Litoria Aurea)

Phylogeography, Population History and Conservation Genetics of the Endangered Green and Golden Bell Frog (Litoria aurea)

Emma Louise Burns

Ph.D.

School of Biological, Earth and Environmental Sciences

University of New South Wales

December 2004

For Ben

…without you this would never have been possible. I hereby declare that this submission is my own work and to the best of my knowledge it contains no material previously published or written by an other person, nor material which to a substantial extend has been accepted for the award of any other degree or diploma at UNSW or any other education institution, except where due acknowledgement is made in this thesis. Any contribution made to the research by other, with whom I have worked at UNSW or elsewhere, is explicitly acknowledged in the thesis.

I also declare that the intellectual content of this thesis is the product of my own work, except to the extent that assistance from others in the project’s design and conception or in style, presentation and linguistic expression is acknowledged.

Signed:

Emma Burns

Preface

This thesis consists of four stand-alone papers (chapters two to five) that have been published, submitted, or prepared for submission, to international journals of high standing. The publication details of each paper and the contribution of co-authors are detailed at the end of each chapter. To prevent unnecessary duplication a single reference list is provided at the end of the thesis.

Chapter one, a general introductory chapter, describes the study species (Litoria aurea) and provides background information on conservation genetics. Chapter two provides a description of the isolation and characterisation of microsatellite markers, which are employed in chapter three. Chapter three provides a detailed examination of the genetic variability and population structure in L. aurea using microsatellite markers. Chapter four, examines the concept of a ‘bell frog species group’ using mitochondrial DNA and tests for the sister taxon to L. aurea, to use as an out group taxon for analyses in the proceeding chapter. Chapter five examines the intraspecific phylogeography of L. aurea using mitchonchondrial DNA. The concluding chapter, chapter six, provides a synthesis of the preceding chapters and a discussion of the conservation management of L. aurea based on the findings of this study.

Acknowledgements

This has been a long journey and there are numerous people that I need to acknowledge and thank. Firstly, I would like to thank my husband Ben Noyen whose constant support and encouragement has made getting to the finish line a reality. Ben, for all the times I contemplated giving up when the obstacles just seemed too big, thank you for talking me out of it!

To my family, Mum, Dad, Fiona, Ashley and Steve, thank you for all your support and for not giving up on me. You never once encouraged me to walk away and that was what I needed. Mum, thanks for the company, fun and great frog catching on the Victorian field trip. You are wonderful.

To the Noyen family, Jo, Di, Summa and Jason, thank you for your support. I know at times you found it difficult to understand why I needed to finish this when it all seemed too hard but thank you for understanding. Summa, thanks for your help formatting and Jas thanks for letting me use your wiz bang computer in the dying days, it made life that little bit easier.

To my old boss at AMBS, Jayne Tipping and my current supervisor Kerry Doyle at

MSMR, a huge thank you to you both. Working full time for the last two and a half years whilst trying to complete my thesis has been made easier with your support.

Now, moving on to the many people who have helped make this project happen. Starting at the beginning, to my initial supervisor Bronwyn Houlden, thank you for inspiring me to do

research. Your commitment to me during this journey has made this all possible. Though I thought my world was slipping away when you first left UNSW, it did not happen. Thank you for continuing to read manuscripts and provide advice after you left.

Rob Brooks, thank you for ‘adopting me’ and taking on my supervision. You have been fantastic and thank you for always encouraging me to “just get it done”. Your faith in me helped make this a reality, and your support made sure I did not “slip through the cracks”.

Now to my two saving ‘knights’, Mark Eldridge and Darren Crayn, without your help mid way through the game, the end would of never been achievable. Thank you for helping me complete my thesis and manuscripts and Darren without you I am sure PAUP and I would never have gotten along!

A special thank you to Bill Sherwin whose door was always open to me and Jo Zuccarello who is a complete wiz in the lab and was always ready to help and listen. A big thanks also to Hal Cogger for providing the title page photo and for all the talks and support you gave me during our habitat inspections etc at Sydney Olympic Park whilst I worked at AMBS.

A special mention now for my fellow students who made this journey so fun; Meg, Ange,

Shaun, Michael, Deirdre and Megan, you guys are great. I have not only achieved a degree

(and hopefully a career) through this process but I have also made life long friends.

Also a big, big thank you to all those who helped with field work and sample collection. A project of this magnitude could not succeed without the help of numerous people in the field and there are heaps of people to thank. I would like to start with a very special thank

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you to Ross Wellington and Arthur White, both of you made yourselves readily available to me and shared your knowledge of the green and golden bell frog which enabled me to plan successful field trips, well mostly, but it is an endangered species so I shan’t complain. I would also like to thank Graham Pyke, Garry Daly, Andrew Hamer, Simon Lane, Mike

Mahony, Rod Pietsch, Graeme Gillespie, John Clulow, Scott Filmer, Rebecca Rudd,

Candice Webb, Dion Hobcroft, Kerry Darcovich, Glenn Muir and many field volunteers and property owners for aid in the collection of tissue samples. All of you helped make this project happen, thank you.

Thank you, Steve Donnellan and Terry Bertozzi of the South Australian Museum and Denis

O’Meally and Don Colgan of the Australian Museum for providing tissue from their collections for Chapter four. Steve Donnellan was also generous enough to review an earlier draft of chapter four and provide helpful comments, thank you.

A special thank you to Alaxandra Schulmeister and Gianfrancesco Ferrari for their volunteer work in the laboratory. Francesco, it was a joy spending time with you and I dearly hope we get to meet again. Thank you Eli Geffen for advice with some statistical analysis in Chapter three and Eric Harley for supplying the program AGARst.

Finally, on a more official note, this project could never have happened without financial support from an Australian Postgraduate Research Award and the following sources:

University of New South Wales-URSP, ARC small grant, Zoological Parks Board of New

South Wales, Roads and Traffic Authority, National Parks and Wildlife Service, Mary

Ethel Read Research Grant, the Joyce W. Vickery Scientific Research Fund, and the W.V.

Scott Foundation. Also, this study was conducted under University of New South Wales

Animal Care and Ethics Committee approval (ACEC 99/39), Zoological Parks Board of

NSW approval (ACEC 3a/06/99), New South Wales National Parks and Wildlife Service scientific permits (A2608, B2022), State Forests of New South Wales special purpose permit (05449) and Victorian Department of Natural Resources and Environment scientific permit (10000851).

Table of Contents

PREFACE...... I

ACKNOWLEDGEMENTS ...... II

LIST OF FIGURES...... X

LIST OF TABLES...... XIII

THESIS ABSTRACT...... XV

CHAPTER ONE: INTRODUCTION AND BACKGROUND INFORMATION...... 1

STUDY SPECIES ...... 1 Species description ...... 1 Species history and conservation status...... 4

CONSERVATION GENETICS ...... 7 Previous molecular studies of frogs ...... 9

THESIS OBJECTIVES...... 11

CHAPTER TWO: ISOLATION AND CHARACTERISATION OF MICROSATELLITE LOCI IN THE GREEN AND GOLDEN BELL FROG (LITORIA AUREA)...... 12

ABSTRACT...... 12

INTRODUCTION...... 13

MATERIALS AND METHODS...... 13

RESULTS AND DISCUSSION ...... 16

PUBLICATION INFORMATION ...... 18

CHAPTER THREE: MICROSATELLITE VARIATION AND POPULATION STRUCTURE IN A DECLINING AUSTRALIAN HYLID (LITORIA AUREA)...... 19

ABSTRACT...... 19

INTRODUCTION...... 20

MATERIALS AND METHODS...... 23 Sampling localities and tissue collection ...... 23 Sample extraction and microsatellite typing ...... 25

Data analysis...... 26

RESULTS...... 28 Genetic diversity...... 28 Population bottlenecks ...... 31 Population differentiation ...... 32 Patterns in genetic differentiation...... 35 Assignment test ...... 37

DISCUSSION...... 39 Patterns of genetic diversity ...... 39 Population bottlenecks ...... 40 Microsatellite surveys of amphibian population structure...... 42 Patterns of population differentiation in L. aurea ...... 43 Conservation implications and management recommendations...... 45

PUBLICATION INFORMATION ...... 46

CHAPTER 3 APPENDIX: ALLELE FREQUENCY TABLE...... 47

CHAPTER FOUR: PHYLOGENETICS AND EVOLUTION OF BELL FROGS (LITORIA AUREA SPECIES-GROUP, ANURA: HYLIDAE) BASED ON MITOCHONDRIAL ND4 SEQUENCES ...... 50

ABSTRACT...... 50

INTRODUCTION...... 51

MATERIALS AND METHODS...... 54 Taxon sampling ...... 54 Mitochondrial DNA sequencing...... 57 Phylogenetic analyses ...... 58

RESULTS...... 59 Sequence variation ...... 60 Phylogenetic analyses ...... 65

DISCUSSION...... 69 L. aurea species-group ...... 69 L. aurea - L. raniformis clade ...... 70 L. cyclorhyncha - L. moorei clade...... 71

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Divergence of south-eastern and south-western species...... 71 Conclusions ...... 73

PUBLICATION INFORMATION ...... 74

CHAPTER FIVE: LOW PHYLOGEOGRAPHIC STRUCTURE IN A WIDELY SPREAD ENDANGERED AUSTRALIAN FROG LITORIA AUREA (ANURA: HYLIDAE) ...... 75

ABSTRACT...... 75

INTRODUCTION...... 76

MATERIALS AND METHODS...... 81 Tissue sampling and outgroup choice ...... 81 Mitochondrial DNA extraction, amplification and sequencing ...... 81 Sequence alignment and haplotype designation ...... 83 Phylogenetic analyses ...... 84 Population analyses ...... 85

RESULTS...... 87 COI phylogeny...... 87 ND4 phylogeny ...... 88 Combined data phylogeny ...... 89 Minimum spanning network and demographic history...... 92 Genetic diversity and population structure ...... 95

DISCUSSION...... 100 L. aurea phylogeography ...... 100 Recent evolutionary history of L. aurea ...... 102 Population structure and variability ...... 105 Conservation Implications ...... 106

PUBLICATION INFORMATION ...... 108

CHAPTER 5 APPENDIX: GEOGRAPHIC DISTRIBUTION OF COI AND ND4 HAPLOTYPES .... 109

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CHAPTER SIX: CLOSING REMARKS - A CONSERVATION MANAGEMENT PERSPECTIVE ...... 110

INTRODUCTION...... 110

SUMMARY OF FINDINGS ...... 111

CONSERVATION MANAGEMENT ...... 114 Conservation units...... 114 Active management: endemic populations ...... 115 Captive populations...... 117

FUTURE DIRECTIONS ...... 118

CLOSING REMARKS ...... 119

REFERENCES ...... 120

List of Figures

Figure 1.1: Map of Australia showing the approximate geographic distribution of ‘bell frogs’. This map was modified from NSW National Parks and Wildlife (NPWS) draft recovery plan (2002). For further detail of the current distribution of L. aurea see Figure 1.2...... 2

Figure 1.2: Map of the south-eastern coastline of Australia detailing current NPWS records for L. aurea. The black dots are approximately proportional in area to the estimated number of individuals at each site. The colored regions relate to proposed management regions suggested in the species draft recovery plan (NPWS 2002), this figure was taken from that plan. Historically L. aurea was distributed relatively continuously throughout these regions (see text and references within for further detail)...... 5

Figure 3.1 Map of the south eastern coastline of Australia. The map details the location of 21 green and golden bell frog populations sampled for genetic analysis in this study. The location of the sampled sites ranged from the far north coast of New South Wales (NSW) to east Gippsland in Victoria (Vic). Due to the large scale of the study area a single point represents sites sampled within close geographic proximity...... 24

Figure 4.1: Map of Australia showing the approximate geographic distributions of extant species of the Litoria aurea species-group. Also shown is the hybrid zone sampling area of L. aurea and L. raniformis at Orbost in East Gippsland. The distributions shown for L. raniformis and L. aurea are historical and not current, both these species have experienced relatively recent contractions of their former range. This map was modified from NSW National Parks and Wildlife (2002)...... 56

Figure 4.2: Plot of uncorrected p-distance and ML (TrN+I+G) distance for first (a), second (b) and third (c) position sites across all taxa including outgroups. Line represents the slope x = y for fig. (a) and (b)...... 64

Figure 4.3: Strict consensus tree of most equally parsimonious trees of length 382 steps; bootstrap values (1000 pseudoreplicates) are shown if >50%. Bars designate phylogenetic groups discussed in text...... 67

Figure 4.4: ML tree resulting from estimation using TrN+I+G model of evolution; bootstrap values (500 pseudoreplicates) shown if > 50%. Bars designate phylogenetic groups discussed in text...... 68

Figure 5.1: Map of the south eastern coastline of Australia. The map details the location of 26 green and golden bell frog populations sampled for this study. The location of the sampled sites ranged from the far north coast of New South Wales (NSW) to east Gippsland in Victoria (Vic). Due to the large scale of the study area a single point represents some sites sampled within close geographic proximity. The corresponding geographical regions for these locations are given in Table 5.1. Note Broughton Island (BI) is situated approximately 3 km off the coast...... 79

Figure 5.2: Phylogenetic relationships among L. aurea mtDNA haplotypes based on combined (COI and ND4) sequence data. (A) Neighbour-joining (NJ) tree based on the TrN+I+G (Tamura & Nei 1993) model of evolution with bootstrap (1000 pseudoreplicates) values >50% shown above the branches. This tree was re-drawn without the outgroup samples to better represent ingroup topology, the distance from outgroup samples to the first node was 0.535. NJ analysis excluding outgroup samples was also performed (under the HKY+I+G model (Hasegawa et al. 1985) and bootstrap values >50% are shown under the branches. (B) MP bootstrap (1000 pseudoreplicates) consensus tree with support values >50% shown above the branch in bold. MP analysis revealed 1078 most parsimonious trees, 61 steps, CI = 0.556, RI = 0.833. As with the NJ tree values below a branch indicate bootstrap (1000 pseudoreplicates) support (>50%) for analysis excluding the outgroup samples (which found 1076 trees, 160 steps, CI = 0.784, RI = 0.864). The ML tree for the data including outgroup samples (using the TrN+I+G model) was similar in topology to the above trees with bootstrap support >50% (500 pseudoreplicates) found for three clades only: Hap19, Hap 23, Hap 26 (58%); Hap 24, Hap 25 (59%); and Hap 16, Hap 45 (57%) (data not shown)...... 93

Figure 5.3: Minimum-spanning network depicting relationships among L. aurea haplotypes based on combined sequence data. The area of the circle is proportional to the haplotype frequency, and the length of the connecting line is proportional to the genetic distance .3. EHWZHHQKDSORW\SHV'DVKHGOLQHVLQGLFDWH alternative topologies. Shadings indicate what region each haplotype was detected in and if a haplotype was detected in more than one region the area of shading is proportional to its relative abundance. Analysis using the raw number of nucleotide differences among haplotypes produced a concordant result...... 94

Figure 5.4:,VRODWLRQE\GLVWDQFHSORWVRI-ST /(1--ST ) plotted against the natural log of geographical distance (km) for all samples pooled into regions (A) and sampled sites with greater than 5 samples (B). In both analyses BI was excluded because of its

