Institute of Biodiversity and Environmental Conservation culty of Resource Science and Technology

DISTRIBUTION PATTERNS, MIGRATION ROUTE AND PHYLOGENETIC RELATIONSHIP OF WADERS (AVES: SCOLOPACIDAE) IN SARAWAK, MALAYSIAN BORNEO

Nurul Ashikeen Binti Ab Razak

Master of Science (Biodiversity Conservation) 2014

DISTRIBUTION PATTERNS, MIGRATION ROUTE AND PHYLOGENETIC RELATIONSHIP OF WADERS (AVES: SCOLOPACIDAE) IN SARAWAK, MALAYSIAN BORNEO

NURUL ASHIKEEN BT AB RAZAK

A thesis submitted in fulfillment of the requirements for the degree of Master of Science (Biodiversity Conservation)

Institute of Biodiversity and Environmental Conservation UNIVERSITI MALAYSIA SARAWAK 2014

DECLARATION

I hereby declare that no portion of the work referred to this thesis has been submitted in support of an application for another degree or qualification to this or any other university or institute of higher learning.

(Nurul Ashikeen Binti Ab Razak) Date:

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ACKNOWLEDGEMENT

Bismillahhirrahmanirrahim… First of all, I would like to praise Allah SWT for His kind blessings throughout completing my MSc study. I am very grateful to my supervisor, Prof. Dr. Mustafa Abdul Rahman, for his dedication throughout my study, the one who has provided his guidance, knowledge and various logistic and moral supports. Also million thanks to my co-supervisor, Prof. Dr. Andrew Alek Tuen, for his opinion, and support throughout my study. A loud applause to my lecturers: Dr. Ramlah Zainuddin, Prof. Mohd. Tajuddin Abdullah, Dr. Yuzine Esa, Prof. Hj. Sulaiman Hanapi, Dr. Leaw Chui Pin, Ms. Siti Nurlydia and Ms. Ratnawati, for their companionship and experience-sharing which had improved my working skills.

To IBEC and Zoology staff: I would also like to express my sincere thanks to: Ms. Rahah Yakup, Mr. Isa Sait, Mr. Mohd Hasri Al-Hafiz, Mr. Huzal Irwan and Mr. Nasron, for their help during the fieldworks and informative knowledge in guiding me throughout this study. Without your help and strength, I won’t be able to catch a single sample by my own. To other staff: Mdm. Mazrina, Mdm. Mazlini, Mdm. Meri Sabas, Mr. Sulaiman Bol, Mdm. Sendi and Mdm. Farhana Anwar, thank you for sharing your laughter and provide a comfortable environment for me to complete my work.

To my PG colleagues and friends: Ms. Zahirunisa, Ms. Nur Aida, Ms. Nur Hafidah, Ms. Siti Zuriani, Mdm. Wan Nurainie, Ms. Irene Christianus, Ms. Farawahida, Ms. Farliana Zulea, Ms. Diana, Mdm. Nor Salmizar, Ms. Madinah, Ms Millawati, Ms. Ho Licia, Ms. Luisa Duya, Ms. Roberta Chaya, Ms. Elvy Quatrin, Ms. Pang Sing Tyan, Mr. Eric Pui Yong Min, Mr.

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Mohd. Hanif Ridzuan, Mr. Mohd Ridwan, Mr. Muhamad Ikhwan, Mr. Mohd Isham and Mr. Muhammad Fadzil Amram for their infinite helps and magnificent friendships.

Deepest and special thanks to my beloved parents, Abdul Razak Ruki and Siti Zubaidah for their endless love and priceless support, prayers and courage. Love you mama and papa! To my family: Nor Zareen, Nur Yasmeen Nadhirah, Mohd Hadri, Zuliza Othman and Mohamad Nazli Hizam, thank you for trusting me and give me strength to complete my study. To Biey Sidq, thank you for always believe in me and always stay with me throughout my ups and downs. Thank you for being my 24-7 mentor.

