). The Totonacs participated in widespread trade networks throughout

Mesoamerica, including the Maya region (Gasco and Berdan 2003; Pool 2006; Zaragoza

Ocaña 2009, Daneels 2012). Many Totonac cities were under Mexica rule by the sixteenth century, and provided tribute of cacao, vanilla, rubber, cotton, and other products (Diehl

2000; Hassig 2010). This geographic region is the most limited in samples. This is due to the scarcity of samples excavated for the Huastec region, and to the limited samples available for study in Veracruz during the Postclassic period. These obstacles will hopefully be negotiated in the future.

The Maya Region

In the Maya region during the Postclassic period, populations are characterized as independent states, engaged in long-distance trade and endemic warfare, with some of the more powerful states expanding their control of resources through conquest (Hammond

2000; Lopéz Austin and Lopéz Luján 2001). Political power and control of resources shifted over time among dominant populations and their allies. Major trade and religious centers, such those at Cozumel (Freidel and Sabloff 1984; Ringle and Bey 2012), existed along the coast of the Yucatan Peninsula. By European contact in the sixteenth century, trade routes from the Maya region had expanded throughout all of Mesoamerica. The long-distance

13 movement of goods such as salt and cacao facilitated a very complex system of exchange that connected groups throughout the Maya region and beyond (Ringle and Bey 2012). It is difficult to include many Maya samples in the investigation of inter-regional interaction, since many of the cities in the Maya region experienced an economic or political collapse prior to the Late Postclassic period. To accommodate this, few samples were used in the inter-regional interaction portion of this study, and all Maya samples were considered in the regional analyses.

Population interaction in biological anthropology

Migration is often conceptualized differently between archaeologists and biological anthropologists. Archaeologists are primarily interested in the distribution and movement of artifacts, and make the assumption that such artifacts represent population interaction and migration (Jones, 1989; Cabana and Clark, 2011). Biological anthropologists, on the other hand, focus on a genetic perspective and the movement of genes without the consideration of cultural interactions (Fix, 2011). Combining cultural and biological relationships is an optimal approach to addressing these issues. Phenetic distances provide an idea of the genetic relatedness of populations using morphological data (Relethford and Blangero, 1990; Scott and Turner, 1997), and thus can be used as a proxy for genetic distances. In genetic distance studies, the distance between two populations should be small if their gene frequencies are similar (Harpending and

Jenkins, 1973; Crow, 1986). As the degree of genetic relatedness between populations decreases, biological distances should increase. For this study, I use phenetic distances

14 based on dental morphological traits to represent genetic relatedness. Though I am using phenotypic similarity as a proxy for genetic similarity, the principles of population genetics that influence population structure are important to consider.

Population genetics

The isolation by distance model, originally proposed by Wright (1943) is an important hypothesis to test in biological distance studies. According to this model, under conditions of random mating, as populations become more separated geographically they become more genetically different (Crow, 1986; Hartl and Clark, 1997). Populations deviate when biological distances are larger or smaller than expected through isolation by distance. Particularly large biological distances between populations may result when isolated populations share a distant common ancestor, if populations are subject to different selective pressures, or if the populations are small and the effects of genetic drift are great (Scott and Turner, 1997; Jobling et al., 2003). Particularly small biological distances may result from reduced impact of genetic drift, the populations being subject to similar selective pressures, or from gene flow between populations (Scott and Turner,

1997; Jobling et al., 2003). These processes are related to the evolutionary forces of natural selection, mutation, genetic drift, and gene flow (migration) (Mayr, 1970).

For the archaeological populations sampled in this study, the processes of import are genetic drift and gene flow. Mutation is not considered here since all populations of interest are from a short period of time (approximately 600 years); several samples represent populations from the Late Postclassic period (AD 1200-1519). The effects of

15 natural selection are also disregarded in this study since their effects on population structure are negligible. Selective pressures likely have no effect on genetic variability because the samples represent populations from a limited geographic and temporal range

(Relethford and Blangero, 1990) that shared similar diets and technology (Scott and

Turner, 1997). Additionally, dental morphological traits appear to be neutral with respect to fitness (Hillson 1996; Scott and Turner, 1997). One final process I have not included in this study is sexual selection. Although some visible morphological features of the incisors may be affected by sexual selection, such as a midline diastema or central incisor winging, there is currently no way to detect this force among archaeological populations.

Both large and small biological distances can be interpreted through the evolutionary processes of genetic drift and gene flow. Large biological distances among populations within a region indicate a high proportion of genetic variance that is accounted for by among-group variation compared with the amount of within-group variation (Crow, 1986; Jobling et al., 2003). If a population is small or experiences a dramatic decrease in size or bottleneck, then genetic variation within that population may be reduced from the shared parent population (Crow, 1986; Hartl and Clark, 1997). This reduction in variation will increase the biological distance between populations. Fixation of alleles leads to a reduction in genetic diversity (Jobling et al., 2003), this occurs most frequently in small populations. In other words, genetic drift can greatly affect population structure among groups with small population sizes.

Gene flow between populations increases within-group variation and decreases between-group variation among human groups. Populations that experience high levels of immigration experience an increase in genetic variation as a result of gene flow (Jobling

16 et al., 2003) and a decrease in genetic distance from populations with which migrants are exchanged. Gene flow and genetic drift are therefore an important factor to consider with biological distances, especially among widely geographically distributed populations

(Jobling et al., 2003; Scott and Turner, 1997).

Dental morphology

The use of morphological variation as a proxy for genetic variation to reconstruct population histories has been repeatedly demonstrated (Berry and Berry, 1967; Turner, 1990;

Relethford, 1991; Scott and Turner, 1997; Stojanowski, 2004). Several morphological features of the skeleton can be used in biological distance studies. In this study I will focus on dental morphological traits. Archaeological samples in Mexico often exhibit poor preservation, or cultural modification, which could limit measurements or observations of the skull (Gonzales Jose et al., 2001; Konigsberg et al., 1993). On the contrary, teeth often preserve well in the archaeological context.

Dental morphological studies analyze data from observations of standardized morphological characteristics found on the crown surfaces of teeth, such as shovel-shaped incisors and Carabelli’s trait (Hrdlicka, 1920; Scott and Turner, 1988). They can be used to track population movements over space and time, as the gene frequencies change due to population factors such as genetic drift and gene flow (Turner et al., 1991; Irish and Turner,

1990). Dental traits are relatively unaffected by sexual dimorphism and aging (Smith, 1977;

Scott and Turner, 1997), and may be adjusted for asymmetry. These traits are observable even with moderate attrition, provide large sample sizes for archaeological populations,

17 provide a high recording replicability, are associated with low inter-trait correlations

(Hanihara, 1976; Hanihara, 2008), possess a high genetic component (Scott and Turner,

1997; Townsend et al. 1992, 2009), and evolve slowly (Turner et al., 1991).

Dental morphology is an effective method with which to trace intra-population variation, inter-population relationships, and microevolution (Scott and Turner, 1997;

Hanihara, 2008; Willermet and Edgar, 2009). Previous biological (phenetic) distance studies using dental morphological traits have been used to assess biological relationships among populations spanning large geographic regions such as Africa (Irish, 1993, 2010); Asia

(Hanihara, 1976; Manabe et al., 2008; Matsumura and Hudson, 2005); as well as many others

(see Scott and Turner, 1997). Other recent works in dental morphological studies have found dental traits to be useful for phenetic distances between populations spanning long periods of time (Coppa et al., 1998; Irish and Guatelli-Steinberg, 2003; Coppa et al., 2007; Sutter and

Mertz, 2004). Recent studies of populations in the Levant and the Americas have also demonstrated that dental trait frequencies are distinguishable even between closely related populations, and populations within close geographic and temporal proximity (Ullinger et al.

2005, Aubry, 2009; Sutter and Verano 2007). Finally, recent biological distance studies using dental morphology in North and South America have been used to evaluate the effects of population interaction and recent shared migration history (Scherer, 2004; Sutter and Mertz,

2004; Sutter and Verano, 2007; Sutter, 1997, 2006, 2009; Aubry, 2009). These studies demonstrate the utility of dental morphology for assessing population structure.

The earliest methods of dental morphology date to Hrdlicka’s (1920) research on the degrees of expression and distribution of discrete dental traits used to assess variation among human populations. The methods for scoring discrete dental traits were later refined and

18 standardized by Dahlberg (1950). The current standards for scoring dental morphological traits utilize the Arizona State University Dental Anthropology System (ASUDAS) (Turner et al., 1991). This system includes a set of plaques and scoring procedures to standardize observations of crown, root, and inter-osseous morphological traits in the permanent (adult) dentition (Turner et al., 1991). This standardization has allowed multiple researchers to employ this method consistently with relatively low intra-observer error (Turner et al., 1991;

Scherer, 2004). Unfortunately, high rates of inter-observer error are continually reported

(Scherer, 2004). To account for this, intra- and inter-observer error tests were conducted for both researchers that contributed data to this study.

Statistical analyses

Throughout this dissertation I employ various statistical methods to investigate population structure. Biological distance approaches include model-free and model-bound analyses. Model-free analyses look at the relationship between trait data and such external factors as geography, time, linguistics, or cultural distance. Model-free analyses are motivated by population genetics, but do not include estimation of genetic parameters in the underlying models. Model-bound analyses, however, adopt a particular population genetic model and then estimate one or more genetic parameters. These explain biological variation in terms of clear, mathematically defined processes. The earliest model-bound analyses focused on comparing genetic distances with matrices representing regional-continuity or replacement models of migration (Konigsberg and Blangero, 1993; Cole, 1996). Recently, model-bound analyses using matrix comparisons have been used to investigate population

19 history in South America using dental morphological data (Sutter, 2006; Sutter and Verano,

2007). In this study, I compare model matrices that combine population genetics and cultural interaction with biological distances derived from dental morphological observations. This study is the first to compare cultural and biological distances in Mexico, and to interpret these relationships through population genetics theory.

Intra- and inter-observer error

All data for this study was collected by Corey Ragsdale (CR) and Heather Edgar

(HE). To estimate inter- and intra-observer error, a sample of fifty dentitions of prehistoric Native American dentitions housed at the Maxwell Museum of Anthropology

Laboratory of Human Osteology were scored by both researchers. Traits with no variation (100% or 0% present) were removed prior to calculation, as these traits are not useful for error testing. Cohen’s kappa, standard error, and percent agreement were calculated for intra- and inter-observer error tests. Kappa values for inter- and intra- observer error range from 0.7 to 1.0, and percent agreement range from 86% to 100%, demonstrating high concordance between observations and observers.

Geographic and cultural matrices

Geographic, cultural, and biological matrices were compared using Mantel and partial Mantel tests (Mantel, 1967). Mantel tests compare matrices in thousands of permutations, eliminating assumptions about the distribution of the data being used

(Manly, 1986). These tests were used to obtain correlations between phenetic distances

20 and geographic/cultural distances. To account for correlations among the variables, I also conducted partial Mantel tests, which allow two matrices to be compared while controlling for similarities with a third matrix (Legendre and Legendre, 1998). The cultural variables tested were shared migration history, shared cultural group, trade, and political interaction. The distances for these matrices were obtained from the archaeological and ethnohistoric records.

FST

To further evaluate the effects of gene flow and migration on population structure, I calculated FST levels for all samples and each geographic region. FST has been a useful tool in past studies for determining the effects of gene flow on phenetic distances between prehistoric groups using dental morphological traits (Relethford and Blangero, 1994;

Stojanowski 2004, 2010; Hanihara and Ishida, 2005; Hanihara, 2008, 2010; Irish, 2010). FST values represent the overall level of genetic variation within a regional mating network.

These values vary between 0 and 1: low values indicate low among-group genetic variation relative to the total variation and high levels of among-group gene flow; high FST values indicate high among-group variation and low levels of among-group gene flow within a regional mating network. Regional FST values that are lower than the total FST value are indicative of more among-group gene flow among samples in those regions. FST will be compared among samples regionally to determine the effects of gene flow on each region.

Combining phenetic distance studies using dental morphological observations with genetic measures such as FST allow for a thorough investigation of population structure. It is

important to note that FST is not considered model-bound unless these values are tested in the context of evolutionary or ecological models.

Dissertation outline

The purpose of this study is to assess the effects of economic and political processes on population structure among Postclassic Mexican populations. Chapter 2 is a test of the effects of geographic distances, shared migration history, and trade on phenetic distances among Postclassic Mexican and American Southwest populations inter- regionally. This chapter demonstrates the use of phenetic distances to test cultural relationships. Chapter 3 expands this research to more samples throughout Mexico during the Postclassic period. This chapter also improves upon the models used in Chapter 2, while also incorporating model matrices for political interaction and shared cultural group. The model matrices are also compared with phenetic distances regionally. Chapter

4 focuses on population structure at the regional and site levels. This chapter focuses on the effects of economic, political, and religious structure on population variance among sites within each major geographic region. The final chapter provides conclusions about the inter-regional, intra-regional, and intra-site analyses, as well as summary remarks regarding the relationship between cultural and evolutionary processes among Postclassic

Mexican populations.

CHAPTER 2: MODELING CULTURAL EFFECTS ON PHENETIC DISTANCES

AMONG POSTCLASSIC MEXICAN AND AMERICAN SOUTHWEST

POPULATIONS

Patterns of human biological variation in pre-contact Mexico and the American

Southwest were affected by migration and genetic exchange associated with widespread trade networks, endemic warfare, imperial expansion, and rapid population growth.

During the Postclassic period (AD 900-1519), these processes intensified with political and economic networks connecting virtually every group in Mexico (Smith 2001; Smith and Berdan 2003). In the American Southwest, large-scale migrations occurred throughout the region, likely in response to a series of droughts occurring around AD

1130-1180 (Schlanger 1993; Douglass 2006). Large, inter-regional trade centers connected groups throughout the American Southwest and Mexico. Although relationships among groups in these regions are well documented in the archaeological and ethnohistoric records, biological relationships among these groups are understudied.

Here, I evaluate how population structure is shaped by the processes examined by cultural ecology, the study of how humans adapt to their cultural and physical environments (Steward 1990). I use phenetic distances obtained from dental morphological observations as a proxy for genetic relationships for comparison with geographic distance, shared migration history, trade, and political interaction among groups from the American Southwest and North, West, and Central Mexico. Previous studies of some of the samples used in this analysis relied upon craniometric and nonmetric data for phenetic comparisons (Corruccini 1972; Mackey 1977; El-Najjar

1978; Schillaci and Stojanowski 2002; Gonzales-Jose et al. 2007). This project expands on these studies to include Northern Mexico, and considers groups within the American

Southwest and Mexico as a single inter-regional network to investigate how cultural and ecological factors affected phenetic distances among Postclassic period Mexican and

American Southwest populations.

The Archaeological and Ethnohistoric Records

Extensive archaeological and ethnohistorical research offers evidence of large- scale migrations, shared ideology, trade, and warfare among the various regions of

Mexico and the American Southwest. Periods of drought and economic collapse led to several migrations, particularly throughout the Postclassic period. Cultural similarities such as ballcourts, burial patterns, irrigation techniques, and architecture demonstrate possible links between these geographically separate networks (Ross 1967; McGuire

1980, 2012; Whalen and Minnis 1996). Trade items such as cacao, macaws, and turquoise also suggest connections between Mesoamerica and the American Southwest through inter-regional trade networks (Ericson and Baugh 1993; Melgar and Ciriaco

2009; Melgar 2010; Crown and Hurst 2009; Weigand 2008). Fortified settlements located near resource production and mining sites in the American Southwest and throughout

Mexico suggest a relationship between continuous warfare and trade. Though many of these groups were connected through cultural and ecological relationships, these geographic regions are typically grouped into two separate core cultural regions: the

American Southwest, including parts of Northern Mexico; and Mesoamerica, including

West and Central Mexico. These geographic regions are shown in Figure 2.1.

Figure 2.1. Map of sites used in this chapter.

American Southwest and Northern Mexico

The Postclassic period of Mexico overlaps the chronological periods of Pueblo II to Pueblo IV in the American Southwest (AD 900-1600). Prior to the Postclassic period ancestral Puebloan, Hohokam, and Mogollon populations primarily occupied the

American Southwest. From around AD 850 to 1130 Chaco Canyon was one of the largest

Pueblo sites in the region. Chaco was likely an economic center for distributing agricultural and luxury goods for the entire San Juan Basin region of Northwest Mexico

(Washburn et al. 2011; Crown 2013). Cacao from the Gulf Coast or Southern Mexico

25 was among the items used and likely traded at Chaco Canyon (Crown and Hurst 2009).

Between AD 1130 and 1180, coinciding with a period of disastrous drought, Chaco

Canyon was abandoned and migrants dispersed south into the Rio Grande Valley and

Northern Mexico (Benson et al. 2007). These migrations likely led to population growth and the development of a large inter-regional trade center at Casas Grandes in Northern

Mexico (Kelley 1993; Leckson 1999a). In the American Southwest, and the frequency of hostile interactions increased with time (LeBlanc 1999; VanPool and Obrien 2013).

Economic and political relationships shifted often in response to access to resources, population growth, and natural phenomena. During the Postclassic period, sites such as

Hawiku in the Cibola area and Puye on the Pajarito Plateau were primarily local distribution centers. Some exotic trade items found in these areas were obtained from as far as Northern Mexico (Mills 1995; Walsh 2000), and Hawiku likely was involved in the trade of items from West Mexico (Riley 1975). Hawiku also participated in inter-group warfare, especially with Hopi and Acoma groups around the region (Hammond and Rey

1940, LeBlanc 1999); other hostile interactions within the Rio Grande Valley are not as well understood. Warfare on the Pajarito Plateau area declined as the pueblos grew after about AD 1400 (LeBlanc 1999, 2000), and it is unlikely these groups had hostile interactions with the Zuni or Hopi groups to the west. Most of the Pajarito Plateau was abandoned around the time of European contact, and occupation of the Zuni site of

Hawiku continued until shortly after the Pueblo Revolt in AD 1680.

Much of Northern Mexico is often referred to as the “Greater Southwest.” Among the populations that occupied this region were the semi-nomadic Chichimecs, who appear in the archaeological record during the Late Postclassic period (around AD 1200). The term

Chichimec does not imply a particular ethnic, linguistic, or technological identity, but refers to a large number of nomadic groups that inhabited Northern Mexico, the Gulf Coast, and parts of Central Mexico (Lopéz Austin and Lopéz Luján 2008). The Coahuilan groups in the northeast occupied caves and open areas that had access to water and desert plains (Turpin

1997). To the northwest, the Casas Grandes culture, centered at Paquimé, controlled a large trade center between the American Southwest and Mexico (DiPeso 1974; Woosley and

Olinger 1993). Casas Grandes grew from a small agricultural community to a large trade center shortly after the abandonment of Chaco Canyon, leading some archaeologists to attribute this demographic growth to ancestral Puebloan migrants (Lekson 1999a). Others argue that this growth was caused by migrants from and trade with Central Mexico (DiPeso

1974; Nelson 1986; Kelley 1993). The Casas Grandes culture and its remnants throughout the region actively participated in trade and continuous inter-group warfare. Areas such as

Copper Canyon in the Sierra Madre Occidental Mountains were inhabited by nomadic groups that lived in temporary cave dwellings. Many burials found in caves in this area show signs of trauma to the skeleton (Walker 2006), and historical accounts from Spanish invaders in the

17th century describe hostile relationships between indigenous groups throughout the region.

These groups were located near major trade routes along the northwestern mountains and coast of Mexico (Weigand 2008). In general, groups from Northern Mexico were highly involved in economic and hostile interactions between the American Southwest and Mexico.

Central and West Mexico

Central Mexico is often considered the center for widespread trade and political expansion during the Postclassic period (Smith 2001; LópezAustin and LópezLujan 2005;

Melgar and Ciriaco 2009). During the Early Postclassic period the dominant Toltec populations inhabited the Valley of Mexico and established political dominance and long- distance exchange routes (Cowgill 2000). After the decline of the Toltecs in the mid-twelfth century AD, these populations continued to settle in Central Mexico as well as in the Gulf

Coast, and throughout the Maya region (Smith and Schreiber 2006). Some recent biological distance studies using dental morphological traits have provided evidence of these migrations

(Aubry 2009; Willermet et al. 2013). During the Late Postclassic period, the Aztecs grew in power and achieved dominance over much of Mexico (Hassig 1995; LópezAustin and

LópezLujan 2005). The Aztecs also maintained large inter-regional markets and trade routes throughout Mexico and beyond, with their goods being found as far north as the American

Southwest and as far south as Guatemala and Honduras (Smith and Berdan 2003). Large markets such as Tlatelolco served as many as 20,000 to 25,000 per day (Anonymous

Conqueror 1971; Berdan 2005), attracting people from various regions around Mexico. Until

Spanish contact, other cities throughout the Aztec realm participated in various forms of market exchange, war campaigns, and paid tribute to the Aztecs.

Throughout the Postclassic period, West Mexico was an important region for trade and for the mining of minerals such as copper. In the Early Postclassic period, several small city-states were widely distributed in defensible positions (Foster and Gorenstein 2000).

During the Late Postclassic period, much of the region was consolidated and controlled by the Tarascan Empire. Like the Aztecs, the Tarascans maintained a relatively large empire, extracting tribute of minerals and luxury items from cities within their range of control

(Pollard and Vogel 1994; Beekman 2010). Unlike the Aztecs, the Tarascan elite maintained firm political and economic control within their domain. Additionally, the Tarascan elite controlled specific raw materials and land, remaining unchallenged in their control until the arrival of the Spanish in AD 1525 (Pollard 2003). Many groups from the northwest part of the region participated in inter-regional exchange, independent of the Tarascan Empire.

These groups settled in defensive city-states primarily settled along riverine valleys, with a large number of imported items found in houses and burial pits (Gorenstein 2001). The

Tarascans were unable to extend their political control into the north, although they likely maintained trade relationships until European contact in the sixteenth century.

Previous Biological Distance Studies

In Mexico, biological distance studies have focused on migration patterns among the

Classic and Postclassic period populations from Northern, West, and Central Mexico. Kemp et al. (2005) used mtDNA from samples from Central Mexico to find that samples such as

Tlatelolco were more similar to other samples from Central and Southern Mexico, and were different from other Uto-Aztecan speaking groups in Northern Mexico and the American

Southwest. Using craniofacial measurements, Gonzales-Jose et al. (2007) found Central

Mexican samples to be more similar to West Mexican samples, and different than earlier

Central or Northern Mexican samples. Finally, Gómez-Valdéz (2008) used dental morphological traits to investigate relationships among West Mexico populations, mostly prior to the Postclassic period. Gómez-Valdéz found Tlatelolco had small biological

29 distances with West Mexico samples, as well as with other Central Mexico samples from the

Classic period (AD 300-900). These distances were especially low between Tlatelolco and the West Mexico samples from the Aztatlan region. These results support a shared migration history between West and Central Mexico.

Craniometric and cranial morphological traits from some of the samples studied here have also been used in biological distance analyses to investigate the origins of sites in the

American Southwest and Central Mexico. Mackey (1977) used cranial morphological traits in samples from around the Rio Grande Valley to find that the Pajarito Plateau (Puye and

Sapawe), Jemez River Valley, and Hawiku were very similar to each other, but different from a sample from Pueblo Bonito. Studies using craniometric data from these samples found similar results (El-Najjar 1978; Schillaci and Stojanowski 2002). However, Corruccini

(1972) found contradictory results when he compared Hawiku and Puye with a different sample from Pueblo Bonito, suggesting Puye and Pueblo Bonito were similar when compared to Hawiku. The difference in these findings may be explained by Schillaci and

Stojanowski (2002), who found a distinction between the west and north samples of Pueblo

Bonito, with the west being more similar to Puye and Hawiku. These results suggest within group variation at Pueblo Bonito that may be a result of migration and some population replacement, and support a shared migration history between Chaco Canyon and later Rio

Grande Valley sites.

Other previous biological distance studies using dental morphological traits from these regions have focused on testing hypotheses about migration, language group distribution, and shared culture (Turner 1993; LeBlanc et al. 2008). Turner’s work (1993) indicated phenetic distances were related to geographic proximity and cultural group among

30 prehistoric and modern American Southwest and Mexican populations. However, phenetic distances were not related to linguistic classification. LeBlanc et al. (2008) also compared

American Southwest and Mexican populations to test cultural and linguistic correlations with phenetic distances using dental morphological traits. The results of this study indicated small phenetic distances among the American Southwest samples of Hawiku, Puye, and Pueblo

Bonito, as well as between these samples and a combined Central Mexico and Coahuilan

(northeast Mexico) sample. The authors combined their Mexican samples to facilitate evaluating the spread of the migrations of Uto-Aztecan speakers. This study expands this work by looking at geographic, economic, and political relationships among samples to examine cultural relationships among site-specific samples across regions.

Materials

We observed dental morphological traits in 311 individuals representing 11 archaeological sites from the American Southwest and Mexico. As is true in most bioarchaeological dental studies, observability was limited by missing teeth, heavy dental attrition, and caries. Because of these reasons, many individuals used in this study are young or middle adults. Figure 2.1 shows the geographic location of all the sites from which the samples are derived. Samples were chosen to represent various forms of economic and political structure. Three samples are derived from sites in the American

Southwest (n=80), Pueblo Bonito (AD 828-1130), Puye (AD 1150-1580), and Hawiku

(AD 1400-1680). Pueblo Bonito is the largest Great House of Chaco Canyon, in northwestern New Mexico. It predates all the other samples (AD 828-1130), but was

31 included in this study because of its importance in Northern Mexico and American

Southwest migration histories. There are two major skeletal samples for Pueblo Bonito: the west and north cemeteries. Here I use the sample from the north cemetery housed at the Smithsonian National Museum of Natural History. The Puye sample comes from the

Pajarito Plateau near the Jemez Mountains in central New Mexico. Finally, Hawiku was a large Zuni site on the New Mexico and Arizona border.

Eight samples are derived from Mexico: three from Northern Mexico (n=60); two from West Mexico (n=57); and three from Central Mexico (n=114). The Northern

Mexico sites of Copper Canyon (AD 1300-1700) and Nararachic (AD 1200-1700) represent possible Casas Grandes remnant populations from the Sierra Madre Occidental

Mountains in the Mexican state of Chihuahua. Copper Canyon is an archaeological and historic site associated with the historic Tarahumara mines. Nararachic is a small cave burial site in Chihuahua, near a small semi-nomadic site possibly under the control of

Paquimé, the center for the Casas Grandes culture. The third Northern Mexico site is a burial cave in Cuatro Ciénegas (AD 1200-1500), located in the Coahuilan Valley of

Northeast Mexico.

The two West Mexico samples are from Zacapú (AD 1200-1540) and Guasave

(AD 900-1400). Zacapú, located within the Tarascan Empire, was the first Tarascan settlement in the present day Mexican state of Michoacan. The Guasave sample comes from the archaeological site in the Mexican state of Sinaloa, from the Aztlan region on the northern frontier of West Mexico, best known for participation in long distance coastal trade between Northern and West Mexico.

The three Central Mexican sites included are Tlatelolco (AD 1335-1519),

Tenayuca (AD 1200-1519), and Texcaltitlán (AD 1100-1519). All come from the Valley of Mexico in Central Mexico, once the site of Lake Texcoco and the center of the Aztec

Empire. Tlatelolco represents a sample of the population from the largest inter-regional market in Mexico during the Postclassic period, and is also the “sister-city” of the Mexica capital Tenochtitlan. Here I use Tlatelolco to represent a combined Tlatelolco-

Tenochtitlan Aztec sample, in accordance with the history provided by the Codex

Cozcatzin. Texcaltitlán and Tenayuca are samples from cities occupied and controlled by the Aztecs. Tenayuca was an early Chichimec settled site that was conquered early by the

Aztecs and made a tributary province. Texcaltitlán was a major city for the Matlatzinca culture, and was conquered and controlled by the Aztecs as a strategic province on the western frontier of the empire (Berdan et al. 1996). Further information about these sites is provided in Table 2.1.

