The Roles of Genetic Drift and Natural Selection in Explaining the Unusual Dental Pattern of New Guinea Highlanders

University of Nevada, Reno

Adrift in Oceania: The Roles of Genetic Drift and Natural Selection In Explaining the Unusual Dental Pattern of New Guinea Highlanders

A thesis submitted in partial fulfillment of the requirements for the degree of Master of Arts in Anthropology

Roman Schomberg

Dr. G. Richard Scott/Thesis Advisor

May, 2018

THE GRADUATE SCHOOL

We recommend that the thesis prepared under our supervision by

ROMAN SCHOMBERG

Entitled

Adrift In Oceania: The Roles Of Genetic Drift And Natural Selection In Explaining The Unusual Dental Pattern Of New Guinea Highlanders

be accepted in partial fulfillment of the requirements for the degree of

MASTER OF ARTS

G. Richard Scott, Ph.D. , Advisor

Marin Piloud, Ph.D., Committee Member

Chris Feldman, Ph.D., Graduate School Representative

David W. Zeh, Ph.D., Dean, Graduate School

May, 2018

Abstract

A primary goal was to resolve the ‘baffling convergence’ of New Guinea and European dental morphology. This is an unusual case where dental morphology is at odds with other lines of biological evidence that show close ties between New Guinea and Australian populations. Observations were made on 182 dental casts from living populations in the New Guinea Highlands to characterize their dental morphology. Trait frequencies were compared to those of world populations to compute distance statistics and derive dendrograms. The conundrum was solved to a large extent when variation of the EDAR gene variant 370A was taken into account. This gene is associated with multiple traits involving hair, skin, and teeth. The high frequency of this polymorphism in North Asia is associated with a high frequency of shovel-shaped incisors. The EDAR 370A gene is not only associated with shoveling but also with double shoveling and lower molar cusp number. Although the gene is in moderate to high frequencies throughout Asia and the Pacific, it is absent in New Guinea. When the dental traits associated with EDAR were removed from the distance analysis, New Guinea now linked with Australia and Melanesia rather than Europe. This suggests that the unusual dental pattern exhibited by New Guinea Highlanders is a product of both genetic drift and natural selection. When compared to other populations, non-EDAR linked traits exhibit distance values that are in accord with differentiation attributable to genetic drift. The EDAR-linked traits reflect selection that has driven the frequency of this gene to zero. In all likelihood, the dental traits associated with EDAR are ‘genetic hitchhikers’ associated with some skin and/or hair trait that have been influenced by selection in this tropical rainforest environment. Although the nature of this selection cannot be determined, at least the ‘baffling convergence’ of New Guinean and European tooth crown morphology has been ‘unbaffled.’

I’d like to dedicate this to my mother. Since I was a small child, she pushed me towards the path of knowledge and curiosity.

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Acknowledgements

I would like to than R.A. Littlewood for graciously lending the collection of dental casts to the University of Nevada Reno. This exemplifies all that is good about the scientific process and I am grateful to have had the opportunity to study the fruits of his labor.

A great deal of gratitude is owed to the late Christy G. Turner II. His relentless work ethic produced an inspiring volume of data. It has made possible, not only this study, but countless others far ranging research on population origins and relationships.

He was a true scientific pioneer and his legacy continues to grow not only through his work, and that of his students and colleagues; but also, I must imagine, through anyone who called him a friend or family member.

I am extremely grateful for my committee members: Dr. G. Richard Scott, Dr.

Marin Piloud, and Dr. Chris Feldman, for their guidance, patience, and most importantly, their expertise.

Table of Contents Introduction ...... iv Materials and Methods ...... 9 ASUDAS Descriptions ...... 11 Upper Dentition ...... 11 Lower Dentition ...... 16 Results ...... 23 Distance Measures ...... 35 Clustering ...... 37 Discussion ...... 39 Conclusions ...... 45 Appendix ...... 49 References ...... 50

List of Tables

1. Table 1. Mean crown frequencies for 16 world groups plus New Guinea Highland sample 2. Table 2. Crown frequencies for 15 world samples and 17 nonmetric crown traits 3. Table 3. Euclidean distance values between 17 regional groupings and from 19 nonmetric crown traits 4. Table 4. Euclidean distance values between 16 regional groupings and from 17 nonmetric crown traits 5. Table 5. Frequencies and mean trait scores for UI1 Shoveling for 9 archaeological samples and 5 living samples

List of Figures

1. Figure 1. UPGMA tree based on distance analysis of 23 crown and root traits in

21 regional groupings. Modified from Scott and Turner (1997)

2. Figure 2. UPGMA tree based on distance analysis of 9 crown and root traits in 43

regional groupings. Modified from Scott and Turner (1997)

3. Figure 3. Photo of UI1 Winging

4. Figure 4. Box and whisker plots based on world frequencies of UI1 Winging

Figure 5.2 from Scott et al. (2018)

5. Figure 5. Box and whisker plots based on world frequencies of UI1 Shoveling

Figure 5.3 from Scott et al. (2018)

6. Figure 6. Photo of UI1 Shoveling

7. Figure 7. Photo of second upper molar without a hypocone

8. Figure 8. Box and whisker plots based on world frequencies of UM2 Hypocone

Figure 5.11 from Scott et al. (2018)

9. Figure 9. Box and whisker plots based on world frequencies of UM1 Cusp 5

Figure 5.13 from Scott et al. (2018)

10. Figure 10. Photo of Cusp 5 on the first upper molar

11. Figure 11. Box and whisker plots based on world frequencies of LM1 Cusp 6

Figure 5.18 from Scott et al. (2018)

12. Figure 12. Photo of Cusp 6 on the first lower molar

13. Figure 13. Photo of 4 cusped second lower molar

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14. Figure 14. Box and whisker plots based on world frequencies of 4 cusped LM2

Figure 5.16 from Scott et al. (2018)

15. Figure15. First data set - Dendrogram displaying results from Euclidean distance

and UPGMA clustering.

16. Figure16. Second data set - Dendrogram displaying results from Euclidean

distance and UPGMA clustering.

17. Figure17. First data set - Dendrogram displaying results from Euclidean distance

and UPGMA clustering without EDAR linked traits

18. Figure18. Second data set - Dendrogram displaying results from Euclidean

distance and UPGMA clustering without EDAR linked traits

Introduction

Physical anthropologists are interested in the origins, diversity and evolution of humans, their ancestors and relatives. Adding data to the body of anthropological literature helps clarify the picture of our origins and variation. Studying a particular region not only illuminates its own history but also helps answer broader questions of human variation and dispersal. The purpose of this study is to address the dental morphological variation of the long-isolated populations of the New Guinea Highlands.

New Guinea is a large island north of the Australian continent. The two landmasses and their neighboring islands were linked to form the continent Sahulland until the end of the Pleistocene (Allen and O'Connell 2008). Sea levels began to rise around 15,000 years ago, separating the island of New Guinea from the continent of

Australia (O'Connell and Allen 2004). The geographic history of New Guinea and

Australia suggests their inhabitants could be related or share common ancestry at some point in time. Geography alone cannot answer this question. Other lines of evidence, such as archaeology, genetics, craniometrics, non-metric cranial traits, and dental morphology, are required to evaluate the extent of shared ancestry between the populations of New

Guinea, Australia, and nearby islands.

The Pleistocene continent of Sahulland included Australia, New Guinea,

Tasmania, the adjacent continental shelves, and small islands nearby when Pleistocene sea levels were lower than in modern times (O'Connell and Allen 2004). Dates for the human settlement of Papua New Guinea have been estimated at 40,000 years ago in the

Huon Peninsula (Groube et al. 1986). The date of this site was subsequently revised to be

47,000 to 61,000 years old using uranium-thorium dating (Roberts, 1997). Four archaeological sites in the eastern highlands of Papua New Guinea have stone tools that date between 36,000 and 49,000 years old (Summerhayes et al. 2010). Calibrated dates for these sites have pushed the upper limit to 52,000 years ago (Allen and O’Connell,

2014). Similar dates have been recorded for the earliest settlement of Australia. There is still some issue as to whether the populations of New Guinea and Australia represent one single early migration or two or more migrations that occurred independently and at different times.

