Mitochondrial Dna Diversity and Its Determinants in the Southwest Pacific

MITOCHONDRIAL DNA DIVERSITY AND ITS DETERMINANTS IN THE SOUTHWEST PACIFIC

A Dissertation Submitted to the Temple University Graduate Board

In Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy

By Danielle Nicole James August, 2008

2008

Danielle Nicole James

ABSTRACT

MITOCHONDRIAL DNA DIVERSITY AND ITS DETERMINANTS IN THE SOUTHWEST PACIFIC

Danielle Nicole James

Doctor of Philosophy

Temple University, 2008

Jonathan Friedlaender, PhD

The purpose of this study is to examine mitochondrial DNA variation in the

Southwest Pacific and determine what factors contribute to the degree and patterning of the observed variation. Population variation is known to be influenced by factors including demographic history, natural selection, climate, isolation, island area/complexity, and population age, as older populations are generally more diverse.

The groups compared are from three regions in the Southwest Pacific; (a) northeast New

Guinea, (b) Manus in northern Island Melanesia and (c) Easter Island in eastern

Polynesia. MtDNA surveys have revealed highly significant differences in molecular variance across these populations. According to traditional biogeographical theory, the likely determinants of these differences are (a) length of time since initial settlement, (b) the comparative isolation of particular islands or regions since settlement, and (c) the size and complexity of settlement areas.

Evidence from archaeology and linguistics provides the necessary framework for the study. Detailed archaeological surveys for several of the study regions provides evidence for settlement dates as well as evidence for isolation and/or frequent contact

iii with other areas, usually in the form of trade and translocation of animals and artifacts.

Linguistics, though not as informative as archaeology for settlement dates, provides

detailed evidence for isolation and/or contact in the form of language isolates, language

families, borrowing and linguistic divergence.

The mtDNA haplogroups found in this study belong to several documented

haplogroups, some of Melanesian origin, and some of Southeast Asian origin. The

distribution of mtDNA variants and the pattern and degree of variation was examined using Analysis of Molecular Variance, standard diversity measures and partial Mantel matrix correlations.

There were strong positive correlations between insular area, isolation and degree

of variation. There were also measurable differences between inland and coastal

populations on the larger islands where diversity in the isolated inland populations was

greater than diversity in the coastal population. While there was some confounding of

the variables, the results of our analysis indicate that insular area/complexity and

isolation influence the pattern of variance more than length of settlement time.

iv ACKNOWLEDGEMENTS

I wish to thank Jonathan and Françoise Friedlaender for their work on all facets of the project. I also wish to thank Joseph Lorenz and L. Christie Rockwell for their laboratory instruction and help with project development. I would also like to thank Charles Weitz,

Leonard Greenfield and Theodore Schurr for their comments on the chapters. Thanks are also due to Krista Latham, Elizabeth Rowe and Laura Scheinfeldt.

v DEDICATION

Dedicated to the people who were there from beginning to end my mother – Jacqueline

James, my sister - Hertasha J. James, my aunts - Bobbie J. and Carolyn Ranson and my friend - Raygan L. Harris.

vi TABLE OF CONTENTS

Page

ABSTRACT……………………………………………………………………………...iii

ACKNOWLEDGEMENTS……………………………………………………………….v

DEDICATION……………………………………………………………………………vi

LIST OF TABLES………………………………………………………………………...x

LIST OF FIGURES………………………………………………………………………xi

CHAPTER

1. FRAMEWORK…………………………………………………………………...1

Introduction….…………………………………………………………….1 Archaeology and Linguistics in Oceania………………………………….2 Human Biological Studies in Oceania…………………………………….4 Definition of Geographic Terms…………………………………………..4

2. ARCHAEOLOGY AND LINGUISTICS IN THE SOUTHWEST PACIFIC……7

Introduction………………………………………………………………..7 Archaeology in Melanesia………………………………………………...7

Initial Colonization of Sahul and the Bismarcks...……………….7 Settlement of Manus……………………………………………..11 Holocene Exchange and the Development of Agriculture………13 The Lapita Expansion……………………………………………15 Origins of Lapita and its South Asian Precursors………………..18 Settlement of Remote Oceania…………………………………...20

Conclusions………………………………………………………………22 Linguistics in Melanesia…………………………………………………23

Papuan/Non-Austronesian Languages…………………………...23 Austronesian Languages…………………………………………27

Conclusions………………………………………………………………29

vii 3. BIOLOGICAL EVIDENCE FOR THE SETTLEMENT …………………….…33 OF THE PACIFIC

Introduction……………………………………………………………....33 Early Genetic Studies………………………………………………….…34

Blood Group Distribution…………………………………….….34 HLA………………………………………………………….…..35 Hemoglobinopathies……………………………………….…….36 Immunoglobulins…………………………………………..…….38

Summary of Early Genetic Studies………………………………..……..39 Mitochondrial DNA……………………………………………..……….41

Evidence for the Settlement of New Guinea and……..………….45 Island Melanesia Holocene Sequences and the Settlement of ……………………..47 Remote Oceania

Evidence from the Y Chromosome…………………………………...….51

Near Oceanic Y Chromosome Lineages………………………....52 Remote Oceanic Y Chromosome Lineages……………………...53

Summary of Genetic Data……………………………………………….55

Concordance of Genetic Data…………………………………....55 Discordance of Genetic Data…………………………………….55

Conclusions………………………………………………………………56

4. METHODS OF GENETIC AND STATISTICAL ANALYSIS FOR…………..57 MITOCHONDRIAL DNA RESEARCH IN THE SOUTHWEST PACIFIC

Samples…………………………………………………………………..57 Laboratory Methods……………………………………………………...58

DNA Extraction………………………………………………….58 PCR Amplification…………………………….……………...…59 Sequence Analysis……………………………………………….60

Data Analysis…………………………………………………………….63

Phylogenetic Analysis……………………………………………63

viii Statistical Analysis……………………………………………….63

5. RESULTS OF MITOCHONDRIAL DNA ANALYSIS IN …………………….66 THE SOUTHWEST PACIFIC

Introduction………………………………………………………………66 Haplogroup Distributions………………………………………………...68

Mitochondrial DNA Distribution in New Guinea…….…………68 Mitochondrial DNA Distribution in Manus……………………..80 Mitochondrial DNA Haplogroup Distribution in ……………….81 Easter Island

Haplogroup Distribution Summary…………...………………………….83 Data Analysis…………………………………………………………….85

Network Analysis………………………………………………...85 Population Structure Analysis……………………………………89 AMOVA…………………………………………………………89 Diversity Measures………………………………………………91 Mantel Matrix Correlation……………………………………….94

Summary of Results……………………………………………………...95

6. GENETIC VARIATION AND POPULATION STRUCTIRE …………………97 IN THE SOUTHWEST PACIFIC

Determinants of Genetic Variation………………………………………97 Structure of Genetic Variation in the Pacific…………………………….99 Discussion of mtDNA Variation in the Southwest Pacific……………..109

REFERENCES CITED…………………………………………………………112

LIST OF TABLES

Table Page

4.1 List of Primers for Amplification of HVS I and HVS II……………………………60

4.2 Defining Mutations for mtDNA Haplogroups in the Southwest Pacific…………....62

5.1 mtDNA Lineage Occurrences in the Southwest Pacific…………………………….70

5.2 mtDNA Haplogroup Frequencies……………………………………………….…..71

5.3 AMOVA based on mtDNA (HVS I)………………………………………………..91

5.4 Haplotype Variation within Populations……………………………………………93

6.1 Diversity Measured for Southwest Pacific Islands………………………………...104

6.2 Island Size and Settlement Dates…………………………………………………..106

LIST OF FIGURES

Figure Page

1.1 Map of Oceania and the Geographic Boundary Between Near and Remote…………6 Oceania

2.1 Location of Pleistocene Sites in New Guinea and the Bismarck Archipelago……...10

2.2 Austronesian Language Classifications……………………………………………..30

2.3 Distribution and Sub-Grouping of Austronesian Languages………………………..31

3.1 Human mtDNA Genome……………………………………………………………44

5.1 mtDNA Schematic Tree for Eurasian Haplogroups…………………………….…..67

5.2 Haplogroup P Frequency Distribution………………………………………………73

5.3 Haplogroup Q Frequency Distribution……………………………………………...75

5.4 Frequency Distribution for Haplogroups B and R…………………………………..77

5.5 Frequency Distribution for Haplogroups M27, M28, M29 and E…………………..79

5.6 Frequency Distribution for Easter Island……………………………………………82

5.7 Median-Joining Network for New Guinea, Lineage N……………………………...86

5.8 Median-Joining Network for New Guinea, Lineage M……………………………..87

5.9 Median-Joining Network for Manus and Easter Island……………………………..88

6.1 Equilibrium Model…………………………………………………………………...98

6.2 Median-Joining Network for Haplogroup B……………………………………….107

CHAPTER 1 Framework

Introduction

As information about different genetic loci in human populations has accumulated over the past 30 years, scientists have looked for major factors that have influenced the pattern and degree of genetic variation at them. It has generally been assumed that besides selection acting on specific functioning genes, demographic factors affecting population size and historical migration events were the primary shapers of variation in human populations. This thesis explores the genetic variation in the Southwest Pacific, and links a set of populations with differing degrees of genetic variation to specific factors affecting demography.

Using mitochondrial DNA, this study will analyze the genetic diversity of several islands. The study will also attempt to determine which factors contribute to the observed genetic variation on these islands. The samples used for comparison are from New

Guinea, Manus Island and Easter Island. Additionally, these data will be supplemented with data from three islands located in Northern Island Melanesia (New Britain, New

Ireland, and Bougainville). Previous mitochondrial DNA surveys have revealed highly significant differences in molecular variance across these populations.

Factors such as geographic isolation, and the area, elevation and complexity of islands have been examined to assess their effects on species diversity. In populations of birds, fish and some reptiles, contemporary biogeography argues that the most likely determinants of species diversity on islands including those in the Pacific are (a) length of time since first settlement, (b) the comparative isolation of particular islands or regions

since initial settlement, and (c) the effective sizes of settlement areas (e.g., island size)

(Mac Arthur and Wilson 1967; Mayr and Diamond 2001). These known amplifiers of

variation are expected to cause increases/decreases in genetic diversity when applied to

human populations.

The Southwest Pacific is a diverse region of the world that has been studied

extensively to understand the events leading to its settlement. Students of prehistory now

generally agree that the colonization of the Pacific occurred in two stages. During the

first stage, migration carried hunter-gatherer populations into the landmass Sahul at least

40,000 years before present (BP) (Groube et al. 1986; O'Connell and Allen 2004;

Summerhayes 2007). For thousands of years, Sahul and the islands to its east, from

Island Melanesia through the Solomons, represented the easternmost edge of the human

range. The second migration carried a horticultural population with advanced maritime

technology into the western Pacific and beyond beginning about 3,500 BP (Kirch 1996;

Kirch 1997; Spriggs 1997). This population settled all of the uninhabited islands of the

Remote Pacific. The material culture, languages and genetics of populations in this

region have been studied in an attempt to further understand its settlement and

subsequent population history.

The information gained from this study will add to a body of evidence on the

human settlement of and population movements in the Southwest Pacific. More

specifically, it focuses on regions of the Pacific where little work has been done. For

example, New Guinea has been studied, but rarely has the internal diversity on the island been examined. Many researchers have been interested in differences between New

Guinea populations and Australians (Bellwood 1989; Forster et al. 2001; Attenborough

2005) or differences between Papuans and Austronesians in the greater Southwest Pacific

(Hill et al. 1989; Hurles et al. 2002; Friedlaender et al. 2005a). Little research has been done on the islands in the Admiralties group, and research conducted on Polynesian populations, like research in New Guinea, has focused on the Papuan/Austronesian language dichotomy and how it has influenced genetic variation in the region.

Archaeology and Linguistics in Oceania

In addition to analyzing the mtDNA diversity and its amplifiers in this region, this study reviews the archeological and linguistic evidence for Pacific settlement.

Archaeological data in Oceania reveals evidence for a number of migrations into the region as well as evidence of technological advances, trade and even the rise of agriculture and animal domestication (Flannery and White 1991; Kirch 1997; Denham et al. 2003; Muke and Mandui 2003). This evidence spans the entire period of Pacific settlement from the Pleistocene to the settlement of Remote Oceania not more than 2,000 years ago. It also details the interactions between regions of the Pacific, and sheds light on possible causes for molecular variation in different regions.

The linguistic history of the region is diverse, and research gives insight into the relationships between Papuans on mainland New Guinea and those in Island Melanesia

(Ross 2001; Dunn et al. 2002; Pawley 2005). With the reconstruction of language families, it is possible to determine how people moved within the region and which areas

were centers for developments like maritime technology and agriculture (Bellwood

2002). Linguistics also reveals insight into the most recent migration into the Pacific,

referred to as the Austronesian expansion. Linguists have been able to trace this

language family from its source in Taiwan to the furthest reaches of Remote Oceania

(Pawley and Green 1973; Ross 1989; Pawley 2002). The presence of this language

family in parts of the Pacific is useful in understanding population movements and

interaction.

Human Biological Studies in Oceania

Human biological variation has been studied in this region for some time.

Information gained from early studies on metric and non-metric characteristics of the

skeleton have been used to support models of single versus multiple migrations

(Pietrusewsky 1990; van Dijk 2005). Data from autosomal markers, mitochondrial DNA

and Y chromosome markers have also shown patterns of settlement and movement

(Hagelberg 1997; Lum and Cann 1998; Kayser et al. 2001; Merriwether and Friedlaender

2004).

Evidence from genetic studies has primarily been used to understand the

settlement history of Polynesia and the evolution and movement of the so called

“Polynesian Motif” (haplogroup B4a1a1)(Redd et al. 1995; Lum et al. 1998; Merriwether and Friedlaender 2004) . More recent research has focused on other issues including the settlement of New Guinea and Island Melanesia and diversity in Papuan populations

throughout Melanesia (Friedlaender et al. 2005a; Scheinfeldt et al. 2006).

Definition of Geographic Terms

The Southwest Pacific has been divided into several overlapping geographical

regions. The primary division for understanding the history of Pacific settlement is

between Near Oceania and Remote Oceania (see Figure 1.1). Near Oceania is the region

that includes Papua New Guinea and the main islands in the Solomons chain. Remote

Oceania is made up of Santa Cruz, Vanuatu, New Caledonia, Fiji, Tonga, Samoa, and the

rest of Polynesia and Micronesia.

Melanesia includes mainland New Guinea and all the islands south of the equator

including Fiji in the east and New Caledonia in the south, with the exception of

Micronesian Nauru. Papua New Guinea is made up of the eastern half of New Guinea

(the Indonesian province, Papua, covers the western half), Manus, New Britain, New

Ireland and Bougainville. The islands to the east of New Guinea are part of the Bismarck

Archipelago, which includes New Britain, New Ireland, Manus, Mussau, New Hanover

and Bougainville.

Triangle Polynesia encompasses the land from Hawaii in the north, Easter Island

in the east and New Zealand in the south and all the islands within the triangle. It is

further separated into eastern and western regions. Western Polynesia is made up of

Tonga, Tuvalu, Samoa and several Polynesian outliers. Eastern Polynesia is made up of

the Cooks, Marquesas, Hawaii and Easter Island.

5 Figure 1.1 Map of Oceania. Geographic Boundary Between Near and Remote Oceania.

Near Oceania

New Ireland

New Guinea Bougainville New Britain

Santa Cruz 6

Vanuatu

Fiji

Australia New Caledonia Remote Oceania

Boundary of geographic region 0 1000 km

CHAPTER 2 Archaeology and Linguistics in the Southwest Pacific

Introduction

This chapter outlines the archaeological history of three distinct regions, New

Guinea, Island Melanesia (including the island of Manus) and Polynesia (including Easter

Island). These locations offer important contrasts in a number of features. First, the regions were settled at different times. New Guinea and Island Melanesia were among the first places settled in the Southwest Pacific. Manus, located to the northeast of New

Guinea, and having a considerable water crossing between the islands, was settled by

20,000 BP, whereas Easter Island at the easternmost end of triangle Polynesia was settled not more than 2,000 years ago with the rest of Polynesia. Second, the mode of settlement was different for each due in part to (1) geographic location (2) distance from other settled areas and (3) the ease and or difficulty in settling the region. These factors are believed to affect genetic diversity. The manner in which these differences in settlement time, distance from previously settled areas and difficulty in access affect genetic diversity should be apparent from an examination of genetic diversity patterns in populations from this region.

Archaeology in Melanesia

Initial Colonization of Sahul and the Bismarcks

At the time of their initial settlement, during the late Pleistocene, New Guinea,

Australia and Tasmania made up the large landmass called Sahul. At this time, the

islands to the east including Java, Borneo and Bali were joined with Vietnam and the

Malay Peninsula to form the large continent of Sunda, the suspected origin of Sahul colonists. Archaeological data is currently unable to pinpoint the exact location and time of the migration from Sunda into Sahul. The first evidence of human occupation in

Southeast Asia, a skull found at Niah Cave (Borneo) and stone tools at Lang Rongrien

(Thailand), can be dated between 42,000 to 43,000 BP, and it is contemporary with the evidence of human occupation in Sahul (Summerhayes 2007).