LVRODWLRQIURPJHQHIORZDQGWKH-ST matrix was formulated based on the K23 . 0.016) substitution model. The solid line represents the best-fit linear regression based on all points. For both analyses Mantel’s test was significant (regions: P < 0.05; all sampled sites: P < 0.001)...... 99

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List of Tables

Table 2.1: Characteristics of microsatellite loci in Litoria aurea...... 17

Table 3.1 Geographical coordinates of sampled locations in Australian Map Grid units (zone 56 Easting and Northing). The number of individuals sampled (n) per site is also detailed...... 25

Table 3.2 Allelic diversity of 21 sampled green and golden bell frog sites. Allelic diversity is given as a direct count (DC) of the average number of alleles per locus and as corrected bootstrap estimates to account for sample size varition. The total number of alleles within sites for each locus is also detailed with the number of private alleles at each indicated in brackets...... 29

Table 3.3 Heterozygosity of 21 sampled green and golden bell frog sites. Heterozygosity

is given as observed (HO) and expected (HE). Weir and Cockerham (1984) Fis values for each locus are detailed and sites that showed a significant deviation (Bonferroni correction P < 0.0125) from HWE over all loci are indicated by ‘Ex’ for an excess of homozygotes, ‘Def’ for a deficiency of homozygotes or ‘Eq’ if in equilibrium...... 30

Table 3.4 Estimates of FST for each locus and averaged over all loci. Also shown are Fishers’s Exact Probabilities of population differentiation over all populations...... 32

Table 3.5 Estimates of pair-wise FST (below diagonal) and Nei’s unbiased genetic distance

(above diagonal). Boxed areas indicate non-significant pair-wise FST comparisons. .. 34

Table 3.6 Assignment test results for the Bayesian method (see text). Values indicate the number of individuals that were assigned to each location based on their genotype. Individuals were not assigned to a location if their assignment probability was less than 0.01. Boxed areas indicate sites within geographic proximity...... 38

Table 3.7 Comparative measures of FST from published studies of amphibian population structure using microsatellite markers. Estimates of geographical distance were taken from Newman & Squire (2001) or estimated from maps given in the relevant publication...... 42

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Table 4.1: Samples analysed for mtDNA sequence variation...... 55

Table 4.2. Variable sites among ND4 haplotypes (5’ – 3’) for Litoria species ...... 61

Table 4.3. Matrix (bottom) of uncorrected p-distances between taxa and matrix (above) of corresponding S.E. estimates (bootstrap method 500 pseudoreplicates)...... 63

Table 5.3: Geographical distribution of 51 L. aurea haplotypes (combined data) summarised across regions...... 91

Table 5.4: Diversity measures for sample locations and regions of L. aurea using combined sequence data and K2P . VXEVWLWXWLRQPRGHO1XPEHUVLQ parentheses give standard deviations...... 96

Table 5.5: Genetic differentiation between L. aurea regions (sampled sites pooled).

Pairwise FST and -ST values are shown (lower left hand matrix based on haplotype IUHTXHQFLHVXSSHUULJKWKDQGPDWUL[DFFRXQWVIRUPROHFXODUGLVWDQFHXVLQJ.3. 0.016). Non-significance comparisons are shown in bold. Significance levels were evaluated by 10,000 permutations and then adjusted for multiple tests using Bonferroni Correction...... 98

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Thesis Abstract

The green and golden bell frog (Litoria aurea) is an Australian hylid, which was once common with a relatively continuous distribution. Historically, this distribution extended from northern New South Wales (NSW), as far as Ballina, to East Gippsland in Victoria; with inland populations as far west as Bathurst and Tumut. Today the species is reported to have disappeared from 80% of its former range and remaining populations are mostly fragmented and typically restricted to the coastline, extending from Yuraygir National Park (northern NSW) to East Gippsland. In this thesis, I report a comprehensive study designed to identify the phylogeographic and conservation genetic parameters of L. aurea. In doing so, I also investigate evolutionary relationships within the ‘bell frog’ species group.

In this study, microsatellite and mitochondrial DNA (mtDNA) markers are employed. The development of species-specific microsatellite markers and the collection of samples was a substantial component of the study. These markers and samples should prove useful for future studies of L. aurea and perhaps more generally the ‘bell frogs’.

Initially, a large-scale assessment of genetic structure and diversity in L. aurea using microsatellite markers was undertaken. Twenty-one locations were sampled from throughout the species range covering 1000 kilometres of the east coast of Australia. Levels of allelic diversity and heterozygosity were high (uncorrected mean alleles/locus and HE: 4.8-8.8 and 0.43-0.8 respectively) compared to other amphibian species and significant differences among sampled sites were recorded. Despite recent population declines, no sites displayed a genetic signature indicative of a population bottleneck.

Significant genetic structuring (overall FST = 0.172) was detected throughout the species range, but was relatively low compared to previous amphibian studies that used microsatellites. In addition, some areas sampled within continuous habitat showed evidence of weak genetic structuring (data subset FST = 0.034).

Next, relationships among extant bell frogs (Litoria aurea species-group) were investigated, using mitochondrial ND4 nucleotide sequence data. Analyses supported a

clade comprised of the temperate members of the species-group, L. aurea, L. cyclorhyncha, L. moorei, and L. raniformis but failed to support the inclusion of the tropical bell frog L. dahlii in this group. Relationships among the four members of the bell frog clade correlated with geographical distribution: the south-western Australian bell frogs (L. cyclorhyncha, L. moorei) and the south-eastern Australian bell frogs (L. aurea, L. raniformis) were reciprocally monophyletic. Results also indicated that divergence of these two lineages occurred during the late Miocene, which was consistent with results of previous studies and with more general assertions that much of the major differentiation and radiation of the Australian biota predated the Quaternary.

Following this, intraspecific phylogeography of L. aurea using two mitochondrial genes COI and ND4 was investigated. I examined extant populations from throughout the species’ range, sequencing 263 individuals from twenty-six locations. Recent evolutionary history, as well as the current population structure of L. aurea, was inferred from the resulting pattern of genetic variation amongst haplotypes, in conjunction with demographic and population analyses. Results indicated that there were no phylogeographic divisions within L. aurea, despite a general consensus that amphibians are highly structured.

However, I did still detect significant structure amongst extant populations (FST = 0.385). Overall, patterns of haplotype relatedness, high haplotypic diversity (mean h = 0.547) relative to low nucleotide diversity (mean = 0.003), and mismatch distribution analysis supported a Pleistocene expansion hypothesis with continued restricted dispersal and gene flow.

Taken together, the results of this thesis indicate that L. aurea is a species with relatively weak population and phylogeographic structure compared to other amphibians. The data provide no support for the existence of distinct evolutionary lineages within L. aurea, implying that there are no historically isolated populations that should be viewed as separate evolutionarily significant units. Nevertheless, remaining populations are still significantly structured but not all populations are genetically distinct.

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Low phylogeographic structure, coupled with evidence for recent gene flow among many sites would permit ‘well managed’ intervention to mediate gene flow amongst currently isolated populations, and I provide some guidelines for the implementation of such conservation strategies. However, there is no evidence to suggest that supplementation through artificial immigration is at this time necessary given current levels of genetic variation within populations.

In the short-term, conservation management in L. aurea should focus on the protection of local populations and habitat to promote population connectivity to ensure processes that maintain adaptive diversity and evolutionary potential are conserved. Preservation of the species’ natural range and the maintenance of dense networks of suitable habitat, in conjunction with maximising local carrying capacity and reproductive output, as well as minimising known threats, are key to securing the long-term persistence of the green and golden bell frog.

xvii Chapter One

Chapter One

Introduction and background information

Study Species

Species description

The green and golden bell frog Litoria aurea (Lesson 1829) is a large and beautifully coloured Australian tree frog (Anura: Hylidae) with striking green and gold dorsal colouration (see title page). Females are larger bodied than males (males 57-69mm, females 65-108mm) and breeding generally occurs from August to April with clutch sizes usually ranging from 2000-6000 eggs; time to metamorphosis is from 2-12 months and newly metamorphosed frogs measure 20-30mm from snout to vent (Barker et al. 1995;

Daly 1995; Pyke & White 2001).

Taxonomically L. aurea has been classified as a member of a species-group commonly known as ‘bell frogs’. This group is currently thought to contain five other species: L. cyclorhyncha (Boulenger, 1882), L. castanea (Steindachner, 1867), L. dahlii (Boulenger,

1896), L. moorei (Copland, 1957), and L. raniformis (Keferstein, 1867). Of these species, three are found in south-eastern Australia: L. aurea, L. castanea and L. raniformis

(Courtice & Grigg 1975; Thomson et al. 1996; Pyke & White 2001) (see Fig. 1.1).

However, L. castanea is now thought to be extinct (R. Wellington pers. comm.).

1 Chapter One

Although a member of the ‘tree frog’ group, L. aurea is primarily a ground dwelling and conspicuous species that can be seen basking in full sun on rocks, reeds and pond banks (E.

Burns pers. obs.). This species has been recorded in a variety of different natural habitat types including coastal flood plains, wetlands, open dry sclerophyll forest and grasslands; and a number of disturbed sites such as industrial plants, sewage plants, brick pits, backyards and purpose built ponds (Pyke & White 2001; E. Burns pers. obs.). Breeding site characteristics vary but generally consist of still, relatively unshaded water bodies low in salinity (Pyke et al. 2002). However, these frogs are opportunistic and have been recorded in nearly every type of fresh water body including: wetlands, marshes, swamps,

2 Chapter One

dams, quarries, ditches, soaks, lakes, sand dune ponds, rock pools, lagoons, ornamental ponds, creeks, rivers, watering troughs, bath tubs and pools (reviewed in Pyke & White

2001; Pyke et al. 2002; E. Burns pers. obs.). Although most research and surveys of L. aurea have focused on water bodies, the species has also been recorded some distance from fresh water in native forest, under stones, logs or vegetation and under debris on flooded river flats (Bell 1982; Cogger 2000 as cited in Hammer 2002).

Little has been published on the species’ population and spatial dynamics, although a metapopulation structure has previously been suggested (Christy 2001). In general, the application of metapopulation dynamics has become increasingly popular to explain amphibian distributions (Alford & Richards 1999; Marsh & Trenham 2000; Hammer

2002). Unlike many frogs, L. aurea is thought to have a high dispersal capability with recorded movement in excess of 10km from known breeding ponds (Pyke & White 2001) but most frequent capture-recapture data is within a 500m radius (Christy 2001; Pyke &

White 2001; Hammer 2002). A PhD study by Hammer (2002) on L. aurea ecology at

Kooragang Island, where a mosaic of permanent and ephemeral water bodies exists, found that water bodies where the species persisted were generally within 50m of a water body where recruitment occurred, and where the density of frogs were higher. Most movement within the population was also restricted to a core area of relatively permanent water bodies, although individuals dispersed into peripheral areas at times of heavy rain.

Hammer (2002) suggests that the species uses both explosive and prolonged breeding as a reproductive strategy and that long-term population viability will be dependant on the conservation of a mosaic of water body types within wetland landscapes.

3 Chapter One

Species history and conservation status

L. aurea like many amphibian species worldwide has undergone dramatic population declines and disappearances over the past 30-40 years (reviewed in Pyke & White 2001).

Through to the early 1980s this species was considered common with a relatively continuous distribution extending from northern NSW, as far as Ballina, to East Gippsland in Victoria; with inland populations as far west as Bathurst and Tumut (Goldingay 1996;

White & Pyke 1996) (Fig. 1.1; Fig 1.2). In addition, the species was introduced (from as early as 1860) to New Zealand, and the Southwest Pacific island countries of New

Caledonia, Vanuatu, and the territory of Wallis and Futuna (reviewed in Pyke & White

2001 and references therein).

Since the 1980s L. aurea has undergone a dramatic decline with disappearances reported from 80% of its native range (Pyke & White 1996 as cited in Pyke et al. 2002). Remaining endemic populations are mostly restricted to the south-eastern coastline of Australia and are generally fragmented with a distribution extending from Yuraygir National Park (northern

NSW) to East Gippsland (Victoria); the two most inland populations are from the Southern

Tablelands near Queanbeyan and the Upper Hunter near Mt. Owen (A. White and R.

Wellington pers. com.; see also Pyke & White 2001). In Victoria, however, the species is still considered common within a restricted range in East Gippsland (Gillespie 1996).

Although there is extensive information relating to the contraction of the species’ distribution, there is no published data on whether extant populations have declined in abundance (Hammer 2002). Currently, L. aurea is listed as ‘Endangered’ under the New

4 Chapter One

South Wales Threatened Species Conservation Act 1995 and as ‘Vulnerable’ under the

Federal Environmental Protection and Biodiversity Conservation Act 1999.

The biology of L. aurea is uncharacteristic of an endangered species. It is highly fecund, with rapid growth and maturity rates, has a high dispersal capability and is also able to breed and persist within disturbed and purposefully built habitat (Pyke & White 2001;

Hammer 2002). These features make it difficult to understand why this species is

5 Chapter One

endangered. However, these features should also make conservation of the species more achievable if we are able to identify and nullify threats.

It is not clear what has caused the loss of populations observed in L. aurea, although several factors have been suggested. The introduced fish species Gambusia holbrooki predates on eggs and tadpoles (Morgan & Buttemer 1996; White & Pyke 1996) and has recently been listed as a ‘key threatening process’ under the NSW Threatened Species

Conservation Act (1995). Other threats include: habitat augmentation and loss through various developments and agricultural practices (White & Pyke 1996); chytridiomycosis, a fatal fungal disease (Berger & Speare 1998; Mahony 1999); pollution (Goldingay 1996) and the use of fertilisers (Hammer 2002).

Similar to amphibian declines globally, threatening processes in L. aurea remain widely debated and poorly understood, and the threats that have been identified do not adequately explain all disappearances. It likely that threatening processes are acting synergistically and may vary under different conditions in different habitat. However, this hypothesis still fails to explain why sympatric pond breeding species (e.g., Limnodynastes peronii, Crinia signifera and Litoria peronii) have not also declined (Mahony 1996).

A fundamental principle in conservation biology is to identify and nullify known threats to species to allow recovery, and further investigation is warranted in threat identification for

L. aurea. Nevertheless, it is still imperative that conservation measures are undertaken while further investigations are made. However, this task is further complicated by the fact that nothing is known about the large-scale population structure of L. aurea, and the current

6 Chapter One

patchy and uneven geographical distribution of remaining populations raises many questions as how to best conserve the species.

Conservation Genetics

Genetic studies have become an integral component of conservation biology, proving instrumental in the formulation of conservation strategies. The strength of molecular genetic studies, though informative in their own right, is that when used in conjunction with other disciplines they can provide a link between ecological, geographical, behavioural and evolutionary information, all of which are needed for effective conservation planning

(Mace et al. 1996). Accordingly, the World Conservation Union (IUCN) recognises the need to conserve biodiversity on three levels: ecosystem diversity, species diversity and genetic diversity (reviewed in Frankham 1995). Genetic diversity occurs on four levels: between species, between populations, within populations and within individuals, and all four levels are important to conserve (Hunter 1996).

At and below the species level, the determination of genetic relationships among populations can be of great importance to the formulation of management practices for species recovery given that it can be used to deduce historical patterns of movement and levels of gene flow among populations (Avise 1992). This information is especially useful for documenting the genetic distinction of populations, identifying populations of higher conservation priority, uncovering dispersal corridors, detecting severe population declines

(i.e. bottlenecks), identifying distinct evolutionary lineages and for identifying individuals

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and/or populations that might provide source material for augmentation/translocation or reintroduction programs (Mace et al. 1996).