This study would not been possible without various administrative and financial supports from UNIMAS. I would like to thank UNIMAS for granting me the Zamalah UNIMAS 2009/11 scholarship. This study was also funded by Shell Chair Research Grant Scheme; SRC/02/2007(02) and Kementerian Pengajian Tinggi (KPT). I thank Sarawak Forest Department, Sarawak Forestry Corporation for granting research permit and giving me an opportunity to collect samples from various sites in Sarawak. Last but definitely not least, I offer my regards and blessings to everyone who involved in my life, directly and indirectly. I am so blessed surrounded by wonderful people. Thanks….

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Abstract Among birds, the order Charadriiformes are considerably well-studied but taxonomic and phylogenetic information at the intra family level are still lacking. The main focus of this study is to describe the evolutionary traits within Scolopacidae species (waders) with inference on their macrogeographic distributional pattern in Southeast Asian region, particularly in Sarawak. This study consists of two main research components. The first is the macrogeographical distribution of Scolopacids in Southeast Asian region and their habitat utilization derived from regional avian database (eg: Bird field guides, published reports and surveys). The data analysis was illustrated by comparative Unweighted Pair Group Method with Arithmetic Mean (UPGMA) on species distribution and their habitat preferences. Essentially, the general distribution pattern of shorebirds within the Southeast Asian countries was also presented with emphasis on the specific distribution of the Scolopacidae species during non-breeding season along the East-Asian Australasian Flyway (EAAF). The second component is the reconstruction of phylogenetic relationship of Scolopacidae species using two different markers; the mitochondrial DNA Cytochrome Oxidase I (COI) and the nuclear DNA Recombinant Activating Gene 1 (RAG1). Overall, 16 species of Scolopacidae were sampled from six selected sampling sites across Sarawak. These include Lundu, Asajaya, Buntal, Sungai Aur, Kampung Chupak and Pulau Bruit. The phylogenetic trees were constructed using four inference methods; Neighbour-Joinning (NJ), Maximum Parsimony (MP), Maximum Likelihood (ML), and Bayesian Inference (BI). In general, the result from my first component revealed that shorebirds as well as waders are widely dispersed throughout Southeast Asian countries although their distributional patterns were slightly different. This is further demonstrated by the dendrogram clustering of waders where Burma was separated from other Southeast Asian countries. Whereas, for dendrogram of shorebirds;

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Burma, Vietnam and Thailand were clustered together as a group. Hence, the distributional patterns are consistent with the recent tectonic plates that consist of mainland and island formations. In addition, waders performed migration using unique and specific pathways within East Asian Australasian Flyway (EAAF). Within their pathways, waders exhibited specific preferences in selecting the most fitting and suitable habitat for feeding and roosting. This is perhaps best modelled by subfamily Scolopacinae (snipe) in which this particular inland group is potentially a habitat specialist rather than a habitat generalist group. On the other hand, the molecular evidences for both DNA genes and combined genes revealed consistent tree topology groupings of two major clades, which are large sandpipers (Numeniinae) derived as the basal lineage and another group consisting of small to medium sandpipers (Calidriinae, Scolopacinae, and Tringinae). Within all phylogenetic trees, Bayesian inference (BI) from combined genes displayed the most resolved tree of all inference methods. As a whole, the evolutionary patterns of genetic traits within the Scolopacidae family were plausibly incongruent with their specific distribution and habitat preferences. This is shown by the cluster analysis depicting that the Scolopacinaes were clearly isolated from the others. On the contrary, this group was closely related to Tringinae in the phylogenetic trees. Although both are genetically related, they have probably evolved different morphological features that permitted them to adapt in suitable habitat.

