An Odontometric Investigation of Biological Affinities of the Yashkun

An Odontometric Investigation of the Biological

Origins and Affinities of the Yashkuns of

Astore, Gilgit-Baltistan, Northern Pakistan

Amber M. Barton

A Thesis Submitted to the Anthropology Program California State University, Bakersfield In Partial Fulfillment for the Degree of Masters of Art

Spring 2016

Amber Marie Barton

2016

An Odontometric Investigation of Biological Origins and Affinities of the Yashkuns of Astore, Gilgit-Baltistan, Northern Pakistan

By Amber M. Barton

This thesis has been accepted on behalf of the Anthropology Program faculty by their supervisory committee:

C1. t.~ Brian E. Hemphill, Ph.D. Committee Member

3 Acknowledgements

The completion of this work has been an opportunity to fulfill the author‘s passion within both archaeology and biological anthropology. The author would like to extend gratitude to those that helped accomplish this milestone. The sincerest appreciation is extended toward my thesis committee. Thanks to Dr. Robert Yohe II and Mr. Patrick O‘Neill for being on my thesis committee and providing advice and encouragement throughout the research process. Thanks to

Dr. Brian Hemphill for guiding me throughout my academic career and providing support and assistance with the research and statistical analyses. Great acknowledgment is given towards the

California State University, Bakersfield‘s Student Research Scholars program and the Ronald E.

McNair Post-baccalaureate Achievement program for providing both financial support and the opportunity to share my research. I would also like to thank the Yashkun and other participants within Northern Pakistan who graciously participated in this research.

4 An Odontometric Investigation of Biological Origins and Affinities of the Yashkuns of Astore, Gilgit- Baltistan, Northern Pakistan

A.M. Barton Program of Anthropology California State University, Bakersfield

Abstract

The Yashkun are a Dardic-speaking ethnic group who live in Gilgit-Baltistan in extreme northern Pakistan. Most researchers assert that the Yashkun are immigrants to northern Pakistan from Central Asia. However, other authorities maintain that the Yashkun are indigenous to northern Pakistan (Dani, 2001). The purpose of this research is to investigate Yashkun biological affinities to determine whether members of this ethnic group represent long-standing indigenous occupants of northern Pakistan or whether they represent immigrants from Central Asia or elsewhere.

This research seeks to identify Yashkun origins through a comparative analysis of permanent tooth size allocation among 163 Yashkun young adults from the village of Astoree, located in Gilgit-Baltistan Province, northern Pakistan. Maximum mesiodistal and buccolingual measurements were obtained for all permanent teeth, except third molars, in accordance with the methods of Moorrees (1957). Individual measurements were scaled against the geometric mean to control for sex dimorphism and evolutionary tooth size reduction. These data were contrasted with 23 samples of prehistoric and living individuals from Pakistan, peninsular India, South- Central Asia, and the Iranian Plateau. Inter-sample differences in tooth size allocation were assessed with pairwise squared Euclidean distances and the patterning of phenetic affinities among samples was assessed with multidimensional scaling, neighbor-joining cluster analysis, hierarchical cluster analysis, and principal co-ordinates analysis.

The results indicate that Yashkuns possess rather close affinities to Wakhis and Khowars, with most distant affinities to other groups from the northern highlands of Pakistan. Yashkuns exhibit no affinities to prehistoric inhabitants of Central Asia or the Indus Valley, or to living ethnic groups of peninsular India. Hence, Dani's assertion that the Yashkuns represent the living descendants of a common, indigenous population of the Hindu Kush and Karakoram highlands appears to be confirmed.

5 Contents Chapter 1: Introduction ...... 11 Peopling of the Indian Subcontinent ...... 13 Ethnohistory of the Autonomous Territory of Gilgit-Baltistan ...... 15 Astore ...... 18 Yashkun Origins ...... 19 Aryan Invasion Model ...... 20 Language ...... 21 Chapter 2: Peopling of South Asia ...... 24 Aryan Invasion Model ...... 24 Long-Standing Continuity Model ...... 27 Early Entrance Model ...... 29 Historic Era Influences Model ...... 32 Chapter 3: General Research Questions...... 34 Chapter 4: Odontometric Heritability ...... 37 Odontogenesis ...... 37 Heritability ...... 42 Dental Genetics ...... 44 Size Differences at the Population Level ...... 47 Chapter 5: Previous Studies of Affinities among South Asian Ethnic Groups ...... 49 Modern Populations ...... 49 Prehistoric Populations ...... 56 Chapter 6: Materials and Methods ...... 58 Materials ...... 58 Methodology ...... 59 Fluctuating Asymmetry ...... 59 Sexual Dimorphism ...... 60 Multivariate Analyses ...... 61 Chapter 7: Comparative Samples ...... 63 Prehistoric Central Asia ...... 63 Prehistoric Indians ...... 64 Prehistoric Indus Valley ...... 66

6 Hindu Kush/Karakoram Highlands ...... 66 Southeast Indians ...... 68 Western India ...... 69 Chapter 8: Operationalized Research Questions ...... 71 Chapter 9: Results I- Odontometric Variation among the Yashkun of Astore ...... 75 Intra-Observer Error Analysis ...... 75 Inter-Observer Error Analysis ...... 75 Asymmetry ...... 78 Sexual Dimorphism ...... 80 Chapter 10: Results II- Odontometric Assessment of the Yashkun Phenetic Affinities ...... 86 Data Preparation for Analysis ...... 86 Hierarchical Cluster Analysis ...... 87 Neighbor-joining Cluster Analysis ...... 87 Multidimensional Scaling ...... 89 Principal Co-ordinates Analysis...... 92 Chapter 11: Discussion ...... 95 References ...... 105 Appendices ...... 118 Appendix A ...... 119 Appendix B ...... 122

List of Figures

Figure 1. Map depicting the Aryan Invasion Model………………………………….…...……..24

Figure 2. Map depicting the Early Entrance Model.………...………………………………...…31

Figure 3. Map of Comparative Samples with Yashkun placed for reference. Color designations are represented in Table 1. ………………………………………………………………………65

Figure 4. Map depicting the Hindu Kush/ Karakorum Highland samples (in purple) with associated geographic landmarks (in yellow)…………………………………………….……...67

Figure 5. Hierarchical Cluster Analysis with Ward‘s (1963) Method………..………………….88

Figure 6. Neighbor-joining Cluster Analysis…………………….………………………………89

Figure 7. Multidimensional Scaling using Guttman‘s (1968) Method…………...……………...91

Figure 8. Multidimensional Scaling using Kruskal‘s (1964) Method………………...…………92

Figure 9. Principal Co-ordinates Analysis……………………………………………...... ……94

List of Tables

Table 1. Comparative Samples with Abbreviations and Sample Sizes…………….……………64

Table 2. Intra-Observer Error using Paired-Sample t-Tests. Highlighted depict significant differences (p< 0.05). ……………….…………………………………………………………...76

Table 3. Inter-Observer Error using Paired-Sample t-Tests. Highlighted depict significant differences (p< 0.05)………………………………………………………..……………………………….……77

Table 4. Paired-sample t-tests of Asymmetry between Antimeric Dental Elements……….……79

Table 5. Descriptive statistics of Odontometric Variation among Yashkun Males of Astore…...80

Table 6. Descriptive statistics of Odontometric Variation among Yashkun Females of Astore…………………………………………………………………………………………….81

Table 7. Male Tooth Dimensions Compared to Female Tooth Dimensions Using t-Tests. Highlighted depict significant differences (p< 0.05). ……………………………..…………….82

Table 8. Percentage of Sexual Dimorphism per Tooth and Dimension.………………………...83

List of Appendices

Appendix A. Euclidean Distances…………………………………………………..…….……118

Appendix B. Yashkun Odontometric Measurements…………………………………...……...121

Chapter 1: Introduction

The modern Islamic Republic of Pakistan encompasses a population in excess of 150 million individuals (Qamar et al., 2002) living within eight governmental administrative units. These include four provinces: Punjab, Khyber Pakhtunkhwa, Baluchistan, a federal capital territory

(Islamabad), a disputed territory (Azad Jammu and Kashmir), the Federally Administrated Tribal

Area (FATA), and the autonomous territory of Gilgit-Baltistan. The country is home to approximately 18 distinct ethnic groups based on both cultural and linguistic markers (Mansoor,

2003; Mohyuddin, 2000) and which, as a group, are speakers of over 60 different languages

(Grimes, 1992). Given such ethnic and linguistic diversity, as well as its location in the extreme northwestern corner of South Asia, Pakistan encompasses an area central to archaeological and anthropological investigations concerning the initial peopling and subsequent population movements into South Asia. Understanding the population history of the region can clarify the depth of interactions and cultural exchange occurring among those inhabiting the margins of

Central Asia, South Asia, and western China. Research has traditionally focused on archaeological and linguistic data (Erdosy 1989, Fairservis 1995, Parpola 1995). However, in recent years, there has been an increase in studies based on biological indicators of population movement and gene flow obtained from genetic investigations among members of living ethnic groups (Moyhuddin, 2000; Mansoor, 2003; Qamar et al., 2002; Quitana-Murci et al., 2001).

Furthermore, analyses that incorporate both living and prehistoric samples can provide an avenue for addressing in a more refined way the temporal periods that population movement and interactions occurred. This research provides additional insight into the origins and migration of the northwestern populations of South Asia in general, and of the Yashkun in particular, through an investigation of tooth size allocation across the permanent dentition.

The Yashkun, who throughout antiquity have also been referred to as the Yeshkun and

Yuechi, are a Dardic-speaking ethnic group residing in Gilgit-Baltistan. The Autonomous

Territory of Gilgit-Baltistan is bounded by the Himalayas to the east, the Hindu Kush to the west, and the Karakorum to the north. The boundary between Baltistan and the Indian state of Jammu and Kashmir delineates the eastern boundary of Gilgit-Baltistan. The Himalayas is a mountain range dividing Gilgit-Baltistan, intersecting with the Indus River and the Rondu Gorge in the north and the Astore River and valleys in the east. Politically, Gilgit-Baltistan is organized into two divisions, Gilgit and Baltistan, and 12 districts. The eastern portion of Gilgit-Baltistan is represented by the Baltistan Division and encompasses the districts of Ghanche, Shigar,

Kharmang, Skardu, Gultari, and Rondu. The western region of Gilgit-Baltistan, located north of the Gilgit Range and Diamar, is represented by the Gilgit Division, which is in turn divided into the six districts of Gilgit, Diamar, Ghizer, Astore, Hunza, and Nagar. The Astore District, whose administrative center is located at Eidghah, encompasses a population of approximately 72,000 according to the 1998 census. Overall, Gilgit-Baltistan has a total population of an estimated

884,000 according to the same census date. The construction of public infrastructure, including bridges, the Karakorum Highway, and the road through Rondu Gorge linking Gilgit and Skardu, have integrated the once isolated valleys and represent a fairly recent ease of access and integration of local populations (Dani, 2001).

A brief prehistory and history of the local and greater regions pertinent to the study will be presented so that a framework for the proposed array of population movements that may have occurred throughout antiquity can be established. The original peopling of Pakistan will be explored and followed by a more detailed ethnohistory of Gilgit-Baltistan in general and an

12 overview of the geographical significance of the Astore Valley in the context of Yashkun origins and biological affinities in particular.

Peopling of the Indian Subcontinent

The earliest evidence of human habitation of the Indian subcontinent dates to the Paleolithic, approximately 700,000 BP years ago (Chauhan, 2009). Paleolithic sites within South Asia are scattered throughout the entire region. Sites during this period can be further divided into three categories, the Lower, Middle, and Upper Paleolithic based upon technological development

(Allchin and Allchin, 1982). The differentiation between periods is observed through variation in lithic assemblages. The Lower Paleolithic is characterized by more robust lithic tools such as hand axes and cleavers. Lower Paleolithic sites vary but are typically represented by habitation sites in rock shelters or open, production sites for material, or a combination of the two (Allchin and Allchin, 1982). The Middle Paleolithic has smaller, flaked tools that have a distinguished shape. Middle Paleolithic sites shift in location relative to earlier Lower Paleolithic sites. For example, Middle Paleolithic sites are less exposed and are located closer to the base of slopes overlooking valleys (as opposed to the Lower Paleolithic locations at summits) (Allchin and

Allchin, 1982). The Upper Paleolithic continues to see a reduction in tool size and includes blades and burins. Within the archaeological record, sites show continuity in use between the

Middle and Upper Paleolithic. The distinguishing feature between the two periods is the difference in technology. The Upper Paleolithic represents a change in methodology which may be indicative of a change in use. Such a change is up for discussion but has been attributed to possible changes in hunting methodology or environmental change (Allchin and Allchin, 1982).

The subsequent period in South Asia, the Mesolithic, is thought to range from approximately c. 9000 to 1000 BC (Allchin and Allchin, 1982). The Mesolithic is also largely recognized by a lithic assemblage and continues to demonstrate a decrease in size of tools. Microliths, similar to those found in France, England, and East Africa, have been recovered from both the Deccan

Plateau and the Punjab. Wolpert (1997) posits that these microliths were transported by populations that were separate from the populations present during the Paleolithic.

The Neolithic is marked by the climatic change at the end of the Pleistocene approximately

10,000 years ago that made environmental conditions suitable for agriculture and subsequent settlement. Mehrgarh, located in Baluchistan, represents the earliest settlement of this period

(Jarrige, 1991; Mohyuddin, 2000). Mehrgarh was initially occupied around 7000 B.C., making its occupation contemporaneous with settlements in Mesopotamia.

The end of the Neolithic is marked by the Early Harappan Period beginning around 3300

B.C. with the appearance of the Bronze Age Indus Valley civilization. Prominent Indus Valley sites include Harappa and Mohenjo-Daro, Chanhu-Daro, Dolvira, Farmana, Sutkagan-Dor,

Balakot, and Shortugai. The people within the Indus Valley established planned settlements with an agrarian economy, as well as trade networks with Mesopotamia and Sumeria (Dales, 1991;

Mohyuddin, 2000).

The decline of the Indus Valley civilization was once thought to have been driven by shifts in tectonic plates that triggered flooding, which disturbed the agricultural system of these populations around 1900-1300 B.C. (Kenoyer, 1998; Dales, 1965; Mohyuddin, 2000). The flooding buried settlements and changed agricultural practices and thereby the economy. Trade was rerouted due to the abandoned settlements. Crops shifted to focus on rice, millet, and sorghum, which could withstand the monsoon seasons that were now characteristic of the region.

The cultural and economic adaptations shifted the political center of the continent from the Indus

Valley to the middle Ganga region over the subsequent thousand years (Kenoyer, 1998).

Since the cities of the Indus Valley Civilization, there has been no break in settled human occupation of the subcontinent (Kenoyer, 1998). Prehistory and archeology pertinent to the current study will be outlined in Chapter 7: Comparative Samples and Chapter 2: Models for the

Peopling of South Asia.

Ethnohistory of the Autonomous Territory of Gilgit-Baltistan

Many ethnographies and geographic accounts of Pakistan and the surrounding region attempted to catalog and categorize the inhabitants and the land during the late 1800s (Drew,

1875; Biddulf, 1880). One of the first classifications of the region was imposed by Dr. G.W.

Leitner, who began his explorations in Gilgit in 1855 (Dani, 2001). Leitner referred to the region as ―Dardistan‖ and the inhabitants as ―Dards.‖ The terminology was taken from the Mair, a tribe living on the right bank of the Indus in Kohistan, to describe the tribes who lived on the opposite bank of the river (Rose, 1970). While this term was used to describe the inhabitants, the people of the Northern Areas do not use this term to describe themselves (Dani, 2001). Even though a generalized term was used to refer to the people within the region, the people represented different ethnic groups who spoke distinct languages. ―Da rd‖ and ―Dardic‖ are also terms used to describe languages spoken within Gilgit-Baltistan.

The Dards have been described historically by Herodotus. Specifically, the Dards, referred to as Dadicae by Herodotus, were part of the Achaemenian Seventh Satrapy, which included the

Sattagydians, Gandarians, and Aparytae (Dani, 2001; Rawlinson, 1945). The Sattagydians,

Gandarians, and Dadicae are described as Aryan groups (Rawlinson, 1945: 550). The identity of the Dards, being recognized as the Dadicae, and even Derdae and Dardae throughout antiquity,

15 has been examined by Eggermont (1984). The link between the Dards and the other references are found in a description by Ptolemy describing the habitation of the Dards as south of the Indus

River, encompassing the Swat Valley and Gandhara Plain. This would include the uplands of

Dir, Swat, and Astore. This specific reference was describing a part of the Persian

(Achaemenian) empire first depicted by Herodotus. The Achaemenid Empire was founded in

550 B.C. and dissolved by 330 B.C. While Ptolemy describes a specific region for the Dard habitation, Dardistan encompasses a wider geographic region that includes modern northern

Pakistan, Indian Kashmir, southern Uzbekistan, Tajikistan, and north-eastern Afghanistan. In regards to the Yashkun, Dardistan did encompass the upper portions of the Gilgit-Baltistan including the Hunza and Nagar valleys.

Dani (2001) describes two significant outcomes for the Dards as a result of being incorporated into Achaemenian jurisdiction. With the inclusion of the Dards into the Seventh

Satrapy, the Dards then became incorporated into the army of the Archaemenians that were fighting against the Greeks during the Persian Wars. The second major effect of being included in the Achaemenian jurisdiction was the productive increase in gold mines within Dardistan. In both the Eggermont and Herodotus accounts, gold mining was described in the regions occupied by the Dards. Gold dust was used as tribute and taxes for the Achaemenians. In addition, gold was used for trade and increased the local economy to include gold procurement on top of the food production, which was the primary economic mode prior to Achaemenian influence.

A description of the culture was documented by Drew in the late 1800s. His accounts describe the groups inhabiting the region north of Azad Jammu and Kashmir; extending to the

Baltis in the east and the Pathans or Afghans in the west (Drew, 1876). Their clothing was

16 described as being made of wool or cotton for the summer. Unique to the Dards is the cap, which is made of rolled woolen cloth (Drew, 1876).

The Dards are subdivided into a caste system. These castes are maintained through social norms involving rules of intermarriage between caste divisions (Drew, 1876). While there are many ethnic groups in Dardistan, Drew (1876) outlines the order of rank (decreasing) for the four Dard castes as: (1) Shina, (2) Yashkun, (3) Kremin/Kamin, and (4) Doms. A brief account of each caste will be provided below (for a more thorough description of the Dard castes, see

Drew 1876: 426). The highest status caste is the Shina. The Shina comprise the second largest population of Dards, next to the Yashkun. The Yashkun are involved with agriculture, especially in Astore and Gilgit, and are now described as landowners (Dani, 2001). The Yashkun inhabit valleys along the Indus tributaries, including the Nagar, Hunza, Iskoman, Yāsīn, and Chitrāl

Rivers (Drew, 1876).

Both the Kremins and the Doms represent a minority among the Dards. The Kremins hold occupations such as potters, millers, and carriers. While the Kremins were craftsmen historically, they are now mostly poorer farmers (Dani, 2001). The lowest caste is the Doms. This caste is represented by musicians. This low rank is also seen in the Marāsīs of the Panjāb and the Doms of India (Drew 1876).

The differential social status of the Shina and Yashkun is reflected by the unidirectional nature of hypergamous marriages among them. Leitner (1866) claims that a Yashkun woman can marry a Shina man (i.e., hypergamy); however, the opposite pairing of a Yashkun man to a Shina woman (i.e., hypogamy) is forbidden. Dani (2001) affirms that the higher castes are arranged into a series of patrilineal exogamous lineages. Families were dependent upon their extended

17 family members for subsistence. For example, brothers often divide agricultural work among themselves.

Although not within the Dardic caste system, Drew also mentions the Ronos as the most prestigious class in the region. Among the Baltis, Ronos were considered as members of the princely elite. This caste was uncommon and primarily located around Gilgit (Drew, 1876).

Drew also suggests that their high ranking is the result of former political power, accounting for the condensed locality of the caste. Dani (2001) clarifies that rather than being considered a primary rank within the Dard caste system, the Ronos were instead a series of families that can be considered ―caste-like.‖ Specifically, the Ronos are families of an unspecified foreign origin that were a part of the political sphere, producing wazirs, or high political officials.

Astore

The area of interest for this study is the village of Astore (Astoor). The region of Astore has also been referred to as Aswira, Husara, and Hasora by the Dogras and Persians (Drew,

1876; Dani, 2001). However, Astore is the name used in the Dardic language. Astore is located within the Astore Valley. The Astore River runs through the valley and joins with the Indus, dividing the valley into two main branches each approximately 60-70 miles in length (Drew,

1876). In historic times Astore was accessible through a variety of routes. Through the eastern branch runs the Dorikun Pass, linking Astore to Skardu to the east, Gurez to the south, and Gilgit to the north. The Kamri Pass runs through the western branch of the Astore Valley. Additional passes include the Mazenu and Hatu Passes. The Hatu Pass in the northeast border on the Astore

Valley runs parallel to the Astore River and links Astore to the Indus River and, eventually, the

Indus Valley.

The hill-sides are covered with light grass, and forests of pine, spruce, and fir. More commonly, birch and Pinus excelsa are found at the higher elevations of 12,000 and 11,300 feet, respectively (Drew, 1876). Cultivation begins at around 10,000 feet and cultigens include, but are not limited to, apricots, walnuts, almonds, apples, and chilgoza (Drew, 1876; Dani, 2001).

Breeding and maintenance of pack-animals, such as mules and ponies, has become an important component of the economy (Dani, 2001).

The city is historically significant due to its location along the main route from Gilgit to

Kashmir (Dani, 2001). Later, as a consequence of British contact, Astore experienced increased traffic due to its location on the route to Gilgit. Astore is also a stop along the route to Gurez, the outpost for rulers of Gilgit (Dani, 2001). Being conveniently located along such an active political route fostered an interactive center for the settled population. However, because of this location, it also made the village a target for political battles. For instance, Astore was conquered by Ali Sher Anchan and incorporated into the Maqpon Dynasty. The Maqpons were centered within the Indus Valley, with other locations within Skardu and Rondu, Tolti, and Kartakhshah.

Eastern influence is noted from the Tibetan origin of ―maqpon, ‖ meaning ―commander of a frontier district‖ (Dani, 2001). The village seems to have always been active within the political community. Currently, Astore acts as a tehsil for the District of Chilas (Dani, 2001). A tehsil is a political unit that serves as an administrative center, for in this case, the District of Chilas.

Yashkun Origins

The origins of the Yashkun, specifically, and the peopling of South Asia, generally, have been topics of much debate. On the one hand, the Yashkun are thought to be native to the region.

Dani (2001) suggests that both the Yashkun and the Kremins are descendants of an aboriginal

19 population, while Leitner (1866) posits that the Yashkun are descendants of mixed marriages between the Shina and an unspecified indigenous population. Contrarily, Drew (1876) counters that the Kremin are more likely to be of a local origin while the Yashkun, together with the

Shina, are representative of a founding immigrant population. Drew reasons that since the

Yashkun have similar occupations and physical characteristics as the Shina, they are more representative of a founding group that later split into two entities for reasons unknown.

Gankovsky (1973) provides an alternate origin in Central Asia, suggesting that the Yashkun were a population that immigrated through Bactria. Gankovsky cites Chinese chronicles dating from the second century B.C. which describes a conflict between the Huns and the Yueh-chi

(Yashkun). The Yueh-chi were inhabitants of the eastern edges of Central Asia and were pushed west by the Huns through the Takla Makan Basin of Xinjiang. Sanskrit manuscripts describe the

Yashkun as absorbing indigenous Indo-European language (which Gankovsky details as East-

Iranian and Massaget-Sakan languages) elements as they migrated west. The Yashkun are described as moving into the interior of the Indo-Pakistan subcontinent and Gankovsky considers them part of a grand Scythian-East-Iranian tribal union.