The settler population traveled one of two possible routes into the region. The first, a southern route, passed through Timor into either the Sahul Shelf or the Aru

Islands. Sites along this route, including Lene Hara in East Timor, have been dated between 30,000 and 35,000 BP (O'Connor et al. 2002). Also along the southern route, dates of 26,000 BP have been found at Liang Lemdubu in the Aru Islands (Spriggs 1998).

The second route passed through a series of islands, including Halmahera, into West

Papua (Bellwood et al. 1998). Evidence for occupation along the northern route has been found, east of Halmahera, at Golo and Wetef Caves and dates to 33,000 BP (Bellwood et al. 1998).

All of the sites along the proposed routes for settlement of Sahul are younger than those found in New Guinea. However, this apparent discrepancy may be due to the destruction of earlier coastal sites after the last glacial maximum, and also a general lack of archaeological knowledge of the region (Summerhayes 2007). Any populations entering New Guinea would have passed through West New Guinea. The oldest site in this region has been dated to 26,000 BP at Toe Cave, but like the regions to the west of

New Guinea, archaeological knowledge of this region is minimal (Pasveer 2004).

During the initial colonization of Sahul, people rapidly spread throughout the

region to colonize areas from Australia to the Solomons. There is evidence of human

occupation in Australia as early as 60,000 BP (Bowler et al. 2003). Thermoluminescence

dates of “waisted blades” found on the reef terraces of the Huon Peninsula (see Figure

2.1) in northeast New Guinea date to at least 40,000 to 50,000 BP (Groube et al. 1986;

Allen et al. 1989; O'Connell and Allen 2004). Similar dates of 39,000 BP, based on

radiocarbon dating, have also been uncovered at Lachitu Cave along the north coast near the Indonesian border (Lilley 2006; Summerhayes 2007).

Occupation of the Bismarck Archipelago, east of mainland New Guinea, would have required some sea faring technology since New Guinea, New Britain and New

Ireland were never joined. Colonization of New Guinea and the Bismarcks must have occurred simultaneously, and colonization of the Solomons occurred shortly after, by

28,000 BP (Wickler and Spriggs 1988; Allen et al. 1989). The oldest site in the Bismarck

Archipelago, Buang Merabak, a cave site on New Ireland, has been dated to 39,500 BP and sites in southern New Ireland at Matenkupkum support this early colonization of the region. New Britain also has a number of sites that can be dated to the time of initial colonization – Yombon 35,000 BP and Kupona na Dari 35,000 to 45,000 BP (Pavlides and Gosden 1994; Torrence et al. 2004; Summerhayes 2007) showing that there was no time gap in the settlement of New Guinea and Island Melanesia (Leavesley 2006).

There is a single Solomon Islands site, Kilu Rockshelter on Buka Island, dating to

28,000 BP. Buka is at the northern end of the Solomons (Wickler and Spriggs 1988).

Early occupation of the rest of the main Solomons chain, as far as San Cristobal, is assumed since the islands are all intervisible. In addition, at the last glacial maximum,

the islands from Buka to Nggela formed one landmass called Bukida, and Guadalcanal,

Malaita and San Cristobal were separated from Bukida by a narrow strait (Wickler and

Spriggs 1988).

Baung Merabak

Manu s Balof

Pamwak New Ireland Matenkupkum Huon

New Guinea

New Britain Yombon

0 200km

Figure 2.1 Location of Pleistocene sites in New Guinea and the Bismarck Archipelago.

Early settlers were broad spectrum hunters and gatherers that exploited both sea and terrestrial resources (Allen et al. 1989). They would have relied heavily on coastal resources as is evidenced by the number of sites near the coast along the migration route, and the fact that coastal resource acquisition would have been familiar and left no need for rapid adaptation to the new environment. There is even evidence of coastal marine resource use at Matenkupkum Cave (Allen et al. 1989).

However, people did not remain confined to the coast, as by 30,000 to 26,000 BP, there is evidence of movement into the highlands of New Guinea (Kirch 2000;

Summerhayes 2007). The first highland sites were located on the fringe of the forest and grasslands, and people were able to exploit both ecological zones. There is evidence of this move into the mountainous region at early sites Nombe (1,669 m above sea level) and Kosipe (2,000 m above sea level) (White et al. 1970; Gillieson and Mountain 1983).

Once in the highlands, people would have been able to hunt larger prey, which may have attracted them to the region in the first place. Evidence suggests population numbers were still small, and there were no large permanent settlements, only camps and seasonal bases (Spriggs 1997; Kirch 2000; Lilley 2006). The previously mentioned open site,

Yombon in New Britain, is also inland. This rainforest site is the oldest non-coastal site in Near Oceania, in contrast to the New Guinea highlands site, Yombon is lowland

(Pavlides and Gosden 1994).

Settlement of Manus

People occupied the island of Manus for the first time at or before 20,000 BP

(Ambrose 2002). One site on the island, Pamwak Rockshelter, has been dated to this first

period of occupation. However, the initial settlement date could be older as is evidenced

by as yet undated materials from the lowest levels of the shelter (Fredricksen et al. 1993;

Spriggs 1997). Even with undated layers, it is a site rich in stone artifacts.

The journey to Manus was made either by island hopping from New Ireland via

New Hanover and Mussau, or from the north coast of New Guinea (Irwin 1992; Spriggs

1997). Either route required an open sea crossing of more than 200 kilometers, with a

stretch of 75 kilometers where there was no inter-island visibility (Irwin 1992; Leavesley

2006). Considerable maritime technology would have been necessary for such a voyage.

It is the only island settled during the Pleistocene, where there were no intervisable

islands for 60 – 90 kilometers (Spriggs 1997).

The initial settlement of Manus was not an isolated event. There is evidence of a

second period of occupation at Pamwak. Animals (cuscus and bandicoot) and nut trees

from New Guinea have been found in layers at Manus dated to 13,000 BP (Specht 2005;

Summerhayes 2007). At 10,000 to 12,000 BP, Rattus praetor was introduced from New

Guinea, again showing either multiple migrations or at least multiple periods of contact between Manus and New Guinea (Summerhayes 2007)

Roughly contemporaneous with the initial settlement of Manus, there is evidence of renewed contact between New Guinea and the Bismarck Archipelago in the movement of animals and goods (Summerhayes 2007). We see the appearance of animal species particularly, Phalanger orientalis, for the first time in New Ireland at around 23,500 to

20,000 BP at Matenbek and Buang Merabak, and at Matenkupkum at 16,000 BP

(Flannery and White 1991; Allen 1996; Leavesley and Allen 1998; Grayson 2001;

Leavesley 2005). Rattus praetor has been found at Panakiwuk, northern New Ireland, in

levels dating to 15,000 BP (Marshall and Allen 1991). Both species are indigenous to

New Guinea and not previously seen in New Ireland (Allen et al. 1989). Other animals

that were introduced to the Bismarck Archipelago during the Pleistocene include other rat

species, Rattus mordax and Melomys rufenscens, and the bandicoot Echympera kulubu

(Flannery and White 1991). New varieties of obsidian were also introduced to regions where it was not previously found (Summerhayes 2007). Obsidian from west New

Britain has been found in 20,000 year old sites in southern and central New Ireland

(Summerhayes and Allen 1993).

Holocene Exchange and the Development of Agriculture

There is evidence that early inhabitants altered the environment by clearing land and burning vegetation, possibly for subsistence (Haberle 2003). It has been postulated that the ‘waisted blades’ found at Huon were used for forest edge manipulation (Irwin

1992). There is evidence for the emergence of agriculture in the highlands of New

Guinea in the mid-Holocene around 10,000 BP (Denham et al. 2003). Increased human presence is evident at Nombe Rockshelter by an increase in stone tools, burnt bone and midden material. There is also evidence of Pandanus processing at Marin in the

Highlands, indicating the possibility of a permanent camp there, which is often only seen

after the advent of agriculture (Summerhayes 2007). Most evidence of this early

agriculture is found at Kuk Swamp (Lilley 2006).

The development of agriculture in this region has been separated into six distinct

phases.

Phase 1, dating from 9,000 BP, has agricultural evidence in the form of gutters, hollows and stake holes probably used for water control. Phase 2, from 6,000 to 5,000

BP, shows evidence of forest clearance and of structures and channels that may have been used for taro cultivation and raised beds for other crops. At Phase 3 (4,000 to 2,500

BP), there is evidence of channels to drain water from agricultural areas. Phase 4 shows the development of patterns of long straight ditches for the enclosure of square or rectangular plots, thought to be planting areas for a single crop.

Both Phases 5 and 6 contained increasingly elaborate systems of drainage, and there is the first evidence of sweet potato cultivation. The final evidence for agriculture is seen with the possible appearance of the pig at Kafiavana, Yuku and Kiowa (Spriggs

1997; Matisoo-Smith 2007). Since the domestication of pigs is generally associated with agriculture, this could be viewed as evidence for the early development of agriculture.

Later during this agricultural period, bananas, sugar cane and tubers were all domesticated in New Guinea. These changes in subsistence would have had a major impact on population size and settlement patterns.

Contemporary with the development of agriculture there is evidence of exchange between New Guinea and Island Melanesia in the distribution of bird shaped pestles and mortars dating between 8,000 and 3,750 BP (Swadling and Hide 2005). Obsidian from

New Britain has also been found on mainland New Guinea, even in the highland region.

Since obsidian is indigenous to New Britain, the Admiralties and Fergusson Island, but not New Guinea, it represents clear evidence of exchange between these regions

(Summerhayes 2007). Obsidian has been found at Kafiavana in layers dating to 4,500 BP and in the Sepik Ramu region (Swadling and Hide 2005). Once again, new animals were

introduced to the Bismarck Archipelago from New Guinea. For example, the wallaby has been found in the New Ireland site Balof 2 dated to 8,400 BP (White et al. 1991),

Buang Merabak dated to 6,200 BP (Leavesley and Allen 1998) and Panakiwuk dated to

2,000 BP (Marshall and Allen 1991).

Manus has two sites dated to the Holocene. The first, the Peli Louson rockshelter, has been dated to between 4,850 and 4,500 BP, and an open coastal site Father’s Water has been dated to between 4,850 and 4,500 BP (Spriggs 1997). Peli Louson has archaeological sequences similar to those at Pamwak with the addition of pottery deposits and evidence of local obsidian use. The Father’s Water site also has small amounts of pottery in the upper layers and obsidian in the lower deposits (Spriggs 1997). The pottery found on Manus has surface decoration similar to what has been seen at Lapita sites

(Ambrose 1997).

It is clear that there was trade between different areas of Near Oceania during the

Pleistocene and early Holocene. The most contact occurred between islands in Island

Melanesia, but there is also evidence of contact between New Guinea and the Bismarcks.

The Lapita Expansion

There was a major movement of people and animals in the Southwest Pacific, as well as the first signs of human occupation of areas to the east of the Solomon Islands chain, commencing at about 3,500 BP. The archaeological phenomenon associated with this movement is called Lapita, after one of the first sites where distinct artifacts were found, in New Caledonia, which is dated to 2,800 BP (Kirch 1997). Lapita sites have been found across the western Pacific from Manus in the Admiralties and the Vitaz

Straits (between New Guinea and New Britain) in the west, to Tonga and Samoa in the east (Spriggs 1995; Walter and Sheppard 2006).

The main evidence for the expansion is seen in highly decorated dentate stamped pottery, which appears to be intrusive since earlier archaeological sites lack such materials (Kirch 1996; Summerhayes 2007). The oldest Lapita dates are found in the

Bismarcks at 3,300 BP, followed by sites in the southeast Solomons and Vanuatu by

3,100 BP, Fiji by 2,900 BP and Tonga and Samoa by 2,800 BP (Summerhayes 2007).

However, the pottery is not the only evidence of intrusive culture. We also see the introduction of domesticated pigs, dogs and chickens, as well as the Polynesian rat,

Rattus exulans (Spriggs 1995; Allen 1996). In addition, we see the introduction of stone adze kits and shell ornaments, as well as the movement of obsidian from the Admiralties as far west as Borneo and as far east as Fiji. Furthermore, there is evidence of extensive forest clearance and higher than previous rates of erosion, and the movement of domesticated plants never before seen in this region (Spriggs 1995).

In addition to the new artifacts at Lapita sites, there was a change in the size and types of settlements. All pre-Lapita sites were either rockshelters, caves or open sites located away from the coast (Spriggs 1997). With the advent of Lapita, there is evidence of large settlements on coastal beaches or even stilt houses built over shallow lagoons

(Kirch 1997; Spriggs 1997). Throughout the region, Lapita sites remain homogenous. At most Lapita sites, there are large numbers of portable artifacts such as stone and shell adzes, flake tools made from obsidian and chert, shell scrappers and peelers, bracelets, rings, beads and tattooing chisels.. Lapita peoples also developed a new form of sea faring that allowed them to travel longer distances in outrigger canoes (Kirch 1997).

Their presence provides evidence that settlements either remained in constant contact

with other settlements or at least maintained frequent contact (Kirch 1997; Summerhayes

2007).

Archaeologists have used the changing themes in Lapita pottery to place sites in

an east to west chronological framework (Summerhayes 2007). Stylistically, there is a

tendency towards increasing simplicity through time, both in motif forms and the

declining number of vessel types. The latest Lapita ware is either entirely plain or

decorated with applied relief designs. There are three recognized sub-styles of Lapita

pottery (Spriggs 1997):

I. Far Western or Early Western Lapita is restricted to the Bismarcks and

dates from 3,500 to 3,200 BP; it represents the most complex vessel

forms and the most elaborate decorations

II. Western Lapita (WL) is found after 3,200 BP in the Bismarcks,

Solomons, Vanuatu and New Caledonia; its forms are less elaborate in

form and decoration. In most regions where WL was found, it was gone

by 2,700 BP.

III. Eastern Lapita is found in Fiji and Western Polynesia at 3,000 BP; the

simplest forms are seen here and they disappear 2,000 years ago.

Aitape on the north coast is the only New Guinea site where Lapita pottery has been found (Spriggs 1995).

Origin of the Lapita culture in Southeast Asia is not supported by all scholars.

Some have argued for a local development of Lapita in the Bismarck Archipelago with

minimal impact from Southeast Asia (Green 2003; Galipaud 2006). This and other

models for Lapita origins and expansion will be further discussed.

Origins of Lapita and its South Asian Precursors

Lapita has been proposed to be a cultural complex that moved into Melanesia and

beyond from Island Southeast Asia. If people carrying Lapita culture migrated from

Island Southeast Asia, then there should be evidence of Lapita or pre-Lapita

archaeological assemblages in that region. Precursors of the Lapita cultural complex

have been found in Taiwan at 4,500 BP, and Halmahera at 3,550 BP (Kirch 1997;

Summerhayes 2007). The archaeological assemblages in Taiwan contain red slipped

pottery dating from 4,350 to 3,850 BP. Vessel forms include bowls and dishes on

pedestal feet and large globular jars with everted rims (Ambrose 1997). Sites in the

region also contain fishhooks made of bone or shell, net sinkers, polishing stones and

shell rings, all seen in later Lapita assemblages (Kirch 1997).

Similar assemblages are also observed in the Philippines, and, by the time pottery reached the Philippines, we see the beginning of dentate stamping, which is similar, but not identical to that seen in Lapita (Kirch 1997). Further east, in the Wallacea region, there is evidence of red slipped pottery with incised designs, the closest match to Lapita.

It is the most compelling archaeological evidence of the Island Southeast Asian origin of

Lapita in both vessel form and decorative motif. However, even with the evidence of

Lapita precursors, there is debate as to the amount (if any) of Island Southeast Asian influence on Lapita and ultimately on the settlement of the furthest region of Oceania,

Polynesia.

Given this debate, there are several proposed models for the Lapita/Austronesian expansion.

The Express/Fast Train model, proposed and supported by Jared Diamond and

Peter Bellwood, compares the movement of people from Island Southeast Asia to

Melanesia to a rapid train journey with few to no stops (Diamond 1988; Green 2003).

They describe the Austronesians as sea-borne colonists who expanded rapidly through

Melanesia and into Polynesia, and state that Lapita must be recognized as the archaeological record of a significant population intrusion. However, Bellwood’s view of the model does allow for the dropping off of “boxcars full of colonists” along the way

(Bellwood et al. 1995; Kirch 1997). In this model, we would expect to see evidence of a

definitive intrusion of a Lapita population in Melanesia, but no evidence of Melanesian

culture in Polynesia. There was time to drop off, but pick ups were never mentioned

(Bellwood 1989).

Allen (1984; 1989) proposed the Indigenous Melanesian Origins model.

According to this model, changes in the archaeological record were not influenced by a

migrating population, but were caused by a set of complex social and subsistence changes

taking place in Melanesia over a period of 35,000 years. The only item borrowed from the west in this model is pottery; all other aspects of the Lapita Cultural Complex are wholly indigenous. This does not mean there was no contact between east and west, but that this contact did not result in the one-way flow of technology from west to east.

The Slow Boat Model supports the origin of Lapita in Island Southeast Asia, but adds a period of 300 years in the Bismarck Archipelago, where it evolved before spreading to Remote Oceania (Oppenheimer and Richards 2001a; 2001b; Kayser et al.