Genetic relationships among populations can be determined by estimating the distribution of genetic variation using a number of different techniques (see for review Smith & Wayne

1996). In this study, I employ nuclear markers in the form of microsatellites and mitochondrial genes cytochrome oxidase one (COI) and ND4 (encoding NADH dehydrogenase subunit 4). Used together, mitochondrial and nuclear markers are highly effective tools in the delineation of evolutionary processes, population structure and population dynamics within species. It is also preferable to use both nuclear and mitochondrial data to examine patterns of genetic variation as there can be discordance between genetic patterns detected (reviewed in Monsen & Blouin 2003). Such discordance is usually the result of differences in effective population size and hence evolutionary rates where the sex ratio and mating systems of species is influential (Hoelzer 1997; Monsen &

Blouin 2003). Monsen and Blouin (2003) suggest that discordance may be more pronounced in frog species where populations are expected to be demographically unstable due to fluctuations in population size and cohort survival.

In addition to understanding historical processes and population structure the identification and maintenance of levels of genetic diversity within and between populations is also a major goal in conservation genetics. A loss of genetic diversity through inbreeding and genetic drift is thought to occur when populations undergo declines and/or become small and isolated (Frankham 1995). When this is the case it is generally thought that low levels of genetic diversity could impact on the short-term fitness and consequently the long-term

8 Chapter One

sustainability of species. The potential threats to populations with reduced genetic diversity have been well documented in the literature (see for e.g. Shaffer 1981; Lacy 1987; Lande

1988; Frankham 1995; Frankham & Ralls 1998) and a general consensuses has emerged that those populations with higher levels of variation are better able to respond to environmental fluctuations and as a result have greater evolutionary potential. For this reason, conservation management in recent years has adapted to incorporate potential genetic threats.

In summary, conservation genetics is an area of study that has made important contributions to conservation biology and should be an integral component in the formulation of conservation strategies because genetic studies can give unique insights into ecological, behavioural and evolutionary processes. However, currently there is little information available to managers to implement strategies with consideration to genetic and evolutionary factors in L. aurea.

Previous molecular studies of frogs

In comparison to other vertebrates, a limited number of molecular studies have been conducted in frogs, especially hylids. Furthermore, the bulk of the literature involving hylids, in Australia and elsewhere, usually relates to phylogenetic (e.g. Barber 1999; Austin et al. 2002) or taxonomic (e.g. Donnellan et al. 1999; Moriarity & Cannatella 2004) studies rather than population level investigations.

Further to this, the large majority of population studies in frogs have been conducted in the

Northern Hemisphere and have generally involved Bufo (e.g. Scribner et al. 1994; Rowe et

9 Chapter One

al. 2000b) and Rana species (e.g. Newman & Squire 2001; Monsen & Blouin 2003).

Nevertheless, in Australia a number of allozyme studies (e.g. Driscoll 1998; Colgan 1996) have been conducted in frog species including L. aurea.

Colgan (1996) conducted a small-scale study of L. aurea, where samples (average sample size ranged from 1 to 38.4) were examined from Sydney, the Shoalhaven (see Fig. 1.2) and

New Caledonia. In this study, the allozymes used were not highly variable (42 loci; percent of polymorphic loci per site ranged from 0% to 36.7%), however, significant genetic structuring was detected. Nevertheless, Colgan (1996) reported that genetic distances between samples were at the lower end reported for conspecific frog populations and that migration rates were higher than the average reported in amphibians (see Colgan 1996 and references therein). In this thesis, I build on Colgan’s (1996) work by sampling extensively throughout the species endemic range and by examining genetic relationships using both nuclear DNA and mtDNA markers. In doing so, I have produced the first frog population genetics study in Australian to use microsatellite markers.

Recently there has been an increase in the number of intraspecific phylogeographic studies of Australian frogs. However, these studies have mainly focused on species from the far north of the south-east coastline, predominately in Queensland (e.g. McGuigan et al. 1998;

James & Moritz 2000). The one exception was a study conducted by Schauble and Moritz

(2001) on Limnodynastes peronii and Lim. tasmaniensis. In this study, the authors report a distinct phylogenetic break positioned somewhere south of the McPherson Range (at the border of NSW and QLD) and north of Sydney. The phylogeographic structure of Lim. peronii is particularly relevant to L. aurea because both species inhabit similar habitats

10 Chapter One

(Pyke et al. 2002) and are frequently recorded at the same water bodies (E. Burns pers. obs.). However, any comparisons made between the phylogeographic study in this thesis and that of Schauble and Moritz (2001) will be limited because Schauble and Moritz (2001) sampled poorly in areas where L. aurea and Lim. peronii are sympatric. To my knowledge, this thesis has produced the first phylogeographic study of a terrestrial vertebrate with relatively continuous sampling from the far north coast of NSW to East Gippsland in

Victoria.

In closing, this thesis constitutes a pioneering study, which examines both population and intraspecific phylogenetic relationships among green and golden bell frogs and more generally examines systematic relationships among the bell frogs.

Thesis Objectives

The primary objective of this study was to make a large-scale assessment of population structure, genetic diversity and phylogeography of L. aurea to aid in the formulation of conservation management strategies. In addition, I examine species’ relationships and the evolutionary history of the bell frogs.

11 Chapter Two

Chapter Two

Isolation and characterisation of microsatellite loci in the green and golden bell frog (Litoria aurea)

Abstract

Four species-specific microsatellite markers were developed to assess genetic diversity and differentiation in green and golden bell frog (Litoria aurea) populations. Here I report on the isolation and characterisation of these markers using captive individuals held at Taronga

Zoo. All loci were polymorphic with between 3 and 6 alleles per locus, and heterozygosity

(HO) values ranged from 0.421 to 0.895. In addition, cross-amplification was also investigated, without success, using nine microsatellite makers isolated from Hyla arborea.

The species-specific microsatellite markers described herein should prove valuable for future studies of genetic structure in wild green and golden bell frog populations.

12 Chapter Two

Introduction

The green and golden bell frog (Litoria aurea) is a large and distinctive tree frog species currently protected under Australian legislation due to dramatic declines and range contractions (reviewed in Pyke & White 2001). Little is known about the population structure of persisting populations, although a small-scale allozyme study suggested low level structuring for an amphibian (Colgan 1996). Microsatellites are increasingly accepted as the marker of choice for studies of conservation genetics (Rowe et al. 2000a) and recently have been used to investigate amphibian population structure (e.g. Newman &

Squire 2001).

Materials and Methods

Microsatellite primer pairs for L. aurea were generated using the enrichment technique of

Gardner et al. (1999). Dinucleotide-repeat sequence (CA)n was cloned and isolated from a wild-caught individual (#390/1, ID TZ1). In brief, genomic DNA (10 µg) was digested with restriction enzyme Sau 3A and ligated to the S62/S61 adaptor (0.9 mmol) (S62: 5’-

GATCCGAAGCTTGGGGTCTCTGGCC-3’; (S61: 5’-

GGCCAGAGACCCCAAGCTTCG-3’) (Gardner et al. 1999). Fragments between 400-

1200 bp were excised from a 1% agarose gel and purified using the freeze-squeeze technique (Tautz & Renz 1983).

Streptavidin MagneSphere® ParaMagnetic beads (100 µL)(Promega) and 200 pmol of the

5’-(CA12)GCTC[Biotin]A-3’oligonucleotide were incubated for 15 min at room

13 Chapter Two

temperature and washed (Gardner et al. 1999). The DNA/adaptor solution (50 µL in 1 x hybridisation solution) (Gardner et al. 1999) was heat denatured at 95 °C for 5 mins in the presence of 20 pmol of S61, cooled to 55 °C, added to the magnetic bead/biotin- oligonucleotide, and incubated for 20 min at 55 °C. The beads were washed to remove unbound DNA fragments (Gardner et al. 1999).

Captured CA-enriched DNA fragments were eluted and purified using a QIAquick column

(QIAGEN GMBH, Hilden, Germany) and used as template in a PCR (Gardner et al. 1999).

The PCR product was purified using a QIAquick column, eluted in 30 µL 10 mM Tris (pH

8.5) and cloned into pGEM T vector (Promega) and used to transform competent E. coli

(JM109)(Promega) according to the manufacturer’s instructions. Colonies were transferred onto Hybond N+ membranes and screened using a synthetic copolymer poly(dA/dC)/poly(dG/dT) probe (Pharmacia), labelled by incorporation of [α32P]-dATP using a ‘nick’ translation kit (Amersham). A total of 65 positive clones were sequenced

(out of 400 screened) using M13 primers to characterise each microsatellite locus. Primers were designed for 26 loci using PRIMER3 (Rozen & Skaletsky 1996). For a number of loci multiple primer combinations were trailed, in total 108 different primers were designed and tested. Only four loci amplified consistently and were polymorphic. Each of these forward primers was synthesised with a fluorochrome label (TET or FAM).

PCR (10 µL) for loci Laurea4-49 and Laurea5M consisted of DNA (50-100 ng), 1.5 pmol of each primer, 1.25 mM MgCl2, 67 mM Tris-HCl, 16.6 mM (NH4)2SO4, 0.45% Triton X-

+ 100, 0.2 mg/mL gelatin, 2 mM dNTPs and 0.5 U Tth (Biotech Australia). The following

14 Chapter Two

MJ Research PTC-100 thermal cycling profile was employed: (i) initial 1 min denaturation at 94 °C; (ii) 35 cycles of denaturation (20 s at 94 °C), annealing (1 min at the selected temperatures in Table 1), and extension (45 s at 72 °C); 3 min at 72 °C. PCR (10 µL) for loci Laurea2A and Laurea4-10 were performed using a FailSafeTM PCR PreMix Selection

Kit (EPICENTRE). Reaction consisted of DNA (50-100 ng), 1.5 pmol of each primer, 0.25

U FailSafe PCR Enzyme Mix and 5µL FailSafe PCR 2X PreMix (100 mM Tris-HCL, 100 mM KCL, 400 µM dNTPs, MgCl2 3-7 mM and FailSafe PCR Enhancer 0-8 X) A and

PreMix C respectively. FailSafe PCR 2X PreMix A and PreMix C differ in MgCl2 and

FailSafe PCR Enhancer concentrations, not disclosed by the manufacturer. The thermal cycling profile employed was: (i) initial 2 min denaturation at 95 °C; (ii) 35 cycles of denaturation (20 s at 93 °C), annealing (1 min at the selected temperatures in Table 1), and extension (45 s at 72 °C); 5 min at 72 °C. The fluorchrome-labelled microsatellites were electrophoresed using 4.25% acrylamide gels on an ABI PRISM™ 377 DNA sequencer.

Banding patterns were analysed using GENESCAN® 3.1 and GENOTYPER® 1.1.1

(Applied Biosystems).

In addition to the development of species-specific markers, cross-amplification was also tested, using primer pairs developed for nine microsatellite loci isolated from Hyla arborea

DNA. These markers were developed and described by Arens & Westende (2000).

Despite extensive optimisation trials none of the nine microsatellites amplified in L. aurea samples.

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Results and Discussion

Using the species-specific loci reported here, genetic diversity was assessed in 19 captive individuals from the Arncliffe population held at Taronga Zoo, Sydney Australia. All loci were polymorphic with between 3 and 6 alleles per locus (Table 2.1). Three of the loci showed an expected dinucleotide allele distribution whilst locus Laurea4-10 exhibited alleles of both odd and even base pair sizes, suggesting that mutation may not be restricted to repeat units (Table 2.1). Observed and expected heterozygosities were estimated using the software package GENEPOP (Raymond & Rousset 1995) version 3.2. Observed heterozygosity (HO) ranged from 0.421 to 0.895 (Table 2.1). Deviations from Hardy-

Weinberg Equilibrium and linkage disequilibrium were tested using Markhov chain approximation (Gou & Thompson 1992) in GENEPOP v 2.0 (Raymond & Rousset 1995).

There was no evidence of linkage disequilibrium, however a heterozygote deficiency (P =

0.006) at locus Laurea4-49 (Table 2.1) may indicate null allele(s).

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Table 2.1: Characteristics of microsatellite loci in Litoria aurea. Allele size No. of H-W Locus name Repeat motif Primer sequence (5’ – 3’) range (bp) Ta °C alleles HO HE Exact P GenBank No.

Laurea4-49 (CA)9GA(CA)19 F-GCTGCCTATGGACTCAAGGA 213-229 55-50TD* 6 0.421 0.734 0.006* AY273937 R-TTCAGCCTTTGGCAGACAG

Laurea5M (CA)4 AA (CA)9 F-TTCACCCAGTGCTTGATTCA 116-136 58 6 0.684 0.759 0.216 AY273938 R-CAGGGTTGTCAGTTGTCCCT

Laurea2A (CA)7AA(CA)13 F-CCATAGCTTTTGAAACAGTGTTTAACCCTTTGAC 196-216 66-62TD** 5 0.895 0.745 0.930 AY273939 R-GATTGCCGCATTTGACCTAGTGGGTTT

Laurea4-10 (CA)6CT(CA)6 F-ACTCCAAATCCAGACCTCCATGGG 212-227 66-62TD** 3 0.474 0.465 0.422 AY273940 R-AGGATCAGGGCGCACTCATCTCTAA

Ta = optimal annealing temperature. TD* = PCR program of decreasing initial annealing temperatures 1°C/cycle for 5 cycles. TD** = PCR program of decreasing annealing temperatures with 10 cycles @ 66°C, 10 cycles @ 64°C, 15 cycles @ 62°C.

HO = observed heterozygosity; HE = expected heterozygosity H-W Exact P = Probability value from Hardy-Weinberg test for heterozygote deficiency, * = significant (P < 0.05)

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Publication Information

This chapter was accepted for publication as a Technical Note in Conservation Genetics and is mostly presented as it appears. However, to help with consistency in this thesis, an abstract and headings have been added (i.e. Introduction, Materials and Methods etc.).

Reference: Burns EL, Ferrari G (2004) Microsatellite loci for the Green and Golden Bell

Frog Litoria aurea. Conservation Genetics, 5, 421-423.

Author contribution: My contribution to this paper included sample collection, laboratory work, data analyses and writing. Gianfrancesco Ferrari volunteered in the laboratory and was an enormous help running optimisation PCRs under my supervision.

18 Chapter Three

Chapter Three

Microsatellite variation and population structure in a declining Australian hylid (Litoria aurea)

Abstract

The green and golden bell frog (Litoria aurea) was once a common Australian hylid.

Today, many populations are small and fragmented due to dramatic declines in distribution and abundance. I undertook a large-scale assessment of genetic structure and diversity in L. aurea using four species-specific microsatellite markers. Twenty-one locations were sampled from throughout the species’ range covering 1000 kilometres of the east coast of

Australia. Levels of allelic diversity and heterozygosity were high (uncorrected mean alleles/locus and HE: 4.8-8.8 and 0.43-0.8 respectively) compared to other amphibian species and significant differences among sampled sites were found. Despite recent population declines, no sites displayed a genetic signature indicative of a population bottleneck. Significant genetic structuring (overall FST 0.172) was detected throughout the species’ range, but was relatively low compared to previous amphibian studies employing microsatellites. In addition, some areas sampled within continuous habitat showed evidence of weak genetic structuring (data subset FST 0.034). I conclude that maintaining areas of continuous habitat is critical to the conservation of the species and argue that population recovery and/or persistence in all areas sampled is possible if appropriate protection and management is afforded.