Aryan Invasion Model: Drew (1876: 7) notes that several ethnic groups residing in the highlands of northern Pakistan possess features considered to be the Aryan prototype and thus distinguishing them as a separate ethnicity. Drew places the Dogras, Chibhalis, Paharis,

Kashmiris, and Dards as those groups showing Aryan physical characteristics. The Dogras inhabit areas within India and Pakistan; the Chibhalis within northern India; the Paharis are found within the Himalayas of Nepal, India, and Pakistan; while the Kashmiris reside within the

Kashmir Valley. The Baltis, Ladakhis, and Champas are considered to be of a Tibetan ancestry

20 originating, in Central Asia and speaking a Turanian language (a combination of Uralic and

Altaic families). Drew states, ―Whether we judge from language or from physiognomy, the conclusion is inevitable that the Dards are an Aryan race‖ (1876:423).

The exact date of the introduction of Vedic culture into India is not certain. However, the

Aryan invasions are thought to date back to 3000 B.C., based upon the Bactrian-Margiana

Archaeological Complex (BMAC) (Sarianidi, 1999). Similar artifacts include glyphs, vessels, and even architectural styles (Sarianidi, 1999). There are two avenues (genetic and cultural) that can be explored to test not only the validity of the posited dates for interaction, but also the degree of interaction.

The Aryans are believed to have been pastoralists, whose origins may be traced to Indo-

European-speaking migrations from West Asia. Proponents of the Aryan Invasion model maintain that the Aryans migrated through the Indian-subcontinent, conquering indigenous populations as they traveled. These conquests are held to have facilitated the importation of

Aryan values, including a language, Sanskrit, religion, and a social stratification system based upon a three-class hierarchy: priests, warriors, and commoners (Mohyuddin, 2000). A biological component (genes) can also be an indicator of this interaction.

Language: Linguistics can also be used to trace the cultural influences and interactions of a group. Shina is a language assigned to the Dardic-branch (Fussman, 2001) of the Indo-Aryan language family (Bashir, 2007). Fussman (2001) claims that languages within Pakistan today are derived from languages introduced by invaders around 1500 B.C. who spoke Indo-European languages. These invaders allegedly called themselves Arya, translating to ―nobles,‖ hence the reference to ―Aryan‖ in literature (Fussman, 2001). While the introduction of Indo-European

21 languages into the region has a general antiquity, the following accounts of the linguistics of the

Yashkun have no associated antiquity provided by the researchers.

Shina is the common language spoken by both the Yashkun and the Shina, as well as the dominant language spoken within the Hunza and Nagar valleys. Shina is spoken within the entire

Astore Valley (Fussman, 2001). It has been suggested that the Yashkun represent an earlier, perhaps indigenous, population that shared the same language and culture as the Burushaski

(Lorimer, 1929), while the Shina were an immigrant group that invaded and conquered the

Yashkun (Lorimer, 1929).

A proposed scenario for the Shina invasion is described by Dani (2001). The Shina and

Tirahi are believed to have interacted based upon linguistics. The Tirahi resided within northwestern Pakistan and were subsequently assimilated into the Pathan tribes. Tirahi and Shina would have separated during retreat from invading Pathan tribes (Dani, 2001). It is possible that this was the scenario that drove the Shina north, leading to the assimilation of the Yashkun and isolation of the still-Burushaski-speaking Yashkun (who subsequently became known as the

Burusho).

Durand (1899) proposes a similar succession. Durand suggests that Dards migrated from the Punjab north through the Indus Valley, either overtaking the native populations, or driving them into the isolation of the surrounding hills. Durand further speculates that the first Dardic wave was composed of the Yashkun, and the Shina represent the second. This two-wave scenario is supported by language distribution. Burushaski is spoken in the Hunza, Nager, and Yasin

Valleys; these regions being mostly inaccessible. By contrast, Shina is spoken in Gilgit, Astore,

Punyal, and Ghizr Valleys. Additionally, when looking at their population distribution, the

Yashkun increase in proportion of the total population along a northern-directed cline such that

22 the Yashkun account for only 4% of the population in the lower Indus Valley near the plains of the Punjab, 78% in Astore, 60% in Nager, and 80% in Hunza. As expected from Durand‘s migration hypothesis, the Shina comprise a decreasing proportion of the population along this same cline, such that the Shina comprise 95% of the population at the lower Indus valley, 35% in

Gilgit, 20% in Nager, and only 5% in Hunza (Durand, 1899; Dani, 2001).

Further linguistic evidence that the proposed scenario was a more recent occurrence is seen through Buddruss‘ (1985) study of the similarity between the phonological systems of the unrelated languages of Gilgit: Shina and Burushaski. Buddruss suggests that the common syntactic constructions and mutual borrowing of words is an indication that Shina and

Burushaski have been in contact for centuries, making the linguistic exchange a matter of a localized and rather recent event.

While Shina is the predominant language of the Yashkun of Astore, Burushaski is spoken by the Yashkun and Burusho of Hunza. Hunza is a subdivision of the Gilgit District, approximately 150 kilometers north of Astore. The Yashkun represent the majority population within Kanjut, or Hunza proper (Dani, 2001). Burushaski is interesting in that it is an isolated language from non-Dardic origins spoken by some Yashkun and by the Burusho. Burushaski remains unwritten and is spoken by more than 40,000 people (Dani, 2001). Dani (2001) posits that the first Burushaski speakers came from Inner Asia or from India due to an absence of

Turkish and lack of Indo-Aryan loan-words within present-day Burushaski. Seeing as, linguistically, the Yashkun have possible links to both east and west origins (Aryan and Asian), it is beneficial to look towards biological methods to determine Yashkun origins. The method chosen for this study is odontometrics.

Chapter 2: Peopling of South Asia

Aryan Invasion Model

Figure 1. Map depicting Aryan Invasion Model.

Historically, investigation of the history of South Asia necessarily involved examination of a variety of texts including those from Alexander‘s trek through northern India as well as such

Indian texts as the Vedas, Ramayana, and Arthashastra (McIntosh, 2008: 27). One significant finding from the study of these texts was made by Sir William Jones, who recognized that the

Sanskrit language of the early texts of India were linguistically similar to texts from Iran (the

Avesta), as well as to some within Europe (primarily Greek and Latin, as well as Celtic and

Germanic languages). This observation founded the discovery of the Indo-European language

24 family, which provides the basis for such theories as the Aryan Invasion Model (see Fig. 1) for the peopling of South Asia (McIntosh, 2008).

While Indo-European languages represent the majority of speakers within South Asia,

Dravidian languages (within southern India and among the Brahui of Baluchistan), Austro-

Asiatic languages (tribal groups within India and Southeast Asia), Tibeto-Burman languages (in the Himalayas and in the Naga Hills), as well as language isolates such as Burushaski (within the western Karakoram) are also found (McIntosh, 2008: 42). Southworth (1979) proposed that the

Indus Valley was the region where contact between speakers of Dravidian and Indo-Aryan languages came into contact based upon the linguistics developed from studying the Rgveda. For example, Southworth claims that place names and other core vocabulary words that are non- cultural indicate antiquity of contact between the languages and finds such examples in Marathi, an Indo-Aryan language spoken in Maharastra, displaying up to 5% of words with a Dravidian origin. Based upon the timeline of the origins of the Rgveda and the commonality in languages,

Southworth presents the case for an eastward expansion into the Deccan Plateau from the Indus

Valley Region.

Proponents of the Aryan Invasion Model claim that population movements across South and Central Asia were the result of an invasion. There are competing routes for the migration.

Sarianidi (1999) proposes that the populations originated from eastern Anatolia and northern

Syria and migrated eastward into western Iran near Lake Urmia, before subsequently spreading eastward to southern Turkmenistan, then Bactria and Margiana before heading south toward

India. This route of migration proposed by Sarianidi (1999) can also be considered to support one version (Renfrew‘s) of the Early Entrance Model (see Early Entrance Model). The second proposed route calls for an eastward migration beginning from the Pontic Steppe, located just

25 north of the Black Sea in southern Ukraine, to south-central Asia towards Bactria and Margiana before heading south through the Helmand Valley of Afghanistan and through the Hindu Kush passes into the Indus Valley and beyond into the Upper Doab region of northern India (Parpola,

1988).

This migrating population, often identified with the Andronovo Culture (Kuzmina, 1997), either took part in (Sarianidi, 1999), or exerted ―elite dominance‖ over (Parpola, 1988; but see

Mallory, 1998) the urban centers of the Bactrian-Margianan Archaeological Complex (BMAC).

The earliest evidence of the BMAC civilization dates between the 3rd and 2nd millennium B.C. and is thought to have centered in Bactria and Margiana (eastern Turkmenia). The archaeological evidence consists of seals and glyptics, monumental architecture, ceramics, art, and metals including gold, silver, bronze, and copper. Architecture is typically composed of mud brick and included fortifications such as the gates and buttresses at Gonur Depe.

The cause of migration has been attributed to climate change causing aridization of the previously cultivable land. The collapse of farming is noted in the archaeological record by the decrease in eastern Anatolian and Iranian habitation sites during this period (Kohl, 1996;

Sarianidi, 1999). However, there are counterarguments for the Aryan Invasion Theory; mainly questioning chronology. While there is linguistic evidence for this theory, supported by the presence of Indo-European languages within the Greater Indus region, there is a lack of invasions within the Indus region reported in the Vedic literature. Parpola (1995) instead suggests that the migration observed within the archaeological is a result of gradual emigration rather than the invasion purported by Sarianidi (1999). It is important to note that much of this theory is based upon the material cultural remains recovered from BMAC urban centers.

Commonality of artifacts is not necessarily correlated with the biology of the population

(Hemphill, 1999). In other words, similar technologies do not directly indicate manufacture by the same biological population, as suggested by the Aryan Invasion Theory.

Long-Standing Continuity Model

Proponents of the Long-Standing Continuity Model assert that South Asia represents a region without any major population movements, either within the subcontinent or from outside, over the last 60,000 years (Kennedy et al., 1984). Due to such isolation, the expected patterning of biological affinities should represent isolation-by-distance (Sokal and Wartenberg, 1983) indicative of populations undergoing genetic drift due to small population sizes and limited access to potential mates. Consequently, phenetic affinities should be greatest among populations that are closest both temporally and geographically. Therefore, the Yashkun should be most similar to other groups that are closest to them both regionally and temporally.

The first major proponents for this model are Kennedy and coworkers (1984) who evaluated cranial metric variation from human remains recovered from 15 prehistoric South

Asian sites. This study not only confirms the heterogeneity of South Asian populations, with the principal component analysis yielding nine factors, representing 99% of total variance, but

Kennedy and coworkers (1984) claim that the patterning of phenetic affinities derived from the analysis suggest an isolation-by-distance effect due to the action of long-standing genetic drift.

Kennedy and coworkers (1984) claim that the positioning of samples along the first principal component reflect geography, in which the most northerly samples from Himalayan Kashmir are positioned at one end of this axis, samples from Sri Lanka are found on the opposite end (a north-south distribution), while groups located in the peninsular India and the Indus Valley of

Pakistan are positioned in the middle. However, there are many samples whose position along

27 the Component 1 does not correspond to the claimed north-south relationship. These include the southern peninsular Indian sites of Adittanular, Tekkalakota, and Brahmagiri are all located in the northern segment of the axis and do not depict any affinities towards each other despite their geographic proximity.

Kennedy and coworkers (1984) claim that the second principal component shows affinities of groups by temporal period, in which the first cluster is represented by hunter- gatherer samples from the Upper Paleolithic, the second consists of agricultural communities, while the third is composed of a later period of hunter-gatherers. While Kennedy and coworkers

(1984) suggest that these affinities are the result of long-standing heterogeneity across the populations, it is also possible that these aggregates are actually a consequence of the mechanical forces associated with differences in premasticatory food preparation. The economically-based aggregates are divided not only by temporal period, but by differences in diet and food preparation techniques. The difference between a hunter-gatherer lifestyle and the more processed agricultural diets has effects on the shape of the cranium due to the difference in mechanical exercise of the jaw (Pinhasi et al., 2008). Therefore, the phenetic affinities found along component 2 may not be correlated to biological distances, but are mere consequences of differences in diet and the premasticatory techniques used to consume there different diets.

Despite the problems with using craniometrics with samples that both pre-date and post- date agriculture, other lines of study have also neglected to provide evidence for the Long-

Standing Continuity Model. Hemphill and coworkers (1992) utilized odontometrics to analyze phenetic among five ethnic groups from peninsular India. Results show that the differential apportionment of tooth size is a successful method for distinguishing these groups and initially provides evidence for the Long-Standing Continuity Model. The strongest affinities occur

28 geographically, especially amongst groups that are caste-members and speak languages classified in the same language family. Non-caste Chenchus were found to be the most biologically distant (Hemphill et al., 1992). However, subsequent research by Hemphill (2013) suggests that the urban samples from Poona (MHR) and Calcutta (BNG) used in the 1992 study are too mixed of castes to be of use in reconstructing population histories.

Another study that supports long-standing continuity was performed by Majumder

(1998). Majumder compared various anthropometric and genetic data of Indian samples to examine the differences and affinities of those groups. The main goal of the study is to test the biological affinities associated with geographical, socio-cultural, and linguistic correlations

(Majumder, 1998). Majumder found that Indian populations are indeed distinct, and that closest affinities are found geographically (southern vs. northern populations) despite socio-cultural affiliations. Subsequent research by Majumder and coworkers utilizing 58 DNA markers of ethnically diverse populations within India concludes that historical gene flow has affected the genetic histories of populations so greatly that geographical and sociocultural affinities are difficult to ascertain (Basu et al., 2003). While a clear congruence for providing evidence for

Long-Standing Continuity has not been established, the model will be tested in this study.

Early Entrance Model

Support for the Early Entrance Model comes from linguistic data which indicates that at least two significant population movements may have played significant roles in the peopling of the Indian subcontinent (Lukacs & Hemphill 1993; Hemphill et al. 1991). The initial movement is associated with the introduction of proto-Dravidian languages by Proto-Elamo-Dravidian speakers from southwestern Iran, which likely occurred at some point between 6000 and 4500

B.C. Two possible scenarios have been proposed to account for the migration. The first scenario describes a westward migration of Dravidian-speakers into South Asia whose penetration was limited to that region found west of the Indus River (Quintana-Merci et al., 2004). A second migration would have followed during the mid-2nd millennium B.C. consisting of proto-

Dravidian speakers entering further into peninsular India, perhaps due to the entry of Indo-

European-speaking populations into the Indus Valley from Central Asia (Aryan Invasion Model)

(see Fig. 2). The second scenario suggests that the major migration consisted of the proto-

Dravidian speakers into both the Indus Valley and peninsular India. No significant secondary migration consisting of Indo-Aryan speakers would have occurred (Hemphill, 1991; Hemphill et al., 1992; Southworth, 1995).

Linguistic evidence in support of the Early Entrance Model suggests that modern

Dravidian languages are descendants of the proto-Elamo-Dravidian languages brought into the

Indian subcontinent from the Elamitic region of southwestern Iran. McAlpin (1974) examined cognates of Elamite with Dravidian languages. The similar cognates provide evidence for a common Proto-Elamo-Dravidian phonology, which further suggests an early entrance of populations from the Persian Gulf (speaking Elamitic languages) to South Asia, before the derivation of Dravidian families from Elamatic.

Southworth (1995) further posits that the introduction of Indo-Aryan languages into

Dravidian languages during the 2nd millennium B.C. based upon the analysis of speech communities. Southworth (1995) suggests that the speech communities display an Indo-Aryan language influence within peninsular India that would have merged into a singular cultural complex by the late 2nd and early 1st millennium B.C. (Camp, 2013). Additional linguistic studies provide further support of the influence of Indo-Aryan languages during this temporal period,

Figure 2. Map depiction of Early Entrance Model. but also suggest the presence of an unidentified ―Language X‖ or even Mundic languages were not only spoken within the Indus Valley, but also throughout a far wider region of North India than they are found today (Witzel, 1995; Parpola, 1988).

Additional support is provided by archaeological evidence. Moore and coworkers (1994) examined subsistence patterns through archaeological, botanical, and osteological data from the

BMAC urban center of Gonur Depe, located in eastern Turkmenistan. The main subsistence pattern identified is nomadic pastoralism, where the inhabitants were dependent upon species domesticated in the Near East. However, this subsistence pattern would be difficult to sustain an urban center like Gonur depe. With such a sedentary population, an agricultural base would also

31 have been necessary. There is more recent evidence of agricultural production of Near Eastern cultigens like wheat (Zeder, 2011).

Lamberg-Karlovsky (1994) also suggests the Early Entrance Model to account for the development of the BMAC by 2000 B.C. by linking the material culture at Altyn depe in

Turkmenistan to the earlier materials within Margiana. This link is based on similar archaeological sequencing throughout Central Asia, Baluchistan, and the Iranian Plateau as identified through similar technologies, such as subsistence patterns (found during the late 7th millennium B.C. at Djeitun), as well as metallurgy and pottery (during the 4th and 5th millennia

B.C.). Lamberg-Karlovsky (1994) argues that this similarity reflects a long-standing continuity of interactions between Near Eastern populations and the inhabitants of the BMAC urban centers of south-central Asia. Francfort (1994) further elaborates this relationship between the BMAC and surrounding areas by describing the relationship of Elamitic language forms and styles to the symbolic systems observed in the BMAC through such artifacts as seals and vases. Francfort

(1994) suggests that the influence of the Elamitic language on the Oxus Civilization‘s mythology is evidence of the cultural influence of southwestern Iranian populations upon the populations of

Bactria and Margiana and perhaps beyond into the Indus Valley, thereby providing additional evidence in support of the Early Entrance Model.

Historic Era Influences Model

Proponents of the Historic Era Influences Model posit that important migratory events have occurred recently, during the historic era. These migrations have added significantly to the ethnic diversity of the region and are supported by the presence of non-South Asian genetic and/or phenetic signatures among ethnic groups found along the northwestern, northern, and

32 northeastern peripheries of South Asia. This model has been posited by a number of studies attempting to recreate the population histories of such ethnic groups residing within Gilgit-

Baltistan and Khyber Pakhtunkhwa as the Kho, Wakhi, Pathans, Swatis, and Chengazis

(Hazara), all of whom are claimed to represent foreign groups into the region due migrations during the historic era (Camp, 2013; Hemphill et al., 2009; O‘Neill and Hemphill, 2009).

Throughout history, contact between South Asian populations has been riddled with plays in political conquest. For example, the Persian Empire (Achaemenid Empire) began its domain in the 5th century B.C. and eventually encompassed the region from the eastern Mediterranean through North Africa in the west, and vast areas of western Asia, including Pakistan, at the eastern periphery. Greek conquest in the 7th Century B.C., led by Alexander the Great overthrew the control of the Achaemenid Empire. Other major conquests in nearby regions at this time include the Mauryan Empire, which expanded across India and the Huns throughout western

South Asia (Fagan, 1996; Willis 2009). Population movements and migrations coinciding with exchanges in political dominance continued throughout history. The migration of indigenous populations into new territories provides the opportunity for genetic admixture as the populations settle into new locations. This exchange in gene flow may have great effects upon the phenetic signatures of the ethnic groups used for analysis within the region.

Chapter 3: General Research Questions.

The biological affinities of the Yashkuns will be analyzed based upon the models in Chapter

2: Population Models for the Peopling of South Asia for the hypotheses seeking to account for the genetic diversity observed among human populations residing within South Asia.

1) Are the Yashkun descendants of Indo-Aryan-speaking populations who migrated from

Central Asia to the Hindu Kush highlands during the 2nd millennium B.C.?

If the Yashkun are descendants of these prehistoric Central Asian populations, then the

Aryan Invasion Model suggests that the Yashkun should show affinities to the samples from southern Central Asia. Consequently, one should expect that the Yashkun possess closer affinities to prehistoric Central Asian populations—their alleged ancestors—than to modern samples that are closer geographically. Further, if this model is true then the Yashkun ought to possess more distant affinities with prehistoric samples from the Indus Valley and peninsular

India since they would not bear an ancestral relationship to the Yashkun.

2) Are the Yashkun descendants of a long-standing isolated, indigenous population

residing within the Hindu Kush highlands?

If Dani (2001) is correct, that the Yashkun are the descendants of an indigenous population of long-standing residence within the Hindu Kush highlands, then this would reflect the Long-

Standing Continuity Model. The Yashkun should share closest affinities to other ethnic groups that are closest to them, both geographically and temporally, reflecting a pattern of isolation-by- distance. Secondary affinities ought to be with the Yashkun‘s ancestors located within the Indus

Valley. Distant affinities should also be observed among Indo-Aryan-speaking groups within northern India due to the common language family. The Yashkun should not exhibit any biological affinities to Dravidian-speaking ethnic groups of southeastern peninsular India. There

34 should be a divergence to populations from prehistoric populations, as well as peninsular India.

These results would support the Long-Standing Isolation Model.

3) Are the Yashkun descendants of a population associated with the introduction of Proto-Elamo-Dravidian languages into South Asia between 6,000 and 4,500 B.C.?

If the Early Entrance Model is supported, then the Yashkun should show distant but equal affinities with populations from prehistoric Central Asia and populations within the Indus Valley after 4,500 B.C. These affinities would demonstrate the migration of Proto-Elamo-Dravidian languages through South Asia. Furthermore, if the Early Entrance model is supported, distant affinities will be observed amongst Dravidian-speaking populations, prehistoric and modern, who are also descendants of the same proto-Elamo-Dravidian-speaking populations who migrated into the region. With the Early Entrance Model, affinities among the Dravidian- speaking populations and prehistoric populations within the Indus Valley should also be observed.

4) Are the Yashkun descendants of populations that migrated to northwestern South Asia in the historic era?

If the Historic Era Influences Model is supported, then members of contemporary populations found within northwestern periphery of South Asia are the result of recent and active migrations. This would be evident through the Yashkun and other ethnic groups occupying the northwestern borderlands of South Asia samples being marked by divergent affinities from prehistoric samples of the Indus and peninsular India. Since it may be that these contemporary ethnic groups living in the northwestern periphery of South Asia have different and distinct source populations, there may be a distinct absence of close affinities among these ethnic groups

35 despite their temporal and geographic proximity. It is also possible that the Yashkun will not share any affinities, marking the population as a recent migrant into the region.

Chapter 4: Odontometric Heritability

Odontogenesis

The importance of the determination of the structure and development of teeth ultimately being the result of genetics is pertinent to utilizing odontometrics to study biological distances.

The process of tooth development is odontogenesis, which begins in the embryo. The interaction of the epithelium and the ectomesenchyme begin odontogenesis. The ectomesenchyme is a type of connective tissue derived from the neural crest that creates dentine and pulp. The cementum and periodontal fibers are derived from the mesoderm (Scott and Turner 1997:75). There are six morphological stages (as opposed to physiological) associated with tooth growth: 1) dental lamina; 2) bud stage; 3) cap stage; 4) early bell stage; 5) late bell stage; and 6) enamel and dentine matrix formation (Scott and Turner 1997: 76). Specifics on what each stage entails can be found within numerous sources in oral development (see Scott and Turner, 1997; Bhaskar,

1976; Ten Kate, 1994). An outline of odontogenesis pertaining to morphology as it relates to odontometrics will be provided here.

Deciduous teeth and most permanent teeth are developed in utero. Specifically, morphology of these teeth, including the crown shape and enamel calcification, is completely developed prior to eruption. The first sign of teeth is produced during the second month of development in utero. The epithelium develops as two horseshoe-shape bands within what will be the mandible and maxilla. The individual bands are referred to as primary epithelial bands.