2006). The migration from Island Southeast Asia was not rapid and there were many stops along the route. This model draws on the concept of the voyaging corridor where people had time to share both genes and culture on the trip through Near Oceania.

The final model for the origin of Lapita is the Triple I Model

(intrusion/innovation/integration), supported by Green and Kirch (Kirch 1997; Green

2003). In Triple I, we see the movement of Austronesians into Melanesia from Island

Southeast Asia carrying their distinct material culture (intrusion). New developments occur within the Bismarcks (innovation), and elements of this material culture are adopted (integration) (Green 1991).

Archaeological evidence best supports a model that allows for the development of

Lapita social forms, settlement and animal domestication outside of the Bismarcks, as there is no evidence in the archaeological record that supports the emergence of this cultural complex in this region over the preceding 35,000 years of human settlement.

Settlement of Remote Oceania

After 300 years in the Bismarck Archipelago, during which the full Lapita

Cultural Complex developed, the Austronesian-speaking descendants set out to colonize

Remote Oceania (all Oceanic Islands east of the main Solomons chain), which required considerable ocean crossings of 350 kilometers at a minimum (Dunford and Ridgell

1997; Lilley 2006). We see the almost simultaneous colonization of the Reef-Santa Cruz

Islands, Vanuatu, New Caledonia, Fiji, Tonga and Samoa. This expansion is reflected in the presence of Eastern Lapita as well as obsidian, stone adzes and chert (Kirch 2000).

After initial colonization, the islands became isolated, and this isolation led to the

formulation of the distinctive Western Polynesian culture – the first development of

Polynesian culture as it is currently recognized.

Eastern Polynesia, made up of the Societies, Cooks, Australs, Marquesas,

Taumotus, Hawaii, Easter Island and New Zealand, and was the last Pacific region to be settled. A number of archaeological sites have been uncovered in Eastern Polynesia, many of which are small coastal villages or hamlets, much like those seen in early Lapita sites (Kirch 2000). The sites provide evidence for horticulture and animal husbandry, especially dogs, pigs and chickens as seen in Lapita sites (Picker 1974). Archaeologists recognize many innovations in adze construction, fishing technology, canoe construction, ornamentation, weaponry and tattooing (Dunford and Ridgell 1997; Kirch 2000). Little or no pottery has been found in Eastern Polynesia and, of the few pottery sherds found, a majority of those are thought to be from Tonga. The lack of pottery in the region has been linked to poor pottery making clays (Claridge 1984).

The picture of Eastern Polynesian settlement is one of early widespread contact followed by isolation. The earliest archaeological site, found in the Marquesas, can be dated to 2,500 to 2,000 BP (Irwin 1992). It appears that this island group was settled first, and was a dispersal center for later colonization of Hawaii, Easter Island and the

Societies. There is evidence for the settlement of Hawaii and the Societies by 2,000 BP

(Irwin 1990).

The timing and process of the colonization of Easter Island has been debated. It is generally accepted that Easter Island was settled by Polynesians from the west.

However, the presence of the South American sweet potato and bottle gourd and evidence of a possible route from South America suggests early South American contact

(Martinsson-Wallin and Crockford 2001) and possible settlement of Easter Island by

Amerindians (Heyerdahl 1952). This is not well substantiated, and the partially South

American origin of Easter Islanders has not been supported by other studies, and more recent archaeological research in the region has led to the discovery of more Polynesian commensals like R. exulans and Polynesian root crops (Hunt and Lipo 2006). Dates for the earliest layers of occupation for Easter Island place its settlement at approximately

1,200 cal AD (Hunt and Lipo 2006).

Conclusions

Archaeological evidence shows at least two major migration events into the

Pacific. After the initial settlement of Near Oceania, there is almost constant contact between the islands of Melanesia, as well as evidence of some isolation in the highlands of New Guinea. The settlement of Manus Island occurred relatively early considering its distance from already settled regions, and there is evidence of contact between Manus and New Guinea in the Pleistocene, and Manus and Island Melanesia in the Holocene.

Of the aforementioned settled regions in Near Oceania, the highlands are the most remote and difficult to access, making them a prime location to test the effects of isolation as well as early date of settlement.

In terms of human settlement, the pattern of colonization of Remote Oceania is not as complex as Near Oceania. There is evidence of only one major population movement into this area. The islands are considerably smaller and the ocean crossings are larger. Eastern Polynesia, particularly Easter Island, is a region of interest for this study because it demonstrates extreme isolation and a small insular area. It is also close

to the Remote Oceanic line of extinction that separates islands that were initially

occupied then abandoned from those which were continuously occupied.

Linguistics in Melanesia

The linguistic history of the Pacific is as diverse as the archaeological record, and has proven to be useful in understanding population history. Together, New Guinea and the western Pacific contain more than 1,200 of the world’s languages, making it one of the most linguistically diverse regions in the world (Foley 2000). The languages can be separated into two broad families, Papuan or non-Austronesian and Austronesian. The

Papuan language group is a residual group whose languages are the descendants of those spoken for millennia by the first colonists of the Pacific, beginning more than 40,000 years ago. Austronesian is younger in the region, and can be traced to a migration not more than 4,000 years ago.

For Pacific scholars, languages offer secure evidence for tracing the origin and affinities of human populations (Bellwood 1989). However, because languages change so rapidly, it is difficult to determine the remote origins of long established populations like so many in the Pacific. Here, we will discuss the origin and dispersal of the Papuan and Oceanic language families in the Pacific and determine whether linguistics supports, or refutes evidence from archaeology.

Papuan/Non Austronesian Languages

Papuan languages extend from Timor and Halmahera through New Guinea and into parts of the Bismarcks and Solomons (Bellwood 1989; Pawley 2002). Linguists

classify languages as Papuan based on three criteria: (1) they must be indigenous to New

Guinea or the nearby island groups; (2) they must not belong to the Austronesian language family; and (3) they must not have relatives outside the Melanesia-East

Indonesia region (Pawley 2007). Given these specifications for placement in the Papuan language family, many languages can be classified as Papuan yet share few to no characteristics with other languages in the family. It is often just a label used for all the

‘genetically’ diverse non-Austronesian languages between Australia to the south and the

Austronesian speaking area to the west, north and east (Pawley 2007).

Currently, there are more than 900 languages spoken in New Guinea, 750 of which are Papuan with an additional 50 Papuan languages spoken on islands surrounding

New Guinea (Pawley 2007). Linguists have used various methods to draw historical inferences about these languages. The research on them is still in the early stages when compared to that on language families like Austronesian and Indo-European. However, in the time since this work began, a number of conclusions have been drawn about the relationships between Papuan languages.

Early work carried out before the 1960s produced preliminary language classifications that separated non-Austronesian languages into 60 families (Pawley 2004;

2007). Linguists continued work in hopes of lumping the small groups into larger language families on the bases of lexicostatistics and typological arguments. The number was greatly reduced by Wurm (1983) to 10 families with at least 10 additional language isolates. He also pioneered the construction of the first large Papuan language family, the

Trans New Guinea Phylum (TNG) (Wurm 1975). Based on his work, nearly 500 languages were assigned to the Trans New Guinea Phylum, another 90 were assigned to

the Sepik Ramu Phylum, and all of the Papuan languages in Island Melanesia and Yeli

Dnye (spoken in the Louisiade Archipelago off the south-eastern tip of New Guinea) were assigned to the East Papuan Phylum (Wurm 1975; Pawley 2007). However, there was much criticism of this early classification. The East Papuan Phylum was found to be invalid due to lack of evidence, while the TNG and the Sepik Ramu Phylum appeared promising and worthy of further study (Pawley 2007).

A few concerns with TNG, as proposed by Wurm, centered on the methods used to construct the language family. The lexicostatistical evidence, with its low cognate percentages between branches, could not definitively prove ‘genetic’ relationships between languages. Too much emphasis was placed on structural resemblances even though these features could be borrowed or lost. The principal method of historical linguists, used in the construction of language families, the comparative method (CM), was not properly applied in this case (Lindstrom et al. 2007; Pawley 2007). CM identifies linguistic elements that are shared by related languages that were retained from the common ancestor, and draws historical inferences from the results.

Ross’ (1995) application of the comparative method to Papuan languages separated then into 23 families, with 9 or 10 languages that could not be assigned a specific family. Later work on TNG by Ross and Pawley has reduced it in size. The new classification is based on 200 putative cognate sets, regular sound correspondence, personal pronouns and resemblances in other grammatical paradigms (Pawley 1998;

2000). In Wurm’s classification, 256 languages were placed in TNG and another 235 were assigned as marginal members. Pawley’s new classification places 350 languages in TNG with another 100 tentatively assigned to the group. With the new classification,

TNG runs almost the full length of New Guinea, dominating all of the inhabited regions of the central highlands from the Bird’s Head to southeast Papua.

Based on the density of high order sub-groups, the region of greatest diversity is located between the Strickland River and the Eastern Highlands Province together with

Madang and Morobe Provinces, marking this area as a possible homeland for the TNG expansion (Pawley 2007). Using Bellwood’s farming and language dispersal hypothesis,

TNG could have spread partially due to the development of agriculture in the region more than 9,000 years ago (Bellwood 2002; Pawley 2002). Agriculture has been linked to the spread of major language expansions based on the idea that populations with agriculture possess significant advantages over non-agricultural populations and these advantages allow them to colonize very large regions (Adams and Otte 1999; Bellwood 2001;

Oppenheimer and Richards 2002). The dispersal of TNG is suspected to have occurred

7,000 to 10,000 BP, which corresponds to dates for the development of agriculture at

Kuk (Denham et al. 2003; Summerhayes 2007). The timing and location of the dispersal are consistent with the farming and language dispersal hypothesis. TNG is the largest of the Papuan language families, and it seems unlikely that it would have covered such a wide range without the speakers having some cultural advantage.

The Papuan languages of Island Melanesia cannot be confined to an East Papuan

Phylum (Ross 2001; Dunn et al. 2002). Instead, the languages of New Britain can be separated into two groups, the East New Britain and West New Britain Families, and two isolates, Sulka and Kol. There is only one Papuan language spoken in New Ireland. The

Papuan languages of Bougainville fall into two families (North Bougainville and South

Bougainville). There are a few Papuan languages scattered throughout the Solomons that appear to be distantly related.

Austronesian Languages

In contrast to the situation with Papuan languages, tracing the origin and dispersal of Austronesian languages is easier because the expansion occurred within the last 5,000 to 6,000 years (Bellwood 1989). Since the spread is recent, these languages retain multiple and clear traces of their relationships, making them subject to the standard comparative method. Austronesian is one of the largest language families in the world, stretching from Madagascar in the west to Easter Island in the east (Lilley 2006). In between these two regions, Austronesian is spoken in Southeast Asia, the Bismarcks, the main Solomons and in some lowland and coastal parts of New Guinea. There are more than 1,200 Austronesian languages spoken worldwide, including more than 150 Oceanic languages in Island Melanesia and all of the languages in Remote Oceania, since they were the only languages spoken in that region prior to European contact (Pawley and

Green 1973).

Linguists place the spread of Austronesian from Southeast Asia at 6,000 to 5,000

BP and its arrival in New Guinea by 3,000 BP (Bellwood 1995). The greatest diversity and the most conservative forms of Austronesian are found in Southeast Asia, and more specifically Taiwan, where nine main branches are found, indicating that this is the homeland of all Austronesian languages (Blust 1984; Meacham 1984; Foley 1992;

Pawley and Ross 1993; Gray and Jordan 2000). The use of linguistic terms points to a

Neolithic pottery-using society with rice agriculture, domesticated pigs and dogs and a developed technology for sailing and house construction (Kirch 1997).

Once the precursor of Proto-Oceanic Proto-Malayo-Polynesian left

Taiwan/Southeast Asia, it split into a number of sub-families, in part due to isolation and also to innovation. Languages belonging to this family east of Indonesia are part of the

Oceanic sub-branch of Austronesian (see figure 2.1) that diverged from Proto-Malayo-

Polynesian in the area of Cenderwasih Bay and southern Halmahera west of New Guinea

(Pawley and Ross 1993; Pawley 2002; Lilley 2006). The Oceanic subgroup makes up

50% of the Austronesian languages spoken throughout the world (Ross 1989).

In Melanesia, Oceanic is separated into several large sub-groups that appear to have diverged over a long period of time. There is a North New Guinea group of languages spoken along the north coast of New Guinea and in New Britain (see Figure

2.3). Languages belonging to the Meso-Melanesian cluster are spoken in the rest of the

Bismarck Archipelago through the northern Solomons. Austronesian languages spoken in the Admiralties, including Manus, are part of the Admiralties Cluster, while the

Oceanic languages spoken in southern New Guinea are in the Papuan Tip Cluster (Ross

1988).

Once Austronesian spreads beyond Western Melanesia, the sub-grouping simplifies. One group, Remote Oceanic, includes the languages of north and central

Vanuatu, Fiji and Polynesia (Pawley 2002).

Language distribution in Polynesia, just like archaeology in the region, presents a picture of very recent settlement by a population of linguistically homogenous individuals. All of the languages in Polynesia belong to the Central Pacific branch, and

the differences between languages can be explained by isolation and innovation (Green

2003). Since many of the languages have been diversifying for less than 2000 years, they

are homogenous and, in some cases, remain mutually intelligible.

Conclusions

Evidence for two distinct language families supports archaeological findings of

two separate migrations into Near Oceania. The complexity of Papuan languages goes to

show that time since settlement and isolation both have a pronounced effect on language diversity. The spread of TNG also lends support to the idea of an independent origin of agriculture in Near Oceania prior to the Austronesian expansion.

In New Guinea and Island Melanesia, Austronesian (Oceanic) languages are restricted to the coast. This pattern corresponds well with the presence of Lapita sites found predominantly in coastal regions. In addition, the presence of Austronesian languages in coastal regions of New Guinea and Island Melanesia and the complete disappearance of Papuan languages in the Admiralties lends strong evidence to the idea of Lapita and Proto-Oceanic being a combined introduced phenomenon, rather than an indigenous one, due to the fact that the two are most often seen in conjunction.

Proto Austronesian

Formosan Proto Malayo-Polynesian

Western Malayo- Proto Central- Eastern Polynesian Malayo-Polynesian

Central Malayo- Proto Eastern Polynesian Malayo-Polynesian

South Halmahera- West New Guinea Oceanic

Figure 2.2 Austronesian language Classifications (After Pawley and Ross, 1993).

Proto-Oceanic

2.2a Distribution of Oceanic languages

Admiralties Southeast Nuclear Central/North New Caledonia- Solomonic Micronesian Vanuatu Loyalties

Western Oceanic Central Pacific

North New Meso- Fijian Polynesian Guinea Melanesian

Papuan Tip Rotuman

2.2b Partial sub grouping of Oceanic languages Figures after Pawley and Ross, 1993

Figure 2.2 Distribution and Sub-Grouping of Austronesian languages.

Similar to the archaeological findings, the Bismarck Archipelago played an important role in the development and spread of Proto-Oceanic. Outside of Taiwan, the complexity of Austronesian languages is greatest in the Bismarcks, marking this as an area for the dispersal of Oceanic languages to the rest of the Pacific. Linguistic patterns in the Remote Pacific are simple compared to those in Near Oceania. With only one language family in the region and a recent divergence time, the languages are quite similar and can be broken into a few subgroups.

Evidence from both archaeology and linguistics supports a dual origin of Pacific populations. Evidence from both disciplines is crucial in determining when and from where Pacific regions were settled. Both also play a role in understanding isolation and interaction or lack of interaction between populations in the study region.

CHAPTER 3 Biological Evidence for the Settlement of the Pacific

Introduction

The archaeological and linguistic evidence used to understand the population history of the Pacific has more recently been complimented by biological data. Major hypotheses have been put forth to explain the initial settlement and subsequent population movements and intrusions. These theories have been supported by archaeology, linguistics and/or genetics, with the most conclusive theories being supported by multiple lines of evidence.

Much of the early research in the region focused on the dichotomy of languages spoken in New Guinea and Island Melanesia that was thought to reflect separate origins for non-Austronesians and Austronesians (Bellwood 1975). It is true that, in some areas,

Austronesian language speakers are genetically homogenous when compared to non-

Austronesian language speakers, but determining the source of these differences is difficult, especially since the differences could result from selective and evolutionary processes acting on a single genetic stock (Terrell 1986). For this reason, many genetic surveys have been carried out to aid in the understanding of Pacific prehistory.

Polymorphisms of nuclear gene encoding proteins were the first type of variants studied in human populations. Since this early research, other forms of genetic variation have become increasingly important, such as the polymorphisms affecting uniparental genetic systems, mitochondrial DNA and Y chromosome DNA. These systems have proved particularly important because of their mechanism of inheritance and genetic properties.

Early Genetic Studies

Blood Group Distribution

The first genetic studies done in New Guinea examined blood group distributions and found differences in the frequencies of ABO and MN blood group antigens between

Austronesians and non-Austronesians (Walsh et al 1953). In the Pacific, the frequency of blood groups varies from one area to the next, but some trends are still visible. In the highlands of New Guinea, type B is found in 10-20% of the population, and type A is present in 15-25% of the population (Serjeantson et al. 1992). Variants of type A can be found in 10-35% of Austronesians from New Guinea and the frequency of type B is less than 10% (Serjeantson et al. 1992). The percentage of type B drops to 1-2% in Island

Melanesia and is absent in Australia and Polynesia (Kirk 1989).