Table 2.1. Information for samples used in this chapter.

Site Occupation Cultural Group Market Political Affiliation N

Hawiku AD 1400-1680 Zuni Regional Independent 20 Puye AD 1150-1580 Tewa Local Independent 30 Pueblo Bonito AD 828-1130 Anasazi Regional Independent 30 Cuatro Ciénegas AD 1200-1500 Chichimec Local Independent 27 Nararachic AD 1200-1700 Raramuri? Local Independent 18 Copper Canyon AD 1300-1700 Raramuri Local Independent 15 Texcaltitlán AD 1100-1519 Matlatzinca Local Tributary (Aztec) 27 Tlatelolco AD 1335-1519 Aztec-Mexica Interregional Tributary (Aztec) 70 Tenayuca AD 1200-1519 Chichimec Local Tributary (Aztec) 17 Guasave AD 900-1400 Aztatlan Interregional Independent 17 Zacapú AD 1200-1540 Tarascan Regional Tributary (Tarascan) 40

Methods

I used phenetic distances calculated from dental morphological observations as a proxy for genetic relationships among samples. Phenetic distances are biological distances based on morphological (phenotypic) observations. I created model matrices based on expected relationships from geographic distance, shared migration history, trade, and political interaction using archaeological and ethnohistoric data (detailed model descriptions below). It is important to note that these relationships are generalizations about intergroup dynamics during the time period of interest. These generalizations are necessary as political and economic relationships sometimes shifted throughout the temporal periods. I compared these model matrices with the matrix of phenetic distances to test for correlations among phenetic, ecological, and cultural relationships.

Edgar (HE) collected the samples from Tlatelolco and Guasave, and Ragsdale

(CR) collected all other samples. To estimate inter- and intra-observer error, I scored a sample of fifty dentitions of prehistoric Native American dentitions housed at the

Maxwell Museum of Anthropology Laboratory of Human Osteology, once by HE and twice by CR. Traits with no variation (100% or 0% present) were removed prior to calculation, as these traits were not useful for error testing. I calculated Cohen’s kappa, standard error, and percent agreement for intra- and inter-observer error tests. Kappa values for inter- and intra-observer error range from 0.7 to 1.0, and percent agreement range from 86% to 100%, demonstrating high concordance between observations and observers. Intra-observer error for HE is available in Edgar (2002).

Phenetic Distances

Dental morphological traits are small variants of the teeth, mostly on the occlusal

(chewing) surface, used to track changes in population phenotypes over space and time, as the gene frequencies change due to factors such as genetic drift and gene flow (Turner et al. 1991). These traits are scored on a graded scale in accordance with the Arizona

State University Dental Anthropology System (Turner et al. 1991). Phenetic distances using dental morphological variation are useful as a proxy for genetic relationships among archaeological populations, since they are strongly under genetic control (Nichol

1989, 1990; Townsend et al. 2009). Previous studies using modern Pima (Nichol 1989) and Euro-Australian (Townsend et al. 2009; Bockmann et al. 2010) sibling-parent relationships show moderate to high levels of genetic inheritance of some of the dental morphological traits used here (heritability has not yet been estimated for the remaining traits). Using 600 individuals from 83 modern Pima families, Nichol (1989) found an average transmissibility estimate of 0.5. However, Nichol (1989) predates the standardization of scoring procedures for dental traits used here (Turner et al. 1991).

More recent studies by Townsend et al. (2009) and Bockmann et al. (2010) examined more of the standardized traits used here, finding heritability estimates averaging 0.7.

These studies support a high level of inheritance for the traits used in this study.

I scored traits on any observable adult teeth and scored both left and right sides; the higher score represent the maximum expression of the trait in each individual to account for asymmetry. Raw data is dichotomized for use in biological distance statistics.

Presence/absence breakpoints for traits were first drawn from Scott and Turner (1997). I then reviewed raw observations among all samples to explore possible breakpoint

35 adjustments. I found that upper and lower incisor shoveling (UISS) and upper incisor double shoveling (UI1DS) have high frequencies in every sample when the standard breakpoints are used. I adjusted the breakpoints for these traits to better detect variation between groups. These adjustments are highlighted in Table 2.2.

In many dental morphological studies, an observation of absence for the protostylid actually includes the lowest expression of the trait, 1= pit, or foramen caecum molaris. A review of the raw data for this study indicated nearly all of the variation exists among these low expressions. Only two individuals from Guasave, one from Zacapú, and four from Tlatelolco had protostylids scorable above grade 2. For this reason, I chose to keep the standard presence/absence breakpoint (0/1) for this analysis.

I used pseudo-Mahalanobis’ D2 to determine the matrix of phenetic distances among groups (Konigsburg 1990; Irish 2010). Pseudo-Mahalanobis D2 extends the squared Mahalanobis’ distance for use with dichotomized data by using z-scores and a tetrachoric correlation matrix in the calculation (Konigsberg, 1990). The tetrachoric correlation matrix is a matrix of correlation coefficients computed for two normally distributed dichotomized variables, and it serves to account for inter-trait correlations. I chose this statistic, as opposed to Smith’s Mean Measure of Divergence (MMD), because it allows for the use of correlated traits. Recent studies comparing pseudo-Mahalanobis’

D2 and MMD have shown the two statistics are highly correlated, so both are useful in biological distance studies (Edgar 2004; Irish 2010). Tetrachoric correlation matrices and pseudo-Mahalanobis’ D2 values were calculated using SAS Statistical Software (SAS

Institute 2007).

I used Ward’s method of hierarchical clustering to illustrate phenetic distances between samples using the pseudo-Mahalanobis’ D2 matrix, and created a three- dimensional principal component (PC) scatterplot to show the relationships between sites on three axes. Ward’s cluster method produces tree diagrams by forming clusters that minimize intra-cluster variation, while maximizing inter-cluster variation (Ward 1963).

The principal component analysis provides eigenvalues and the percent of the variance accounted for by each axis provided using the phenetic distance matrix, and provides the percentage of variance among samples accounted for on each axis. These analyses were conducted using PAST (Hammer et al. 2001).

Geographic and Cultural Relationships

I used Mantel and partial Mantel tests (1967) to investigate correlations between geographic, cultural, and phenetic distances. Mantel tests compare matrices in thousands of permutations, eliminating assumptions about the distribution of the data being used

(Manly 2005). To test for correlations among cultural variables, I calculated a correlation matrix using Pearson’s correlation coefficient. To account for correlations among the variables, I conducted partial Mantel tests, which allow two matrices to be compared while controlling for similarities with a third matrix (Legendre and Legendre 1998). I created a two-dimensional PC plot of the Mantel correlations, and correlations between geographic and cultural variables. These analyses were conducted using PAST (Hammer et al. 2001). The cultural variables tested were geographic distance, shared migration history, economic exchange, and political interaction.

Table 2.2. Dental morphological traits used to calculate the pseudo-Mahalanobis D2 phenetic distance matrix. Traits are provided with standardized breakpoints, samples size (N), and percent present (%) for each sample. Non-standard breakpoints are italics.

Trait HU PY PU CU NV CC TX TO TN ZU Tooth (- , +) (N) % (N) % (N) % (N) % (N) % (N) % (N) % (N) % (N) % (N) % Shoveling UI1 (0-3, 4-7) (19) 70 (20) 80 (20) 80 (6) 90 (4) 90 (5) 90 (8) 70 (48) 70 (15) 75 (10) 80 Double Shoveling UI1 (0-2, 3-6) (19) 45 (16) 54 (18) 80 (5) 75 (4) 75 (5) 85 (8) 75 (47) 90 (15) 71 (10) 55 Double Shoveling UI2 (0, 1-6) (20) 25 (17) 18 (20) 40 (9) 55 (5) 50 (6) 83 (9) 55 (44) 93 (15) 33 (6) 60 Interruption Groove UI2 (0, 1-4) (21) 24 (18) 44 (20) 30 (8) 10 (6) 10 (6) 50 (9) 37 (44) 41 (16) 33 (15) 14 Tuberculum Dentale UI1 (0-1, 2-6) (20) 65 (19) 63 (20) 50 (8) 43 (5) 90 (5) 67 (8) 75 (44) 36 (15) 86 (10) 50 Tuberculum Dentale UI2 (0-1, 2-6) (19) 47 (18) 28 (19) 53 (8) 62 (5) 90 (6) 33 (9) 25 (40) 42 (15) 43 (14) 15 Tuberculum Dentale UC (0-1, 2-6) (18) 72 (16) 85 (21) 90 (9) 57 (7) 86 (8) 90 (18) 89 (41) 58 (15) 36 (18) 70 Metacone UM1 (0-4, 5-6) (19) 74 (27) 57 (24) 62 (17) 29 (16) 69 (11) 40 (29) 59 (54) 66 (16) 66 (35) 85 Metacone UM2 (0-4, 5-6) (19) 32 (28) 92 (24) 17 (17) 06 (15) 25 (11) 10 (28) 18 (53) 17 (17) 19 (35) 40 Hypocone UM1 (0-4, 5-6) (20) 78 (28) 64 (24) 83 (17) 11 (16) 69 (10) 89 (28) 57 (54) 66 (16) 80 (36) 92 Hypocone UM2 (0-1, 2-6) (20) 60 (26) 20 (24) 71 (17) 69 (15) 83 (10) 89 (27) 73 (52) 81 (17) 37 (36) 83 Cusp 5 UM1 (0, 1-5) (20) 05 (28) 25 (24) 13 (17) 31 (11) 33 (9) 12 (28) 07 (49) 49 (16) 06 (36) 25 Carabelli’s Cusp UM1 (0, 1-7) (20) 01 (28) 04 (23) 33 (19) 64 (16) 11 (9) 71 (23) 64 (48) 56 (11) 40 (36) 57 Parastyle UM1 (0, 1-6) (18) 02 (25) 64 (23) 17 (16) 10 (9) 12 (9) 12 (28) 07 (54) 13 (15) 14 (36) 27 Shoveling LI2 (0-2, 3-7) (16) 26 (14) 67 (15) 71 (11) 49 (5) 90 (6) 80 (7) 66 (45) 98 (16) 50 (19) 83 Anterior Fovea LM1 (0-1, 2-4) (15) 33 (22) 14 (22) 40 (11) 08 (8) 20 (7) 40 (18) 38 (49) 49 (12) 18 (26) 65 Protostylid LM1 (0, 1-7) (15) 33 (22) 23 (22) 50 (13) 75 (8) 43 (7) 83 (21) 75 (54) 62 (16) 46 (27) 77 Protostylid LM2 (0, 1-7) (18) 29 (23) 61 (22) 54 (16) 62 (8) 60 (8) 40 (18) 61 (54) 49 (15) 28 (24) 69 Cusp 5 LM2 (0, 1-5) (18) 22 (25) 23 (24) 29 (18) 44 (8) 33 (8) 57 (21) 40 (52) 86 (15) 28 (24) 33 Cusp 6 LM1 (0, 1-5) (18) 06 (20) 20 (25) 04 (18) 31 (7) 01 (7) 33 (17) 11 (45) 42 (15) 01 (25) 12

Geographic Distance. To determine the extent to which phenetic distances were correlated with geographic distances, this study tested an isolation by distance model

(Wright 1943). According to this model, as geographic distances increase, biological distances should increase. Geographic distances were calculated between all sites, following the shortest possible route given geographic barriers such as mountains or large bodies of water, using global positioning system (GPS) coordinates provided by Google

Earth (see Figure 2.1). Archaeological and historical data provide useful information on routes used for trade and military campaigns to give an estimate of a most likely traveled route. These distances were used to form a model matrix, which, like the other three model matrices (described below) was compared with the matrix of phenetic distances.

Shared Migration History. I created a model matrix of expected group relationships using archaeological, ethnohistoric, and linguistic data for the Postclassic period. Migration histories among populations used here were drawn from archaeological data (Matos Moctezuma 1989; Townsend 1992; Lekson and Cameron 1995; Benson et al.

2007; Beekman 2010), and from ethnohistoric migration documents such as the Boturini

Codex, Codex Xolotl (Douglas 2010), Codex Cozcatzin, and Codex Chimalpopoca

(Bierhorst 1992). Distances used for this matrix were based on branches representing time since a migratory split between populations. I scored a “1” for diverging branches from parent populations to account for migration, as well as for 300 year temporal intervals to account for drift. These scores were added up to give a shared migration distance between any two samples in the study. This model is represented in Figure 2.2a.

Economic Exchange. During the Postclassic period, trade existed on a variety of scales among different regions throughout Mexico and the American Southwest. Trade

39 relationships were drawn from the archaeological record (Riley 1975; Smith and Berdan

2003; Weigand 2008; Crown and Hurst 2009; Beekman 2010; Washburn et al. 2011) and ethnohistoric sources such as the Codex Mendoza (Berdan and Anawalt 1997) and the

Florentine Codex (Sahagun 1950-1982). I coded each sample as a local market, regional market, or inter-regional market. Local markets were periodic events where local food and utility items were exchanged. They acted as venues for intra-population trade.

Regional markets were more frequent and often perennial events that incorporated luxury items as well as utility items, and were venues for intra-regional interaction among populations. Lastly, inter-regional markets were year-round, large markets that exchanged a wide variety of items from various regions around Mexico and the American

Southwest. Trade distances were measured in branch lengths between samples using various market exchange forms. I scored a “1” for interactions between a local market and their respective regional/interregional market; a “2” for interactions between local markets within the same regional trade networks, and for interactions between interregional/regional markets; a “3” for interactions between local markets and regional/interregional markets from another regional trade network; and a “4” for interactions between local markets from different regional trade networks. I also combined scores for samples not in direct contact through trade, but for which goods were likely exchanged through another site. In the statistical analysis, a “99” represented cases where there was no economic interaction between groups. Pueblo Bonito was not included in this analysis as the sample predates all other samples. A representation of this model is provided in Figure 2.2b.

Political Interaction. During the Postclassic period, political expansion and endemic warfare existed throughout Mexico and the American Southwest. Political alliances, military conquest, and the control of resources led to powerful empires such as the Aztec and Tarascan Empires. I coded political interaction based on political structure and relationships among populations (Berdan et al. 1996; LeBlanc 1999; LópezAustin and LópezLujan 2005; Anderson et al. 2012; VanPool and Obrien 2103). I recorded each sample as a city-state, or a capital city-state. City-states refer to all populations in the study that are not a political capital, but are independent cities within a larger polity.

These city-states may also be important trade or religious centers. City-state capitals refer to capital cities within a city-state cultural region or polity; generally, these capitals control other city-states and towns with the same political affiliation. Political distances were measured for different political relationships, for each city-state in the study. I scored a “1” for political allies; a “2” for strict dominant-subordinate relationships between samples such as tributary provinces in the Aztec Empire; a “3” for loose dominant-subordinate relationships between samples such as client-state or frontier provinces around the Aztec Empire; and a “4” for hostile or enemy relationships between samples. For samples with no political interactions, or for political interactions that have not been documented, a “99” was used in the statistical analysis. Pueblo Bonito was not included in this analysis as the sample predates all other samples. Figure 2.2c shows this model.

Figure 2.2: (A) Model for shared migration history. (B) Model for economic exchange. (C) Model for political interaction. Distances represent an average interaction between sites. Pueblo Bonito (PUE), Puye (PUY), Hawiku (HAW), Copper Canyon (COP), Nararachic (NAR), Cuatro Cienegas (CUA), Guasave (GUA), Zacapu (ZAC), Texcaltitlan (TEX), Tenayuca (TEN), and Tlatelolco (TCO).

Results

Pseudo-Mahalanobis’ D2 distances among samples were calculated using data from 21 dental morphological traits. These traits are provided in Table 2.2. Pseudo-

Mahalanobis’ D2, cultural, and geographic model distances are provided in Table 2.3. A

Ward’s cluster dendogram (see Figure 2.3) and three-dimensional principal component scatterplot (see Figure 2.4) show the phenetic distances graphically. Consistent with other

42 biological distances studies of the American Southwest samples (Mackey 1977; El-Najjar

1978; Turner 1993; Schillaci and Stojanowski 2002; LeBlanc et al. 2008), Hawiku and

Puye are relatively close to each other and distant from Pueblo Bonito. Interestingly,

Pueblo Bonito is closer to the Northern Mexico samples from Copper Canyon and

Nararachic than others in the American Southwest. Two of the Central Mexico samples,

Tlatelolco and Texcaltitlán, and the two samples from West Mexico, are closer to each other, compared with samples from Northern Mexico and the American Southwest. One of the Central Mexico sites, Tenayuca, is closer to the Northern Mexico samples and

Pueblo Bonito than to the Central Mexico and West Mexico samples. This result is surprising, especially Tenayuca’s relatively close relationships with the Coahuilan sample from Cuatro Ciénegas, as shown in the Ward’s cluster dendogram. The result of the three-dimensional PC scatterplot shows the greatest distance between Cuatro Ciénegas and all the other samples, as could be expected given the site’s geographic location and economic structure.

Figure 2.3: Ward’s cluster dendogram of phenetic distances using the pseudo-Mahalanobis’ D2 matrix.

Figure 2.4: Three-dimensional principal component analysis of phenetic distances using the pseudo- Mahalanobis’ D2 matrix. Site name abbreviated as in Figure 2.2.

Table 2.3: Distances for pseudo-Mahalanobis D2 and other variables used in Mantel and partial Mantel tests.

HU PY PU CU NR CC TX TO TN ZU GU Hawiku D2 0 Geog 0 Migration 0 Trade 0 Political 0 Puye D2 8.941 0 Geog 268 0 Migration 3 0 Trade 1 0 Political -- 0 Pueblo D2 13.613 17.916 0 Bonito Geog 154 160 0 Migration 2 1 0 Trade -- -- 0 Political -- -- 0 Cuatro D2 14.127 26.213 13.703 0 Ciénegas Geog 1104 1072 1150 0 Migration 9 8 7 0 Trade ------0 Political ------0 Narar- D2 15.424 14.176 9.266 11.162 0 achic Geog 809 898 906 501 0 Migration 4 3 2 9 0 Trade 3 ------0 Political ------0 Copper D2 16.174 34.677 9.390 23.639 23.740 0 Canyon Geog 868 984 981 577 117 0 Migration 4 3 2 9 2 0 Trade 3 ------2 0 Political ------4 0 Texcal- D2 36.487 25.352 16.484 20.867 21.937 15.893 0 titlán Geog 2004 1982 2100 916 1243 1231 0 Migration 9 8 7 8 8 7 0 Trade ------0 Political ------0 Tlateloco D2 30.730 24.948 19.039 13.800 18.891 12.492 16.381 0 Geog 1977 1960 2032 888 1236 1242 92 0 Migration 9 8 7 2 8 8 2 0 Trade ------3 -- -- 1 0 Political ------4 -- -- 3 0 Tenayuca D2 22.558 25.689 22.715 22.335 16.186 20.944 24.003 24.075 0 Geog 1965 1948 2020 876 1224 1229 96 12 0 Migration 9 8 7 2 8 8 3 3 0 Trade ------4 -- -- 2 1 0 Political ------4 ------2 0 Zacapú D2 31.672 37.475 27.093 38.261 28.267 31.166 10.667 15.427 28.412 0 Geog 1824 1841 1898 798 1042 1029 223 274 282 0 Migration 9 8 7 8 9 9 4 4 8 0 Trade ------5 -- 4 3 4 0 Political ------4 4 -- 0 Guasave D2 34.699 25.333 19.272 13.378 7.245 30.767 12.257 8.502 19.939 9.976 0 Geog 1073 1166 1187 657 294 183 1147 1176 1135 925 0 Migration 8 7 6 7 8 8 3 3 7 3 0 Trade ------3 -- 3 2 3 1 0 Political ------4 0

The results of the Mantel tests show shared migration history (corr=0.496, p=0.004), trade (corr=0.441, p=0.005), and geographic distance (corr=0.304, p=0.02) are significantly correlated with pseudo-Mahalanobis’ D2 phenetic distances. Political interaction (corr=0.157, p=0.133) is not significantly correlated with phenetic distances.

Partial Mantel tests indicate that geographic distance is not significantly correlated with phenetic distances when similarities with shared migration history (corr=0.148, p=0.127) or trade (corr=0.067, p=0.681) are controlled. However, shared migration history

(corr=0.493, p=0.003), and trade (corr=0.223, p=0.049) remain correlated when similarities with geographic distance are controlled. The results of the Mantel tests also show all geographic and cultural variables are correlated with the exception of shared migration history and trade (corr=0.06, p=0.593), emphasizing the usefulness of the partial Mantel tests. Results of the Mantel and partial Mantel test are listed in Table 2.4.

A two-dimensional PC plot of the correlations and Mantel tests (Figure 2.5) shows all variables are relatively close, as well as the relative proximity of each variable to phenetic distances. Shorter distances correspond to higher correlations.

Discussion

Although most samples clustered within regional networks or with adjacent regional networks, many samples were not as phenetically similar as the nearest geographically located groups. Pueblo Bonito and Tenayuca are grouped with the

Northern Mexico samples, which are located much further away than other samples from within their respective geographic regions. Mantel and partial Mantel tests show

46 geographic distance is correlated with phenetic distances, but not when trade and shared migration history are controlled.

Table 2.4. Mantel test results for correlations with phenetic distances.

Mantel and Partial Mantel Tests (α=0.05) Variable Correlation p

Mantel tests for geographic/ cultural variables Geographic Distance * Shared Migration 0.518 0.004** Geographic Distance * Trade 0.514 0.003** Geographic Distance * Political Interaction 0.467 0.003** Shared Migration * Trade 0.06 0.593 Shared Migration * Political Interaction 0.44 0.032* Trade * Political Interaction 0.607 0.002** Mantel tests for Phenetic Distances Geographic Distance 0.304 0.02* Shared Migration 0.496 0.004** Trade 0.441 0.005** Political Interaction 0.157 0.133 Partial Mantel tests for Phenetic Distances Geographic Distance + Shared Migration 0.148 0.127 Geographic Distance + Trade 0.067 0.681 Shared Migration + Geographic Distance 0.493 0.003** Trade + Geographic Distance 0.223 0.049*

* p < 0.05. ** p < 0.005.

Northern Mexico and American Southwest samples group together in the Ward’s cluster and principal component analyses. Pueblo Bonito is less distant from the Northern

Mexico samples than to the other Rio Grande Valley samples of Hawiku and Puye, probably due to shared migration history between the Northwest Mexico samples and

Pueblo Bonito. The West Mexico and Central Mexico samples also have a shared migration history and are grouped together, with the exception of Tenayuca in Central

Mexico. Tenayuca was likely established by Chichimec populations from Northern

Mexico (LópezAustin and LópezLujan 2005), which may explain the close phenetic similarity between Tenayuca and the Northern Mexico samples. Tlatelolco and

Texcaltitlán are most similar to the West Mexico samples of Guasave and Zacapú. These similarities are concordant with migration histories of Postclassic Central Mexican groups from an area called Aztlán, believed to be located in West Mexico, from which the Aztec origin myths are derived (Berdan et al. 1996; Berdan 2005).

The Mantel and partial Mantel tests show that economic exchange is correlated with phenetic distance, even when controlling for geographic distance. Generally, most of the samples are grouped together based on their respective regional trade networks or with groups connected through major trade routes. This suggests that although interregional exchange may have had some effect on population movement and genetic exchange, the relationships seen through phenetic distances among the samples are mostly consistent with regional trade relationships. This result is expected, since many of the samples are from the American Southwest and Northern Mexico, where regional markets were often all that was accessible. Some evidence of inter-regional exchange facilitating population movement is seen in the close phenetic relationships between the

West and Central Mexico samples, where trade existed across political boundaries. For example, Zacapú is located within the Tarascan Empire, where trade was regulated by the capital Tzintuntzan (Pollard 2003), although the sample is phenetically similar to samples within the neighboring Aztec Empire. This relationship is confounded by migration history, however, and more data from samples within both regions are needed to further test these relationships.

Finally, the Mantel and partial Mantel tests show no correlation between political interaction and phenetic distance. The only capital city-state among the samples is

Tlatelolco, representing the dominant Tlatelolco-Tenochtitlan group in the Valley of

Mexico. Texcaltitlán and Tenayuca maintained different political relationships with

Tlatelolco and Tenochtitlan. Tenayuca was located in a tributary province, while

Texcaltitlán was located in a strategic province. No other dominant-subordinate relationship occurred among any of the samples. With semi-nomadic populations in

Northern Mexico, geographically isolated sites in the American Southwest, and specific imperial borders in West and Central Mexico, it is not surprising that political relationships had little to no effect on phenetic distances. Future research should include data from more political capitals and subordinate towns or cities.

Conclusion

Data for shared migration histories and trade relationships provided by archaeological and ethnohistoric records are plentiful for Postclassic period Mexican populations, making these groups an ideal choice for testing correlations between biological and cultural relationships. The results presented here suggest cultural processes affect phenetic distances among Postclassic Mexican populations. Here, biological affinities are shaped primarily by shared migration history and economic relationships.

Phenetic distance relationships among the samples chosen here are congruent with what is known about migration patterns in the American Southwest and Mexico. It is interesting that interaction through trade has an effect on population interaction across

49 large geographic areas, and separate political boundaries. This is particularly true for the groups from West and Central Mexico, which were connected only through migration history and trade.

Although Northern Mexico is often considered a region peripheral to the

American Southwest or Mesoamerica, I suggest groups throughout this region played an important role in shaping population affinity in Mexico prior to European contact. These are preliminary results for testing population interaction in prehistoric Mexico, and may be improved upon with more data from other geographic regions and temporal periods.

Further, I conclude the model used here may be usefully applied to more samples from varying political and economic relationships in Mexico and the American Southwest.

This study demonstrates a new approach using modeling to test cultural relationships using dental morphological observations as a proxy for genetic relationships. The model presented here can be extended to other geographic regions or temporal periods.

CHAPTER 3: CULTURAL AND BIOLOGICAL DISTANCE IN POSTCLASSIC PERIOD MEXICO

Widespread trade networks, endemic warfare, imperial expansion, and rapid population growth are factors that are believed to have affected patterns of human variation in pre-contact Mexico. Ethnohistoric records provide a wealth of information about migration history during the Postclassic period, and the archaeological record provides information for population interaction from as early as the first known civilization in Mexico, the Olmec (1500-500 BC). Migrations may involve a series of individuals acting upon the basis of common motives, or the movement of large social groups whose actions are coordinated by a central authority (Cabana and Clark, 2011).

During the Postclassic period in Mexico (AD 900-1519), migrations varied in scale, from the large and long-distance migrations of the nomadic Chichimec populations in Northern

Mexico (Smith, 1984; Bierhorst, 1992), to settlements of several families within the

Aztec Empire to the frontiers of the Gulf Coast (Berdan, 2004, 2014), to political leaders intentionally resettling merchants in high trade areas (Gasco and Berdan, 2003). It is clear that by the Postclassic period, economic, political, and cultural relationships connected virtually every population throughout Mexico (Smith and Berdan, 2003; Melgar, 2010;

McGuire, 2012). At the time of Spanish contact in AD 1519, imperial powers such as the

Aztec and Tarascan Empires dominated much of Mexico. What is not understood is how geographic distances and cultural relationships affected biological relationships and population structure in Mexico prior to Spanish contact. Here, I investigate these phenomena by comparing a triangular matrix of biological distances based on dental

51 morphological traits with triangular matrices of distances derived from geographic distances, political interaction, trade, shared migration history, and shared cultural group membership. Biological similarity derived from morphological (phenotypic) data among groups is assumed to approximate genetic similarity (Scott and Turner, 2000; Hanihara,

2008; Ricaut et al., 2010), and are appropriate for comparing biological and cultural relationships.