The dental lamina and the vestibular lamina develop within this band; with the dental lamina forming first and the vestibular lamina developing subsequently and adjacent to the dental lamina. Ten laminae appear along the jaw where the deciduous tooth germs will develop. Within

37 the epithileal bands, tooth development is initiated with the thickening of placodes. Later, between the fifth and tenth month of development in utero, laminae will continue to develop lingually to the original structure for permanent tooth germs. The development of tooth germs for the permanent molars that lack a preceding deciduous tooth germ (M2 and M3, if present) extends until the fourth or fifth year of age (Scott and Turner, 1997: 76; Bhussry, 1976). The importance of placodes in development is seen with a reduction corresponding to reduced or missing teeth and an increase is correlated with larger or supernumerary teeth (Nanci 2008:72).

The anatomy of development will be outlined before describing the subsequent stages in tooth development. The enamel organ remains separated from the dental papilla by a basement membrane. Superior to this membrane is the inner enamel epithelium. The outer enamel epithelium is immediately superior to the enamel organ. Between the inner and outer epithelia are the stratum intermedium and stellate reticulum, which are responsible for amelogenesis and dentinogenesis, respectively. The dental papilla is connected to the tooth germ by the basement membrane and dental sac. The dental sac encloses the tooth germ and is connected at the dental papilla.

Tooth development can be described in four stages: bud, cap, early bell and late bell. The bud stage refers to the epithelial cells‘ movement into the ectomesenchyme from the dental lamina. With the increase in cell movement, the resultant outgrowth is known as the dental papilla. Together the condensed dental papilla extending out of the ectomesenchyme is referred to as the dental organ. The cap stage occurs as the dental papilla continues to grow out of the dental lamina. The cap stage is where the first morphological differences in patterning occur.

From this stage, the condensed ectomesenchymal cells are recognizable as the dental papilla. The dental papilla will generate dentin and pulp. The final stage, the bell stage, is recognized when

38 the tooth crown has been morphodifferentiated via the crown (consisting of ameloblasts and odontoblasts) displaying its final physical appearance (Nanci, 2008; White et al., 2012; Scott and

Turner, 1997). The bell stage is separated into the early bell stage and the late bell stage. The early bell stage is characterized by the development of the shape of the tooth crown. Mitosis, in addition to the dental papilla, drives the folding that occurs within the inner enamel epithelium which creates the major cusps of the tooth crown (Scott and Turner, 1997:78).

More specifically than mitosis, enamel knots have an important function in cusp and tooth crown formation. Enamel knots are the grouped epithelial cells observed histologically beginning in the cap stage of incisor and molar germs (Nanci, 2008: 82, Matalova et al., 2005).

Enamel knots play a function in molecule signaling for gene expression; thereby, playing a role the morphology of teeth (see Nanci, 2008 and Thesleff and coworkers, 1995 for a description of the specific signaling molecules expressed within the enamel knots at varying stages of tooth development relative to crown pattern formation). The initial formation of enamel knots at the cap stage is referred to as primary enamel knots. These primary enamel knots begin the molecular signaling associated with tooth cusp morphogenesis and growth within both incisor and molar germs. Secondary enamel knots develop from a separate cluster of epithelial cells during the late cap stage- early bell stage and only within molar germs (Matalova et al., 2005).

Continuing with stages in tooth development, the final stage, the late bell stage, is characterized by the development of hard tissues within the tooth crown, specifically with enamel and dentin. Enamel is permanent and only develops during this stage. During life, the only changes occur through wear or decay, which are physical and chemical processes, respectively. Dentin is developed during both tooth formation, where it is referred to as primary dentin, and during root maturation where it is referred to as secondary dentin (White et al., 2012:

107). Root formation begins after the tooth crown has been developed.

Like all mammals, humans display heterodonty- teeth that are distinguished between different patterns or classes. These patterns include incisiform, caniniform, and molariform.

There are three competing models that describe tooth patterns and morphology: dental morphogenic field theory, dental clone theory, and the odontogenic homeobox code hypothesis.

The dental morphogenic field theory was initially proposed by Butler (1939), who suggested that tooth form is dependent upon location specific to morphogenic fields: incisor, canine, and molar.

In 1945, Dahlberg applied this concept to human dentition. This model suggests that tooth shape is the result of ectomesenchymal cells receiving positional information within the dental arch.

With such a scenario, each tooth is pluripotent; that is, capable of differentiating into any morphogenic field. The final form that is determined is based upon the position of the tooth germ within the dental arch (Butler, 1963). Butler further suggested that the mechanism for determination of the morphology of the tooth is controlled by ‗pattern genes,‘ which affect the tooth germ directly. The morphology of the tooth is determined based upon a hierarchy of variables including the order within the dental arch, the tooth class, type within the class, and cuspal morphology (Scott and Turner, 1997: 82). This theory has been supported by Hlusko and

Mahaney (2009), whose study of Papio hamadryas found tooth development to be based upon morphogenetic distinction, as well as a genetic difference between premolars and molars. Hlusko and Mahaney (2009) identified distinct genetic correlations, referred to as modules, between incisors, premolars, and molars through the quantitative genetic analysis of maxillary tooth size variation. Phenotypic data (odontometrics) was collected and compared to the genetic data collected from a captive colony. The study revealed genetic independence between incisors and molars. Furthermore, while premolars do have overlapping size variation with molar size, they

40 are not identical, and therefore have a distinct modularity. This incomplete pleiotropy supports the dental morphogenic field theory in that each class is independent.

Osborn (1978) proposed the dental clone model, which suggests that rather than being based on position in the dental arcade, tooth shape is determined by a single progenitor for each tooth family on each arcade and side. Osborn postulated that there are three primordia from which the crowns develop in both classes and gradients: the anterior (for deciduous and permanent incisors), the canine (for deciduous and permanent canines), and posterior (for deciduous molars and permanent premolars and molars). It appears that tooth shape formation is determined by the ectomesenchymal cells in themselves rather than being equipotent (White et al., 2012:109). The progenitor produces clones that are the most prototypical. Each subsequent tooth is reduced in its ability to resemble the prototype (White et al., 2012: 109). This is because the mesenchyme undergoes more mitotic divisions the further the clone teeth are from the progenitor, causing the gradation seen in subsequent teeth within a class. As such, teeth are representative of a meristic series within which the individual members are metameres exhibiting duplication with some variation (Scott and Turner, 1997: 81; Weiss, 1990). While there are distinct morphological classes which exclude a continuous gradient in variation, the human dentition nevertheless exhibits morphological gradation in that teeth that are adjacent are more similar. For example, although not seen across all population in the mandibular dentition, canines are often incisiform and premolars are often caniniform (Scott and Turner, 1997: 81).

The odontogenic homeobox code hypothesis (HHE) is based upon spatial gene expression. Proponents of the HHE hypothesis claim that development is time-dependent and based upon signaling molecules to the ectomesenchyme through homeodomains within specific regions of the dental arch (Thomas and Sharpe, 1998; Cobourne and Sharp, 2010, White et al.,

2012). Development and morphology is dependent upon specific homeobox gene combinations within specific regions of the epithelium. In other words, the genes determine morphology before the physical development takes place (Rizk et al., 2013: 140). Msx-1 and Msx-2 are two homeobox genes that initiate development within the distal and midline ectomesenchyme for incisors and canines. Dlx-1 and Dlx-2 initiate tooth germs within the ectomesenchyme for multicuspid teeth (Nanci, 2012: 76-77; Rizk et al., 2013: 140).

The three models are not mutually exclusive. The mechanisms that drive odontogenesis are driven by the location, timing of development, and genetics of the tooth. Furthermore, teeth within a specific family or patterning are influenced by the same genes. There is a difference in genes between these categories. Teeth that are adjacent to a separate category are more alike than teeth that are further from the distinction of tooth type.

Heritability

A brief introduction to heritability and its estimation is presented to provide a general background into the process of determining the extent of genetic and environmental variance affecting the manifestation of permanent tooth size. Equations estimating the amount of heritability are limited in application to tooth crown sizes. These estimates are most accurate when the genetic variation is additive. Tooth crown size has been determined to be polygenic

(see Dental Genetics below). Therefore, such complex genetic factors cannot be accurately calculated from heritability estimate equations. Regardless, having an idea of how heritability is calculated gives the reader an idea of how the phenotype can be utilized in lieu of direct information on the genotype, and how individual variation is interpreted at the population level.

Heritability is the proportion of genetic variance to total variance. Heritability describes the proportion of variance at the population level, including environmental factors affecting the

42 population. Heritability can be quantified from multiple equations. Broad-sense heritability refers to the relationship of genotype to phenotype. The ratio for determining broad-sense heritability is: VG/VP, where heritability is the result of the ratio of genetic variance (VG) to phenotypic variance (VP ). Narrow-sense heritability looks at the ratio of additive genetic variance to phenotypic variance, as opposed to total genetic variance in the broad-sense heritability equation.

Hence, narrow-sense heritability is found through the following ratio: VA / VP, where heritability is considered through the relationship of total additive genetic variance to total phenotypic variance. Additive genetic variation is an aspect of polygenism and it occurs when alleles contribute a single fixed value to a quantitative phenotype. Total genetic variance accounts for multiple interactions. Estimating heritability using the given equations allows the researcher to observe heritability at the population and generation level. The accuracy of the application of such equations is dependent upon the representativeness of the sample to the population or generation from which it was drawn (Dempsey et al., 1999).

Total genetic variation is the combination of three forms of variance: additive, dominance, and interaction genetic variation. Therefore, the total phenotypic variation observed in an individual (including odontometric variation), is the combination of total genetic variance, the effects of environmental factors, and the interaction between genetic and environmental factors. This is expressed through VP = VG+ VE ; where VP is phenotypic variation, VG is genetic variance, and VE; is environmental variance. The genetic variance can be expressed in terms of the additive effects of alleles (VA ), dominance effects between alleles at the same locus (VD) and epistatic interactions between loci (VI ) (Dempsey et al., 1999: 9). Additionally, the environmental variance may be considered as the contribution of both common environment

(VC) and individual environment (VE ). Common environment is composed of the shared

43 environment, or family environment; while the individual environment consists of the environment specific or random to whichever individual is under consideration (Dempsey et al.,

1999). When examining the ratios for heritability, the researcher is essentially looking at the proportion of phenotypic variance that is caused by genetic factors and environmental factors.

Heritability allows the researcher to quantify variation that affects phenotype, thus allowing comparisons at the population level to address questions such as population histories without looking specifically at genetic differences. Heritability in dental development is essential for this study and the validity of which will be further discussed in the section on Dental Genetics below.

Dental Genetics

The principles of dental genetics began with Bateson‘s (1894) concept of teeth as developing within a meristic series; specifically with the idea that individual teeth—much like individual digits or vertebrae—ought to be evaluated as individual members within a unit. A meristic series suggests that teeth are developed by the same genetic message being repeated serially (Kieser, 1991). However, other research made an opposing hypothesis that suggested differences within teeth are not simply morphogenetic, but functional (Scott, 1892; Wortman,

1886).

Heritability of tooth crown size in permanent dentition has been found to have a range of estimates that differ by study. These estimates range from 21% (Townsend et al., 1986) to 90 %

(Garn et al., 1965). However, Dempsey and coworkers (1999) report that most studies generate a heritability estimate over 60%. Furthermore, a number of these studies have found that genetic variation plays a statistically significant role in tooth crown size (Lundstrӧm, 1948; Kraus et al.,

1959; Garn et al., 1965; Potter and Nance, 1976; Rebich and Markovic, 1976: as reported by

Dempsey et al., 1999).

The effects of genetics and environment on dental development remain a current topic under debate. For example, Townsend and coworkers (2006) conducted an analysis on 600 pairs of Australian twins to identify heritability in a number of dental traits, including dental crown dimensions. Using structural equation modeling, they found that genetic effects on phenotype variation are inconsistent among dental traits. Structural equation modeling allows for identifying the influence of both genetics and environment through examining variation within, as well as the covariation between, the variables. This method allows for phenotypic variation to be evaluated not only by a single genetic variable, but also as a result of additive genetic variation. Townsend and coworkers conclude that odontogenesis is influenced by epigenesis and that individual genes can be identified with a genome-scanning approach.

Approximately 200 genes involved in odontogenesis have been identified (Sperber,

2004). Furthermore, a homeodomain code of transcription factors have also been identified in creating gross tooth shape (thereby yielding the class-level differentiation of incisors, canines, premolars, and molars). These transcription factors include Msx genes, D1x family members,

Pax 9, Lhx genes, and Barx1 (Maas and Bei, 1997; Francis-West et al., 1998; Jung et al., 2003;

Sperber, 2004). While the effects of these factors are still being examined, there has been some research that has illuminated some these factor‘s roles (see Sperber, 2004). While these genes control tooth formation, teeth are nevertheless subject to environmental influences (Sperber,

2004; Townsend et al., 2006).

While genetics have been identified as a significant contributing factor in odontogenesis, the specific amount of genetic control is still subject to study. A survey of previous studies will be presented. Osborne and coworkers (1958) conducted one such twin study utilizing mesiodistal measurements of the six maxillary and six mandibular permanent anterior teeth to test for genetic

45 variability through the comparison of mean intrapair variance of monozygotic twin pairs to dizygotic twin pairs. Osborne and coworkers (1958), along with Lundstrom (1948) and Korkhaus

(1930), found a strong genetic factor in variability of mesiodistal dimensions; especially among incisors. Additionally, Osborne and coworkers (1958) applied cross-twin values (comparing differences of tooth size on genetically similar individuals) and found some evidence of genetic control of general tooth size for lateral incisors and canines. Dempsey and coworkers (1999) analyzed tooth crown size among 295 pairs of twins. Buccolingual and mesiodistal measurements were taken for all permanent teeth. This study also concluded that statistically significant genetic factors (both additive and non-additive) are behind the determination of tooth crown size. Environmental variance was also found to be significant for the maxillary first molars.

Historically, tooth size has been considered the result of genetic control in dentistry

(Korkhaus, 1930; Lunstrom, 1948) and odontometrics (Dahlberg 1945; Moorrees et al., 1957).

However, with the relatively recent accumulation of knowledge in developmental genetics, a greater understanding of the relationship of genetics and odontogenesis has been established.

The role of genetics in odontogenesis is expressed significantly when observing the role of primary and secondary enamel knots in the generation of tooth cusps. The differential molecular signaling can be attributed to morphology and even tooth class (Jernvall and Thesleff, 2000).

Variation in cusp patterns has been attributed by the signals to homeobox genes initiated by the enamel knots. Studies on these molecular signals in mice and organ cultures have paved the process for studying tooth development in humans. For example, Keranen and coworkers (1998) identified specific genes and signal molecules within secondary enamel knots in mice molars that code for particular tooth shapes. Research on genes and molecular signaling within enamel knots

46 in both rodents and humans continues to support the correlation to tooth morphogenesis

(Kapadia et al., 2007, Lin et al., 2007, Miyado et al., 2007). The significance of genetic control of tooth shape is evident in that it is not just a process in humans, but across mammals.

Therefore, the modularity observed in teeth can be extrapolated to the ability of a trait undergoing phenotypic evolution (Stock, 2001). This provides the basis for observing and comparing phenotypes at a population-level.

Size Differences at the Population Level

Tooth size has been assessed at the population level. Phenotypic variation is a visible marker of genotype. Since tooth size variation is directly observable, measuring differences in phenotype has been a method used to identify gene flow and genetic drift among divergent populations (Sperber, 2004). To utilize odontometrics, it is important to identify the cause of variation in individuals. While the genetic basis of tooth morphology and size has been supported, correlations in variance components have also been studied. Harris (2003) tested seven potential causes for variation in tooth size, including race, sex, arcade, tooth class, tooth position, and a residual term. The majority of variance (82.8%) was accounted for by tooth class.

The remaining components make up the rest of the variance. While tooth class metrics vary, can the variation be accounted for at the population level?

A number of studies have demonstrated that diversity can be observed within regional and larger geographic populations (Lewontin, 1972; Latter, 1980; Barbujani et al., 1997; Jorde et al., 2000). For example, Goose (1963) compared mesiodistal and buccolingual diameters among

English males to males of other samples including: Eskimos (Pedersen, 1949), Javanese

(Mijsberg, 1931), and Lapps (Selmer-Olsen 1949). Goose notes that the greatest variance occurs among the third molars. For example, comparing English and Eskimos in a t-test results in

47 t=3.792, P < 0.001 (Goose, 1963: 141). The second significant variance that Goose describes is

P the buccolingual diameters of P3 to P4 by the index . Goose concludes that it may be P possible to use odontometrics to distinguish differences between ethnic groups.

Some examples of such studies include Hanihara and Ishida (2005), who tested metric dental variation using 72 modern human populations utilizing mesiodistal and buccolingual crown diameters. The study made a number of observations, including that dental variation found among members of the same geographic region is consistent with the variation observed from genetic and craniometric data. Another study utilizing odontometrics was conducted by

Harris and Lease (2005). This study, based on mesiodistal crown dimensions of deciduous teeth, compared 80 samples used in published studies to establish patterning of variation between populations, temporal period, and sex. Additional examples of odontometrics and population- level studies are provided in Chapter 5 below.

Chapter 5: Previous Studies of Affinities among South Asian Ethnic Groups

The peopling of South Asia is an issue that has long been debated. Numerous methodologies have been utilized to elucidate the biological affinities within the region including linguistics, archaeology, and genetic studies. A review of research on both modern and prehistoric populations will be presented in this chapter.

Modern Populations

A number of studies have focused on the biological affinities of modern populations in

South Asia. The Centre for South Asian Dental Research (CSADR) has focused research in this region in particular. For example, Hemphill (2009) examined the genetic affinities of the Swatis from Mansehra District of Khyber Pakhtunkhwa Province, Pakistan. Previously, origins had been attributed to either Afghan populations, populations indigenous to the Hindu Kush highlands, or to populations from peninsular India. Results from both dental morphology and odontometrics reveal affinities with modern ethnic groups from the Hindu Kush highlands. However, these affinities are more distant than that observed between all of the other highland samples, except

Khowars and the inhabitants of Madak Lasht, who also exhibit rather distant affinities to other inhabitants of the Hindu Kush/ Karakorum highlands, as well as to one another. Such affinities may indicate that the inhabitants of Mansehra District and adjacent districts encompassing the foothills forming the northern boundary of the Indus Valley possess different affinities than those possessed by ethnic groups occupying the Hindu Kush/ Karakorum highlands to their north.

Intriguingly, the Swatis were found to possess even more distant affinities to samples of prehistoric populations from the North Kachi Plain (Mehrgarh), Indus Valley floor (Harappa) and the northern foothills bordering the Indus Valley (Sarai Khola, Timargarha) of Pakistan as well as the Kopet Dagh foothill plain (Altyn depe), Tedjen Oasis (Geoksyur) and the

Surkandarya Valley (Djarkutan, Sapalli Tepe) of southern Central Asia. No affinities were observed between Swatis and ethnic groups from peninsular India.

Hemphill (2011) expanded his studies on the migrations within Central Asia, the Indus

Valley, and India to focus on the inhabitants of Madak lasht. The Madak Lasht are the inhabitants of an isolated village in the south-central region of Chitral District of northern

Pakistan. Hemphill used dental morphology to analyze the biological affinities of the Madak

Lasht in relation to the surrounding region. Hemphill concludes that like the Kho, the inhabitants of Madak Lasht appear to be an isolated population within northern Pakistan. They do not show affinities towards populations from Central Asia or India either. Hemphill concludes that due to the shared similarities with the Swatis (another group within Pakistan, living north of the Indus

Valley along the Himalayan foothills), both groups may have originated from the west in

Afghanistan.

Blaylock (2008) performed a dental morphology analysis on the Kho (Khowar), the numerically dominant ethnic group of Chitral District, Khyber Pakhtunkhwa. Khowar oral traditions claim ancestry from the Kafirs of Nuristan Province, northeastern Afghanistan, located to the southwest of Chitral District and they maintain that they are descendants of Aryan- speaking invaders from Central Asia (see the Aryan Invasions Model below). Results from her analysis do not suggest strong affinities to any of the comparative groups. Blaylock suggests that the closest affinities may be the result of historic population influences from Iran or Afghanistan.

The Kho were also the subjects of a study by Hemphill and coworkers‘ (2007) of examining the biological affinities of the Kho using both dental morphology and odontometrics.

The Kho were compared to both prehistoric and modern population samples throughout South

Asia. Like the morphological trait frequencies studied by Blaylock (2008), odontometrics also

50 depicted affinities towards prehistoric Central Asian populations and the Chalcolithic period population of Mehrgarh. Hemphill and coworkers‘ study also suggests that the Kho represent an isolated population. Ultimately, the Kho are thought to represent a recent immigrant population into the Hindu Kush.

O‘Neill and Hemphill (2009, 2010) and O‘Neill (2012) tested biological affinities of four samples of Wakhi and Shina populations residing in the Karakorum highlands within the Gilgit

Division of Gilgit-Baltistan, Pakistan to samples of contemporary and prehistoric populations throughout Central Asia, India, and Pakistan using odontometrics. The studies do not identify consistent aggregates of highland populations, which also suggest that historic era migrations are likely a greater factor than prehistoric migrations and influence. O‘Neill (2012) argues that despite aggregates forming around geographic and temporal samples of populations, the relationship between the Pakistani highland populations and the other aggregates does not share specific affinities to one another or to other regionally close samples. This suggests that there has been significant population movement throughout recent history (the past 1000 years) and such movements have only been increasing over the past 300 years (O‘Neill, 2012). O‘Neill (2012) concludes that linguistics is an important indicator of biological affinity.

Willis (2010) also utilized odontometrics to test biological affinities of another modern population from the Gilgit Division of Gilgit-Baltistan, the Burusho. Competing oral traditions suggest an ancestry derived either from either the Greek invasion led by Alexander the Great (as claimed in Burusho oral traditions) or from northwestern India, with ancestors fleeing to Pakistan from invaders. Willis compared modern and prehistoric samples from Central Asia, Pakistan and

India. Distant affinities were identified between the Burusho and living Pakistanis, as well as prehistoric Central Asians. The analysis revealed no affinities to either prehistoric Pakistanis or

51 to living ethnic groups from peninsular India. The Burusho speak Burushaski, which is a linguistic isolate with no known origin surrounded by Indo-European languages of varying affiliation (i.e., Dardic, Indo-Iranian, Indo-Aryan). Willis concludes that these results support the contention that Burusho represent a long-standing indigenous population that became increasingly genetically isolated over time—an isolation further reinforced by their linguistic isolation.

Hemphill has extensively researched biological distances of populations within South

Asia utilizing dental morphology. Among these studies, Hemphill (2009) compared the dental morphology of 16 prehistoric and living populations within the current study‘s project area of

Central Asia, India, and the prehistoric Indus Valley. Hemphill describes a discontinuity between populations relating to the Dravidian-speaking populations of southeast India and the Indo-

Aryan-speaking populations. Hemphill argues that these results reflect early population migrations of proto-Elamo-Dravidian-speakers in the fifth millennium BCE followed by a separate, less genetically impacting migration of Indo-Aryan-speaking populations. While linguistic affinities and differences have been proposed as a method for identifying patterns of biological affinity, it has also been suggested that geography is the predominant factor (see

Hemphill, 2007, 2009, 2011; Hemphill et al., 2007; Mohyuddin, 2000; Mansoor, 2003).

Genetic data has also been utilized to analyze biological affinities of contemporary

Pakistani populations. Qamar and coworkers (2002) used Y-chromosome haplogroup frequencies and found that Pakistani groups, despite linguistic differences, were more closely affiliated with each other, followed by other Indo-European-speaking populations. However, variation within the Y-chromosome also reveals clustering within Pakistani populations that allow for specific comparisons due to isolation and genetic drift. While microsatellites can

52 provide information concerning combination in a rapid evolutionary setting (Mansoor, 2003), Y- chromosome studies provide analysis on a portion of the genome that is non-recombining with stable binary markers. When combined with the analysis of microsatellites, Y-chromosome phylogenies can be reconstructed to examine genetic history from the male line (Qamar et al.,

2002).