19 Chapter Three

Introduction

The gene pool of most species is structured and comprised of multiple populations that vary in the rate of exchange of individuals. Over time dispersal patterns within species help establish geographical distribution, local adaptions and speciation (Newman & Squire

2001). Species viability is dependant on the persistence of local populations, and fragmentation of populations increases the risk of local extinctions due to loss of genetic diversity, increased inbreeding and stochastic demographic processes (Lacy 1987;

Frankham 1995). Hence anthropogenic alteration of population structure is often implicated in species decline (e.g. Lande 1988; Templeton et al. 2001).

Amphibian species’ declines are topical and well publicised (e.g. Alford & Richards 1999).

Despite this, amphibian population dynamics are generally poorly understood. Delineation of inter-population movement and population structure is difficult in many species including amphibians. Direct observations of individual movement through mark-recapture data have previously proved informative (Driscoll 1997; Dodd & Cade 1998) but such methods are often inefficient at detecting long-distance dispersal and are rarely able to demonstrate if dispersal has resulted in effective breeding. In theory genetic data can be used to suggest levels of dispersal and recent molecular research has help contribute to a further understanding of amphibian population dynamics, with studies providing new information about population structure, dispersal and migration patterns (Hitchings &

Beebee 1997; Newman & Squire 2001; Rowe et al. 2000b; Shaffer et al. 2000).

20 Chapter Three

Amphibian populations are often thought to exhibit strong site fidelity (Daugherty &

Sheldon 1982; Reading et al. 1991; Sinsch 1991; Kusano et al. 1999) and various genetic studies have supported the idea that populations tend to be relatively isolated and show significant differentiation even at a fine scale (i.e. < 10km) (Driscoll 1998; Routman 1993;

Rowe et al. 2000b; Shaffer et al. 2000). However, some species have now been shown to depart from this pattern (Seppa & Laurila 1999; Tallmon et al. 2000; Newman & Squire

2001), and several are thought to have a metapopulation structure (Marsh & Trenham 2000;

Alford & Richards 1999).

Like many amphibian species worldwide, green and golden bell frogs (Litoria aurea) have undergone dramatic population declines and local extinctions during the last 30-40 years

(Pyke & White 2001). Though once regarded as common throughout its range L. aurea is now thought to have disappeared from over 80% of its historical distribution (White &

Pyke 1996 as cited in Pyke et al. 2002). Remaining endemic populations are mostly restricted to the south-eastern coastline of Australia where many populations are small and fragmented. This coastline is also the most densely human populated region of Australia.

Under Australian legislation L. aurea is listed as ‘Vulnerable’ nationally (Environmental

Protection and Biodiversity Conservation Act 1999) and ‘Endangered’ in New South Wales

(Threatened Species Conservation Act 1995).

L. aurea is a pond breeding species thought to have a high dispersal capability for a hylid.

Hylids are typically known as ‘tree frogs’ and are heavily represented in Australia and found throughout most parts of the world (Hoser 1989). L. aurea have been known to move 1.5km in one night (Pyke & White 2001) and travel in excess of 10km from known

21 Chapter Three

breeding ponds (Pyke & White 2001). However, most frequent observations of movement, between successive recaptures are less than 500m (Pyke et al. 2002; Christy 2001; Pyke &

White 2001). Little is understood about this species’ population dynamics, although a metapopulation structure has been suggested (Christy 2001) and they have been described as a ‘weedy’ or ‘colonising’ species (Pyke & White 2001).

The patchy distribution of present-day L. aurea populations compounds difficulties relating to management options for conservation. A determination of genetic relationships among populations could be of assistance to the formulation of management practices including identifying areas of high conservation priority, revealing historical and/or contemporary dispersal corridors among populations, detecting severe population declines (i.e. bottlenecks) and identifying individuals and/or populations that might provide source material for augmentation/translocation or reintroduction programs (Mace et al. 1996). The objective here was to make an empirical assessment of genetic variation and population structure throughout the species’ range.

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Materials and Methods

Sampling localities and tissue collection

The study was conducted over approximately 1000 kilometres of the east coast of Australia, from the far north coast of New South Wales to East Gippsland in Victoria (Fig. 3.1).

Sampling occurred during the breeding season from late August to early April for three consecutive seasons (1999-2001). In total, tissue samples were collected from 527 individuals from 21 locations (Table 3.1). Sample sizes ranged from 7 to 48 with an average of approximately 25 individuals per site (Table 3.1). Samples obtained from discrete locations consisting of multiple ponds were pooled if sample sizes from individual ponds were less than seven. In most instances this involved ponds being pooled within a range of 1m to 2km. In the case of Maitland, samples were collected from two locations separated by approximately 5km.

All individuals sampled were adults or juveniles greater than 30mm. Individuals from each site were captured by hand, sampled and released within the immediate vicinity of the ponds surveyed. The pad of the outer toe on the back left foot was clipped from each frog using a sterile blade and the tissue stored individually in a 1.5ml screw cap vial containing

90-95% ethanol.

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24 Chapter Three

Table 3.1 Geographical coordinates of sampled locations in Australian Map Grid units (zone 56 Easting and Northing). The number of individuals sampled (n) per site is also detailed. Location Population Name AMG Easting (m) AMG Northing (m) n Crescent Head, NSW CH 501009 6558000 21 Broughton Island, NSW BI 436400 6391100 48 Kooragang Island, NSW KIS 379700 6363500 27 Sandgate, NSW SAND 378586 6362935 15 Maitland, NSW MAT 343947 6409566 7 North Avoca, NSW NA 354488 6296251 23 Homebush, NSW HB 321700 6253700 41 Newington, NSW NEW 321500 6255500 23 Kurnell, NSW K 331300 6233700 35 Port Kembla, NSW PK 306800 6181350 21 Incitec-Port Kembla, NSW INC 307840 6182781 22 Coomonderry Swamp, NSW CS 291833 6145613 28 Brundee Swamp, NSW SB 286168 6132202 44 Greenwell Point, NSW GP 292100 6134400 14 Culburra, NSW CU 296416 6131281 31 Sussex Inlet, NSW SX 279300 6105600 27 Lake Meroo, NSW LM 262947 6070124 15 Captains Flat-Queanbeyan, NSW Q 171196 6074574 20 Point Hicks-Cann River, VIC HICKS 162147 5846114 20 Alcox Farm-Bemm River, VIC ALCOX 145846 5814335 19 Evans Farm-Bemm River, VIC EVANS 146101 5815053 26

Sample extraction and microsatellite typing

DNA was extracted from samples using a standard phenol-chloroform extraction protocol

(Sambrook et al. 1989), or a High Pure PCR Template Preparation Kit (Roche) following the manufacturer’s instructions. Four microsatellite loci were amplified from each individual as described elsewhere (Burns & Ferrari 2004; Chapter 2), and are assumed to be neutral (reviewed in Bruford & Wayne 1993; Sunnucks 2000).

25 Chapter Three

Data analysis

Genetic diversity within populations. Genetic diversity was measured as allelic diversity

(mean number of alleles per locus) and observed (HO) and expected (HE) heterozygosities, using GENEPOP (Raymond & Rousset 1995b) version 3.2. To account for variation in sample sizes, adjusted allelic diversity was calculated using a bootstrapping technique executed in AGARst (Harley 2001). Differences in adjusted allelic diversity among populations were tested using two-way analysis of variance to account for the effect of locus, followed by Tukey’s multiple comparison test (Zar 1984). Differences in HE among populations were assessed using Kruskal-Wallis nonparametric test (Zar 1984). Evidence of linkage disequilibrium and deviations from Hardy-Weinberg Equilibrium (HWE) were assessed using Markhov chain approximation (Gou & Thompson 1992) in GENEPOP.

Bottleneck testing. Evidence of recent population bottlenecks was assessed via

BOTTLENECK (Piry et al. 1999) using all three mutational models. Given the dataset (i.e. four loci), I followed the recommendation of Piry et al. (1999) and used the Wilcoxon signed-rank test. Two-tailed probabilities were used as the population history of many sites was not certain (Luikart & Cornuet 1998). A qualitative descriptor of the allele frequency distribution (mode-shift indicator) (Luikart et al. 1998a) was also used to detect any evidence of population bottlenecks.

Population differentiation. A number of methods were employed to assess population differentiation. First, heterogeneity in allele frequencies across populations, and all pairs of populations was tested using the exact probability test (Raymond and Rousset 1995a)

26 Chapter Three

implemented in GENEPOP. Second, the level of genetic differentiation among populations was quantified using FST. FST (Weir & Cockerham 1984) was calculated using FSTAT v.

2.9.3. (Goudet 1995) with significance of pair-wise comparisons tested using 10,000 iterations without assuming HWE. For analyses involving multiple comparisons I adjusted the critical probability for each test using the sequential Bonferroni correction (Rice 1989).

Finally, genetic distance was calculated among populations using Nei’s unbiased genetic distance (Nei 1972) using MICROSAT (Minch et al. 1998). Nei’s genetic distances were used to construct a neighbor-joining tree in MEGA version 2 (Kumar et al. 1993).

Bootstrap analysis was performed by first generating 1000 distance matrices using

MICROSAT which were then used to generate 1000 neighbor-joining trees with the program NEIGHBOR in PHYLIP (Felsenstein 1993). These 1000 trees were then summarised using the CONSENSE program in PHYLIP.

Patterns of genetic differentiation. Allele frequency variation at all loci for all populations was summarised in two dimensions using multidimensional scaling (MDS) analysis via

SPSS 10.0 for Windows (SPSS Inc., Chicago, IL, USA) using an allele frequency matrix generated in GENEPOP. I then tested for a relationship between genetic differentiation and the natural log of geographical distance using the measure FST /(1-FST) (Rousset 1997). The significance of the log-linear association was tested using Mantel’s procedure with 5000 permutations of the data, as implemented in GENEPOP.

Assignment test. An assignment test was done using GeneClass2 (Piry et al. submitted to

Molecular Ecology, web address http://www.montpellier.inra.fr/URLB/index.html). Both the Bayesian method (Rannala & Mountain 1997) and Frequencies-based method (Paetkau

27 Chapter Three

et al. 2004) of analysis were employed. For theses analyses a threshold of 0.01 was set and

100, 000 simulations were performed.

Results

Genetic diversity

All four loci used in this study were variable with the total number of alleles detected ranging from 12 to 23. Uncorrected allelic diversity and HE values among locations ranged from 4.8 to 8.8 and 0.43 to 0.80 respectively (Table 3.2; Table 3.3). Allelic diversity levels were adjusted for sample size differences and corrected estimates ranged from 2.7 to 5.7

(Table 3.2), and significant differences among locations were detected (ANOVA, P =

0.002). A post hoc test revealed that the island population at Broughton Island was significantly lower in allelic diversity than all sites except Kurnell, Incitec and the three

Victorian sites Point Hicks, Alcox farm and Evans farm (Fig. 3.2). Other groupings of non- significant differences are shown in Figure 3.2. Significant differences in HE (Table 3.3) among locations were also found (Kruskal-Wallis P = 0.04), with the lowest levels detected among the same six locations that had low allelic diversity.

A total of ten locations out of the 21 analysed had private (i.e. unique) alleles (Table 3.2) with a mean 3.75 unique alleles per locus. The frequency of private alleles in all sampled sites was low, ranging from 0.0179 (locus Laurea4-49; location Crescent Head) to 0.0536

(locus Laurea4-49; location Coomonderry Swamp). The average frequency of private alleles across all 10 sampled sites for all four loci was 0.0338 (Chapter 3 Appendix).

28 Chapter Three

Table 3.2 Allelic diversity of 21 sampled green and golden bell frog sites. Allelic diversity is given as a direct count (DC) of the average number of alleles per locus and as corrected bootstrap estimates to account for sample size variation. The total number of alleles within sites for each locus is also detailed with the number of private alleles at each indicated in parentheses.

Sample Site Number of alleles Mean number of alleles per locus Mean Locus Locus Locus Locus Total D.C. Boot. sample Laurea 4-Laurea Laurea Laurea no. of size 49 5M 2A 4-10 alleles CH 20 6(1) 9 10 4 29(1) 7.3 4.7 BI 44.5 4(1) 4 3 8(1) 19(2) 4.8 2.7 KIS 26.8 7 11 8 4 30 7.5 5.1 SAND 15 8(1) 9 8 3 28(1) 7 4.8 MAT 7 5 7 6 4 22 5.5 4.7 NA 23 6 5 8 5 24 6 4.3 HB 40.8 8 8(1) 8 8 32(1) 8 4.9 NEW 23 7 4 8 6 25 6.3 4.6 K 34.3 6 6 7 5 24 6 3.7 PK 21 7 5 7 5 24 6 4.7 INC 22 6 4 6 6 22 5.5 3.5 CS 27.5 13(2) 6 9 7 35(2) 8.8 5.5 SB 43.3 10 10 10 5 35 8.8 5.6 GP 13.5 8 6 7 3 24 6 4.6 CU 30.5 10 7 8 5 30 7.5 5.2 SX 26.8 8 7 10(1) 6 31(1) 7.8 5 LM 15 11(1) 12(2) 9 3 35(3) 8.8 5.7 Q 19.5 4 5 9(2) 5 23(2) 5.8 4.2 HICKS 19.8 4 4 8 6(1) 22(1) 5.5 3.4 ALCOX 19 4 4 8 5 21 5.3 3.7 EVANS 25.5 4 6 12(1) 4 26(1) 6.5 3.7

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Table 3.3 Heterozygosity of 21 sampled green and golden bell frog sites. Heterozygosity is given as observed (HO) and expected (HE). Weir and Cockerham (1984) Fis values for each locus are detailed and sites that showed a significant deviation (Bonferroni correction P < 0.0125) from HWE over all loci are indicated by ‘Ex’ for an excess of heterozygotes, ‘Def’ for a deficiency of heterozygotes or ‘Eq’ if in equilibrium. Sample Site Heterozygosity Hardy-Weinberg Exact Test Fis Values

HO HE Locus Locus Locus Locus Ave (S.E) Eq/Ex/Def Laurea4-49 Laurea5M Laurea2A Laurea4-10

CH 0.62 0.63 0.018 -0.086 0.143 -0.039 0.01 (0.05) Eq

BI 0.36 0.43 0.229 0.829 -0.207 0.331 0.30 (0.21)** Ex

KIS 0.65 0.75 0.521 -0.095 0.200 0.189 0.20 (0.13)** Ex

SAND 0.7 0.74 0.282 0.061 -0.089 -0.052 0.05 (0.08)* Ex

MAT 0.61 0.82 1.000 0.178 -0.235 0.048 0.25 (0.27)* Ex

NA 0.73 0.67 0.099 -0.124 -0.120 -0.160 0.08 (0.06) Eq

HB 0.78 0.76 -0.010 0.016 -0.242 0.123 -0.03 (0.08)** Def

NEW 0.8 0.74 -0.089 -0.343 -0.192 0.294 -0.08 (0.14) Eq

K 0.68 0.62 -0.109 -0.007 -0.233 -0.022 -0.09 (0.05) Eq

PK 0.7 0.77 0.262 0.236 -0.212 0.175 0.12 (0.11)** Ex

INC 0.51 0.55 0.110 -0.069 0.159 0.055 0.06 (0.05) Eq

CS 0.76 0.8 0.182 0.104 -0.125 0.015 0.04 (0.07) Eq

SB 0.65 0.79 0.231 0.287 0.157 -0.013 0.17 (0.07)** Ex

GP 0.57 0.76 0.429 0.812 0.043 -0.553 0.18 (0.29)** Ex

CU 0.66 0.78 0.309 0.158 -0.149 0.349 0.17 (0.11)** Ex

SX 0.76 0.75 0.211 -0.015 -0.160 -0.136 -0.03 (0.08)* Def

LM 0.72 0.78 0.451 -0.032 -0.157 0.109 0.09 (0.13)* Ex

Q 0.64 0.68 0.172 -0.089 -0.184 0.462 0.09 (0.14)* Ex

HICKS 0.6 0.57 0.267 0.031 -0.218 -0.131 -0.01 (0.11) Eq

ALCOX 0.53 0.61 0.675 0.255 -0.157 -0.056 0.18 (0.19)* Ex

EVANS 0.55 0.58 -0.067 0.121 -0.101 0.208 0.04 (0.07) Eq

*Significant at the 0.01 level, **Significant at the 0.001 level

Genotype frequencies showed a significant departure from HWE in 13 out of 21 locations.