I tested five non-mutually exclusive hypotheses about how biological variation relates to cultural variation among Postclassic Mexican groups:

1) geographic distances are correlated with biological distances

2) shared migration history is correlated with biological distances

3) trade is correlated with biological distances

4) political interaction is correlated with biological distances

5) shared cultural group is correlated with biological distance.

If population interaction was primarily influenced by geographic proximity, then the first hypothesis should be supported. If archaeological reconstructions and ethnohistoric accounts of migration are reflected in biological variation, then hypothesis two should be supported. If cultural relationships such as trade and/or political interaction had an effect on migration and genetic exchange among populations, then hypotheses three and/or four should be supported. Finally, if groups primarily interacted with other groups of the same cultural affiliation, then hypothesis five should be supported.

A common approach to investigating political and economic interaction among

Postclassic Mexican populations is to view Mesoamerica using a modified world systems

52 approach (Blanton and Feinman, 1984; Blanton, 1994). Mesoamerica is a term that refers to the cultural area encompassing most of Mexico, Belize, and extending southward into

Central America. A world system, a concept originally developed by Wallerstein (1974) to explain the origins of modern capitalism, is an economic zone composed of core and peripheral societies that extends beyond a single geographic region in which exchange benefits the core. In Mesoamerica, regions such as the Valley of Mexico, Michoacan

(West Mexico), and the Maya region are noted for particularly high levels of interaction and exchange (Blanton 1994). The major criticism of applying this theory to

Mesoamerica is that it is composed of too many competing cores, each distinguished by political or economic structure rather than being dominated by a single core (Smith and

Berdan, 2000; Kepecs and Kohl, 2003). To account for this, the Mesoamerican world system extends cores and peripheries to inter-national trade centers (exchange circuits), affluent production zones, resource extraction zones, and unspecialized peripheries

(Smith and Berdan, 2003). Trade centers engage in inter-regional trade, have a high volume of exchange, and involve a high diversity of goods. Affluent production zones incorporate high production and exchange, but lack powerful polities and large cities such as those found in the Valley of Mexico. Resource extraction zones are located along the periphery, and contain several mines or other extraction areas. Finally, unspecialized peripheries refer to areas that do not fall under any of the aforementioned categories and are often considered on the periphery or outside Mesoamerica. For this study, trade networks include sites of varying socioeconomic structures categorized into these zones, each contributing to the greater Mesoamerican world system. A second criticism of the

Mesoamerican world system is that such a perspective tends to underestimate the

53 contributions of frontier provinces, or areas outside of the known core zones of

Mesoamerica such as Northern Mexico, and parts of the Maya Highlands and Gulf Coast

(Wells, 2006). To accommodate this reservation, I considered populations in these regions as part of the Mexican world system, as it is assumed these populations contributed to population interactions.

A holistic approach to understanding population interaction and migration is optimal for gaining a better understanding of the effects of imperial expansion, intensified trade, and shared ideology on patterns of migration among prehistoric human populations. This study also evaluates how well migration histories from written sources and reconstructions of migration histories based upon material culture are reflected in population structure.

Previous Biological Distance Studies

Previous biological distance studies have focused on migration patterns among the

Classic and Postclassic period populations in Northern, Western, and Central Mexico. Using craniofacial measurements, Gonzales-Jose et al. (2007) found Central Mexican samples to be similar to West Mexican samples, and different than earlier Central and Northern Mexican samples. Several other studies have utilized dental morphological data to address issues surrounding population relationships. Aubry (2009) found relatively close biological distances between Central Mexican and Maya groups during the Classic period (AD 300-

900). These patterns were consistent with migration patterns identified on the basis of archaeological similarities, as well as inter-regional interaction through trade. Willermet et al.

(2013) found similar results in a small-scale study of population structure in Mexico during the Classic and Postclassic periods, which supported a migration history from the Aztitlan region in West Mexico to other areas of West Mexico as well as Central Mexico. Gómez-

Valdéz (2008) investigated relationships among mostly West Mexican samples from the

Classic period (AD 300-900). He found the Postclassic period sample from Tlatelolco in

Central Mexico to be similar to West Mexico, as well as to other Central Mexico samples from the Classic period. Distances were especially low between Tlatelolco and the samples from the Aztitlan region of West Mexico. Finally, Ragsdale and Edgar (2014) found similarities between Central, West, and North Mexican Postclassic samples, thereby providing supporting evidence for migrations from the North and West into Central Mexico at this time. Their study also found shared migration and trade to be related to biological distances among Postclassic populations in Mexico and the American Southwest.

Other biological distance studies using dental morphological traits from these regions have focused on testing hypotheses about migration, language group distribution, and shared cultural group (Turner, 1993; LeBlanc et al., 2008). Turner’s work (1993) indicated that biological distances were related to geographic proximity and cultural group among prehistoric and modern American Southwest and Mexican populations. However, biological distances were not related to linguistic classification. LeBlanc et al. (2008) also compared

American Southwest and Mexican samples to examine how culture and language correlated with biological distances. Their results revealed small biological distances between American

Southwest and Northern Mexican, combined Central Mexican, and Coahuilan (Northeast

Mexico) samples. Unlike LeBlanc et al. (2008), who combined Mexican samples to facilitate

55 an evolution of the spread of Uto-Aztecan speakers, the current study evaluates cultural and biological relationships among samples without combining them by region or nation.

Others have have used ancient DNA as the basis for assessing the relationship between biology and culture. Kemp et al.’s (2005) analysis of mtDNA found the sample from

Tlatelolco to be more similar to other samples from Central and Southern Mexico than to other Uto-Aztecan speaking groups in Northern Mexico and the American Southwest. In a second study, Mata-Miguez et al. (2012) used mtDNA to investigate the effect of Aztec political dominance on the population structure of the city-state capital of Xaltocan. Their results show populations existing before and after Aztec expansion were found to have different mtDNA haplotypes, indicating a change in population structure corresponding to the Aztec conquest of Xaltocan.

Materials and Methods

The geographic locations of all samples included in the current study are provided in

Figure 3.1. I observed dental morphological traits in the permanent dentition of 810 human skeletal remains housed at various institutions in the United States and Mexico. Since the objective of this study is to investigate the effects of trade and political relationships on population movements during the Postclassic period, I selected samples to represent populations involved in various forms of trade, military, or political interaction, and with several different migration histories and cultural affiliations. All samples date to the Middle to Late Postclassic period (AD 1200-1519), with some assemblages possibly encompassing a few individuals from the Late Classic (AD 600-900), Early Postclassic (AD 900-1200), and

Early Colonial (AD 1519-1600) periods. Twelve samples are from Central Mexico (n=428), six are from West Mexico (n=155), and ten samples are from the peripheral regions of

Northern Mexico (n=110), the Gulf Coast (n=107), and the Maya region (n=110). A list of samples, their dates, cultural group, and world system zone classification is provided in Table

3.1. It is important to note, the Maya sample from Jaina Island likely corresponds to the

Terminal Classic/Early Postclassic periods (AD 800-1200), predating most of the other samples in this study. We include the sample here for the purpose of investigating migration histories and early economic processes.

Figure 3.1. Location of sites used in this chapter.

Table 3.1. Sites represented by samples. Corey Ragsdale (CR) and Heather Edgar (HE).

Archaeological Site (n) Date (AD) Cultural Group Observer World System Zone Northern Mexico Cuatro Ciénegas (18) 1300-1500 Coahuilan-Chichimeca CR Periphery Candelaria-Paila (32) 1300-1500 Coahuilan-Chichimeca HE Periphery Paquimé (35) 1180-1400 Casas Grandes CR Periphery Nararachic (25) 1300-1600 Casas Grandes- Raramuri CR Periphery West Mexico Autlan-Tuxcacuesco (15) 1100-1550 West Mexico CR Extraction Chalpa-Tecualilla (22) 1100-1350 West Mexico CR Production/Extraction Guasave (20) 900-1400 Aztitlan CR/HE Extraction Huejuquilla (18) 1000-1550 Aztitlan HE Extraction Tzintzuntzan (30) 1200-1550 Tarascan-Patzcuaro CR Core/Exchange Zacapú (50) 1200-1550 Tarascan-Zacapu CR Production/Exchange Toluca Valley Teotenango (27) 1250-1450 Matlatzinca-Chichimeca CR Extraction/Exchange Texcaltitlán (27) 1250-1550 Matlatzinca-Chichimeca CR Extraction/Exchange Valley of Mexico Azcapotzalco (47) 1200-1519 Aztec-Tepeneca CR Core/Exchange Cholula (58) 1300-1519 Tolteca-Cholulan CR/HE Core/Exchange Culhuacán (32) 1220-1519 Tolteca-Chichimeca CR Core/Exchange Huexotla (20) 1200-1519 Aztec-Alcolhua CR Core/Exchange Tenayuca (20) 1200-1519 Tepenec-Chichimeca CR Core/Exchange Teopanzolco (26) 1200-1550 Aztec-Tlahuica CR Production/Exchange Tlatelolco (70) 1340-1519 Aztec-Mexica CR/HE Core/Exchange Xochimilco (49) 1200-1519 Aztec-Xochimilca CR Core/Exchange Oaxaca Valley Yagul (32) 1200-1519 Zapotec CR Production Zaachila (20) 1200-1519 Zapotec CR Production Gulf Coast of Mexico Tamtok (37) 1200-1550 Huastec CR Production Vista Hermosa (25) 1200-1550 Huastec CR Production Zapotal (45) 1000-1550 Totonac HE Production/Exchange Maya Region Chicoasen (20) 1200-1550 Chiapa Maya CR Production/Extraction Cozumel (40) 1200-1550 Yucatec Maya CR Production/Exchange Jaina Island (50) 700-1100 Yucatec Maya HE Production/Extraction

Biological distances among samples were obtained from dental morphological trait frequencies were compared with model matrices to determine whether cultural, political and trade relationships correlate with biological distances. The distance matrix based on dental morphology serves as a phenetic proxy for the genetic distances between samples.

Geographic and cultural distances were recorded as pair-wise relationships using matrices for each variable tested. These variables include geographic distance, shared migration history, shared cultural group, trade, and political interaction. These models were created using information from archaeological and ethnohistoric sources. Mantel and partial Mantel tests were used to investigate correlations between geographic, cultural, and biological distances.

Biological distances

Observations were made on 62 maxillary and mandibular dental morphological traits on all permanent teeth for which these traits could be assessed. Consequently, traits were not recorded in cases of damaged teeth, teeth affected by severe dental wear, or teeth suffering from large carious lesions. The trait expressions were scored on a standardized ordinal graded scale in accordance with the Arizona State University Dental

Anthropology System (Turner et al., 1991) and dichotomized for statistical analysis.

Traits were scored on both left and right antimeres. The highest score for each trait, representing the maximum expression, was used consistently in analysis to control for asymmetry (Turner and Scott, 1977; Turner et al., 1991; Scott and Turner, 2000).

Dichotomization breakpoints were drawn primarily from Scott and Turner (2000). In some cases, breakpoints were adjusted based on the variance among samples in the study.

These traits include shoveling of the maxillary incisors, shoveling of the mandibular central incisors, and the protostylid (lower first and second molars). Shoveling on the

59 maxillary and mandibular incisors is present at high frequencies (over .90) for all of the samples used here, so an adjusted breakpoint was necessary for analysis. For the protostylid, the foramen caecum molaris (score of “1”) was not included as present, as the use of this expression is controversial. Hence, the protostylid was only considered as present when scored at grade 2 and above. Adjusted breakpoints are provided in

Appendices 1-3.

Intra- and inter-observer error tests for dental morphological observations were conducted to evaluate repeatability for each observer, and replicability between observers. Observations were made on 50 dentitions from a prehistoric skeletal collection. I calculated Cohen’s kappa, standard error, and percent agreement.

Tetrachoric correlation matrices and pseudo-Mahalanobis’ D2 values were calculated using SAS Statistical Software v.9.1.3. I used PAST (Hammer et al., 2001) to create a three-dimensional principal component scatterplot to show the relationships between sites.

Dental morphological traits are generally not sexual dimorphic (Scott and Turner,

2000). To test the effects of sexual dimorphism on observations, I calculated trait frequencies separately for males and females and compared the frequencies using a Chi- squared test. Chi-squared values (χ2) for the traits used in the final analysis ranged from

χ2= 0.90 to χ2= 1. I also conducted a Mantel test to evaluate the correlation between the male and female datasets. The frequency datasets were highly correlated (r= 0.967, p=0.0002), and the differences between males and females ranged from 0 to 0.25 among the traits used in the final analysis.

The pseudo-Mahalanobis’ D2 distance statistic was used to create the biological distance matrix (Konigsberg, 1990; Irish, 2010). This statistic extends the squared

Mahalanobis’ distance for use with frequency data by using a tetrachoric correlation matrix in the calculation (Konigsberg, 1990). The tetrachoric correlation matrix consists of correlation coefficients computed for two normally distributed dichotomized variables, and it serves to account for inter-trait correlations. Traits with similar frequencies among all samples were removed prior to calculating the tetrachoric correlation matrix since variation could not be detected. Additionally, traits with missing data for more than half of the individuals within any of the samples were removed prior to calculating the tetrachoric correlation matrix to avoid misrepresentation of trait frequencies. Twenty- three of the 62 traits scored were included in the tetrachoric correlation matrix.

Some biological distance studies based upon dental morphological trait frequencies use the Mean Measure of Divergence (MMD) statistic, since it is useful in comparing groups with small sample sizes and high amounts of missing data (De Souza and Houghton, 1977). Previous comparisons of pseudo-Mahalanobis’ D2 and MMD have shown overall agreement between biological distance matrices generated using both methods (Edgar, 2004; Irish, 2010). I chose to use the pseudo-Mahalanobis’ D2 because, unlike MMD, it allows for the inclusion of correlated traits (Edgar, 2004; Irish, 2010).

Geographic and cultural variables

I used Mantel and partial Mantel tests (Mantel, 1967) to determine correlations between distances obtained from biological, geographic, and cultural variables. Mantel

61 tests compare matrices in thousands of permutations, eliminating assumptions about the distribution of the data being used (Manly, 1986). These tests were used to calculate correlations (ZN) between the geographic and cultural variables. To account for correlations among the variables, I also conducted partial Mantel tests, which allow two matrices to be compared while controlling for similarities with a third matrix (Legendre and Legendre, 1998). These analyses were conducted using PAST (Hammer et al., 2001).

The cultural variables tested were shared migration history, shared cultural group, trade, and political interaction. I also combined trade and political interaction into a single matrix to represent total economic-political interaction. Each variable is described in detail below.

Geographic distance. This study tests an isolation by distance model, which assumes that as geographic distances increase, so too do biological distances (Wright,

1943). Geographic distances were calculated using global positioning system (GPS) coordinates between any two sites following the shortest possible route given major geographic barriers such as mountains or large bodies of water (see Figure 3.1 for approximate GPS locations). GPS coordinates and geographic distances were obtained using Google Earth. The matrix of geographic distances is provided in Table 3.2.

Shared migration history. A model matrix was used to determine the relationship between biological variance and shared migration history. The model matrix was based upon expected relationships drawn from available ethnohistoric and linguistic data for the

Postclassic period. See Figures 3.2a and 3.2b for an illustration of this model. Migration histories among the samples used here were estimated primarily from such ethnohistoric migration documents as the Boturini Codex, Codex Xolotl (Douglas, 2010), Codex

Cozcatzin, and Codex Chimalpopoca (Bierhorst, 1992). These sources provide a wealth of information about migrations, primarily for Central and West Mexican populations.

Further ethnographic sources for migration are provided in Smith (1984). Where ethnohistoric sources were unavailable, migration was inferred from archaeological data

(Lekson and Cameron, 1995; Townsend, 2000; Benson et al., 2007; Beekman, 2010).

Figure 3.2. Model for shared migration history. Branch lengths representing time since split from parent population. Abbreviations: Autlan-Tuxcacuesco (AT); Azcapotzalco (AZ); Candelaria-Paila (CP); Chalpa- Tecualilla (CT); Chicoasen (CN); Cholula (CH); Cozumel (CZ); Culhuacan (CU); Cuatro Ciénegas (CC); Guasave (GU); Huejuquilla (HU); Huexotla (HX); Jaina Island (JA); Nararachic (NA); Paquimé (PA); Tamtok (TK); Tenayuca (TN); Teopanzolco (TP), Teotenango (TG); Texcaltitlán (TX); Tlatelolco- Tenochtitlan (TO); Tzintzuntzan (TZ); Vista Hermosa (VH); Xochimilco (XO); Zaachila (ZA); Yagul (YG); Zacapu (ZU); and Zapotal (ZP).

For this study, I focus on large-scale migrations, since these are the most evident in the ethnohistoric and archaeological records. These data were used to create a model matrix representing relationships among all the samples, with each branch representing time since the most shared migration between any two groups. Distances between samples used for this matrix were based on branch lengths from shared parent populations. These branches represent number of generation since a split from a shared parent population, based on 25-year generations. These distances account for the effects of genetic drift over time. To account for cases where two samples shared multiple migrant groups, I created a second matrix based on the number of parent populations shared between samples. I then divided the values of the first matrix by the values of the second matrix to form the final shared migration history matrix used in the Mantel tests.

This scaled the original matrix to account for multiple shared migrations between groups.

For this model I assume all migrant populations are equal size, since it is not possible to discern otherwise from archaeological or ethnohistoric data. Since this model is based on populations founding new sites, I also assume equal size of populations for initial settlements.

Shared cultural group. Archaeologists distinguish cultural identities using a wide array of material culture data (Emberling, 1997). However, cultural similarities may not

64 be the best indicator of population movement. Art styles and religious ideas can be exchanged across disparate populations through elite interactions, and similarity in tool form may occur through necessity to accomplish a specific function. In this study, I seek to test the reliability of material culture and shared language group as an indicator of group membership. Cultural group was recorded for each sample as identified from archaeological data in order to test the extent to which it is correlated with biological similarity. When material remains were present in burials, cultural group was determined based on the associated artifacts. In all other cases, a general cultural affiliation was determined based upon the archaeological data from the site from which the sample was derived. The known cultural groups associated with samples used in this study are provided in Table 3.1. I scored distances between samples based on shared language group, shared cultural group, and, in some cases, shared cultural sub-group. See Figure

3.3 for an illustration of this model.

Figure 3.3. Model for shared cultural group. Abbreviations are the same as in Figure 3.2a

Trade. I recorded trade as relationships determined by trade systems that crossed political boundaries as defined by Mesoamerican world systems theory (Smith and

Berdan, 2000; Smith, 2001). Trade existed on a variety of scales among different regions throughout Mexico during the Postclassic period, ranging from local trade networks within a city or town, to intra-regional exchange, to long-distance trade (Berdan, 1989;

Blanton, 1996; Gasco and Berdan, 2003). Trade was facilitated through trade routes that stretched across political borders and through regional markets that were in continuous use throughout the year. Distances were recorded between samples according to trade relationships documented by archaeological and ethnohistoric data. I recorded each sample in the study as a local, regional, or inter-regional market (Berdan, 1989; Blanton,

1996). Local markets were periodic events where local food and utility items were exchanged, and acted as venues for frequent intra-population trade. Regional markets were more frequent and often perennial events that incorporated luxury items as well as utility items (Berdan, 1989; Blanton, 1996), and were venues for much inter-population and intra-regional interaction among populations. Lastly, inter-regional markets were year-round, large markets that featured the exchange of a wide variety of items from various regions within and adjacent to Mexico (Berdan, 1989; Blanton, 1996, Gasco and

Berdan, 2003). Inter-regional markets were venues for inter-regional interaction, as well as a place of settlement for merchants such as the pochteca, professional Aztec merchants. Trade relationships were measured in distances between these various market exchange forms. The distances reflect population interaction through trade. Low scores were recorded for interactions between local markets and regional/inter-regional markets

66 from the same region and between regional markets; high scores were recorded for interactions between local markets and regional markets from other regions, and between local markets in different regions. Since inter-regional markets served as regional exchange centers for numerous regions, interactions with these markets were scored as regional markets for multiple, adjacent regions. Trade distances were based on average, generalized relationships among sample pairs were employed to account for shifting trade relationships over time. See Figure 3.4 for an illustration of this model.

Figure 3.4. Model for economic exchange (trade). Abbreviations are the same as in Figure 3.2a

Political interaction. I recorded political interaction among samples as distances between groups based on frequency of political contact. Particularly in Central Mexico, political relationships such as through tribute payments and military campaigns are well documented in ethnohistoric sources such as the Codex Mendoza (Berdan and Anawalt,

1997). I recorded all samples as either a city-state or a capital city-state. City-states are samples in the study drawn from populations that did not serve as a political capital, but

67 are independent cities within a larger polity. These city-states may also be important trade or religious centers independent of, or in addition to, their status as political centers. City- state capitals are capital cities within a city-state cultural region or polity that controlled other city-states or towns with the same political affiliation. Political distances were measured for different political relationships among all city-states in the study. Low scores were recorded for direct political relationships such as political allies and tributary provinces; high scores were recorded for frontier provinces, frequent hostile interactions between two samples, and groups that had only occasional interactions through raiding or political envoys. Political relationships were constantly changing throughout the

Postclassic period, particularly within imperial boundaries, so I used average relationships were recorded according to the best archaeological and ethnohistoric information. See Figure 3.5 for an illustration of this model.

Figure 3.5. Model for political interaction. Abbreviations are the same as in Figure 3.2a

There are missing data in the political relationship matrix, because not all groups interacted politically. For this reason, I also compared the biological distance matrix to a matrix representing combined trade and political interaction. This matrix allows full representation of cultural interaction among groups, based on what is known from ethnohistoric and archaeological records. Groups with the most shared trade and political interaction have the lowest scores, and groups with little or no interaction through either process have the highest scores.

Results

Results of the inter- and intra-observer error tests show high concordance between observations and observers. Kappa values for inter-observer error range from 0.7 to 1.0, and percent agreement range from 86% to 100%. Both intra-observer tests showed a kappa value of 0.85 to 1.0, and a percent agreement of 91% to 100%. These results are also available in Ragsdale and Edgar (2014), and other intra-observer error results are provided in Edgar (2002).

The pseudo-Mahalanobis’ D2 distance matrix and the matrix of pairwise geographic distances are provided in Table 2. Figure 3.6 is a scatterplot showing these relationships on the first three principal axes, accounting for approximately 83% of the total variation.

Results of the three-dimensional principal component analysis show that many of the samples from Central Mexico, West Mexico, and the Gulf Coast are clustered together on

Components 1 and 2.

Table 3.2. Pseudo-Mahalanobis’ D2 distance matrix (bottom diagonal) and geographic distances in

kilometers (top diagonal).

0.00

217

952

413

780

1037

633

788

1321

1690

1390

509

790

721

701

574

579

435

415

408

211

465

241

445

415

397

275

3.15

0.00

250

985

552

261

1070

666

821

1354

1666

1366

485

766

697

677

551

556

411

391

384

188

441

218

421

391

373

251

27.71

33.70

0.00

754

342

127

889

564

710

1171

1863

1563

682

963

894

874

763

768

608

588

581

400

638

430

618

588

570

446

19.22

25.38

3.43

0.00

409

750

303

635

657

539

2585

2285

1404

1685

1616

1596

1514

1519

1330

1310

1303

1151

1360

1181

1340

1310

1292

1169

11.21

8.20

25.36

24.51

0.00

367

591

483

597

884

2183

1883

1002

1283

1214

1194

1097

1102

928

908

901

734

958

764

938

908

890

765

13.71

15.10

33.41

28.59

7.90

0.00

950

684

823

1245

1923

1623

742

1023

954

934

806

811

668

648

641

443

698

473

678

648

630

514

23.94

17.59

24.40

18.24

24.20

25.54

0.00

480

397

283

2277

2457

1817

1657

840

1018

1599

1604

1368

1348

1341

1236

1398

1266

1378

1348

1330

1229

30.78

30.64

49.73

42.11

28.35

29.52

32.75

0.00

149

763

1935

2357

1335

1105

371

534

1142

1147

871

851

844

779

901

809

881

851

833

753

29.90

24.38

46.15

39.04

25.60

18.36

33.85

16.96

0.00

680

2100

2500

1457

1227

466

656

1281

1286

999

979

972

918

1029

948

1009

979

961

883

12.39

15.39

33.88

19.76

17.27

22.00

12.07

26.19

26.91

0.00

2560

2740

2100

1940

1123

1301

1871

1876

1625

1605

1598

1508

1655

1538

1635

1605

1587

1497

18.44

18.02

18.94

16.50

24.08

21.53

22.01

32.41

40.39

26.69

0.00

475

630

1360

1190

810

780

1604

1612

1656

1582

1625

1572

1581

1498

1603

20.00

20.28

50.25

46.34

17.95

15.33

49.47

35.77

28.46

36.79

35.11

0.00

740

890

1645

1475

1107

1077

1304

1312

1356

1282

1325

1272

1281

1198

1303

29.04

23.40

28.95

24.01

21.31

67.49

48.63

26.15

41.69

49.57

28.06

20.81

0.00

230

993

820

392

356

704

712

756

682

725

672

681

598

703

16.19

13.61

21.44

17.91

17.96

15.73

20.28

25.22

25.64

23.72

3.17

27.93

36.36

0.00

763

592

224

189

486

502

497

539

468

512

452

466

382

482

18.37

10.65

20.85

19.33

17.85

11.81

27.83

40.01

36.10

26.58

12.23

20.71

37.05

12.54

0.00

170

613

697

378

355

343

426

410

411

342

374

393

357

12.11

10.19

13.23

13.85

18.61

10.06

18.00

43.73

36.62

25.32

12.73

26.03

47.36

12.66

5.03

0.00

684

626

309

286

275

363

345

346

274

304

327

300

11.87

12.57

46.93

31.48

16.53

21.47

36.78

56.15

40.55

20.53

29.42

40.32

19.75

25.97

21.60

25.80

0.00

411

382

404

343

386

384

390

363

287

385

12.76

17.84

50.20

36.70

9.20

11.96

35.50

48.04

30.26

21.70

27.53

23.75

11.07

19.82

18.75

21.85

5.64

0.00

434

405

429

368

409

407

413

386

302

404

11.87

15.60

44.80

36.64

13.22

9.52

20.42

27.25

25.13

16.80

21.45

17.36

26.37

15.02

17.60

17.35

21.85

12.06

0.00

130

10.03

18.45

27.36

23.75

11.84

13.65

16.33

34.57

41.10

19.67

8.89

22.89

45.66

10.36

10.55

10.09

25.43

19.82

8.04

0.00

115

151

13.56

12.30

23.78

17.70

16.74

19.14

19.94

35.43

32.24

14.48

15.77

29.55

37.80

14.39

11.25

12.10

14.41

18.04

13.60

10.18

0.00

144

125

110

206

128

9.89

6.45

37.35

27.30

10.44

15.19

19.27

39.56

30.25

12.51

21.73

32.67

26.63

17.46

16.29

17.37

9.66

10.01

8.54

13.14

8.26

0.00

150

10.26

14.07

58.94

44.42

11.13

20.11

40.86

39.26

29.06

20.38

34.50

23.19

13.81

25.75

21.18

31.43

11.55

7.80

11.35

22.75

13.19

11.32

0.00

137

15.11

14.01

27.71

18.89

16.46

20.12

24.18

37.31

35.88

21.41

18.17

41.67

33.83

17.15

15.39

17.52

13.52

15.92

17.82

14.60

11.60

12.98

20.03

0.00

188

17.28

8.66

32.63

22.67

9.97

9.96

21.85

43.89

34.90

14.67

17.18

27.73

25.51

15.50

7.82

10.25

6.69

7.84

11.78

9.31

9.63

6.17

12.24

10.64

0.00

125

17.16

9.04

29.40

25.96

10.52

11.46

13.64

28.31

30.38

20.81

9.98

29.34

42.11

8.88

12.97

10.99

27.84

21.95

7.08

5.31

13.48

12.98

24.37

10.54

12.88

0.00

145

15.01

10.63

22.67

16.40

13.09

13.43

16.18

29.66

24.17

18.52

10.42

31.21

34.81

5.43

11.42

11.71

20.88

16.02

13.04

11.59

12.67

14.03

19.59

6.28

10.25

6.97

0.00

163

11.80

7.83

41.43

30.85

15.47

12.14

18.53

25.09

25.42

16.26

14.06

27.01

25.69

9.27

15.16

18.01

15.65

10.47

5.42

9.07

12.36

10.26

11.32

7.93

8.43

6.16

6.35

0.00

Zacapu

Tzintzuntzan

Huejuquilla

Guasave

Tecualilla

Tuxcacuesco

Nararachic

Candelaria

Cienegas Cienegas

Paquime

Jaina Island Jaina

Cozumel

Chicoasen

Zapotal

Vista Hermosa Vista

Tamtok

Zaachila

Yagul

Xochimilco

Tlatelolco

Tenayuca

Texcaltitlan

Teopanzolco

Teotenango Teotenango

Huexotla

Culhuacan Cholula Azcapotzalco

Figure 3.6. Three dimensional principle components analysis of pseudo-Mahalanobis’ D2 distances. Abbreviations are the same as Figures 3.2-3.5. Shapes represent geographic regions: square=Central Mexico; triangle=West Mexico; inverted triangle=Maya region; diamond=Northern Mexico; and cross=Gulf Coast.