The Y-haplogroup data was examined using principal components analysis. Qamar and coworkers found that Pakistani ethnic groups cluster most closely with each other, and then with samples from ethnic groups from other parts of South Asia and the Southwest Asia. More distant affinities are seen among Pakistani ethnic groups and ethnic groups from North Africa, Central

Asia, and Europe. These results indicate affinities based upon geographic proximity. This study also does not see a distinction based upon the languages spoken by the Burusho (a linguistic isolate) and Brahuis (attributed to the Dravidian family of languages) relative to geographically adjacent populations. Qamar and coworkers conclude that their results are not atypical of Y- chromosome variation studies, for other such studies also indicate affinities based upon geography rather than language (Rosser et al., 2000; Zerjal et al., 2001). Similar to other studies,

Qamar and coworkers posit that Pakistani populations had contact with populations of both eastern and western Eurasia. However, more biological contact is observed with western

Eurasian populations, and this is reflected by the fact that four of five haplogroups found in

Pakistan (haplogroups 1, 2, 3, and 9) occur with high frequency among western Asian and

European populations, but not among the eastern Eurasian populations of China or Japan (Qamar et al., 2002).

Additional studies analyzing Y-chromosome lineages have attempted to account for the dispersal of languages throughout southwestern Asia. Quintana-Murci and coworkers (2001)

53 claim that Y-chromosomal data accounts for two major migrations, one from southwestern Iran and the other from western and central Asia. Quintana-Murci and coworkers suggest that the first of these migrations resulted in Dravidian and Indo-Iranian language dispersal, which they maintain was associated with the development of agriculture. Although linguists maintain that

Dravidian languages developed in situ within South India, Quintana-Murci and coworkers (2001) suggest the expansion of agriculture from southwestern Iran and the Zagros Mountains was a mechanism for the spread of Dravidian languages eastward, accounting for languages seen in areas of Pakistan and India (Cavalli-Sforza et al., 1994; Renfrew, 1996). This is thought to have occurred between 6,000-5,000 B.P. (Quintana-Murci et al., 2001). A second migration associated with pastoralism in Central Asia (Aryans) occurred around 4,000 B.P. and initiated the dispersal of Indo-European languages throughout western China, Pakistan and north India (Renfrew, 1987,

1996; Cavalli-Sforza, 1988).

A study performed by Quintana-Murci and coworkers (2001) evaluated these hypotheses based upon archaeological and linguistic evidence using genetic data from population samples located within the geographic locations associated with the migration movements. Samples were drawn from ethnic groups located in Iran, Pakistan, and India and were compared to previously analyzed samples from India, Sri Lanka, Southwest Asia, Europe, and Africa. The results from the Y-chromosome haplogroup analysis show high frequencies of HG 9 and HG 3, which are thought to be indicative of demic diffusion associated with the expansion of farming from the

Fertile Crescent in the Middle East toward Europe, due to its frequencies within Caucasoid populations, especially among Middle Eastern populations (Quintana-Murci et al., 2001).

Quintana-Murci and coworkers (2001) further posit that the origins of the HG 9 haplotype are within Iranian populations, due to the high frequencies and diversity within the haplotype.

Contact with Central Asian populations is supported by the presence of the HG 3 haplotype, which is only found with these populations. With the collection of frequencies of HG

9 and HG 3 haplotypes among the selected populations, Quintana-Murci and coworkers estimated the mutation rates through the use of mean variance of microsatellite repeats. The researchers concluded that, based upon these mutation rates and the presence of these specific haplotypes, biological evidence supports the linguistic and archaeological evidence for demic diffusions of both farmers from southwest Asian populations and pastoralists from Central Asian populations.

Quintana-Murci and coworkers (2004) then tested the postulated demic diffusions using mtDNA obtained from 23 ethnic groups within the region. With this methodology, Quintana-

Murci and coworkers provided further support for their previous study by showing the affinities of Indus Valley populations with western Eurasian populations. This study also compared the results of the mtDNA data with Y-chromosome data to test both the results and the impacts of mating patterns.

Quintana-Murci and coworkers (2004) found that mtDNA haplogroup frequencies analyzed with principal components analysis separate ethnic groups of the Iranian Plateau from their counterparts in the Indus Valley and northwest India. Haplogroup frequencies were further examined using AMOVA (Analysis of Molecular Variance), with which all population samples were analyzed as a single group to determine whether linguistic divisions emerged. They found that genetic variance was not significantly correlated with linguistic group (Quintana-Murci et al., 2004). Based upon these findings, Quintana-Murci and coworkers (2004) asserted that the

Indus Basin defines a genetic barrier, in which populations to the west form a group with strong affinities to populations from Iran, Anatolia and the Caucasus, but little affinity South Asian and

55 eastern Eurasian populations. They found that Y-chromosome data was relatively complex, depicting asymmetrical mating patterns and founder effects.

While the specific biological affinities are conflicting, there is a general consensus from these studies. Despite methodology, whether it is based upon odontometrics, morphometrics, or genes, the studies agree in the general sense that modern Pakistani populations have experienced genetic admixture from outside populations and that these populations are located further to the west, especially those of closer geographic proximity. To address the timing of population movements independently of the coalescence estimates based upon the genetic differences found among living, contemporary populations, a better understanding of the behavior of prehistoric populations is necessary.

Prehistoric Populations

While emphasis is placed on the migration and settlement of modern populations, it is also helpful to look at migration and population interactions of prehistoric populations in order to place modern observations in context. Hemphill (2010) examined the genetic component associated with interaction spheres of the Iranian Plateau during the Bronze Age. Archaeological evidence suggests cultural (commercial) interaction between south Central Asia and the Indus

Valley of Pakistan. Both morphometric and odontometric analyses test whether there is also a significant gene flow to accompany this cultural exchange among populations in Central Asia and Tepe Hissar, located within northeastern Iran. However, biological affinities do not show such significant interaction between Iran and populations, neither modern nor prehistoric, within the Indus Valley and peninsular India. Since the biological affinities do not match the archaeological evidence, further research was conducted to see whether other populations may have served as agents for the commercial flow of goods and services between the Indus Valley

56 and Central Asia. Hemphill (2011) used a sample from Hasanlu IV to test this hypothesis.

Hasanlu is located in northwestern Iran and archaeological evidence suggests that its population served as a link to Mesopotamian populations. A dental morphology analysis incorporated the dental sample from Hasanlu IV, and thereby the Greater Mesopotamian Interaction Sphere, into account to test for affinities among the Bronze Age population of Tepe Hissar. With the addition of Hasanlu, the closest affinities were found between Tepe Hissar and Hasanlu. Again, no close affinities were noted between Central Asian, Indus Valley, and peninsular Indian populations.

Hemphill (2011) concludes that archaeological evidence is supported with gene flow among western populations, but not eastward across the Iranian Plateau. Similar results were found when these samples were examined with craniometric data (Barton and Hemphill, 2011). Once again there is evidence of early contact between populations within the Iranian Plateau and

Central Asia, most likely during the early Bronze Age, but with this early sphere of interaction shifted towards populations in northern Mesopotamia during the Middle to Late Bronze Age.

This finding was corroborated by an odontometric study (O‘Neill and Hemphill, 2011) that showed close affinities between Tepe Hissar and south Central Asians, as well as southern

Turkmenistan populations during the Middle Bronze Age. Affinities were also noted between

Tepe Hissar and Hasanlu. However, gene flow was not observed between the inhabitants of Tepe

Hissar and southern Uzbekistan during the Late Bronze Age. Once again, these results indicate genetic interaction shifting from Central Asia towards the west by the end of the Late Bronze

Age, as posited by Hemphill (2011).

While prehistoric populations have a general expansion westward by the Late Bronze Age, the incorporation of modern populations into analyses can continue to address population histories with the addition of the temporal aspect.

Chapter 6: Materials and Methods

Materials

This project investigates Yashkun origins and biological affinities through a comparative analysis of permanent tooth size allocation among 163 Yashkun young adults from the village of

Astore, located in Gilgit-Baltistan Province, northern Pakistan. These samples were collected by

Hemphill and his team from the Departments of Archaeology and Genetics, Hazara University during the 2008 field season and analyzed by the author at the Centre for South Asian Research at California State University, Bakersfield. Maximum mesiodistal and buccolingual measurements were obtained for all permanent teeth, except third molars, in accordance with standardized methods (Moorrees 1957; Wolpoff 1971). The mesiodistal dimension is defined as greatest width of the tooth crown parallel to the occlusal surface (Moorrees, 1957). The buccolingual dimension is defined as the dimension of the tooth from the buccal (cheek) to the lingual (tongue) surface.

Individual measurements were scaled against the geometric mean to control for sexual dimorphism and evolutionary tooth size reduction (Jungers et al., 1995). These data were contrasted with 23 samples of prehistoric and modern individuals from Pakistan, peninsular

India, Central Asia, and the Iranian Plateau. These comparative samples were chosen based both upon geographic location and temporal period to best address each of the migration models for the peopling of South Asia. Descriptions for the locations and temporal significance of each of the samples are presented in Chapter 7: Comparative Samples. The models for the peopling of

South Asia were described in Chapter 2 and operationalized in Chapter 8.

Terminology for the analysis will use the following abbreviations: specific tooth types will be designated by the capitalized first letter of that type, such that incisors are designated by

I, canines by C, premolars by P and molars by M. When referring to teeth located within the maxilla, the prefix U will be used (for upper jaw), while for teeth located in the mandible, L will be used (for lower jaw). In addition, individual teeth will be numerated moving from mesial to distal beginning with ―1,‖ except for canines (which are represented by only one member in each quadrant of the mouth), and the premolars, which are numbered mesiodistally from ―3‖ to ―4‖ reflecting the phylogenetic loss of the first two premolars and last premolar possessed by stem

Eutherian mammals. Regarding measurements, buccolingual dimensions will be referred to using

BL and mesiodistal dimensions will be designated as MD.

Methodology

Dental stone casts were taken for all subjects. Buccolingual and mesiodistal measurements were taken using digital needle-point calipers. All measurements were rounded to the nearest tenth of a millimeter. A total of 56 measurements per individual are possible, depending on whether the tooth was present, well-preserved, and accurately cast. To test the degree of inter-observer error for comparison to the other 23 samples, the author selected a sample – the Madak Lasht- to compare her measurements to the measurements taken by

Hemphill. The data was compared using paired-sample t-tests. Intra-observer error was measured by re-measuring 30 randomly selected individuals from the Yashkun sample from Astore. Once again, paired-sample t-tests were used to assess the level of intra-observer repeatability.

Fluctuating Asymmetry

Symmetry is defined as metrically and morphologically identical bilateral structures

(Scott and Turner, 1997: 96). Fluctuating asymmetry occurs when paired variables exhibit

59 random side differences when they ought to be symmetrical. Unlike directional asymmetry, with fluctuating asymmetry there is no side preference. Symmetry is the genetic ideal, yet outside influences create the random imbalances seen in fluctuating asymmetry (Scott and Turner, 1997).

The human dentition is broken into symmetrical halves by jaw, in which the antimere on the opposite side represents a mirror image of its counterpart on the opposing side. Differences in the metric qualities of dental antimeres are attributed to fluctuating asymmetry due to environmental interference with genetically controlled odontogenesis. Fluctuating asymmetry is attributed to insignificant, random differences between antimeres and can vary in a number of variables including population, dental arcades, and morphogenetic fields (Townsend and Brown 1980,

Townsend, 1981; Mizoguchi, 1986; Kieser et al., 1986).

Paired sample t-tests will be performed to determine whether there are any statistically significant differences in odontometric dimensions between antimeres. If no significant differences are found, then left antimeres will be used in the multivariate analyses, except in those situations in which data could not be collected for left-side members. In such cases, measurements from the right-side antimere will be substituted, if possible.

Sexual Dimorphism

Sexual dimorphism is apparent in human crown dimensions with male teeth being 2-6% larger than female teeth (Moorrees, 1957; Garn et al., 1964, 1966; Mizoguchi, 1988). Among the sample of modern Euro-American children and young adults studied by Garn and coworkers

(1977), discriminant function analyses accounted for the dimorphism with an accuracy rate of

86%. The magnitude and patterning of sex dimorphism differs across samples (Moorrees, 1957;

Garn et al., 1964, 1966; Mizoguchi, 1988). In this analysis, sexual dimorphism will be controlled for in inter-sample comparisons by scaling the data against the geometric mean for each sample.

Multivariate Analyses

All data is initially corrected for sexual dimorphism and evolutionary tooth size reduction by scaling against the geometric mean. The patterning of these geometrically scaled values were then contrasted between sample pairs with squared Euclidean distances. All statistical analyses were performed with PHYLIP, NT-SYS and SYSTAT Version 11.

Between-group variation can be analyzed in both two- and three-dimensions. Within this analysis, pairwise differences in tooth size allocation profile for each sample are assessed with squared Euclidean distances, yielding a diagonal matrix. This data was then analyzed through hierarchical cluster analysis using Ward‘s (1963) minimum variance technique, neighbor-joining cluster analysis (Saitou and Nei 1987), multidimensional scaling using Guttman‘s (1963) coefficient of alienation, and principal co-ordinates analysis (Gower 1966).

Several data reduction analyses are employed so that the relationships between groups can be identified as robust relationships rather than products of a coincidence of a particular algorithm utilized within a single analysis. Ward‘s minimum variance analyzes data by minimizing the error sum of squares. Ward‘s method is a form of hierarchical cluster analysis that allows for a representation of both the similarities and differences between taxonomic units, in this case ethnic group samples (Hemphill 1991).However, this analysis forces data into binary clusters, even if those oppositions may not be the best representation of inter-sample differences.

Another type of cluster analysis is neighbor-joining cluster analysis. This method provides a graphic representation of a phylogenetic tree depicting similarities between groups by branch length and directionality. Branch length is determined by minimum evolution or maximum parsimony, allowing similarities to be valued at unequal rates (Saitou and Nei 1987:

406). By allowing for unequal rates of evolution, neighbor-joining cluster analysis is capable of

61 identifying both genetic drift resulting from isolation as well as rapprochement from recent gene flow. However, while neighbor-joining analysis may be calculated without being rooted like hierarchical cluster analysis, it cannot address fine-scale differences like multidimensional scaling or principal co-ordinates analysis.

Multidimensional scaling using Guttman‘s (1963) coefficient of alienation is a data reduction method that is applied to a diagonal matrix of Euclidean distances. Guttman‘s coefficient of alienation normalizes the extreme values generated from the iterations of the principal components matrix derived from the Euclidean distances. This normalization differentiates the method from other multidimensional scaling models (Kruskal). Data from the

Euclidean distances creates a three-dimensional configuration based upon the dissimilarities in data. With nonmetric multidimensional scaling the axes and distance units are completely relative, for they are arbitrary.

Like multidimensional scaling, principal co-ordinate analysis can assess the amount of variation between the groups. This technique reduces the variance in data into eigenvectors through an orthogonal transformation. The orthogonal transformation takes the values and transforms them linearly. Three principal components are used in this analysis. The first principal component (Z1) represents the greatest variance. Each subsequent component accounts for the rest of the variance observed. This technique works most efficiently where high correlations exist among the variables considered (Hemphill, 1991). Odontometric variables tend to be highly inter-correlated and thereby making principal co-ordinates analysis an efficient test.

Chapter 7: Comparative Samples

The comparative samples chosen for this analysis encompass a wide range in temporal periods and geographic locations throughout Central Asia, India, and Pakistan from previously published data. Living groups are represented by 11 samples within the Hindu Kush and

Karakoram highlands, as well as western and southeastern peninsular India. Archaeological populations are represented by 12 samples from Central Asia, the Indus Valley, and western

India (see Fig. 3). The samples have been arranged by region and temporal period in Table 1.

Each group is represented by a color (purple for Hindu Kush/Karakoram highland samples, blue for west-central Indians, et cet.) that will be used to designate each geographic region in the graphic depiction of multivariate statistical results. The only exception is for the prehistoric samples from Central Asia, which are listed in red in Table 1, but are depicted in yellow in the figures to increase the contrast in visibility.

Prehistoric Central Asia

Prehistoric samples from Central Asia are six in number and include: Altyn Depe (n=

25), Geoksyur (n= 64), Sapalli Tepe (n= 49), Djarkutan (n= 48), Kuzali (n= 31), Molali (n= 52).

Altyn Depe is located in the Kopet Dagh foothill plain along the northern slopes of the Kopet

Dagh Mountains, which provide the physical border between southern Turkmenistan and northern Iran. The skeletal remains recovered from Altyn Depe are associated with the Namazga

V period occupation of the site, which dates to the latter half of the third millennium B.C. (4500-

4200 BP)(Kohl, 1985). Geoksyur is also located within Turkmenistan but along what was once the Tedjen River delta in the southeast. Geoksyur represents the first successful sedentary occupation of the Karakum Desert and was occupied during the Namazga III period dating to

5500-5000 BP (Kohl, 1985).

Sapalli Tepe and Djarkutan are located within the North Bactrian oasis and are representative of the Bactrian-Margianan Archaeological Complex (BMAC) (Heibert, 1994).

The site of Djarkutan features a very large cemetery in which the inhumations have been assigned to four allegedly temporally successive periods based upon associated grave furniture.

The current study encompasses samples from the first three of these temporal periods: Djarkutan

(2000 -1800 B.C.), Kuzali (1800-1650 B.C.), and Molali (1650-1500 B.C.). Human remains were recovered and analyzed for the last of these temporal periods (Bustan: 1500-1350 B.C.), but the number of individuals is too few to yield statistically reliable results. The earliest sample from southern Central Asia comes from the site of Sapalli Tepe, whose human remains have been assigned to the Sapalli phase, which dates roughly to 2200-2000 B.C. (Hemphill, 1999).

Table 1. Comparative Samples with Abbreviations and Sample Sizes

Sample Abb. n Sample Abb. n Hindu Kush/ Karakoram Highlands Prehistoric Central Asia Swatis SWT 190 Altyn Depe ALT 25 Madak Lasht MDK 191 Geoksyur GKS 64 Khos KHO 104 Sapalli Tepe SAP 49 Yashkuns YASa 163 Djarkutan DJR 48 Wakhis from Gulmit WAKg 156 Kuzali KUZ 31 Wakhis from Sost WAKs 166 Molali MOL 52 Western Indians Prehistoric Indus Valley Vaghelia Rajputs RAJ 190 Neolithic Mehrgarh NeoMRG 42 Garasias GRS 207 Chalcolithic ChalMRG 28 Mehrgarh Bhils BHI 208 Harappa (Cem. R37) HAR 26 Timargarha TMG 21 Sarai Khola SKH 25 Southeast Indians Prehistoric Indians Pakanati Reddis PNT 184 Inamgaon INM 38 Gompadhompti Madigas GPD 177 Chenchus CHU 196 Total Living: 2132 Total Prehistoric: 449 TOTAL: 2581

Prehistoric Indians

The sole prehistoric sample from peninsular India derives from the site of Inamgaon (n=

38). This sample was recovered from western Maharashtra and dates to 3,600-2,700 BP (Lukacs

Figure 3. Map of Comparative Samples with Yashkun placed for reference. Color designations are represented in Table 1.

65 and Hemphill, 1991). Previous odontometric and dental morphology studies suggest that the inhabitants of Inamgaon share biological affinities to prehistoric samples from the Indus Valley

(Lukacs and Hemphill, 1991; Hemphill, 2010, 2011, 2012; O'Neill, 2012).

Prehistoric Indus Valley

Prehistoric Indus Valley samples include human remains recovered from the following sites: Neolithic and Chalcolithic period Mehrgarh (n= 42; n= 28, respectively), Harappa (n = 26),

Timargarha (n= 21), and Sarai Khola (n = 25). The site of Mehrgarh is located in the Kachi Plain of Baluchistan Province, Pakistan. The two temporally distinct samples from Merhgarh date to ca. 6500 BP (Chalcolithic period) and ca. 8000 BP (Neolithic period), respectively. Both samples represent early farming villages (Jarrige 1981, Lukacs, 2007). The sample from Harappa is from

Cemetery R37, which has been securely dated to the Mature Harappan period, which dates from

4500-4000 BP (Hemphill, 1999). Timargarha and Sarai Khola represent Late Bronze Age to early Iron Age populations. Timargarha dates between approximately 3700-3300 BP, while Sarai

Khola dating to c. 2000 BP (Hemphill, 1999; Lukacs, 2007).

Hindu Kush/Karakoram Highlands

The samples of living individuals from the Hindu Kush and Karakoram highlands were collected for the Centre for South Asian Research by Hemphill during the 2005, 2007, and 2008 field seasons. The samples are from northern Pakistan and comprise six groups: the Wakhi of

Sost (n= 170) and Gulmit (n= 166), Khowar (n=104), Madak Lasht (n= 191), Swatis (n= 190), and Yashkuns of Astore (n= 163) ( see Fig. 4). The Madak Lasht come from the Hindu Kush highlands and the Swatis are located within the foothills along the northern rim of the Indus

Valley. The Wakhi, Khowar, and Yashkun reside within Gilgit-Baltistan. Except for the two geographically distinct samples of Wakhis, each sample was derived from a distinct

66 ethnolinguistic group. The Swatis, Madak Lasht, and Wakhi speak an Indo-Iranian language, while the Yashkun and Khowar speak a Dardic language within the Indo-European language family. Broadly, the Indo-European language family can be divided into three branches: Dardic,

Indo-Iranian, and Indo-Aryan.

The Wakhi claim to represent an emigrant group that entered the Gilgit-Baltistan area of northern Pakistan, from the Pamir region of Tajikistan via the Wakhan Corridor of Afganistan in the 1970s (Felmin, 1996; Sharani, 1979; Biddulf, 1888; O'Neill, 2012). The group practices agriculture and pastoralism.

Figure 4. Map depicting the Hindu Kush/ Karakorum Highland samples (in blue) with associated geographic landmarks (in yellow).

The Kho claim to have immigrated to the Chitral District in northern Pakistan from

Central Asia during the 13th century (Blaylock, 2008). The inhabitants of Madak Lasht also reside within Chitral District, but are isolated within a mountain village. The Madak Lasht claim

67 to be recent immigrants to the Chitral District from Nuristan, located in northeastern

Afghanistan. The sample of Swatis included in this study do not reside in either the Hindu Kush or Karakoram highlands. Instead, this sample was collected in Mansehra District, which is located in the east-central portion of Khyber Pakhtunkhwa Province. As such the Swatis included in this study inhabit the southern foothills of the Himalayas near the northern border of the Indus Valley. Although it is generally agreed that the Swatis are immigrants to this region of northern Pakistan, their exact origins are the subject of much debate. One proponent argues for a historic migration to the Hazara Division of Khyber Pakhtunkhwa (of which Mansehra District is a part) at some point between A.D. 1500-1700 from the Swat Valley (Schofield 2003). Another hypothesis is that the Swatis ―were once a race of Hindu origin who once ruled the whole country from the Jahlem to Jalalabad,‖ but who were driven out of southern Afghanistan and into the northern hills of Swat and Buner during the mid-13th century, and then subsequently driven out of this region eastward into the Hazara region around the end of the 15th century (Ibbetson,

1916: 95). The Yashkun also inhabit the area and have disputed origins that have been described in Chapter 1.

Southeast Indians

The samples from southeast India are represented by three Dravidian language (Telegu) speaking groups: Pakanati Reddis (n= 184), Gompadhompti Madigas (n= 177), and Chenchus

(n= 196). All odontometric data on these groups was collected by Hemphill (1991).

The Pakanati Reddis are a caste (also referred to as the Kapu) mainly living within the

Chittoor District of Andhra Pradesh. This group belongs to a higher caste of land-holders and cultivators. The Reddis can be subdivided into 17 major endogamous subcastes of which the

Pakanatis are one.