Between 1962 and 1963 R.A. Littlewood conducted a physical anthropological survey of the peoples of the eastern highlands of New Guinea (Littlewood 1972). At the time, groups south of the Gadsup (a group of peoples living around the Aiyura Valley) had only been studied by anthropologist J.B. Watson and missionary linguists of the

Summer Institute of Linguists (Littlewood 1972). Littlewood’s (1972) survey sought to provide a more thorough anthropological workup of the inhabitants of the region. When he began his study, populations in this area had been contacted by Europeans as recently as the 1920’s and 1930’s. Government censuses and government enforcement did not arrive in the area until the mid-1950’s (Littlewood 1972). To a large extent, the participants in the study were living a traditional lifestyle.

The central spine of New Guinea is mountainous with ridges and valleys from

4,000 to 6,000 feet in altitude, with many peaks topping 10,000 feet. One bio-geographic divide is the occurrence of endemic malaria below 4,000 feet (Littlewood 1972). Recent research corroborates this divide and cites the prevalence of malaria in Papua New

Guinea to be 1.6% in the highlands (between 1500 -1800 meters [4921-5906 feet] and

30% below 900 meters [2953 feet]) (Mueller et al. 2003). This divide may lead to micro- differentiation of the people in the region through some combination of isolation and genetic adaptation. Littlewood (1972) alludes to distinctions in New Guinea by noting,

“The Highland native, sometimes referred to as ‘Papuan,’ is physically as well as linguistically distinct from his neighbors on the coast” (Littlewood 1972: pp 9).

Littlewood mentions that the Highland type, among other characteristics, has a larger dentition than the lowlander. Kanazawa et al. (2000) found similar, albeit mixed results, with highland New Guinea populations who generally had larger dentitions.

The uniqueness of New Guinea languages is one part of the puzzle that can be used to address population origins and affinities. New Guinea is often described as one of the most linguistically diverse areas on the planet. Almost three million people are in a language family called ‘Papuan,’ that includes hundreds of mutually unintelligible languages, many of which have 3000 or fewer speakers (Pawley, 2006). The linguistic term ‘Papuan’ is associated with American linguist Joseph Greenberg, who clustered all the non-Austronesian languages of Papua New Guinea together with Andaman Islands and Tasmanian languages (Pawley 2006). Significantly, Greenberg (1971) does not cluster languages in New Guinea with mainland Australian languages. Spriggs (1997) notes the difficulty of establishing genetic affinities for New Guinea languages is a product of time depth of the populations who have inhabited the island for many millennia.

A recent genetic study of Aboriginal Australian Y chromosomes indicates a shared origin for Aboriginal Australians and Papuans (Bergström et al. 2016). The two most common Y chromosome haplogroups (C and K*) shared between Aboriginal

Australians and Papuans have a deep divergence of 48,000 to 50,100 years ago

(Bergström et al. 2016). Haplogroup M is rare in Australia but is in high frequencies in

Papua New Guinea and Melanesia. This haplogroup shows a more recent divergence between Papuans and Australians (10,4000 years ago). Papuan and Australian Y chromosomes diverged from the rest of global human populations roughly 54,000 years ago (Bergström et al. 2016). This divergence time allows for Papuans and Australians to drift away from each other for almost as long as they have been diverging from the rest of the world. Some mitochondrial DNA research has produced similar results and postulated a 50,000-year age for a common founder between Australian and Papuan mtDNA

(Hudjashov et al. 2007).

Genome wide studies show a deep ancestral link between populations from New

Guinea and Australia. Pugach et al. (2013) found an ancient genetic association between groups from the New Guinea Highlands, Australia, and a Negrito group from the

Philippines called the Mamanwa. They discovered a divergence time of approximately

36,000 years ago (Pugach et al. 2013). Malaspinas et al (2016) found similar results when analyzing high coverage genomes from 83 Aboriginal Australians and 25 Papuans from the New Guinea Highlands. They found a divergence time of 25,000 to 40,000 year ago for Aboriginal Australians and Papuans from the New Guinea Highlands.

Genetic analysis of world populations shows much the same pattern as the study of cranial metric and nonmetric traits. In a study of classic genetic markers, Nei and

Roychoudhury (1982) and Cavalli-Sforza et al. (1994) found that New Guinea and

Australia clustered together although the root of the cluster suggested a deep time depth for the divergence of these populations.

Genetic studies on the human pathogen Helicobacter pylori found that the variant hpSahul (found in New Guinea and Australia) split from Asian populations 31,000 to

37,000 years ago. The New Guinean and Australian versions of hpSahul have been isolated from each other for roughly 23,000 to 32,000 years (Moodley et al. 2009).

Evidence points to a shared founding of Sahul and a relatively quick separation and isolation between New Guinea and Australia.

Anthropologists who have studied cranial measurements and nonmetric cranial traits have found that New Guineans, Australians, and populations from big-island

Melanesia are related. Pietrusewsky (1994) studied 32 standard cranial measurements and found New Guineans, Australians, and Melanesians plotted together in a discriminant function analysis and distance analyses produced trees where these groups were on a common cluster. Pietrusewsky (2006) performed an analysis of 73 male groups using 24 cranial measurements and found similar results, with New Guineans, Australians, and

Melanesians clustering together. Hanihara et al. (2003) studied 70 samples from across the globe for 20 nonmetric cranial traits. The results of their analysis showed New

Guinea, Australian, and Melanesian populations clustered together.

In the Anthropology of Modern Human Teeth, Scott and Turner (1997) performed a global analysis of crown and trait frequencies and found New Guinea and Western

Eurasia clustered on the same branch. In two analyses involving (1) 23 crown-root traits

(Figure 1) and (2) 9 crown traits (Figure 2), New Guinea samples clustered with

Europeans, and North Africans in both instances (Scott and Turner 1997).

The expected linkage between New Guinea and Australo-Melanesian populations was not evident. Scott and Turner (1997) suggested the difference between New Guinea and

Australo-Melanesian populations might reflect extensive genetic drift in the isolated mountain valleys of New Guinea, but they could not account for their similarities to

Europeans.

Itou and Matsuno (2011) performed a dental morphological analysis of New

Guinean casts similar to those observed in the present study. They compared their sample to 31 Asian populations. Their study produced a multidimensional plot in which the New

Guinean sample was isolated from both the Sinodonts (Northeast Asians and derived populations) and Sundadonts (Southeast Asians) (see Turner,1990, for an extensive definition of these terms). They concluded that the New Guinean dentition was

morphologically simplified compared to the Australian dentition but made no attempt to explain this simplification.

The association between New Guineans and Western Eurasians was explored again in Scott and Schomberg (2016). Trait by trait comparisons of frequencies and different clustering methods sought to illustrate the relationship, if any, between the two populations. An analysis of variance was performed on the trait means of 28 variables.

Nine showed similarities between New Guinea and Europe with both differing from

Australia. For seven traits, Australian frequencies were similar to New Guinea, with both differing from Europe (Scott and Schomberg 2016). Clustering methods performed in the above study found New Guinea juxtaposed between Europe and Australia as well. In one analysis New Guinean clustered with Europe. When additional samples were added from

Africa and South Asia, these additions altered the clusters and New Guinea no longer clustered with the European samples. In this analysis New Guinea, Australia, and

Melanesia clustered together, but the connection of New Guinea to these populations was at a deep node, suggesting a distant relationship (Scott and Schomberg, 2016).

Are the populations of New Guinea and Australia closely related? The geographic and human settlement history of the two landmasses, along with several lines of biological evidence, indicates the populations of New Guinea are related, albeit distantly, to the inhabitants of Australia. Linguistics (Greenberg 1971), however, does not show close ties between the two populations. Archaeological evidence (Summerhayes et al.

2010; Groube et al. 1986; O'Connell and Allen 2004; Allen and O’Connell 2014) points to both New Guinea and Australia being colonized near 50,000 years ago. These dates are close to those estimated by the divergence of Y chromosome and mitochondrial DNA

haplogroups between New Guineans and Australians (Bergström et al. 2016; Hudjashov et al. 2007), indicating a common origin at colonization and a subsequent separation.