MN distributions show a clinal pattern in the western Pacific, with M decreasing in frequency from north to south (Kirk 1989). Frequencies are low in the highlands of

New Guinea (less than 10%) and in Island Melanesia. In Austronesian language speakers from New Guinea and Island Melanesia, the frequency of M is higher at 15-35%

(Serjeantson et al. 1992), while it reaches 60% in parts of Polynesia and in aboriginal

Taiwanese populations (Kirk 1989).

Overall, ABO and MN blood group distributions divide the populations in New

Guinea and Island Melanesia into four main groups (Booth and Simmons 1972;

Serjeantson et al. 1992).

I. Austronesian speakers from Island Melanesia and the south coast of New Guinea

II. Papuan speakers from New Britain, the Markham Valley and the south coast of New Guinea

III. Madang and Sepik provinces

IV. New Guinea Highlanders

The separation based on blood group data reflects both linguistic and geographic differences. Austronesians are separated from Papuans in both New Guinea and Island

Melanesia. In addition to the linguistic separation, speakers of Papuan languages are further separated by geographic proximity in some cases and (one group that includes both the Markham Valley and New Britain) by multiple colonization events in others

(Serjeantson et al. 1992).

HLA

Human leukocyte antigens (HLA) are cell surface glycoproteins essential in immune function. The HLA system is useful in population studies because it is highly polymorphic with more than 30 alleles at HLA-A locus and 50 alleles at HLA-B locus

(Schanfield 1980; Serjeantson 1989; Main et al. 2001). A portion of these alleles are confined to certain parts of the world. HLA data paint a complex picture of Pacific settlement. According to frequency distributions of HLA loci, Aboriginal Australians and New Guinea highlanders share a common, but ancient, ancestry. However, both are separated from coastal New Guinea populations, that in some cases, show affinity with

Island Melanesians (Kirk 1989). On the other hand, Melanesians share some old HLA types with New Guinea highlanders and Aboriginal Australians, although some HLA types have clearly been overlaid with Austronesian types that increase in frequency moving east toward Polynesia (Kirk 1989; Main et al. 2005).

The distribution of HLA class II DR antigens shows markedly different

distributions in New Guinea highland and coastal populations. As with HLA class I loci,

class II loci group Eastern Highlanders with Aboriginal Australians based on the presence

of DRB1*1401 and DRB3*0201, which are found in both regions but are absent in

coastal populations (Main et al. 2005). DR5 is the most frequent allele in coastal

Melanesians, but is rare in the highlands of New Guinea. DR5 is also the most common

variant found in Polynesians (Serjeantson et al. 1992). Melanesians and Polynesians also

share some HLA variants while others are restricted to either Melanesia or Polynesia.

The pattern of HLA variation in the Pacific suggests multiple waves of migration

into the region. There is evidence of common ancestry between New Guinea and

Australia, particularly in the highlands. There is also a marked difference between

coastal and New Guinea highland populations that is believed to be the result of multiple

migrations, long settlement history and geographic isolation there. In addition, there is

evidence that the pattern of variation seen along the coast has been influenced by

population movement from Southeast and mainland Asia (Main et al. 2005).

Hemoglobinopathies

Genetic variants of hemoglobin have been surveyed in many parts of the world including the Pacific. Since some hemoglobin gene mutations are protective against malaria, which is prevalent in coastal regions from New Guinea to Vanuatu, they are found in higher frequencies than most other region-specific markers (Hill et al. 1989). In the southwest Pacific, various types of thalassemia have been identified in multiple populations, with these being caused by defects in either the α or β globin genes.

Thalassemias from both groups have been found in the Pacific, but α thalassemias are

much more prevalent. Common deletions are the result of independent mutations of

either a 4.2 or 3.7 kilobase region. Both the 4.2 and 3.7 kb deletions are found in varying

frequencies from New Guinea to eastern Polynesia (O'Shaughnessy et al. 1990).

The first alpha-globin gene deletion found in the Pacific, Hb J Tongariki , is a variant

of -α 3.7 which occurs in central Vanuatu, Ontong Java, the Solomon Islands and along

the north coast of New Guinea (Hill et al. 1989). The -α 3.7 deletion can be further

subdivided by the position of the deletion into three different haplotypes to demarcate

different mutational events (Higgs et al. 1984). In both Near and Remote Oceania, the

two major deletions are -α 3.7 type III and -α 4.2 type IIIa, neither has been found west of the Wallace line . The -α 4.2 deletion is most common in Papuan speakers in Near

Oceania while -α3.7 III is found in the Bismarck Archipelago and -α 3.7 I is found on

mainland New Guinea (Yenchitsomanus et al. 1986). An -α 4.2 deletion has been found in

moderate frequency on the western fringe of Remote Oceania, while the -α 3.7 III is found at a considerably higher frequency as far as eastern Polynesia (Hill and Serjeantson

1989).

RFLP haplotypes from individuals lacking α-globin gene deletions can also be

informative. The distribution of normal ( αα ) globin genes shows that type Ia , which is

common in Polynesians, also appears in Europe and Asia, but is rare in Near Oceania

(Hill et al. 1989). Types IIIa and IVa are common in Oceania, but occur infrequently in

other parts of the world.

The distribution of α globin gene variants in the Pacific, like other genetic

systems, reveals clear distinctions between coastal and highland populations. However,

this is probably due in part to the selective force exerted by malaria. Globin gene

variants that do not offer any protection against malaria do not show any significant

difference between the regions. Evidence from globin genes supports a population

intrusion from Southeast Asia into Polynesia through the distribution of normal α globin genes. However, the presence of Melanesian α thalassemias is evidence of Melanesian influence in Polynesia.

Immunoglobulins

Immunoglobulins are serum proteins that are integral in the immune response to the presence of foreign antigens, and have proven to be useful markers of population history (Giles et al. 1965; Friedlaender and Steinberg 1970; Curtain et al. 1971; Propert

1989; Roberts-Thomson et al. 1996; Schanfield et al. 2007). There are several immunoglobulin classes (IgG, IgM, IgD etc.) and subclasses (IgG1, IgG2, IgA1) and all are polymorphic. The Gm polymorphism is the most informative locus, and it was the first genetic marker system investigated in the western Pacific.

GM *A B occurs in New Guinea and the northern coast of Australia. Its highest frequencies are among West Papuan Highlanders, and it appears less frequently in Island

Melanesia. With its presence in Australia and the highlands of New Guinea, this allotype appears to have been brought to the Pacific by the original inhabitants of Sahul

(Schanfield et al. 2007). GM*A,F B occurs at its highest frequency in Thailand, in Han

Chinese and aboriginal populations in Taiwan. Given its high frequencies in Southeast

Asia, it is clear that this variant developed there. It also appears in both Papuans and

Austronesians in Near Oceania, but its frequency is higher (reaching almost 50%) in

Austronesian populations. Based on its distribution, it is possible to trace the migration

route of Austronesians across the north coast of New Guinea into Madang and Morobe

provinces before reaching Island Melanesia (Schanfield et al. 2007). GM*A, X G,

another informative GM allotype, has been found in Aboriginal Australians and Papuans from New Guinea and Island Melanesia. The frequency is highest in the Eastern

Highlands, where it reaches frequencies as high as 18%. In East New Britain, the frequency is high among non-Austronesians and Austronesians.

GM allotypes reveal differences between Austronesians and Papuans, suggesting the independent origin of the two populations (Giles et al. 1965; Schanfield et al. 2007).

This difference is seen in the distribution of GM*A,F B haplotypes in New Guinea. In

Island Melanesia, however, there is clear evidence of differences or significant levels of

interaction between Austronesian and non-Austronesian populations in that region. In

addition, the presence of GM*A,F B in Austronesians is evidence of a link between

Southeast Asian populations and Austronesians in Near and Remote Oceania (Schanfield

et al. 2007). The presence of GM*A B in Australians and non-Austronesians and

Austronesians in New Guinea can be used as evidence of contact and gene flow between

these populations.

Summary of Early Genetic Studies

Results from these early genetic studies show that, across the groups, there is

some correlation between language and genetic relationships in Near Oceania.

Austronesian populations in New Guinea and Island Melanesia are similar to Southeast

Asians in blood group systems, HLA variants, normal ( αα ) globin and immunoglobulin

allotypes. In all of the studies reviewed, populations from the eastern highlands of New

Guinea cluster together, while Madang populations cluster with Island Melanesians.

There is also evidence that, of the populations studied, New Guinea eastern highlands

populations share some genetic affinities with Aboriginal Australians. Within Near

Oceania, globin gene variants are difficult to use as markers of population history in New

Guinea because malarial pressures in lowland and coastal areas have driven the high

frequency of α thalassemias in that region. However, the distribution does give clues to the level of isolation between coastal and highland regions in that α thalassemias found in

coastal populations at somewhat high frequencies are completely absent from the

highlands.

Analyses of classical genetic markers in Remote Oceania show some genetic

affinities between populations in this region and those from Southeast Asia. Blood

group, immunoglobulin and HLA types in this region are a combination of those found in

Southeast Asia and Melanesia. It is evidence of contributions from at least two regions.

The distribution of thalassemias in this region does not include any data from Southeast

Asia, but there are several Southeast Asian variants of normal ( αα ) globin present. The thalassemias in Polynesian are the same as those thought to have developed in Melanesia.

Overall, the pattern of genetic variation in the Pacific paints a picture of multiple migrations into the region at or around the time of initial settlement. Subsequent migrations to the region, from Southeast Asia, introduced new genetic variants to coastal and lowland areas. These new variants did not widely penetrate the isolated highlands of

New Guinea, and they did not spread to Australia. These new variants, plus others that

appear to have developed in Melanesia, are found in Remote Oceania all of the way to eastern Polynesia.

Mitochondrial DNA

More recent research has focused on the use of unilineal genetic systems.

Mitochondrial DNA is widely used to study human evolution, migration and population histories (Cann et al. 1987; Melton et al. 1998; Redd and Stoneking 1999; Schurr and

Wallace 2002; Ingman and Gyllensten 2003; Friedlaender et al. 2007b; Hill et al. 2007).

The 16,569 base pair mtDNA genome has become a useful marker of population history because of its high copy number, maternal inheritance, lack of recombination and high mutation rate. In addition, the sequence of the entire mtDNA molecule is known

(Anderson et al. 1981; Andrews et al. 1999).

The mtDNA molecule is transmitted from mother to offspring with new lineages arising only through the accumulation of mutations (mainly substitutions and deletions).

Since mtDNA does not experience the shuffling of recombination, it is a useful tool for relating individuals to one another (Cann et al. 1987). MtDNA also has a high rate of local differentiation due to random genetic drift (Stoneking et al. 1990). A majority of the sequence encodes genes involved in energy production and protein synthesis. The

Control Region (D-loop), an ~1100 bp section of the genome dedicated to replication, encompasses hypervariable regions I and II (HVR I and HVR II), and contains a number of sites that accumulate mutations at a rapid rate (see Figure 3.1).

The mutation rate of mtDNA is nonuniform and several orders of magnitude higher than nuclear DNA (Hasegawa et al. 1993; Heyer et al. 2001; Howell et al. 2003).

The rate in the coding region is estimated at 0.017 x 10 -6 substitutions per site per year

(Ingman et al. 2000; Pakendorf and Stoneking 2005). The mutation rate is even higher in the control region, but the exact rate has been the subject of much debate. Based on phylogenetic comparisons, the rate has been estimated at 0.075-0.165 x 10 -6 substitutions per site per year (Stoneking et al. 1992; Tamura and Nei 1993). Observations of mtDNA mutations in families or pedigrees yields an estimate of 0.47 x 10-6 substitutions per site per year, higher than the phylogenetic estimates (Howell et al. 2003; Pakendorf and

Stoneking 2005).

There are several possibilities why these rates are so different. The phylogenetic method detects mutations that have reached an appreciable frequency in the population, while the family tree method detects mutations that have occurred quite recently and may never go to fixation (Pakendorf and Stoneking 2005). Such differences could also be due to the presence of “mutational hot spots” where mutations occur faster than average control region sites (Meyer et al. 1999; Heyer et al. 2001). The rate most often used in population studies based on a 275 base pair section of the HVR is one transition per

20,180 years (Richards et al. 2000).

Diversity in mtDNA was first studied in the 1980’s using RFLP analysis (Brown

1980; Denaro et al. 1981; Blanc et al. 1983; Horai et al. 1984). Restriction enzymes cut

DNA in sections where recognition sites are present. A mutation in the sequence can prevent the cutting of the DNA, or can create new restriction sites. High resolution RFLP typing, using 18 different restriction enzymes, can screen 20% of the mitochondrial genome (Torroni et al. 1992; 1993; Huoponen et al. 2001). With the introduction of

PCR, the sequencing of HVS I became the preferred method of analyzing diversity.

Because of its hypervariability, sequencing HVS I alone can often provide enough information for phylogenetic lineage assignment. Torroni et al (1996), Richards et al

(2000) and Macaulay et al (1999) show that the results of sequencing and RFLP analysis are congruent in terms of detecting variation and inferring phylogenetic relationships.

More recent studies involve the sequencing of the entire mtDNA genome (Ingman et al.

2000; Finnila et al. 2001; Herrnstadt et al. 2002; Ingman and Gyllensten 2003; Hudjashov et al. 2007). Phylogenetic trees based on whole genome sequences provide the best resolution, but whole genome sequences do not always reveal information not gained by

RFLP and or HVS I sequencing alone (Ingman et al. 2000).

16024 16365 73 340 576 1 tRNA HVS I HVS II tRNA

Figure 3.1 Human mtDNA genome. Nucleotide sites for common Southwest Pacific haplogroups and control region segments HVS I and HVS II are displayed. After (Friedlaender et al. 2007a).

Evidence for the Settlement of New Guinea and Island Melanesia

Historically, mtDNA research in the region has focused on several major issues, including (1) the simultaneous colonization of Australia and New Guinea, (2) the origin of the Polynesians, and (3) the genetic relationship between Papuans and Austronesians.

Since New Guinea and Australia were physically joined until 8,000 BP, it is possible that the first people in this region settled Australia and New Guinea simultaneously. Several mtDNA studies have attempted to determine whether a single migration or multiple migrations colonized the region. Although, many studies in the Southwest Pacific involved limited sampling, some trends are visible. All of the mtDNAs in the region can be linked to founder lineages M or N that appeared outside Africa for the first time some

50-70,000 years ago (van Holst Pellekaan et al. 2006; Friedlaender et al. 2007a;

Hudjashov et al. 2007).

The first studies conducted on variation in HVS I and HVS II supported a separate origin for New Guinea and Australian populations (Stoneking et al. 1990; Redd and

Stoneking 1999). More recent studies support a common, albeit ancient, connection between aboriginal populations from Australia and New Guinea highlanders (van Holst

Pellekaan et al. 1998; Huoponen et al. 2001; Ingman and Gyllensten 2003). Ingman and

Gyllensten (2003) found that New Guineans and Aboriginal Australians share two minor mtDNA clades, 1c and 1d (P2 and P3 with new nomenclature) (Friedlaender et al.

2005b). Both clades were very old indicating that any relationship between the two regions would have been ancient, with a possible spilt dated between 31,000 BP to

46,000 BP (Ingman and Gyllensten 2003).

Comparisons of populations in New Guinea show that there are differences in the distribution of mtDNA haplotypes when comparing coastal and highland populations, and when comparing eastern highlands populations to southern highlands populations

(Stoneking et al. 1990; Redd and Stoneking 1999). In addition, Friedlaender (2007a) described a series of mtDNA haplotypes that developed in the region of Sahul about the time of its initial settlement. Many of them appear to have developed in regions closely associated with particular language groups and particular island regions.

Haplogroup P is the oldest mtDNA lineage in the region. Coalescence dates for its branches are ~40,000 years, in accordance with archaeological settlement dates for

New Guinea and northern Island Melanesia (Green 2003; Summerhayes 2004; Leavesley

2006; Summerhayes 2007). This lineage appears to have developed in Near Oceania, as it has only been found in a few samples west of the Wallace Line (Friedlaender et al.

2007a). P is most common in the highlands of New Guinea, and decreases in frequency from New Britain, New Ireland, Bougainville and further southeast (Friedlaender et al.

2005b; Friedlaender et al. 2007a). In addition, there are several sub-haplogroups of P, P1 is reportedly the most common and widespread but P2, P3 and P4 are also found either in

New Guinea or other regions of the Southwest Pacific (Huoponen et al. 2001; Ingman and Gyllensten 2003; Friedlaender et al. 2005b).

Haplogroup Q, part of macrohaplogroup M, is found in high frequencies in some

Pacific populations. Three branches of Q-Q1, Q2 and Q- have been identified (Redd and

Stoneking 1999; Tommaseo-Ponzetta et al. 2002; Ingman and Gyllensten 2003;

Friedlaender et al. 2005b). Of the three variants, Q1 is the most common variant found in

New Guinea, New Britain and north Bougainville (Friedlaender et al. 2005b). Q2 is

found rarely in New Guinea, but is more common in parts of New Britain, particularly

where Papuan languages are spoken (Friedlaender et al. 2007b). Q3 is also rare and has

been found in only a few individuals from New Guinea and New Britain (Friedlaender et al. 2007a). Haplogroup Q has also been found in Polynesia, and the presence of this lineage is evidence for at least a partial Melanesian origin for Polynesian populations

(Sykes et al. 1995).