Key words: shorebirds, Scolopacidae, macrogeography, habitat preference, phylogenetic

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Abstrak Order Charadriiformes adalah antara burung yang sering dikaji tetapi taksonomi dan maklumat filogenetik pada peringkat famili masih belum mencukupi. Fokus utama kajian ini adalah untuk menggambarkan ciri-ciri evolusi dalam spesies Scolopacidae (waders) berkaitan corak taburan geografi mikro mereka di rantau Asia Tenggara, khususnya di Sarawak. Kajian ini terdiri daripada dua komponen penyelidikan yang utama. Yang pertama adalah taburan geografi mikro daripada Scolopacids di rantau Asia Tenggara dan penggunaan habitat mereka yang diperolehi dari pangkalan data burung serantau (contohn: buku panduan lapangan burung, terbitan laporan dan kajian survei). Analisis data telah dipaparkan oleh analisis “Unweighted Pair Group Method with Arithmetic Mean” (UPGMA) mengenai taburan spesies dan habitat pilihan mereka. Secara amnya, corak taburan umum burung persisiran pantai di negara-negara Asia Tenggara telah dibentangkan dengan memberi penekanan kepada taburan spesis Scolopacidae semasa musim bukanpembiakan di sepanjang “East Asian Australasia Flyway” (EAAF). Seterusnya, komponen kedua ialah pembinaan semula hubungan filogenetik spesies Scolopacidae menggunakan dua penanda molecular yang berbeza; DNA mitokondria “Cytochrome Oxidase I” (COI) dan nuklear DNA “Recombinant Activating Gene 1” (RAG1). Secara keseluruhan, 16 spesis Scolopacidae telah disampel dari enam kawasan persampelan terpilih di seluruh Sarawak. Ini termasuklah kawasan Lundu, Asajaya, Buntal, Sungai Aur, Kampung Chupak dan Pulau Bruit. Pokok-pokok filogenetik telah dibina menggunakan empat kaedah inferens; “Neighbour-Joinning” (NJ), “Maximum Parsimony” (MP), “Maximum Likelihood” (ML), dan “Bayesian Inference” (BI). Secara umum, hasil daripada komponen pertama saya mendedahkan bahawa burung persisiran pantai serta “waders” tersebar secara meluas di seluruh negara-negara Asia Tenggara walaupun corak taburan mereka sedikit berbeza. Ini

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ditunjukkan oleh dendrogram waders yang meletakkan Myanmar sebagai kelompok dasar kepada negara-negara Asia Tenggara lain. Manakala, dalam dendrogram burung pesisiran pantai; Myanmar, Vietnam dan Thailand membentuk kumpulan bersama. Oleh itu, corak taburan mereka dikatakan konsisten dengan plat tektonik terkini yang terdiri daripada tanah besar dan pembentukan pulau. Di samping itu, waders bermigrasi menggunakan laluan yang unik dan khusus dalam EAAF. Dalam laluan mereka, waders mempamerkan keutamaan khusus dalam memilih habitat yang paling sesuai untuk mencari makanan dan berehat. Kemungkinan ini telah dimodelkan oleh subfamili Scolopacinae (snipe) di mana kumpulan ini dikenal pasti berpotensi menjadi burung habitat khusus daripada satu lagi kumpulan iaitu burung habitat am. Sebaliknya, keputusan molekul bagi kedua-dua gen DNA dan gen gabungan mendedahkan topologi yang konsisten di dalam pokok filogenetik iaitu terbahagi kepada dua cabang utama; waders besar (Numeniinae) sebagai keturunan dasar dan satu lagi kumpulan terdiri daripada waders kecil dan sederhana (Calidriinae, Scolopacinae, dan Tringinae). Dalam semua pokok filogenetik, rujukan Bayesian (BI) daripada gen gabungan memaparkan pokok yang terbaik dari semua kaedah rujukan. Secara keseluruhannya, corak evolusi genetik dalam Scolopacidae berkemungkinan tidak selari dengan taburan khusus mereka dan pemilihan habitat. Ini ditunjukkan oleh analisa di mana Scolopacinae jelas terasing daripada spesies yang lain. Sebaliknya, di dalam pokok filogenetik, kumpulan ini didapati berkait rapat dengan Tringinae. Walaupun kedua-duanya berkaitan secara genetiknya, mereka mungkin telah megalami perubahan pada ciri-ciri morfologi untuk membolehkan mereka menyesuaikan diri di mengikut habitat tertentu.