Of these, all but two were deficient in heterozygotes (Table 3.3). All loci showed deviations from HWE in one or more sites with no one locus showing deviations in all cases. Deviations in locus Laurea4-49 were, however, more prevalent, showing significant heterozygote deficiencies in 9 of 14 sites (Table 3.3). These deviations could be the result of a Wahlund effect, non-random sampling, violations of HWE assumptions (e.g.

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inbreeding) or alternatively may indicate the presence of null alleles (Pemberton et al.

1995). Statistical corrections for allele frequencies (Chakraborty et al. 1992; Brookfield

1996) for locus Laurea4-49 were not attempted because they assume that a population would otherwise be in HWE and evidence of null alleles was not conclusive. Finally, there was no significant evidence for linkage disequilibrium.

8 7 6 5 4 3 2 1 0 B I H I C KS I NC K A L C O X E VA N S Q N A N E W G P CH M A T P K S A ND H B SX K I S CU C S SB L M

Figure 3.2 Bootstrap adjusted allelic diversity levels with sites shown in ascending order (abbreviations as per Table 3.1). Horizontal bars show groups not significantly different by Tukey’s multiple comparisons.

Population bottlenecks

Evidence of population bottlenecks was assessed using two methods. There was no significant excess of heterozygosity in any of the 21 locations relative to drift-mutation equilibrium. There was evidence of a ‘mode-shift’ (Luikart et al. 1998a) in two areas:

Maitland and Port Kembla. However, this method is qualitative (Luikart et al. 1998a) and sample sizes in both areas were less than recommended (30 individuals) for analysis.

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Population differentiation

Genetic structure was detected initially from significant differences in allele frequencies using Fisher’s exact test (P < 0.0001, Table 3.4). This result was supported by multi-locus values over all sites for FST, further indicating genetic differentiation throughout the species range (Table 3.4). In pair-wise population analysis most FST comparisons were significantly different from zero (Bonferroni correction P < 0.0024, Table 3.5). However, non-significant comparisons were also recorded (Table 3.5) and most of these involved locations within geographical proximity (Fig. 3.1). Note all comparisons involving

Maitland should be interpreted cautiously given the small sample (n = 7).

Table 3.4 Estimates of FST for each locus and averaged over all loci. Also shown are Fishers’s Exact Probabilities of population differentiation over all populations.

Locus Fisher’s Exact P FST Laurea4-49 <0.0001 0.254 Laurea 5M <0.0001 0.190 Laurea 2A <0.0001 0.091 Laurea 4-10 <0.0001 0.145 All loci <0.0001 0.172

Nei’s distance is presented in Table 3.5 and was used to generate a neighbor-joining tree

(Fig. 3.3). In the tree, Victorian populations form a strongly supported group (bootstrap

99) as does Crescent Head and North Avoca (bootstrap 87). The moderate node support for the Captains Flat, North Avoca and Crescent Head grouping (bootstrap 72) was unexpected given the geographical location and isolation of Captains Flat (Fig. 3.1). The population on

Broughton Island falls out distinctly in the tree but was not strongly supported (bootstrap

61). All remaining nodes are also poorly supported.

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KIS

SAND

87 CH 72 NA

NEW

PK 50 INC Mainland NSW 38 K 32 30 CS

61 SX CU 40 SB 60 52 GP LM

ALCOX 99 HICKS 59 Victoria EVANS

61 MAT BI Broughton Island

0.1

Figure 3.3 Neighbour-Joining tree of sampled sites based on Nei’s unbiased genetic distance. Topologically, populations separate into three broad classifications: Mainland populations within the state of NSW (MAT the exception), three populations within the state of Victoria, and Broughton Island. Numbers at nodes indicate the percentage support value from 1000 bootstrap replicates.

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Table 3.5 Estimates of pair-wise FST (below diagonal) and Nei’s unbiased genetic distance (above diagonal). Boxed areas indicate non-significant pair-wise FST comparisons. CH BI KIS SAND MAT NA HB NEW K PK INC CS SB GP CU SX LM Q HICKS ALCOX EVANS

CH 0.821 0.364 0.207 0.307 0.059 0.382 0.220 0.563 0.399 0.570 0.563 0.443 0.456 0.523 0.404 0.606 0.216 0.634 0.484 0.594 BI 0.448* 0.570 0.566 0.344 0.761 0.647 0.715 0.882 0.780 0.854 0.760 0.638 0.749 0.576 0.711 0.761 0.897 0.725 0.750 0.738 KIS 0.141* 0.316* 0.345 0.180 0.392 0.255 0.314 0.491 0.321 0.446 0.505 0.384 0.533 0.331 0.359 0.571 0.461 0.449 0.348 0.340 SAND 0.092* 0.334* 0.102* 0.115 0.187 0.242 0.209 0.545 0.247 0.454 0.407 0.250 0.277 0.269 0.326 0.487 0.440 0.409 0.335 0.460

MAT 0.124* 0.269* 0.047 0.030 0.247 0.242 0.221 0.518 0.302 0.502 0.349 0.222 0.310 0.225 0.220 0.377 0.412 0.442 0.397 0.486

NA 0.032* 0.409* 0.138* 0.076* 0.096* 0.268 0.102 0.437 0.269 0.502 0.435 0.359 0.382 0.395 0.283 0.461 0.211 0.501 0.388 0.532 HB 0.143* 0.320* 0.075* 0.073* 0.065* 0.097* 0.064 0.286 0.182 0.360 0.256 0.265 0.336 0.210 0.247 0.390 0.390 0.263 0.225 0.330

NEW 0.098* 0.368* 0.098* 0.070* 0.067* 0.046 0.021 0.197 0.129 0.391 0.203 0.189 0.239 0.154 0.159 0.257 0.266 0.323 0.225 0.376

K 0.254* 0.454* 0.190* 0.213* 0.198* 0.197* 0.119* 0.094* 0.386 0.546 0.192 0.378 0.423 0.227 0.227 0.383 0.371 0.544 0.476 0.564 PK 0.150* 0.378* 0.091* 0.071* 0.070* 0.098* 0.052* 0.041* 0.155* 0.255 0.242 0.199 0.288 0.207 0.283 0.270 0.296 0.389 0.285 0.419

INC 0.283* 0.484* 0.196* 0.209* 0.220* 0.242* 0.160* 0.185* 0.275* 0.129* 0.362 0.353 0.428 0.443 0.413 0.434 0.484 0.557 0.479 0.538 CS 0.185* 0.353* 0.128* 0.106* 0.074* 0.139* 0.068* 0.059* 0.088* 0.062* 0.159* 0.166 0.167 0.122 0.164 0.103 0.465 0.527 0.473 0.584 SB 0.145* 0.304* 0.096* 0.064* 0.038* 0.120* 0.065* 0.048* 0.128* 0.051* 0.149* 0.030* 0.040 0.053 0.220 0.133 0.419 0.503 0.407 0.480

GP 0.171* 0.389* 0.145* 0.079* 0.067 0.136* 0.094* 0.074* 0.172* 0.077* 0.196* 0.042* 0.003 0.135 0.262 0.051 0.495 0.517 0.448 0.555

CU 0.179* 0.304* 0.091* 0.075* 0.049* 0.131* 0.058* 0.046* 0.099* 0.054* 0.186* 0.030* 0.010 0.034 0.157 0.170 0.474 0.401 0.332 0.399

SX 0.156* 0.360* 0.107* 0.100* 0.062 0.106* 0.075* 0.054* 0.103* 0.083* 0.186* 0.047* 0.047* 0.078* 0.046* 0.200 0.367 0.510 0.418 0.498

LM 0.206* 0.381* 0.147* 0.129* 0.081* 0.153* 0.103* 0.076* 0.156* 0.070* 0.193* 0.025* 0.025 0.009 0.042* 0.058* 0.567 0.594 0.534 0.642

Q 0.102* 0.447* 0.153* 0.151* 0.130* 0.092* 0.129* 0.099* 0.170* 0.101* 0.234* 0.141* 0.119* 0.160* 0.147* 0.128* 0.173* 0.707 0.546 0.630 HICKS 0.298* 0.438* 0.190* 0.186* 0.196* 0.236* 0.122* 0.152* 0.269* 0.169* 0.301* 0.120* 0.184* 0.216* 0.166* 0.211* 0.232* 0.298* 0.009 0.050

ALCOX 0.228* 0.432* 0.141* 0.143* 0.157* 0.179* 0.097* 0.103* 0.229* 0.118* 0.255* 0.168* 0.143* 0.175* 0.129* 0.166* 0.195* 0.229* 0.006 0.015

EVANS 0.282* 0.436* 0.153* 0.202* 0.207* 0.245* 0.145* 0.171* 0.274* 0.178* 0.291* 0.215* 0.181* 0.227* 0.166* 0.207* 0.247* 0.274* 0.036 0.009

* Significant pair-wise differences after Bonferroni correction (P < 0.0024)

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Patterns in genetic differentiation

Allele frequency differences summarised in the form of a MDS plot (stress=0.19; r2=0.88)

(Fig. 3.4) generally support relationships detected by Nei’s genetic distance: Broughton

Island is highly distinct whilst Victorian populations show some tendency to cluster.

Within the mainland NSW sites Crescent Head, Captains Flat, Lake Meroo, Incitec and

Kurnell are not tightly clustered with other NSW sites (Fig.3.4).

Under drift-mutation equilibrium a relationship between genetic differentiation and geographical distance is predicted. In this study, a highly significant relationship

(Mantel’s, P < 0.0001) was found amongst sampled locations (excluding Broughton Island)

(Fig. 3.5). However, the geographical scale of this study was over 1000km and numerous populations occur within fragmented habitat. To investigate isolation by distance on a finer scale I analysed the relationship amongst six sampled locations (Coomonderry Swamp,

Brundee Swamp, Greenwell Point, Culburra, Sussex Inlet and Lake Meroo) where habitat is mostly continuous. Approximate geographic distance between these locations ranged from 5 to 80km and pair-wise FST estimates ranged from 0.078 to 0.003 (Table 3.5). The

FST estimate over all six sites was FST = 0.034. The relationship between genetic differentiation and geographic distance at this scale was not significant (Mantel’s, P =

0.251).

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Q CH LM 1 Mainland NSW Inc NA GP K CS PK SX SB 0 New HB Sand Mat CU KIS

-1 Alcox

Evans Victoria Hicks Broughton Island -2 BI

-3 D i m en s on 2 -2 -1 0 1 2 3 4

Dimension 1

Figure 3.4 MDS analysis from allele frequency data for four loci and 21 sample locations. A geographical ov erlay of sites has been given as mainland NSW, Broughton Island and Victoria.

-1 Rsq = 0.2408 Fst/1-Fst -.1 0.0 .1 .2 .3 .4 .5

LN of Distance (kms)

Figure 3.5 Isolation by distance plot of FST/(1-FST) plotted against the natural log of geographical distance (km). BI has been excluded from the analyses because of its isolation from gene flow. The solid line represents the best-fit linear regression (P < 0.0001) based on all points.

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Assignment test

The Bayesian method (Rannala & Mountain 1997) of assignment performed slightly better

(53.7 %) than the Frequencies-based method (50.3%, Paetkau et al. 2004) in assigning individuals to correct sampling locations. Individual assignments using the Bayesian method are shown in Table 3.6. Of the individuals that were assigned to a non-source population 25.25% were assigned to a location within geographical proximity, with remaining individuals assigned to more distant populations (Table 3.6).

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Source Assigned Population Pop. CH BI KIS SAND MAT NA HB NEW K PK INC CS SB GP CU SX LM Q HICKS ALCOX EVANS % source* Unassig.** CH 13 3 2 1 61.9 2 BI 43 1 89.6 5 KIS 1 20 1 1 1 74.1 3 SAND 10 1 1 66.7 3 MAT 1 2 1 1 1 14.3 1 NA 1 15 4 1 1 65.2 1 HB 1 1 22 4 7 1 2 53.7 3 NEW 1 6 9 1 4 1 39.1 1 K 5 1 20 5 1 2 57.1 1 PK 1 2 12 1 1 1 57.1 3 INC 1 4 10 3 3 43.5 1 CS 16 3 3 3 1 57.1 2 SB 1 2 6 19 2 5 2 6 43.2 1 GP 1 1 7 1 1 4 6.67 0 CU 2 2 4 1 15 2 4 48.39 1 SX 1 5 1 2 16 1 59.3 1 LM 4 2 1 5 33.3 3 Q 1 1 2 1 15 75.0 0 HICKS 1 1 1 1 10 5 1 50.0 0 ALCOX 1 2 1 1 3 5 6 26.3 0 EVANS 5 7 14 53.85 0

* % Source: The percentage of individuals assigned to the site they were sampled from. ** Unassign: The number of individuals from a sampling location that were not assigned to any sampling location.

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Discussion

Results of this study indicate significant genetic structuring throughout the range of L. aurea. However, a lack of structure was detected among some sites within areas of continuous habitat. Within sampled sites allelic diversity and heteozygosity levels were either equivalent to or greater than those reported in other amphibian species (e.g. Scribner et al. 1994; Rowe et al. 1998; Newman & Squire 2001). This suggests that negative genetic effects resulting from current isolation of many L. aurea populations have been limited to date.

Patterns of genetic diversity

Estimates of genetic diversity (allelic diversity and heterozygosity) were significantly different among sites and results were consistent with known population histories.

Diversity measures for six sites were comparatively low, with Broughton Island exhibiting lowest levels. It is expected that island populations will have lower levels of genetic diversity compared with mainland populations (Frankham 1997) and for Broughton Island this is most likely due to founder effects and drift. Three sites in the state of Victoria also showed comparatively low genetic diversity, which may be due to an ‘edge effect’ because they occur at the southern end of the species’ range. Two centrally distributed sites, Incitec and Kurnell, unexpectedly showed low levels of genetic diversity. The population history of Incitec is unknown because it was first discovered in 2000. Therefore, Incitec could have been colonised recently by a limited number of individuals. This would account for the unexpected level of genetic differentiation between Incitec and the geographically close

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(approximately 2km) Port Kembla population, and also explain the low genetic diversity detected for Incitec. If this were the case then current levels of differentiation and diversity may be transient. The population history of Kurnell is better known (A. White and M.