The Gompadhompti Madiga are one of six endogamous subcastes within the Madiga caste cluster of Andhra Pradesh and Tamil Nadu. The Gompadhompti Madiga are representative of the greatest Madiga population and found in the greatest numbers in Cuddapah and Chittor

Districts of southern Andhra Pradesh. They are members of a low-status caste of the left-hand whose occupations include leather-working, field laborers, grass-cutters, rickshaw pullers, and house servants (Hemphill, 1991).

The Chenchu are members of a tribal population residing within the Namali Hills, an area that spans Mahabubnagar, Kurnool, Prakasam, and Guntur Districts of northern Andhra Pradesh

(now Telegana). The Chenchu are a non-caste group. Despite culturally recognized ethnic subdivisions, the Chenchu have no tribal identity; rather, affiliation is based upon clan or village

(Hemphill, 1991).

Western India

The samples from western India are drawn from three groups: the Vaghela Rajputs (n=

190), Garasias (n= 207), and Bhils (n= 208). The dental casts upon which the data is based were collected by Lukacs in 1983-1984 in collaboration with the Government Dental College and

Hospital, Department of Orthodontics in Ahmedabad as well as the Gujarat Vidyapeth Tribal

Research and Training Institute, also in Ahmedabad. The Vaghela Rajputs represent a high-status caste, the Garasias a low-status caste, and the Bhils a non-caste tribal population. The samples were obtained in rural villages within Gujarat, approximately 100-170 km northeast of

Ahmedabad.

The Rajputs are a warrior caste that became dominant over the Bhils during the 8th A.D.

Early on male Rajputs married Bhil women to consolidate the change in political power. The children of these marriages formed a new caste known as the Garasias. Many of the Garasias

69 have converted to Buddhism as an attempt to escape the low Hindu status. The Garasias remain endogamous. The Bhils are a patrilineal and patrilocal tribal population found in an extensive area running from Gujarat and Rajasthan in the west to Madhya Pradesh in the east. The sample collected in Gujarat is from a group that lives within a plains environment and who reside in settled agricultural communities (Lukacs and Hemphill, 1993). The Bhils speak Bhili, which is derived from an Indo-European language, but with Dravidian and Mundic influences.

Chapter 8: Operationalized Research Questions

To assess questions regarding biological affinities of the Yashkun, hypotheses specific to the four research questions described in Chapter 1 will be formulated and tested using multivariate analyses of the apportionment of geometrically scaled measurements of permanent tooth size throughout the dentition. The hypotheses for each question include a null hypothesis (H0) and an alternate hypothesis (Ha). The alternate hypothesis displays the order of greatest affinities expected by each model while the null hypothesis depicts the affinities necessary for rendering the model null.

1) The Aryan Invasion Model: Are the Yashkun descendants of Indo-Aryan-speaking populations who migrated from Central Asia to the Hindu Kush and Karakoram highlands during the 2nd millennium B.C.?

H01: The Yashkun are not descendants of Indo-Aryan-speaking populations who migrated from Central Asia during the 2nd millennium B.C. (YASa ≠ SAP, DJR, KUZ, MOL, GKS, ALT).

Ha1: The Yashkun are descendants of Indo-Aryan-speaking populations who migrated from Central Asia during the 2nd millennium B.C. (YASa ≈ KHO > WAKg, WAKs, SWT, MDK > SAP, DJR, KUZ, MOL, GKS, ALT > TMG, SKH> BHI, GRS, RAJ > NeoMRG, ChlMRG, HAR, TMG, SKH, PNT, GPD, CHU, INM) If the Aryan Invasion Model is supported, than the Yashkun should possess affinities with living descendants of Indo-Aryan Central Asian populations, represented by the Khowar.

Secondary affinities may be seen with the Indo-Iranian populations of the Wakhi, Swatis, and

Madak Lasht. Closer affinities should also be shared with ancestral prehistoric Central Asian populations. Affinities should be noted between the Yashkun and Altyn Depe, Geoksyur, Sapalli

Tepe, Djarkutan, Kuzali, and Molali. Distant affinities with western Indians (Vaghelia Rajputs,

Garasias, and Bhils) will be observed due to shared Dravidian language families. Affinities with prehistoric samples from the Indus Valley (e.g., Neolithic Mehrgarh, Chalcolithic Mehrgarh, and

Harappa) and peninsular India (Inamgaon) should not be observed since these populations would not bear an ancestral relationship to the Yashkun. If no affinities are shared between the

Yashkun and any modern Indo-Aryan and Indo-Iranian-speaking populations or prehistoric

Central Asian samples, than the null hypothesis is supported and the Aryan Invasion Model is not supported.

2) Long-Standing Continuity Model: Are the Yashkun descendants of a long-standing isolated, indigenous population residing within the Hindu Kush/Karakoram highlands?

H02: The Yashkun are not descendants of a long-standing isolated, indigenous population residing within the Hindu Kush/Karakoram highlands (YASa ≠ WAKg, WAKs, KHO,MDK, SWT, NeoMRG, ChlMRG, HAR, TMG, SKH).

Ha2: The Yashkun are descendants of a long-standing isolated, indigenous population residing within the Hindu Kush/Karakoram highlands (YASa ≈ WAKg, WAKs> KHO, MDK> SWT >NeoMRG, ChlMRG, HAR, TMG, SKH ≠ RAJ, GRS, BHI, PNT, GPD, CHU, ALT, GKS, SAP, DJR, KUZ, MOL, INM) Based upon the Long-Standing Continuity Model, the Yashkun should share closest affinities to other modern populations within the Hindu Kush highlands, depicting a pattern of isolation- by-distance. Therefore, the Yashkun ought to exhibit closest affinities with the Wakhi, Khowars, and the residents of Madak Lasht. However, due to the claims of a much more recent migration by all three populations (the Madak Lasht, Khowar, and Wakhi), it is not likely that close affinities among the groups will be observed. The closest affinities should therefore then be observed between the Yashkun and the Khowar, due to the fact that both speak languages assigned to the Dardic branch of Indo-European. Secondary affinities are expected among the

Yashkun‘s ancestors within the Indus Valley who are composed of the Neolithic and

Chalcolithic Mehrgarh, Harappa, Timargarha, and Sarai Khola. The Yashkun should not exhibit any biological affinities to Dravidian-speaking ethnic groups of southeastern peninsular India.

There should be a divergence to populations from prehistoric Central Asia and India populations

(Altyn Depe, Geoksyur, Sapalli Tepe, Djarkutan, Kuzali, Molali, Inamgaon), as well as peninsular India (Pakatani Reddis, Gompadhompti Madigas, Chenchus). These results would support the Long-Standing Isolation Model. Contrarily, the null hypothesis would be supported if the Yashkun do not show affinities for any of the other Hindu Kush/ Karakorum highland populations or prehistoric Indus Valley samples.

3) Early Entrance Model: Are the Yashkun descendants of a population associated with the introduction of Proto-Elamo-Dravidian languages into South Asia between 6,000 and 4,500 B.C.?

H03: The Yashkun are not descendants of a Proto-Elamo-Dravidian speaking populations from India between 6,000 and 4,500 B.C. (YASa ≠ PNT, GPD, CHU, GKS, ALT, SAP, DJR, KUZ, MOL, SKH, TMG, RAJ, GRS, BHI).

Ha3: The Yashkun are descendants of a Proto-Elamo-Dravidian speaking populations from India between 6,000 and 4,500 B.C. (YAS a≈ PNT, GPD, CHU >GKS, ALT, SAP, DJR, KUZ, MOL, SKH, TMG > RAJ, GRS, BHI >WAKg, WAKs, KHO, MDK, SWT ≠ NeoMRG, ChlMRG, HAR, INM). Following the Early Entrance Model, distant affinities will be observed amongst modern

Dravidian-speaking populations who are also descendants of the same proto-Elamo-Dravidian- speaking populations who migrated into the region. These populations include the southeast

India populations (Pakanati Reddis, Gompadhompti Madigas, and Chenchus). Distant but equal affinities should also be observed among the Yashkun and populations from prehistoric Central

Asia (Altyn Depe, Geoksyur, Sapalli Tepe, Djarkutan, Kuzali, and Molali) and populations within the Indus Valley after 4,500 B.C. (Sarai Khola and Timargarha). Distant affinities between the prehistoric Central Asia samples and the western Indian populations may be observed as the Vaghelia Rajputs, Garasias, and Bhils would be expected to represent descendants of Aryan-speaking Central Asians. Generally, affinities among the Dravidian- speaking populations and prehistoric populations within the Indus Valley should be observed to support the Early Entrance Model. Affinities should not be expected with Chalcolithic Indus

Valley samples (Chalcolithic Mehrgarh and Harappa). If no affinities were observed between the

Yashkun and any descendants of proto-Elamo-Dravidian-speaking populations or prehistoric

Central Asians and late Indus Valley samples, than the null hypothesis would be supported and the Early Entrance Model would not be supported.

4) Are the Yashkun descendants of populations that migrated to northwestern South Asia in the historic era?

H04: The Yashkun are not descendants of populations that migrated to northwestern South Asia in the historic era (YASa ≈ NeoMRG, ChlMRG, HAR, TMG, SKH).

Ha4: The Yashkun are descendants of populations that migrated to northwestern South Asia in the historic era (YASa ≠ NeoMRG, ChlMRG, HAR, TMG, SKH>PNT, GPD, CHU). If the Yashkuns reflect the Historic Era Influences Model, than the Yashkun and other ethnic groups occupying the Hindu Kush/ Karakorum Highlands samples (Wakhis from Gulmit,

Wakhis from Sost, Madak Lasht, or Khowar) will be marked by divergent affinities from prehistoric samples of the Indus Valley (Timargarha, Sarai Khola, Harappa, or Neolithic and

Chalcolithic period Merhgarh) and peninsular India (Pakanati Reddis, Gompadhompti Madigas, or Chenchus). This is due to the result of historical migrations having great impact on the genetic history of the populations. If any of these populations do show affinities, than the null hypothesis is supported and therefore the Historic Era Influences Model would not be supported. To distinguish results from the Long-Standing Continuity Model, all of the Pakistani groups should not share any affinities with each other, nor with the prehistoric Indus Valley populations.

Chapter 9: Results I- Odontometric Variation among the Yashkun of Astore

Intra-Observer Error Analysis Intra-observer error was tested in order to determine the author‘s accuracy in measurement repeatability. The author re-measured buccolingual and mesiodistal variables of 35 randomly selected specimens from the Yashkun of Astore dental cast collection eight months apart, the initial measurements being taken in September 2011 and the second set in May 2012.

Intra-observer error was tested using two-tailed paired-sample t-tests. The left upper and lower teeth were selected for comparison. Of the 28 variables compared, three of the variables

(LM1MD, LCMD, UCMD) were found to differ significantly between measuring bouts (see

Table 2). All three significant differences represent discrepancies in the consistency of measuring mesiodistal lengths. Nevertheless, despite these differences, it is clear that the vast majority of the author‘s measurements (25/28= 89.3%) are consistent in their repeatability and therefore should not seriously compromise the outcome of results for the assessment of population distances.

Inter-Observer Error Analysis Inter-observer error was tested between the author, Barton, and Hemphill, who collected the majority of data for the 23 comparative samples. Inter-observer error analysis tests the accuracy of measurements between researchers to ensure reliability of results during analysis using datasets generated by multiple researchers. A total of 35 specimens were selected from the

Madak Lasht sample of dental casts for comparison using two-tailed paired-sample t-tests.

Buccolingual and mesiodistal measurements of the specimens taken by the author were compared to those obtained by Hemphill to test the inter-observer error rates between researchers

(see Table 3). Both maxillary and mandibular teeth were selected for comparison. When

75 measurements for particular specimens were absent from one observer‘s dataset, that variable was not included in the t-test. Of the 28 variables compared, four were found to be significantly different (LM1MD, LP3MD, LI2MD, UCMD). Once again, all of these significant differences involved mesiodistal measurements, and in this case the measurements taken by Barton tended to be smaller than those taken by Hemphill. Despite the significant differences of two variables,

86% of the measurements are accurate with no significant differences. Due to the high percentage of measurements that are accurate, it is possible to accurately utilize data of both researchers in the study.

Table 2. Intra-Observer Error using Paired-Sample t-Tests. Highlighted numbers are those that yield significant differences (p< 0.05).

Std. Error Tooth Trial 1 Trial 2 Mean of Dimension Mean Mean Difference Difference t Sig. 9.922 9.895 0.027 0.048 0.5609 0.578 LM2MD 10.055 10.103 -0.048 0.032 1.4900 0.147 LM2BL 10.818 10.918 -0.100 0.028 3.5143 0.001 LM1MD 10.498 10.600 -0.102 0.047 2.1610 0.370 LM1BL 6.363 6.350 0.012 0.029 0.4357 0.665 LP4MD 8.355 8.480 -0.125 0.141 0.8841 0.379 LP4BL 6.423 6.460 -0.056 0.063 0.8898 0.379 LP3MD 7.779 7.823 -0.072 0.111 0.6482 0.521 LP3BL 6.343 6.435 -0.092 0.033 2.7635 0.009 LCMD 7.584 7.573 -0.055 0.107 0.5175 0.608 LCBL 5.480 0.105 0.098 1.0731 0.287 5.585 LI2MD 6.433 6.455 -0.036 0.124 0.2885 0.775 LI2BL 4.903 4.925 -0.016 0.109 0.1450 0.886 LI1MD 6.126 6.187 -0.061 0.047 1.2827 0.208 LI1BL

9.719 9.797 -0.133 0.160 0.8345 0.412 UM2MD 11.026 10.845 0.096 0.239 0.4002 0.693 UM2BL 10.157 10.130 0.027 0.046 0.5979 0.553 UM1MD

11.339 11.403 -0.030 0.131 0.2276 0.821 UM1BL 6.010 5.933 0.064 0.073 0.8730 0.388 UP4MD 9.037 9.203 -0.216 0.144 1.5007 0.142 UP4BL 6.377 6.360 0.018 0.037 0.4684 0.642 UP3MD 8.905 9.018 -0.123 0.104 1.1790 0.246 UP3BL 7.238 7.332 -0.095 0.037 2.5536 0.015 UCMD 8.018 8.067 -0.176 0.183 0.9655 0.341 UCBL 6.184 6.265 0.103 0.069 1.4857 0.146 UI2MD 6.378 6.438 -0.172 0.186 0.9221 0.364 UI2BL 8.168 8.237 -0.074 0.049 1.5087 0.140 UI1MD 7.410 7.577 -0.363 0.221 1.6410 0.112 UI1BL

Table 3. Inter-Observer Error using Paired-Sample t-Tests. Highlighted numbers are those that yield significant differences (p< 0.05). Barton Hemphill Mean Std. Error of Tooth Dimension Mean Mean Difference Difference t Sig. 9.500 9.703 LM2MD 0.022 0.124 1.6846 0.101 9.626 9.795 -0.194 0.109 1.7774 0.085 LM2BL 10.297 10.556 0.036 0.117 2.3411 0.025 LM1MD 9.938 9.932 -0.000 0.116 0.0000 1.000 LM1BL 6.100 6.207 -0.129 0.151 0.8569 0.397 LP4MD 7.688 7.771 -0.092 0.135 0.6840 0.498 LP4BL 6.307 6.514 -0.207 0.078 2.6592 0.011 LP3MD 7.349 7.360 -0.027 0.132 0.2040 0.839 LP3BL 6.159 6.319 -0.172 0.088 1.9503 0.059 LCMD

6.947 7.045 -0.113 0.175 0.6463 0.522 LCBL 5.491 5.640 -0.182 0.084 2.1664 0.038 LI2MD 5.882 6.015 -0.149 0.192 0.7728 0.444 LI2BL 4.887 4.801 0.015 2.574 0.7466 0.483 LI1MD 5.541 5.538 0.003 0.123 0.0219 0.983 LI1BL 9.244 9.316 -0.088 0.229 0.3845 0.704 UM2MD 10.460 10.689 -0.324 0.173 1.8714 0.074 UM2BL 9.544 9.673 -0.088 0.144 0.6100 0.548 UM1MD 10.820 11.025 -0.188 0.128 1.4676 0.155 UM1BL 5.660 5.924 -0.244 0.134 1.8169 0.082 UP4MD 8.644 8.749 -0.116 0.149 0.7811 0.442 UP4BL 6.320 6.456 -0.204 0.120 1.6932 0.103 UP3MD 8.641 8.817 -0.259 0.184 1.4042 0.179 UP3BL 7.093 7.295 -0.268 0.077 3.4792 0.002 UCMD 7.708 7.828 -0.308 0.194 1.5913 0.125 UCBL 6.206 6.317 -0.154 0.135 1.1450 0.260 UI2MD 6.359 6.334 -0.119 0.173 0.6869 0.498 UI2BL 8.214 8.280 -0.100 0.096 1.0433 0.306 UI1MD 7.056 7.208 -0.248 0.196 1.2633 0.219 UI1BL

Asymmetry An assessment of fluctuating asymmetry between left and right antimeres among the

Yashkun of Astore was performed using paired-sample t-tests after testing the distribution using the Shapiro-Wilks test. This analysis tests if there is a significance of differences in size between antimeres. If there are no significant differences between the buccolingual or mesiodistal measurements in antimeres, then it is permissible to substitute measurements from the right side when that measurement cannot be made on the left side dental element. As can be seen in Table

4 below, no significant asymmetry was found for any of the 28 variables tested among the

Yashkun from Astore.

Table 4. Paired-sample t-tests of Asymmetry between Antimeric Dental Elements.

Tooth Pairs N t df Sig. (2-tailed) 0.398 150 0.691 LLM2MD & LRM2MD 76 0.385 142 0.701 LLM2BL & LRM2BL 72 0.596 284 0.552 LLM1MD & LRM1MD 143 0.272 258 0.786 LLM1BL & LRM1BL 130 0.682 304 0.496 LLP4MD & LRP4MD 153 0.865 281 0.388 LLP4BL & LRP4BL 142 0.650 294 0.561 LLP3MD & LRP3MD 148 0.641 282 0.522 LLP3BL & LRP3BL 142 0.165 266 0.869 LLCMD & LRCMD 134 0.414 250 0.967 LLCBL & LRCBL 126 0.288 210 0.774 LLI2MD & LRI2MD 106 0.024 226 0.981 LLI2BL & LRI2BL 114 0.032 236 0.975 LLI1MD & LRI1MD 119 0.044 214 0.965 LLI1BL & LRI1BL 108 0.384 116 0.702 ULM2MD & URM2MD 59 0.035 126 0.972 ULM2BL & URM2BL 64 0.184 272 0.854 ULM1MD & URM1MD 137 1.284 236 0.200 ULM1BL & URM1BL 119 0.744 276 0.457 ULP4MD & URP4MD 139 0.103 260 0.918 ULP4BL & URP4BL 131 1.008 288 0.314 ULP3MD & URP3MD 145 0.611 264 0.541 ULP3BL & URP3BL 133

0.625 272 0.532 ULCMD & URCMD 137 0.585 190 0.559 ULCBL& URCBL 96 0.342 230 0.732 ULI2MD & URI2MD 116 0.300 176 0.764 ULI2BL & URI2BL 89 0.049 270 0.961 ULI1MD & URI1MD 136 0.833 202 0.406 ULI1BL & URI1BL 102

Sexual Dimorphism Among primates, sexual dimorphism is apparent in many traits including tooth size.

Descriptive data for the entire sample was calculated prior to testing for sexual dimorphism

(Tables 5 and 6). To test the degree of sexual dimorphism among the Yashkun of Astore the difference in tooth size between the two sexes was calculated using both independent t-tests and as a percentage: ((Male-Female/Female)). The results are presented in Tables 7-8.

Sexual dimorphism is present among the Yashkuns from Astore since every measurement exhibits a smaller female average than male average. Independent t-tests indicate that with every measurement, male teeth are significantly larger than female teeth. The degree of sex dimorphism ranges from a low 2.77 % for the buccolingual dimension of UP3 to a high of

8.9% for the buccolingual dimension of the L1 (Table 8). While a significant difference of sexual dimorphism is present among the Yashkuns from Astore, geometrically-scaling the values of the measurements prior to running the bio-distance analyses will account for the differences and allow for an accurate assessment of the phenetic affinities.

Table 5. Descriptive statistics of Odontometric Variation among Yashkun Males of Astore. Yashkun Males Measurements N Minimum Maximum Mean Std. Deviation LM2MD 76 8.5 11.6 10.008 0.712 LM2BL 67 8.5 11.3 10.191 0.569

LM1MD 91 9.4 12.8 10.889 0.651 LM1BL 90 8.5 11.9 10.479 0.583 LP4MD 92 5.5 7.4 6.385 0.433 LP4BL 89 6.5 9.5 8.261 0.627 LP3MD 92 5.6 7.6 6.472 0.388 LP3BL 89 6.3 9 7.792 0.540 LCMD 90 5.5 7.7 6.393 0.402 LCBL 86 5 9.9 7.444 0.816 LI2MD 81 4.2 6.7 5.465 0.432 LI2BL 83 4.6 9.2 6.470 0.689 LI1MD 83 4.1 6 4.935 0.394 L11BL 74 4.5 7.7 6.222 0.635 UM2MD 53 8 12.1 9.713 0.782 UM2BL 54 9.2 12.5 10.887 0.753 UM1MD 85 8.9 12.4 10.266 0.607 UM1BL 80 9.1 13 11.216 0.685 UP4MD 86 4.9 6.8 6.003 0.441 UP4BL 83 7.4 10.6 9.105 0.632 UP3MD 87 5.4 7.3 6.436 0.393 UP3BL 85 7.6 10.5 8.944 0.617 UCMD 86 5.9 8.3 7.253 0.520 UCBL 78 5.3 10.3 8.105 0.850 UI2MD 72 4.7 10 6.528 0.754 UI2BL 84 4.9 7.1 6.281 0.463 UI1MD 84 6.7 9.8 8.160 0.600 UI1BL 57 5.4 8.8 7.400 0.789

Table 6. Descriptive statistics of Odontometric Variation among Yashkun Females of Astore. Yashkun Females Std. Measurements N Minimum Maximum Mean Deviation LM2MD 65 8 11 9.269 0.576 LM2BL 62 8.6 11 9.760 0.563 LM1MD 67 8.9 11.4 10.178 0.526 LM1BL 66 8.2 11.3 10.299 0.557 LP4MD 68 5.3 8.2 6.162 0.420 LP4BL 68 6 9.1 7.971 0.534 LP3MD 69 5.5 7.1 6.246 0.389

LP3BL 69 6.2 8.9 7.338 0.523 LCMD 68 5.1 6.9 5.984 0.381 LCBL 64 5.4 8 6.928 0.536 LI2MD 57 4.4 6.3 5.237 0.419 LI2BL 64 4.7 7.1 6.030 0.433 LI1MD 56 3.9 5.7 4.705 0.367 L11BL 61 3.9 7 5.749 0.579 UM2MD 47 8.1 10.6 9.162 0.586 UM2BL 49 8.9 12.1 10.410 0.660 UM1MD 65 8.7 11.1 9.634 0.498 UM1BL 63 8.5 12 10.817 0.580 UP4MD 65 4.6 6.6 5.789 0.469 UP4BL 65 7.2 10.6 8.783 0.662 UP3MD 65 5.1 7.3 6.231 0.407 UP3BL 64 7.2 9.6 8.673 0.534 UCMD 65 5.9 7.7 6.889 0.377 UCBL 63 5.7 8.7 7.503 0.615 UI2MD 65 4.8 7.8 6.046 0.654 UI2BL 59 4.7 7.7 5.976 0.667 UI1MD 65 6.6 9.2 7.857 0.539 UI1BL 57 5.8 8.5 6.974 0.624