Kata kunci: burung persisiran pantai, Scolopacidae, macrogeography, pemilihan habitat, filogenetik

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TABLE OF CONTENTS Declaration

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Acknowledgements

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Abstract

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Abstrak

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Table of contents

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List of Figures

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List of Tables

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Abbreviations

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CHAPTER ONE General Introduction 1.1

Migration of shorebirds

1

1.2

Distribution of shorebirds of Southeast Asia

3

1.3

Staging sites

6

1.4

Taxonomic classification of shorebirds

9

1.5

History of waders occurrences in Borneo

10

1.6

Species studied

13

1.7

General and specific aims of study

15

1.8

Outline of thesis

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CHAPTER TWO General Materials and Methods 2.1

Introduction

17

2.2

Study sites

17

2.2.1 Buntal

20

2.2.2 Sambir

20

2.2.3 Pulau Bruit

21

2.2.4 Lundu

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2.2.5 Kampung Chupak

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2.2.6 Telaga Air

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2.3

General field techniques 2.3.1 Mist-netting birds

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2.3.2 Banding birds

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2.3.3 Sample collection

25

2.3.4 Preparation of study skins

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2.4

General laboratory techniques

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2.5

General Data Analysis 2.5.1 Molecular Genetics

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2.5.2 Macrogeography distribution of shorebirds in Southeast Asia

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CHAPTER THREE Macrogeographic Distribution and Habitat Preferences of Waders (Charadriiformes: Scolopacidae) and Other Shorebirds in Southeast Asia 3.1

3.2

3.3

3.4

3.5

Introduction 3.1.1 Migrational route of shorebirds in East Asian-Australian Flyway

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3.1.2 Staging sites of waders in Malaysia

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3.1.3 Description of habitat preferences

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3.1.4 Specific research objectives

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Materials and Methods 3.2.1

Data collection

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3.2.2

Data analysis

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Results 3.3.1 General distributional pattern of shorebirds in Southeast Asia

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3.3.2 Wader occurrences in Southeast Asia

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3.3.3 The potential routes within EAAF

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3.3.4 Habitat utilization by Scolopacidae

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Discussion 3.4.1 General Distributional pattern in Southeast Asia

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3.4.2 Habitat selection and utilization

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Conclusion

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CHAPTER FOUR Phylogenetic relationships of waders (Family Scolopacidae) in Sarawak inferred from Cytochrome Oxidase I and Recombinant Activating Gene 1 4.1

Introduction

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4.1.1 Gene characteristic of mtDNA Cytochrome Oxidase I (COI) and

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nucDNA Recombinant activating gene (RAG1) 4.1.2 Specific research objectives 4.2

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Materials and Methods 4.2.1 Molecular and laboratory methods 4.2.1.1 DNA extraction of tissue samples

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4.2.1.2 Polymerase Chain Reaction (PCR)

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4.2.1.3 Purification of PCR Product and DNA Sequencing

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4.2.2 Data analysis

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4.2.2.1 Sequence divergence

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4.2.2.2 Partition homogeneity test and combined genes analysis

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4.2.3 Phylogenetic analysis 4.3

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Results 4.3.1 Analysis of sequence 4.3.1.1 Nucleotide composition

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COI, RAG1, combined gene 4.3.1.2 Substitution Saturation test

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COI, RAG1, combined gene 4.3.1.3 Pairwise distance

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COI, RAG1, combined gene 4.3.2 Phylogenetic trees analysis

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4.3.2.1 Partial Cytochrome Oxidase I (COI) gene

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NJ MP ML Bayes 4.3.2.2 Recombinant Activating Gene 1 (RAG 1)

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NJ MP ML Bayes 4.3.2.3 Charpartition and combined genes xi

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NJ MP ML Bayes 4.3.3 Divergence time 4.4

4.5

110

Discussion 4.4.1 Genetic associations among and within Scolopacidae species

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4.4.2 Phylogeny using COI and RAG1 gene

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4.4.3 Divergence times of Scolopacidae

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Conclusion

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CHAPTER FIVE General Discussion and Conclusions 5.1

5.2

General Discussion 5.1.1 Phylogeny of Scolopacidae in relation to their habitat preferences