Friedlaender et al (2007b) also identified a set of haplogroups that are found at various frequencies in Near Oceania at the exclusion of New Guinea. All of these haplogroups belong to macrohaplogroup M, and appear to have developed in Northern

Island Melanesia, as they are most common and diverse in this region (Friedlaender et al.

2007b). M28, the most common of these haplogroups, is found in high frequencies in

New Britain, Santa Cruz and Vanuatu (Cox 2003; Kayser et al. 2006; Ohashi et al. 2006;

Friedlaender et al. 2007a). It is also found in appreciable frequencies in New Caledonia and Fiji, but is rare or absent in New Ireland, Bougainville, the central Solomons and

Polynesia (Kayser et al. 2006; Ohashi et al. 2006; Friedlaender et al. 2007b). M27 is most commonly found in Bougainville (Friedlaender et al. 2007b), while sub-lineage

M27b is most common in New Britain and M27c has a scattered distribution. The final

M haplogroup thought to have developed in Northern Island Melanesia, M29, reaches its highest frequencies in East New Britain (Friedlaender et al. 2007b).

Holocene Sequences and the Settlement of Remote Oceania

New branches of haplogroups appear in the Southwest Pacific during the

Holocene. The most common, haplogroup B, is marked by a 9bp deletion between the

cytochrome oxidase (COII) and transfer RNA for lysine (tRNA lys) region which is a useful marker for Asian populations (Horai and Matsunaga 1986; Wrischnik et al. 1987;

Ballinger et al. 1992; Harihara et al. 1992; Lum et al. 1994; Redd et al. 1995). The mutation has also been found in Asian populations (Horai and Matsunaga 1986;

Stoneking and Wilson 1989; Ballinger et al. 1992; Harihara et al. 1992) and in Native

Americans (Schurr et al. 1990; Ward et al. 1991; Shields et al. 1992; Shields et al. 1993;

Ward et al. 1993). There is evidence that the mutation arose independently several times in Asia and at least once in Africa (Vigilant et al. 1991). The form of the mutation, haplogroup B4a1a1,commonly found throughout Near and Remote Oceania is further defined by four mutations at 16189, 16217, 16247 and 16261 within HVSI (Melton et al.

1995; Redd et al. 1995; Lum and Cann 1998; Merriwether et al. 1999). Aside from

Madagascar, this combination of mutations is virtually absent from all populations west of Indonesia. Since this haplotype is found at such high frequency in Polynesia, it has been dubbed the “Polynesian Motif”(Redd et al. 1995).

There are two models for the origin of proto-Polynesians and the Polynesian

Motif. In the first model, haplotypes of haplogroup B are thought to have spread from island Southeast Asia with Lapita 3,500 YBP when sea level increases encouraged eastward migration (Oppenheimer and Richards 2001a; Cox 2005). In the second model, populations from southern China with a farming economy migrated from the region into

Taiwan by 6,000 years ago and spread to the Philippines, eastern Indonesia and New

Guinea by 3,500 YBP (Cox 2005). The frequency of haplogroup B in island Southeast

Asia is 21%, offering some support to the idea of a Southeast Asian origin for the lineage

(Melton et al. 1995; Redd et al. 1995; Sykes et al. 1995).

There has been some opposition to the idea of a Southeast Asian origin for the

“Polynesian Motif” although some evidence for the presence of intermediate forms of the

B4a1a1 haplotype appears in aboriginal populations of Taiwan (Richards et al. 1998;

Oppenheimer and Richards 2001a; Friedlaender et al. 2007a). These “pre-Polynesian

Motif” haplotypes are highest in frequency from Taiwan south through the Philippines and east Indonesia, with the greatest diversity appearing in Taiwan (Merriwether et al.

1999).

Haplogroup B is now found in coastal New Guinea and throughout Island

Melanesia in up to 42% of coastal Melanesians (Hertzberg et al. 1989; Stoneking and

Wilson 1989; Lie et al. 2006; Kayser et al. 2008a). However, “Polynesian Motif” haplotypes have not been found in the New Guinea highlands, or in some Papuan speaking areas of Island Melanesia, particularly north Bougainville and New Britain

(Merriwether et al. 1999; Friedlaender et al. 2007a).

In Island Melanesia, there is a west to east increase in the frequency of haplogroup B. In Island Melanesia, haplogroup B is found in all Oceanic Austronesian language speakers and many non Austronesians. Significant correlations between linguistic distances and genetic distances suggests possible coevolution of genetic and linguistic patterns (Lum and Cann 1998). Exceptions to the language/mtDNA connection can be seen in east Bougainville, where the frequency of haplogroup B is high in both language groups, and in Vanuatu where its frequency among Austronesians is relatively low (Lum and Cann 1998; Merriwether et al. 1999).

Several other Southeast Asian haplogroups have been found in the Southwest

Pacific. Haplogroup E has been identified in the Ata and Sulka from New Britain and in

some Oceanic speaking populations in Island Melanesia (Ballinger et al. 1992;

Friedlaender et al. 2007b; Kayser et al. 2008a; Ricaut et al. 2008). Haplogroup E probably originated in Southeast Asia, as it has also been found in mainland and Island

Southeast Asia and appears in multiple sub-lineages in both regions (Hill et al. 2007).

The distribution of several other Southeast Asian haplogroups (M7, F, Y) in the

Southwest Pacific is too spotty to shed any light on settlement and population relationships (Friedlaender et al. 2007b; Kayser et al. 2008a; Ricaut et al. 2008).

Mitochondrial DNA analysis in the Southwest Pacific shows that there is a great deal of variation present. Although sample sizes are often small in regional studies, some trends are still visible. Australian Aborigines and New Guinea highlanders show genetic affinities when compared to other worldwide populations. There is a significant difference between coastal and highland New Guinea populations that is due to both isolation of the highlands and the overlay of old mtDNA haplogroups with newer

Southeast Asian types arriving 3,500 YBP along the coast (Redd et al. 1995; Redd and

Stoneking 1999). The pattern of variation seen in Island Melanesia is also added evidence of multiple migrations into the region. Coastal populations on many of the islands show evidence of a Southeast Asian contribution to the Island Melanesian gene pool, while inland populations have high frequencies of older mtDNA haplogroups similar to those present in New Guinea. In many cases, Papuan speaking groups retain older Melanesian haplogroups while Oceanic speakers share haplogroups with Island

Southeast Asian populations. However, this pattern does not fit all populations.

Almost all mtDNA sequences in Remote Oceania can be assigned to one of several well defined lineages. In Remote Oceania, the diversity in mtDNA lineages

decreases markedly until a single haplogroup, B, becomes almost fixed on some islands.

Haplogroup Q has also been found throughout Remote Oceania, proving that there has been a Melanesian contribution to the populations of Remote Oceania (Sykes et al. 1995;

Cox 2003).

MtDNA only represents a single line of evidence for understanding the population history of the Pacific. For this reason, it is useful to also include Y chromosome data to provide a more complete picture of human population history here.

Evidence from the Y Chromosome

The haploid and completely paternally inherited Y chromosome is used as a male complement to maternally inherited mtDNA. Less than 10% of the 60 million base pair

Y chromosome recombines (nonrecombining Y or NRY) while the pseudoautosomal region undergoes recombination with the X chromosome (Hurles and Jobling 2001;

Attenborough 2005). As a result, these polymorphisms in the NRY make it easy to trace paternal lineages. SNPs in the NRY have a high degree of region specificity, making them very informative when tracing population relationships (Seielstad et al. 1998; YCC

2002). Furthermore, the Y chromosome is prone to genetic drift due to its small effective population size and male social behavior. This, in turn may produce genetic drift effects that generate geographic clustering where large differences are seen between populations

(Cavalli-Sforza, 1998).

Near Oceanic Y Chromosome Lineages

Like mtDNA, research done on the NRY focuses on two major issues, the initial settlement of Sahul and the Holocene expansion of Austronesian speaking peoples. NRY lineages in Near Oceania do not support a common origin for Melanesians and

Australians (Kayser et al. 2000; 2001; 2003). The oldest lineage in the region, C-RPS4Y, can be dated to 50,000 YBP, and was probably introduced by the initial settlers of the

Sunda shelf and Sahul (Underhill 2004). The frequency of this lineage is low in

Southeast Asia, Taiwan, Indonesia, Australia and coastal New Guinea, and is absent in

Island Melanesia and Remote Oceania (Hage and Marck 2003; Scheinfeldt et al. 2006).

Other branches of haplogroup C are found in greater frequency throughout the Southwest

Pacific. For example, C2-M38* can be found as far west as Borneo, but reaches its highest frequencies in eastern Indonesia and coastal New Guinea. C2b-M208 appears at high frequencies in the highlands of West Papua, in the Cook Islands, the Admiralties and in the Sepik region of New Guinea, and is used as evidence for a possible Melanesian contribution to the origin of the Polynesians (Kayser et al. 2003; Scheinfeldt et al. 2006;

Kayser et al. 2008a).

Haplogroup K is the most common in the region, and occurs at considerable frequencies in many populations. It is defined by the presence of the M9 SNP and the absence of any other haplogroup defining polymorphisms. A subdivision of K-M9, K-

M230, reaches a frequency of 52% in the highlands of New Guinea, has lower frequencies in Island Melanesia, the Admiralties and is absent from Polynesia (Kayser et al. 2003; Karafet et al. 2005; Scheinfeldt et al. 2006; Kayser et al. 2008a). A second sub-

lineage, K6-P79, is common in parts of New Britain and central New Ireland (Scheinfeldt

et al. 2006).

The Near Oceanic haplogroup M is rarely found west of the Wallace Line. M-

M4* and M2-P87* are found in Papuans from New Guinea to New Ireland and New

Britain (Scheinfeldt et al. 2006). M2a-P22, another branch of M found predominantly in

Papuans, reaches a frequency of 80% in Bougainville, 70% in New Hanover and 30% in

parts of New Britain and New Ireland (Scheinfeldt et al. 2006).

There is a great deal of NRY diversity in Near Oceania, and the most ancient

lineages in the region appear to date from the time of initial settlement. The oldest

lineage dates to 50,000 YBP, which is in agreement with mtDNA ages for the settlement

of Sahul. NRY haplogroups are more regionally specific than those from other genetic systems, thus, to truly get a clear picture of Near Oceanic settlement based on NRY, more regions will have to be sampled.

Remote Oceanic Y Chromosome Lineages

Analysis of Y chromosome diversity in Remote Oceania supports a dual origin of

Polynesian peoples in agreement with the Slow Boat hypothesis (Kayser et al. 2000;

2006). Most NRY lineages in Remote Oceania support a Melanesian origin for

Polynesians (Kayser et al. 2000; Capelli C et al. 2001; Underhill et al. 2001; Hurles et al.

2002). NRY haplogroups found in Polynesia that are believed to have a Melanesian origin include C-M38, C-M208, M-M4, M-P34, K-M254, M-M104 and K-M9

(Polynesian K-M9 clusters with Melanesian K-M9, and does not share features with

Asian or Australian K-M9). These Melanesian haplogroups account for 65.8% of NRY

variation in Polynesia. Of these haplogroups, C-M208 accounts for 34.5% of the variation and K-M9 accounts for 17.9% (Kayser et al. 2006).

The remaining NRY haplogroups, O-M175, O-M122, O-M134, O-M95, O-M119,

C-RPS4Y and NO-M214, are of East Asian origin (Kayser et al. 2000; Su et al. 2000;

Kayser et al. 2003; Kayser et al. 2006). Haplogroup O-M122 makes up 24.3% of the

28.3% of Asian lineages found in Polynesia (Kayser et al. 2006). Lineage O is found throughout East Asia and is common in several Polynesian populations including the

Cook Islanders, Western Samoans and the Maori (Capelli et al. 2001; Underhill et al.

2001; Hage and Marck 2003; Kayser et al. 2006). Variants of haplogroup O are also found in low frequencies among Oceanic speaking Melanesians. Two sub-lineages, O-

M353 and O-M122 DYS385 are restricted to Polynesia, an indication that Polynesia is where these haplogroups developed (Kayser et al. 2006).

According to research using both uniparentally inherited genetic systems, 65.8% of Polynesian NRY lineages are Melanesian compared to 6% of Polynesian mtDNA lineages, while 28% of Polynesian NRY lineages are East Asian compared to 93% East

Asian mtDNA lineages. Evidence from the Y chromosome supports a dual origin for the

Polynesians. The amount of Melanesian influence on the Polynesian gene pool is very different for the NRY and the mtDNA. Hage and Marck (2003) and Kayser et al. (2003;

2006) attribute these differences to admixture bias for Melanesian men due to matrilocal residence patterns on Polynesian islands, but this view is subject to debate. In addition, there is a west to east reduction in NRY and mtDNA diversity in the Southwest Pacific that is currently attributed to founder effects, although this interpretation is also questioned (Hurles et al. 2002; Kayser et al. 2006).

Summary of Genetic Data

A majority of the recent studies reviewed here gives evidence in support of multiple migrations into the Southwest Pacific. The first occurred 40-50,000 YBP and

colonized the landmass Sahul, leaving traces of a common ancestry for Australian

Aborigines and New Guinea highlanders. The second migration occurred 3,500 YBP,

and left traces of a Southeast Asian influence on coastal and lowland regions of Island

Melanesia. The mtDNA lineages from this second migration were the first to colonize the

Remote Pacific.

Concordance of Genetic Data

In terms of variation within Melanesia, HLA, α globin gene variants,

immunoglobulin allotypes and mtDNA haplotypes all separate highland New Guinea and

other Papuan-speaking populations from coastal and lowland, often Oceanic, populations

across the rest of Melanesia, with some exceptions (Serjeantson 1989; Serjeantson et al.

1992; van Holst Pellekaan et al. 1998; Mack et al. 2000; Main et al. 2001; Ingman and

Gyllensten 2003). In Remote Oceania, the presence of Southeast Asian α type Ia in Fiji,

Vanuatu, Tonga and Samoa supports a Southeast Asian origin for Oceanic populations

(Roberts-Thomson et al. 1996). The case for the dual origin of Oceanic populations is

strongest based on the mtDNA data.

Discordance of Genetic Data

Although there is a great deal of consistence in the patterns shown by different

genetic markers, some disagreement still exists. ABO blood group variants commonly

found in Oceanic-speaking populations from Island Melanesia are not seen in

Polynesians (Ohashi et al. 2004). Also, common Southeast Asian α thalassemias are not found in populations from the Southwest Pacific (Main et al. 2001). The most noticeable contradiction in the genetic data is between mtDNA and the Y chromosome. Southeast

Asian male lineages are found in surprisingly low frequency in Island Melanesia, in direct disagreement with the high frequency of the mtDNA haplogroup B (Polynesian

Motif) in the same region. NRY data reveal some differences between coastal and highland New Guinea populations, but the differences are not as significant as with the other genetic systems (Kayser et al. 2001).

Conclusions

Previous genetic studies of New Guinea show a great deal of geographic isolation and more diversity than other regions of the world (Stoneking et al. 1990; Kayser et al.

2001; Merriwether and Friedlaender 2004; Main et al. 2005; Friedlaender et al. 2007b).

There is a great deal of agreement but some disagreement about the exact patterning of variation and the level of contribution from different regions. However, overall genetic diversity in the genetic systems decreases as one moves west to east from New Guinea to

Polynesia. Possible explanations for this pattern will be explored in Chapters 5 and 6.

CHAPTER 4 Methods of Genetic and Statistical Analysis of Mitochondrial DNA Research in the Southwest Pacific

Samples

Four hundred samples from three islands in the Southwest Pacific were chosen for mitochondrial DNA analysis. Two hundred fifty urine samples from mainland New

Guinea were selected. Information collected from volunteers included sex, age, village/district and province of residence. Samples were chosen from five Eastern

Highlands villages or districts. The Eastern Highlands province was chosen because past research on populations in this region revealed a great deal of genetic diversity

(Stoneking et al. 1990; Roberts-Thomson et al. 1996; Redd and Stoneking 1999). The highlands are comparatively isolated when compared to coastal/lowland populations and are suspected to be less prone to recent admixture. Thus they are more likely to retain lineages from the earliest settlement of Sahul, making them perfect to test the effect of time depth and the effect of isolation.

Samples were also chosen from Madang province along the north coast of New

Guinea. Mainland New Guinea and Karkar Island, off the north coast, were both represented in this sampling. This region shows traces of the Holocene expansion of

Austronesians into Near Oceania with the presence of both Austronesian and Papuan languages there. With both Austronesian and NAN populations living in close proximity, the effect of linguistic difference on genetic variation can be examined to determine whether differences in genetic patterns observed in speakers of the Oceanic branch of

Austronesian and NAN or Papuans reflect differences in linguistic patterns.

In addition, one hundred plasma samples from Manus Island were collected.