Christy, pers. comm.) and it is likely that ongoing decline, fragmentation and isolation have contributed to relatively low levels of genetic diversity. The high level of genetic differentiation between Kurnell and other sites in Sydney (i.e. Homebush and Newington,

Fig. 3.4; Table 3.5) support this explanation.

Levels of genetic variation within most sampled locations were at the higher end of the observed spectrum (Table 3.2; Table 3.3), suggesting contemporary processes affect populations, i.e. their genetic structure is unlikely to be entirely attributable to historical factors (Segelbacher & Storch 2002). However, it seems unreasonable to think that gene flow is current among all populations, as a number of sites are geographically isolated and significantly structured (Table 3.5). It may therefore be that in certain areas sufficient time has not passed, since fragmentation and isolation, for reduced variation due to drift to occur. However, other sites, for example within the southern distribution of NSW (six locations sampled, CS, GP, CU, SX, SB and LM) and Victoria (three locations, HICKS,

ALCOX and EVANS), which still persist in relatively continuous habitat, may still be connected by gene flow (Table 3.6).

Population bottlenecks

Allele frequency data provided no direct evidence of severe population declines (i.e bottlenecks). Although L. aurea populations are known to fluctuate and the species has undergone a recent large-scale decline it may be that tested locations have not experienced

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genetic bottlenecks. Alternatively, migration levels among sites in certain areas may have been sufficient to ameliorate any bottleneck effects, by increasing the number of rare alleles without substantially affecting heterozygosity, thus masking any excess HE caused by a bottleneck (Cornuet & Luikart 1996; Keller et al. 2001). A further possibility is that I may have failed to detect any bottleneck signatures because too few loci were examined to achieve adequate power and/or because the HE observed in post-bottlenecked populations is a transient feature, expected to last only a few generations (Luikart & Cornuet 1998).

Furthermore, several of the sites tested were not in Hardy-Weinberg Equilibrium, which could have biased the result of the BOTTLENECK test (Cornuet & Luikart 1996).

Caution needs to be applied when interpreting results of the BOTTLENECK program, as it has previously failed to detect known population bottlenecks (Whitehouse & Harley 2001).

Another informative approach for bottleneck detection is the comparison of a given population’s allelic diversity with that of an ancestral or demographically stable population

(see for e.g. Houlden et al. 1996; Luikart et al. 1998b; Spencer et al. 2000; Whitehouse &

Harley 2001). No ancestral samples were available to us so the latter approach was taken.

The Homebush population is one of the largest remaining populations of L. aurea and the results of monitoring programs indicate that the population has remained relatively stable since monitoring began in 1993 (Christy 2001; SOPA 2002). A two-way ANOVA of adjusted allelic diversity indicated that Homebush had significantly greater allelic diversity compared to Broughton Island (P = 0.003) and Point Hicks (P = 0.044). Lower variation detected at Point Hicks is most likely due to an edge effect and at Broughton Island due to a founder effect. No other sampled sites showed significantly reduced levels of allelic diversity in comparison to Homebush, which is consistent with the BOTTLENECK results.

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Microsatellite surveys of amphibian population structure

Few published microsatellite studies of amphibian population structure are available for comparison and to my knowledge no other studies of hylids are available. However, I have summarised what current published microsatellite data is available and relevant in Table

3.7 (see also Newman & Squire 2001 for a literature survey), which encompasses two Bufo species and three Rana species. Only one of these studies (Palo et al. 2003) was conducted on a similar geographic scale to this study (Table 3.7).

Species Approx. distance range (km) FST Reference Bufo bufo 5.5 - 14.5 0.016 Scribner et al. 1994 Bufo calamita (A) 2 - 3.6 0.060 Rowe et al. 2000b Bufo calamita (B) 2 - 16 0.224 Rowe et al. 2000b Bufo calamita (C) 0.5 - 9 0.111 Rowe et al. 2000b Rana luteiventris 3 - 34 0.07 Call et al. 1998 Rana sylvatica 0.05 - 21 0.014 Newman & Squire 2001 Rana temporaria 200 - 1600 0.235 Palo et al. 2003 Litoria aurea 1-1000 0.172 This study (overall) Litoria aurea 5-80 0.034 This study (continuous habitat subset)

The overall level of genetic structuring detected in L. aurea, as measured by FST, was FST =

0.172 (Table 3.7). On a smaller scale the overall estimate of FST for the southern region of

NSW where six discrete sites were sampled was FST = 0.034. Both these estimates are within the range reported for FST in previous studies (FST = 0.014 – 0.235, Table 3.7).

However, in comparison to these studies the level of structuring in L. aurea is relatively low given the geographical scale of the study area. Even considering a sub-set of the data over a range of 5 to 80km the level of detected structuring was only greater than that reported in two studies both of which were conducted over a range of less than 22km

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(Table 3.7). The results suggest that L. aurea has low genetic structuring compared to other amphibians and challenges the idea that amphibians will exhibit a high degree of spatial structure at a scale greater than a few kilometres (Shaffer et al. 2000), which reinforces the need for species-specific research.

Patterns of population differentiation in L. aurea

The investigation of between-population dynamics gave some indication of existing population structure and patterns of gene flow throughout the study area. The range of L. aurea was significantly structured with the majority of sampled locations being genetically distinct (Table 3.5). An isolation-by-distance pattern was evident (for analysis involving all populations except Broughton Island), suggesting that the great majority of dispersal occurs between nearest neighbouring habitat patches with only a few individuals moving longer distances, which is consistent with ecological observations (see for review Pyke & White

2001).

Areas within continuous habitat, namely within southern NSW and Victoria, were less structured with some pair-wise FST comparisons being non-significant (Table 3.5).

Amongst the sites within southern NSW there was no significant association between genetic and geographical distance, suggesting that in this region gene flow is sufficiently large to confound genetic differentiation and/or that barriers to dispersal are more important in structuring genetic variation where habitat persists (Slatkin 1993; Roy et al. 1994).

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Levels of genetic diversity in most sampled locations were relatively high (Table 3.2 and

Table 3.3) and either equivalent to or greater than levels found in other amphibian studies

(e.g. Scribner et al. 1994; Rowe et al. 1998; Newman & Squire 2001). Relatively high levels of genetic diversity may persist because population fragmentation of this species has only occurred over the last 30-40 years and prior to this the species was common with a mostly continuous distribution throughout its range (White & Pyke 1996; Pyke & White

2001). However, levels of genetic diversity may not persist with increasing isolation, as decreased migration and drift will result in a loss of genetic diversity and increased potential for inbreeding within populations.

Prior to decline and fragmentation the natural genetic structure of L. aurea was most likely weak (relative to today and other amphibian studies) due to high dispersal activity (as is currently found in Victoria). It is likely that the significant structuring detected in this study is predominately due to the effects of drift. However, most sites may have not been isolated long enough for levels of within population diversity to become reduced. This hypothesis is supported by low variation in Broughton Island where it is presumed the population has been isolated since originally founded. However, as isolation of remaining

L. aurea populations is maintained or increased, genetic drift will play a greater role, increasing genetic differentiation and decreasing genetic diversity and thereby potentially altering the natural dynamic of the species.

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Conservation implications and management recommendations

Given this interpretation, I suggest that a key issue for L. aurea conservation should be the preservation of habitat to allow population connectivity. The data reinforces the conservation value of areas where multiple populations currently exist within mostly continuous habitat (e.g. southern region of NSW and Victoria). These areas should have high conservation priority to make certain the natural network of genetic connections between populations is maintained. This should ensure the processes that maintain adaptive diversity and evolutionary potential are conserved.

Conservation management in this species should focus on the protection of local populations and habitat to promote population connectivity. Translocation and reintroduction programs may be viable conservation strategies based on genetic evidence but a complex variety of other considerations need also be considered with such strategies

(see for example Greer 1996) and consideration would be required on a case-by-case basis.

It would be preferable to establish and/or preserve habitat corridors and existing habitat patches to allow for future natural colonisation events and sustainable population expansion. If managers only preserve localities where these frogs currently exist, then the species may continue to decline and to lose evolutionary potential. Maintenance of a dense network of suitable habitat patches and stepping-stones, maximising local carrying capacity and reproductive output and minimising known threats, are the key to securing the long- term survival of the green and golden bell frog.

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Publication Information

This chapter was accepted for publication in Molecular Ecology.

Reference: Burns EL, Eldridge MDB, Houlden BA (2004) Microsatellite variation and population structure in a declining Australian hylid Litoria aurea. Molecular Ecology, 13,

1745-1757.

Author contribution: My contribution to this paper included sample collection, laboratory work, data analyses and writing. I wrote the first draft submission of this paper under

Bronwyn Houlden’s supervision. Following her retirement from the University of New

South Wales, Mark Eldridge supervised the resubmission of this paper to Molecular

Ecology.

46 Chapter Three

Chapter 3 Appendix: Allele Frequency Table

Alleles CH BI KIS SAND MAT NA HB NEW K PK INC Locus 4--49 1 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 2 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.167 0.000 3 0.100 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 4 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 5 0.000 0.266 0.000 0.000 0.000 0.065 0.000 0.000 0.000 0.000 0.000 6 0.000 0.021 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 7 0.000 0.702 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 8 0.000 0.000 0.074 0.100 0.286 0.000 0.000 0.000 0.000 0.000 0.000 9 0.000 0.000 0.000 0.033 0.000 0.000 0.000 0.000 0.000 0.000 0.000 10 0.000 0.011 0.056 0.000 0.143 0.130 0.183 0.087 0.029 0.024 0.000 11 0.025 0.000 0.148 0.200 0.143 0.022 0.000 0.000 0.000 0.191 0.023 12 0.025 0.000 0.000 0.033 0.000 0.000 0.012 0.000 0.000 0.000 0.023 13 0.025 0.000 0.519 0.000 0.143 0.065 0.329 0.217 0.250 0.238 0.318 14 0.800 0.000 0.148 0.267 0.286 0.674 0.110 0.326 0.029 0.191 0.000 15 0.025 0.000 0.000 0.267 0.000 0.000 0.012 0.022 0.015 0.024 0.000 16 0.000 0.000 0.019 0.000 0.000 0.000 0.171 0.196 0.662 0.000 0.023 17 0.000 0.000 0.037 0.000 0.000 0.000 0.171 0.130 0.000 0.167 0.591 18 0.000 0.000 0.000 0.000 0.000 0.044 0.000 0.022 0.000 0.000 0.023 19 0.000 0.000 0.000 0.067 0.000 0.000 0.000 0.000 0.000 0.000 0.000 20 0.000 0.000 0.000 0.000 0.000 0.000 0.012 0.000 0.015 0.000 0.000 21 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 22 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 23 0.000 0.000 0.000 0.033 0.000 0.000 0.000 0.000 0.000 0.000 0.000 Locus 5--M 1 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 2 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 3 0.000 0.000 0.000 0.033 0.071 0.000 0.049 0.000 0.043 0.191 0.705 4 0.000 0.000 0.039 0.033 0.143 0.000 0.000 0.000 0.000 0.000 0.000 5 0.028 0.938 0.077 0.333 0.357 0.130 0.134 0.087 0.000 0.000 0.000 6 0.361 0.021 0.058 0.333 0.071 0.326 0.317 0.391 0.143 0.214 0.046 7 0.083 0.000 0.173 0.033 0.000 0.000 0.110 0.000 0.000 0.024 0.000 8 0.111 0.031 0.192 0.133 0.000 0.174 0.171 0.239 0.171 0.405 0.205 9 0.194 0.010 0.212 0.033 0.143 0.283 0.171 0 .283 0.600 0.167 0.046 10 0.056 0.000 0.058 0.033 0.143 0.000 0.000 0.000 0.000 0.000 0.000 11 0.083 0.000 0.058 0.000 0.000 0.000 0.000 0.000 0.029 0.000 0.000 12 0.028 0.000 0.039 0.000 0.071 0.000 0.000 0.000 0.000 0.000 0.000 13 0.000 0.000 0.000 0 .000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 14 0.056 0.000 0.077 0.000 0.000 0.087 0.024 0.000 0.014 0.000 0.000 15 0.000 0.000 0.019 0.033 0.000 0.000 0.000 0.000 0.000 0.000 0.000 16 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 17 0.000 0.000 0.000 0.000 0.000 0.000 0.024 0.000 0.000 0.000 0.000 Locus 2--A 1 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 2 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 3 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 4 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 5 0.191 0.000 0.130 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 6 0.000 0.000 0.000 0.000 0.000 0.000 0.012 0.022 0.000 0.119 0.000 7 0.000 0.000 0.000 0.000 0.000 0.065 0.000 0.000 0.000 0.024 0.000 8 0.095 0.000 0.019 0.033 0.000 0.044 0.012 0.087 0.000 0.000 0.046 9 0.024 0.000 0.130 0.133 0.000 0.000 0.000 0.000 0.029 0.143 0.182

47 Chapter Three

10 0.048 0.000 0.000 0.000 0.071 0.044 0.012 0.000 0.118 0.000 0.000 11 0.119 0.000 0.071 0.100 0.000 0.109 0.085 0.109 0.338 0.000 0.000 12 0.167 0.239 0.241 0.067 0.071 0.239 0.000 0.044 0.059 0.048 0.296 13 0.048 0.228 0.037 0.233 0.214 0.304 0.390 0.435 0.397 0.429 0.364 14 0.000 0.000 0.000 0.200 0.214 0.022 0.037 0.000 0.000 0.214 0.023 15 0.024 0.533 0.278 0.033 0.357 0.000 0.134 0.152 0.044 0.000 0.000 16 0.167 0.000 0.093 0.200 0.071 0.174 0.317 0.109 0.042 0.024 0.091 17 0.119 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 18 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.044 0.000 0.000 0.000 19 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 Locus 4--10 1 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 2 0.000 0.014 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 3 0.000 0.081 0.074 0.100 0.000 0.000 0.013 0.000 0.042 0.000 0.023 4 0.024 0.027 0.019 0.000 0.143 0.087 0.050 0.217 0.250 0.167 0.046 5 0.000 0.027 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 6 0.000 0.000 0.000 0.000 0.000 0.196 0.038 0.044 0.000 0.095 0.000 7 0.071 0.027 0.000 0.000 0.143 0.022 0.013 0.000 0.029 0.000 0.091 8 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.022 0.000 0.000 0.000 9 0.714 0.135 0.482 0.667 0.429 0.630 0.450 0.522 0.485 0.429 0.750 10 0.191 0.676 0.426 0.233 0.286 0.065 0.225 0.109 0.000 0.191 0.046 11 0.000 0.014 0.000 0.000 0.000 0.000 0.200 0.087 0.221 0.119 0.046 12 0.000 0.000 0.000 0.000 0.000 0.000 0.013 0.000 0.000 0.000 0.000 Alleles CS SB GP CU SX LM Q HICKS ALCOX EVANS Locus 4--49 1 0.054 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 2 0.036 0.000 0.000 0.000 0.000 0.667 0.000 0.000 0.000 0.000 3 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 4 0.000 0.000 0.000 0.000 0.000 0.033 0.000 0.000 0.000 0.000 5 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 6 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 7 0.036 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 8 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 9 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.024 0.000 0.000 10 0.054 0.081 0.143 0.067 0.111 0.167 0.000 0.191 0.056 0.040 11 0.054 0.093 0.000 0.050 0.000 0.067 0.000 0.000 0.000 0.000 12 0.000 0.047 0.000 0.033 0.019 0.000 0.053 0.000 0.000 0.000 13 0.071 0.070 0.036 0.183 0.167 0.000 0.105 0.762 0.694 0.880 14 0.018 0.163 0.179 0.033 0.111 0.067 0.684 0.000 0.111 0.040 15 0.054 0.093 0.143 0.033 0.000 0.000 0.000 0.000 0.000 0.000 16 0.357 0.221 0.214 0.367 0.093 0.100 0.158 0.000 0.000 0.000 17 0.196 0.163 0.214 0.083 0.148 0.367 0.000 0.024 0.000 0.000 18 0.036 0.023 0.036 0.000 0.056 0.033 0.000 0.000 0.000 0.000 19 0.018 0.047 0.036 0.100 0.296 0.033 0.000 0.000 0.000 0.000 20 0.000 0.000 0.000 0.050 0.000 0.033 0.000 0.000 0.000 0.000 21 0.000 0.000 0.000 0.000 0.000 0.033 0.000 0.000 0.139 0.040 22 0.018 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 23 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