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5.1.2 Importance of staging area

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Conclusions

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5.2.1 Recommendations

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REFERENCES

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APPENDICES

150

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LIST OF FIGURES Figure 1.1

The colored lines indicated migratory flyways of shorebirds throughout continent in the world (adapted from: Bamford et al., 2008). Multiple colored lines represent; purple=Eastern Pacific America, green with dotted=Central America, blue=Western Atlantic America, pink=Northern and Eastern Atlantic (Eurasia to Africa), yellow=Europe to Western Asia to Western Africa, green= Central Asia to Eastern/Southern Africa, thin blue= Central Asian, light green=Eastern Asia to Australasia and Central Pacific.

2

Figure 1.2

Southeast Asian countries within EAAF (adapted from: Bamford et al., 2008). The red line represents East Asia to Australasia flyway of migratory shorebirds.

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Figure 2.1

Map of sampling sites in Sarawak. The blue lines represent riverbanks and red lines indicate main road in Sarawak. My sampling sites were marked with red dots and black dots represent the capital of district in Sarawak.

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Figure 3.1

The dendrogram showed two major regional groupings of shorebirds in Southeast Asian region by Jaccard’s coefficient. CAB=Cambodia; BUM=Burma; THA=Thailand; LAO=Laos; VIE=Vietnam; PM=Peninsular Malaysia; SIN=Singapore; PHI=Philippine; BOR=Borneo; JAV=Java; BAL=Bali; SUM=Sumatra.

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Figure 3.2

General clustering of Scolopacidae species in countries of Southeast Asia with Jaccard’s coefficient. CAB=Cambodia; BUM=Burma; THA=Thailand; LAO=Laos; VIE=Vietnam; PM=Peninsular Malaysia; SIN=Singapore; PHI=Philippine; BOR=Borneo; JAV=Java; BAL=Bali; SUM=Sumatra.

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Figure 3.3

Three major migration corridors within the EAAF. The three pathways are marked with blue yellow and green color.

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Figure 3.4

Two major migration corridors within the EAAF. The two pathways are marked with blue and yellow color.

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Figure 3.5

Dendrogram showing two major habitat classifications indicated by the dotted line with the corresponding Scolopacidae species occupying each respective habitat (produced by UPGMA method with Jaccard’s coefficient).

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Figure 3.6

Map showing regional partitioning of shorebird’s distribution between countries on mainland and islands. The solid line indicates the clustered of major group which is the mainland

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Figure 3.7

region and the insular region. The lateral line and dotted on the map represent clustering of countries in the shorebirds distribution dendrogram previously. Map showing regional partitioning distribution pattern of Scolopacidae. Based on the wader’s distribution dendrogram earlier, the vertical line indicates the first group (Laos and Cambodia). The dotted indicates group 2A (Burma) while the lateral line represent group 2B (Peninsular Malaysia/Singapore, Java/Bali, Sumatra, Vietnam, Thailand, Philippine and Borneo).

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Figure 3.8

A contour map showing the major river system in mainland region of Southeast Asia.

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Figure 3.9

A contour map showing elevational gradients of (a) the Southeast Asia mainland and (b) Borneo island (source: http://naturalhistoryonthenet.com and http://en.wikipedia.orglabel).

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Figure 3.10

Routes of southwards migration (indicated by coloured lines) of Scolopacidae within EAAF.

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Figure 4.1

The image of DNA extraction bands run on 1% agarose gel with 1x TAE buffer for about 40 minutes under the voltage of 100 V. Lane1 indicate 1kb DNA ladder. Lane2 until Lane 13 are the DNA extraction products of Scolopacidae species.

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Figure 4.2

The image of PCR product DNA bands run on 1% agarose gel with 1x TAE buffer for about 40 minutes under the voltage of 90 V. Lane1 indicate 100bp DNA ladder, Lane2 until Lane 9 are the PCR products of approximately 600bp.

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Figure 4.3

The image of purification PCR product DNA bands run on 1% agarose gel with 1x TAE buffer for about 40 minutes under the voltage of 90 V. Lane 1 is 100bp DNA ladder. Lane2 until Lane 8 are the purification products of Scolopacidae species.