The samples from Central Mexico are slightly separated on Component 1.

Texcaltitlán (TX), Xochimilco (XO), Azcapotzalco (AZ), and Huexotla (HX) are more similar to some samples from West Mexico; Tenayuca (TN), Teotenango (TG), Cholula

(CH), Culhuacan (CU), and Tlatelolco (TO) are more similar to the Gulf Coast samples from Tamtok (TK), Vista Hermosa (VH), and Zapotal (ZP). Other samples from each region, excluding the Gulf Coast, are located outside this cluster. Among the closest similarities are those between Azcapotzalco (AZ) and Xochimilco (XO), Cholula (CH) and Zapotal (ZP), Culhuacan (CU) and Tlatelolco (TO), Tamtok (TK) and Vista Hermosa

(VH), Jaina Island (JA) and Zapotal (ZP), Huejuquilla (HU) and Guasave (GU), and

Tzintzuntzan (TZ) and Zacapú (ZU).

Matrices for shared migration history, shared cultural group, trade, political interaction, and combined trade/political interaction are available in Appendices 4-8, respectively. Results of the Mantel and partial Mantel tests between these variables are also provided in Appendix 9. Most of the distances are correlated at the (p = 0.05) or (p =

0.005) level, highlighting the importance of the partial Mantel tests. However, geographic distance is not correlated with trade (ZN = 0.173, p = 0.057) or cultural interaction (ZN =

0.074, p = 0.121). Nor is trade correlated with shared cultural group (0.157, p = 0.054).

The results of the Mantel tests comparing the pseudo-Mahalanobis’ D2 distances to the geographic and cultural variables show shared migration (ZN = 0.348, p = 0.002), trade

(ZN = 0.344, p = 0.002), shared cultural group (ZN = 0.348, p = 0.002), political interaction (ZN = 0.0.271, p = 0.005), and trade/political interaction (ZN = 0.374, p =

0.002) are significantly correlated with biological distances, while geographic distance

(ZN = 0.054, p = 0.794) is not. When analyzed further using partial Mantel tests, geographic distance remains uncorrelated. Political interaction remains correlated with biological distance when similarities with geographic distance (ZN = 0.283, p = 0.002) and shared migration (ZN = 0.283, p = 0.002) are controlled. Political interaction is not correlated with biological distances when similarities with shared cultural group (ZN =

0.181, p =0.056) and trade (ZN = 0.158, p = 0.052) are controlled. Shared cultural group and trade remain correlated with phenetic distances with all other variables considered in the partial Mantel tests. Regional Mantel tests results are available in Appendix 10.

Table 3.3. Results of Mantel and partial Mantel tests for pseudo-Mahalanobis D2 distances.

Variable (s) Correlation (ZN ) p Geographic Distance 0.054 0.794 Shared Migration 0.348 0.002** Trade 0.344 0.002** Political Interaction 0.271 0.005* Trade/Political 0.374 0.002** Cultural Group 0.348 0.002** Geographic + Migration 0.073 0.888 Geographic + Trade 0.072 0.869 Geographic + Political 0.101 0.958 Geographic + Trade/Political 0.101 0.956 Geographic + Cultural Group 0.085 0.923 Migration + Geographic Distance 0.258 0.004* Migration + Trade 0.272 0.005* Migration + Political 0.238 0.004* Migration + Trade/Political 0.218 0.013* Migration + Cultural Group 0.213 0.011* Cultural Group + Geographic Distance 0.343 0.002** Cultural Group + Migration 0.218 0.017* Cultural Group + Trade 0.305 0.006* Cultural Group + Political 0.256 0.009* Cultural Group + Trade/Political 0.250 0.018* Trade + Geographic Distance 0.369 0.001** Trade + Migration 0.362 0.002** Trade + Cultural Group 0.381 0.001** Trade + Political 0.369 0.002** Political + Geographic Distance 0.283 0.002** Political + Migration 0.181 0.038* Political + Cultural Group 0.151 0.056 Political + Trade 0.158 0.052 Trade/Political + Geographic Distance 0.382 0.001** Trade/Political + Migration 0.342 0.001** Trade/Political + Cultural Group 0.401 0.001** Note: p values are averaged over 10 tests. Italics indicate the variable that is controlled for in the partial Mantel tests. *0.05 **0.005

Discussion

The pseudo-Mahalanobis’ D2 distance matrix shows strong similarities among most of the groups within Central Mexico, as well as between these Central Mexican samples and samples from parts of West Mexico and the Gulf Coast. It is not surprising that many of the groups in the Valley of Mexico are similar to each other, since they share migration histories (López Austin and López Lujan, 2001; Berdan, 2004; Douglas,

2010), were in frequent contact through economic processes such as regional and inter- regional trade (Smith and Berdan, 2003), and are geographically proximate to each other.

Some of the samples from the Valley of Mexico, however, were unexpectedly more similar to samples from other areas in Central Mexico and other regions. Some examples of these similarities are Teopanzolco (TP) and the Oaxaca Valley samples, Cholula (CH) and the Gulf Coast sample of Zapotal (ZP), and the cluster of Chichimec samples from the Valley of Mexico (Tenayuca (TN) and Huexotla (HX)) and the Toluca Valley

(Texcaltitlán (TX) and Teotenengo (TG)) to the West. The samples from the Huasteca region (Tamtok (TK) and Vista Hermosa (VH)) are also unexpectedly similar to samples from the Valley of Mexico (Tlatelolco-Tenochtitlan (TO) and Culhuacán (CU)), given the relative geographic isolation of this region. The similarities between some of the West

Mexico samples and the samples from Central Mexico are also surprising. These regions were politically and geographically disparate, and interaction between the two regions is believed to have been primarily hostile (Hassig, 1988; Berdan et al., 1996; Pollard and

Smith, 2003). None of the geographic or cultural variables are correlated with phenetic distances in West Mexico. This may be due to limited samples available for this region;

74 more data from other groups in this region will help further elucidate these relationships.

Results concerning each of the hypotheses are discussed below.

Hypothesis 1: geographic distances and biological distances. This hypothesis is not supported by the Mantel or partial Mantel tests. Although many of the samples fit within clusters of other samples in their respective geographic region, the Mantel and partial Mantel tests indicate populations are not most similar to other populations to which they are geographically most proximate. This is particularly true in Central

Mexico, where all of the samples are relatively similar to one another. Even when similarities with all other variables are controlled, geographic distance remains uncorrelated. The principal component scatterplot also shows significant overlap between the West Mexico, Central Mexico, and the Gulf Coast samples. When viewed regionally, geographic distance remains uncorrelated in the Mantel tests, indicating proximity within geographic regions is not related to phenetic similarity. These results indicate population interaction is not limited by geographic proximity, but is confounded by cultural interactions.

Hypothesis 2: shared migration history among populations and biological distances. This hypothesis is supported by the Mantel and partial Mantel tests. These results are concordant with migration histories developed using archaeological and ethnohistoric sources. Several Central and West Mexico samples are biologically similar to each other, as expected if those samples shared a parent population originating in West

Mexico. There are also close similarities among the samples that are Chichimec or

Matlatzinca settled sites. This agrees with the origin account of Northern Mexican migrations into West and Central Mexico (López Austin and López Lujan, 2001; Berdan,

2004; Douglas, 2010). Small biological distances among Central and the West Mexico samples also supports these migration origin accounts. The Gulf Coast samples are also similar to the Central Mexican samples from Tenayuca, Teotenango, Cholula, Culhuacán, and Tlatelolco-Tenochtitlan. Such similarities may reflect the migration of Toltec populations after the demise of Tula in the twelfth century, particularly for Culhuacán and Cholula, remnant Toltec cities that survived the Toltec collapse (Berdan et al., 1996;

López Austin and López Lujan, 2001; Smith and Berdan, 2003). The Mexica at

Tlatelolco and Tenochtitlan claimed a strong heritage with the Toltecs in Central Mexico to legitimate their claims for power, and were mercenaries of Culhuacán before establishing their own city at Tenochtitlan (Berdan, 2004, 2014). Another interesting connection between Central Mexico and the Gulf Coast involves a great famine of the

Valley of Mexico (AD 1450-54), when Aztec families sent large numbers of their children to the coast in exchange for maize (Berdan 2004; 2014). Some of these individuals may have stayed on the coast for the duration of their lives. Although migration origin accounts suggest migrants from Northern and West Mexico, migrations from adjacent cities in the Valley of Mexico may have also contributed to population growth for the two cities. It is also possible that the sample from Tlatelolco-Tenochtitlan contains several individuals from other remnant Toltec populations in the area, who were resident for economic or political reasons. As such, the similarities between the Gulf

Coast and Central Mexico sites reflect the migrations of Toltec groups to the Gulf Coast

(López Austin and López Lujan, 2001). The sample from Jaina Island is most similar to

Gulf Coast and Central Mexico groups, and different than the other Maya samples. These results indicate a shared migration history between the Maya groups on the Gulf Coast of

76 the Yucatan Peninsula, and groups from Central Mexico and the Gulf Coast around

Veracruz. More data from the Maya region are necessary to evaluate these histories.

Shared migration is correlated with phenetic distances in all regions.

Hypothesis 3: trade and biological distances. This hypothesis is supported by the

Mantel and partial Mantel tests. Trade is correlated with biological distances, even when similarities with geographic distance, shared cultural group, and political interaction are controlled. Results suggest that groups in frequent contact through market exchange and trade routes share close phenetic affinities. These relationships are present in West and

Central Mexico, where most of the samples are grouped together and small biological distances reflect gene flow facilitated by close trade relationships. The Gulf Coast samples, particularly Vista Hermosa and Tamtok, are similar to Central Mexico groups.

In addition to a shared migration of Toltec populations, Central Mexico maintained strong trade relationships with the Gulf Coast (Diehl, 2000; López Austin and López

Lujan, 2001; Pool, 2006). Cholula is also similar to samples from the Valley of Mexico and Gulf Coast. The large inter-regional market at Cholula was centrally located between the Gulf Coast and the Valley of Mexico, and likely served as a venue for interaction between these regions (McCafferty, 1996). The Central Mexico sample of Teopanzolco is similar to the samples from the nearby Oaxaca Valley (Yagul and Zaachila). Teopanzolco had an established regional market, and participated in political and economic activities independent of the Aztec Empire (Hodge and Smith, 1994; Smith and Berdan, 2003). It is possible these trade relationships with populations inhabiting the Oaxaca Valley to the

South had an effect on immigration between these areas. Additionally, the sample from

Paquimé is similar to many of the samples from Central and West Mexico. Paquimé is located along a major inter-regional trade route connecting the American Southwest and

Mesoamerica, and was likely a large center for trade between these regions (DiPeso,

1974; Kelley et al., 2012). Samples representing sites far from major markets and trade routes, such as those from Northeast Mexico and the Maya region, are biologically most separated from the other samples. The exception is the sample from Jaina Island, which may have been in trade with the Gulf Coast groups given the geographic location of the site. The Maya site of Cozumel was located along a major trade route, and served as an important trade center (Gasco and Berdan, 2003), but was located far from the other samples in this study. Trade relationships remain correlated with biological distances when similarities with political interaction are controlled; indicating trade had an effect on population interaction independent of political relationships. Trade is correlated with phenetic distances in Central Mexico, but not in West Mexico and the peripheral regions.

This variable is the most significant in the Mantel and partial Mantel tests. Regionally, trade is correlated with phenetic distances in Central Mexico, Northern Mexico, and the

Maya region, but not in West Mexico.

Hypothesis 4: political interaction and biological distances. Political interaction is correlated with biological distances in the Mantel test, but not when similarities with shared cultural group and trade are controlled in the partial Mantel test. These results indicate the effects of political interaction are limited to samples with a shared cultural group, particularly in Central Mexico. Some of the relationships between samples in this study represent dominant-subordinate relationships, especially in Central Mexico. The

Aztecs were relatively late in their imperial expansion, maintaining most of their tributary

78 relationships for less than 150 years (Berdan et al., 1996; Berdan and Anawalt, 1997;

Berdan, 2014). Political alliances were inconsistent, and tributary provinces were constantly in rebellion (Hassig, 1988; Berdan, 2004, 2014). Although many of the samples that represent cities or towns under the control of the Aztec Empire are similar to other Central Mexico samples, in most cases the smallest biological distances do not match the dominant-subordinate relationships. Some possible exceptions are present with

Tlatelolco-Tenochtitlan and Culhuacán, Azcapotzalco and Xochimilco, and Paquimé and

Nararachic. Tenochtitlan, the Aztec-Mexica capital city, controlled Culhuacán early in its political expansion. Additionally, these cities, as well as others throughout the Valley of

Mexico engaged in frequent intermarriage among elites (Berdan 2004; 2014). Though this would not have had a major impact on the total population of the time, this may be represented in the burial samples, as they were recovered from major city center excavations. The two sites also traded heavily (especially with Tlatelolco), and also shared a migration history (Berdan, 2004; Douglas, 2010). Azcapotzalco controlled

Xochimilco prior to the existence of Tenochtitlan and the formation of the Aztec Triple

Alliance (Townsend, 2000; Berdan, 2005). The inhabitants of Azcapotzalco and

Xochimilco arrived in the Valley of Mexico around the same time, and maintained trade relationships after Azcapotzalco was conquered by the Aztecs in the fifteenth century

(Hodge and Smith, 1994; Townsend, 2000). It is possible this prior political relationship facilitated migration, but biological similarities may also be the consequence of a shared migration history and migration that occurred due to later trade relationships. Another interesting event that may have contributed to similarities between Central Mexico and the Gulf Coast comes from the ethnohistoric record. A great famine in the Valley of

Mexico in the 15th century (1450-1454) led to several families within the Aztec Empire to send their children to the Gulf Coast in exchange for maize, which was abundant

(Berdan, 2004, 2014). Some of these individuals may have stayed on the Gulf Coast and continued to reproduce. Isolated incidents such as this are difficult to test directly with archaeological burial populations, but should be considered when looking at biological similarity. When viewed regionally, political interaction is correlated with phenetic distances in Central Mexico, Northern Mexico, and the Maya region. Political interaction is not correlated in West Mexico.

Hypothesis 5: shared cultural group and biological distances. This hypothesis is supported by the Mantel tests and partial Mantel tests. Archaeologists distinguish cultural identities using ceramics, architecture, lithics, basketry, textiles, food, body ornamentation, and mortuary ritual (Jones, 1996, 1997; Emberling, 1997). The results indicate a shared cultural group assigned through these types of data correlates with phenetic distance. Some of the similarities among the biological distances, particularly outside of Central and West Mexico, are between samples of the same cultural affiliation.

Surprisingly, shared cultural group remains correlated with phenetic distances even when similarities with shared migration history are controlled. Groups from the same cultural affiliation based on archaeological and linguistic data have a similar or the same migration history. This is evident in the relatively high correlation between these variables (ZN = 0.481, p = 0.001). Shared cultural group differs from shared migration since it includes various ethnic (sub-cultural) groups within general language-based cultural affiliations. The importance of these layers of cultural groups, and the independence of this variable compared with shared migration are highlighted in the

80 partial Mantel tests. Future research regarding the relationship between phenetic similarity and language groups can be better evaluated with the inclusion of more data from related language groups. Shared cultural group is correlated with phenetic distances in all regions.

Conclusion

Migration during the Postclassic period in Mexico was frequent, and occurred at both regional and inter-regional scales. Much of what I know about migration history in prehistoric Mexico is based on account of origins, linguistic similarities, shared ideology, and similarities in material culture. Many of these migration patterns are debated among scholars of Mesoamerican population history, particularly with regard to those that involved the populations of Central and West Mexico. The results provide biological support for several migration origin accounts during the Classic (AD 300-900) and Early

Postclassic (AD 900-1200) periods, rather than a single migration from one particular region in Mexico. In Central Mexico, the results suggest migrants came from Northern,

West, and Central Mexico. This supports the Aztec origin account of a migration to the

Valley of Mexico from Aztlan, perhaps located in West or Northern Mexico (López

Austin and López Lujan, 2001; Berdan, 2004). Migrations from Northern and West

Mexico are also supported for the West Mexico samples. Biological similarities suggest shared migrations among the samples from both geographic regions. Shared migration history affects biological distance independent of shared cultural group membership, indicating that several different populations had shared migration histories. These

81 migrations are further supported by the correlation between cultural group and phenetic distances. It is important to note the correlations for both shared migration history and shared cultural group are low, ranging from ZN = 0.21 to ZN = 0.34 when political interaction, trade, and geographic distance are controlled in the partial mantel tests. These results indicate genetic drift has an effect on phenetic variation among samples, but does not fully explain the variation among samples.

Trade networks throughout the period likely facilitated contact among groups all over Mexico and beyond, but imperial expansion did not occur until relatively late (after

AD 1400) (Hassig, 1988; Berdan et al., 1996; López Austin and López Lujan, 2001;

Berdan, 2004). The Spanish conquest of Mexico, beginning in AD 1519, put an abrupt halt to political expansion and control of the Aztec and Tarascan Empires. Prior to contact, the Aztecs had maintained a large empire, but it was loosely controlled through tributary and strategic provinces and shifting alliances. Unlike the Aztecs, the Tarascans maintained firm control within their political realm, but were unable to expand their empire far beyond the Zacapu and Pátzcuaro basins (López Austin and López Lujan,

2001; Beekman, 2010; Pollard, 2003). Since many groups in this study had no political relationship, this variable alone is not completely reliable for comparison. When combined with trade to account for missing data, the combined trade/political interaction variable is highly correlated with phenetic distances. Interestingly, the combined variable is more correlated in the Mantel and partial Mantel tests than trade or political interaction alone. These results highlight the effects of cultural relationships on phenetic distances among populations in Postclassic period Mexico. More data from other samples

82 representing political contacts in pre-contact Mexico are needed to further evaluate these relationships.

Unlike political relationships, trade relationships were long-standing throughout the entire period. Many trade routes remained from the previous Classic period, and continued to permit population movement as political dominance shifted among groups.

Archaeological findings and ethnohistoric records in Mexico indicated that trade existed independent of political relationships. These results support these findings, and indicate that regional and inter-regional trade had an effect on migration and population structure among Middle to Late Postclassic Mexican groups. Migrations facilitated through trade are not restricted to the boundaries of Mesoamerica, for groups considered peripheral to the core of Mesoamerican interaction sphere participated in inter-regional exchange, and this participation appears to have had an impact upon population structure. In this study, trade is the most significant variable when compared to phenetic distances. Trade is a difficult variable to test, since material culture can be transmitted among populations through various means. I suggest overall trade relationships seen through market interactions had an important effect on population interaction in Mexico during the

Postclassic period.

CHAPTER 4: REGIONAL POPULATION STRUCTURE IN POSTCLASSIC

MEXICO

The archaeological record for pre-contact Mesoamerica is extensive. Much of what we know about Mesoamerican populations is derived from material culture, architectural patterns and settlement data, and, in some cases, written accounts (Pollard

1997; Pool 2006; Balkansky 2006; Smith and Schreiber 2006; Beekman 2010; Nichols and Pool 2012). Mesoamerica refers to the cultural area that encompasses most of

Mexico as well as some parts of Central America. The major geographic regional networks in Mesoamerica include Central Mexico, West Mexico, the Gulf Coast, and

Maya region (see Figure 4.1). For this study, the focus is populations in Mexico, which does not include all of Mesoamerica. Northern Mexico is often considered part of the

American Southwest, separate from Mesoamerica (Kirchhoff 1981). However, this region is included in the present study because of shared cultural characteristics and economic exchange among groups in this region and other regions in Mexico (Ericson and Baugh

1993; Weigand and Weigand 1996; Weigand 2008).

Since archaeological and ethnohistoric data provide a wealth of information about cultural interaction among the populations within these regions, it is an ideal environment to investigate the relationship between biology and culture among prehistoric human groups. In this paper, I use dental morphological observations from skeletal samples throughout Mexico to examine how cultural and political processes at the regional and site levels affect population structures. For this study, population structure refers to the

84 amount of phenotypic (morphological) variation within groups, as well as among them. I hypothesize that Central Mexico, West Mexico, and the Maya region will show evidence of more genetic exchange than will Northern Mexico, since populations throughout the first three regions experienced higher frequencies of contact through trade and political interaction than the last. Second, I hypothesize that samples that represent important economic, political, or religious centers in all regions will show higher within group variation relative to other samples.

Figure 4.1: Map of archaeological sites represented by samples and major regional networks in Mexico during the Postclassic period. 1= Paquimé; 2= Tayopa; 3= Nararachic; 4= Cuatro Ciénegas ; 5= Candelaria- Paila; 6= Guasave; 7= Chalpa-Tecualilla; 8= Huejuquilla; 9= Zacapú; 10= Autlan-Tuxcacuesco; 11= Tzintzuntzan; 12= Tlatelolco-Tenochtitlan; 13= Tenayuca; 14= Huexotla; 15= Azcapotzalco; 16= Culhuacán; 17= Xochimilco; 18= Cholula; 19= Teopanzolco; 20= Texcaltitlán ; 21= Teotenango; 22= Yagul; 23= Zaachila; 24= Tamtok; 25= Vista Hermosa; 26= Chicoasen; 27= Tulum; 28= Coba; 29= San Gervasio-Cozumel; and 30= Playa del Carmen.

Regional Interaction in Postclassic Mexico

The Postclassic period in Mexico (AD 900-1519) is characterized as a time of rapid population growth, high frequency of inter-regional trade, and endemic warfare

(Berdan 1988, 2000; Smith 1990, 2001; LópezAustin and LópezLujan 2001). During this time, groups throughout Mexico were organized into city-state cultures, with a capital city controlling nearby towns or cities (Smith 2000). Economically, trade was facilitated through a complex system of markets, including small-scale local, regional, and large inter-regional markets (Berdan 1988; Smith and Berdan 2003; Hirth 2012). Several of the inter-regional markets around Mexico were not city-state capitals, and trade existed across political borders (Smith 1990; Berdan 1994; Berdan 2000; Smith and Berdan

2003; Hirth 2012). Major religious centers and pilgrimage sites existed all over Mexico during the Postclassic period, and drew worshippers from throughout each region.

Economic and political relationships varied across geographic regions throughout Mexico during the Postclassic period. For this reason, a regional approach to investigating the effects of cultural interaction on population structure is employed here.

A list of archaeological sites represented by samples, as well as economic and political structure of each site is provided in Table 4.1. A brief overview of economic and political structure for each region considered in this study is provided below.

Table 4.1. Samples used in this chapter. Archaeological Estimated Date (AD) Cultural Sample Site (n) Pop. Size Group Location Northern Mexico Paquimé (35) $ * 10,000 1180-1400 Casas Grandes ASU Tayopa (15) 1,000 1300-1600 Yaqui AMNH Nararachic (25) 1,000 1300-1600 Raramuri NMNH Cuatro Ciénegas (18) 500 1200-1500 Coahuila-Chichimeca NMNH Candelaria-Paila (30) 500 1200-1500 Coahuila-Chichimeca INAH West Mexico Guasave (20) $ 8,000 600-1400 Aztitlan AMNH Chalpa-Tecualilla (22) 3,000 1150-1350 West Mexico INAH Huejuquilla (18) 3,000 900-1550 Aztitlan INAH Zacapú (50) 6,000 1100-1550 Tarascan AMNH Autlan-Tuxcacuesco (15) 3,000 1200-1550 West Mexico INAH Ihuatzio-Tzintzuntzan (30) †* 25,000 1200-1550 Tarascan INAH Central Mexico Tenayuca (20) 15,000 1100-1519 Tepenec-Chichimeca AMNH Azcapotzalco (47) 17,000 1400-1519 Aztec-Tepeneca INAH Tlatelolco-Tenochtitlan (50) $* 100,000 1340-1519 Aztec-Mexica INAH Huexotla (20) 15,000 1100-1519 Aztec-Alcolhua INAH Culhuacán (32) 5,000 1220-1519 Tolteca-Chichimeca INAH Xochimilco (39) 10,000 1400-1519 Xochimilca INAH Cholula (50) † $ 100,000 1325-1519 Tolteca-Cholulan INAH Teopanzolco (26) 20,000 1200-1550 Tlahuica INAH Texcaltitlán (27)* 8,000 1200-1550 Matlatzinca AMNH Teotenango (27) 3,000 1150-1450 Matlatzinca INAH Yagul (20) 6,000 1200-1519 Zapotec INAH Zaachila (20)* 10,000 1200-1519 Zapotec INAH Huasteca/Maya Regions Vista Hermosa (25) 1,000 1350-1550 Huastec INAH Tamtok (37) * 5,000 1350-1550 Huastec ENAH Chicoasen (20) 1,000 1000-1550 Maya-Mixe Zotec INAH Tulum (10) 2,000 1300-1550 Yucatec Maya INAH Playa del Carmen (25) 5,000 1100-1550 Yucatec Maya INAH San Gervasio/Cozumel (29) † $ 10,000 1200-1550 Yucatec Maya INAH Coba (9) 8,000 1000-1550 Yucatec Maya INAH

Note: † indicates a major religious center; $ indicates an inter-regional trade center; * indicates a political capital. Sample location abbreviations: Instituto Nacional de Antropologia e Historia (INAH); Escuela Nacional de Antropologia e Historia (ENAH); National Museum of Natural History (NMNH); American Museum of Natural History (AMNH); Arizona State University (ASU).

Central Mexico

Central Mexico is considered the center for widespread trade and political expansion during the Postclassic period (Hodge and Smith 1994; Smith 2001;

LópezLujan 2005; Melgar and Ciriaco 2009). During much of the Middle-Late

Postclassic period (AD 1200-1519), the Aztec Triple Alliance, led by the Mexica in the

Valley of Mexico, grew in power and achieved dominance over much of Mexico (Evans

2004; LópezAustin and LópezLujan 2005). Although many city-state political capitals existed throughout Central Mexico, the Aztec Triple Alliance maintained centers for imperial control in Tenochtitlan, Texcoco, and Tlacopan. The Aztecs also maintained the center of economic exchange, with a large inter-regional market at Tlatelolco. The market served an estimated 20,000 to 25,000 people daily (Anonymous Conquerer 1971). A large, inter-regional market was also present at the city of Cholula (McCafferty 1996;

Gasco and Berdan 2003). In addition to inter-regional markets, regional markets with specialized goods and labor were also present in the Valley of Mexico (Berdan 1988).