48 Chapter Three

Locus 5--M 1 0.000 0.000 0.000 0.000 0.000 0.033 0.000 0.000 0.000 0.000 2 0.000 0.163 0.385 0.000 0.000 0.133 0.000 0.000 0.000 0.019 3 0.250 0.093 0.039 0.000 0.056 0.033 0.263 0.000 0.000 0.000 4 0.000 0.000 0.000 0.000 0.000 0.033 0.000 0.000 0.000 0.000 5 0.077 0.198 0.192 0.283 0.204 0.133 0.000 0.357 0.194 0.346 6 0.154 0.023 0.154 0.117 0.037 0.100 0.000 0.595 0.583 0.404 7 0.115 0.151 0.115 0.067 0.019 0.067 0.105 0.000 0.000 0.000 8 0.115 0.244 0.115 0.317 0.148 0.167 0.184 0.024 0.139 0.173 9 0.289 0.081 0.000 0.150 0.500 0.200 0.421 0.024 0.083 0.039 10 0.000 0.023 0.000 0.000 0.037 0.000 0.000 0.000 0.000 0.000 11 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 12 0.000 0.000 0.000 0.000 0.000 0.033 0.000 0.000 0.000 0.000 13 0.000 0.012 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.019 14 0.000 0.000 0.000 0.050 0.000 0.033 0.026 0.000 0.000 0.000 15 0.000 0.012 0.000 0.017 0.000 0.000 0.000 0.000 0.000 0.000 16 0.000 0.000 0.000 0.000 0.000 0.033 0.000 0.000 0.000 0.000 17 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 Locus 2--A 1 0.000 0.000 0.000 0.000 0.000 0.000 0.025 0.000 0.000 0.000 2 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.020 3 0.000 0.000 0.000 0.000 0.000 0.000 0.050 0.000 0.000 0.000 4 0.000 0.034 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.020 5 0.071 0.102 0.107 0.048 0.077 0.067 0.200 0.050 0.139 0.300 6 0.000 0.000 0.000 0.000 0.000 0.067 0.200 0.075 0.167 0.120 7 0.018 0.011 0.000 0.065 0.019 0.033 0.000 0.025 0.000 0.040 8 0.018 0.000 0.000 0.000 0.000 0.000 0.025 0.000 0.000 0.000 9 0.000 0.080 0.214 0.161 0.000 0.133 0.125 0.000 0.000 0.000 10 0.000 0.000 0.000 0.000 0.019 0.000 0.100 0.075 0.028 0.020 11 0.089 0.023 0.036 0.032 0.154 0.100 0.000 0.075 0.028 0.040 12 0.036 0.023 0.000 0.000 0.000 0.067 0.025 0.000 0.028 0.020 13 0.286 0.341 0.286 0.307 0.250 0.300 0.250 0.500 0.500 0.320 14 0.250 0.136 0.250 0.177 0.135 0.133 0.000 0.175 0.083 0.020 15 0.089 0.216 0.071 0.194 0.154 0.100 0.000 0.000 0.000 0.000 16 0.143 0.034 0.036 0.016 0.115 0.000 0.000 0.000 0.000 0.000 17 0.000 0.000 0.000 0.000 0.058 0.000 0.000 0.025 0.000 0.040 18 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.028 0.040 19 0.000 0.000 0.000 0.000 0.019 0.000 0.000 0.000 0.000 0.000 Locus 4--10 1 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.048 0.000 0.000 2 0.054 0.000 0.000 0.000 0.019 0.000 0.000 0.048 0.000 0.019 3 0.071 0.116 0.039 0.097 0.000 0.067 0.000 0.452 0.361 0.481 4 0.411 0.314 0.462 0.307 0.296 0.633 0.000 0.000 0.056 0.000 5 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 6 0.071 0.000 0.000 0.032 0.056 0.000 0.050 0.000 0.000 0.000 7 0.018 0.023 0.000 0.000 0.037 0.000 0.000 0.048 0.028 0.058 8 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 9 0.321 0.500 0.500 0.452 0.574 0.300 0.475 0.381 0.528 0.442 10 0.054 0.047 0.000 0.113 0.019 0.000 0.050 0.024 0.028 0.000 11 0.000 0.000 0.000 0.000 0.000 0.000 0.375 0.000 0.000 0.000 12 0.000 0.000 0.000 0.000 0.000 0.000 0.050 0.000 0.000 0.000

49 Chapter Four

Chapter Four

Phylogenetics and evolution of bell frogs (Litoria aurea Species- Group, Anura: Hylidae) based on mitochondrial ND4 sequences

Abstract

Relationships among Australian tree frogs (family Hylidae) are poorly known. Several

‘species-groups’ within the genus Litoria have been proposed based on morphology and call structure characteristics. Here, species relationships among one of these groups, the bell frogs (Litoria aurea species-group), are investigated using mitochondrial ND4 nucleotide sequence data. Parsimony and maximum likelihood analyses support a clade comprised of the temperate members of the species-group, L. aurea, L. cyclorhyncha, L. moorei, and L. raniformis but failed to support the inclusion of the tropical Australian bell frog (L. dahlii) in this clade. Relationships among the four members of the bell frog clade are correlated with geographical distribution: the south-western Australian bell frogs (L. cyclorhyncha, L. moorei) and the south-eastern Australian bell frogs (L. aurea, L. raniformis) are reciprocally monophyletic. Results also suggest that divergence of these two lineages occurred during the late Miocene, which is consistent with results of previous albumin clock analyses and with more general assertions that much of the major differentiation and radiation of the Australian biota predated the Quaternary.

50 Chapter Four

Introduction

The Australopapuan hylid frog genus Litoria Tschudi, 1838 (subfamily Pelodryadinae) is one of three recognised tree frog genera, including Nyctimystes Stejneger, 1916 and

Cyclorana Steindachner, 1867 native to Australia; with Litoria being the most widely distributed (Tyler & Davies 1993). These genera are thought to have Gondwanan origins

(reviewed in Roberts & Watson 1993) and include frogs that are arboreal, ground dwelling, scansorial (Litoria and Nyctimystes) or fossorial (Cyclorana) (Tyler & Davies 1993).

Relationships among Australian tree frogs have a confused history and remain poorly resolved. The placement of Cyclorana in Hylidae is relatively recent (Tyler et al. 1978) with the genus originally being placed in Myobatrachidae (Parker, 1940). Also, three species originally placed in Cyclorana are now recognised as Litoria (Straughan 1969;

Tyler 1973; Tyler et al. 1978; Cogger et al. 1983), namely L. inermis (Peters, 1867), L. alboguttata (Gunther, 1867) and L. dahlii (Boulenger, 1896). Tyler et al. (1981) proposed that there were four lineages of Australian tree frogs: the terrestrial hylids, the genus

Cyclorana, the Litoria aurea species-group (thought to be closely allied with Cyclorana) and the arboreal hylids. This possible phylogeny of Australian Hylidae was partly supported by micro-complement fixation (MC’F) (Maxson et al. 1982; Hutchinson &

Maxson 1987) and karyological studies (King et al. 1979), all of which provided evidence for a close relationship between Cyclorana and the Litoria aurea species-group. To date no general consensus has been reached on the phylogeny and evolutionary history of

Australian hylids and in particular an explicit phylogeny based on a comprehensive sample of constituent taxa is yet to be achieved.

51 Chapter Four

The composition and relationships within the L. aurea species-group have a muddled history and are still a matter for debate. Courtice and Grigg (1975) revised the species- group and proposed that L. aurea aurea and L. a. raniformis be treated as distinct species,

L. aurea (Lesson, 1829) and L. raniformis (Keferstein, 1867); that L. aurea ulongae and L. a. major be synonymised with L. aurea and L. raniformis respectively; and that the geographically isolated population of L. a. raniformis in the New England Tablelands of northern NSW be recognised as a new species, L. flavipunctata (Courtice & Grigg 1975).

Two Western Australian species, L. cyclorhyncha (Boulenger, 1882) and L. moorei

(Copland, 1957), were also included in the L. aurea species-group (Courtice & Grigg

1975). Although the recognition of L. flavipunctata as a distinct species has not been challenged, the nomenclature is problematic. Cogger et al. (1983) synonymised L. flavipunctata and Hyla castanea Steindachner, 1867 under L. castanea (Steindachner,

1867). This concept was later supported by Thompson et al. (1996) and is currently widely accepted. Thompson et al. (1996) also supported the suggestions of Humphries (1979) and

Watson and Littlejohn (1985) that a southern form of L. castanea also occurred on the

Southern Tablelands of NSW.

Tyler and Davies (1978) defined a number of species-groups within the genus Litoria, recognising seven species in the L. aurea species-group: L. aurea, L. raniformis, L. flavipunctata (= L. castanea), L. moorei, L. cyclorhyncha, L. alboguttata and L. dahlii (see also Tyler et al. 1978). Litoria alboguttata is distributed in central and coastal Queensland, the peripheral coastal margin of the Northern Territory and the western slopes and central plains of northern NSW (Cogger 2000). Litoria dahlii is distributed from the Cape York

52 Chapter Four

Peninsula of Queensland to the north-western parts of the Northern Territory (Cogger

2000).

The inclusion of L. alboguttata in the species-group has been disputed on the basis of

MC’F results (Maxson et al. 1982) which suggest that this species is more closely related to species of Cyclorana than to Litoria. Further investigations confirmed this result (Maxson et al. 1985) and concluded that all species of Cyclorana studied, including L. alboguttata, were genetically closest to, but distinct from, species in the L. aurea species-group.

Therefore, the species-group is currently thought to contain six species: L. aurea, L. cyclorhyncha, L. castanea, L. dahlii, L. moorei, and L. raniformis. Litoria castanea is thought to be extinct, however (R. Wellington pers. comm.). Members of this species group are commonly known as ‘bell frogs’.

Mitochondrial DNA (mtDNA) sequences are widely used for phylogenetic analysis in animals, and several recent studies have employed these data in intra- and interspecific phylogenetic studies of amphibians (e.g. James & Moritz 2000; Schauble et al. 2000;

Sumida et al. 2000; Read et al. 2001). The ND4 gene, encoding NADH dehydrogenase subunit 4, has proven informative in interspecific phylogenetic studies of the frog genus

Limnodynastes (Schauble et al. 2000) and the Litoria citropa species-group (Mahony et al.

2001). It was therefore expected to be evolving at a rate appropriate to provide sufficient information to reconstruct a L. aurea species-group phylogeny.

The objectives of the present study were: (i) to use nucleotide sequences of the mitochondrial ND4 gene to estimate a Litoria aurea species-group phylogeny; (ii) to use

53 Chapter Four

this phylogeny to test existing hypotheses of relationships among the extant species; and

(iii) to identify the sister taxon of L. aurea for outgroup analysis in a study of L. aurea phylogeography (Burns et. al., in prep; Chapter 5.).

Materials and Methods

Taxon sampling

Tissue samples of all extant species of the L. aurea species-group were included in the study; however, particular emphasis was placed on sampling of L. aurea and L. raniformis

(Table 4.1). These two species are sympatric in East Gippsland, Victoria (Fig. 4.1) and are suspected to hybridise in this area, although the evidence is anecdotal and there is no published research that supports this (see Pyke & White 2001 for review). Seven animals that were morphologically indistinguishable from L. aurea (G. Gillespie pers. comm.) were sampled from a section of this putative hybrid zone. For all other species a minimum of two samples were used to help identify any possible contamination or misidentified specimens. Samples of L. genimaculata and L. impura were used as outgroups because an on-going study of Australasian Hylidae suggests a relatively close relationship between L. raniformis, L. genimaculata and the New Guinean species L. impura (Donnellan, Monis &

Wheaton, unpublished data). Litoria castanea was not included in the study because tissue samples suitable for DNA extraction were not available.

Litoria aurea and L. raniformis tissue samples (toe-clips) were taken from adults or juveniles greater than 30 mm with all frogs sampled and released within the immediate vicinity of the ponds surveyed. Toe-clips were stored in 90-95% ethanol. For the

54 Chapter Four

remaining species, frozen tissue samples or DNA were acquired from the South Australian

Museum or the Australian Museum (Table 4.1).

Table 4.1: Samples analysed for mtDNA sequence variation. Species Location Sample No. Haplotype Litoria aurea 1 - Yuraygir National Park, NSW LaureaY1 La1 L. aurea 2 - Broughton Island, NSW LaureaBI1 La2 L. aurea 3 - Kooragang Island, NSW LaureaNC1 La3 L. aurea 4 - North Avoca, NSW LaureaNA12 La4 L. aurea 5 - Homebush brickpit, NSW LaureaHB3 La5 L. aurea 6 - Port Kembla, NSW LaureaPK1 La6 L. aurea 7 - Springbank Rd fire dam, NSW LaureaSC84 La7 L. aurea 8 - Lake Meroo, NSW LaureaFSC3 La8 L. aurea 9 - Captains Flat-Queanbeyan, NSW LaureaQ1 La9 L. aurea 10 - Point Hicks-Cann River, VIC LaureaV1 La10 Hydrid Zone 11 - Morass-Orbost, VIC HZ1 Hz1 Hydrid Zone 11 - Morass-Orbost, VIC HZ2-6 La8 Hydrid Zone 11 - Morass-Orbost, VIC HZ7 Hz2 L. raniformis 12 - Merri-Melbourne, VIC ME1-10 Lr1 L. raniformis 13 - Newport-Melbourne, VIC NE1-4, 6, 10 Lr2 L. raniformis 13 - Newport-Melbourne, VIC NE5, 7-9 Lr1 L. moorei 14 - 22km N Eneabba -Western Flora Caravan park, WA EBU 3859 Lm1 L. moorei Location unknown, WA ABTC07164 Lm2 L. cyclorhyncha Location unknown, WA ABTC07162 Lc1 L. cyclorhyncha 15 - 145k W Ravensthorpe, WA ABTC28280 Lc2 L. dahlii 16 - 16 Km E Karumba, QLD ABTC72773 Ld1 L. dahlii 17 - Burke Dev Rd 13k ENE Karumba T/off, QLD ABTC72848 Ld2 L. genimaculata Mt. Lewis, QLD ABTC16057 Lg1 L. genimaculata Mt. Lewis, QLD ABTC16059 Lg2 L. impura Noru, PNG ABTC43282-3 Li1

Note. Numbered locations refer to Figure 4.1. Museum samples are from the Australian Museum (EBU) and the South Australian Museum (ATBC).