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Figure 4.4

Pie-chart showing means percentage of nucleotide composition on partial COI gene.

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Figure 4.5

Pie-chart showing average percentages of nucleotide composition of RAG1 gene.

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Figure 4.6

Pie-chart showing average percentage of nucleotide composition of combined gene partial COI and RAG1 gene.

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Figure 4.7

Saturation plot of partial COI gene sequences [total number of substitutions (both in transition, Xs and in transversion, Δv)

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against total amount of uncorrected sequence divergence] calculated using DAMBE 5.1.1 (Xia et al. 2003). Figure 4.8

Saturation plot of RAG1 gene sequences [total number of substitutions (both in transition, Xs and in transversion, Δv) against total amount of uncorrected sequence divergence] calculated using DAMBE 5.1.1 (Xia et al. 2003)

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Figure 4.9

Neighbour-joining (NJ) tree analysis of Scolopacidae based on COI gene. The tree was constructed using PAUP with Kimura-2parameter distance by 1000 replication. Bootstrap values on nodes are indicated in percentages. Bootstrap values are indicated above branch (>50% only).

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Figure 4.10

Maximum Parsimony tree of Scolopacidae based on sequences of COI mtDNA (Tree length = 629, Consistency index (CI) = 0.4754, Retention index (RI) = 0.8437). Values on the branches represent MP bootstrap estimates, based on 1000 replicates. Bootstrap values are indicated above branch (>50% only).

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Figure 4.11

Rooted ML tree (-Ln likelihood = 3371.67724) generated based on nucleotide data set of COI with GTR+G+I model. Values on the branches represent ML bootstrap estimates, based on 100 replicates. Bootstrap values are indicated above branch (>50% only)

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Figure 4.12

Bayesian tree of Scolopacidae using partial COI gene based on GTR+G+I model for the last 250,000 trees after 3 million generations. Values on the branches represent Bayesian Posterior Probabilities (BPP). All nodes received a posterior probability of 1.00 unless otherwise labeled.

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Figure 4.13

Neighbour-joining (NJ) tree analysis of Scolopacidae based on RAG1 gene. The tree was constructed using PAUP with Kimura 2-parameter distance by 1000 replication. Bootstrap values on nodes are indicated in percentages. Bootstrap values are indicated above branch (>50% only).

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Figure 4.14

Maximum Parsimony tree of Scolopacidae based on sequences of RAG1 ncDNA (Tree length = 269, Consistency index (CI) = 0.7918, Retention index (RI) = 0.9167). Values on the branches represent MP bootstrap estimates, based on 1000 replicates. Bootstrap values are indicated above branch (>50% only).

101

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Figure 4.15

Rooted ML tree (-Ln likelihood = 2921.03) generated based on nucleotide data set of RAG1. Values on the branches represent ML bootstrap estimates, based on 100 replicates. Bootstrap values are indicated above branch (>50% only).

102

Figure 4.16

Bayesian tree of Scolopacidae using RAG1 based on GTR+G+I model for the last 250,000 trees after 3 million generations. Values on the branches represent Bayesian posterior probabilities (BPP). All nodes received a posterior probability of 1.00 unless otherwise labeled.

103

Figure 4.17

Neighbour-joining (NJ) tree analysis of Scolopacidae. The tree was constructed using PAUP with Kimura 2-parameter distance by 1000 replication. Bootstrap values on nodes are indicated in percentages. Bootstrap values are indicated above branch (>50% only).

106

Figure 4.18

Maximum Parsimony tree of Scolopacidae based on sequences of combined gene partial COI mtDNA and RAG1 ncDNA (Tree length = 848, Consistency index (CI) = 0.5837, Retention index (RI) = 0.8494). Values on the branches represent MP bootstrap estimates, based on 1000 replicates. Bootstrap values are indicated above branch (>50% only).

107

Figure 4.19

Rooted ML tree (-Ln likelihood = 6319.35090) generated based on nucleotide data set of combined gene partial COI and RAG1. Values on the branches represent ML bootstrap estimates, based on 100 replicates. Bootstrap values are indicated above branch (>50% only).