These include the sites of Azcapotzalco, Xochimilco, Teopanzolco, and Zaachila.

West Mexico

The Tarascans were the major political power in West Mexico during the

Postclassic period. Like the Aztecs, the Tarascans maintained a large empire, extracting tribute of minerals and luxury items from cities within their range of control (Pollard and

Vogel 1994; Beekman 2010). Unlike the Aztecs, the Tarascan elite maintained firm political and economic control within their domain, controlled by a major political capital at Tzintzuntzan. Additionally, the Tarascan elite controlled specific raw materials such as copper, and land, and retained control until the arrival of the Spanish in AD 1525 (Pollard

2003). Outside of the imperial boundaries of the Tarascan Empire, many city-states in

West Mexico were highly active in trade, particularly in metals and marine goods

(Beekman 2010). The Aztitlan trade route was located along the Pacific coast of West

Mexico, and was home to several small, densely populated cities and towns that were often fortified with defensive structures and high walls. The Tarascan capital of

Tzintzuntzan maintained a regional market, and trade throughout the Tarascan Empire was likely controlled through this imperial center (Gorenstein and Pollard 1983; Pollard

1993). Along the Pacific coast of West Mexico, particularly in Northwest Mexico, inter- regional trade occurred through sites such as Guasave (Beekman 2010). This area was frequently in contact with groups in Northwest Mexico, and as far as the American

Southwest (Wilcox et al. 2008; Kelley et al. 2012).

Huasteca/Maya region

The Huastec populations inhabited the northern Gulf Coast in settlements that were scattered and relatively low density, with larger concentrations of sites near the major rivers of the region (LópezAustin and LópezLujan 2005). The Aztecs thought the

Huastecs were savage barbarians (Sahagun 1982), though their strong resistance to Aztec political expansion during the Late Postclassic period highlights their political/military organization (Hassig 1988). Groups in this area participated in widespread trade networks reaching from the Maya region as far as the Mississippi Valley in North America (Lopéz

Austin and Lopéz Luján 2008; Dávila 2009). Other populations along the Gulf Coast of

Mexico, such as those in Veracruz, participated in widespread trade networks throughout

Mesoamerica, including the Maya region (Gasco and Berdan 2003; Pool 2006; Zaragoza

Ocaña 2009, Daneels 2012).

2000; Lopéz Austin and Lopéz Luján 2001). Political power and control of resources shifted over time among dominant populations and their allies. Major trade and religious centers, such those at Cozumel (Freidel and Sabloff 1984; Ringle and Bey 2012), existed along the coast of the Yucatan Peninsula. The Gulf Coast and Yucatan Peninsula were connected through trade and shared migration history (Diehl 1983; Stresser-Peán, 1989;

Fowler 2001). For this reason, and since samples are limited from the Huasteca, I combined the regions for regional analyses in this project.

Northern Mexico

The Coahuila-Chichimec groups in Northern Mexico occupied caves and open areas that had access to water and desert plains (Turpin 1997). These nomadic groups

90 traveled great distances to participate in trade, and settlements were primarily located near available resources. The Casas Grandes culture, centered at Paquimé, traded with both Mesoamerican and American Southwest populations (DiPeso 1974; Weigand 2008).

Paquimé served as an economic gateway between these two major cultural regions, exchanging goods such as cacao and macaws from southern Mexico and turquoise from the American Southwest (Woosley and Olinger 1993; Weigand 2008; Crown and Hurst

2009). It is also possible Paquimé was involved in inter-group warfare (Walker 2006;

Anderson et al. 2012) for various groups around Northern Mexico.

Previous Research on Population Structure in Pre-Contact Mexico

There has been a recent increase in research investigating population structure in pre- contact Mexico. Using craniofacial measurements, Gonzales-Jose et al. (2007) found Central

Mexican samples to be similar to West Mexican samples, and different than earlier Central or

Northern Mexican samples. These results supported a migration history from the Aztitlan region in West Mexico. Gómez-Valdéz (2008) investigated relationships among mostly West

Mexican samples that mostly dated prior to the Postclassic period. He found Tlatelolco in

Central Mexico similar to West Mexico samples, as well as to other Central Mexico samples from the Classic period. Distances were especially low between Tlatelolco and the West

Mexico samples from the Aztitlan region. Ragsdale and Edgar (2014) also found similarities between Central, West, and North Mexican samples, providing supporting evidence for migrations from the North and West into the Central Mexico. Scherer (2007) used dental metrics among Classic period (AD 250-900) Maya groups to determine the amount of intra-

91 regional, inter-group variation. Using a sample of 321 individuals in 12 samples, Scherer found low inter-group variation, with an FST estimate of 0.018 among all samples. Regional

FST estimates ranged between 0.003 and 0.019, indicating high intra-regional variation among all tested sample sets. These results are indicative of high amounts of gene flow or migration among samples in the Maya region during the Classic period. The research presented here extends these analyses to other regions of Mexico during the Postclassic period.

Other related studies involve analysis of ancient DNA. Kemp et al. (2005) used mtDNA from samples from Central Mexico to find that samples such as Tlatelolco were more similar to various samples from Central and Southern Mexico, and were different from other Uto-Aztecan speaking groups in Northern Mexico and the American Southwest.

Additionally, Moreno-Estrada et al. (2013) used DNA to calculate FST values for 511 modern

Native Mexican individuals from 20 groups throughout Mexico. Their results show high FST values for most regions throughout Mexico. Moreno-Estrada et al. (2013) also found genetic similarities between Maya and Veracruz groups, as well as between lowland Maya and

Central Mexican groups, supporting a shared migration history based on linguistic similarities (Diehl 1983; Stresser-Peán 1989). These results are similar to those found through phenetic distance studies of the same populations as described above.

Materials

Trait frequencies were derived from observations of dental morphological traits from

811 human skeletons housed at various institutions in the United States and Mexico. Samples

92 were selected to represent different geographic regional networks around Mexico, with varying economic and political structures. All samples date to the Middle to Late Postclassic period (AD 1200-1519), with some sites possibly containing a few individuals from the Late

Classic (AD 600-900), Early Postclassic (AD 900-1200), and Early Colonial (AD 1519-

1600) periods. Twelve samples are derived from Central Mexico (n=378); six samples from

West Mexico (n=155); five samples from Northern Mexico (n=123); and seven samples from the Gulf Coast (n=62) and Maya regions (n=93). A list of samples is provided in Table 4.1, and the locations of archaeological sites are provided in Figure 4.1.

In Central Mexico, the samples from Azcapotzalco, Culhuacán, Huexotla,

Xochimilco, Tenayuca, Teopanzolco, Cholula, and Tlatelolco-Tenochtitlan represent the

Valley of Mexico. We use Tlatelolco to represent a combined Tlatelolco-Tenochtitlan Aztec sample, in accordance with the history provided by the Codex Cozcatzin (García Lascuráin and Tena 1994), since the author has no knowledge of a skeletal sample representing the population of pre-contact Tenochtitlan. Tlatelolco-Tenochtitlan was the political capital and economic center for the Aztec Empire. Cholula also maintained an inter-regional market, and additionally served as a religious pilgrimage center (Ringle 1998; Gasco and Berdan 2003).

Teotenango, Texcaltitlán, Yagul, and Zaachila represent the Toluca Valley, west of the

Valley of Mexico. Zaachila and Yagul are located in the Oaxaca Valley, south of the Valley of Mexico. Zaachila was a Zapotec political capital (Marcus and Flannery 2000), and a strategic province of the Aztecs.

West Mexico is represented by the Tarascan samples from Zacapú and Ihuatzio-

Tzintzuntzan, as well as samples from outside or on the periphery of the Tarascan Empire.

Ihuatzio-Tzintzuntzan represents the political and economic capital of the Tarascan Empire.

These samples were combined since there is no clear evidence of one particular site affiliation in the excavation records. Tzintzuntzan was also a major religious center in West

Mexico (Gorenstein and Pollard 1983). The other samples from West Mexico represent important mining and economic centers in West Mexico (Hosler 2003; Beekman 2010).

These include Guasave, Chalpa-Tecualilla, Huejuquilla, and Autlan-Tuxcacuesco.

Tamtok and Vista Hermosa represent the Huastecs of the northern Gulf Coast. The

Maya region is represented by samples from Chicoasen, Coba, Tulum, Playa del Carmen and

San Gervasio/Cozumel. Chicoasen is a small, isolated site in the Maya Highlands, located in the modern Mexican state of Chiapas. Coba, Tulum, Playa del Carmen, and San

Gervasio/Cozumel are all Maya sites located on the east side of the Yucatan peninsula. These sites were all likely involved in maritime trade networks that traded key items such as salt

(MacKinnon and Kepecs 1989; Kepecs 2003). Cities and towns located throughout the area were often connected by stone causeways (Chase and Chase 2003), indicating a high amount of population contact, probably for economic exchange. Fortifications and watch towers at sites such as Tulum also suggest high levels of inter-site warfare (Webster 1976; Sharer and

Traxler 2006). Cozumel was a major religious and economic center for the Maya (Freidel and Sabloff 1984). The Gulf Coast and Maya regions were combined into one regional network for this analysis due to limited sample availability for the Gulf Coast region.

The Northern Mexico samples consist of Tayopa, Cuatro Ciénegas and Candelaria-

Paila Caves, Paquimé, and Nararachic. Tayopa is located along the Pacific Coast of the

Mexican state of Sonora. Several nomadic groups inhabited this area. The Cuatro Ciénegas and Candelaria-Paila Caves sites are representative samples of the nomadic Coahuila-

Chichimec groups. Paquimé was the political and economic center for the Casas Grandes

94 culture (DiPeso 1974; Woosley and Olinger 1993; Kelley 1993), and may have controlled the semi-nomadic populations near the burial site of Nararachic.

Methods

Dental morphological observations

Dental morphological observations were used to study population structure among Postclassic Mexican populations. Dental morphology is an effective method for tracing intra-population variation, inter-population relationships, and microevolution

(Scott and Turner 1997; Hanihara 2008; Willermet and Edgar 2009). Dental morphological studies analyze observations of standardized morphological characteristics found on the crown surfaces of teeth. These characteristics are relatively unaffected by sexual dimorphism and aging (Smith 1977; Scott and Turner 1997), and may be adjusted for asymmetry. These traits are observable even with moderate attrition, provide large sample sizes for archaeological populations, provide a high recording replicability, are associated with low inter-trait correlations (Hanihara 1976; Hanihara 2008), possess a high genetic component (Scott and Turner 1997; Townsend et al. 1992 2009), and evolve slowly (Turner et al. 1991). For these reasons, dental morphological observations are ideal for analyzing population structure.

Observations were made for a maximum of 62 maxillary and mandibular dental morphological traits on observable adult teeth. Traits were not recorded in cases of damaged teeth, severe dental wear, or large carious lesions. Traits were scored on both left and right antimeres to account for asymmetry, with the higher score representing the

95 maximum expression of the trait in each individual. The trait expressions were scored on a graded scale in accordance with the Arizona State University Dental Anthropology

System (Turner et al. 1991). Breakpoints were drawn primarily from Scott and Turner

(1997), and used to divide trait expressions into presence and absence for use in regional biological distance analyses. In some cases, breakpoints were adjusted based on previous analyses of pre-contact Mexican groups (Ragsdale and Edgar 2014). Traits for which breakpoints were adjusted include maxillary shoveling (upper central and lateral incisors), mandibular shoveling (lower central incisors), and protostylid on the mandibular molar (lower first and second molars). Shoveling on the maxillary and mandibular incisors is present at high frequencies (over 0.90) for all of the samples used here, so an adjusted breakpoint was necessary for analysis. For protostylid, the foramen caecum molaris (score of “1”) was not included as present, as the use of this expression is controversial. Dichotomized data was used for intra-regional variation analyses, and raw, non-dichotomized data was used for intra-group variation analyses.

Phenetic distances

Phenetic distance matrices were calculated for Central Mexico, West Mexico,

Northern Mexico, and the Huasteca/Maya region. Phenetic distances are biological distances derived from morphological (phenotypic) data, such as dental morphological observations. The pseudo-Mahalanobis’ D2 statistic was used to obtain the distances matrices. Pseudo-Mahalanobis’ D2 extends the squared Mahalanobis’ distance for use with dichotomized data by using z-scores and a tetrachoric correlation matrix in the

96 calculation (Konigsberg 1990). The tetrachoric correlation matrix is a matrix of correlation coefficients computed for two normally distributed dichotomized variables, and it serves to account for inter-trait correlations. This statistic was used, as opposed to

Smith’s Mean Measure of Divergence (MMD), because it allows for the use of correlated traits, and can be used in the calculation of FST (see below). Studies comparing pseudo-

Mahalanobis’ D2 and MMD show the two statistics are highly correlated, and both are useful in biological distance studies (Edgar 2004; Irish 2010). Tetrachoric correlation matrices and pseudo-Mahalanobis’ D2 values were calculated using SAS Statistical

Software (SAS Institute 2007). A principal component (PC) scatterplot was created from the pseudo-Mahalanobis’ D2 matrices to show the relationships between sites on two axes for each region. The PC analysis provides the percentage of variance among samples accounted for on each axis. These analyses were conducted using PAST (Hammer et al.

2001). A list of traits used in the final analysis with standardized and adjusted breakpoints are available for Central, West, and Northern Mexico, the Gulf Coast, and

Maya region in Appendices 11- 13.

FST

FST is a measure of genetic or population differentiation that represents the total variation among samples within a particular region (Relethford and Harpending 1994;

Leigh et al. 2003). Low FST values indicate low variation among samples within a region; high FST values indicate high variation among samples. For example, an FST value of 0.10 means that 10% of the total variation exists in differences among samples within a

region, while 90% of the variation is between individuals within and across samples. FST is useful in estimating the amount of gene flow and migration among populations within a region. If FST values in a particular region are low when compared to FST values derived from all samples across all regions, then there is a higher amount of gene flow and migration among the populations in that particular region. FST can be extended for use with morphological data when a distance matrix, relative population sizes, and heritability estimates are available (Relethford and Blangero 1990; Hanihara 2008, 2010;

Irish 2010).

Both scaled and unscaled FST values were calculated for Central Mexico, West

Mexico, Northern Mexico, and the Huasteca/Maya region. For scaled FST estimates, population sizes based on settlement data were used to rank each population’s size relative to all other populations regionally and inter-regionally (Relethford and Blangero

1990; Scherer 2007). Settlement data for several sites used in this analysis are available from archaeological reports and analyses (DiPeso 1974; Hodge 1994; Smith 1994;

Gorenstein 2000; Balkansky 2006; Pool 2006; Joyce 2010; Córdova Tello 2012). For sites for which population sizes have not been previously estimated, population size was scaled based on the relative geographic size of the archaeological site. Population size estimates are provided in Table 4.1. As with many archaeological samples, reliable population size estimates are nonexistent for some of the groups used in this study. For this reason an unscaled FST, which assumes all population sizes are equal, was also calculated.

Another element required to calculate FST using morphological data is a heritability estimate for the traits used (Relethford and Blangero 1990). Heritability is a

98 measure of genetic inheritance for morphological traits. A conservative approach to

2 calculating FST is to assume complete heritability (h =1), which results in the minimum

FST value. Heritability is a population specific value, and currently no heritability data exists for prehistoric Mexico, so calculating FST with multiple heritability estimates is a pragmatic approach. Studies of dental morphological trait heritability using monozygotic and dizygotic twins have found the majority of trait heritabilities to range from 0.5 to 0.9

(Mizoguchi 1977; Boraas et al. 1988; Hanihara 2008; Townsend et al. 1992 2009;

Bockmann et al. 2010). Since estimates range from 0.5 to 0.9 for nearly all of the dental morphological traits for which heritability has been estimated, I calculated FST values using (h2=0.5 and h2=0.9).

Non-metric multidimensional scaling

Non-metric multidimensional scaling (MDS) analyses are useful in evaluating intra-regional and intra-group variation. This technique allows a graphical representation of phenetic distances among individuals within a sample or set of samples (Kruskal and

Wish 1978). Non-metric MDS allows for the comparison of a single line of data, in this case individuals within a site, with all other lines of data within a region. Recently, non- metric MDS analyses using dental morphological data have been used to investigate intra-site variation among prehistoric human groups (Martinón-Torres et al. 2013;

Stojanowski et al. 2013). Here we use non-metric MDS to evaluate patterns of intra-site variation among samples regionally.

Non-metric MDS analyses were performed using raw, non-dichotomized data

99 from maxillary and mandibular dental morphological traits for each region. Traits were selected based on highest number of available observations among samples regionally.

Traits that exhibited very little (< 5%) or no variation among samples were removed prior to analysis. Individuals with missing data were removed prior to computation, or were excluded from the analysis using pairwise deletion. Since skeletal samples from archaeological populations are often missing teeth or exhibit severe dental wear, several individuals were removed from each sample for these analyses. Gower similarity coefficients were used to perform the non-metric MDS since they are useful for mixed data types (Gower 1971), in this case ordinal and binary data. A convex hull was determined for each sample. The convex hull is the smallest convex polygon that includes all individuals within a sample. This provides a visual representation of the distribution of each sample within a particular region. Samples that have high within-group variation have a larger distribution and a larger convex hull, compared to groups with low within- group variation. MDS were performed using PAST (Hammer et al. 2001). Traits used for the non-metric MDS are highlighted in Appendices 14-16.

Results

Phenetic distances and FST

Pseudo-Mahalanobis’ D2 matrices for each region are provided in Table 4.2. PC scatterplots of the pseudo-Mahalanobis’ D2 distances are provided in Figure 4.2. In

Central Mexico, the distances for the Valley of Mexico are relatively small. Some large distances are present with the samples from the Oaxaca Valley samples from Yagul

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Table 4.2. Pseudo-Mahalnobis’ D2 distance matrices for Central Mexico, West Mexico, Huasteca/Maya regions, and Northern Mexico. Abbreviations are the same as Figure 4.2.

Central Mexico AZC CHO CUL HLA TGO TEN TEO TEX TLA XOC YAG

AZC 0 CHO 9.78 0 CUL 6.25 3.55 0 HLA 12.41 8.97 8.51 0 TGO 11.82 8.66 9.37 10.20 0 TEN 10.07 16.96 17.10 11.42 16.12 0 TEO 8.66 11.49 9.26 10.72 14.25 10.81 0 TEX 11.31 9.72 15.96 5.79 13.88 5.79 10.08 0 TLA 8.87 10.90 10.39 11.56 15.28 20.16 19.02 11.87 0 XOC 4.11 7.54 6.58 6.99 12.16 10.19 11.28 14.11 3.50 0 YAG 9.46 21.30 18.86 20.51 27.03 10.33 7.51 31.09 19.24 15.77 0 ZAA 12.13 13.79 17.27 8.86 12.76 17.12 15.23 28.45 13.17 16.12 4.20 0

West Mexico TZI ZAC AUT CHA HUE GUA

TZI 0 ZAC 20.93 0 AUT 8.99 23.01 0 CHA 5.39 28.17 2.56 0 HUE 18.05 19.60 23.60 5.06 0 GUA 15.96 16.39 25.89 12.60 4.41 0

Huasteca/Maya Region CHN COB PLA CZL TUL TAM VIS

CHN 0 COB 12.05 0 PLA 18.12 9.97 0 CZL 13.28 5.12 12.86 0 TUL 8.68 12.11 4.23 3.05 0 TAM 3.10 13.75 15.72 19.41 5.71 0 VIS 4.84 5.55 15.86 17.67 15.21 2.84 0

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Northern Mexico TAY PAQ NAR CAN CUA

TAY 0 PAQ 14.43 0 NAR 16.33 2.56 0 CAN 18.98 10.23 13.22 0 CUA 34.20 36.21 16.66 26.27 0

(YAG) and Zaachila (ZAA) and several other samples, distinguishing this region from the Valley of Mexico and Toluca Valley. There are large distances between Tlatelolco-

Tenochtitlan (TLA), and Texcaltitlán (TEX) and Tenayuca (TEN). There are small distances between the Oaxaca Valley samples, Culhuacán and Cholula (CHO), and between Tlatelolco-Tenochtitlan and Xochimilco (XOC).

In general, most of the distances among Central Mexican samples are small. In the PC scatterplot, most of the samples from the Valley of Mexico are grouped closely together on Components 1 (48.33% variance) and 2 (21.32% variance). The exceptions are with Tlatelolco-Tenochtitlan on Component 2, and Tenayuca on both components.

The samples from the Toluca Valley, Teotenango (TEO) and Texcaltitlán are separated from the Valley of Mexico samples on Component 2, and the samples from the Oaxaca

Valley are separated from all other samples on Component 1. Yagul is also separated from the Valley of Mexico samples on Component 2.

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Figure 4.2: Principle component analyses based on regional pseudo-Mahalanobis’ D2 matrices. PAQ= Paquimé; NAR= Nararachic; CUA= Cuatro Ciénegas ; CAN= Candelaria-Paila; GUA= Guasave; CHA= Chalpa-Tecualilla; HUE= Huejuquilla; ZAC= Zacapú; AUT= Autlan-Tuxcacuesco; TZI= Tzintzuntzan; TLA= Tlatelolco-Tenochtitlan; TEN= Tenayuca; HLA= Huexotla; AZC= Azcapotzalco; CUL= Culhuacán; XOC= Xochimilco; CHO= Cholula; TEX= Texcaltitlán; TGO= Teotenango; TEO= Teopanzolco; YAG= Yagul; ZAA= Zaachila; TAM= Tamtok; CZL= San Gervasio-Cozumel; PLA= Playa del Carmen; TUL= Tulum; and CHN= Chicoasen. Stars indicate major political centers. Grey shading indicates a major economic center.

In West Mexico, most of the phenetic distances among samples are high.

Relatively high distances are present between Zacapú (ZAC) and all other samples,

Huejuquilla (HUE) and the other samples except Chalpa-Tecualilla CHA) and Guasave

(GUA), and between Guasave and the other samples except Huejuquilla. Relatively low distances are present between Tzintzuntzan (TZI) and Chalpa-Tecualilla, Chalpa-

Tecualilla and Huejuquilla, Chalpa-Tecualilla and Autlan-Tuxcacuesco (AUT), and

103 between Huejuquilla and Guasave. The PC scatterplot shows most of the samples to be different from one another, with Guasave plotted closely with Huejuquilla on

Components 1 (59.07% variance) and 2 (35.23% variance); Chalpa-Tecualilla, Autlan-

Tuxcacuesco, and Tzintzuntzan are grouped together on Component 1 but are separated by Component 2; and Zacapú is different than all other samples on Components 1 and 2.

Most of the distances among the Huasteca and Maya groups are relatively small.

Particularly small distances are present between Vista Hermosa (VIS) and Tamtok

(TAM), Chicoasen (CHN) and Vista Hermosa, Chicoasen and Tamtok, Tulum (TUL) and

Cozumel/San Gervasio (CZL), and between Tulum and Playa del Carmen (PLA). Some relatively large distances are present between Chicoasen and Playa del Carmen, Playa del

Carmen and the Huastec samples from Tamtok and Vista Hermosa, Cozumel/San

Gervasio and the Huastec samples from Tamtok and Vista Hermosa, and between Tulum and Vista Hermosa. The PC scatterplot shows two separate groups on Component 1

(62.22% variance). Vista Hermosa, Tamtok, and Chicoasen are grouped together;

Cozumel/San Gervasio, Playa del Carmen, Tulum, and Coba are also grouped together.

The similarity between the lowland Maya and Huastec samples is only on Component 2

(19.03% variance). Chicoasen is plotted between Tamtok and Vista Hermosa on

Component 2. Coba (COB) is separated from most of the other Maya samples on

Component 2, and is most similar to Vista Hermosa and Cozumel/San Gervasio.

Most of the phenetic distances are large in Northern Mexico. The only small distance is between Paquimé (PAQ) and Nararachic (NAR). Particularly large distances are present between Cuatro Ciénegas (CUA) and Tayopa (TAY), Cuatro Ciénegas and

Paquimé, and between Cuatro Ciénegas and Candelaria-Paila Caves (CAN). Results of

104 the PC scatterplot show Paquimé, Nararachic, and Candelaria-Paila Caves are grouped together on Components 1 (59.07% variance) and 2 (35.23% variance). Tayopa and

Cuatro Ciénegas is most similar to and Tayopa on Component 2. Cuatro Ciénegas is the furthest from all the other Northern Mexico samples. The sample from Candelaria-Paila

Caves is located in the center of all samples on both components.

Table 4.3. FST for geographic regional networks. Region Number Heritability Unscaled Scaled S.E. 2 of Sites (h ) FST FST Central Mexico 12 0.9 0.04* 0.01* 0.014 0.5 0.09* 0.02* West Mexico 6 0.9 0.15 0.07 0.093 0.5 0.29 0.14 Huasteca/ 7 0.9 0.06* 0.04* 0.041 Maya Region 0.5 0.12* 0.08* North Mexico 4 0.9 0.08 0.06 0.015 0.5 0.15 0.13 All Mexico 29 0.9 0.07 0.05 0.016 Samples 0.5 0.13 0.09

*Regional FST lower or equal to total FST.

The results of the FST tests are consistent with the patterns found in the pseudo-

2 Mahalanobis’ D distance matrices. Scaled and unscaled FST values for each region are

2 2 provided in Table 4.3. The overall FST values for all samples at h = 0.9 and h = 0.5

(unscaled= 0.07, 0.13; scaled= 0.05, 0.09) are low. When viewed regionally, the unscaled

FST values are low for Central Mexico (0.04, 0.09) and the Huasteca/Maya regions (0.06,

0.12). FST values are higher for West Mexico (0.15, 0.29); Northern Mexico values are intermediate (0.08, 0.15) regions. When FST values are scaled by estimated relative population size, FST values remain low for Central Mexico (0.01, 0.02) and the

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Huasteca/Maya regions (0.04, 0.08); FST values remain relatively high for the West (0.07,

0.14) and Northern Mexico (0.06, 0.13) regions.

Non-metric MDS

The results of the non-metric MDS analyses are provided in Figures 4.3a-4.3d.

All of the samples from Central Mexico are similar, with individuals from all samples plotted close to each other. The distribution of individuals from Tlatelolco-Tenochtitlan,

Cholula, and Zaachila are large on Components 1 and 2 compared to the other groups from Central Mexico, indicating a high level of within-site variation for these samples.

All of the other samples are distributed in small ranges, indicating low within-site variation.

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Figure 4.3: Non-metric multidimensional scaling for Central Mexico: square= Teotenango; filled square= Texcaltitlan; triangle= Culhuacan; filled triangle= Huexotla; inverted triangle= Xochimilco; filled inverted triangle=; Azcapotzalco diamond= Teopanzolco; filled diamond= Tenayuca; circle= Cholula; star (*)= Tlatelolco-Tenochtitlan; cross (x)= Yagul; and cross (+)= Zaachila.

In West Mexico, the patterns are much different than those from Central Mexico.

Guasave and Huejuquilla are noticeably different than the other samples from West

Mexico. The sample from Zacapú is widely distributed, and many of the individuals are similar to the other samples. The other samples are distributed in small ranges, with overlaps between the samples of Autlan-Tuxcacuesco, Chalpa-Tecualilla, and Ihuatzio-

Tzintzuntzan; and between Guasave and Huejuquilla.

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Figure 4.4: Non-metric multidimensional scaling for West Mexico: triangle= Tzintzuntzan; filled triangle= Zacapu; diamond= Guasave; filled diamond= Huejuquilla; square= Chalpa-Tecualilla; filled square= Autlan-Tuxcacuesco.