Table 7. Male Tooth Dimensions Compared to Female Tooth Dimensions using Independent Samples t- Tests. Highlighted numbers identify significant differences (p< 0.05). Male Female Mean Std. Error of Tooth Dimension Mean Mean Difference Difference t Sig. 9.256 LM2MD 9.989 0.733 0.121 6.080 0.0001 10.187 9.750 0.437 0.112 3.888 0.0002 LM2BL 10.895 10.148 0.748 0.101 7.437 0.0001 LM1MD 10.474 10.166 0.308 0.093 3.315 0.0012 LM1BL 6.382 6.158 0.224 0.070 3.211 0.0016 LP4MD 8.317 7.977 0.340 0.093 3.648 0.0004 LP4BL 6.467 6.242 0.226 0.063 3.561 0.0005 LP3MD 7.813 7.340 0.473 0.085 5.550 0.0001 LP3BL 6.410 5.987 0.422 0.066 6.422 0.0001 LCMD

7.436 6.932 0.503 0.121 4.162 0.0001 LCBL 5.471 5.249 0.222 0.077 2.886 0.0046 LI2MD 6.443 6.031 0.412 0.099 4.179 0.0001 LI2BL 4.937 4.715 0.222 0.069 3.212 0.0017 LI1MD 6.246 5.736 0.511 0.105 4.864 0.0001 LI1BL 9.767 9.191 0.575 0.157 3.661 0.0004 UM2MD 10.878 10.417 0.461 0.166 2.772 0.0071 UM2BL 10.261 9.648 0.613 0.097 6.301 0.0001 UM1MD 11.190 10.877 0.313 0.110 2.842 0.0052 UM1BL 6.019 5.792 0.227 0.076 2.996 0.0032 UP4MD 9.090 8.802 0.288 0.110 2.616 0.0099 UP4BL 6.435 6.243 0.192 0.067 2.884 0.0045 UP3MD 8.951 8.710 0.241 0.098 2.474 0.0146 UP3BL 7.279 6.869 0.410 0.079 5.185 0.0001 UCMD 8.136 7.577 0.559 0.137 4.081 0.0001 UCBL 6.271 6.056 0.215 0.099 2.159 0.0327 UI2MD 6.453 5.938 0.515 0.124 4.153 0.0001 UI2BL 8.151 7.842 0.309 0.099 3.117 0.0022 UI1MD 7.434 6.991 0.443 0.137 3.224 0.0017 UI1BL

Table 8. Percentage of Sexual Dimorphism by Dental Element and by Dimension. Std. Tooth & % Sex Error Dimension Sex N Mean Dimorphism SD Mean 9.989 0.716 0.095 LM2MD M 57 7.92% 9.256 0.549 0.073 F 57 10.187 0.554 0.077 LM2BL M 54 4.48% 9.750 0.589 0.080 F 52 10.895 0.655 0.070 LM1MD M 87 7.37%

10.148 0.525 0.066 F 63 10.474 0.577 0.063 LM1BL M 85 3.03% 10.166 0.517 0.066 F 62 6.382 0.435 0.046 LP4MD M 90 3.64% 6.158 0.423 0.052 F 67 8.284 0.614 0.066 LP4BL M 87 4.03% 7.963 0.532 0.066 F 65 6.467 0.386 0.041 LP3MD M 89 3.61% 6.242 0.394 0.048 F 67 7.813 0.521 0.056 LP3BL M 87 6.44% 7.340 0.526 0.064 F 68 6.410 0.396 0.043 LCMD M 84 7.06% 5.987 0.382 0.049 F 62 7.436 0.822 0.090 LCBL M 84 7.26% 6.932 0.544 0.069 F 62 5.471 0.427 0.049 LI2MD M 75 4.22% 5.249 0.408 0.057 F 51 6.443 0.667 0.075 LI2BL M 79 6.84% 6.031 0.438 0.056 F 62 4.937 0.393 0.044 LI1MD M 79 4.70% 4.715 0.374 0.051 F 53 6.246 0.636 0.075 L11BL M 71 8.90% 5.736 0.508 0.068 F 56 9.767 0.747 0.108 UM2MD M 48 6.26% 9.191 0.625 0.106 F 35 10.878 0.768 0.113 UM2BL M 46 4.43% 10.417 0.550 0.102 F 29

10.261 0.618 0.069 UM1MD M 80 6.35% 9.648 0.504 0.064 F 62 11.190 0.672 0.079 UM1BL M 72 2.88% 10.877 0.495 0.068 F 53 6.019 0.428 0.047 UP4MD M 83 3.93% 5.792 0.475 0.060 F 62 9.090 0.637 0.072 UP4BL M 78 3.27% 8.802 0.643 0.082 F 61 6.435 0.394 0.043 UP3MD M 85 3.08% 6.243 0.405 0.051 F 63 8.951 0.609 0.068 UP3BL M 80 2.77% 8.710 0.505 0.065 F 60 7.279 0.520 0.058 UCMD M 81 5.97% 6.869 0.375 0.048 F 61 8.136 0.806 0.098 UCBL M 67 7.37% 7.577 0.572 0.083 F 48 6.271 0.470 0.054 UI2MD M 75 3.54% 6.056 0.662 0.088 F 57 6.453 0.654 0.083 UI2BL M 62 8.67% 5.938 0.610 0.089 F 47 8.151 0.598 0.066 UI1MD M 83 3.94% 7.842 0.556 0.072 F 60 7.434 0.787 0.108 UI1BL M 53 6.34% 6.991 0.621 0.084 F 55

Chapter 10: Results II- Odontometric Assessment of the Yashkun Phenetic Affinities

Data Preparation for Analysis

The data was standardized by using the geometric mean for each group prior to submission to multivariate analysis. Tooth size standardization controls for differences in gross size due to sex dimorphism and the evolutionary reduction in tooth size caused by the shift to agriculture and the introduction of more sophisticated premasticatory food preparation practices

(e.g., ceramic vessels, querns, etc.). The geometric mean values for the 28 variables were then used as input for calculating the pairwise diagonal Euclidean distance matrix between samples

(see Appendix A). These Euclidean distances provide a measure of dissimilarity between sample pairs. An array of multivariate data reduction techniques, including hierarchical cluster analysis with Ward‘s linkage (Ward 1963), neighbor-joining cluster analysis (Saitou and Nei 1987), multidimensional scaling using Guttman‘s and Kruskal‘s method (Guttman 1968, Kruskal 1964), and principle co-ordinates analysis were conducted to ease interpretation of sample differences in the allocation of permanent tooth size across the dentition. Table 1 presents the samples utilized in all multivariate analyses. The samples are divided by region and temporal period. The samples maintain the same color groupings as described in Chapter 5. Each region and temporal period is designated by color within the graphics of these analyses. For example, the prehistoric Indus

Valley populations are designated in pink and the modern Southeast Indian populations are green. The only exception is for the prehistoric samples from Central Asia which are listed in red in Table 1, but are depicted in yellow in the illustrative graphics to increase the contrast in visibility. The results are discussed below.

Hierarchical Cluster Analysis

Hierarchical cluster analysis with Ward‘s (1963) method yields a fundamental split between Hindu Kush/ Karakorum highlanders and prehistoric Central Asians on one side versus prehistoric inhabitants of the Indus Valley and the samples of living inhabitants of peninsular

India on the other (Fig. 5). Among the former, prehistoric Central Asians are distinguished from

Hindu Kush/ Karakorum highlanders with two exceptions. The Djarkutan Period sample from

Djarkutan (DJR) is identified as possessing closest affinities to the Yashkuns from Astore (YAS) and to the Kho (KHO), coupled with somewhat more distant affinities to both Wakhi samples

(WAKs, WAKg). The sample of Dravidian-speaking tribal Chenchus (CHU) are identified as possessing affinities to Swatis (SWT) and to the inhabitants of Madak Lasht (MDK), while the

Namazga V Period sample from the Kopet Dagh foothill plain urban center of Altyn Depe (ALT) is identified as possessing peripheral affinities to the Hindu Kush/ Karakorum highland samples.

Among the remaining samples there is a nearly complete separation between prehistoric inhabitants of the Indus Valley and peninsular Indians. The only exception is the prehistoric sample from Inamgaon (INM), which is identified as possessing closer affinities to the prehistoric samples from the Indus Valley than to the samples of living peninsular Indians.

Neighbor-joining Cluster Analysis

Neighbor-joining cluster analysis divides the 24 samples into four aggregates based upon geographic region and temporal period and four isolates (Fig. 6). The four isolates include the

Namazga V period sample from Altyn Depe (ALT) in the upper left, the Swati sample from

Mansehra District (SWT) and the Dravidian-speaking Chenchu tribals (CHU) from southeast

India in the central-right, and the inhabitants of Madak Lasht (MDK) of the Hindu Kush /

CHU SWT MDK WAKs WAKg YASa KHO

TMG SKH ChlMRG NeoMRG HAR INM BHI GRS RAJ PNT GPD

0.0 2 4 6 8 10 12

Figure 5. Hierarchical Cluster Analysis with Ward‘s (1963) Method.

Karakorum highlands in the lower center. The isolates indicate a lack of affinity to any of the other samples included in the study. The first aggregate is located in the lower left. It is composed of prehistoric Central Asians. The only exception is the living Kho (KHO) from the

Hindu Kush/ Karakorum highlands, who occupy the most peripheral position within this aggregate. The second aggregate is composed of the two Wakhi samples (WAKg, WAKs), which bear closest affinities to one another and to the Yashkuns from Astore (YAS). The third aggregate is located in the upper right and is composed of all of the living samples of peninsular

Indians, except the Dravidian-speaking tribal Chenchus (CHU). The fourth aggregate is located in the lower right and is composed of the prehistoric samples from the Indus Valley.

BHI GRS

RAJ GPD YASa PNT WAKg WAKs

SWT CHU

KHO ChlMRG NeoMRG MDK

HAR SKH TMG

INM

Figure 6. Neighbor-joining Cluster Analysis.

Multidimensional Scaling

Multidimensional scaling using Guttman‘s method was accomplished in 22 iterations with a stress of 0.086 and accounting for 96.6% of the variation (see Fig. 7). Four samples are identified as possessing little affinity to the other samples included in this analysis. These include the Namazga V prehistoric sample from Altyn Depe (ALT), which occupies an isolated position

89 in the upper center of the array, the Dravidian-speaking tribal Chenchus (CHU) in the lower left, and the two latest prehistoric samples from the Indus Valley- Timargarha (TMG) and Sarai

Khola (SKH)- found in the lower center. The remaining samples form regional aggregates that occupy distinct positions relative to samples from the other regions. Prehistoric samples from

Central Asia are found on the right side of the array and link to living Hindu Kush samples via the Khowars (KHO). The Yashkuns from Astore (YAS) possess closest affinities to the

Khowars, followed by the two Wakhi samples (WAKg, WAKs), who possess closest affinities to one another.

Prehistoric samples from the Indus Valley occupy the center of the array and are marked by distant affinities to the prehistoric sample from western peninsular India (Inamgaon: INM).

Samples of living peninsular Indians occupy the left side of the array, with the three Indo-Aryan- speaking samples from Gujarat (BHI, GRS, RAJ) possessing lower scores on the first dimension than their Dravidian-speaking caste counterparts from Andhra Pradesh (GPD, PNT). The exception to this observation is the Chenchu. This result may be due to the Chenchu being a phenetic outlier to the other southeast Indian populations due to their non-caste group status.

Multidimensional scaling using Kruskal‘s (1964) method was also calculated to determine whether the method of scaling had an effect on the interpretation of data (Fig. 8).

Kruskal‘s method was configured in 28 iterations with a stress of 0.069 and accounting for

96.7% for the variation. This analysis depicts identical affinities to those identified with

Guttmann‘s method. Isolation of groups by region and temporal period is apparent. The Yashkun from Astore (YAS) are identified by Kruskal‘s method as possessing even closer affinities with the Kho (KHO) than depicted using Guttmann‘s method. Secondary affinities are still observed

90 between the Yaskhuns of Astore and the two Wakhi samples (WAKg, WAKs). The prehistoric samples from Altyn Depe (ALT), Timargarha (TMG), and Sarai Khola (SKH), as well as the

Dimension Three

Figure 7. Multidimensional Scaling using Guttman‘s (1968) Method.

tribal Chenchu (CHU)of northern Andhra Pradesh, still occupy isolated positions, affirming the fact that they possess little affinities to any of the other samples included in the study. Prehistoric samples from Central Asia are also located on the right side of the array and are linked to the living Hindu Kush samples via the Kho (KHO). The prehistoric Indus Valley samples are still distantly linked to the prehistoric peninsular Indian sample from Inamgaon (INM) in the center

91 of the array. The living peninsular Indian samples are located on the left side of the array and share the same affinities as described for Guttmann‘s method.

YASa Dimension Three

Figure 8. Multidimensional Scaling using Kruskal‘s (1964) Method.

Principal Co-ordinates Analysis

Principal co-ordinates analysis yields three axes that combine to account for 87.5% of the total variance among samples (Fig. 9). The patterning of inter-sample affinities is similar to the results yielded by multidimensional scaling; however, there are some notable differences. Once again, the two latest prehistoric samples from the Indus Valley – Timargarha (TMG) and Sarai

Khola (SKH)- which are found in the lower center of the array, are identified as possessing similarities to one another, but to no other samples included in this analysis. Similarly isolated phenetic positions are occupied by the inhabitants of Madak Lasht (MDK) and Swatis (SWT) in the upper center, as well as the Dravidian-speaking tribal Chenchus (CHU) in the center.

Prehistoric Central Asians are found on the left side of the array and the Kho (KHO) of the

Hindu Kush highlands are identified as possessing closest affinities to them. The Yashkuns of

Astore (YAS) occupy a phenetic position on the left side of the array that is equidistant from the

Kho (KHO) on the one hand and the Wakhi sample from Sost (WAKs) on the other. Living ethnic groups from peninsular India are found in the center-right. The two Hindu caste samples from Andhra Pradesh (GPD, PNT) exhibit close affinities to one another, while affinities among the three samples from Gujarat (BHI, GRS, RAJ) are more diffuse. Once again, the prehistoric sample from Maharashtra (INM) shows no affinities to living peninsular Indians. Instead, it is marked by distant affinities to prehistoric inhabitants of the Indus Valley.

MDK

GRS Axis Three Axis

Figure 9. Principal Co-ordinates Analysis.

Chapter 11: Discussion

The intent of this research has been to utilize quantifiable phenetic data to address questions concerning human migration and habitation in South Asia over the course of the last several millennia. Specifically, this study provides an analysis of a modern Pakistani ethnic group (the

Yashkuns of Astore) in terms of their own population history and whether they represent a distinct phenetic group unto themselves or whether they share close biological affinities to other populations residing in the highland regions of northern Pakistan.

As noted in Chapter 1, there are several competing theories that seek to account for Yashkun origins. These include Dani (2001) and Leitner‘s (1866) assertion that the Yashkun are the descendants of a long-standing indigenous population of the Karakoram highlands, as well as

Drew‘s (1876) contention that the Yashkun represent relatively recent immigrants to the

Karakoram highlands from peninsular India. These hypotheses are tested using biological data in the form of odontometrics. Furthermore, this data is used to extrapolate piecing together not only the population history of the Yashkun, but to provide insight into the four competing population history models for South Asia. The comparison of biological data through the use of odontometrics allows for additional insights through previous hypotheses created using linguistic, archaeological, and historical data. Several research questions were posed to assess the region‘s population history. These research questions are as follows:

1) The Aryan Invasion Model: Are the Yashkun descendants of Indo-Aryan-speaking populations who migrated from Central Asia to the Hindu Kush and Karakoram highlands during the 2nd millennium B.C.?

H01: The Yashkun are not descendants of Indo-Aryan-speaking populations who migrated from Central Asia during the 2nd millennium B.C. (YASa ≠ SAP, DJR, KUZ, MOL, GKS, ALT).

If the Aryan Invasion Model is supported, the Yashkun should possess affinities with living descendants of Indo-Aryan Central Asian populations and to ancestral prehistoric Central Asian samples. Within the hierarchical cluster analysis, there is a distinct split between the Hindu Kush and Karakoram highlanders and prehistoric Central Asians versus the prehistoric samples from the Indus Valley and both modern and prehistoric samples from peninsular India. The Yashkun show close affinities with the Kho and secondary affinities to Djarkutan period inhabitants of

Djarkutan, located in southern Central Asia and representing one of the urban centers of the

Bactrian-Margianan Archaeological Complex (BMAC). More distant affinities are observed between these groups and the two Wakhi samples, and even more distant affinities with the other prehistoric Central Asian samples. In formulaic form, the results obtained by hierarchical cluster analysis may be represented by YAS ≈ KHO, DJR> WAKs, WAKg> MDK, SWT, CHU, ALT.

Neighbor-joining cluster analysis also reveals an aggregation of prehistoric Central

Asians, with the Kho continuing to express peripheral affinities to these Central Asians.

However, in this analysis, the Yashkun are grouped into a separate aggregate with both Wakhi samples. Distant secondary affinities are observed among the prehistoric Central Asians. The results obtained from neighbor-joining cluster analysis may be represented by the following equation: YAS ≈ WAKs, WAKg, ALT, DJR, KHO, GKS, SAP, KUZ, MOL.

Both methods of multidimensional scaling yield regional aggregates. Once again, prehistoric Central Asians are linked to the Hindu Kush/Karakoram highland samples via the

Kho. The Yashkun share closer affinities to Kho than to either prehistoric Central Asians or the

Wakhi. Multidimensional scaling describes the affinities of the Yashkun as: YASa ≈ KHO, DJR,

SAP, GKS, MOL, KUZ.

Principal co-ordinates analysis also separates aggregates based on regions. Prehistoric

Central Asians are again identified as possessing affinities to ethnic groups occupying the Hindu

Kush/Karakoram highlands via the Kho. The Yashkun are identified as possessing equidistant affinities to both the Kho and the Wakhi sample from Sost. Principal co-ordinates analysis is represented by YASa ≈ KHO, WAK>, WAKg> DJR, MOL.

While there does seem to be a relationship between prehistoric Central Asians and the sampled ethnic groups from the Hindu Kush/Karakoram highlands, and hence the Yashkuns, it is more interesting to note that every analysis is grouped based upon temporal period and geographic region. Hemphill (1991) posits that geography is a greater factor in phenetic affinities between ethnic groups than other typically associated indicators including social status or language. Such patterning appears to be yielded by all the multivariate analyses conducted here, especially considering the diverse backgrounds of each of the highland groups. While other studies, such as those by O‘Neill (2012) and Willis (2010), also show the Kho to consistently express close affinities to the prehistoric Central Asian samples, especially those from the North

Bactrian oasis of southern Uzbekistan, Blaylock (2008) concluded that the Kho are recent migrants into the Hindu Kush highlands. This, in conjunction with the current study, does support Blaylock‘s contention that the Khowar are, in fact, migrants from Central Asia.

However, given the fluctuating affinities of the Yashkuns of Astore between the Kho on the one hand and the Wakhi on the other, such affinities suggest that the Yashkun are more likely being grouped with samples with whom they share geographic proximity while nevertheless

97 maintaining a phenetically distinct identity. For the Yashkun to be immigrants into the region, as well as descendants of prehistoric Central Asians, as suggested by proponents of the Aryan

Invasion Model, the multivariate bio distance analyses ought to have identified more consistent and proximate affinities between the Yashkuns of Astore and the prehistoric Central Asian samples, especially those stemming from the BMAC urban centers of southern Uzbekistan, their alleged ―source‖ population of these ―Aryan invaders.‖ This is just this scenario that is represented by the hypothesis Ha1: YASa ≈ KHO > WAKg, WAKs, SWT, MDK > SAP, DJR,

KUZ, MOL, GKS, ALT > TMG, SKH> BHI, GRS, RAJ > NeoMRG, ChlMRG, HAR, TMG,

SKH, PNT, GPD, CHU, INM. However, such close secondary affinities with these prehistoric

Central Asian samples were not identified.

Furthermore, for the Aryan Invasion Model to be fully supported, the prehistoric Central

Asian samples ought to have been identified as showing consistently close affinities of the post-

Harrappan samples of the Indus Valley (Timargarha and Sarai Khola) as well as to the modern

Indo-Aryan-speaking ethnic groups of western peninsular India. While the Yashkun do share some affinities with prehistoric Central Asian samples, these affinities are not close and therefore, the Aryan Invasion Model is not supported by this study.

2) Long-Standing Continuity Model: Are the Yashkun descendants of a long-standing isolated, indigenous population residing within the Hindu Kush/Karakoram highlands?

If the Yashkun represent an isolated indigenous population, as originally claimed by Dani

(2001), then such an identification would be consistent with the expectations of the Long

Standing Continuity Model. If this scenario is supported, the Yashkun should show closest affinities to samples that are both temporally and geographically most proximate to them.

Therefore, closest affinities should be with the Wakhi, followed by the Kho, and possibly with the inhabitants of Madak Lasht (see below) coupled with even more tenuous and distant affinities to the Swatis. Closest affinities should be shared with the Wakhi due to the closest geographic proximity between these ethnic groups residing within the Karakoram highlands. The Kho are located primarily within the Hindu Kush highlands of Chitral District, Khyber Pakhtunkhwa and the western portion of the Gilgit Division of Gilgit-Baltistan. The Madak Lasht on the other hand not only reside in a single village and practice endogamy, but they also claim to be relatively recent immigrants (c. 400 years) to Chitral District from their ancestral home in Nuristan, located further to the west in northeastern Afghanistan. Therefore, it is unlikely that close affinities would be observed with other Hindu Kush/ Karakorum highland populations. The Swatis are located within Mansehra District, which is a great distance from the Yashkun occupation of the

Astore Valley across extremely rugged terrain. As such, when coupled with the possibility that the Swatis themselves may be immigrants whose ultimate homeland is to be found in southern

Afghanistan, it is unlikely for close affinities will be found between the members of these two populations.

The Long Standing Continuity Model would be further supported if the Yashkun then showed a divergence from prehistoric and living samples from peninsular India. Members of each regional aggregate ought to show closest affinities to one another, coupled with secondary affinities to members of other aggregates that are closer geographically. The Long Standing

Continuity Model would be expected to share the closest affinities as follows: YASa ≈ WAKg,

WAKs> KHO, MDK> SWT >NeoMRG, ChlMRG, HAR, TMG, SKH ≠ RAJ, GRS, BHI, PNT,

GPD, CHU, ALT, GKS, SAP, DJR, KUZ, MOL, INM in order to support the model.

Based on all four multivariate analyses, the Yashkun do show close affinities to the other samples of living inhabitants of the Hindu Kush and Karakoram highlands and as expected, both neighbor-joining cluster analysis and principal co-ordinates analysis indicate that of these highland groups, the Yashkuns of Astore possess closest affinities to their Karakorum highland co-residents, the Wakhis. However, contrary to expectations, both multidimensional scaling and hierarchical cluster analysis identify that Yashkuns from Astore possess closest affinities, not to their co-residents of the Karakoram highlands, the Wakhis, but with the geographically more distant occupants of the Hindu Kush highlands, the Kho. Still further, the expected affinities towards their alleged ancestors within the Indus Valley are not observed among any of the analyses. Distant affinities toward other Indo-Aryan speaking groups, such as those within north

India (BHI, GRS, RAJ) were also never depicted in any of the analyses. As such, the Long

Standing Continuity Model is not supported by this study.

3) Early Entrance Model: Are the Yashkun descendants of a population associated with the introduction of Proto-Elamo-Dravidian languages into South Asia between 6,000 and 4,500 B.C.?