Information collected from Manus volunteers included language, village of residence and

village of birth for mother and father. Little research has been done in this region, where

Papuan languages have completely been replaced by Austronesian languages. All

samples from New Guinea and Manus were collected by Charles S. Mgone of the Papua

New Guinea Institute for Medical Research.

The final set of samples consisted of 50 plasmas from Easter Island residents

(Rapa Nui). Easter Island, in eastern Polynesia, offers a glimpse of the effect of isolation, since it is the easternmost island in Polynesia where Pitcairn Island, 1900km to the west, is the closest inhabited island. Studying this population allowed a view of diversity seen when an insular area is very small and when genetic drift is probable. The Easter Island samples were sent from the laboratory of Dr. Moses Schanfield of the George

Washington University, Washington, DC. Demographic information for these individuals was not available at the time of the study.

This study was approved by the Institutional Review Board of Temple University and the Papua New Guinea Medical Research Advisory Committee.

Laboratory Methods

DNA Extraction

DNA from the collected samples was extracted in the Laboratory of Molecular

Anthropology at Temple University, Philadelphia, Pennsylvania. Urine samples were thawed and transferred to 50 mL polypropylene centrifuge tubes. The urine was

centrifuged at a speed of 2500 rpm for 10 minutes to pellet urine sediments. The supernatant was discarded and the pelleted sediment was washed with 10 mL of 1X phosphate buffered saline (PBS) pH 7.4. The pellets and PBS were vortexed and centrifuged at 2500 rpm for 10 minutes. The PBS supernatant was poured off leaving approximately 200 mL of PBS with the pellet. The tube was vortexed and DNA was extracted from the mixture using the QIAamp DNA Blood Mini Kit (Qiagen, Valencia,

CA) blood and body fluid spin column extraction protocol. The amount of DNA in most samples was too small to quantify with a spectrophotometer, so dilutions were not performed. Extracted DNA was stored at -20˚C.

Plasma samples were thawed and 200 mL of each sample was transferred to a

2mL centrifuge tube. When 200 mL of sample was not available, the appropriate amount of 1X PBS was added to achieve the desired volume. DNA was extracted from the samples following the protocol outlined above.

PCR Amplification

All samples from New Guinea, Manus and Easter Island were screened for presence or absence of the 9 bp deletion defining haplogroup B. Standard PCR amplifications were performed in a reaction volume of 25 l consisting of 2.5 l of a 10X

® buffer, 2.5 l MgCl 2, 2.0 l dNTP mix, 0.2 l Platinum Taq (Invitrogen, Carlsbad, CA),

0.2 l of each primer from set one (Table 4.1), 15.4 l molecular grade water and 2 l of

DNA . The samples were amplified with an initial denaturation temperature of 95˚C for

12 minutes followed by 35 cycles of denaturation at 95˚C for 1 minute, annealing at 58˚C for 1 minute and elongation at 72˚C for 1 minute with a 10 minute final extension at

72˚C. Amplification products were run on a 6% acrylamide gel and stained with 1% ethidium bromide for visualization with a UV light box. Samples lacking the 9 bp deletion were prepared for direct sequencing of the HVS I, while those having the deletion were prepared for the sequencing of HVS I and HVS II.

After the initial screening, all samples were PCR amplified with primers targeting

HVS 1 (Table 4.1 primer set two). The profile used for the previous set of amplifications was also used to amplify HVS I. Two l of amplification products were run on a 6% acrylamide gel stained with 1% ethidium bromide to verify successful amplification for sequencing. Samples that did not amplify successfully were re-amplified using 2 l of the initial amplification product. Samples that were selected for sequencing of HVS II were amplified with primer sets three and four (Table 4.1) following the same protocol.

Table 4. 1 List of Primers for Amplification of HVS I and HVS II

Primer Set Name Sequence

1 8316 5' ATGCTAAGTTAGCTTTACAG 3'

1 8196 5' ACAGTTTCATGCCCATCGTC 3' 2 L15996 5' CTCCACCATTAGCACCCAAAGC 3' 2 H16401 5' TGATTTCACGGAGGATGGTG 3' 3 L16313 5' CCCTTAACAGTACATATAC 3' 3 H161 5’ GTAATATTGAACGTAGGTGCG3’ 4 L27 5’ GGTCTATCACCCTATTAACC 3’ 4 H411 5’ GACTGTTAAAAGTGCATACCG 3’

Sequence Analysis

Samples were prepared for sequencing by PCR purification with the QIAquick

PCR Purification Kit (Qiagen, Valencia CA) microcentrifuge protocol. PCR products were sequenced using BigDye ® Terminator v1.1 Cycle Sequencing Kit (Applied

Biosystems, Foster City, CA). Sequencing reactions contained 4 l BigDye ® reaction mix, 0.6 l of a 10:1 molecular grade water to primer mixture (L15996, H16401, L16313,

H161, L27, H411) and 5.4 l of the purified PCR product. The amplification was done with an initial 1 minute denaturation at 96˚C, followed by 10 seconds for denaturation at

96˚C for, 25 cycles, 50˚C for 5 seconds for annealing and 60˚C for 4 minutes for elongation. The cycle sequence profile for HVS II had an annealing temperature of 55˚C for 5 seconds, while all other temperatures and times remained the same.

After completion of the cycle sequencing reaction, excess dye terminators were removed from samples using the DyeEx 2.0 Spin Kit (Qiagen, Valencia, CA). Samples were then dried at 70˚ C for 30 minutes. The dried samples were resuspended in 10 l

Hi-Di Formamide and loaded into 96 well plates. Sequencing results were collected on a

96 well capillary ABI 3730 DNA Analyzer at the Coriell Institute for Medical Research,

Camden, New Jersey (Applied Biosystems, Foster City, CA).

Completed sequence data were loaded into the program Sequencher v.4.1.4 (Gene

Codes Corporation, Ann Arbor, MI). Chromatogram files were viewed and edited to remove the ends of the sequences. Sequences were aligned with the Cambridge

Reference Sequence to form contigs for editing (Anderson et al. 1981; Andrews et al.

1999). Haplogroup assignments were made based on Table 4.2, and consensus files were exported in text format for further analysis.

Samples tentatively assigned to haplogroups P4 and R14 (Hudjasov 2006) were subsequently amplified for HVS II using primer sets three and four following standard protocols. Haplogroup R14 was further sequenced because it was newly defined at the

time of the study and P4 was further sequenced because it was defined by a single mutation in the HVS I.

Table 4.2 Defining Mutations for mtDNA Haplogroups in the Southwest Pacific

Haplogroup HVS I HVS II

B4a1a1 16189 16217 16261 146 B4a1a1a 16189 16217 16261 16247 146 B5b 16140 16189 16243 103

P1 16176 16266 16357 P2a 16278 16497 P2b 16164 16256 P4 16319 35 36 146 152

Q1 16129 16144 16148 16223 16241 16265C 16343 Q2 16066 16129 16223 16241 63 Q3 16129 16223 16241 16311

E1b 16223 16261 16362 16390 E2 16051 16223 16362 16390

M7b1 16129 16192 16223 16297

M28 16086 16129 16148 16223 16362 16468 b1 16148 16223 16318T 16362 16468

M29 16189 16223 16311

R14 16187 16288 16304G 16363 56 182 207 234

Data Analysis

Phylogenetic Analysis

The program Network 4.2.0.1 (Bandelt and Dress 1992; Bandelt et al. 1995) was used to construct networks to visualize the phylogenetic relationships among haplotypes.

Binary data was imported into Network from formatted Excel files, and default values were used, 10 for character weight and 1 for frequency (Bandelt et al. 2007). The algorithms in the program are designed specifically for non-recombining molecules.

Network 4.2.0.1 uses variable data to construct the shortest, least complex maximum parsimony tree. Using the reduced median option, simple networks can be created, and this option was used to create preliminary networks for all sample sets

(Bandelt et al. 1995). In the median joining building option, more complex networks can be created with little or no reticulation (Bandelt et al. 1999). For very complex networks, the reduction threshold was set to one to create full networks containing all MP trees; this option was used when the MJ option created networks that were not clear or that were difficult to interpret (Polzin and Daneschmand 2003). Bandelt nodes represent haplotypes and median vectors (hypothesized sequences required to connect existing sequences); branch lengths are proportional to the number of polymorphic sites linking the nodes, and node diameter is proportional to number of subjects sharing the same haplotype (Bandelt et al. 2007).

Statistical Analysis

Raw sequence data were exported into the editing program PSPad for statistical formatting. Arlequin ver 3.1 was used to calculate diversity measures, AMOVA and

Mantel partial correlations (Excoffier et al. 2005). Diversity measures were calculated to

measure the level of variation within the populations. Three measures of diversity were

used, Nei’s gene diversity, mean number of pairwise difference and average nucleotide

diversity over loci. Nei’s gene diversity measures the probability that two randomly

chosen haplotypes will be different (Nei 1987). Mean number of pairwise differences

measures the extent of sequence similarity between all pairs of haplotypes in the sample

(Tajima 1983; Tajima 1993). Nucleotide diversity over all loci measures the probability

that two randomly chosen nucleotide sites will be different (Tajima 1983; Nei 1987).

To compare relationships within populations linguistically, genetically and

geographically, Mantel partial correlation tests were performed. Mantel tests examine

the correlation or partial correlations between matrices by permutation (Mantel 1967;

Smouse et al. 1986). The genetic matrix was constructed using Fst values calculated in

Arlequin. Fst compares the relative distance from the centroid within and between

populations. The language matrix was constructed using numerical values for linguistic differences. Since exact languages were not recorded for the populations, language family affiliation was used to construct the matrix. Papuan speaking populations belonging to the main section of TNG were given a distance of 1 to each other and a distance of 4 to languages belonging to the Madang-Albert Range branch of TNG. All of the Austronesian languages spoken by study participants belong to three different branches of Oceanic, and were given a distance of 3 to each other (Pawley and Ross

1993). In addition, Oceanic languages were given a distance of 6 to NAN languages.

Two geographic matrices were constructed. The first used approximate longitude and latitude coordinates for each population to measure the distance between them, and the

second used island size in Km 2 to measure differences in land mass and their effect on genetic diversity..

Standard AMOVA (Analysis of Molecular Variance) was used to quantify the distribution of variation within and between populations by estimating differentiation directly from the molecular data (Excoffier et al. 1992). AMOVA was run with several non-genetic partitions of the data. The first structure did not partition the data, the second partitioned the data for geography (3 islands: New Guinea, Manus and Easter Island), and the third partitioned the data for language family affiliation (2 families: Papuan/NAN and

Austronesian/Oceanic).

CHAPTER 5 Results of Mitochondrial DNA Analysis in the Southwest Pacific

Introduction

MtDNA studies in the Southwest Pacific have revealed the presence of a diverse set of mtDNA lineages. Representatives of two macrohaplogroup lineages, M and N, are

found throughout the region (Redd and Stoneking 1999; Forster et al. 2001; Friedlaender

et al. 2005b; Merriwether et al. 2005). There is evidence that these macrohaplogroups

branched from the African L3 root approximately 60,000 years ago and appeared in the

Southwest Pacific approximately 40,000 years ago (Forster et al. 2001; Kivisild et al.

2002).

Haplogroups belonging to M include E, M7, M27, M28, M29 and Q, and

haplogroups belonging to lineage N include B, F and P (see Figure 5.1). MtDNA

haplogroups found in the Pacific can be separated based on their age and geographic

distribution. Of the haplogroups found in this region, few are found west of the Wallace

Line, which is a clear indicator of the level of isolation experienced by the populations

that entered this region. Haplogroups that are found in Southeast Asia and in both Near

and Remote Oceania, such as B4a1a, E, M7 and a few others, reflect a more recent

expansion into the region during the Holocene (Friedlaender et al. 2007a; Hill et al. 2007;

Kayser et al. 2008a; Ricaut et al. 2008).

Using the methods described in Chapter 4, an analysis of the mtDNA distribution

in New Guinea, Manus Island and Easter Island was conducted. This analysis observed

representatives from many of the previously mentioned haplogroups as well as a few

more that were not well represented in the literature. 67

M7 C Z Q M27 M29 M28 E M9a D G A I W X Y N9a B F P H V J T U K

R 68

M N

Figure 5.1. mtDNA schematic tree for Eurasian haplogroups

Haplogroup Distributions

Mitochondrial DNA Distribution in New Guinea

Two hundred and fifty samples from New Guinea were analyzed. The samples were separated into several groups, the Eastern Highlands Province (EHP) group was the largest, with 209 samples. The samples from EHP were further divided into several villages or districts, including Okapa 32, Watabung 11, Lufa 42, Kainantu 46, and

Kiseveroka 78. The remaining 41 samples came from Madang Province, including

Karkar Island, and have been combined to form one group, referred to here as Madang.

Based on the results of this study, the region is genetically diverse. The mtDNA haplogroups found in this sampling of New Guinea include B, E, M, P, Q and R. Tables

5.1 and 5.2 present frequencies of individual haplogroups by village.

In EHP, a majority of the samples (133 or 64%) from this region belonged to haplogroup P. P1, defined by transitions at 16176, 16266 and 16357, was found in 91 individuals and represents the most common branch of P in this data set (see Table 4.2 for a list of defining mutations). When separated into villages, 39% of the samples from

Kainantu belonged to P1, as did 51% of Kiseveroka samples, 36% of the Lufa samples,

41% of Okapa samples and 46% of Watabung samples. Figure 5.2 shows the village location and frequency of the P sub-haplogroups.

A second branch of P, P2a, defined by mutations at 16278 and 16497 was found in 31 individuals who were spread evenly throughout the villages sampled. A third branch of P, P4, defined by a transition at 16319 in HVS I and transitions at 35, 36, 146

and 152 in HVS II , was found in 10 individuals, with a majority of this haplotype appearing in Kiseveroka.

Table 5.1. mtDNA Lineage Occurrences in the Southwest Pacific

Haplogroups

Village/ Island N P1 P2a P2b P4 Q1 Q2 Q3 R14 B4a1a B4a1a1 B5b E E1b E2 M28 M29 M7b1 Other Lufa 42 15 10 1 15 1 Kiseveroka 78 40 7 6 14 1 8 2 Kainantu 46 18 7 1 18 2 Watabung 11 5 1 1 3 1 Okapa 32 13 6 1 12

71 Madang 41 3 1 5 8 1 2 1 3 2 1 1 1 1 11

New Guinea 250 94 31 1 15 70 1 1 12 1 3 2 3 1 1 1 11 2 Manus 105 3 4 2 40 2 14 32 1 1 4 2 Easter Is 47 1 46 Total 402 97 35 1 17 110 3 1 12 16 81 1 2 3 1 2 1 15 4

Table 5.2. mtDNA Haplogroup Frequencies (n=402)

Haplogroups

Village/ Island P1 P2a P2b P4 Q1 Q2 Q3 R14 B4a1a B4a1a1 B5b E E1b E2 M28 M29 M7b1 Other Total Lufa 0.36 0.24 0.00 0.02 0.36 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.02 0.00 0.00 0.00 0.00 0.00 1.00 Kiseveroka 0.51 0.09 0.00 0.08 0.18 0.00 0.01 0.10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.02 1.00 Kainantu 0.39 0.15 0.00 0.02 0.39 0.00 0.00 0.04 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.00 Watabung 0.45 0.09 0.00 0.09 0.27 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.09 0.00 0.00 0.00 0.00 0.00 1.00

72 Okapa 0.41 0.19 0.00 0.03 0.38 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.00

Madang 0.07 0.00 0.02 0.12 0.20 0.02 0.00 0.05 0.02 0.07 0.00 0.05 0.02 0.02 0.02 0.02 0.27 0.00 1.00

New Guinea 0.38 0.12 0.00 0.06 0.28 0.00 0.00 0.05 0.00 0.01 0.00 0.01 0.01 0.00 0.00 0.00 0.04 0.01 1.00 Manus 0.03 0.04 0.00 0.02 0.38 0.02 0.00 0.00 0.13 0.30 0.01 0.00 0.00 0.00 0.01 0.00 0.04 0.02 1.00 Easter Is 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.02 0.98 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.00 Total 0.24 0.09 0.00 0.04 0.27 0.01 0.00 0.03 0.04 0.20 0.00 0.00 0.01 0.00 0.00 0.00 0.04 0.01 1.00

The frequency of haplogroup P was 22% in Madang, with three sequences belonging to P1. P2b, a haplogroup not found in EHP, defined by mutations at 16184 and 16256, was found in one individual and P4 was found in five individuals. P was much more prevalent in the highlands than in Madang, which was expected, due to its proposed origin among Papuan speaking peoples.

Manus

Watabung

Kainantu

Madang

Lufa Okapa

Kiseveroka

0 100km

P1 P2a P2b P4 other

Figure 5.2. Haplogroup P Frequency Distribution

After haplogroup P, Q was the second most common in EHP. It was found in

30% of the individuals from EHP (see Figure 5.3 for village locations and frequency distributions). Sixty-two of those sampled belong to haplogroup Q1, defined by transitions at nts 16129, 16144, 16148, 16223, 16241, 16311, 16343 and a transversion at

16265. The frequency of Q1 in Kainantu (at 39%) was the same as the frequency of P in that village. A second Q haplogroup, Q3, defined by transitions at 16129, 16223, 16241 and 16311, was found in one individual in Kiseveroka. Haplogroup Q was also present in 22% of samples from Madang, with eight belonging to the Q1 branch. Q2 defined by transitions at 16066, 16129, 16223 and 16241 was not present in the highlands, but was found in one individual in Madang Province.