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Figure 4.5: Non-metric multidimensional scaling for Huasteca/Maya region: diamond= Tamtok; filled diamond= Vista Hermosa; square= Chicoasen; triangle= Coba; filled triangle= Tulum; inverted triangle= Playa del Carmen; and filled inverted triangle= San Gervasio-Cozumel.

In the Huasteca/Maya region all of the samples are similar to each other. All of the Maya samples are grouped together. The Huastec samples from Tamtok and Vista

Hermosa also share some similarity with the Maya groups. Tamtok is largely distributed on Components 1 and 2, indicating a high level of within-group variation for this sample.

Vista Hermosa seems widely distributed, but is actually separated into two groups on

Component 1. Both groups are within the range of similarity of Tamtok, and are also plotted on the periphery of the individuals from the Maya samples.

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Figure 4.6: Non-metric multidimensional scaling for Northern Mexico: diamond= Nararachic; filled diamond= Paquime; triangle= Cuatro Cienegas; filled triangle= Candelaria-Paila; and circle= Tayopa.

Finally, in Northern Mexico, patterns of population structure appear uncorrelated with economic or political complexity. The individuals from the Casas Grandes trade center of Paquimé are very similar to each other, except for a few outliers. On the other hand, the small nomadic groups represented by the Nararachic, Cuatro Ciénegas, and

Candelaria-Paila Caves are highly variable. This is particularly true for Nararachic, which is widely distributed around the range of variation of the other Northern Mexican samples. The sample from Tayopa is similar to the Paquimé and Nararachic samples, but different than the Cuatro Ciénegas, and Candelaria-Paila Caves samples. This result is expected, given the geographic location of the site.

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Discussion

These results show low between-site, and high within-site variation in Central

Mexico and the Huasteca/Maya regions, suggesting high levels of gene flow among groups facilitated through cultural interaction. During the time of the Aztec Empire, much of Central Mexico was incorporated into a complex system of trade, tribute, and warfare (Berdan 1988, 2000; Blanton et al. 1993; Berdan et al. 1996). Large, inter- regional markets were located at sites such as Tlatelolco and Cholula (Smith 1996;

McCafferty 1996; Berdan and Anawalt 1997; Gasco and Berdan 2003). Xochimilco and

Teopanzolco also maintained active trade network and regional markets in Central

Mexico, independent of the Aztec Empire (Berdan et al. 1996; Berdan 2000). These trade relationships extended to the Oaxaca Valley, particularly with Teopanzolco. With these relationships in mind, it is not surprising the samples from the Valley of Mexico are similar to one another. The low FST value for Central Mexico argues further for frequent population interaction, facilitated through economic and political relationships. The FST values for Central Mexico are low when compared with the overall FST values, and are the lowest regional FST values among the regions tested here. These results suggest gene flow and/or migration has a strong influence on population structure in Central Mexico, particularly for sites with important political, economic, or religious centers.

The widely distributed sample from Tamtok indicates high levels of inter-regional migration and gene flow. This result is consistent with known patterns of inter-regional exchange based on archaeological findings at Tamtok (Córdova Tello et al. 2012). All of the Maya samples are similar to each other. The high level of similarity among the Maya samples could represent gene flow and/or a shared migration history. The same is true for

111 the similarities between the Huastec and Maya samples, although gene flow facilitated through trade would have been less direct due to geographic distance. There are no clear distinctions between the highland (Chicoasen) and lowland (Coba, Playa del Carmen, San

Gervasio-Cozumel, and Tulum) Maya samples, or between the coastal or mainland samples in the non-metric MDS analyses. Interestingly, some of the individuals from the

Tulum sample are slightly different that the geographically proximate samples from

Coba, Playa del Carmen, and San Gervasio-Cozumel. This result is similar to previous biological distance studies that found Tulum to be phenotypically different than samples from the Cancun region of Quintana Roo (Cucina et al., 2008; Cucina and Tiesler, 2008).

These differences may be attributed to the burial population of Tulum, being excavated from palatial structures, and may represent a group of non-local merchants (Vargas

Pacheco, 1982). More data from this site will help to further evaluate these interpretations in future research. The FST values for the Huasteca and Maya regions are slightly lower than the overall FST values. These results indicate there is a relatively high amount of gene flow among populations in this region, albeit not as high as in Central Mexico.

These results suggest at least some of the similarity among the Maya groups reflects population interaction and gene flow.

The patterns of population structure in West and Northern Mexico are different than those in Central Mexico. There are large distances between groups, as well as widely scattered and separate distributions of individuals. This result for West Mexico is surprising, since the region was also a major center for economic and political interaction. The Tarascan Empire expanded into much of West Mexico, and, unlike the

Aztecs, maintained firm control of cities and resources within their imperial control

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(Pollard and Vogel 1994a; Gorenstein 2001; Pollard et al. 2001). In West Mexico,

Huejuquilla and Guasave are particularly different from the other West Mexico samples.

These samples are located in the West Mexico mining area, far north of the Tarascan capital of Tzintzuntzan (Gorenstein 2000; Weigand 2008; Cabrero 2010). The sample from Chalpa-Tecualilla is also located in the mining area, but is more similar to the other

West Mexico samples within and around the Tarascan Empire. The FST values are the highest for West Mexico of the four regions studied, further indicating limited gene flow among populations in this region. These similarities are consistent with archaeological evidence of high levels of interaction through trade relationships among the Pacific Coast and through Tzintzuntzan (Weigand and Weigand 1996; Cabrero 2010; Pollard 2003).

More samples from around the Patzcuaro Basin and Tarascan Empire will help further evaluate these relationships in West Mexico.

The results for Northern Mexico show more similarity between groups than in

West Mexico, but less than in Central Mexico and the Huastec and Maya regions. The

FST values for Northern Mexico are smaller than in West Mexico, but slightly larger than the overall FST values. This indicates there is some gene flow among the Northern Mexico groups, but relatively low when compared with Central Mexico and the Huasteca and

Maya regions. The small distributions of most of the samples indicate slow within-site variation and low levels of gene flow among samples. This is particularly true for the

Northeast Mexican samples, where genetic drift may be the primary evolutionary force influencing phenotypic variation. In the MDS plot, Nararachic in Northwest Mexico is the most widely distributed of the samples from this region. This result is surprising, since it is not a major economic or political center, although it is located along the Aztlan

113 trade route. Migrants from both West and Northwest Mexico could account for this variation. Equally surprising is the narrow distribution of most of the individuals from

Paquimé, the center for the Casas Grandes culture, although some individuals are noticeably different than the rest of the sample. Future research incorporating more samples from the American Southwest may help to further evaluate the biological affinity of these individuals. There is also a high amount of similarity between the Paquimé and

Nararachic samples. The Casas Grandes culture dominated part of Northwest Mexico economically (DiPeso 1974; Woosley and Olinger 1993; Kelley 1993), and there is evidence of warfare among the nomadic groups throughout the region (Anderson et al.

2012). These relationships may have facilitated frequent interactions among these groups.

The Northeast Mexico samples are different than the other Northern Mexico samples, excepting some similarity with Nararachic.

Conclusion

In this paper, I have attempted to evaluate the effects of political, economic, and religious structure on the evolutionary processes of gene flow and genetic drift among

Postclassic Mexican populations, using phenotypic data. The results show that cultural structures affect population structures, particularly in Central Mexico and the Huasteca and Maya regions. This is also partially true for Northern Mexico, particularly among

Northwest Mexican groups. Population structures in these regions are influenced by gene flow and migration. This is not true for West Mexico, based on the samples used in this study. Population structures in West Mexico, and to a lesser extent Northeast Mexico, are

114 primarily influenced by genetic drift. These patterns are consistent with interpretations of regional population interaction based on archaeological findings. The political and economic complexity of Central Mexico, particularly in the Valley of Mexico and the

Maya region, likely facilitated high levels of population interaction. The similarity between the Huastec and Maya groups also support shared migration histories based on linguistic similarities (Diehl 1983; Stresser-Peán 1989). More data from the Huasteca region, as well as comparative data from other areas of the Gulf Coast will help evaluate this relationship further.

This work also highlights the importance of combining analyses of between-group and within-group variation using phenotypic data to investigate the relationship between cultural and evolutionary processes. It should be noted that the samples from Central

Mexico make up a large portion of the samples used to calculate the overall FST values.

This could have an effect on the relatively low FST values for all samples. More data from regions outside of Central Mexico, particularly from the Gulf Coast and West Mexico, will allow further evaluation of these results in future work.

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CHAPTER 5: CONCLUSION

The ethnohistoric, archaeological, and biological data analyzed here suggest high levels of population interaction among Postclassic Mexican groups. These results contribute to the understanding of how cultural relationships affect biological interactions in Mesoamerica and the American Southwest. The broad interpretations of this study are as follows:

1. Dental morphological observations can be used to evaluate the processes of

genetic drift, gene flow, and migration among prehistoric North American

populations, even among groups that share recent migration histories.

2. Comparisons of models derived from geographic and cultural relationships with

biological distances can be used to investigate the interaction between cultural

and biological processes.

3. Sites and regions with high levels of trade and/or political interaction show

population structures shaped most strongly by gene flow and migration;

sites/regions with low levels of trade and/or political interaction show population

structures influenced most strongly by genetic drift.

4. The patterns of population interaction and population structure based on

phenotypic data strongly coincide with the archaeological and ethnohistoric

records.

This dissertation employed multiple statistical methods to relate cultural and evolutionary processes among human groups during the Postclassic period in Mexico.

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Examining population structure at the inter-regional, regional, and city-state level, and comparing patterns of human variation with cultural complexity accomplished this. Inter- regional population variation was examined by calculating phenetic distances (pseudo-

Mahalanobis’ D2), derived from dental morphological trait frequencies among populations throughout Mexico, as well as the American Southwest. Distances among all populations in this study were compared with model matrices that represent geographic and cultural relationships derived from the archaeological and ethnohistoric records, using Mantel and partial Mantel correlations. Patterns of regional population structure

2 were evaluated using D while also incorporating genetic similarity measures (FST) as well as alternate statistical methods using raw, non-dichotomized data (Gower non-metric multidimensional scaling) to investigate variation at the population or city-state level.

The results of these analyses are interpreted in an evolutionary context. The overarching conclusion is that cultural relationships affect phenetic distances among Postclassic

Mexican populations independent of geographic proximity. A summary of conclusions for Chapters 2-4 are provided below.

Chapter 2 Conclusions: Cultural effects on phenetic distances among Postclassic

Mexican and American Southwest populations.

The results of this chapter confirm that population interaction among Postclassic period Mexican populations can effectively be detected using phenetic distances based on dental morphological traits. Inter-regional interactions among Postclassic Mexican groups were assessed using samples from the American Southwest, Northern Mexico,

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West Mexico, and Central Mexico. Further, this chapter evaluated the use of model-based analyses to compare biological, cultural, and geographic similarities. Similarities through trade and shared migration history are correlated with phenetic distances among the groups used in this study; similarities through political interaction and geographic proximity are not correlated with phenetic distances. Results of the partial Mantel tests show shared migration history and trade remain correlated with phenetic distances when similarities with geographic distance are controlled.

This work is the first to compare biological, archaeological, and ethnohistoric data among populations in Postclassic Mexico. The limitations of this chapter include a relatively small number of samples representing Postclassic Mexico, no representation of the Gulf Coast and/or Maya regions, and a relatively incomplete matrix for political interaction. These limitations are addressed in Chapter 4, which improves upon this work.

However, a model-based approach to testing the relationship between biological, geographic, and cultural variables, innovative in bioarchaeology, and the reliability of using dental morphological traits s a proxy for genetic data is established.

Chapter 3 Conclusions: Cultural interaction and biological distance among Postclassic

Mexican populations.

This chapter expanded on the work presented in chapter two by incorporating more samples from around Mexico during the Postclassic period, including the from the

Huasteca and Maya regions. This study also improved the models for shared migration history, trade, and political interaction, and includes a new model representing shared

118 culture-language group. It compares geographic, cultural, and biological similarities inter-regionally. This approach was aimed at investigating population movement associated with long-distance trade and political expansion, the focus of many archaeological studies of Postclassic period Mexico (Berdan et al. 1996; Smith and

Berdan 2005). Like the previous chapter, the results of this study show that samples representing populations with similar migration histories and high frequencies of trade are more biologically similar. Unlike the findings of the previous chapter, samples representing populations with high frequencies of political interaction are also more biologically similar. The results of the partial Mantel tests show shared migration history remains correlated with phenetic distances when similarities with all other variables are controlled. Trade remains highly correlated with phenetic distances in the partial Mantel tests. The findings presented in this chapter show population structures are influenced by inter-regional cultural interaction, though political and economic structures varied across

Mexico during the Postclassic period. This chapter further emphasizes the importance of the effects of trade and a recent shared migration history on phenetic distances among the groups in this study.

Chapter 3 is a comprehensive analysis of inter-regional population interaction among Postclassic Mexican populations. The results further highlight the importance of cultural relationships, such as those of trade, on migration and genetic exchange among populations throughout Mexico. The results also support migration histories recorded in ethnohistoric and archaeological sources, and demonstrate the importance of these data for interpreting levels of gene flow and genetic drift among populations inter-regionally.

Mantel tests were also calculated for populations regionally. Separate phenetic distance

119 matrices were calculated for regional analyses to allow for this comparison; these regional phenetic distance matrices are incorporated in Chapter 4. With this limitation in mind, it is difficult to differentiate how much of the biological similarity among samples is a result of a shared migration history, continuous interaction through trade and political contact, or both. To address this issue, a more in depth analysis of intra-regional and intra-site variation was performed in Chapter 4.

Chapter 4 Conclusions: Regional population structure in Postclassic Mexico.

This study investigates population structure at intra-regional and site levels. It also expands on the previous chapters by incorporating more samples from the Maya region.

Most of the Maya samples predate the other Postclassic Mexican samples in this study.

For this reason the Maya groups were only included in analyses at the intra-regional level. Intra-regional analyses provide information about population interaction within a particular geographic region compared with other regions, and Postclassic Mexico as a whole. These analyses also provide some insight into how much of the total variation is affected by each particular region. The results of the regional phenetic distance, FST, and non-metric multidimensional scaling (MDS) analyses confirm the relationship between biological and cultural similarities. Regions with high levels of interaction through trade and/or political processes have high levels of inter-group migration and genetic exchange; regions with low levels of interaction through trade and/or political processes have low levels of inter-group migration and genetic exchange. The principal component scatterplots and FST values for Central Mexico and the Huasteca/Maya regions differ from

120 those from the Northern and West Mexico regions. The results support less between- group variation as a result of more migration and genetic exchange among populations in

Central Mexico and the Huasteca/Maya regions compared to the Northern and West

Mexico regions. These differences are related to the differences in cultural relationships outlined in Chapters 2 and 3.

The results of the non-metric MDS show that samples representing city-states with inter-regional trade centers, political capitals, and important religious/pilgrimage centers have higher within-group variation compared with other samples within the same geographic region. Similar to the results of the regional phenetic distances and FST analyses, the non-metric MDS results confirm higher similarity among individuals and groups from Central Mexico and Huasteca/Maya regions compared to Northern and West

Mexico. The results of the intra-regional and intra-site analyses performed in Chapter 4 are complementary to the results of the previous chapters, and suggest that both genetic drift and gene flow/migration influenced population structure in Postclassic Mexico.

Hostile interactions, the non-hegemonic Tarascan Empire, and the presence of several semi-nomadic groups limited population interaction in West and Northern Mexico

(Pollard and Vogel 1994; Turpin 1997; Gorenstein 2000; Walker 2006). Although the effects of both genetic drift and gene flow are detected in West Mexico, genetic drift has a more potent affect than gene flow/migration overall in North and West Mexico. In

Central Mexico and the Huasteca/Maya regions populations had high levels of interaction through trade independent of political relationships, shared ideology, tributary relationships, political alliances, and other processes associated with the hegemonic

Aztec Empire (Stresser-Peán 1989; Berdan et al. 1996; Smith and Berdan 2000, 2003;

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Smith 2001; Sharer and Traxler 2006). In these regions, gene flow/migration is the primary influence on population structure. Trade and political relationships affect biological relationships throughout Postclassic Mexico, but patterns vary among regional cultural groups. It is interesting to note that more peaceful interactions, such as trade and political alliances, facilitated more migration and genetic exchange; hostile interactions limited migration and genetic exchange. These relationships highlight the biological consequences of cultural interactions.

Limitations of the current research

This research is limited by the lack of data from Veracruz on the Gulf Coast of

Mexico and the Oaxaca Valley in Central Mexico. These regions are limited because of availability of and access to skeletal collections. Additionally, the regions of West

Mexico and the Huasteca are represented by only a few samples. Though this does not greatly affect the conclusions of this study, future incorporation of more data from these regions can improve upon this work. It is likely the patterns of population interaction/structure in West Mexico, Oaxaca Valley, and the Huasteca will remain consistent with the patterns presented here upon the inclusion of more data. The patterns of population structure/interaction among the groups in the region of Veracruz would likely be similar to those of the Huasteca and Maya regions. Future inclusion of data from

Veracruz will greatly contribute to a more complete picture of Mesoamerican population history.

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Other limitations of this research are related to limitations associated with bioarchaeological studies in general. Many of the individuals used in this study were represented by skulls, isolated crania or mandibles, or comingled loose teeth. Limited availability of materials could be from overall poor preservation of the site, or due to burial context. These preservation issues limited the ability to obtain reliable sex and age estimates for most individuals. In addition to poor preservation, provenience for many skeletal samples in Mexico is not well understood. Excavation records, such as those used to determine provenience among samples used in this study, offer a general time period assessed using architectural features or archaeological artifacts associated with the burials. These time periods may range from 100 to 600 years for samples representing the

Postclassic period. Cultural relationships such as political interactions among populations may change several times within such a time period, so the models employed in this study are based on averages over long periods of time. Particularly problematic samples include the Maya samples from Coba and Jaina Island. It is highly probable that these samples correspond to the Terminal Classic/Early Postclassic periods (AD 800-1200), which predates most of the samples from Central, West, and Northern Mexico. These limitations decrease the accuracy of recording cultural relationships, but do not greatly affect the overall results presented here. These samples remain useful in evaluating migration histories, and may still be useful when evaluating intra-site and intra-regional interactions, such as those performed in Chapter 4.

Finally, population studies using prehistoric skeletal materials are limited by sample size. Many of the samples used in this study are but a small representation of the populations from which they derive. The Aztec capital of Tenochtitlan was home to over

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200,000 people (Smith 2005), but is represented as a combined Tlatelolco-Tenochtitlan samples of 70 individuals. Additionally, most of the skeletal samples included in this study were excavated from within city centers; the hinterlands of these cities are not represented. Thus, the samples primarily represent individuals that probably lived and/or died within the city. This is not a serious a limitation for many of the Northern and West

Mexico samples since some groups were semi-nomadic and did not live in major city centers, but applies to nearly all of the samples from Central Mexico. Since many samples from the Valley of Mexico represent individuals buried within or around city- centers, it is possible some individuals in the skeletal collection may be elites. If this is the case, it may account for some of the similarities related to political interaction. For example, elite families from around the Valley of Mexico happily and frequently inter- married to solidify political relationships (Berdan et al. 1996; Berdan, 2014). These limitations highlight a major problem in bioarchaeology in general (Larson 1997; Martin et al., 2013).

Recent archaeological interpretations of Mesoamerican city-states discussed by

Smith (2014) suggest frequent intra-city migrations of peasants into city centers through the process of village nucleation. These migrations may occur for protection against invaders/raiding groups, or for better economic opportunities (Smith, 2014). Because of this, it is not unreasonable to assume that many of the sample populations used in this study could be peasants or a combination of peasants and elites. Whichever the case, subsets of populations are useful for assessing general population structures, and the results presented here are a representation of general patterns of population interactions among the Postclassic Mexican groups used in this study.

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Additional statistical methods

Many biological distance studies using dental morphological data use the Mean

Measure of Divergence (MMD) statistic (Irish 1993, 2010; Sutter 1997, 2006, 2009;

Sutter and Mertz 2004; Scherer 2007; Sutter and Verano 2007; Aubry 2009). The pseudo-

Mahalanobis’ D2 statistic used here is preferred since it allows for the use of correlated traits (Konigsberg 1990) and is related to FST, which is used for analyses in population genetics (Relethford and Blangero 1990; Scherer 2007). Previous studies suggest a high concordance between both statistical approaches (Edgar 2004; Irish 2010). I used a general Procrustes analysis (GPA) to further evaluate this using the dental trait data used in Chapter 3. GPA scales, translates, and rotates coordinates derived from different sets of data (Kenyhercz et al. 2013). This is particularly useful for comparing datasets of differing sizes, such as biological distances from the pseudo-Mahalanobis’ D2 and MMD matrices (Edgar 2002). GPA removes size by scaling all data to the same centroid size.

Once size is removed, a mean of all variables and a consensus (agreement) of shape can be calculated (Kenyhercz et al. 2013). GPA produces a scatterplot including principle coordinates of the scaled datasets. Since I am interested in the overall consensus between the two matrices, I then calculated the correlation between the sets of coordinates for the pseudo-Mahalanobis’ D2 and MMD distances.

The results of the GPA for the pseudo-Mahalanobis’ D2 and MMD distances are provided in supplementary Figure 1. GPA for the pseudo-Mahalanobis’ D2 distance and

125 geographic/cultural matrices are also provided in Appendices 17-21. The GPA for the pseudo-Mahalanobis’ D2 and MMD matrices shows a high consensus (correlation= 0.71, p = 0.001) between the datasets. This result is consistent with previous comparisons of these methods (Edgar 2004; Irish 2010). It is important to note that the MMD and pseudo-Mahalanobis’ D2 distances were calculated using the same traits, including those that were found correlated in the tetrachoric correlation matrix. The assumptions of the

MMD statistic are violated by the inclusion of correlated traits. Correlated traits, when used in the MMD, can lead to differential weighting of the distances and provide errors throughout the distance matrix, such as negative values that have no biological meaning

(Sjøvold 1977; Harris and Sjøvold 2004). However, correlations among traits are expected in calculations of the pseudo-Mahalanobis’ D2 (refer to Table 1.1). This may account for some of the differences between the two matrices.

Biological distances and the theoretical perspectives

Recall the central focus of this study was to determine how processes of economic exchange and political expansion affect migration and genetic exchange among

Postclassic period Mexican populations. These relationships were examined through biological distance measures within the context of models derived from cultural ecology and political economy. The political and economic relationships that connected people throughout Mexico during the Postclassic period, similar to the “push/pull” factors described by Anthony (1990), had an influence on migration and population structure among these groups. This is especially true in West Mexico, Central Mexico, and the

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Maya region, where these processes were particularly intense. The effects of cultural relationships of population interaction, and population structure, are evident in Chapters 3 and 4. The effects of climatic “push/pull” variables are also evident throughout this study.

In Chapter 2, migrations from the American Southwest into Northern and West Mexico that may have been influenced by severe droughts (Benson et al. 2007) are supported by the patterns of biological distances among the groups in these areas. Similar climatic events in Central Mexico (Berdan, 2005, 2014) are also supported by the patterns of biological distances in Chapter 3, though these migration events are also related to economic and political relationships. In general, the relationship between climatic relationships, political economic processes, and biological distances are supported throughout this study among Postclassic Mexican groups.

In the context of the Mesoamerican world system theory, most results of this study are consistent with relationships expected for groups within exchange circuits, affluent production zones, resource extraction zones, and unspecialized peripheries

(Blanton and Feinman, 1984). In Chapters 2 and 3, high levels of population interaction demonstrated by low biological distances are present among groups throughout the

Central Mexico and Maya regions. Affluent production/resource extraction zones, such as those found in West Mexico, yield higher biological distances among the groups within these regions. This is likely a result of less frequent population interaction between groups, and consequently less genetic exchange. Finally, in Chapter 4, samples representing sites with inter-regional trade centers have high levels of within-group variation when compared to samples representing regional or local markets. These results indicate higher levels of population interaction and immigration for sites with inter-

127 regional trade centers, assumed through archaeological interpretations. Additionally, these relationships are not true for the older, more outdated port of trade model (Polanyi

1957).

An interesting contradiction to the Mesoamerican world system theory found throughout this study are the effects of populations located in the unspecified peripheral regions of Northern Mexico and the Huasteca region of the Gulf Coast. Low biological distances among groups within both of these regions, as well as among groups in the nearby regions of West and Central Mexico, suggest populations from throughout these regions were more heavily involved in inter-regional interaction than anticipated.

Additionally, the high levels of within-group variation among the samples of Paquimé in

Northern Mexico, and Tamtok from the Huasteca region, suggest high levels of immigration to and from these regions. Though Paquimé is considered a part of the

American Southwest and not Mesoamerica, the low biological distances between

Paquimé and samples within Mesoamerica should be considered in future discussions of the interactions between Mesoamerica and the American Southwest. The results of this study demonstrate the importance of studying population interaction within the context of the Mesoamerican world system throughout all of the regions of Mexico.

Future directions

The research presented here provides a broad understanding of population interaction among Postclassic Mexican populations. This work may be improved upon by investigating, in more depth, migration events on a smaller scale. For example, in

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Chapter 4, the similarities among the Gulf Coast and Maya groups offer support of the long proposed migration history between the Huasteca groups of the Gulf Coast and the early Highland Maya. Additionally, in Chapter 3, similarities between Central Mexican and Gulf Coast groups support ethnohistoric records of Aztec cities sending children to the Gulf Coast in trade for food during a time of great drought and famine. Events such as these are important for understanding the changes in population structure around prehistoric Mexico, and more research in the future may be complimentary to this work.

This research can be further improved upon by expanding these analyses to earlier

(Classic and Preclassic periods) and later (Colonial) periods in Mexico. Potential questions include: 1) do patterns of population interaction change throughout the different temporal periods as changes occur in population sizes, resource availability, and economic and political complexity?; and 2) how do Spanish colonization and the importation of African slaves change population structures throughout Mexico during the

Colonial period? The methods employed in this study are a useful way of investigating these questions, and the results provide a base of comparison for such analyses. A longitudinal study of population change such as this would greatly improve upon the research presented here.

Finally, this research can be improved in the future is with the incorporation of data representing population health. Do patterns of population structure relate to variability in indicators in health? The incorporation of data representing frequencies of disease and nutritional stress among populations in prehistoric and historic Mexico would be useful in evaluating the relationship between population variation and health among groups throughout Mexico. These analyses, combined with biological distance studies

129 such as this study, could provide a much better understanding of the effects of social change on prehistoric human migrations.

Summary

The research presented here is an innovative approach to studying population interaction among Postclassic Mexican groups. Other previous biological distances studies in Mesoamerica mentioned here have focused primarily on regional patterns of interaction (Cucina et al., 2008; Cucina and Tiesler, 2008; Aubry, 2009), and research regarding inter-regional interaction typically focuses on archaeological and/or ethnohistoric data (Berdan et al., 1996; Smith and Berdan, 2000, 2003). This dissertation uses a multi-regional approach to population structure by comparing biological distances with distances based on geographic location, cultural/linguistic group, political interaction, and trade relationships. The method employed here demonstrates the use of comparing these different lines of data to better understand prehistoric human population interaction and movement. It is important to note that other complex variables that were not tested in this study also facilitated the movement of people throughout Mexico during the Postclassic period. These include, but are not limited to elite interactions, marriage arrangements, and the occasional selling of children during times of drought or famine.

Since the socio-economic status and precise temporal provenience for most of the samples in this study are limited or unavailable, these relationships cannot accurately be assessed. More detailed information about these sites and populations in the future may allow for such analyses.