Previous studies on dental morphology are at odds with archaeology and multiple lines of biological evidence indicating ties between New Guinea and Australian populations. New Guinea populations cluster with Europeans and Western Eurasians

(Scott and Schomberg 2016; Scott and Turner 1997), show a distant relationship with

Australians (Scott and Schomberg 2016), and are very different from their Southeast

Asian neighbors, including Melanesians, Micronesians, and Polynesians (Itou and

Matsuno 2011).

To reevaluate the ‘baffling convergence’ between the dental morphology of New

Guinea and Europe (Scott and Schomberg, 2016), dental casts obtained by R.A.

Littlewood in highland New Guinea populations affords a new opportunity to examine the question of origins and relationships. The data in this thesis are used to determine how New Guinea dental morphological variation is similar to or different from other world populations. Tooth crown and root traits, in most cases, reflect population relationships shown by other biological variables. Why, in this single instance, is dental morphology an outlier, producing a result that is fundamentally unique when compared to other lines of evidence?

I use the Arizona State University Dental Anthropology System (ASUDAS) system to characterize the key features of the New Guinea dentition. It is the most widely used classification system for non-metric dental traits. I seek to accomplish the following goals: (1) further characterize the dental pattern of New Guinean populations by recording observations on a sample of casts from living New Guinea Highlanders; (2)

describe trait frequencies of the PNG Highlands sample and previously published samples from New Guinea and compare them to Australia, Melanesia, Europe, and other regional populations to address the findings of previous work (Scott and Turner 1997;

Scott and Schomberg 2016); (3) determine if the results of Scott and Turner (1997) and

Scott and Schomberg (2016) are replicable by applying biodistance statistics and clustering methods on the data collected from the PNG Highlands sample and analyzing it in the context of world populations; and (4) determine if the dental pattern mirrors that reported by Scott and Turner (1997) and Scott and Schomberg (2016).

Materials and Methods Dental morphological observations were made on one hundred and eighty-three dental casts collected by Littlewood in 1962-63 to characterize the dental pattern of New

Guinean populations. This allows me to make comparisons to other populations and calculate biodistance statistics. Littlewood originally collected 218 casts, but some were misplaced or could not be scored. The casts were loaned to the University of Nevada,

Reno Anthropology department.

The Arizona State University Dental Anthropology System (ASUDAS) (Turner et al. 1991; Scott and Irish, 2017), was used to score the morphological characteristics of the New Guinea dental casts. The dental plaques of this system show ranked grades of expression (usually absent and several degrees of expression from slight to pronounced) for over three dozen traits. This system has become the standard method for documenting variation in dental morphology for human populations. Standardizing measurements for

d ental characterizations is crucial for scientific replicability. It has been a successful standardization because it has the following aspects (Turner et al. 1991):

● The traits are easily observed

● The physical structure of the traits withstand crown wear

● There is little to no sexual dimorphism

● The traits evolve at a slow rate

● The traits show a relationship to population ancestry

ASUDAS Trait Descriptions

Upper Dentition ● Winging - Rotation of the upper central incisors. It is scored as: (0) absent; (1)

trace winging; (2) moderate winging; and (3) pronounced winging (Scott and Irish

2017).

● Shoveling - Shoveling is defined by the presence of lingual marginal ridges on

the incisors on both the upper and lower dentitions. The classification used

mirrored the ASUDAS scoring system with grades 0-7 (none, faint, trace,

semishovel, semishovel+, shovel, marked shovel, and barrel (UI2). Scores greater

than or equal to two (first analysis) and three (second analysis) were used to

calculate trait frequencies for population comparisons.

● Double Shoveling - This trait occurs when marginal ridges appear on the labial

aspect of the incisors. The 0-6 scale (none, faint, trace, semi-double-shovel,

double-shovel, pronounced double-shovel, and extreme double shovel) outlined in

Turner et al. (1991) was used and any score of two or greater was used to record

trait frequency.

● Interruption Groove - This trait is exhibited on both upper incisors. It is

characterized by grooves that cross marginal ridges or the cingulum. Since

observations were made on plaster dental casts, there was some difficulty in

viewing manifestations on the cingulum. This trait was tabulated as present or

absent.

● Incisal Curvature or Labial Convexity - This trait of the upper incisors

categorizes the extent, if any, of curvature on the labial surface when viewed from

an occlusal aspect (Turner et al. 1991). Possible scores range from 0-4 (flat, trace,

weak, moderate, and pronounced convexity); any score of two or greater was

tabulated for frequency data.

● Bushman Canine or Canine Mesial Ridge - This trait occurs mostly in African

populations, especially the Bushmen. Presence of this trait is indicated when the

mesiolingual ridge is greater in dimension than the distolingual ridge and to the

degree that it connects to the tuberculum dentale. The scoring system is as

follows: (0) the mesial and distal ridges are equal in size and neither connects to

the tuberculum dentale (TD); (1) the mesial ridge is greater than the distal ridge

with a weak attachment to the TD; (2) larger mesial ridge and moderate

attachment to the TD; and (3) “Morris Type,” a significantly bigger mesial ridge

and full incorporation of the TD (Turner et al. 1991). This study used a score of

one or greater to calculate trait frequency.

● Tuberculum Dentale - This trait is found on the lingual cingulum of the upper

incisors and canine. It can be expressed as tubercles (most common on the upper

canines and upper lateral incisors) or as ridges on the lingual surface of the upper

central incisors (Turner et al. 1991: 16). The presence of the trait was calculated

for the upper central incisors when it was greater than or equal to two. For the

upper lateral incisors and upper canines, a score of two or greater was used to

calculate trait frequency.

● Distal Accessory Ridge - This variable “Occurs in the distolingual fossa between

the tooth apex and the distolingual marginal ridge” (Turner et al. 1991:17). Scores

range from 0-5 (absent, faint, weak, moderate, strong, very pronounced). Any

score greater than or equal to two was tabulated for trait frequency.

● Uto-Aztecan Premolar or Distosagittal Ridge - Pronounced ridge from the

apex of the buccal cusp extends to the distal occlusal border at or near the sagittal

sulcus. There is also a mesial rotation of the buccal surface and a buccolingual

expansion of the buccal cusp (Turner et al. 1991). This trait was scored as either

present or absent.

● Odontomes - Characterized as a “pin-sized,” “spike-shaped” enamel and dentin

protuberance occurring on the premolar occlusal surface (Turner et al. 1991). The

trait is scored as present (1) or absent (0).

● Mesial Accessory Ridge - An accessory ridge on the mesial end of the buccal

cusp of the upper premolars. It is scored present (1) or absent (0).

● Distal Accessory Ridge - An accessory ridge on the distal end of the buccal cusp

of the upper premolars. It is scored present (1) or absent (0).

● Marginal Tubercles - A free standing accessory tubercle found on either the

mesial or distal side of the first or second upper premolar. Marginal tubercles are

scored as:(0) No tubercles present (1) single mesial tubercle present. (2) single

distal tubercle present. (3) mesial and distal tubercle present (Scott and Turner,

1997). Marginal tubercles were scored when present in any expression.

● Hypocone - The distolingual cusp of the upper molars. The trait is evident on the

upper first molars in most populations. Its presence is more variable for the

second molar (Scott and Turner, 1997). Scoring this trait is as follows: “(0). No

hypocone, (1) Faint ridging present at the site. (2) Faint capsule present. (3) Small

cusp present. (3.5) Moderate-sized cusp present. (4) Large cusp present. (5) Very

large cusp present” (Turner et al. 1991:18) In this study, the 3.5 score was

omitted, and the scoring table was adjusted to 1-6. The trait frequency was

tabulated for scores of three or greater.

● Carabelli’s Trait - This trait is expressed on the lingual surface of the

mesiolingual cusp (protocone) of the upper molars. It has a wide range of

expression from absence to a large free-standing cusp. The scoring system for the

trait is: (0) The mesiolingual aspect of cusp 1 us smooth; (1) a groove is present.

(2) pit is present; (3) a small Y-shaped depression is present; (4) a large Y-shaped

depression is present; (5) a small cusp with a free apex but the distal border of the

cusp does not contact the lingual groove separating cusps 1 and 4; (6) a medium-

sized cusp with an attached apex making contact with the medial lingual groove;

and (7) a large free-standing cusp (Turner et al. 1991).