Ha3: The Yashkun are descendants of a Proto-Elamo-Dravidian speaking populations from India between 6,000 and 4,500 B.C. (YASa ≈ PNT, GPD, CHU >GKS, ALT, SAP, DJR, KUZ, MOL, SKH, TMG > RAJ, GRS, BHI >WAKg, WAKs, KHO, MDK, SWT ≠ NeoMRG, ChlMRG, HAR, INM). Proponents of the Early Entrance Model suggests that South Asia witnessed a significant influx of immigrants of Proto-Elamo-Dravidian speakers at some point between the 5th and 7th

100 millennia BC whose ultimate origins may be traced to southwestern Iran. If the Early Entrance

Model is true, the Yashkun should show close affinities to other Dravidian-speaking populations as well as to prehistoric samples from the Indus Valley and Central Asia that post-date this immigration event, coupled with little to no affinities to prehistoric Indus Valley samples that antedate the immigration event (i.e., Neolithic Mehrgarh) or to samples from western peninsular

India. This would be best represented by affinities following this expectation: YASa ≈ PNT,

GPD, CHU >GKS, ALT, SAP, DJR, KUZ, MOL, SKH, TMG > RAJ, GRS, BHI >WAKg,

WAKs, KHO, MDK, SWT ≠ NeoMRG, ChlMRG, HAR, INM.

While the Yashkun show closest affinities to other ethnic groups of the Hindu Kush and

Karakoram highlands, these regional populations show secondary affinities to prehistoric Central

Asians (except for the highly anomalous tribal Chenchu). Within the hierarchical cluster analysis, there is a separation in affinities between the prehistoric Central Asian samples and

Hindu Kush/Karakoram highlanders and southeastern Indian samples; that could offer some support for the Early Entrance Model. However, the prehistoric Indus Valley and western India samples do not show any affinities towards the Yashkun or other Hindu Kush highland populations.

Neighbor-joining analysis, multidimensional scaling analysis, and principle co-ordinate analysis also fail to depict affinities between the Yashkun and prehistoric Indus Valley samples.

Affinities among the western Indian populations, the prehistoric Indus Valley, and the Yashkun are also absent in these analyses. Therefore, the Early Entrance Model is not directly supported by this study.

4) Are the Yashkun descendants of populations that migrated to northwestern South Asia in the historic era?

101

H04: The Yashkun are not descendants of populations that migrated to northwestern South Asia in the historic era (YASa ≈ NeoMRG, ChlMRG, HAR, TMG, SKH).

Ha4: The Yashkun are descendants of populations that migrated to northwestern South Asia in the historic era (YASa ≠ NeoMRG, ChlMRG, HAR, TMG, SKH>PNT, GPD, CHU). If the Historic Era Influences Model is true, then the Yashkun, as well as the other living ethnic groups found in the rugged highlands on the extreme northwestern periphery of South

Asia, should not be closely related to other South Asian populations. This can be further emphasized with the members of the modern ethnic groups residing within the Hindu Kush and

Karakoram highlands expressing diverging affinities from prehistoric populations, which would distinguish the mechanism for peopling of the region from the Long-Standing Continuity Model.

The Historic Era Influences Model would best explain the locations of contemporary populations if the analyses revealed the following YASa ≠ NeoMRG, ChlMRG, HAR, TMG, SKH>PNT,

GPD, CHU. The Yashkun consistently showed diverging affinities from prehistoric Indus Valley populations in all analyses.

The Historic Era Influences Models best describes the patterning of affinities possessed by members of the living populations within the rugged Hindu Kush and Karakoram highlands of northern Pakistan considered here. These ethnic groups show closer affinities towards each other, but not with geographically similar populations dating to earlier periods. This is indicative of more recent population movement that is not associated with the earlier prehistoric inhabitants. The results of this study offer greatest support for this model, for the Yashkuns and the other samples of living ethnic groups of the Hindu Kush and Karakoram highlands are marked by no direct affinities to any prehistoric or living samples from South Asia; except for the Kho, who in turn show close affinities to prehistoric Central Asian samples. With the distant

102 affinities based upon geography, yet consistent temporal aggregates, this study seems to support the historic migrations of populations within the region. This is especially evident when comparing the results to other factors, such as language. The Yashkun possess closest affinities to other living ethnic groups of the Hindu Kush and Karakoram highlands, especially with the

Kho, who also speak a Dardic language, but also with the Wakhi, who speak an Indo-Iranian language. While the language family is not a consistent predictor of phenetic affinities, geographic proximity remains the consistent factor in predicting the results of the multivariate analyses.

While there are some affinities among the Hindu Kush highland populations, they are not as closely related as would be expected based upon the other models if the region was populated by immigrating populations under any theory. When incorporating other ethnic groups of the

Hindu Kush and Karakoram highlands, such as the Shina, in addition to the Wakhi and Burusho,

O‘Neill (2012) also found no consistent patterning of phenetic affinities among these ethnic groups. Modern migrations seem apparent. These affinities do not support the Yashkun being an immigrant population from Central Asia (as claimed by Leitner (1866), Drew (1875) and

Gankovsky (1973)). Dani‘s (2001) assertion that the Yashkun are indigenous to northern

Pakistan seems to be supported in that there are no samples within the study that definitely suggest a prehistoric migration. However, the antiquity of the Yashkun is uncertain due to the lack of affinities towards prehistoric Indus Valley samples. Therefore, historic era migrations seem to be the predominant factor.

By continuing with the use of phenetic indicators in analysis by including more samples from within the Pakistani region, the origins of the Yashkun may be more specifically identified.

The comparison of biological data in conjunction with other lines of evidence, such as

103 linguistics, archaeology, and historical data can continue to build a more accurate and complete picture of the human past and population migrations within South Asia.

104

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117

Appendices

118

Appendix A Euclidean Distances

119

ALT BHI CHLMRG CHU DJR GRS GKS GPD HAR INM KHO KUZ MDK MOL 0.000 3.890 0.000 4.225 2.584 0.000 3.703 2.845 3.558 0.000 3.769 3.873 3.105 3.223 0.000 3.780 1.434 2.854 2.660 3.609 0.000 4.589 4.215 3.500 3.811 2.657 3.942 0.000 3.953 2.099 2.489 2.811 3.795 2.012 3.909 0.000 4.303 2.844 2.613 3.266 3.614 3.090 3.838 2.764 0.000 5.244 2.911 2.813 4.044 4.400 3.402 4.687 3.001 2.581 0.000 3.216 3.337 2.972 2.912 1.972 2.938 2.534 3.273 3.574 4.481 0.000 4.548 4.512 3.688 3.799 3.460 4.411 2.978 3.951 3.504 4.412 3.305 0.000 3.496 2.710 2.349 2.379 2.513 2.573 2.902 2.388 2.545 3.337 2.196 2.984 0.000 4.331 4.312 3.229 3.927 2.859 4.258 2.732 4.105 3.642 4.667 2.652 2.371 2.678 0.000 3.873 2.111 1.668 2.889 2.828 2.403 3.027 2.325 2.298 2.747 2.752 3.249 1.937 3.083 4.006 2.111 2.441 2.474 3.336 1.952 3.637 1.005 2.476 2.676 3.043 3.704 3.056 3.862 3.628 1.926 2.887 2.257 3.384 1.405 3.937 1.717 2.918 3.343 2.956 4.250 2.264 4.094 3.935 3.950 3.185 3.444 2.321 3.808 1.883 3.910 3.595 4.692 1.935 2.541 2.683 1.982 4.550 3.090 3.098 3.283 3.061 2.982 2.791 3.556 2.859 3.887 2.723 3.617 2.533 3.189 3.140 2.287 2.398 2.221 2.634 2.016 3.343 1.992 2.847 3.530 2.234 3.573 1.453 3.212 4.944 3.379 3.134 3.297 3.626 3.580 3.402 3.346 2.309 3.521 3.422 3.028 2.892 3.344 2.925 2.940 2.81 2.698 2.356 2.669 3.235 2.782 3.677 4.293 2.086 3.875 2.152 3.138 2.871 2.907 2.778 2.625 2.147 2.709 3.148 2.999 3.607 4.263 1.899 3.548 2.097 2.810 3.136 3.962 3.809 2.893 2.507 3.412 2.675 3.495 4.116 5.279 1.856 3.536 2.526 3.254

120

NEOMRG PNT RAJ SAP SKH SWT TMG WAKG WAKS YASA

0.000 2.205 0.000 2.530 1.333 0.000 2.763 3.675 3.789 0.000 2.231 3.321 3.210 2.520 0.000 2.063 1.668 1.635 3.141 3.096 0.000 2.621 3.120 3.436 2.888 2.313 3.428 0.000 2.657 2.592 2.358 2.847 3.477 1.473 3.901 0.000 2.529 2.771 2.458 2.458 3.206 1.724 3.566 0.874 0.000 3.379 3.348 3.199 2.351 3.419 2.524 3.957 2.064 2.098 0.000

121

Appendix B Odontometric Measurements of Yashkun

122

SpNo Sex LM2MD LM2BL LM1MD LM1BL LP4MD LP4BL LP3MD LP3BL LCMD LCBL LI2MD LI2BL LI1MD LI1BL UI1MD UI1BL UI2MD UI2BL UCMD UCBL UP3MD 1 M 11.3 10.6 6.4 9 6.5 8.3 6.5 8.2 6 6.4 5.1 6 8.1 8.1 6.7 7 7.8 8.3 6.5 2.1 M 9.2 11 11.5 10.8 5.5 7.9 6.5 7.9 6.8 8.8 5.8 7 5.1 6.1 7.4 6.1 8 5.8 2.2 10.9 10.3 6 8.1 6.2 7.7 6.3 6.7 5.3 4.9 3 M 10.2 11 10.6 6.7 8.3 7.1 8 7.3 8 7.8 7.4 6.7 7.5 8.4 6.6 4 M 11.4 11.6 11.1 7.1 9 6.9 7.8 7.7 8.2 8.6 8.7 6.8 6.6 8.2 6.9 5 M 10.1 10.6 11 10.7 7.1 8.3 6.6 8.1 7 8.2 6.1 7 6.5 8.8 7.3 7 6.2 7.6 8.1 6.6 6 M 11.4 6.5 7.6 6.4 7.1 7.3 5.6 4.6 5 4.8 8.5 7.7 6.3 6.7 7.6 7.9 6.7 7 M 11 10.3 6.8 8.9 7.6 8.3 6.8 7.2 4.7 6.5 6.7 7.5 5.3 7.4 8.8 6.9 8 M 11.5 10.6 12.1 10.7 6.8 9.3 6.4 8.4 6.5 9.3 5.2 7.1 4.9 5.3 8.3 6.5 7.5 6.9 9 M 10.5 6.7 8.6 6.4 8 6.6 8 5.9 6.7 5.1 6.6 8.1 6.5 6.4 7.6 8.5 6.6 10 M 9.8 10.3 10.4 6.9 9.3 6.8 9 6.4 7.5 4.9 6.8 4.8 6.5 7.9 6.3 7.1 6.7 11.1 M 11.8 6.5 8.7 6.7 7.9 6.7 8.3 5.6 5 8.4 8.3 7 8.2 8.3 10.2 7.2 11.2 10.3 9.7 11 10.3 6.2 7.7 5.6 7 6.5 7 5.2 5.3 11.3 10.6 10.2 6.1 8.3 6.7 7.6 6.1 7 5.3 5.8 4.8 5.8 12 M 10.5 11.6 10.5 7.1 8.8 6.7 7.7 6.1 6.9 5.6 7 5.5 6.2 8.9 6.9 7.6 7.5 6.8 13 M 11.6 8.5 11.3 10.3 6.3 8.1 6.2 8 6.3 8.1 5.3 4.7 7.9 8.5 6.3 6.9 7.8 6.6 14 M 11.5 11.2 6.7 8.3 6.5 8 6.2 8.4 5.6 7 5.1 6.8 9.1 8 6.6 7.9 7.6 9 6.3 15 M 8.6 6.2 7 6.7 16 M 10.4 10.8 11 10.8 5.9 8.9 6.4 8.8 4.3 8.1 5.4 6.9 8.2 6.5 17 M 10.1 10.5 11.1 6 6.6 6.3 6.9 5.8 6.6 4.7 5.6 4.1 5.4 8.2 6 5.2 5.9 6 5.9 18 M 9.9 10.1 11.1 10.5 6.7 6.9 6.3 6.9 6 5.2 5.9 4.9 5.9 8.1 6 7.1 6.1 19 M 9.6 9.1 9.6 10.1 6.4 7.7 6.1 7.4 6.5 7.9 5.7 6.7 4.2 6.5 7.7 8.4 6.6 6.8 7.8 9 6.8 20 M 9.9 10 10.9 10.2 6.3 8.3 6.2 7.5 6.1 6.9 5.5 6.4 5 5.8 7.9 7.3 6.5 7 7.7 7.5 6.5 21 M 9.8 10.9 10.1 6.2 7.5 6.3 7.6 6.4 7.5 5.5 6.9 4.9 6.6 7.4 5.9 22 M 11.3 11.7 6.4 9.3 6.8 8.6 7.1 9.3 6.7 5.6 9.2 7 8.2 10.3 6.1 23 M 10.1 10.4 11.2 10.6 5.9 8 6.2 7.3 6.3 7.4 5.5 5.4 8.5 6.3 5.5 6.5 7.3 5.9 24 M 8.7 9.9 9.8 9.6 5.9 7.4 6.3 7.4 5.8 7.2 4.2 5.8 4.9 5.6 7.9 6.5 6.7 5.9 7 7.7 6.2 25.1 M 9.8 9.9 9.7 10.2 5.6 7.8 6.5 7.6 6.3 7.4 4.9 6.4 4.3 6.5 7.9 5.6 7 6.3 25.2 10.7 10.5 6.5 7.7 6.6 8.1 6.6 6.9 5.9 6.6 4.5 26 M 9.3 11.4 11.3 7 9.5 7.1 8.6 7.2 8.3 5.6 6.7 6 6.4 9.8 6.1 7.3 8 9.3 6.7 27 M 11.2 11.3 10.5 11 7.4 8.6 7.5 8.6 6.6 8 6.3 7.6 5.6 7.3 8.7 6.9 7.1 6.9 28 M 10.1 9.8 10.6 10.5 6.1 8,6 6.5 7.9 6 6.8 5 6.5 4.8 6.2 8.2 7.7 7 6.8 7.1 8.3 6.2 29 M 10.2 9.9 10.8 10.3 6.8 8.2 6.9 7.7 6.5 6.9 6.3 4.8 6.1 8.5 7.4 6.4 5.7 6.6 6.2 7.3 123

SpNo Sex LM2MD LM2BL LM1MD LM1BL LP4MD LP4BL LP3MD LP3BL LCMD LCBL LI2MD LI2BL LI1MD LI1BL UI1MD UI1BL UI2MD UI2BL UCMD UCBL UP3MD 30 M 10.9 6.2 5.8 6.3 7.5 7.3 5.7 6.6 6.2 7 5.5 31 M 9.8 10.9 10.9 11.2 6.3 8.2 6 7.7 6.2 7.8 4.6 6.5 4.5 5.8 8 8.2 4.9 6.3 6.6 5.9 32 M 10.2 9.4 9.2 7.1 7.5 6 6.2 5.6 4.8 7.9 8.7 6.8 6.5 7.3 6.7 6.2 33 M 10.9 10.6 11 6.8 9 6.9 8.6 6.6 8 5.5 6.6 4.9 6.7 8.3 8.4 6.3 6.4 7.2 8.8 6.9 34 M 10.4 11.3 11.7 11.2 6.5 8.5 6.2 7.9 6.7 7.8 5.5 6.2 5.4 6.7 8 6 7.2 8.2 6.4 35 M 10 10.1 10.1 10 6.1 8.1 6.1 7.7 6.3 7.6 5.8 5.9 5.6 6.1 7.7 7 6.3 6.7 8.5 5.5 36 M 6.1 6.7 4.8 6.7 4.3 7.2 6.9 6.8 5.6 5.4 6.8 7.8 6.4 37 M 10.3 10.7 10.8 11 6.6 8.5 7.2 8.4 5.5 7.5 5.6 5.7 5 6.6 7.8 8.3 6.6 6.5 6.5 38 M 10.7 10.1 6.1 7.6 5.7 7.2 6.9 6.6 8.3 6.4 7.1 5.7 39 M 10.8 10.6 6.6 8.5 6.4 8.1 7.3 5.7 6.9 4.9 6.3 7.7 5.8 6.4 7.5 7.3 6.7 40 M 8.7 9.9 10 10 5.9 8.5 6.2 8 6.5 8.3 5.7 6.6 5.2 6.1 8.2 7.1 6.7 6.6 7.6 5.9 41 M 10 10 11.1 10.2 6.5 8.2 6.7 6.2 5.8 6.8 5 6.5 7.9 7.3 6 7 7.4 8.2 6.5 42 M 9.4 10 10.6 10 5.8 8.1 8 6.1 7.7 5.6 6.4 5.2 7.7 6.7 7.5 8.9 6.2 43 M 8.8 9.9 10.9 10.1 5.6 8.7 6 7.7 6.2 6.6 5.3 6.2 4.3 5.6 44 M 8.3 6.7 7 7.6 5.8 6.9 5.1 5.8 8.9 7.5 5.8 6.7 8.1 9.2 6.9 45 M 10.1 10.5 11 10.4 6.6 8.7 6.7 7.6 5.7 5 5.5 5.6 4.9 5.7 7.4 6.1 7.3 46 M 10.7 11.2 11.2 11.3 6.6 9 6.6 8.2 6.3 8 5.4 6 5.3 6.3 7.8 6.5 6.7 7.2 8.4 6.7 47 M 10.1 9.2 10.6 10 5.7 7.3 6.2 6.7 6.2 7.5 5.6 6.2 4.8 6.5 8.5 6.8 6.3 5.8 7.6 8.6 5.9 48 M 11.3 9.9 7.4 7,7 7.2 7.6 6.9 7.9 5.7 4.8 7.1 6.3 7.2 8 49 M 10.6 11.5 10 7 8.4 7.2 8 6.4 9.9 6.2 9.2 5.5 7.5 8.7 6.6 7.6 8.5 6.5 50 M 9.2 10.6 6.6 8.6 6.2 7.9 6.7 7.4 5 6.4 4.6 6.5 7.5 6.1 6.7 6.8 7.6 8 6.6 51 M 9.7 9.7 10.7 9.8 6.3 8.4 6.5 8.1 6.4 8.2 5.2 8 4.2 7.6 8.3 8 5.7 7.5 8.3 6.1 52 M 10.3 10.3 11.5 10.4 6.6 8.8 6.7 7.4 6.4 7.4 5.1 5.9 4.7 5.7 8.2 7.2 5.1 6.2 7.2 8.3 6.6 53 M 10 9.7 9.6 10.2 5.8 8.2 5.9 8.2 6.1 8.2 4.8 6.3 4.7 6.3 7.6 7.7 5.9 6.7 7.3 8.4 6 54 M 9.1 10 10.9 9.3 6.4 7.2 6.1 6.9 6.3 7.7 8.1 5.6 6.4 7.5 5.9 55 M 11 11.2 11.9 11.1 6 8.5 6.4 8.6 6.8 8.2 5.4 6.8 4.8 6.3 6.7 5.4 5.9 7.9 7.3 9.2 6.5 56 M 8.8 10.1 9.7 9.9 6.2 8.2 6.2 7.9 6.1 8 4.8 6.4 4.8 6.7 7.3 6.3 6.8 5.9 57 M 10.9 10.6 11.6 10.8 7.1 8.6 6.6 7.7 6.5 6.7 5.1 6.3 5.5 6.4 9 8.8 5.9 7.5 8 8.8 6.7 58 M 10 10.7 11.1 6.5 9.5 6.4 8.2 6.4 8.5 5.5 7.4 4.3 6.6 7.7 7.3 6.2 6.8 7.3 7.9 6.2 59 M 11.8 10.8 6.7 8.8 6.4 7.5 6.7 7.8 5.8 6.6 5 6.6 7.9 6.5 60 M 10 11.7 11.9 7.3 8.7 6.5 8.2 6.4 5.9 5.4 5.6 6.4 5.5 7.5 8.2 6.6 61.1 M 11.4 10.8 6.1 8.5 6.2 7.6 6 7.5 4.9 6.3 7.5 6.4 5.7 6 6.9 7.7 6 61.2 9.8 10.3 10.2 10.5 6 7.9 6 7.3 6.4 6.7 5.2 6.4 4.5 6.5 124

SpNo Sex LM2MD LM2BL LM1MD LM1BL LP4MD LP4BL LP3MD LP3BL LCMD LCBL LI2MD LI2BL LI1MD LI1BL UI1MD UI1BL UI2MD UI2BL UCMD UCBL UP3MD 62 M 11.1 10.5 7 8.2 7 8.1 6.8 7.4 5.4 6.7 5.2 6.8 7.8 8.1 6.7 7 8.1 7.7 6.5 63 M 10 10.8 10.9 6 9.2 6.8 8.7 6.5 7.8 5.6 7.8 5.1 7.5 8.3 7.2 6.2 6 7.1 8.9 6.6 64.1 M 9.7 10.9 10 6 8.7 6 7.6 6.4 6.5 6.2 5.9 64.2 7.2 7.9 5.6 7.4 7 8 5.4 65 M 10.7 8.5 6.6 7.5 6.3 8.2 6 7 6 6.5 5.5 9.1 7.7 6.7 6.6 6.9 7.7 6.9 66 M 9.8 10.8 10.1 10.9 6.1 8.5 6.9 8.7 5.9 7.9 5.6 7.5 4.9 7.7 67 M 10.8 11.1 6.6 8.8 6.4 8 6.1 7 5.6 5.8 5 5.5 8.3 7.1 6.4 6.3 6.8 68 M 11.3 10.8 6.2 8.8 6.8 8.2 6.9 7.4 6.1 5 6.1 9 6.6 5.9 5.9 8.3 7.1 69 M 11.2 9.3 6 7.6 5.8 7.5 5.9 5.8 5.7 8.7 7.3 5.9 6 6.8 7.5 6.3 70 M 10 9.7 9.9 9.9 5.9 7.5 6.2 6.9 6.5 6.7 5.8 7.1 4.8 5.9 8.7 7.1 6.7 6 7.7 7.8 6.3 71 M 8.8 10.2 9.4 10.7 6 7.9 6.9 7.7 6.9 7.4 5.8 5.1 5.5 8.2 7.5 7.8 9 6.5 72 M 11.1 10.4 6 8 6.6 7.6 6.2 6 5.2 6.5 4.6 6.1 6.3 7.2 7 8.2 6.5 73 M 10.9 11 10.8 6.8 8.7 6.5 8.3 5.6 5.6 6.3 5 6.2 8.7 8.1 6.4 6.2 7.2 7.5 6.9 74 M 75 M 10.3 11.1 10.9 6.4 9 6.9 8.3 6.6 8.3 5.8 6.9 4.8 6.1 8.1 8.2 6 6.2 7.7 9.4 6.6 76 M 10.6 10.5 7.8 6.3 8.4 6.6 7.2 6.5 77 M 10.4 10.3 6.4 8.1 6.2 7.8 7.7 5.6 6.5 5 7.2 7 5.8 6.5 7 7.7 6.4 78 M 6.8 6.3 79 M 7.9 7.7 6.4 5.4 6.6 80 M 10.5 10.7 6.4 7.8 5.9 7.4 6 6.7 5.1 6.2 4.3 5.9 8.2 8.2 6.4 6.8 7.7 9.2 6.7 81 M 9.1 10.4 10 6.5 7.2 6.7 8 6.3 6.6 5.2 6.4 4.7 5.9 8.3 6.8 6.6 7.2 7.8 7.7 6.6 82 M 9.5 9.7 10.3 5.7 8.3 6.2 8 6.5 5.8 6.8 5.1 7.2 8.3 6.6 6 4.7 7.3 6.9 6 83 M 10.4 11.5 11 6.5 8.6 6.4 7.8 6.2 7.6 5.9 5.2 5 4.5 7.2 6.8 6.7 6.8 6.6 84.1 M 8.1 6.9 6.4 6.2 7.6 8.7 6.8 84.2 7.9 5.5 5.8 6.4 7.5 6.2 85 M 12.8 11.7 6.7 8.8 6.5 7.8 6.2 7.4 5.8 6.4 5.7 6 9.3 6.3 7.5 6.3 86 M 87 M 10.8 10.2 11.8 10.6 6.8 8.5 6.8 7.9 7.1 6.7 5.6 6.5 9.1 8 7 5.6 8.1 8.1 88 M 11.2 10.8 6.5 8.5 6.6 7.5 6.7 7.1 5.8 5.7 5.5 5.7 9.7 7.1 6.9 7.9 8.9 6.6 89 M 8.8 9.7 11.1 9 5.7 6.5 6.2 6.9 6.2 6.5 5.2 6 4.5 5.8 90 M 9.5 10.4 9.5 10.4 5.9 7.5 6.2 6.5 5.9 6.4 5 4.9 4.6 4.7 7.8 6.9 6.3 6.1 7.4 8 6.3 91.1 M 9.1 9.5 11.3 10.4 6.2 8.6 6.8 7.5 6.2 6.7 5.7 5.9 91.2 9.8 10.2 11.7 10.1 6 8.1 6.3 7.9 6.8 6.1 4.6 6.7 125