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The results of this dissertation show cultural interaction through political and economic processes influence migration and population interaction. Patterns of population structure based on biological (phenetic) distances are consistent with much of what is known about population movement through archaeological and ethnohistoric data. These relationships are particularly true in the core regions of Central Mexico, the

Gulf Coast, and the Maya region. Interestingly, relatively peaceful relationships such as trade and political alliances welcomed migration and facilitated population interaction throughout Mexico during the Postclassic period, while hostile relationships such as war and elite control of resources did not facilitate such interactions. This important result highlights the relationship between different socio-economic and biological processes.

Though this study focuses on Mexico during the Postclassic period, the models employed here can be applied to populations and temporal periods, since similar political economic processes exist around the world throughout prehistory/history.

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BIBLIOGRAPHY

Anonymous Conqueror. 1971. Relacion de algunas cosas de la Nueva Espana y de la

Gran Ciudad de Temestitan Mexico: escrita por un companero de Hernan Cortes.

In Coleccion de Documentos para la Historia de Mexico, Icazbalceta JC (ed.),

Antigua Libraria, Mexico City.

Anthony DW. 1990. Migration in Archaeology: The Baby in the Bathwater. American

Anthropologist 92: 895-914.

Aubry BS. 2009. Population Structure and Interregional Interaction in Prehispanic Mesamerica: a biodistance study. Ph.D. Dissertation, the Ohio State University: Columbus

Balkansky AK. 2006. Surveys and Mesoamerican Archaeology: The Emerging Macroregional Paradigm. Journal of Archaeological Research 14:53–95.

Beekman C. 2010. Recent Research in Western Mexican Archaeology. J Archaeological Research 18:41–109.

Benson L, Peterson K, Stein J. 2007. Anasazi (Pre-Columbian Native-American) Migrations during the Middle-12Th and Late-13th Centuries - Were they Drought Induced? Climate Change 83:187–213.

Berdan FF, Blanton RE, Boone EH, Hodge MG, Smith ME, Umberger EE. 1996. Aztec imperial strategies. Washington DC: Dumbarton Oaks Research Library and Collection.

Berdan FF, Anawalt PR. 1997. The essential Codex Mendoza. Berkeley: University of California Press.

Berdan FF. 1989. Trade and Markets in Precapitalist States. In Plattner S, editor.

Economic Anthropology. Stanford University Press.

Berdan FF. 2004. Aztecs of Central Mexico: An Imperial Society. 2nd ed. Wadsworth Publishing.

Berdan FF. 2014. Aztec Archaeology and Ethnohistory. Cambridge University Press.

132

Berry AC, and RJ. Berry. 1967. Epigenetic Variation in the Human Cranium. Journal of Anatomy. 101(2):361-379

Bierhorst J. 1992. Codex Chimalpopoca: The Text in Nahuatl with a Glossary and Grammatical Notes. Tucson: University of Arizona Press.

Blanton R, Feinman GM. 1984. The Mesoamerican World System. American Anthropologist 86:673–682.

Blanton R. 1994. Ancient Mesoamerica: A Comparison of Change in Three Regions. Bull Latin American Research 13:358–360.

Blanton R. 1996. Basin of Mexico Market System and Growth of Empire. In Berdan

FF, Blanton RE, Boone EH, Hodge MG, Smith ME, Umberger E, editors. Aztec

Imperial Strategies. Washington DC: Dumbarton Oaks Research Library and Collection. p 47-84.

Bockmann MR, Hughes TE, and Townsend GC. 2010. Genetic Modeling of Primary

Tooth Emergence: A Study of Australian Twins. Twin Research and Human

Genetics 13(6): 573-581.

Boraas JC, Messer LB, and Till MJ. 1988. A Genetic Contribution to Dental Caries,

Occlusion, and Morphology as Demonstrated by Twins Reared Apart. Journal of Dental Research 67:1150–1155.

Cabana GS, Clark JJ. 2011. Rethinking Anthropological Perspectives on Migration.

University Press of Florida.

Cabana GS, Clark JJ. 2011. Migration in Anthropology. In GS Cabana and JJ Clark (eds.) Rethinking Anthropological Perspectives on Migration. University Press of Florida.

Cameron CM. 2013. How People Moved among Ancient Societies: Broadening the View. American Anthropologist 115: 218-231.

Chase AF, Chase DZ. 2001. Ancient Maya Causeways and Site Organization at Caracol, Belize. Ancient Mesoamerica 12: 273-281.

Cole TM. 1996. The Use of Matrix Permutation Tests for Evaluating Competing Hypotheses of Modern Human Origins. Journal of Human Evolution 31: 477-484.

133

Coppa A, Cucina A, Mancinelli D, Vargiu R, Calcagno J. 1998. Dental anthropology of central-southern Iron Age Italy: the evidence of metric versus non-metric traits. American Journal of Physical Anthropology 107: 371-386.

Córdova Tello G, Martinez Mora E, Hernandez Espinoza PO. 2012. Tamtok: Esbozo de una antigua sociedad urbana. Instituto Nacional de Antropologia e Historia.

Corruccini RS. 1972. The biological relationships of some prehistoric and historic Pueblo populations. American Journal of Physical Anthropology 37: 373-88.

Cowgill GL. 2000. The central Mexican highlands from the rise of Teotihuacan to the

decline of Tula. The Cambridge history of the native peoples of the Americas,

Vol. 2: Mesoamerica, Part 1, Adams RE and MacLeod MJ (eds.), Cambridge

University Press.

Crow JF. 1986. Basic Concepts in Population, Quantitative, and Evolutionary

Genetics. W.H. Freeman and Company, New York

Crown PL, Hurst WJ. 2009. Evidence of cacao use in the Prehispanic American Southwest. Proc Natl Acad Sci 106:2110–2113.

Crown PL. 2013. Pre-hispanic Use of Cocoa. Chocolate in Health and Nutrition. Human Press: 3-9.

Dahlberg AA. 1951. The dentition of the American Indian. In W.S. Laughlin (ed).

The Physical Anthropology of the American Indian, pp. 138-176. The Viking Fund, New York.

Dávila P. 2009. La Huasteca: problematica y nexos culturales. In Zaragoza Ocaña D (ed.), Memoria del taller arqueologia de la Huasteca. Homenaje a Leonor Merino Carrion. Coleccion Cientifica, Serie Arqueologia, 541. Instituto Nacional de Antropologia e Historia.

Daneels A. 2012. Developmental Cycles in the Gulf Lowlands. In Nichols DL, Pool

CA (Eds.), The Oxford Handbook of Mesoamerican Archaeology. Oxford University Press, New York, NY. 1-30.

Diehl RA. 1983. Tula: the Toltec capital of ancient Mexico. London: Thames and Hudson.

134

Diehl RA. 2000. The Precolombian cultures of the Gulf Coast. In Adams RE, MacLeod

MJ, editors. The Cambridge history of the native peoples of the Americas

Volume 2: Mesoamerica Part 1. Cambridge University Press. p 156-196.

DiPeso CC. 1974. Casas Grandes, A Fallen Trade Center of the Gran Chichimeca.

American Anthropologist 78.

Douglass AE. 2006. The secret of the Southwest solved by talkative tree rings. Kessinger

Publishing.

Douglas E de J. 2010. In the Palace of Nezahualcoyotl: Painting Manuscripts, Writing the Pre-Hispanic Past in Early Colonial Period Tetzcoco, Mexico. Austin: University of Texas Press.

Edgar HJH. 2002. Biological Distance and the African American Dentition. Ph.D. Dissertation, the Ohio State University: Columbus.

Edgar HJH. 2004. Dentitions, distance, and difficulty: a comparison of two statistical

techniques for dental morphological data. Den Anthropol 17:55-62.

El-Najjar MY. 1978. Southwestern physical anthropology: do the cultural and biological

parameters correspond? American Journal of Physical Anthropology 48: 151-158.

Ericson JE and Baugh TG. 1993. The American Southwest and Mesoamerica: Systems of

Prehistoric Exchange. Interdisciplinary Contributions to Archaeology.

Emberling G. 1997. Ethnicity in complex societies: Archaeological perspectives. Journal of Archaeological Research 5:295–344.

Evans ST. 2004. Ancient Mexico and Central America: Archaeology and culture history. London: Thames and Hudson.

Fix AG. 1999. Migration and Colonization in Human Microevolution. Cambridge

University Press. Cambridge, MA.

Foster MS and Gorenstein S. 2000. Greater Mesoamerica: The Archaeology of West and Northwest Mexico. University of Utah Press.

135

Freidel DA, Sabloff JA. 1984. Cozumel: Late Classic Maya Settlement Patterns. Academic Press. New York, NY.

García Lascuráin ARV, Tena R. 1994. Códice Cozcatzin. Códices mesoamericanos: 4.

Instituto Nacional de Antropologia e Historia.

Gasco J, Berdan FF. 2003. International Trade Centers. In Smith ME, Berdan FF,

editors. The Postclassic Mesoamerican World. Salt Lake City UT: University of

Utah Press. p 109-116.

Gilpin R, Gilpin JM. 1987. The political economy of international relations. Princeton:

Princeton University Press.

Gómez-Valdés J. 2008. Antropología dental en poblaciones del Occidente de Mesoamérica. México DF: Instituto Nacional de Antropología e Historia.

Gonzalez-Jose R, Martinez-Abadias N, Gonzalez-Martin A, Bautista-Martinez J, Gomez- Valdes J, Quinto M, Hernandez M. 2007. Detection of a population replacement at the Classic-Postclassic transition in Mexico. Proc B 274:681–688.

Goodman Ah, Leatherman TL. 1998. Building a New Biocultural Synthesis: Political- Economic Perspectives on Human Biology. The University of Michigan Press, Ann Arbor, MI.

Gorenstein S. 2000. Western and northwestern Mexico. In Cambridge History of the Native Peoples of the Americas, Volume 2, Part 1, Trigger BG, Washburn WE, and Adams RE, Cambridge University Press.

Gower JC .1971. A General Coefficient of Similarity and Some of its Properties. Biometrics 27: 857-74.

Hammer Ө, Harper DA, Ryan PD. 2001. PAST: Paleontological Statistical Software for

Education and Data Analysis. Paleontological Association 4:1-9.

Hammond GP and Rey A. 1940. Narratives of the Coronado Expedition 1540-1542.

University of New Mexico Press. Albuquerque, NM.

Hammond N. 2000. The Maya lowlands: pioneer farmers to merchant princes. In The

136

Cambridge History of the Native Peoples of the Americas, Volume 2: Mesoamerica, Part 1, edited by R.E.W. Adams and M.J. MacLeod, pp. 197-249. Cambridge University Press, Cambridge.

Hanihara K. 1976. Statistical and comparative studies of the Australian aboriginal

dentition. University of Tokyo, Bull. 11:1–57.

Hanihara T. 2008. Morphological variation of major human populations based on nonmetric dental traits. American Journal of Physical Anthropology 136:169–182.

Harpending HC, T. Jenkins. 1973. Genetic Distance among Southern African

Populations. In M. Crawford, and P. Workman (eds): Methods and Theories

of Anthropological Genetics, pp 177-199. Albuquerque: University of New Mexico Press.

Harris EF. 1977. Anthropologic and genetic aspects of the dental morphology of Solomon Islanders, Melanesia. Ph.D. dissertation, Arizona State University, Tempe.

Harris EF, Sjøvold T. 2004. Calculation of Smith's mean measure of divergence for intergroup comparisons using nonmetric data. Dental Anthropology 17: 83-93.

Hartl DL, and AG. Clark. 1997. Principles of Population Genetics. 3rd edition.

Sunderland. Sinauer Associates, Inc.

Hassig R. 1988. Aztec warfare : imperial expansion and political control. 1st ed. Norman: University of Oklahoma Press.

Hillson S. 1996. Dental anthropology. Cambridge: Cambridge University Press

Hirth K. 2012. Markets, Merchants, and Systems of Exchange. In Nichols DL, Pool

CA (Eds.), The Oxford Handbook of Mesoamerican Archaeology. Oxford University Press, New York, NY. 1-30.

Hodge MG, Smith ME. 1994. Economies and Polities in the Aztec Realm. Austin: University of Texas Press.

Hrdlička A. 1920. Shovel-Shaped Teeth. American Journal of Physical

Anthropology 3:429-465.

137

Irish JD, and Guatelli-Steinberg D. 2003. Ancient teeth and modern human origins: A expanded comparison of African Plio-Pleistocene and Recent world dental samples. Journal of Human Evolution 45: 113-144.

Irish JD. 1993 Biological Affinities of Late Pleistocene through Modern African

Aboriginal Populations: The Dental Evidence. Ph.D. dissertation, Arizona State

University, Tempe

Irish J. 2010. The mean measure of divergence: its utility in model-free and model-bound analyses relative to the Mahalanobis D2 distance for nonmetric traits. American Journal of Human Biology 22:378–395.

Jobling MA, Hoolox E, Lurles M, Kivisild T, Tyler-Smith C. 2013. Human Evolutionary Genetics 2nd edition. Garland Science. New York, NY.

Jones L. 1989. The Hermeneutics of Sacred Architecture: A Reassesment of the similtude between Tula, Hidalgo and Chichén Itzá, Yucatán. Ph.D. Dissertation. University of Chicago.

Joyce AA. 2010. Mixtecs, Zapotecs, and Chatinos: Ancient Peoples of Southern Mexico. 1st ed. Wiley-Blackwell.

Kelley J, MacWilliams AC, Stewart JD, Adams KR, Cunningham JJ, Garvin RE, Maillol GM, Reimer PJ, Zborover D. 2012. The View from the Edge: The Proyecto Arqueológico Chihuahua (PAC) 1990 to 2010: An Overview. Canadian Journal of Archaeology 36:82–107.

Kelley JC. 1993. Zenith passage: the view from Chalchihuites. In Culture and contact: Charles C DiPeso’s Gran Chichimeca, Woosley AI and Ravesloot JC, American Foundation and University of New Mexico Press.

Kemp BM, Resendez A, Berrelleza R, Malhi RS, Smith DG. 2005. An analysis of ancient Aztec mtDNA from Tlatelolco: Pre-columbian relations and the spread of Uto- Aztecan. In Reed DM, editor. Biomolecular archaeology: genetic approaches to the past. Carbondal IL: Southern Illinois University Press.

Kenyhercz MW, Klales AR, Kenyhercz WE. 2013. Molar Size and Shape in the Estimation of Biological Ancestry: A Comparison of Relative Cusp Location Using Geometric Morphometrics and Interlandmark Distances. American Journal of Physical Anthropology 153: 269-280.

Kepecs S, Kohl P. 2003. Conceptualizing Macroregional Interaction. In Smith ME,

138

Berdan FF, editors. The Postclassic Mesoamerican World. Salt Lake City UT:

University of Utah Press. p 14-20.

Kirchhoff, P. 1981. Mesoamerica: Its Geographic Limits, Ethnic Composition, and

Cultural Characteristics. In Ancient Mesoamerica, John Graham (ed.), pp 1-10. Peek Publications, Palo Alto, California.

Konigsberg LW, Blangero J. 1993. Multivariate Quantitative Genetic Simulations in

Anthropology with an Example from the South Pacific. Human Biology 65: 897- 915.

Konigsberg L. 1990. Analysis of prehistoric biological variation under a model of isolation by geographic and temporal distance. Human Biology 62:49–70.

Kruskal JB, Wish M. 1978. Multidimensional scaling (Sage, Beverly Hills, CA).

Larson CS. 1997. Bioarchaeology: Interpreting Behavior from the Human Skeleton. Cambridge University Press. New York, NY.

LeBlanc SA. 1999. Prehistoric Warfare in the American Southwest. University of Utah Press. Salt Lake City, UT.

LeBlanc SA. 2000. Regional Interaction and Warfare in the Late Prehistoric Southwest. In The Archaeology of Regional Interaction: Proceedings of the 1996 Southwest Symposium, Hegmom M (ed.), University Press of Colorado.

LeBlanc SA, Turner CG, and Morgan ME. 2008. Genetic Relationships Based on Discrete Dental Traits: Basketmaker II and Mimbres. International Journal of Osteoarchaeology 18: 109-130.

Legendre P. 1998. Numerical ecology. 2nd English ed. Amsterdam; New York: Elsevier.

Lee ES. 1966. A Theory of Migration. Demography 3: 47-57.

Legendre P and Legendre L. 1998. Numerical Ecology. Elsevier.

Lekson SH, Cameron CM. 1995. The Abandonment of Chaco Canyon, the Mesa Verde Migrations, and the Reorganization of the Pueblo World. Journal of Anthropological Archaeology 14:184–202.

Lekson SH. 1999. The Chaco Meridian: centers of political power in the Ancient Southwest. Alta Mira Press.

139

López Austin A, Lopéz Luján L. 2001. Mexico’s indigenous past. Norman OK: University of Oklahoma Press.

Lopéz Austin, A. and L. Lopéz Luján 2008. Aztec human sacrifice. In The Aztec World. E.M. Brumfiel and G.M. Feinman, (editors). pp. 137-152. Abrams Press, New York.

Martin DL, Harrod RP, and Perez PR. 2013. Bioarchaeology: An Integrated Approach to Working with Human Remains. Springer, NY.

Mackey J. 1977. A multivariate, osteological approach to Towa culture history. American Journal of Physical Anthropology 46:477-482.

MacKinnon JJ, Kepecs S. 1989. Prehispanic Saltmaking in Belize: New Evidence. American Antiquity 54: 522-533.

Manly B. 1986. Multivariate statistical methods : a primer. London; New York: Chapman and Hall.

Mantel N. 1967. The Detection of Disease Clustering and a Generalized Regression Approach. Cancer Res 27:209–220.

Marcus J, Flannery KV. 1983. An Introduction to the Late Postclassic. In Flannery KV, Marcus J (eds.), The Cloud People: Divergent Evolution of the Zapotec and Mixtec Civilizations. Academic Press. New York, NY. 217-226.

Martinón-Torres M, Bermúdez de Castro JM, Martin-Francés L, Gracia-Téllez A, Martinez I, Arsuaga JL (2013) in Anthropological Perspectives on Tooth Morphology: Genetics, Evolution, Variation. Cambridge University Press, New York, NY), pp 201-221.

Mata-Míguez J, Overholtzer L, Rodriguez-Alegria E, Kemp BM, Bolnick DA. 2012. The genetic impact of Aztec imperialism: ancient mitochondrial DNA evidence from Xaltocan, Mexico. American Journal of Physical Anthropology 149:504–16.

Matos Moctezuma E. 1989. The Aztecs. Rizzoli. New York, NY.

Matsumura H, and Hudson MJ. 2005 Dental perspectives on the population history of Southeast Asia. American Journal of Physical Anthropology 127:182-209.

Mayr E. 1970. Populations, Species and Evolution. Harvard University Press. Cambridge, MA.

140

McCafferty G. 1996. Reinterpreting the Great Pyramid of Cholula, Mexico. Anc Mesoam 7:1–17.

McGuire RH. 1980. The Mesoamerican Connection in the Southwest. Kiva 46: 1-2.

McGuire RH. 2012. Mesoamerica and the Southwest/Northwest. In Nichols, Pool CA,

editors. The Oxford Handbook of Mesoamerican Archaeology. Oxford

University Press. p 513-524.

Melgar Tisoc ER. 2010. Una Relectura del Commercio de la Turquesa: Entre

Yacimientos, Talleres y Consumidores. Caminos y Mercados de Mexico.

Mexico DF: Universidad Autonoma de Mexico.

Melgar Tisoc ER, and Solis Ciriaco RB. 2009. Manufacturing Techniques of the

TurquoiseMosaics from the Great Temple of Tenochtitlan, Mexico. 2nd Latin- American Symposium on Physical and Chemical Methods in Archaeology, Art and Cultural Heritage Conservation & Archaeological and Arts Issues in Materials Science. Mexico City, Mexico.

Michelet D. 1995. La zona occidental en el Posclassico. In Manzanilla L, López Luján

(eds.), Historia antigua de Mexico, vol. 3, El horizonte Posclassico y algunos aspectos intelectuales de las culturas mesoamericanas. Instituto Nacional de Antropologia e Historia. 153-188.

Mills BJ. 1995. The organization of the protohistoric Zuni ceramic production. In

Ceramic production in the American Southwest, Mills BJ and Crown PL, University of Arizona Press.

Mizoguchi Y. 1977. Genetic variability of tooth crowns as ascertained from twin data.

Journal of the Anthropological Society of Japan 85(4): 301-309.

Moreno-Estrada A, Gignoux CR, Fernandez-LópezJC, Zakharia F, Sikora M, Contreras

AV,Acuña Alonzo V, Sandoval K, Eng C, Romero-Hidalgo S, Ortiz-Tello P, Robles V, Kenny EE, Nuño-Arana I, Barquera-Lozano R, Macin-Perez, G, Granados-Arriola J, Huntsman S, Galanter JM, Via M, Ford JG, Chapela R, Rodriguez-Cintron W, Rodriguez-Santana JR, Romieu I, Sienra-Monge JJ, Rio Navarro B, London SJ, Ruiz-Linares A, Garcia-Herrera R, Estrada K, Hidalgo- Miranda A, Jimenez-Sanchez G, Carnevale A, Soberon X, Canizales-Quinteros S,

141

Rangel-Villalobos H, Silva-Zolezzi I, Gonzales Burchard E, Bustamante CD. 2013. The genetics of Mexico recapitulates Native American substructure and affects biomedical traits. Science: 344, 6169. 1280-1285.

Mountjoy JB. 2000. Prehispanic Cultural Development Along the Southern Coast of West Mexico. In Foster MS, Gorenstein S (eds.), Greater Mesoamerica: The Archaeology of West and Northwest Mexico. University of Utah Press, Salt Lake City, UT. 81-106.

Nelson RS. 1986. Pochtecas and Prestige: Mesoamerican Artifacts in Hohokam Sites. In

Ripplesin the Chichimec Sea: New Considerations of Southwestern Mesoamerican Interactions. Mathien FJ and McGuire RH (eds.). Southern Illinois University Press. Carbondale and Edwardsville, IL.

Nichol CR. 1989. Complex Segregation Analysis of Dental Morphological Variants.

American Journal of Physical Anthropology 78: 37-59.

Nichol CR. 1990. Dental Genetics and Biological Relationships of the Pima Indians of

Arizona. Ph.D. Thesis, Arizona State University, Tempe.

Nichols Dl, Pool CA. 2012. Mesoamerican Archaeology: Recent Trends. In Nichols DL,

Pool CA (Eds.), The Oxford Handbook of Mesoamerican Archaeology. Oxford University Press, New York, NY. 1-30. di Peso C. 1974. Casas Grandes : a fallen trading center of the Gran Chichimeca. 1st ed. Dragoon [Ariz.]: Amerind Foundation.

Pollard HP, Smith ME. 2003. The Aztec/Tarascan Border. In Smith ME, Berdan

FF, editors. The Postclassic Mesoamerican World. Salt Lake City UT:

University of Utah Press. p 87-91.

Pollard HP, and Vogel TA. 1994. Late Postclassic Imperial Expansion and Economic

Exchange Within the Tarascan Empire.

Pollard HP. 2003. West Mexico beyond the Tarascan Frontier. In Smith ME, Berdan

FF, editors. The Postclassic Mesoamerican World. Salt Lake City UT:

University of Utah Press. p 55-57.

142

Pool CA. 2006. Current Research on the Gulf Coast of Mexico. Journal of Archaeological Research 14:189–241.

Ragsdale CS, Edgar HJH. 2014. Cultural Effects on Phenetic Distances Among Postclassic Mexican and Southwest United States Populations. International Journal of Osteoarchaeology (online).

Rathje WJ, Sabloff JA. 1973. Ancient Maya commercial systems: A research design for the island of Cozumel, Mexico. World Archaeology 5: 221-231.

Relethford JH and Blangero J. 1990. Detection of differential gene flow from patterns of quantitative variation. Human Biology 62(1): 5-25.

Relethford JH, and Harpending HC. 1994. Craniometric Variation, Genetic Theory, and Modern Human Origins. American Journal of Physical Anthropology 95: 249- 270.

Relethford JH. 1991. Genetic Drift and Anthropometric Variation in Ireland. Human Biology 63:155-165.

Ricaut F, Auriol V, von Cramon-Taubadel N, Keyser C, Murail P, Ludes B, Crubezy E. 2010. Comparison between morphological and genetic data to estimate biological relationship: the case of the Egyin Gol necropolis (Mongolia). American Journal of Physical Anthropology 143:355–64.

Riley CL. 1975. The Road to Hawikuh: Trade and Trade Routes to Cibola-Zuni During Late Prehistoric and Early Historic Times. The Kiva 41:2.

Ringle WM, Bey III GJ. 2012. The Late Classic to Postclassic Transition Among the

Maya of Northern Yucatán. In Nichols DL, Pool CA (Eds.), The Oxford Handbook of Mesoamerican Archaeology. Oxford University Press, New York, NY. 1-30.

Ross SH. 1967. Prehistoric trade routes between Mesoamerica and the American Southwest: a tentative assessment. The California Geographer 8: 9-19.

Sahagun B. 1950-1982. Florentine Codex: General History of the Things of New Spain. Anderson AJ, Dibble CE (eds.). 12 vols. Salt Lake City: University of Oklahoma Press.

Scherer A. 2004. Dental Analysis of Classic Period Population Variability in the

Maya Area. PhD. Texas A&M University.

143

Scherer AK. 2007. Population structure of the Classic period Maya. American Journal of Physical Anthropology 132:367–380.

Schillaci MA and Stojanowski, CM. 2002. Investigating social organization at Aztec Ruins using determinant ratio analysis. In Forward into the past: papers in honor of Teddy Lou and Francis Stickney, Wiseman RN, O’Laughlin TC, and Snow CT (eds.), Albuquerque: Archaeological Society of New Mexico.

Schlanger SH and Wilshusen RH. 1993. Local abandonments and regional conditions in the North American Southwest. Abandonment of settlements and regions: Ethnoarchaeological and archaeological approaches 1: 85-98.

Schutkowski H. 2008. Between Biology and Culture. Cambridge University Press. Cambridge, MA.

Scott GR, Turner II CG. 1997. The Anthropology of Modern Human Teeth: Dental Morphology and its Variation in Recent Human Populations. Cambridge University Press.

Sharer RJ, Traxler LP. 2006. The Ancient Maya, 6th edition. Stanford University Press. Stanford, CA.

Sjøvold T. 1977. Non-metrical divergence between skeletal populations: the theoretical foundation and biological importance of C.A.B. Smith's mean measure of divergence. Osteological Research Laboratory 4: 1-133.

Smith ME, Berdan FF. 2000. The Postclassic Mesoamerican World System. Current Anthropology 41:283.

Smith ME, Berdan FF. 2003. The Postclassic Mesoamerican World. 1st Edition. Salt Lake City UT: University of Utah Press.

Smith ME, Schreiber K. 2006. New World States and Empires: Politics, Religion, and Urbanism. Journal of Archaeological Research 14:1–52.

Smith ME. 1984. The Aztlan Migrations of the Nahuatl Chronicles: Myth or History? Ethnohistory 31:153–186.

Smith ME. 2001. The Aztec Empire and the Mesoamerican World System. In Alcock

SE, D'Altroy DN, Morrison KD, Sinopoli CM, editors. Empires: Comparative

Perspectives from Archaeology and History. Cambridge University Press.

144

Smith CA. 1977. A note on genetic distance. Annual Human Genetics 40:463-479.

Smith ME. 2003. Small Polities in Postclassic Mesoamerica. In ME Smith and FF

Berdan (editors) The Postclassic Mesoamerican World. 1st ed. University of Utah Press. de Souza P, Houghton P. 1977. The mean measure of divergence and the use of non- metric data in the estimation of biological distances. Journal of Archaeological Science 4:163–169.

Steward JH. 1990. Theory of Culture Change: The Methodology of Multilinear Evolution. University of Illinois Press.