● Cusp 5 (Metaconule) - The fifth cusp of the upper molars. It is found in the distal

fovea between the metacone and hypocone. It is more common in the first molar

and is rounded, conical or triangular (Scott and Turner, 1997). It is scored as, (0)

site of cusp 5 is smooth, their being only a single distal groove present separating

cusp 3 and 4; (1) faint cuspule is present; (2) trace cuspule present; (3) small

cuspule present; (4) small cusp present; and (5) medium-sized cusp present

(Turner et al 1991). A score of 1 or greater was used to tabulate frequencies.

● Mesial Paracone Tubercle (MPT) - This tubercle is located on the mesial

accessory ridge of the paracone of the upper molars. It is scored as a present (1) or

absent (0).

● Mesial Accessory Tubercle (MAT) - This tubercle is located on the mesial

marginal ridge of the paracone of the upper molars. It is located between the

Mesial Paracone Tubercle and the Protoconule. It is scored as a present (1) or

absent (0).

● Protoconule - A hypertrophied mesial accessory ridge of the protocone with an

independent cusp tip (Scott and Turner 1997).

● Parastyle (Paramolar Tubercles) - A paramolar tubercle on the buccal surface

of the paracone may be derived from the cingulum. Pronounced expressions of

this trait might be supernumerary teeth fused to the buccal surface of the upper

molars (Scott and Turner 1997; Scott et al. 2018). Turner et al. (1991), have set

the following scoring system: (0) buccal surfaces of cusps 2 and 3 are smooth; (1)

a pit is present in or near the buccal groove between cusps 2 and 3; (2) a small

cusp with an attached apex; (3) a medium-sized cusp with a free apex; (4) a large

cusp with a free apex; (5) a very large cusp with a free apex usually involving the

buccal surface of cusps 2 and 3; and (6) An effectively free peg-shaped crown

attached to the root of the third molar is present. This condition is extremely rare.

● Missing Upper 3rd Molar - Congenital absence of the upper third molar was

scored as (1) absent or (0) present.

● Peg Shaped Upper 3rd Molar - Any third molar that demonstrably differs in

size and shape from a morphologically normal molar was considered peg shaped.

Lower Dentition ● Canine Distal Accessory Ridge - Occurs in the distolingual fossa between the

tooth apex and the distolingual marginal ridge (Turner et al. 1991). Scores range

from 0-5 (absent, faint, weak, moderate, strong, very pronounced). Any score

greater than or equal to one was tabulated for frequency data.

● Multiple Lingual Cusps - Multiple lingual cusp variation is scored by the

number of lingual cusps and their relative size. The scoring system used is as

follows: (0) one lingual cusp; (1) one or two lingual cusps (an indecisive reading

when teeth are worn); (2) two lingual cusps with the mesial cusp being larger than

the distal cusp; (3) two lingual cusps with the mesial cusp being larger than the

distal cusp; (4) two lingual cusps with the mesial and distal cusps being equal; (5)

two lingual cusps with the distal cusp being larger than the mesial; (6) two lingual

cusps with the distal cusp being much larger than the mesial; (7) two lingual cusps

with the distal cusp being much larger than the mesial; (8) three lingual cusps of

around the same size; and (9) three lingual cusps with the mesial being the largest

of the three (Turner et al. 1991). Trait frequencies were tabulated based on grade

2 and above.

● Mesial Accessory Ridge - An accessory ridge on the mesial end of the buccal

cusp of the lower premolars. It is scored as present (1) or absent (0).

● Distal Accessory Ridge An accessory ridge on the distal end of the buccal cusp

of the lower premolars. It is scored as present (1) or absent (0).

● Odontomes - Characterized as a “pin-sized,” “spike-shaped” enamel and dentin

protuberance occurring on the premolar occlusal surface (Turner et al. 1991). The

trait is scored as present (1) or absent (0).

● Cusp Number LM1 and LM2 - The presence or absence of the hypoconulid is

the key to this trait. Scoring is either: (4) no hypoconulid or (5) the hypoconulid is

present. A score of (4) is calculated for frequencies of 4-cusped lower molars.

● Groove Pattern - To score groove pattern, (Y) indicates cusps 2 and 3 are in

contact, for (+), all cusps (1-4) are in contact at the central occlusal fossa, (X),

cusps 1 and 4 are in contact. This study tabulated the following as Y = 1, + = 2,

and X = 3. Scores of 1 were tabulated for frequency data.

● Cusp 6 - Presence or absence of the sixth cusp (entoconulid). It is scored as, (0)

cusp 6 is absent; (1) cusp 6 is much smaller than cusp 5; (2) cusp 6 is smaller than

cusp 5; (3) cusp 6 is equal in size to cusp 5; (4) cusp 6 is larger than cusp 5; and

(5) cusp 6 is much larger than cusp 5 (Turner et al. 1991). A score of 1 or greater

is used to calculate frequencies.

● Deflecting Wrinkle - The occlusal ridge of the metaconid normally follows a

straight line from the cusp tip to the central fossa. The trait is present when the

ridge deflects distally toward the central occlusal fossa. Scored as: (0) absent; (1)

ridge is straight but shows a midpoint constriction; (2) ridge deflects distally but

does not contact cusp four; and (3) ridge deflects distally and contacts cusp four.

A score of 2 or greater is recorded for this study.

● Cusp 7 - A supernumerary cusp between the metaconid and entoconid of the

lower molars. Scored as: (0) absent; (1) faint cusp present; (2) small cusp present;

(3) medium sized cusp present; and (4) large cusp present. A score of 1 or greater

is recorded for the frequency of the trait.

● Protostylid - A cingulum derived presence on the buccal surface of the

protoconid. Scored as: (0) absent; (1) a pit centered in the buccal groove (i.e.,

buccal pit); (2) the buccal groove is curved distally; (3) a faint secondary groove

extends mesially from the buccal groove; (4) more pronounced secondary groove;

(5) strong secondary groove that is easily seen; (6) the extension of the secondary

grooves forms a small cusp and (7) a cusp with a free apex. A score of 1 or

greater is used to calculate frequencies.

● Distal Trigonid Crest - A buccolingual ridge or crest that transverses the distal

aspect of the primitive trigonid. Scored as, (0) absent or (1) present. A score of 1

is recorded for trait frequency.

● Anterior Fovea - A groove separating the protoconid and the metaconid. Well-

developed versions form a triangular shape. Scored as, (0) absent; (1) a weak

ridge connects cusps 1 and 2 to form a faint groove; (2) larger ridge and deeper

groove; (3) greater ridge than grade 2; and (3) very long groove and robust ridge.

A score of 2 or greater is recorded for trait frequency.

Appendix 1 shows the frequencies for 20 non-metric crown traits observed on 182 casts. The table has frequencies for each degree of expression and the breakpoint for the trait. The breakpoint is the grade of trait expression used to calculate the trait frequencies used in calculating biodistances. The sample included mostly males (151 males, 31 females), but that is not a major issue as most traits are not sexually dimorphic (Scott et al. 2018).

The first data set used to compare trait frequencies for my sample of New Guinea

Highlanders contains broad regional groups (e.g., Western Europe, North Africa, East

Asia, etc.). Multiple samples from each region allowed Scott et al. (2018) (Table 1) to characterize seventeen regional groups from all parts of the world. This analysis compares the observations made in this study (PNG Highlands) with the data provided by

Scott et al. (2018). The data in the appendix is primarily the product of Christy G.

Turner’s efforts to characterize crown and root trait variation in 30,000 individuals across a broad range of New World, Asian, Pacific, and European populations (Scott et al.

2018). The comparison of 19 trait frequencies in Table 2 allowed the estimation of biodistance measures and associated dendrograms.