Manus

Watabung Kainantu

Madang

Lufa Okapa

Kiseveroka

0 100km

Q1 Q2 Q3 other

Figure 5.3. Haplogroup Q Frequency Distribution

Haplogroup B was found in a small percentage of New Guinea samples. None of the individuals from EHP belonged to lineage B (see Figure 5.4) and only four individuals from Madang could be assigned to this haplogroup. Of the Madang samples in haplogroup B, three samples were B4a1a1, the Polynesian Motif, defined by transitions at nts 16189, 16217, 16247 and 16261, and the other was its precursor, B4a1a which lacks the transition at 16247.

Haplogroup R14, defined by transitions at 16187, 16288 and 16362 and a transversion at 16304 in HVS I and transitions at 56, 182, 204 and 234 in HVS II, was present in 10 individuals or 5 % of EHP samples. Two sequences belonging to haplogroup R14 were found in the Madang sample.

Manus

Watabung

Kainantu

Madang

Lufa Okapa

Kiseveroka

0 100km

R14 B4a1a B4a1a1 B5b other

Figure 5.4. Frequency Distribution for Haplogroups B and R

Other haplogroups were also found at low frequencies in New Guinea.

Haplogroup E was found in two EHP individuals, one from Lufa and one from

Watabung. Haplogroup E was also found in 10% or four people from Madang. Two additional branches of E, E1b defined by transitions at 16261, 16362, 16390 and E2 defined by transitions at 16051, 16362 and 16390, were both present in Madang, but E2 was absent from the EHP sample.

There were several branches of M present in New Guinea. The most common,

M7b1, was found in 11 individuals or 27 % of the population from Madang. Two other

M haplogroups, M28 and M29, were both found in Madang in one person each.

Otherwise, M was absent from New Guinea.

Manus

Watabung

Kainantu

Madang

Lufa Okapa

Kiseveroka

0 100km

M7b1 M29 M28 E E1b E2 other

Figure 5.5. Frequency Distribution for Haplogroups M7, M28, M29 and E

Mitochondrial DNA Distribution in Manus

The second island sampled in this study, Manus, is located approximately 320 km north of New Guinea and is part of the Admiralty Islands. One hundred and three samples from Manus were analyzed. Individuals from all parts of the island have been grouped together, since the coverage of villages was too limited for further separation.

Like New Guinea, Manus HVS I sequences revealed a great deal of population diversity. Haplogroup Q was widespread with 42% of the population belonging to this lineage. Q1 was the most common and appeared in 40 individuals, or 39% of the population, while Q2 was rare being found in only three individuals. No other branches of Q were present on Manus.

In contrast, haplogroup P, which was found at high frequencies in New Guinea, was rare on Manus, being found in only 8% of the population. Three branches of P-P1,

P2a and P4-were all represented in the sample. P2a, found in four individuals, was the most common P haplogroup in Manus, while P1 was found in two individuals and P4 was also found in two individuals.

Forty-six percent of the sequenced samples were assigned to haplogroup B. This frequency is similar to that recorded in Bougainville and Island Melanesia as a whole

(Friedlaender et al. 2007a).. Based on HVSI and HVS II sequences, there were three branches of lineage B present on Manus. B4a1a1 was found in 31 individuals, while

B4a1a was found in 14 individuals and B5b, defined by transitions at nts 16189, 16243 and 16519 in HVS I and 73, 103, 152, 204, 207 and 263 in HVS II, was found in one.

Two haplogroups from lineage M were present on Manus. M7b1, also found in coastal New Guinea made up 4% of the Manus population, while M28 was found in one individual. Haplogroups E and R were absent from Manus.

Mitochondrial DNA Haplogroup Distribution in Easter Island

Easter Island, the eastern most continuously populated island in Polynesia, was chosen as the final island for this study. Forty-seven samples from Easter Island were sequenced and analyzed. All samples are referred to as Easter Island, since demographic information for these individuals was not available at the time of the study. All of the samples belonged to haplogroup B (figure 5.6). All but one of the samples could be assigned to Haplogroup B4a1a1, while one sample lacking the transition at 16247 was assigned to B4a1a.

Figure 5.6. Frequency Distribution for Easter Island.

83 Easter Island

0 1000

B4a1a B4a1a1 KM

Haplogroup Distribution Summary

The results from this data set reveal the presence of ancient Southwest Pacific haplogroups P and Q in all populations with the exception of Easter Island. The most common of these large haplogroups, P1 and Q1, predominated in the Highlands, but the frequency decreased sharply in the populations from Madang and Manus. Equally old, and of Near Oceanic origin, P2 reached appreciable frequencies in the Highlands but also declined in frequency in Madang and Manus. P4, which is thought to show connections between Australian and Near Oceanic populations, surprisingly reached its highest frequency in Madang, in contrast to earlier studies that placed its highest frequency in the

Fringe Highlands (Friedlaender et al. 2005a). Q2 and Q3 were rare, but both were found in New Guinea, and Q2 was also found in Manus. Previous studies placed Q2 in the

Markham Valley and Q3 in the Highlands (Friedlaender et al. 2007a).

R14, a newly discovered Pacific haplogroup previously found in New Guinea

(Hudjasov 2006) was rare in these samples, but was found in three New Guinea populations, two highland and one coastal..

Several haplogroups that appear to have developed in Northern Island Melanesia were found in low frequency in Madang and Manus. M28, with a suspected origin in

New Britain among the Baining, has only been found west of New Britain in one other sample from Misima in the Louisiade Archipelago off the southern coast of New Guinea

(Friedlaender et al. 2007a). M29, most common in East New Britain among the Tolai, and believed to have developed in southern New Ireland, has also been found sporadically in Vanuatu and the Solomons (Friedlaender et al. 2007a). In these samples,

it was found in one individual from Madang Province. The presence of M28 and M29

west of the Bismarcks is interesting since they have not been observed there before.

Haplogroup B, believed to have been recently introduced from Southeast Asia,

was absent from the Highlands but was present, albeit at low frequency, in Madang

Province. Its absence from the Highlands was expected, as other samples from this

region have reported a similar absence of this haplogroup (Melton et al. 1995; Redd et al.

1995). However, the frequency of haplogroup B in the coastal sample from Madang was lower than expected, as previous studies have reported a frequency of more than 30% in coastal populations from New Guinea (Merriwether et al. 1999; Friedlaender et al.

2007a).

The frequency of haplogroup B was high in Manus, second only to Q1, and the frequency of the precursor to the full Polynesian motif B4a1a was also high. One additional sub-haplogroup of B, B5b, was found in Manus. This haplogroup has not been found in any other Island Melanesian studies. In these regions, where Austronesian languages are spoken, the presence of haplogroup B is further evidence that it can be used as a marker of a Holocene expansion into the region that did not include inland regions, such as the New Guinea Highlands. In the Polynesian sample from Easter Island, haplogroup B was the only haplogroup represented.

Haplogroup E, also of Southeast Asian origin, was found both in the Highlands, specifically Lufa and Watabung, and in Madang Province. Haplogroup E has previously been found in Thailand and among Taiwanese Aboriginals in the west, and in New

Britain, New Ireland, Manus and Bougainville in the east (Friedlaender et al. 2007b; Hill

et al. 2007; Ricaut et al. 2008). The presence of E in Watabung and Lufa is surprising

since it was absent from all other Highland populations, and is thought to be restricted,

like haplogroup B, to Austronesian speakers in Near Oceania.

Data Analysis

Network Analysis

Median joining networks were constructed for each of the islands to visualize the phylogenetic relationships. The sequence diversity in New Guinea was markedly high, and two networks were created.. The data were separated into macrohaplogroups M and

N derivatives for network construction. Figure 5.7 for the N network shows a great deal of diversity, particularly within P1. Haplogroups B4a, P4 and R14 show little internal diversity, while P2 shows more than the aforementioned but far less than P1. Figure 5.8 for the M network also shows a great deal of internal diversity. The clear star-like shape of Q indicates a past population expansion, and it was the most common and diverse branch of M in this study. All of the other M lineages showed much less diversity.

The combined network for Manus and Easter Island was less complex than the

New Guinea networks. Overall, the haplogroups showed similar branching to their New

Guinea counterparts, with Q being among the most diverse lineages and showing a star- like expansion pattern and the other haplogroups showing less diversity. Since haplogroup B was better represented in Manus and Easter Island, the pattern of diversity within it is evident. Like Q, B has a star-like signature, also indicative of a population expansion.

B4a B4a1a1

P4 P2b R14

P2 P1

Figure 5.7. Median Joining network for New Guinea, Lineage N. Node size is proportional to number of samples sharing the haplotype.

M29 M28 M7b1 E1b

Q2 Q3

Figure 5.8. Median Joining network for New Guinea, Lineage M. Node size is proportional to number of samples sharing the haplotype.

B41a1a M28 P4 M7b1 B5b Q2 Q1 P2a

B4a1a

Figure 5.9. Median Joining network for Manus and Easter Island. Node size is proportional to number of samples sharing the haplotype

Population Structure Analysis

To analyze the population structure of the mtDNA results, an analysis of molecular variance (AMOVA) was performed on the data. AMOVA measures the percentage of diversity between and within populations. Data can be partitioned by non- genetic criteria, such as language and geography, to determine where these non-genetic criteria significantly influence genetic differentiation (Excoffier et al. 1992). In addition to AMOVA, standard diversity measures were also calculated (i.e., heterozygosity, gene diversity, mean number of pairwise difference and nucleotide diversity). These diversity measures are useful when the primary evolutionary factors are mutation and random genetic drift (Tajima 1983). Finally, partial Mantel tests were used to assess the correlation between genetic distances, linguistic distances and geographic distances

(Mantel 1967; Smouse et al. 1986).

AMOVA

AMOVA was performed on HVS I sequences only, as data for the HVS II were not available for all samples. Multiple groupings were analyzed using the Arlequin

AMOVA settings to ensure that both geographic relationships and linguistic affiliation were examined. The first grouping partitioned the variance among groups, among populations within groups and within populations, with all the individuals belonging to one large Southwest Pacific group. The second AMOVA run partitioned the variance among groups, among populations within groups and within populations, with the individuals separated into (populations) islands – New Guinea, Manus and Easter Island.

The final partitioning of variance was between individuals speaking Papuan languages in one group and individuals speaking Oceanic languages in the other.

Results show that with no population division, the percentage of variance within populations is more than three times the variance among groups (see table 5.2 for exact values), this value is similar to what is seen in African populations (Wood et al. 2005).

Partitioning the variance by geography introduces variation among groups that at almost 18 % is high, while the variation within groups is quite low compared to reports from Island Melanesia, Africa and the Americas (Lewis et al. 2005; Wood et al. 2005;

Friedlaender et al. 2007a), possibly due to the fact that the populations on two of the islands in the study could not be separated into different villages. The variance among groups is high compared to variance reported for African and Native American populations (Lewis et al. 2005; Wood et al. 2005).

Partitioning the variance by the two major language families in the Southwest

Pacific, Papuan and Oceanic, yields results that are almost identical for both among group and within group variance. The percentage of variance accounted for by linguistic affiliation is high among groups when compared to Island Melanesia and Africa, and is low within groups (Wood et al. 2005; Friedlaender et al. 2007a). Overall, the within population variance was higher than the among group variance and the among population variance combined regardless of non-genetic partitioning.

Table 5.3. AMOVA based on mtDNA (HVS I)

Variance Components (%) Number Among Number of of Among Populations Within Grouping Populations Groups Groups Within Groups Populations No grouping (populations) 8 1 … 17.9 82.1 Geography (3 islands)* 8 3 17.8 5.5 76.8 Language (2 groups)** 9 2 11.6 10.3 78.2 *Groups for geography: New Guinea, Manus and Easter Island **Linguistic groups: Papuan, Oceanic

Diversity Measures

Like AMOVA, the diversity measures were calculated using only HVS I sequences. Diversity measures for each of the EHP villages were recorded and a weighted average was calculated for total New Guinea values.

Gene diversity measures the probability that two randomly chosen haplotypes are different in the sample. Mean number of pairwise differences is the difference between all pairs of haplotypes in the sample and nucleotide diversity measures the probability that two randomly chosen nucleotide sites will be different.

When compared to the other two islands in this study, New Guinea is considerably more diverse than both Manus and Easter Island. The standard gene diversity values for New Guinea and Manus were close, at 0.933 and 0.917, and are double the standard gene diversity for Easter Island. The nucleotide diversity, which is reported as being very informative when studying difference, is high in New Guinea at

.026, Manus follows with a nucleotide diversity of .019 and Easter Island is the least diverse at .001. The final population comparison measures the number of differences

between any given pair of sequences and shows the greatest difference between the populations with New Guinea once again showing the greatest amount of differentiation.

Table 5.4. Haplotype Diversity within Populations

number Standard of number of Gene Mean number of nucleotide diversity pairwise Islands /Villages samples haplotypes Diversity s.d differences s.d (average over loci) s.d NG-Lufa 41 23 0.96 0.02 7.99 3.79 0.03 0.01

94 NG-Okapa 32 21 0.97 0.02 8.30 3.95 0.02 0.01

NG-Kainantu 46 22 0.95 0.01 8.90 4.18 0.03 0.01 NG-Madang 42 28 0.94 0.03 6.79 3.26 0.02 0.01 NG-Watabung 11 10 0.98 0.05 6.18 3.18 0.04 0.02 NG-Kiseveroka 76 25 0.89 0.03 8.83 4.12 0.03 0.01 New Guinea 248 0.93 0.02 8.17 3.87 0.03 0.01 Manus 103 36 0.92 0.02 6.39 3.05 0.02 0.01 Easter Island 47 6 0.45 0.09 0.41 0.38 0.00 0.00

Mantel Matrix Correlation

Mantel matrix correlation analyzes distance matrices to quantify significant correlations among them. Matrices were constructed to compare Fst values, geographic distances and linguistic distances to reveal any relationships between patterns of genetic variation with geography or language. The linguistic and geographic distance matrices were constructed following methods discussed in Chapter 4. Less than 5 % of the mtDNA variation was determined by language, while more than 60% of the variation was determined by geography when the geographic matrix was constructed using distance measured in km from New Guinea to Manus and Easter Island. The correlation coefficient for the genetic and geographic correlation was (r=0.84, p=0.02) and the correlation between genetics and linguistics was (r=0.40, p=0.008). When the geographic distance matrix was constructed to assess correlations between genetic distance and insular area measured in km 2, 40% of the variation was determined by insular area

(r=0.67, p=0.01), and 5% of the variation was determined by language (r=0.45, p=0.003).

The magnitude and significance of the correlations remain the same when geography and linguistic distance are held constant.

The significant correlation between genetic distance and geography suggests a clear connection between the two variables. However, linguistic distance does not produce evidence of as strong a correlation between language family affiliation and genetic distance.

Summary of Results

Overall, the findings for New Guinea were consistent with previous research that reports great diversity in the Highlands (Redd and Stoneking 1999; Ingman and

Gyllensten 2003; Friedlaender et al. 2007b). The diversity among the village populations was evenly distributed, and there were many unique haplotypes in New Guinea and

Manus, indicating a long time of occupation and a lack of selective sweeps or strong genetic drift. This is not the case for Easter Island, where only six haplotypes were reported, very likely an indicator of founder effect in Polynesia.

According to the AMOVA data, both geography and language affiliation appear to have some effect on variance in this data set. However, AMOVA results from Island

Melanesia reveal evidence that geography influences variance while linguistic affiliation generally does not (Friedlaender et al. 2007a).

The diversity indices mark New Guinea as the most diverse of the three regions in terms of gene diversity, number of pairwise difference and nucleotide diversity, with

Manus following closely and Easter Island with less than half of the gene diversity of the other two regions, and with number of pairwise difference and nucleotide diversity values even lower.

In determining what contributed to the observed diversity in the region, partial correlations were calculated for genetic distance, geographic distance and linguistic distance. Mantel tests revealed a strong statistically significant positive correlation between genetic distance and geographic distance while the correlation between linguistic and genetic distance was weaker, but still significant.

The following chapter will discuss the patterns and determinants of variation in New Guinea, Manus and Easter Island and compare these patterns with those observed in the Bismarck Archipelago.

CHAPTER 6 Genetic Variation and Population Structure in the Southwest Pacific

Determinants of Genetic Variation

Population variation is known to be influenced by factors including population demographic history, natural selection, climate, isolation, island area and even island elevation (Hamilton et al. 1964; Mac Arthur and Wilson 1967; Hamilton 1976).

Diversity can also be influenced by population age, as older populations are generally more diverse.

In addition, island size is generally an important factor because larger islands are able to support larger permanent populations. At the species level, there is a strong relationship between the size of a sample area and the number of species found in that area (Mac Arthur and Wilson 1967). As islands become larger, the topography becomes more complex and the degree of habitat heterogeneity increases allowing for more species as well (MacArthur and Wilson 1967). In studies on bird species number on

Pacific Islands, 80-90% of the variation can be attributed to island area and complexity

(Hamilton et al. 1964; Mac Arthur and Wilson 1967; Mayr and Diamond 2001). Insular area would not be expected to influence variation in human populations as strongly, but the effect that island area has on degree of variation is evident (Cavalli-Sforza et al.