SpNo Sex LM2MD LM2BL LM1MD LM1BL LP4MD LP4BL LP3MD LP3BL LCMD LCBL LI2MD LI2BL LI1MD LI1BL UI1MD UI1BL UI2MD UI2BL UCMD UCBL UP3MD 92 M 10.2 10.1 11.3 10.3 5.9 8.2 6 8 6.3 7.6 5.8 6.7 5.1 6.6 8.3 6.1 6.2 6.7 7.7 6.4

101 F 8.9 9.5 9.2 10.3 6 8.4 5.9 7.7 5.9 7.4 6.1 4.7 5.6 7.3 7 6.1 5.7 6.7 8.2 5.8 102 F 8.8 9.6 9.6 9.8 5.3 8 5.5 6.9 5.5 6.7 5.3 5.8 4.3 6.2 7.4 6.2 5.4 4.7 6.4 7.2 5.4 103 F 10 9.3 10 9.3 6.4 8.5 6.6 7.4 5.7 6.5 5 5.4 4.6 5.1 8.1 6.9 5.2 5.7 6.7 7.2 6.5 104 F 9.4 9.5 10.5 10.1 6.4 7.2 5.7 6.9 5.7 6.6 5.2 6 4.9 5.7 7.8 6 6.8 7.6 5.7 105 F 6 8.2 5.7 8.2 6 7.5 5.2 6 4.9 5.6 7.9 7.3 5.8 5.8 6.7 6.3 106 F 9.3 9.5 9.4 9.2 5.7 7.5 6.1 6.9 6 6.6 5.4 6.5 5 5.6 7.7 6.8 6.2 6.8 7.2 6.1 107 F 8.9 9.1 10.2 6.4 7.9 6.6 7.5 6.5 7.1 5.3 5.9 4.7 5.8 7 6.4 5.8 7.3 7.9 6.7 108 F 109 F 8.8 9.3 10.5 9.9 6 8 6.3 6.5 5.7 6.4 5 6 4.9 5.9 7.8 6.1 5.2 5.4 6.3 7.3 6.1 110 F 9.1 9.9 9.4 10.3 6.2 8.1 5.6 7.2 5.8 6.6 5.5 6.2 4.9 5.6 7.8 5.8 5.1 5.2 6.6 7.5 6 111 F 8 8.6 9.7 9.4 5.8 7.5 5.9 7 5.6 6.4 5.2 5.8 5.1 5.3 8.4 6.5 6.7 5.9 6.5 6.6 5.6 112 F 113.1 F 9.2 10.1 10.4 10.7 6.6 7.5 6.4 7.2 5.5 6.4 5 5.8 8 7.4 5.7 6.9 6.9 7.9 6.2 113.2 9.4 10.1 9.7 10.3 6.4 8.3 6.5 7.7 6.4 7.4 6.3 6.1 5.7 9.2 7.8 7.3 8.1 6.3 114 F 9.6 9.1 10.1 9.6 6.1 7.4 5.9 6.8 5.8 7.1 5.3 6.3 4.7 5.8 7.6 6.6 5 5.3 6.7 7.5 5.7 115 F 9.6 9.9 8.9 10.1 5.6 7.1 5.6 6.8 5.6 6.6 4.8 5.5 3.9 5.3 6.6 6.5 4.8 5 5.9 5.6 116 F 10.4 9.9 10.8 6.7 7.8 6.7 7.3 6 5.4 5.7 4.9 5.9 8.1 6.5 6 5.7 6.2 7.1 6.4 117 F 9.7 10.2 10.5 6.5 8.1 6.6 7.6 6.1 5.6 6.7 4.7 6.9 8.2 6.7 6.7 8.2 6.5 118 F 10.2 10.3 6.1 8.7 6.3 7.6 6.1 119 F 8.5 8.8 10.8 9.7 6.4 7.9 5.7 6.6 6.2 6.1 5.4 5.9 5 6.1 8.1 7.4 6.5 6.7 7 8 6 120 F 8.7 9.6 10.1 10.5 5.8 7.8 5.9 6.6 6.2 7.1 5 8.2 6.9 6.1 6 6.7 7.6 6 121 F 10.3 10.7 10.5 6.1 8.6 6.8 8.2 6.6 6.2 5.1 6.2 8.7 6.5 6.3 6.3 7.4 7.3 122 F 9.5 10.2 10 10.1 6.3 8.1 6.3 7.2 6 7.7 5.3 6.8 4.3 7 7.4 6.9 5.7 5.9 6.8 7.8 6.1 123 F 9.6 9.9 10.7 10.2 5.8 8 6.3 7.6 6.7 6.7 5.7 6 5 6 9 8.3 7.3 7.4 7.5 8.3 6.4 124 F 9.6 10.6 11 10.5 6.1 8 6.4 7.4 6.5 7.2 6.4 4.5 5.8 7.9 6.8 6.5 6.4 7.1 8.1 6.8 125 F 10.4 6.8 8.2 6.2 7.6 5.8 7 4.6 5.6 8.6 8 6.6 7.1 7.1 6.8 127 F 8.4 9.8 10.3 9.7 6.1 5.2 6.1 5.2 5.3 8.1 6.5 5.6 5.5 6.8 7.1 6.1 128 F 8.6 8.9 10 9.9 6.2 7.5 6.1 6.9 6.3 7.3 5.2 6.1 4.7 5.5 7.9 7.3 6.7 7 7.1 7.9 6.5 129 F 10.6 10.1 6.3 8 6.3 6.8 6.5 5.5 6.2 6.6 6.4 130 F 9.5 9.5 10.1 6.2 8.2 6.3 7.4 5.8 7.1 5 6 4.3 7.7 7.3 6 5.8 7.2 6.8 126

SpNo Sex LM2MD LM2BL LM1MD LM1BL LP4MD LP4BL LP3MD LP3BL LCMD LCBL LI2MD LI2BL LI1MD LI1BL UI1MD UI1BL UI2MD UI2BL UCMD UCBL UP3MD 131 F 9.2 9.3 10.3 10.6 6 7.9 6.3 7.3 6.1 7.2 5.3 6.2 4.8 5.8 7.8 7 6.8 5.5 7.2 7.7 6.8 132 F 8.9 10.2 10.6 11 6.2 9 6.6 7.7 6.1 6.9 5.3 5.6 4.7 5.3 7.5 6.8 6 6.7 6.9 6.6 133 F 9.6 10.7 11.4 11 6.8 9 6.7 8.3 6.7 7.5 5.8 6.3 5.3 6.4 8.7 8 7 6.7 7.3 8.7 6.5 134 F 9.4 10.4 10.3 10 5.8 7.8 6.4 7.2 5.9 7.1 5 6.3 4.7 6 8 6.9 6.1 6.2 6.8 7.8 6.4 135 F 10.9 10.8 6.9 6.7 8.2 6.6 7.1 6.7 8.5 7.7 7.4 6.8 7.7 7.4 6.6 136 F 9.4 10.7 10.5 10.9 8.4 6.3 8 6.8 5.9 5.5 6.7 6.9 5.1 5.8 6.5 7.2 6.1 138 F 9 9.8 9.5 9.5 5.8 7.7 5.7 6.6 5.1 6.3 4.4 5.4 3.9 5 7.1 7.1 4.9 5.9 6.5 5.7 139 F 9.9 9.4 9.3 9.3 6.3 8 6.6 7.5 5.5 5.7 5 5.3 4.1 5.1 7.2 5.9 6.7 6.3 140 F 9.5 9.2 9.4 9.5 6 7 6.4 6.5 5.6 7.2 4.9 6 4.6 5.7 7.8 6 5.5 5.2 7 7.2 5.9 141 F 9.3 9.6 10.2 9.8 5.8 7 6.1 7.5 6.1 6.9 6 7.5 6.5 5.6 5.5 7.3 7.4 6.1 142 F 10 10.3 10.3 10.5 6.2 8.3 6.3 7.8 6.3 7.5 5.4 5.9 6 7.4 7.4 6.3 143 F 9.1 9.7 10.2 10.2 6.2 7.9 6.3 7.1 5.5 6.1 4.7 4.7 4.5 3.9 7.6 6.6 5.7 5 6.9 7 6.2 145 F 8.9 10.9 10.7 6.4 8.2 8 7.3 6.6 4.7 6.3 8.4 7.1 6.7 6.8 6.8 7.9 6.2 147 F 8.3 9 9.8 10.2 6.4 8.2 6.7 7.9 6 5.4 7.5 7 6.5 6.4 7.1 7.5 6.7 152 F 10.1 6 8 6.3 7.4 6.1 7.3 5.6 4.8 8.1 7.9 5.6 6.5 7.2 8.2 6.6 153 F 9.3 10.8 9.9 10.5 5.8 7.9 5.5 7.5 5.5 7.1 6.3 6.1 6.5 5.7 6.5 7.2 6 154 F 10.1 11 10.9 11.3 6.5 9.1 6.9 8.6 6.2 8 6.1 6.7 5.3 6.5 8.5 7.5 6.8 6.7 7.4 8.7 6.7 155 F 10 11 10.9 11.2 6.3 9 7.1 8.9 6.3 7.8 6 6.7 5.2 6.4 8.6 7.5 6.6 6.7 7.3 8.7 6.7 156 F 10.2 10 6 7.4 6 7.1 5.3 5.9 5.6 5.3 7.1 6.2 4.9 5.6 6.2 5.7 5.9 157 F 158 F 9.2 9.9 10.4 10.3 5.6 8.4 5.9 7.8 6.1 7.8 5.6 6.1 4.9 6 8.2 7.4 6.3 6.3 7.2 8.3 6.6 159 F 9 9.5 9.7 9.9 5.4 8.3 6.4 7.7 6.2 6.7 4.7 5.8 5.6 7.2 6 6.3 7.4 6.4 160 F 8.7 9.4 9.2 10.1 5.6 7.7 6.2 6.8 6.9 4.9 6 4.6 5.5 7.6 5.6 5.4 7.1 7.2 6 161 F 8.8 9.3 10 9.7 5.6 7.8 5.8 7.1 5.8 7.1 5 6.1 4.1 5.7 7.1 6.7 6.1 5.8 6.5 5.7 162.1 F 10 9.3 10.3 8.2 6 7.1 6.2 6.2 6.6 5 6.1 4.8 5.8 162.2 9.6 10.1 6.1 8.1 6.3 7.6 5.8 6.8 5.2 6.2 5.8 163 F 6 6.2 7.1 5.6 6.5 4.8 5.8 4.2 5.4 7.4 6.3 5.1 6.7 164 F 8.9 10.3 10.4 6.6 8.6 6.7 8 4.3 8.4 6 6.8 6.7 165 F 9.6 10.8 7 8.1 6.5 7.6 6.7 7.7 5.8 6.5 5.3 6.5 8 7.4 6.3 7.5 6.8 166 F 11 10.8 6.4 8.1 6.3 7.3 6 4.8 4.7 8.4 7.1 6 167 F 8.4 8.9 10.2 9.6 5.9 7.3 5.7 6.4 6.4 5.6 5.4 7.7 7.6 5.5 6.7 7 5.8 168 F 8 9 9.8 9.4 5.7 7.4 5.6 7.1 5.7 4.5 6.8 4.6 5.7 7.5 6.2 6.3 5.1 169 F 9.4 9.5 9.6 9.6 6 7.5 5.7 6.8 6.8 5.8 5.5 7.7 6.7 5.6 6.1 6.8 7.4 6 127

SpNo Sex LM2MD LM2BL LM1MD LM1BL LP4MD LP4BL LP3MD LP3BL LCMD LCBL LI2MD LI2BL LI1MD LI1BL UI1MD UI1BL UI2MD UI2BL UCMD UCBL UP3MD 170 F 8.9 9.3 10.4 10.7 6.2 7.9 6.2 7.1 5.4 6.5 5 5.8 4.3 5.3 7.2 6.6 5.6 5.2 7 7.1 5.9 171 F 9 9.7 10.5 10.1 6.3 7.8 5.6 6.9 6 7.5 4.7 6.2 7.7 6.1 7 7.7 6.1 172 F 10.6 10.5 10.5 6.1 8.3 6.4 7.4 5.9 6.9 5.7 6 5.1 5.2 7.6 6.6 6 5.5 7.2 7.8 6.2 173 F 176 F 9.1 9.7 10.1 9.5 6.4 7.4 6.3 7.1 5.9 7 5.3 5.6 4.7 5 178 F 9.6 9.8 5.9 8.2 6.2 7 6.1 6.6 5.4 5.6 5 5.4 7.2 6.5 7 6.2 191 F 9.5 9.7 10.7 5.9 8.3 6 7.5 5.7 7 4.6 6.1 3.9 5.6 6.6 6.3 5.3 6.5 7.5 6.1 195 F 8.6 8.2 6.6 6.5 201 F 10.3 9.3 9.7 9 6.3 7.2 6.6 7 6 7.2 5.4 6 4.7 5.9 8.1 8.5 7.1 8 6.8 205 F 9.3 9.7 10 10.1 6.2 8.1 6.9 7.2 6.9 7.8 5.5 6.6 4.6 6.4 8.2 6.1 207 F 10 10.9 10.7 10.6 6.1 8.3 6.3 7.5 6.2 8 5.8 7.1

128

SpNo UP3BL UP4MD UP4BL UM1MD UM1BL UM2MD UM2BL 1 9.6 6.4 10.1 10.2 11.5 10.1 11.1 2.1 9.3 5.6 9.1 11.1 12.3 10.9 12 2.2 3 9 6 9.4 10.5 10.9 9.3 11.3 4 9.9 6.1 10.4 10.6 5 8.3 6.2 8.2 10.4 9.7 6 8.6 6.3 9.1 11.1 11.1 9.7 10.5 7 9.7 6.1 9.9 11.5 8 10.2 6.2 11.1 9 9.2 6.5 10.2 10.4 11.5 9.6 10 9.7 6.3 9.3 9.7 12.1 11.1 10.5 6.7 10.2 11.3 11.2 11.3 12 9 6.3 8.9 12.4 11.3 13 8.9 5.9 8.8 10.3 11.6 10.7 10.7 14 8.9 6.2 9.3 10.5 12.3 15 6.5 10.8 16 9.2 6.3 9.6 10.6 11.7 9.9 11.3 17 7.6 5.4 8 9.7 11.5 18 8.2 5.5 8.9 10.6 10.5 19 8.8 6.8 8.9 8.9 11.1 9 20 8 5.4 9 10.5 11 21 8.5 5.9 8.6 9.8 10.7 22 8.9 6.1 9.7 10.4 12 23 5.5 8.6 10 10.3 9.8 10.2 24 8.5 5.7 8.7 9.5 10.7 9.2 10.2 25.1 5.6 9.9 25.2 26 9.7 6.5 10.6 10.8 12.4 27 9.9 6.7 9.8 10.6 11.8 10.5 11.1 28 9.3 6 9.6 9.5 11.6 9.3 11 29 8.8 6.4 9.5 10.1 11.9 9.3 129

SpNo UP3BL UP4MD UP4BL UM1MD UM1BL UM2MD UM2BL 30 7.6 5 7.5 10.1 9.5 31 9.2 5.5 9.2 10.8 9 11.2 32 8.7 8.3 9.2 10.7 9 9.6 33 9.5 6.8 9.9 10.6 11 10.3 10.4 34 8.6 6.1 8.4 10.9 12 35 8.7 5.6 8.6 9.1 10.7 9.2 10.2 36 8.7 5.9 8.3 9.6 9.8 8.7 9.6 37 5.9 9.6 10.1 12 9.1 11.3 38 8.1 5.4 8.7 11.8 39 9.4 6.3 8.8 10.5 11.3 40 9 9.3 9.5 8.3 9.5 41 8.7 6.1 9 10.2 10.9 8.9 10.5 42 9.7 5.8 9.6 9.3 11 9.3 10.6 43 44 9.2 6.4 9.1 11 45 6.5 10.6 8.1 11 46 9.7 6.6 10 10.7 10.7 12.5 47 8 5.8 8.4 10 10.8 9.8 48 11 11.7 49 8.1 5.8 9.2 11.5 50 9 6.8 8.7 9.5 9.1 51 8.4 6 8.5 10.5 10.7 10.4 9.7 52 9.1 6.2 9.5 10.7 11.7 10.7 11.9 53 8.7 5.4 9 10 11.3 9.3 11.6 54 8.2 6 8.4 9.6 10.6 10.2 11.1 55 9.3 6 9.5 10.9 12 10.7 11.7 56 9.1 57 8.6 6.2 8.5 10.7 11.1 9.3 11.3 58 8.5 6.4 8.9 10.1 11.8 10.8 11.3 59 9.6 6.6 10.9 60 9 6.3 9.2 10.3 11.7 10.1 9.2 61.1 9.1 6.4 9.6 9.9 11.3 61.2 130

SpNo UP3BL UP4MD UP4BL UM1MD UM1BL UM2MD UM2BL 62 8.4 6.1 8.4 9.9 11 10.3 10.6 63 9.2 5.9 9.9 10.2 11.8 10.6 64.1 64.2 8.3 5.9 8.6 9.8 11.2 65 8.7 6.4 9.5 10.6 10.5 66 67 9.2 6.3 9.2 10.6 11.1 9.5 10.2 68 10.3 6 9.5 10.2 11.9 69 8.9 5.8 8.8 10.4 70 7.8 5.9 8.1 9.2 10.5 71 9 6.1 8.7 10.2 11.4 9.2 11.3 72 9.2 5.5 9.4 9.9 11.1 10.4 73 9.5 6.7 9.6 9.9 11 10.7 74 75 9.3 6 9.3 10.3 11.5 76 9.1 5.2 8.7 11 11.3 77 9.1 5.8 9.6 78 8.2 5.2 8.5 9.7 10.5 9.8 79 9.9 6.3 10 10.6 11.3 80 9.9 5.9 9.3 10.4 10.8 9.8 10.9 81 9 5.5 8.3 11.2 82 8.3 4.9 8.3 9.7 10.8 9.4 11.6 83 9.2 6 9.5 10.4 11.8 10.6 11.7 84.1 8.8 5.6 8.9 9.9 11 9.4 11.3 84.2 8.7 5.1 9.4 11.1 10.1 10.6 85 9 6.3 9.6 10.7 12.7 10 12.5 86 87 8.8 6.1 9.2 11.1 11.8 11.7 88 8.7 6.3 8.7 10.5 11.4 10 89 90 7.8 5.9 7.4 9.8 10.4 9.5 11.3 91.1 91.2 131

SpNo UP3BL UP4MD UP4BL UM1MD UM1BL UM2MD UM2BL 92 9.2 6 9.2 9.8 11.3 9.3 11.1

101 9 5.3 9.3 10.2 11.1 8.8 10.1 102 7.7 4.6 7.7 8.9 10.6 103 9 5.9 8.7 9.9 10.4 9.1 10.5 104 7.8 5.9 8 9.4 105 8.5 6.1 8.4 9.6 106 8 5.6 8.3 8.7 10.6 8.9 107 8.8 6.1 8.7 10.2 10.5 108 109 8.6 5.8 8.6 9.8 11.4 9.6 11.1 110 8.6 5.7 8.6 9 10.3 8.8 10 111 8.9 5.6 9 8.9 8.5 112 113.1 9.4 6.1 9.2 10.2 11.1 9.5 11 113.2 9.1 6 9.5 9.4 11.1 8.9 10.8 114 8 5.7 7.6 9.6 10.4 115 7.8 5.1 7.8 9 10.6 9.2 10.7 116 8.4 8.8 10.2 11.4 117 8.9 5.9 8.8 9.8 10.4 118 119 8.3 5.5 9.1 9.7 9.9 120 8.1 5.3 8.6 9.7 11.2 9.4 10.6 121 9.6 6.2 9.3 11.1 122 9 5.8 8.6 9.5 10.8 9.7 11.1 123 9.5 5.7 9.7 10 10.8 124 9.1 6.5 8.7 9.7 11.2 125 9.2 6.2 9.4 10 11.1 9.2 10.3 127 8.2 5.2 8.4 9.3 10.6 10.4 128 9.2 5.7 9.1 9.3 11 129 8.1 6.2 8.2 9.3 130 8.4 6.2 8.9 9.6 11.6 8.8 132

SpNo UP3BL UP4MD UP4BL UM1MD UM1BL UM2MD UM2BL 131 8.6 6.3 8.5 9.7 10.7 132 9 5.4 9.5 9.6 133 9.4 6.1 9.6 10.3 11.9 9.2 134 8.8 5.5 8.8 9.5 11.5 9.4 11.2 135 8.9 6.3 8.9 10.3 10.8 10.1 10.8 136 8.6 5.3 9.2 10 11.1 138 8.1 5.3 8.4 9.3 10.2 9.4 10.6 139 8.9 6.3 9.4 9.1 10.3 8.7 9.6 140 8.3 5.4 8.3 9.4 10.7 9.2 141 8.2 4.7 8.2 9.1 10.8 11.1 142 5.6 9.5 143 8.1 6.4 8.9 9.5 10.7 9 10.7 145 8.4 6.3 9 10.4 147 9.2 5.8 8.5 9.3 10.8 8.7 9.4 152 9.6 6.3 9 10.7 8.1 10.4 153 8.5 4.8 7.9 9.4 10.9 154 9.4 6.6 10.6 10.1 11.8 10.2 155 9.4 6.5 10.5 10 11.7 10.3 156 8.4 4.7 7.2 9.6 10 157 158 9.5 5.9 9.3 9.8 11.4 10.4 159 8.5 5.7 8.4 9.3 10.3 8.4 9.8 160 8.7 5.5 9 9.1 10.7 8.1 10.3 161 8.3 5.3 8.5 9.5 8.4 8.9 162.1 162.2 163 8.5 164 9.4 6 9.6 10 11.6 165 8.9 6.3 9 10.1 11.1 9 10.6 166 6.2 11 11.7 167 8.3 5.6 8.1 9.5 10 10.1 168 169 8.1 5.8 7.8 8.9 10.1 133

SpNo UP3BL UP4MD UP4BL UM1MD UM1BL UM2MD UM2BL 170 8.3 6 8.1 10.1 10.6 9.3 9.7 171 9.4 5.6 9.1 9.4 11.2 9.4 10.1 172 8.8 6.6 9.5 9.5 10.7 9 10.9 173 176 178 5.4 9.2 9.2 11 8.5 191 8.6 5.5 8.5 9.1 10.8 10.5 10.9 195 9.4 5.8 9.4 10.8 11.8 10.6 201 8.9 6.5 8.4 9.5 9.8 205 5.9 9.1 9.8 10.8 207