Table 1.First data set - Mean crown frequencies for 16 world groups plus New Guinea Highland Sample Comparative data from Scott et al. (2018)

Sample/Trait No. samples; k = Double Interruption Tuberculum Bushman Winging Shoveling Shoveling grooves dentale Canine Hypocone Tooth UI1 UI1 UI2 UI2 UI2 UC UM2 Breakpoint 1 2+ 2+ 1+ 2+ 1+ 3+ PNG Highlands n = 182 0.175 0.430 0.000 0.041 0.380 0.043 0.654 New Guinea 6 0.065 0.256 0.046 0.146 0.254 0.020 0.894 Australia 15 0.104 0.678 0.063 0.200 0.200 0.008 0.894 Melanesia 5 0.176 0.485 0.204 0.243 0.396 0.055 0.891 Micronesia 2 to 3 0.531 0.725 0.224 0.179 0.395 0.014 0.686 Polynesia 6 0.179 0.541 0.186 0.272 0.248 0.010 0.855 Southeast Asia 14 0.224 0.804 0.270 0.294 0.308 0.029 0.840 East Asia 11 0.249 0.934 0.424 0.366 0.195 0.008 0.785 Northeast Siberia 3 0.296 0.974 0.625 0.591 0.277 0.000 0.563 Western Europe 5 0.066 0.184 0.131 0.393 0.301 0.014 0.688 Eastern Europe 6 0.139 0.198 0.331 0.367 0.206 0.023 0.633 North Africa 11 0.047 0.090 0.085 0.311 0.343 0.055 0.737 India 21 0.053 0.148 0.013 0.189 0.338 0.021 0.750 Nubia 12 0.089 0.266 0.030 0.244 0.363 0.098 0.831 East Africa 2 to 6 0.031 0.184 0.037 0.112 0.333 0.134 0.850 W & S Africa 10 0.053 0.264 0.014 0.123 0.418 0.151 0.849 San 10 0.056 0.201 0.007 0.081 0.294 0.401 0.915

Lingual Sample/Trait No. samples; k = Peg-reduced cusp Carabelli’s Cusp trait Cusp 5 missing number Groove pattern Cusp 6 number Tooth UM1 UM1 UM3 LP2 LM2 LM1 LM2 Breakpoint 2+ 1+ 1+ 2+ Y 1+ 4 PNG Highlands n = 182 0.383 0.494 0.287 0.969 0.231 0.102 0.843 New Guinea 6 0.417 0.622 0.068 0.698 0.389 0.133 0.556 Australia 15 0.410 0.613 0.054 0.745 0.257 0.645 0.096 Melanesia 5 0.334 0.489 0.088 0.885 0.356 0.463 0.436 Micronesia 2 to 3 0.476 0.261 0.425 0.886 0.341 0.511 0.218 Polynesia 6 0.330 0.344 0.310 0.836 0.284 0.589 0.331 Southeast Asia 14 0.390 0.260 0.189 0.776 0.298 0.354 0.319 East Asia 11 0.303 0.193 0.355 0.702 0.218 0.352 0.273 Northeast Siberia 3 0.195 0.016 0.178 0.309 0.179 0.509 0.027 Western Europe 5 0.592 0.120 0.130 0.577 0.261 0.074 0.792 Eastern Europe 6 0.405 0.178 0.195 0.679 0.262 0.080 0.686 North Africa 11 0.534 0.113 0.146 0.710 0.326 0.085 0.683 India 21 0.278 0.219 0.156 0.467 0.265 0.151 0.810 Nubia 12 0.637 0.246 0.098 0.765 0.421 0.047 0.545 East Africa 2 to 6 0.443 0.104 0.039 0.611 0.737 0.098 0.354 W & S Africa 10 0.547 0.280 0.044 0.706 0.579 0.221 0.238 San 10 0.276 0.281 0.060 0.749 0.702 0.037 0.093

Sample/Trait No. samples; k = Deflecting Distal trigonid wrinkle crest Protostylid Cusp 7 Odontomes Tooth LM1 LM1 LM1 LM1 UP & LP Breakpoint 2+ 1+ 1+ 1+ 1+ PNG Highlands n = 182 0.118 0.058 0.018 0.083 0.057 New Guinea 6 0.104 0.000 0.049 0.045 0.000 Australia 15 0.388 0.048 0.073 0.048 0.035 Melanesia 5 0.298 0.038 0.134 0.115 0.033 Micronesia 2 to 3 0.377 0.046 0.221 0.020 0.021 Polynesia 6 0.289 0.072 0.149 0.032 0.015 Southeast Asia 14 0.427 0.059 0.211 0.083 0.025 East Asia 11 0.390 0.071 0.224 0.060 0.026 Northeast Siberia 3 0.675 0.027 0.308 0.024 0.000 Western Europe 5 0.121 0.063 0.103 0.039 0.007 Eastern Europe 6 0.152 0.018 0.147 0.042 0.024 North Africa 11 0.091 0.023 0.299 0.070 0.002 India 21 0.125 0.112 0.192 0.089 0.000 Nubia 12 0.180 0.008 0.263 0.069 0.011 East Africa 2 to 6 0.185 0.005 0.267 0.173 0.003 W & S Africa 10 0.247 0.010 0.228 0.242 0.005 San 10 0.181 0.008 0.099 0.225 0.000

Of the seventeen combined groups (Scott et al. 2018), four groups are from the

Sahul region: the PNG Highlands sample (n=182), New Guinea (k = 6), Australia (k =

15), and Melanesia (k = 5), where k = number of samples used to derive mean frequency by regional group. Two groups are from the Pacific region: Polynesia (k = 6) and

Micronesia (k = 2 or 3). For mainland and insular Southeast Asia, k = 14; other mainland groups include East Asians (k = 11) and Northeast Siberia (k = 3). There are four West

Eurasian groups: Western Europe (k = 5), Eastern Europe (k = 6), North Africa (k = 11), and India (k = 21). From Africa, there are four groups: Nubia (k = 12), East Africa (k = 2 or 3), West and South Africa (k = 10), and San (k = 10).

The second data set is simplified to help clarify the biodistance results and frame the evolutionary forces underlying the differences between New Guinea, Australia, and

Melanesia. This data set includes 17 nonmetric crown traits from 15 samples across the globe. It contains two samples from New Guinea (noted as NG), one of which is the original data from this study while the other is based on mean frequencies for six New

Guinea skeletal samples observed by C.G. Turner II. In addition, there are two samples from Australia (AUS), two samples from Melanesia (MEL), two samples from East Asia

(EAS), two samples from Native North America (NA), two samples from Europe (EUR), two samples from Southeast Asia (SEA), and one sample from Sub-Saharan Africa

(AFR). The comparative data were obtained from the C.G. Turner database reported by

Scott and Irish (2017). To make the results easier to interpret, the samples from each region are noted by the shorthand noted above along with the number 1 or 2.

Table 2. Second data set - Crown frequencies for 15 world samples and 17 nonmetric crown traits

Sample/Trait n Double Interruption Tuberculum Bushman Winging Shoveling Shoveling grooves dentale Canine Hypocone Tooth UI1 UI1 UI2 UI2 UI2 UC UM2 Breakpoint 1 3+ 2+ 1+ 2+ 1+ 3+ NG 1 182 0.177 0.070 0.000 0.041 0.380 0.043 0.654 NG 2 50 0.076 0.000 0.000 0.161 0.251 0.019 0.900 AUS 1 74 0.043 0.163 0.000 0.116 0.271 0.000 0.899 AUS 2 57 0.150 0.139 0.000 0.229 0.384 0.036 0.934 EAS 1 63 0.245 0.647 0.279 0.409 0.177 0.035 0.818 EAS 2 190 0.309 0.833 0.000 0.377 0.188 0.000 0.823 NA 1 103 0.496 0.855 0.000 0.587 0.418 0.014 0.805 NA 2 98 0.313 0.661 0.000 0.473 0.326 0.045 0.749 EUR 1 255 0.096 0.044 0.016 0.295 0.222 0.022 0.641 EUR 2 131 0.024 0.028 0.055 0.437 0.270 0.048 0.646 SEA 1 89 0.135 0.427 0.172 0.278 0.223 0.026 0.772 SEA 2 66 0.237 0.711 0.279 0.536 0.481 0.023 0.597 MEL 1 140 0.232 0.089 0.000 0.192 0.365 0.019 0.874 MEL 2 78 0.250 0.176 0.059 0.308 0.429 0.031 0.927 AFR 1 72 0.074 0.105 0.000 0.043 0.417 0.324 0.876