108

Figure 4.20

Bayesian tree of Scolopacidae for combined gene based on GTR+G+I model for the last 250,000 trees after 3 million generations. Values on the branches represent Bayesian posterior probabilities (BPP). All nodes received a posterior probability of 1.00 unless otherwise labeled.

109

Figure 4.21

A simplified chronogram indicating genera specific-nodes only. Divergence times were derived from pairwise matrix of NJ tree. Geological time scale was adapted from Geological Society of America (2012).

110

Figure 5.1

A diagram indicating genetic groupings (subfamilies) of Scolopacidae with their respective habitat preferences.

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LIST OF TABLES Table 1.1

Scolopacidae species occurrences in Borneo ( indicated species present)

11

Table 2.1

List of sampling sites with sampling dates and GPS coordinates.

18

Table 3.1

Selected bird’s field guides and published reports used for data collection

41

Table 3.2

Specific habitat classification for inland and coastal areas

42

Table 3.3

Expression of Binary instances i and j

43

Table 3.4

Binary coefficients and their respective formulas

43

Table 3.5

List of species utilizing two migration routes

49

Table 4.1

The sequence for COI (Palumbi et al., 1991) and RAG 1 gene (Groth and Barrowclough, 1999)

76

Table 4.2

The PCR reaction mixture

76

Table 4.3

PCR configuration for COI gene

77

Table 4.4

PCR configuration for RAG1 gene

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Table 4.5

Nucleotide composition based on partial mtDNA COI gene sequences used in this study (codon position 1, 2, 3 and total)

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Table 4.6

Nucleotide composition based on partial nucDNA RAG1 gene sequences used in this study (codon position 1, 2, 3 and total)

84

Table 4.7

Nucleotide composition based on charpartition sequences used in this study (codon position 1, 2, 3 and total)

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Table 4.8

Average pairwise genetic distance matrix between species in percentage (%) for COI gene calculated using Kimura 2-parameter (Kimura,1980)

90

Table 4.9

Average pairwise genetic distance matrix between species in percentage (%) for RAG1 gene calculated using Kimura 2parameter (Kimura,1980)

91

Table 4.10

Average pairwise genetic distance matrix between species in percentage (%) for both COI and RAG1 gene calculated using Kimura 2-parameter (Kimura,1980)

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ABBREVIATIONS

°C

degree Celcius (temperature)

µl

microliter

µM

micromolar

asl

above sea level

AWC

Asian Waterbirds Census

bp

base pair

BPP

Bayesian Posterior Probabilities

COI

Cytochrome Oxidase I

CTAB

cetyltrimethylammonium bromide

DNA

deoxyribonucleic acid

dNTP

deoxyribonucleotide triphosphate

EAAF

Eurasian Asian Australian flyway

EDTA

ethelene diamine tetra acetic acid

EtBr

ethidium bromide

g

gram

Km

kilometer

M

molar

MEGA

Molecular Evolutionary Genetics Analysis

MgCl2

magnesium chloride

mm

millimeter

ml

milliliter

ML

maximum-likelihood xviii

MP

maximum parsimony

mM

millimolar

MP

maximum parsimony

mtDNA

mitochondrial deoxyribonucleic acid

mya

million years ago

MZU

Museum of Zoology UNIMAS

NaCl

natrium chloride

NJ

neighbour-joining

nucDNA

nuclear deoxyribonucleic acid

PAUP

Phylogenetic Analysis using Parsimony

PCR

polymerase chain reaction

RAG1

Recombinant Activating Gene 1

SDS

sodium dodecyl sulphate

TAE

tris-acetate-ethylenediaminetetraacetic

TE

tris EDTA

UV

ultraviolet

V

Volt

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CHAPTER ONE General Introduction

1.1

Migration of shorebirds

Shorebirds known as “waders” migrate long distance across the continents which enables them to breed in wetlands at high (Arctic) latitudes of northern hemisphere during northern summer and disperse widely to southern hemisphere for the rest of the year. Waders utilized flyways while migrating from its breeding ground to non-breeding ground or vice versa. With exception of waders, very few passerine species migrate from the northern hemisphere all the way to Australia. They include the yellow wagtail (Motacilla flava), fork-tailed swift (Apus pacificus) and oriental cuckoo (Cuculus optatus) (Dingle, 2008).