Stojanowski CM, Johnson KM, Duncan WN .2013. in Anthropological Perspectives on Tooth Morphology: Genetics, Evolution, Variation. Cambridge University Press, New York, NY, pp 408-452.

Stojanowski CM. 2004. Population History of Native Groups in Pre- and Postcontact

Spanish Florida: Aggregation, Gene Flow, and Genetic Drift on the Southeastern

U.S. Atlantic Coast. American Journal of Physical Anthropology 123:316-332.

Stresser-Peán, G. 1989. Enquêtes sur l'Amérique moyenne. Instituto Nacional de

Antropología e Historia, 16.

Steward JH. 1990. Theory of Culture Change: The Methodology of Multilinear

Evolution.University of Illinois Press.

Sutter RC. 1997. Dental variation and biocultural affinities among prehistoric populations

from the coastal valleys of Moquegua, Peru, and Azapa, Chile. PhD dissertation, University of Missouri, Columbia.

Sutter RC. 2006. The test of competing models for the prehistoric peopling of the Azapa

Valley, northern Chile, using matrix correlations. Chungara 38: 63-82.

Sutter RC. 2009. Post-Tiwinaku ethnogenesis in the coastal Moquegua Valley, Peru. In

Knudson KJ, Stojanowski CM (eds.), Bioarchaeology and Identity in the Americas. University of Florida PRess. Gainesville, FL. 103-125.

145

Sutter RC, and Mertz L. 2004. Nonmetric cranial trait variation and prehistoric

biocultural change in the Azapa Valley, Chile. American Journal Physical Anthropology. 123:130–145.

Sutter RC, and Verano JW. 2007. Biodistance analysis of the Moche sacrificial victims

from Huaca de la Luna plaza 3C: Matrix method test of their origins. American Journal of Physical Anthropology 132:193–206.

Townsend RF. 2000. The Aztecs. London: Thames and Hudson.

Townsend GC, Hughes TE, Luciano M, Bockmann MR, and Brook A. 2009. Genetic and

environmental influences on human dental variation: A critical evaluation of studies involving twins. Archives of Oral Biology 54:45–51.

Turner II CG, Scott GR. 1977. Dentition of Easter Islanders. In Dahlberg AA, Graber TM, editors. Orofacial growth and development. Berlin: Mouton de Gruyter.

Turner II CG, Nichol CR, Scott GR. 1991. Scoring procedures for key morphological

traits of the permanent dentition: the Arizona State University Dental

Anthropology System. In Kelley MA, Larson CS, editors. Advances in Dental Anthropology. New York: Wiley-Liss.

Turner CG. 1990. The major features of Sundadonty and Sinodonty including

suggestions about east Asian microevolution, population history, and late Pleistocene relationships with Australian aboriginals. American Journal of Physical Anthropology 75:305-321.

Turner II CG. 1993. Southwest Indians: Prehistory through Dentition. Res Explor 9:32.

Turpin SA. 1997. Cradles, Cribs, and Mattresses: Prehistoric Sleeping Accomodation in the Chihuahuan Desert. Journal of Big Bend Studies 9: 1-18.

Ullinger JM, Sheridan SG, Hawkey DE, Turner CG, and Cooley R. 2005.

Bioarchaeological analysis of cultural transition in the southern Levant using dental nonmetric traits. American Journal of Physical Anthropology 128:466–476.

VanPool TL and O’Brien MJ. 2013. Sociopolitical Complexity and the Bow and Arrow in the American Southwest. Evolutionary Anthropology 22: 111-117.

146

Walker CM. 2006. The bioarchaeology of newly discovered burial caves in the Sierra

Tarahumara. Ph.D. dissertation, University of Oregon, Eugene.

Walsh MR. 2000. Material evidence for social boundaries on the Pajarito Plateau, New Mexico. Kiva 65:197-213.

Ward JH. 1963. Hierarchical grouping to optimize an objective function. Journal of the

American Statistics Association 58.

Webster, D. 1976. Lowland Maya Fortifications. Proceedings of the American Philosophical Society, pp. 361-371.

Wallerstein I. 1974. The Modern World-System I: capitalist agriculture and the origin of the European World Economy in the sixteenth century. New York: Academic Press.

Washburn DK, Washburn WN, and Shipkova PA. 2011. The prehistoric drug trade: Widespread consumption of cacao in ancestral Pueblo and Hohokam Communities in the American Southwest. Journal of Archaeological Science, 38: 1634-1640.

Weigand PC. 2008. Turquoise: Formal Economic Interrelationships between Mesoamerica and the North American Southwest. In Archaeology without Borders: Contact, Commerce, and Change in the U.S. Southwest and Northwestern Mexico, Webster LD and McBrinn ME (eds.), University of Colorado Press.

Wells E. 2006. Recent Trends in Theorizing Prehispanic Mesoamerican Economies. J Archaeol Res 14:265–312.

Whalen ME and Minnis PE. 1996. Ballcourts and Political Centralization in the Casas Grandes Region. American Antiquity 61(4).

Willermet CM, Edgar HJH. 2009. Dental morphology and ancestry in Albuquerque, NM Hispanics. Homo Journal of Comparative Human Biology 60:207-224.

Willermet C, Edgar HJH, Ragsdale CS, Aubry BS. 2013. Biodistances among Mexica, Maya, Toltec, and Totonac Groups of Central and Coastal Mexico. Chungará Arica.

Woosley AI and Olinger B. 1993. The Casas Grandes ceramic tradition: production and

147

interregional exchange of Ramos Polychrome. In Culture and Contact: Charles C. DiPeso’s Gran Chichimeca, Woosley AC and Ravesloot JC (eds.) Amerind Foundation.

Wright S. 1943. Isolation by Distance. Genetics 28:114–138.

Zaragoza Ocaña D. 2009. Memoria del taller arqueologia de la Huasteca. Homenaje a

Leonor Merino Carrion. Coleccion Cientifica, Serie Arqueologia, 541. Instituto Nacional de Antropologia e Historia.

148

APPENDICES

Appendix 1. Shared migration history matrix used in the Mantel tests.

0.00

2.00

6.00

2.00

6.00

2.00

6.00

2.00

6.00

8.00

4.00

52.00

4.00

52.00

2.00

47.00

48.00

2.00

48.00

6.00

48.00

6.00

48.00

1.33

48.00

18.00

1.33

0.33

48.00

18.00

1.50

50.00

0.50

2.50

0.50

48.00

0.67

6.00

8.00

2.00

0.50

2.50

1.00

48.00

2.67

9.00

5.00

3.50

5.50

4.00

1.75

11.00

54.00

0.50

2.50

1.00

0.33

2.00

48.00

0.67

7.00

1.00

0.67

2.00

1.00

25.00

50.00

0.50

2.50

1.00

0.33

2.00

0.33

1.00

48.00

0.67

7.00

1.00

0.67

2.00

1.00

0.67

1.00

25.00

50.00

0.67

6.00

4.00

8.00

2.00

0.50

2.50

1.00

0.25

1.50

0.33

0.67

0.33

0.67

48.00

0.67

8.00

2.00

0.50

2.50

1.00

0.25

1.50

0.33

0.67

0.33

0.67

0.25

12.00

48.00

0.50

2.50

1.00

0.50

3.50

0.50

48.00

52.00

48.00

25.00

0.67

6.00

8.00

2.00

0.50

2.50

1.00

0.25

1.50

0.33

0.67

0.33

0.67

0.25

0.33

48.00

Zacapu

Tzintzuntzan

Huejuquilla

Guasave

Tecualilla

Tuxcacuesco

Nararachic

Candelaria

Cienegas Cienegas

Paquime

Jaina Island Jaina

Cozumel

Chicoasen

Zapotal

Vista Hermosa Vista

Tamtok

Zaachila

Yagul

Xochimilco

Tlatelolco

Tenayuca

Texcaltitlan

Teopanzolco

Teotenango Teotenango

Huexotla

Culhuacan Cholula Azcapotzalco

149

Appendix 2. Shared cultural group matrix used in the Mantel tests.

Tzintzuntzan

Huejuquilla

Guasave

Tecualilla

Tuxcacuesco

Nararachic

Candelaria

Cienegas

Paquime

Jaina Island

Cozumel

Chicoasen

Zapotal

Vista Hermosa

Tamtok

Zaachila

Yagul

Xochimilco

Tlatelolco

Tenayuca

Texcaltitlan

Teopanzolco

Teotenango Teotenango

Huexotla

Culhuacan Cholula Azcapotzalco

150

Appendix 3. Trade matrix used in the Mantel tests.

Zacapu

Tzintzuntzan

Huejuquilla

Guasave

Tecualilla

Tuxcacuesco

Nararachic

Candelaria

Cienegas

Paquime

Jaina Island

Cozumel

Chicoasen

Zapotal

Vista Hermosa

Tamtok

Zaachila

Yagul

Xochimilco

Tlatelolco

Tenayuca

Texcaltitlan

Teopanzolco

Teotenango Teotenango

Huexotla

Culhuacan Cholula Azcapotzalco

151

Appendix 4. Political interaction matrix used in the Mantel tests.

Zacapu

Tzintzuntzan

Huejuquilla

Guasave

Tecualilla

Tuxcacuesco

Nararachic

Candelaria

Cienegas

Paquime

Jaina Island

Cozumel

Chicoasen

Zapotal

Vista Hermosa

Tamtok

Zaachila

Yagul

Xochimilco

Tlatelolco

Tenayuca

Texcaltitlan

Teopanzolco

Teotenango Teotenango

Huexotla

Culhuacan Cholula Azcapotzalco

152

Appendix 5. Combined trade and political interaction matrix used in the Mantel tests.

Zacapu

Tzintzuntzan

Huejuquilla

Guasave

Tecualilla

Tuxcacuesco

Nararachic

Candelaria

Cienegas

Paquime

Jaina Island

Cozumel

Chicoasen

Zapotal

Vista Hermosa

Tamtok

Zaachila

Yagul

Xochimilco

Tlatelolco

Tenayuca

Texcaltitlan

Teopanzolco

Teotenango Teotenango

Huexotla

Culhuacan Cholula Azcapotzalco

153

Appendix 6. Mantel tests for geographic and cultural variables.

Variable (s) Correlation p Geographic x Migration 0.581 0.001** Geographic x Trade 0.173 0.057 Geographic x Political 0.446 0.001** Geographic x Trade/Political 0.334 0.002** Geographic x Cultural 0.074 0.121 Migration x Trade 0.219 0.011* Migration x Political 0.437 0.001** Migration x Trade/Political 0.366 0.002** Migration x Cultural 0.481 0.001** Trade x Political 0.388 0.002** Trade x Cultural 0.157 0.054 Political x Cultural 0.419 0.002** Trade/Political x Cultural 0.313 0.002**

Note: p values are averaged over 10 tests. Italics indicate the variable that is controlled for in the partial Mantel tests. * 0.05, **0.005

154

Appendix 7. Regional Mantel tests.

Variable (s) Correlation p Central Mexico Geographic Distance 0.159 0.135 Shared Migration History 0.533 0.001** Shared Cultural Group 0.336 0.009* Trade 0.401 0.001** Political Interaction 0.351 0.008* Trade/Political 0.451 0.001** West Mexico Geographic Distance 0.013 0.507 Shared Migration History 0.285 0.041* Shared Cultural Group 0.369 0.039* Trade 0.166 0.445 Political Interaction 0.074 0.331 Trade/Political 0.071 0.552 Northern Mexico Geographic Distance 0.298 0.071 Shared Migration History 0.515 0.001** Shared Cultural Group 0.387 0.034* Trade 0.166 0.457 Political Interaction 0.274 0.017* Trade/Political 0.194 0.064 Gulf Coast/Maya Region Geographic Distance 0.027 0.877 Shared Migration History 0.297 0.014* Shared Cultural Group 0.221 0.018* Trade 0.485 0.001** Political Interaction 0.329 0.012* Trade/Political 0.541 0.001**

Note: p values are averaged over 10 tests. Italics indicate the variable that is controlled for in the partial Mantel tests.

155

Appendix 8. Differences between male and female trait frequencies. Samples were limited to those with available sex estimates. Azcapotzalco (AZC), Tlatelolco (TLO), Texcaltitlan (TEX), Nararachic (NAR), Zacapu (ZAC), Jaina Island (JAI), and Vista Hermosa (VIS).

Trait AZC TLO TEX NAR ZAC JAI VIS Tooth

Shoveling 0.10 0.05 0.00 0.00 0.00 0.23 0.00 UI1 Shoveling 0.00 0.00 0.00 0.00 0.15 0.00 0.00 UI2 Double Shovel 0.25 0.16 0.00 0.00 0.00 0.00 0.17 UI1 Tuberculum 0.10 0.05 0.00 0.00 0.00 0.17 0.33 UI2 Metacone 0.13 0.33 0.10 0.10 0.14 0.25 0.05 UM1 Hypocone 0.25 0.21 0.11 0.22 0.14 0.25 0.00 UM1 Hypocone 0.16 0.03 0.14 0.25 0.14 0.08 0.25 UM2 Cusp 5 0.11 0.27 0.14 0.13 0.06 0.10 0.10 UM1 Carabelli’s 0.00 0.01 0.57 0.17 0.11 0.50 0.33 UM1 Shoveling 0.00 0.18 0.00 0.00 0.10 0.00 0.00 LI2 Complexity 0.07 0.01 0.00 0.00 0.10 0.33 0.00 LP4 Protostylid 0.10 0.00 0.00 0.33 0.10 0.00 0.00 LM1 Cusp 5 0.23 0.17 0.10 0.08 0.00 0.10 0.13 LM2 Cusp 6 0.11 0.17 0.00 0.00 0.00 0.25 0.00 LM2 Cusp 7 0.00 0.07 0.00 0.00 0.05 0.00 0.00 LM1

156

Appendix 9. Tetrachoric correlation matrix for dental morphological traits used in Chapter 3.

0.4256

0.0173

0.0749

0.0556

0.1173

0.2115

0.2274

0.0317

0.0337

-0.0984

0.0617

-0.0116

0.3218

0.0082

0.0571

LM1C6

0.4256

-0.0312

0.1517

0.2197

0.342

0.0995

0.4054

0.0314

-0.1618

-0.148

0.2811

0.0804

0.4006

0.0394

0.1554

LM2C5

0.0173

-0.0312

0.5907

0.0193

0.1395

0.1879

-0.0111

0.1881

-0.0288

0.0144

-0.0482

0.1993

0.189

0.1616

0.1485

LM2PS

0.0749

0.1517

0.5907

0.1742

0.0984

0.1438

0.0895

0.0273

-0.2352

-0.1354

-0.1077

0.2069

0.0563

0.1511

0.1466

LM1PS

0.0556

0.2197

0.0193

0.1742

0.1524

0.2678

0.2505

0.0765

-0.184

-0.1892

0.1384

0.0963

0.3505

-0.0277

-0.1258

LP4LC

0.1173

0.342

0.1395

0.0984

0.1524

0.2448

0.2201

0.1931

-0.2936

-0.1094

-0.1307

0.014

0.3637

0.3505

0.4122

LI1SS

0.2115

0.0995

0.1879

0.1438

0.2678

0.2448

0.3568

0.2714

0.0241

-0.1119

0.1818

0.0875

0.4017

-0.0274

0.0996

UM1CB

0.2274

0.4054

-0.0111

0.0895

0.2505

0.2201

0.3568

0.148

-0.2722

-0.3248

0.4535

0.1599

0.3095

0.1092

0.0544

UM1C5

0.0317

0.0314

0.1881

0.0273

0.0765

0.1931

0.2714

0.148

0.1596

0.0413

0.1601

0.079

0.2115

-0.0249

0.0318

UM2HC

0.0337

-0.1618

-0.0288

-0.2352

-0.184

-0.2936

0.0241

-0.2722

0.1596

0.4948

-0.2095

-0.135

-0.2636

-0.1512

-0.0855

UM1HC

-0.0984

-0.148

0.0144

-0.1354

-0.1892

-0.1094

-0.1119

-0.3248

0.0413

0.4948

-0.3742

-0.0985

-0.306

-0.0427

-0.0341

UM1MC

0.0617

0.2811

-0.0482

-0.1077

0.1384

-0.1307

0.1818

0.4535

0.1601

-0.2095

-0.3742

0.0739

0.185

-0.014

0.1828

UCDR

-0.0116

0.0804

0.1993

0.2069

0.0963

0.014

0.0875

0.1599

0.079

-0.135

-0.0985

0.0739

0.0571

-0.0211

-0.039

UI2TD

0.3218

0.4006

0.189

0.0563

0.3505

0.3637

0.4017

0.3095

0.2115

-0.2636

-0.306

0.185

0.0571

0.1639

0.1994

UI1DS

0.0082

0.0394

0.1616

0.1511

-0.0277

0.3505

-0.0274

0.1092

-0.0249

-0.1512

-0.0427

-0.014

-0.0211

0.1639

0.7412

UI2SS

0.0571

0.1554

0.1485

0.1466

-0.1258

0.4122

0.0996

0.0544

0.0318

-0.0855

-0.0341

0.1828

-0.039

0.1994

0.7412

UI1SS

LM1C6

LM2C5

LM2PS

LM1PS

LP4LC

LI1SS

UM1CB

UM1C5

UM2HC

UM1HC

UM1MC

UCDR

UI2TD

UI1DS UI2SS UI1SS

157

Appendix 10. Tetrachoric correlation matrix for dental morphological traits used in Chapter 4.

0.5651

0.1086

-0.0128

-0.0564

0.2579

-0.0934

-0.1251

0.0114

0.2714

-0.2032

-0.0777

LM2C5

0.5651

0.2294

0.1924

0.0996

0.208

0.5209

0.4537

-0.1795

0.4891

0.2262

-0.1388

LM1C5

0.1086

0.2294

0.0471

0.3651

0.2342

0.1929

0.3323

-0.3711

-0.3067

-0.1445

0.2654

LM1DW

-0.0128

0.1924

0.0471

0.403

0.0606

0.0132

0.2404

0.1027

-0.1682

0.2133

0.0394

LM1AF

-0.0564

0.0996

0.3651

0.403

0.2366

0.0452

0.0415

0.1735

0.2091

0.0144

0.1456

LP4LC

0.2579

0.208

0.2342

0.0606

0.2366

0.1603

0.2771

0.1983

-0.3075

-0.2781

0.4328

LI2SS

-0.0934

0.5209

0.1929

0.0132

0.0452

0.1603

0.356

0.1421

-0.2169

0.3889

-0.2093

UM1CB

-0.1251

0.4537

0.3323

0.2404

0.0415

0.2771

0.356

0.1405

0.0633

-0.2997

-0.3616

UM1HC

0.0114

-0.1795

-0.3711

0.1027

0.1735

0.1983

0.1421

0.1405

0.0598

-0.0806

0.1329

UCDR

0.2714

0.4891

-0.3067

-0.1682

0.2091

-0.3075

-0.2169

0.0633

0.0598

0.1093

-0.196

UI2TD

-0.2032

0.2262

-0.1445

0.2133

0.0144

-0.2781

0.3889

-0.2997

-0.0806

0.1093

-0.3462

UI1DS

-0.0777

-0.1388

0.2654

0.0394

0.1456

0.4328

-0.2093

-0.3616

0.1329

-0.196

-0.3462

UI1SS

LM2C5

LM1C5

LM1DW

LM1AF

LP4LC

LI2SS

UM1CB

UM1HC

UCDR

UI2TD UI1DS UI1SS

158

Appendix 11. Mean Measure of Divergence (MMD) matrix for all samples compared in Chapter 3.

159

Appendix 12. Procrustes analysis plot for shared migration history (diamond) and pseudo-Mahalanobis’ D2 distances (square). Abbreviations: Autlan-Tuxcacuesco (AT); Azcapotzalco (AZ); Candelaria-Paila (CP); Chalpa-Tecualilla (CT); Chicoasen (CN); Cholula (CH); Cozumel (CZ); Culhuacan (CU); Cuatro Ciénegas (CC); Guasave (GU); Huejuquilla (HU); Huexotla (HX); Jaina Island (JA); Nararachic (NA); Paquimé (PA); Tamtok (TK); Tenayuca (TN); Teopanzolco (TP), Teotenango (TG); Texcaltitlán (TX); Tlatelolco- Tenochtitlan (TO); Tzintzuntzan (TZ); Vista Hermosa (VH); Xochimilco (XO); Zaachila (ZA); Yagul (YG); Zacapu (ZU); and Zapotal (ZP). Correlation= 0.71, p = 0.001.

60 CN

50 CP TX CZ CC 40 YG TP 30 CZ YG 20 ZA JA HU 10 TZ ZA ZU PA XO CNXOTK GU VHCTTP PA 0 CTTX ZU TO CP HX TZ CC ZP HU F2 (27.24 (27.24 F2 %) AT HX TGCU NA GU -10 TN CH VH ZP TG JA TNCHCU AT TO NA -20 TK

-30

-40

-50 -40 -30 -20 -10 0 10 20 30 40 50 60 70 F1 (72.76 %)

160

Appendix 13. Procrustes analysis plot for shared migration history (diamond) and pseudo-Mahalanobis’ D2 distances (square). Abbreviations: Autlan-Tuxcacuesco (AT); Azcapotzalco (AZ); Candelaria-Paila (CP); Chalpa-Tecualilla (CT); Chicoasen (CN); Cholula (CH); Cozumel (CZ); Culhuacan (CU); Cuatro Ciénegas (CC); Guasave (GU); Huejuquilla (HU); Huexotla (HX); Jaina Island (JA); Nararachic (NA); Paquimé (PA); Tamtok (TK); Tenayuca (TN); Teopanzolco (TP), Teotenango (TG); Texcaltitlán (TX); Tlatelolco- Tenochtitlan (TO); Tzintzuntzan (TZ); Vista Hermosa (VH); Xochimilco (XO); Zaachila (ZA); Yagul (YG); Zacapu (ZU); and Zapotal (ZP).

40 TP CN TNTGYGTPTX CZ YG CU ZA CC 20 CN CP VH NA XO CPCC CT AZTX XOAZZA TZ ZU

F2 (41.57 F2 (41.57 %) HX 0

HX CH AT PA TG ZP JI TN TK CZ VH CHTOCU -20 ZP HUATCT JI NA TK TZZU GU GU HU -40 TO PA -40 -20 0 20 40 60 F1 (58.43 %) 161

Appendix 14. Procrustes analysis plot for shared cultural/linguistic group (diamond) and pseudo- Mahalanobis’ D2 distances (square). Abbreviations: Autlan-Tuxcacuesco (AT); Azcapotzalco (AZ); Candelaria-Paila (CP); Chalpa-Tecualilla (CT); Chicoasen (CN); Cholula (CH); Cozumel (CZ); Culhuacan (CU); Cuatro Ciénegas (CC); Guasave (GU); Huejuquilla (HU); Huexotla (HX); Jaina Island (JA); Nararachic (NA); Paquimé (PA); Tamtok (TK); Tenayuca (TN); Teopanzolco (TP), Teotenango (TG); Texcaltitlán (TX); Tlatelolco-Tenochtitlan (TO); Tzintzuntzan (TZ); Vista Hermosa (VH); Xochimilco (XO); Zaachila (ZA); Yagul (YG); Zacapu (ZU); and Zapotal (ZP).

60 HU 50

40 GU

30 NA CC JA HU TK 20 TK ZP 10 VH CUTOCH CP PA TG TN CHNAZUATCTPACUTZZATNTGTX XOAZHXTPTO 0 ZP JACZCN YGAT

F2 (20.12 (20.12 F2 %) -10 CC ZU TZ HX CT TXAZ -20 VH XO CN CZ ZA GU -30 CP YG -40 TP -50

-60 -90 -80 -70 -60 -50 -40 -30 -20 -10 0 10 20 30 F1 (79.88 %)

162

Appendix 15. Procrustes analysis plot for trade (diamond) and pseudo-Mahalanobis’ D2 distances (square). Abbreviations: Autlan-Tuxcacuesco (AT); Azcapotzalco (AZ); Candelaria-Paila (CP); Chalpa-Tecualilla (CT); Chicoasen (CN); Cholula (CH); Cozumel (CZ); Culhuacan (CU); Cuatro Ciénegas (CC); Guasave (GU); Huejuquilla (HU); Huexotla (HX); Jaina Island (JA); Nararachic (NA); Paquimé (PA); Tamtok (TK); Tenayuca (TN); Teopanzolco (TP), Teotenango (TG); Texcaltitlán (TX); Tlatelolco-Tenochtitlan (TO); Tzintzuntzan (TZ); Vista Hermosa (VH); Xochimilco (XO); Zaachila (ZA); Yagul (YG); Zacapu (ZU); and Zapotal (ZP).

40 TP CN TNTGYGTXTP CZ YG CU ZA CC 20 CN CP NA XO VH CPCC CT AZTX TZ XOAZZA HX ZU F2 (41.57 (41.57 F2 %) 0 HX CH AT PA TGJA TKCZ TNZP VH CHCU TO -20 ZP HUATCT JA NA TK TZZU GU GU HU -40 TO PA -40 -20 0 20 40 60 F1 (58.43 %)

163

Appendix 16. Procrustes analysis plot for political interaction (diamond) and pseudo-Mahalanobis’ D2 distances (square). Abbreviations: Autlan-Tuxcacuesco (AT); Azcapotzalco (AZ); Candelaria-Paila (CP); Chalpa-Tecualilla (CT); Chicoasen (CN); Cholula (CH); Cozumel (CZ); Culhuacan (CU); Cuatro Ciénegas (CC); Guasave (GU); Huejuquilla (HU); Huexotla (HX); Jaina Island (JA); Nararachic (NA); Paquimé (PA); Tamtok (TK); Tenayuca (TN); Teopanzolco (TP), Teotenango (TG); Texcaltitlán (TX); Tlatelolco- Tenochtitlan (TO); Tzintzuntzan (TZ); Vista Hermosa (VH); Xochimilco (XO); Zaachila (ZA); Yagul (YG); Zacapu (ZU); and Zapotal (ZP).

40 TZ ZU AT CT TK TOCU CH JA HU GU HU 20 VHZP NAGU TNTX TG HXTG AT CZCNJA AZTZZU PA NA 0 TX PA TNCT TP ZAYG F2 (29.93 (29.93 F2 %) XOAZ ZPVH -20 HXXOTO ZA TK CUYG CPCCCH CC CP -40 TP CZ CN -60

-80 -80 -60 -40 -20 0 20 40 60 80 F1 (70.07 %)

164

Appendix 17. Procrustes analysis plot for trade and political interaction combined (diamond) and pseudo- Mahalanobis’ D2 distances (square). Abbreviations: Autlan-Tuxcacuesco (AT); Azcapotzalco (AZ); Candelaria-Paila (CP); Chalpa-Tecualilla (CT); Chicoasen (CN); Cholula (CH); Cozumel (CZ); Culhuacan (CU); Cuatro Ciénegas (CC); Guasave (GU); Huejuquilla (HU); Huexotla (HX); Jaina Island (JA); Nararachic (NA); Paquimé (PA); Tamtok (TK); Tenayuca (TN); Teopanzolco (TP), Teotenango (TG); Texcaltitlán (TX); Tlatelolco-Tenochtitlan (TO); Tzintzuntzan (TZ); Vista Hermosa (VH); Xochimilco (XO); Zaachila (ZA); Yagul (YG); Zacapu (ZU); and Zapotal (ZP).

ZUTZ 40 ATCT HU HU TK GU GU JA NA 20 CHTO ZP CU VH TN TG PA AT HX PA 0 TZ ZU AZ JACZ TX CT TX CN F2 (33.89 (33.89 F2 %) TO TG ZP AZZA NA XO TN TK XO CH TPYG VH -20 HX ZA CU YG CCCP CC CP CZ -40 TP CN

-60 -60 -40 -20 0 20 40 60 F1 (66.11 %)