Sample/Trait No. samples; k = Peg-reduced Lingual cusp Carabelli’s Groove Cusp 5 missing number Cusp 6 Cusp number trait pattern Tooth UM1 UM1 UM3 LP2 LM2 LM1 LM2 Breakpoint 2+ 1+ 1+ 2+ Y 1+ 4 NG 1 182 0.383 0.494 0.287 0.969 0.231 0.102 0.843 NG 2 50 0.390 0.456 0.066 0.702 0.422 0.033 0.591 AUS 1 74 0.500 0.603 0.066 0.754 0.235 0.638 0.101 AUS 2 57 0.483 0.604 0.046 0.843 0.325 0.806 0.088 EAS 1 63 0.350 0.086 0.315 0.680 0.237 0.350 0.232 EAS 2 190 0.277 0.286 0.472 0.892 0.265 0.268 0.145 NA 1 103 0.391 0.220 0.183 0.478 0.265 0.677 0.034 NA 2 98 0.325 0.141 0.160 0.506 0.311 0.566 0.092 EUR 1 255 0.660 0.224 0.116 0.519 0.148 0.079 0.868 EUR 2 131 0.609 0.122 0.114 0.593 0.312 0.092 0.731 SEA 1 89 0.367 0.105 0.227 0.666 0.323 0.388 0.285 SEA 2 66 0.283 0.052 0.500 0.792 0.526 0.467 0.190 MEL 1 140 0.412 0.683 0.130 0.907 0.431 0.429 0.497 MEL 2 78 0.275 0.420 0.065 0.774 0.308 0.457 0.378 AFR 1 72 0.583 0.619 0.031 0.821 0.625 0.364 0.167

Sample/Trait No. samples; k = Protostylid Cusp 7 Odontomes Tooth LM1 LM1 UP & LP Breakpoint 1+ 1+ 1+ NG 1 182 0.018 0.096 0.057 NG 2 50 0.071 0.080 0.000 AUS 1 74 0.094 0.037 0.038 AUS 2 57 0.071 0.074 0.000 EAS 1 63 0.214 0.088 0.057 EAS 2 190 0.195 0.124 0.015 NA 1 103 0.383 0.061 0.081 NA 2 98 0.376 0.171 0.007 EUR 1 255 0.000 0.070 0.000 EUR 2 131 0.200 0.037 0.000 SEA 1 89 0.189 0.064 0.026 SEA 2 66 0.068 0.060 0.056 MEL 1 140 0.219 0.132 0.018 MEL 2 78 0.051 0.185 0.075 AFR 1 72 0.200 0.674 0.000

NG 1 (PNG Highlands), From Scott and Irish (2017) - NG 2 (New Guinea), AUS 1 (Lower Murray), AUS 2 (North Australia), EAS 1 (South China), EAS 2 (Urga), NA 1 (Alabama), NA 2 (Iroquois), EUR 1 (Basques), EUR 2 (England), SEA 1 (Philippines), SEA 2 (Taiwan), MEL (New Britain), MEL (Loyalty Islands), AFR 1 (West Africa)

The Euclidean distance method was used on these datasets. The Mean Measure of

Divergence developed by Smith (1962) to estimate biodistance for nonmetric skeletal traits in mice, it is often used for nonmetric dental analyses of human populations (Irish

2010). Scott and Schomberg (2016) found that Euclidean distances positively correlated

with Mean Measures of Divergence and did not produce significantly different results.

The calculation of the distances was calculated in the R environment version 3.3.2 (R

Core Team 2016) using the package ‘ecodist’ version 1.2.9 (Goslee 2007). The

Euclidean distance was calculated as part of the R package ‘pvclust’ version 2.0-0

(Suzuki and Shimodaira 2015).

The data were processed through a clustering method that first calculated a

Euclidean distance and then produced hierarchical clusters with each cluster assigned a p- value from multiscale bootstrap resampling. This was performed using the R package

‘pvclust’ version 2.0-0 (Suzuki and Shimodaira 2015). The clustering methods used were

UPGMA and Ward's minimum variance method. The bootstrap feature in this package replicates the dataset to test if the observed clusters are the result of sampling error. It produces replicate datasets with increased numbers of observations (Suzuki and

Shimodaira 2015; Shimodaira 2004). Any cluster with a p-value > 0.95 is considered stable and not likely due to sampling error.

Results

Key trait descriptions There were six traits with frequencies that had a significant impact on the PNG

Highlands sample’s relationships to world populations. These traits were useful for comparing the PNG Highlands sample to the New Guinea combined group, Australia,

Melanesia, and the Western Eurasian groups (Western Europe, Eastern Europe, North

Africa, and India). The six traits are: winging (UI1), shoveling (UI1), hypocone

expression (UM2), cusp 5 (UM1), cusp 6 (LM1), and four cusped LM2. The frequencies of these traits and their relationships are described below.

Winging UI1 - The PNG Highlands sample displays a relatively high frequency for upper central incisor winging (0.175). This is greater than New Guinea (0.065), Western

Eurasia (0.066), and Australia (0.104). The frequency for this trait is closer to Melanesia

(0.176), Polynesia (0.179) and Eastern Europe (0.139).

Shoveling UI1 - Using a grade 2 breakpoint, the PNG Highlands sample has a moderate amount of shoveling on the upper central incisors (0.430). This is higher than that of New

Guinea skeletal samples (0.256) and much higher than Western and Eastern Europe

(0.184 and 0.198 respectively). Melanesians have the closest frequency (0.485) to the

PNG Highlands sample. Polynesia and Australia have higher frequencies for this trait

(0.541 and 0.678 respectively). PNG Highlands, Melanesia, Polynesia, and Australia

have intermediate frequencies for this trait (0.430 to 0.678). Low frequencies are found in groups from Western Eurasia and Africa while higher frequencies are found in East and

Southeast Asia.

Hypocone UM2 - Using a breakpoint of 3+, the PNG Highlands sample displayed moderate levels of hypocone reduction (0.654). Other groups with reduced expression of the hypocone are: Eastern Europe (0.633), Western Europe (0.688), Micronesia (0.686), and Northeast Siberia (0.563). New Guinea, Melanesia and Australia had slightly higher frequencies (0.894, 0.894, and 0.891 respectively).

Cusp 5 UM1 - The PNG Highlands sample has a high frequency (0.494) of cusp 5 on the upper first molar. This is like New Guinea (0.622), Australia (0.613), and Melanesia

(0.489). Western Europe (0.120), Eastern Europe (0.178), and North Africa (0.113) have much lower frequencies for this trait.

Cusp 6 LM1 - Low frequencies of cusp 6 on the lower first molar were found for the

PNG Highlands sample (0.102), New Guinea (0.133), Western Europe (0.074), Eastern

Europe (0.080), and North Africa (0.085). The frequency of the trait separates both New

Guinea samples from Australia (0.645) and Melanesia (0.463).

4 Cusp LM2 - High frequencies of four cusped lower second molars were found in the

PNG Highlands sample (0.843), New Guinea (0.556), Western Europe (0.792), Eastern

Europe (0.686), North Africa (0.683), and India (0.810). Australia (0.096) and Northeast

Siberia (0.027) have the lowest frequencies for the trait.

Traits where PNG Highlands sample had similar frequencies to New Guinea, Australia, and Melanesia include: Winging UI1, Shoveling UI1, and Cusp 5 UM1. Traits where

PNG Highlands sample had similar frequencies to Western Eurasian groups included:

Hypocone UM2, Cusp 6 LM1, and 4 Cusped LM2.

Distance Measures A Euclidean distance matrix (Table 3) was produced to display the distances between the PNG Highlands sample and 16 groups from the first dataset. This matrix was used to create neighbor-joining trees. It included every measure of dissimilarity for each group in the analysis. The PNG Highlands sample had the lowest distance measures with

New Guinea (0.622), Nubia (0.715), India (0.725) and Eastern Europe (0.738). The

Melanesian, North African, and Western European groups had the next closest dissimilarity measures (0.742, 0.771, and 0.775 respectively). The New Guinea group had its lowest dissimilarity with the Nubian group (0.537). It was also similar to the

Melanesian group (0.598), the Indian group (0.633), and West and South Africa (0.647).

PNG Highlands and New Guinea differed in their relationship to Australia. The PNG

Highland sample had a dissimilarity measure of 1.113 with Australia. The dissimilarity measure between New Guinea and Australia was 0.874. Australia was closest to

Polynesia (0.526) and Melanesia (0.567). Overall, Western Europe and North Africa were the two most similar groups in the analysis (0.322).