1994).

Traditional biogeographical theory also presents a model for an equilibrium between immigration and extinction that affects species number. This equilibrium between immigration and extinction contributes to the increased diversity on larger islands and those that are closer to centers of dispersal, as both larger islands and islands 98

closer to sources of dispersal receive more immigrants (see Figure 6.1) (Mac Arthur and

Wilson 1967).

near small

Rate

far large

Number of Species Present, N

Figure 6.1. Equilibrium model for islands of varying size and distance from source region. An increase in distance lowers the immigration curve and an increase in area lowers the extinction curve. (After MacArthur and Wilson 1967.).

Current patterns of genetic variation in human populations also link isolation and distance from source populations and variation (Prugnolle et al. 2005; Foll and Gaggiotti

2006). Variation between populations increases as distance between those populations increases, and isolates are more likely to experience genetic drift that reduces variability.

However, variation within populations decreases with distance from Africa, as African populations are more variable than all others and are considered to be the source population for modern human dispersal (Vigilant et al. 1991; Jorde et al. 2000; Manica et

al. 2005; Handley et al. 2007). The same factors should influence the pattern of genetic

variation in the Southwest Pacific.

Structure of Genetic Variation in the Pacific

Results from previous studies and those reported here mark the Pacific as an area of great genetic diversity. The mitochondrial DNA results from this study are in general agreement with earlier studies, with some modifications (Lum and Cann 1998;

Merriwether and Friedlaender 2004; Lie et al. 2006; Friedlaender et al. 2007a;

Friedlaender et al. 2007b; Kayser et al. 2008b; Ricaut et al. 2008).

The oldest and most common haplogroups in New Guinea, P and Q, have been reported in every other survey of mtDNA variation in the region, and both are well represented here. The absence of haplogroup B in the highlands, and its presence, along

with several other Southeast Asian haplogroups, along the coast and on the offshore

island of Karkar is also confirmed in the literature (Stoneking et al. 1990; Kayser et al.

2001; Ricaut et al. 2008). Differences from prior studies include the presence of Island

Melanesian haplogroups M28 and M29 in the coastal New Guinea sample, as well as the

presence of P2 and P4, both usually found in highlanders (Friedlaender et al. 2005a;

Ricaut et al. 2008). The newly discovered haplogroup R14 was found in both the coastal

and highland sample and has been found in only highland samples in the past (Hudjasov

2006). This haplogroup may have relatives as far east as India, and further study of this

haplogroup is needed to determine its origin and distribution.

100

A great deal of mtDNA diversity was also found in Manus, which is also

supported by earlier work in this region (Kayser et al. 2008a) and the lack of diversity in

Easter Island is similarly documented.

For a more comprehensive understanding of Pacific diversity, the results from

Chapter 5 have been supplemented by data collected by Dr. Jonathan Friedlaender from

Bougainville, New Ireland and New Britain (Friedlaender et al. 2005a; Friedlaender et al.

2005b; Friedlaender et al. 2007a). The pattern of diversity seen in Island Melanesia is

similar to New Guinea, with islands directly to the east of New Guinea sharing early

settlement dates and also showing the presence of at least two migrations in the form of

old and new haplogroups.

Analysis of the variation within populations was calculated using standard

diversity measures. New diversity measures were calculated for New Guinea, Manus and

Easter Island for comparison with New Britain, New Ireland and Bougainville (see Table

6.1). Values for all standard measures are higher for New Guinea than any of the other

regions, marking it the most diverse island in the study. In terms of standard gene

diversity, which measures the probability that two randomly chosen haplotypes are

different in the population, values are also high for New Britain, New Ireland and Manus.

Mean number of pairwise differences measures the average observed differences between

haplotypes of pairs of individuals and values are high for New Guinea, New Britain, and

Manus. Finally, nucleotide diversity over loci, which measures the probability over loci that two randomly chosen haplotypes are different in a population, is high in New

Guinea, New Britain, Bougainville and Manus. The pattern of variation is not uniform across the diversity measures, but some trends are evident.

101

New Guinea shows the greatest diversity for all of the diversity measures, and

Manus shows the second greatest diversity. In Northern Island Melanesia, the diversity

measures order islands from New Britain, Bougainville and New Ireland in terms of

heterozygosity, number of pairwise difference and nucleotide diversity. The one measure

that does not hold up to this ordering is gene diversity, which is highest in New Ireland.

A possible explanation for this result is the extremely low values for gene diversity found

amongst several of the isolated non-Austronesian populations in New Britain and

Bougainville since isolation is believed to be negatively correlated with diversity.

Across the diversity measures used in this study, values tend to be higher on the

larger islands with few exceptions. According to insular area measurements (see Table

6.2), Manus should be less diverse than New Britain, Bougainville and New Ireland. In

fact, many of the populations from New Britain and Bougainville have diversity values

that are higher than those in Manus, but the overall values for these two large islands are decreased significantly by low values in some of the populations (see Tables 6.1). A reasonable cause for the marked differences in diversity between populations within these islands can be explained by location on the island. Past Pacific studies have revealed significant differences in the levels of variation between coastal and inland populations and the inland populations in both New Britain and Bougainville have the lowest diversity measures for their respective islands.

Several recent Pacific studies of Island Melanesian diversity, using mtDNA and

NRY, revealed greater diversity in shore populations than inland populations

(Friedlaender et al. 2007a; Hunley et al. 2007; Schanfield et al. 2007). It is suspected that the genetic distances were smaller and diversity greater in these populations because

102

genetic drift in inland populations has reduced diversity and people on the coast generally live in larger groups, are less isolated, and have not been in the region long enough for the effects of genetic drift to be visible (Friedlaender et al. 2007a; Hunley et al. 2007).

This finding is in contrast to what was found in New Guinea in the current study, where inland populations were found to be more variable than the coastal populations.

The difference between inland and shore populations in this study is illustrated by the lower diversity measures in the coastal population from Madang when compared to the highland populations in New Guinea, in that most of the diversity measures place

Madang very low in terms of diversity measures. The inland groups on New Guinea appear to be genetically more distinct than populations on the shore.

Upon further analysis, the increased diversity in highland New Guinea consists of diversity within very few haplogroups, primarily the Pleistocene era haplogroups that are believed to be the result of the initial colonization, and that are found amongst most NAN language speakers on the large islands of Melanesia (i.e., P and Q). Inland populations share few haplogroups with one another and with coastal populations. In contrast, the coastal Madang population is more diverse in terms of the number of haplogroups represented, including a number of recently introduced haplogroups from the west, but

these haplogroups lack the extensive haplotype variation present in the interior.

When compared to the haplotype sharing pattern that occurs in the inland

population, with high frequencies of older haplogroups, the coastal groups with higher

frequencies of the younger haplogroups share more haplotypes. The inland populations

on the larger islands share, on average, 15 haplotypes, while the coastal populations share

approximately 30 haplotypes. Even when all haplogroup B samples are included in one

103

median joining network there is little branching. Most of the haplotypes cluster together with the exception of a few singletons.

104

Table 6.1. Diversity Measures for Southwest Pacific Islands

number Islands /Villages of number of mean expected sd Standard Gene Sd Mean number of sd nucleotide diversity sd Pairwise samples haplotypes heterozygosity Diversity differences (average over loci) Aita 52 6 0.01 0.06 0.42 0.08 4.51 2.26 0.01 0.01 Buka 15 10 0.02 0.08 0.94 0.04 5.03 2.59 0.03 0.02 Nagovisi 15 3 0.00 0.03 0.60 0.07 0.67 0.54 0.00 0.00 Nasioi 30 13 0.02 0.09 0.96 0.02 6.84 3.31 0.02 0.01 Rotokas 19 3 0.02 0.10 0.66 0.06 6.46 3.20 0.02 0.01 Saposa 21 7 0.01 0.05 0.83 0.05 3.34 1.79 0.01 0.01 Siwai 19 8 0.01 0.07 0.85 0.07 4.50 2.32 0.01 0.01 Torau 45 18 0.02 0.08 0.89 0.03 6.84 3.28 0.02 0.01

105 Teop 17 8 0.02 0.08 0.86 0.06 6.41 3.19 0.02 0.01

Bougainville 233 0.02 0.07 0.79 0.05 5.24 2.61 0.02 0.01 Anem 17 5 0.02 0.08 0.66 0.13 5.68 2.86 0.02 0.01 Ata 58 13 0.02 0.07 0.78 0.03 7.62 3.61 0.02 0.01 Kagat 59 9 0.01 0.06 0.77 0.04 3.06 1.62 0.01 0.01 Kol 57 15 0.02 0.08 0.88 0.02 6.19 2.98 0.02 0.01 Kove 17 7 0.02 0.08 0.75 0.09 4.93 2.52 0.02 0.01 Mali 58 8 0.01 0.08 0.75 0.03 5.01 2.47 0.01 0.01 Mamusi 62 13 0.02 0.08 0.85 0.03 6.89 3.29 0.02 0.01 Mangseng 17 14 0.02 0.09 0.97 0.03 7.18 3.54 0.02 0.01 Melamela 21 11 0.02 0.08 0.90 0.04 5.55 2.78 0.02 0.01 Mengen 23 11 0.02 0.09 0.94 0.03 7.28 3.54 0.02 0.01

(Table 6.1 continued)

number Islands /Villages of number of mean expected sd Standard Gene Sd Mean number of sd nucleotide diversity sd Pairwise samples haplotypes heterozygosity Diversity differences (average over loci) Nakanai 65 15 0.02 0.08 0.85 0.03 6.09 2.94 0.02 0.01 Sulka 28 14 0.02 0.07 0.93 0.04 5.15 2.57 0.02 0.01 Tolai 77 24 0.02 0.07 0.88 0.02 5.88 2.84 0.02 0.01 Loso 16 8 0.02 0.08 0.81 0.09 5.79 2.92 0.02 0.01 New Britain 575 0.02 0.08 0.83 0.04 5.85 2.85 0.02 0.01 Lavongai 18 11 0.01 0.06 0.93 0.04 3.18 1.72 0.01 0.01 Notsi 17 9 0.01 0.06 0.92 0.06 3.32 1.79 0.01 0.01 Kuot 62 7 0.01 0.04 0.87 0.03 1.70 1.01 0.01 0.00

106 Nailik 24 9 0.01 0.07 0.91 0.04 4.16 2.14 0.01 0.01

Madak 31 9 0.01 0.06 0.86 0.04 3.70 1.92 0.01 0.01 New Ireland 152 0.01 0.05 0.89 0.04 2.98 1.60 0.01 0.01 Lufa 41 23 0.02 0.09 0.96 0.02 7.99 3.79 0.03 0.01 Okapa 32 21 0.02 0.09 0.97 0.02 8.30 3.95 0.02 0.01 Kainantu 46 22 0.03 0.09 0.95 0.01 8.90 4.18 0.03 0.01 Madang 42 28 0.02 0.07 0.94 0.03 6.79 3.26 0.02 0.01 Watabung 11 10 0.03 0.10 0.98 0.05 6.18 3.18 0.04 0.02 Kiseveroka 76 25 0.03 0.08 0.89 0.03 8.83 4.12 0.03 0.01 New Guinea 248 0.02 0.08 0.93 0.02 8.17 3.87 0.03 0.01

(Table 6.1 continued)

number Islands /Villages of number of mean expected sd Standard Gene Sd mean number of sd nucleotide diversity sd Pairwise samples haplotypes heterozygosity Diversity differences (average over loci) Manus 103 36 0.02 0.09 0.92 0.02 6.39 3.05 0.02 0.01 Easter Is 47 6 0.00 0.02 0.45 0.09 0.41 0.38 0.00 0.00

Table 6.2. Island Size and Settlement Dates 107

Island Date Size (km 2) New Guinea ~40,000- 50,000 BP 462,000km 2 New Britain ~40,000 BP 37,819km 2 New Ireland ~40,000 BP 7,405km 2 Bougainville ~32,000 BP 10,954km 2 Manus ~20,000 BP 1,925km 2 Easter Island ~1,200 AD 163km 2

B4a1a1 median vector

B4a1a

median vector B5b

New Guinea Manus Easter Island

Figure 6.2. Median-joining network for Haplogroups B4a1a and B4a1a1 and B5b. Node size is proportional to number of samples sharing the haplotype.

Another factor that is often assumed to be closely tied with genetic diversity is the effect of isolation. Here, the effect of isolation on diversity from island to island as well as the effect of isolation on populations within the same island is important. There are a number of ways to measure isolation, by examining the items being moved back and forth from one place to another, examining how often exchanges and interactions occur and counting the number of people moving from one area to another. For the Pacific data, level of isolation was primarily measured by examining artifacts and plant and

108

animal translocations from island to island and between different regions on the larger islands (Lilley 2006; Matisoo-Smith 2007; Summerhayes 2007).

After the initial settlement of New Guinea and the Bismarcks, there is little evidence of movement between the two regions for 20,000 years. At 20,000 BP, with the settlement of Manus, there is clear evidence, in the form of plant and animal translocations and the movement of obsidian, of interaction between islands within Island

Melanesia and New Guinea (Flannery and White 1991; Leavesley and Allen 1998;

Summerhayes 2007). The degree of isolation indicated here was based partially on population interaction, evidenced by archaeology and on geographic distance.

The mtDNA pattern also provides evidence of the relative isolation of the populations in the region. Based on the haplogroup distributions, it appears that isolated inland populations have retained lineages from the earliest settlement of Sahul and the

Bismarcks, and that coastal populations share many haplogroups with each other, increasing their overall variability. Isolated populations would be expected to show less evidence of admixture and are, therefore, more likely to retain lineages from ancient migrations. The Easter Island population in Remote Oceania has by far the lowest diversity measures, due to the high frequency of B4a1a1 the Polynesian motif. The clustering of Remote Oceanic lineages and low heterozygosity reflects genetic drift in isolated populations, and indicates these populations were less effected by post settlement gene flow due to their extreme isolation. In Remote Oceania, isolation is more of a determining factor of species diversity than insular area or island complexity.

In this study, the effects of age on population diversity do not show any patterning. Using population age as an indicator of diversity, New Guinea, New Britain

109

and New Ireland would be the most diverse regions in this data set followed by

Bougainville, Manus and Easter Island in order of settlement. When New Guinea, New

Britain and New Ireland are actually compared to Manus, Bougainville and Easter Island, the most recently settled regions in the study, the results are mixed. In all the diversity measures, Easter Island is least diverse, which follows the idea that more recently settled regions are less diverse, but Manus is placed directly behind New Guinea, and ahead of the other islands in Melanesia. If population age has a measurable effect on genetic diversity, this does not hold true in the Southwest Pacific as age of settlement has no discernable effect here.

Discussion of mtDNA Variation in the Southwest Pacific

The aims of this study were to survey the mitochondrial DNA variation in the

Southwest Pacific and to determine what factors contribute to the observed pattern of variation.

The mtDNA diversity in the Southwest Pacific shows no discernable pattern of haplotype sharing across the haplogroups. Most haplogroups, including E, P, M7b1,

M28 and M29, had too few members across the islands for any pattern to be visible.

Haplogroup Q showed little patterning when placed in a median joining network

(network not shown). Many of the same Q haplotypes were found in both Manus and

New Guinea. Similarly, B haplotypes are shared across the islands with the exception of a few B4a1a1 haplotypes that were not found in either New Guinea or Easter Island, and one B5b that was not found in any other sampling of this region (see Figure 6.2).

110

The pattern of variation shows strong correlations between geographic factors

(isolation and insular area) and genetic variability, but little or no correlation with time

since initial settlement. On these islands, genetic diversity is organized primarily by

island size, and the internal diversity is organized by coastal/shore location. Differences

in the Papuan speaking populations drives the pattern of mtDNA variation, and this

pattern of diversity strongly suggests population isolation in island interiors is a stronger

determinant of variability on the larger islands. The coastal populations are distinct from

one island to the next, but less than what is seen in the Papuan isolates.

This insular variation is also divided, at least partially, along linguistic family

lines. Inland groups are often Papuan speaking groups, and have experienced the effects

of isolation and drift, and the coastal populations are often Oceanic speaking groups that are more mobile and intermixed. There was also a positive correlation between language family affiliation and genetic variability, but when compared to the geographic factors, the strength of the geography/genetic correlation is unquestionable. In order to assess the true correlation between linguistic and genetic distances, more detailed information is needed to ensure that the relationship between these variables has not been underestimated.

The decreased variation on the smaller islands is due primarily to the link between population size and genetic variation where population size is generally positively correlated with variability in populations. But in the case of Easter Island, with its distance from New Guinea, distance from dispersal regions more than likely plays a very important role. To gain a clear understanding of this concept, equally small islands that are closer to centers of dispersal should be examined.

111

Ultimately, the pattern of diversity and the strength of the correlations parallel the biogeography of birds on Pacific islands, where insular area and complexity strongly correlates with species number. An important next step in understanding how close human population dynamics parallels that of other species will be to use additional genetic markers to test the strength of these correlations.

112

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