Flyways described a geographic region that supports a group of migratory shorebirds travel from northern hemisphere to southern hemisphere throughout their annual cycle. There are eight major flyways throughout the world (Figure 1.1) which include 1) eastern Pacific America, 2) central America 3) western Atlantic America 4) northern and eastern Atlantic (Eurasia to Africa), 5) Europe to western Asia to western Africa, 6) central Asia to eastern/southern Africa, 7) central Asian, 8) eastern Asia to Australasia, and central Pacific (Bamford et al., 2008).

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Figure 1.1: The colored lines indicate migratory flyways of shorebirds throughout major continents (adapted from: Bamford et al., 2008). Multiple colored lines represent; purple=Eastern Pacific America, green with dotted=Central America, blue=Western Atlantic America, pink=Northern and Eastern Atlantic (Eurasia to Africa), yellow=Europe to Western Asia to Western Africa, green= Central Asia to Eastern/Southern Africa, thin blue=Central Asian, light green=Eastern Asia to Australasia and Central Pacific.

In early April, autumn season, shorebirds migrate to its breeding ground in the northern hemisphere (Morris, 1996). During northern summer, countries near North Pole such as Russia and Japan are directly exposed to sun rays. This phenomenon creates summer season in June and July at northern hemisphere. At the same time, South Pole experienced winter which received very low angle of sun ray. During summer in the Arctic region, daylight is long which is almost 24 hours. The temperature is warm enough to provide favorable habitat for shorebirds to breed and supplied enough food for them and their chicks to survive. Most of shorebirds could not survive the freezing weather when Arctic region experienced spring and winter, therefore they migrate to South Pole for other months of the year (CWBO, 2009). Both plovers and sandpipers are shorebirds but they differ in their geographic distributions. Plovers habitually originate from temperate and tropical regions, whereas sandpipers come from more distantly northern part of hemisphere (Colwell, 2010). 2

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Distribution of shorebirds of Southeast Asia

Macrogeogrpahic distrubtion patterns of avifauna in Southeast Asia region is well described within the east and west of Wallace‟s line (Rahman, 2007). The studied focused on resident and waterbirds revealed that the distribution pattern of avifaunal support the predicted glacial biographic model. Macro refers to large size, while geography refers to the physical features of the earth and its atmosphere including the distribution of populations and resources and political and economical activities (APA, 2003). Hence, macrogeography distribution is defined as an approach to examine a large scale patterns in spatial distribution of shorebirds as well as waders in Southeast Asia region.

Shorebirds are the world‟s most amazing

migrants, making round trip journeys from the high arctic to southern South America, Africa, Asia, Australia and widely scattered islands of the Pacific, often to the same sites year after year. Southeast Asian countries are within East Asia Australasian Flyway (EAAF) (Figure 1.2), and some other countries also included like parts of Alaska, Russia, Mongolia, Korea, Japan, China, Philippines, Papua New Guinea, Australia and New Zealand. Approximately 60 species of shorebirds migrate using this flyway (Colwell, 2010).

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Figure 1.2: Southeast Asian countries within EAAF (adapted from: Bamford et al., 2008). The red line represents East Asia to Australasia flyway of migratory shorebirds. Shorebirds‟ breeding grounds using EAAF usually overlaps with other birds that utilized other flyways generally comprised of Arctic and sub-Arctic Russia and Alaska, areas within China, the Korean Peninsula and Japan. They spend about two months within their breeding ground and subsequently migrate to the southern pole to avoid freezing in winter season.

Waders‟ migration towards North Pole is frequently observed while in the state of urgency while migration towards South Pole is a bit relaxed (Howes and Bakewell, 1989). Waders regularly spend about two months on both journeys and often used the same route every time.

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