Table 3. Euclidean distance values between 17 regional groupings and from 19 nonmetric crown traits PNG NG MEL AUS POL MIC SEA EA NES EE WE IND NAF NUB EAF WSAF SAN PNG 0.000 NG 0.622 0.000 MEL 0.742 0.598 0.000 AUS 1.113 0.874 0.567 0.000 POL 0.870 0.783 0.378 0.526 0.000 MIC 1.029 1.094 0.700 0.801 0.546 0.000 SEA 0.947 0.897 0.503 0.632 0.439 0.516 0.000 EA 1.130 1.120 0.772 0.824 0.597 0.606 0.344 0.000 NES 1.724 1.629 1.281 1.219 1.135 1.082 0.918 0.747 0.000 EE 0.738 0.687 0.787 1.159 0.824 1.045 0.864 0.967 1.381 0.000 WE 0.775 0.709 0.899 1.239 0.957 1.181 0.988 1.138 1.533 0.357 0.000 IND 0.725 0.633 0.857 1.196 0.927 1.209 1.017 1.175 1.570 0.522 0.450 0.000 NAF 0.771 0.675 0.843 1.220 0.917 1.142 0.982 1.162 1.585 0.413 0.322 0.454 0.000 NUB 0.715 0.537 0.693 1.034 0.820 0.999 0.820 1.060 1.536 0.565 0.496 0.615 0.352 0.000 EAF 1.027 0.735 0.853 1.125 0.954 1.135 0.965 1.184 1.551 0.803 0.796 0.753 0.631 0.515 0.000 WSAF 0.943 0.647 0.652 0.878 0.787 0.962 0.811 1.077 1.474 0.843 0.842 0.823 0.690 0.472 0.360 0.000 SAN 1.118 0.811 0.897 1.088 1.013 1.196 1.045 1.251 1.642 1.029 1.096 1.020 0.945 0.777 0.512 0.505 0.000

NG (New Guinea), MEL (Melanesia), AUS (Australia), POL (Polynesia), MIC (Micronesia), SEA (Southeast Asia), EA (East Asia), NES (Northeast Siberia), EE (Eastern Europe), WE (Western Europe), IND (India), NAF (North Africa), NUB (Nubia), EAF (East Africa), WSAF (West and South Africa), SAN (Khoisan)

The Euclidean distance matrix for the second dataset (Table 4) produced similar results. The NG 1 sample (PNG Highlands) had its lowest distances with NG 2 (0.583),

MEL 1 (0.671), EUR 1 (0.701), EUR 2 (0.786), and MEL 2 (0.794). The NG 2 sample had its closest distances to MEL 1 (0.579), EUR 2 (0.613), MEL 2 (0.628), and EUR 1

(0.641). The two Australian samples (AUS 1 and AUS 2) had the closest distance of all the samples in the analysis (0.298).

Table 4. Euclidean distance values between 16 regional groupings and from 17 nonmetric crown traits MEL MEL NG 1 NG 2 AUS 1 AUS 2 EAS 1 EAS 2 NA 1 NA 2 EUR 1 EUR 2 SEA 1 SEA 2 AFR 1 1 2 NG 1 0.000 NG 2 0.583 0.000 AUS 1 1.036 0.844 0.000 AUS 2 1.139 0.979 0.298 0.000 EAS 1 1.159 1.043 0.964 1.039 0.000 EAS 2 1.193 1.159 1.045 1.106 0.502 0.000 NA 1 1.578 1.449 1.130 1.102 0.727 0.793 0.000 NA 2 1.359 1.190 0.949 0.960 0.528 0.681 0.379 0.000 EUR 1 0.701 0.641 1.125 1.260 1.103 1.319 1.506 1.273 0.000 EUR 2 0.786 0.613 1.084 1.195 0.982 1.231 1.388 1.129 0.368 0.000 SEA 1 0.966 0.801 0.753 0.850 0.340 0.657 0.848 0.561 0.909 0.771 0.000 SEA 2 1.298 1.276 1.180 1.163 0.579 0.677 0.831 0.721 1.347 1.191 0.662 0.000 MEL 1 0.671 0.579 0.602 0.619 1.019 1.048 1.249 1.057 0.960 0.904 0.812 1.171 0.000 MEL 2 0.794 0.628 0.578 0.574 0.786 0.911 1.033 0.823 0.923 0.859 0.593 0.961 0.454 0.000 AFR 1 1.156 0.962 0.894 0.899 1.273 1.305 1.461 1.222 1.311 1.233 1.087 1.392 0.799 0.870 0.000

NG 1 (PNG), From Scott and Irish (2017) - NG 2 (New Guinea), AUS 1 (Lower Murray), AUS 2 (North Australia), EAS 1 (South China), EAS 2 (Urga), NA 1 (Alabama),

NA 2 (Iroqouis), EUR 1 (Basques), EUR 2 (England), SEA 1 (Phillipines), SEA 2 (Taiwan), MEL (New Britain), MEL (Loyalty Islands), AFR 1 (West Africa)

Clustering A dendrogram constructed from the distance matrix of the first data set is shown as Fig. 15. The Northeast Siberian sample formed an outgroup to all the other samples.

The PNG Highlands sample clustered near the New Guinea group. The two were part of a larger cluster containing Western Europe, Eastern Europe, North Africa, Nubia, and

India. The bootstrapping analysis done on this tree had each had these clusters as being statistically weak. The cluster down the tree containing Western Europe, Eastern Europe,

North Africa, Nubia, and India. Bootstrapping analysis showed this cluster was statistically significant (p = 0.05). The Australian and Melanesian samples clustered on the other side of the tree. These results mirror those of Scott and Turner (1997) and Scott and Schomberg (2016).

The tree produced from the second dataset is shown as Fig. 16. The NG 1 and NG

2 groups cluster with Europe, but this cluster is also not statistically significant (p >

0.05). As neither cluster is statistically significant, the link with Europe is tenuous. The

Australian and Melanesian groups (AUS 1, AUS 2, MEL 1, and MEL 2) cluster together with the African sample (AFR 1). This grouping is also not statistically significant. The

two major Asian groups (EAS and SEA) cluster with the derived population from North

America (NA).

To reexamine the results of my analysis given the link between EDAR and dental morphology, I looked for traits that researchers have linked to EDAR (shoveling UI1,

d ouble shoveling UI1, 4-cusped LM2, and cusp 6 LM1). To evaluate how EDAR linked traits impacted distance analysis, I replicated the methods exactly as before minus those four traits. The results of the reanalysis (Fig. 17) produced a surprising result. Now New

Guinean, Australian, and Melanesian populations cluster together. No longer does New

Guinea show a ‘baffling convergence’ with Western Eurasia.

The same reanalysis was performed on the simplified data set. Unlike analysis one, the samples of this data set are not derived from the means of multiple groups but represent individual samples. The analysis (Fig. 18) of the second data set (Figure X) produced a cluster that includes all the New Guinean (PNG Highlands = NG1),

Australian, and Melanesian samples. The bootstrapping analysis on the tree shows this cluster is statistically significant (p = 0.01).

Discussion The results of this study indicate there are four nonmetric crown traits that cause the PNG Highlands sample and other New Guinea samples to differentiate from their geographic neighbors of Australia and Melanesia. These traits are UI1 Shoveling, UM2 hypocone expression, presence of cusp 6 on LM1, and the frequency of 4-cusped LM2.

The key features of the New Guinean dental pattern are reduction and simplification, and in this respect, they converge with European populations. Scott and Schomberg (2016)

found a similar pattern. In their analysis, New Guinea shared more nonmetric dental traits with Europe than with Australia (9 and 7, respectively). These traits often involve cusp (e.g., high incidence of 4 cusped LM1) and root simplification (UM2), along with reduced incisor shoveling frequencies. Scott and Schomberg (2016) did not speculate on the cause of the convergence of New Guinea and Europe. The problem remained: why does New Guinea show dental morphological convergence with Western Eurasians when every other biological variable shows this relationship is untenable. Given that dental morphology has proved to be an accurate indicator of population affinity in almost all other cases, why is New Guinea unique.

A recent publication by Hlusko et al. (2018) triggered an evaluation of New

Guinea dental variation in a new light. They focused on how natural selection impacted breast milk, fatty acid metabolism, and shovel-shaped incisors in a high latitude environment. The link between shoveling and breast milk was mediated through the

Ectodysplasin A receptor 370A variant (EDAR 370A variant). A figure in this article showed the frequency of EDAR in Asia and the Pacific. The key observation was that

EDAR was extremely common and even fixed in some high latitude populations that also had very high frequencies of shovel-shaped incisors. Southeast Asians, who exhibit lower frequencies and less pronounced expressions of shoveling, have significantly lower

EDAR frequencies, in the range of 20-30%. Remarkably, the frequency of EDAR in

New Guinea is at or near zero.

The expression of shoveling in world populations can be seen below in Fig. 6.

The distribution of UI1 shoveling mirrors that of EDAR frequencies. East Asian and

Native American groups have the highest frequency of shoveling and higher mean trait

scores. Compared to East Asians and Australians, New Guinea, Australia and Melanesia have low levels of shoveling. The Melanesian group has slightly more shoveling. This mirrors Fujimoto’s (2008) EDAR frequencies where Solomon Islanders had approximately ten percent of the EDAR variant connected to shoveling.

Table 5. Frequencies and Mean trait scores for UI1 Shoveling for 9 archaeological samples and 5 living samples From Scott and Irish (2017) and Scott 2018 personal communication.

n 0 1 2 3 4 5 6 7 MTS NG 30 0.200 0.500 0.300 0.000 0.000 0.000 0.000 0.000 1.1 Australia 317 0.085 0.234 0.571 0.092 0.016 0.002 0.000 0.000 1.73 Melanesia 163 0.119 0.250 0.379 0.250 0.003 0.000 0.000 0.000 1.79 East Asia 440 0.004 0.011 0.187 0.452 0.152 0.154 0.040 0.000 3.37 SE Asia 221 0.046 0.175 0.450 0.244 0.074 0.012 0.000 0.000 2.16 Polynesia 218 0.095 0.369 0.371 0.149 0.016 0.000 0.000 0.000 1.62 NS Amer 1368 0.001 0.004 0.076 0.466 0.188 0.186 0.080 0.000 3.71 Europe 479 0.201 0.606 0.151 0.041 0.000 0.000 0.000 0.000 1.03 Africa 247 0.160 0.383 0.393 0.063 0.000 0.000 0.000 0.000 1.36

Aust live 186 0.065 0.435 0.403 0.097 0.000 0.005 0.000 0.000 1.56 China live 149 0.007 0.094 0.342 0.429 0.102 0.027 0.007 0.000 2.64 As Ind live 361 0.306 0.408 0.238 0.049 0.000 0.000 0.000 0.000 1.23 Malay live 207 0.095 0.272 0.395 0.188 0.034 0.010 0.000 0.000 1.81 PNG Highlands 85 0.141 0.424 0.365 0.035 0.035 0.000 0.000 0.000 1.4

MTS (mean trait score)

The Ectodysplasin A receptor is a protein coded by the EDAR 370A gene. This gene affects ectodermal tissues like skin, hair, and teeth (Monreal et al. 1999). This gene affects the dentition in several ways that are significant in the analysis of dental morphology. Tucker et al. (2004) found that the EDAR gene affects cusp number in mice. They produced a mouse phenotype that had extra cusps on the molar teeth by activating a variant in the EDAR gene (Monreal et al. 1999). In human populations, high

frequencies of this variant of the EDAR gene are found in China and Japan, lower frequencies in Southeast Asia (Thailand and Indonesia), very low frequencies in the

Solomon Islands (Melanesia), and virtually absent in New Guinea and Europe (Fujimoto et al. 2008). Frequencies for Australia are unknown at this time. Park et al. (2012) found that the variant EDAR 370V/A, also known by the single-nucleotide polymorphism rs3827760, was associated with shoveling and double shoveling of the upper incisors and the presence of the hypoconulid (fifth cusp) on the lower molars. Bryk et al. (2008) found that EDAR 370V/A has been a target of positive selection in East Asia. Park et al. (2012) suggest that some dental traits reflect the pleiotropic action of the EDAR 370A gene.

What Scott and Schomberg (2016) called a baffling convergence (i.e., the clustering of New Guinea and Europe) is at least partially ‘unbaffled’ when dental morphology is examined by removing variables associated with EDAR 370V/A. Genetic research has shown New Guinea to be almost bereft of EDAR 370V/A, while their neighbors carry this single-nucleotide polymorphism at low frequencies, approximately

10% for Solomon Islanders (Fujimoto et al. 2008).

The geographic origins of this point mutation are unknown. It is absent in Africa,

Europe, and remarkably, New Guinea. Although there are many data points to be filled, there is a north to south cline in EDAR frequencies in Asia, with the highest in the northern latitudes. The ancestral condition is unknown. What is known, however, is that

Asian and Asian derived populations in the Pacific and New World have moderate to high frequencies of this allele while it is absent in New Guinea. Unfortunately, the

Australian frequency of EDAR 370A is unknown but based on the frequencies of morphologically linked EDAR traits, the allele frequency in Australia is probably not

zero (based on more shoveling than in New Guinea, a much higher frequency of LM1 cusp 6, and a much lower frequency of 4-cusped LM2). Melanesians from nearby islands do carry the EDAR variant but there is no frequency data for lowland New Guinea populations.

From an evolutionary standpoint, there are several issues to consider. The geography of the New Guinea highlands has been a significant barrier to gene flow. If neighboring groups in big island Melanesia have the trait, there is no evidence that it penetrated the interior. Moreover, Highland New Guinea is a unique environment that differs significantly from Australia and island Melanesia (Heads 2006). The lack of

EDAR 370V/A in the New Guinea Highlands may involve selection. Pressures that positively select for EDAR 370V/A may be absent in the New Guinea Highlands.

Conversely, given the pleiotropic effects of this gene, selection involving phenotypic variables linked to skin or hair may be the focus in this tropical rainforest environment, with dental simplification an ancillary aspect of selection (i.e., genetic hitchhiking)

(Gillespie 2000; Scott et al. 2018).

The bootstrapping analysis of the data set where the EDAR influenced traits were removed produced significant clusters. With directed trait editing, dental morphology produces patterns of relationships indicated by multiple biological lines of evidence.

Excluding EDAR-related traits, genetic drift is the likely mechanism producing these patterns. This is one of the few cases where a gene subjected to selection (Park et al.

2012) greatly disrupts results based on dental morphological relationships that are normally accounted for by genetic drift. More research on EDAR 370V/A should be conducted in New Guinea to map the frequencies of this variant and assess its relationship to skin and hair variables that may be under strong selective pressure.

Conclusions The PNG Highlands and New Guinea samples cluster with European populations when all morphological crown traits are included in an analysis. The expected relationship with Aboriginal Australians and Melanesians, predicted by all other lines of biological evidence, is not evident. The absence of the EDAR 370A allele may play a significant role in these findings. An analysis that eliminated traits linked to EDAR

370V/A had a dramatic impact on patterns of relationships indicated by dental morphology. Now, New Guinea clusters with Australia and Melanesia, in agreement with patterns produced by genetic and skeletal data. A working hypothesis on the differences between the dental patterns of New Guinea and Australo-Melanesia is their discordance in the frequencies of EDAR 370V/A. Key points that support this hypothesis:

● A distant but shared genetic origin with Australia and a subsequent genetic

divergence from Aboriginal Australians of around 50,000 years (Bergström et al.

2016). This would provide ample time for drift to differentiate the populations of

these two regions and time for selection to drive the EDAR 370V/A allele to zero.

● The highlands of New Guinea must have served as a significant barrier to gene

flow because surrounding populations had the EDAR 370V/A allele. If the allele

was introduced, it could have been lost through either chance or selection.

● Similarities in crown morphology between New Guinea and Europeans are

through convergence related to the lack of the EDAR 370V/A variant in these two

groups (Fujimoto 2008). Genetic studies show shared origins with Australians and

Melanesians (Kayser et al. 2003; Hudjashov et al. 2007), but not Europeans or

South Asians.

● The New Guinea dental pattern shares traits with Australian that are not common

in Europe (UM1 cusp 5, multiple lingual cusps LP2, and UI1 winging). These

traits have not been linked to EDAR 370V/A (Park et al. 2012). New Guinea and

Australia are also known for having large teeth (Kondo et al. 2005), a trait not

shared by Europeans.

Appendix

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