55 Chapter Four

56 Chapter Four

Mitochondrial DNA sequencing

DNA was extracted from tissue samples using a PUREGENE® DNA Isolation Kit

(GENTRA Systems, Minneapolis, USA) following the manufacturer’s instructions. Target

DNA was amplified in 25µl PCR reactions, which were comprised of the following: template DNA (∼50-200 ng), 2.5µl 10x reaction buffer, 3 mM MgCl2, 1 mM dNTPs, 0.5 mM each primer and 0.5 U Tth+ (Biotech Australia, Sydney, Australia) DNA polymerase.

Two primer pairs were used: (i) ‘Limno2’ (Schauble et al. 2000) and ‘ND4’ (Arèvalo et al.,

1994), which amplified an 850 bp product; and (ii) L. aurea specific primers ‘ND4-3’

(forward, 5’-TTAGCAGGAACACTTCTAAAACTAG-3’) and ‘ND4-1’ (reverse, 5’-

GAAAGTGTTTAGCTTTCATCTCTAG-3’), that I designed and which amplified a 750 bp product. Reactions were performed in an MJ Research PTC-100 thermal cycler

(GeneWorks, Hindmarsh, Australia) with the hot lid enabled and the following cycling profile: (1) initial 2 min denaturation at 94 °C, (2) 30 cycles of denaturation (30 sec at 94

°C), annealing (1 min at 50 °C), and extension (45 sec at 72 °C), (3) 5 mins at 72 °C.

Amplified products were visualised by ethidium bromide staining of 1% agarose gels.

Following purification by PEG precipitation, both DNA strands were sequenced using the

BigDye™ Terminator Cycle Sequencing Ready Reaction Kit (Applied Biosystems v3.1,

Foster City, USA) according to the manufacturer’s specifications, and an MJ Research

PTC-100. Sequenced fragments were purified by ethanol precipitation and visualised using an ABI 3730 capillary sequencer (Applied Biosystems, Foster City, USA). For each individual, forward and reverse sequences were evaluated and a consensus derived using

AUTOASSEMBLER™ 1.3.0 (Applied Biosystems, Foster City, USA). Following this,

57 Chapter Four

complete consensus sequences were aligned by eye and trimmed to 524 bp; there were no internal gaps so alignment was unproblematic. Variable sites were identified from the chromatograms. Mitochondrial origin of the sequences was confirmed by translation (using

MacClade 4; Maddison & Maddison 2000) and comparison with other ND4 sequences from Litoria (e.g. GenBank accession numbers AF282598-608).

The correct reading frame of haplotypes was determined with reference to published data

(Mahony et al. 2001). The data were examined for substitutional saturation by plotting pair-wise uncorrected (‘p’) distances against maximum likelihood (ML) distances (model

TrN+I+G; Tamura and Nei 1993) for each of the codon positions. To detect possible effects of substitutional saturation on tree topology, phylogenetic analyses were performed including, and then excluding, saturated positions.

Phylogenetic analyses

Maximum parsimony (MP) and maximum likelihood (ML) analyses were performed using

PAUP* 4b10 (Swofford 1998). Two outgroup taxa (represented by three sequences) were employed to minimise branch lengths leading to outgroups and increase the balance of resulting trees (Smith 1994). In addition, analyses were run without outgroups to determine if the choice of outgroup had a detectable impact on the ingroup topology (Barber 1999).

For the MP analyses, all optimal trees under the Fitch model (all character-state changes equally weighted) (Fitch, 1971) were found by branch-and-bound search. Branch support was estimated using non-parametric bootstrapping (Felsenstein 1985), employing 1000 pseudoreplicates and branch-and-bound search.

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For the ML analyses, the simplest evolutionary model that adequately explained the complete data was determined using the likelihood ratio test, automated using

MODELTEST (Posada & Crandall 1998). This test indicated that the likelihood of a tree under the TrN+I+G model (Tamura & Nei 1993) was not significantly worse than trees optimised under more complex (parameter-rich) models. Therefore, the ML analysis implemented this model in a heuristic search using model parameter values taken from the

MODELTEST analysis. Non-parametric bootstrap analysis was performed using 1000 pseudoreplicates and heuristic search. Additional ML analyses were conducted (using models determined by MODELTEST analysis): 1) excluding the third codon position and using the HKY85+G model (Hasegawa et al. 1985); and 2) excluding outgroups and using the TrN+I model (Tamura & Nei 1993).

The monophyly of the bell frog complex was evaluated directly using the Kishino-

Hasegawa (Kishino & Hasegawa 1989), Wilcoxon signed-rank, and winning-sites (sign) tests, as implemented in PAUP. The shortest trees found in which the bell frogs were constrained to monophyly was tested against the shortest unconstrained trees (Fig. 4.3). A

Shimodaira-Hasegawa (Shimodaira & Hasegawa 1999) test of the constrained tree against the ML tree (Fig. 4.4) was also conducted in PAUP, using the same evolutionary model as the ML phylogenetic analysis, 1000 bootstrap replicates, and a one-tailed test of significance.

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Results

ND4 sequences were obtained from 47 individuals representing seven taxa (including outgroups). Seven of the L. aurea individuals were from the purported L. aurea-L. raniformis hybrid zone located in East Gippsland, Victoria (Fig. 4.1; Table 4.1). All sequences showed close similarity to published hylid ND4 sequences (Mahony et al. 2001), and translations showed them to be free of internal stop codons. The aligned ND4 dataset comprised 524 positions.

The 47 ND4 sequences comprised 23 haplotypes; twelve of these were unique to L. aurea.

The remaining taxa each had two haplotypes with the exception of L. impura, which had one (Table 4.2). All phylogenetic and descriptive analyses were performed on a dataset comprising these 23 haplotypes (GenBank accession numbers AY755415 – AY755437).

Sequence variation

Mean sequence divergence between taxa ranged from 0.6% between L. aurea and the hybrid zone samples, to 26.7% between L. impura and L. genimaculata (Table 4.3). Across all haplotypes, sequence divergence ranged from 0.2% between different L. aurea haplotypes to 26.7% between L. impura and L. genimaculata (data not shown).

Intraspecific variation within L. aurea ranged from 0.2% (haplotypes La1/La5; La4/La5;

La8/La5) to 1.7% (La2/La10) and intraspecific variation within remaining taxa (excluding hybrid zone samples) ranged from 0.2% (L. raniformis, L. dahlii, L. genimaculata) to 1.0%

(L. moorei).

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Table 4.2. Variable sites among ND4 haplotypes (5’ – 3’) for Litoria species. #La1 CCACTTTCTT TCACTGTTCT CTAAAGACAT ATTTTAAATC AACATCTGCT ACCTACTTAT GTCTCACAAC CGTCACGAAT ATTCCAAGCA #La2 ...... C...... T...... #La3 ...... C...... #La4 ...... #La5 ...... #La6 ...... #La7 ...... #La8 ...... #La9 ...... G...... #La10 ...... T...... #Hz1 ...... #Hz2 ...... #Lr1 ...... T...A..T. ....G..T.. ...C....CT GGT.C...TC .T..G.CCG. A...... G. ....GTAG.C ...T.GGA.. #Lr2 ...... T...A..T. ....G..T.. ...C....CT GGT.C...TC .T..G.CCG. A...... G. ....GTAG.C ...T.GGA.. #Lm1 .T..C..... CTG..A.CT...... GT.. G.GC...... TC.ACAT. ...C..CC.. A...... T .A.T.TA...... G.A.. #Lm2 .T..C..... CTG..A.CT...... GT.. G.GC...... TC.ACAT. ...C..CC.. A...... T .A.T..A...... G.A.. #Ld1 ...... CT.C C..TCA..A. .A.G.A.TG. G.GG...GCT ...TC...TA .TTCT..CT. ...A..TT.. .A..TTA.G...... TGA.. #Ld2 ...... CT.C C..TCA..A. .A.G.A.TG. G.GG...GCT ...TC...TA .TTCT..CT. ...A..TT.. .A..TTA.G...... TGA.. #Lc1 .T..C..... CTG..A.CT...... GT.. G.GC...... TC.ACAT. ...C..CC.. A...... T .A.T.TA...... G.A.. #Lc2 .T..C..... CTG..A.CT...... GT.. G.GC...... TC.ACAT. ...C..CC.. A...... T .A.T.TA...... G.A.. #Lg1 T.GT....A. .T..CA..A. TA...AGTGG GCCCGT.... G.T.CAA.AC .A.C.ACC.C .A.C....G. TA..TTAC.. G.CA.G.A.G #Lg2 T.GT....A. .T..CA..A. TA...AGTGG GCCCGT.... G.T.CAA.AC .A.C.ACC.C .A.C....G. TA..TTAC.. G.CA.G.A.G #Li1 TT...A..CA ..G.CTCCAA ..T..AG... GCCC..C..T .G.CCA.... T.TC..CC.C AGT.TTT..T A.C.CT.G.. .CCGT.G.T.

#La1 ATAATATACT ATCTATTAAA AGTGCTAACT TCACATTTTT TATATACACC CTTATTCATT CCGTCACAAT TAAACCTCCC ATTCGCCAAA #La2 ...... T...... C...... #La3 ...... C...... G.. #La4 ...... T...... G...... #La5 ...... #La6 ...... #La7 ...... G...... G...... #La8 ...... G...... #La9 ...... G...... #La10 ...... C...... G...... #Hz1 ...... C....G...... #Hz2 ...... G...... G...... #Lr1 ..G.....T. GC.CT....G ...AT....C ..C.G...... CCC...... CG.C...C T.AC.GTG.. C.GG...... TA..G.. #Lr2 ..G.....T. GC.CT....G ...AT....C ..C.G...... CCC...... CG.C...C T.AC.GTG.. C.GG...... TA.....

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#La1 CCACTTTCTT TCACTGTTCT CTAAAGACAT ATTTTAAATC AACATCTGCT ACCTACTTAT GTCTCACAAC CGTCACGAAT ATTCCAAGCA #Lm1 ..C...... C ...C.C.GG. .A.TT....C C..T.....A .G...... C T.CCT.T... .G...... G..TA..G.T #Lm2 ..C...... C ...C.C.GG. .A.TT....C C..T.....A .G...... C T.CCT.TG.. .G...... G..TA..G.T #Ld1 ..CGCC...C GC.C....T. .AGCT...TA CT.T.AC..A CCA...... T TA..C.T..C .TACT...C. C...... ATT ...... C.C #Ld2 ..CGCC...C GC.C....T. .AGCT...TA CT.T.AC..A CCA...... T TA..C.T..C .TACT...C. C...... ATT ...... C.C

#La1 ATAATATACT ATCTATTAAA AGTGCTAACT TCACATTTTT TATATACACC CTTATTCATT CCGTCACAAT TAAACCTCCC ATTCGCCAAA #Lc1 ..C...... C ...C.C.GG. .A.TT....C C..T.....A .G...... C T.CCT.T... .G...... G..TA..G.T #Lc2 ..C...... C ...C.C.GG. .A.TT....C C..T.....A .G...... CC T.CCT.T... .G...... G..TA..G.T #Lg1 ...G.C...G .C.CC...T. GAAT.CG..C AA.T..CCCC CG..C..G.. T.C...... C .AAC..TGT. C.CCT.G.T. .G.TAA...T #Lg2 ...G.C...G .C.CC...T. GAAT.CG..C AA.T..CCCC CG..C..G.. T.C...... C .AAC..TGT. C.CCT.G.T. .G.TAA.C.T #Li1 GACTC.CCTC TCT.T.C.C. .AACTC.G.C C.C..CC.GA CT..CTGTGA .AA...TT.. T..C.GT.TG C..C.T..T. T.CT..TTGT

#La1 AACCTCTAAC CATTATTATA TCGCAATCTT CAAC #La2 ...... #La3 ...... #La4 G...... #La5 G...... #La6 GG...... #La7 G...... G...... #La8 G...... #La9 G...... #La10 G...... G...... #Hz1 G...... #Hz2 G...... #Lr1 ....C.CCT. .GCC..C... ..AT.G.T.C ...T #Lr2 ....C.CCT. .GCC..C... ..AT.G.T.C ...T #Lm1 .GT....CT. .GC...... AT.....C ...T #Lm2 ..T....CT. .G...... AT.....C T..T #Ld1 ..T.A..TTA T..C..C.C. CTA.TG.GC. T.GT #Ld2 ..T.A..TTA T..C..C.C. CTA.T..GC. T.GT #Lc1 .GT....CT. .GC...... T.....C ...T #Lc2 .GT....CT. .GC...... TAT.....C ...T #Lg1 .GTAC..CTT .TCC.CCC.G GAA.GGC..C .C.. #Lg2 .GTAC..CTT .TCC.CCC.G GAA.GGC..C .C.. #Li1 ...ACTATGT ..C.G.C.CC .TAT...... TGGT

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Among the bell frogs (excluding hybrid zone samples) mean sequence divergence ranged from 0.8% to 20.7%; excluding L. dahlii reduced the maximum divergence to 14.5% (Table

4.3).

Of the 214 variable ND4 sites (23.4% first position, 6.0% second position and 70.6% third position), 184 were potentially parsimony-informative (Table 4.2). Forty-nine transition substitutions (nine first position, two second position and 39 third position) and 18 transversion substitutions (four first position and 14 third position) were observed (mean transition/transversion ratio, 2.8:1). The saturation plots of the first and second codon positions showed approximate linearity, whereas the plot of the third codon positions did not, which indicates saturation in those data (Fig 4.2). Base compositions (A = 27.9%, C =

27.5%, G = 11.6% and T = 33.0%) indicated a slight paucity of guanine, however base bias was unlikely to pose a problem in the present study since biases were not evident between taxa (χ2= 22.9, p = 1.00).

Table 4.3. Matrix (bottom) of uncorrected p-distances between taxa and matrix (above) of corresponding S.E. estimates (bootstrap method 500 pseudoreplicates). 1 2 3 4 5 6 7 8 1 L. aurea 0.002 0.015 0.014 0.014 0.016 0.017 0.018 2 hybrid zone 0.006 0.015 0.014 0.014 0.016 0.017 0.018 3 L. raniformis 0.144 0.146 0.015 0.015 0.017 0.017 0.019 4 L. moorei 0.129 0.129 0.143 0.003 0.016 0.017 0.017 5 L. cyclorhyncha 0.130 0.131 0.145 0.008 0.016 0.017 0.018 6 L. dahlii 0.193 0.195 0.207 0.189 0.191 0.017 0.017 7 L. genimaculata 0.224 0.225 0.202 0.198 0.197 0.225 0.019 8 L. impura 0.240 0.240 0.246 0.232 0.232 0.253 0.267

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Phylogenetic analyses

Fitch parsimony analysis of the data including all codon positions found eight trees of length 382 steps (consistency index excluding uninformative characters, CI = 0.72, retention index, RI = 0.86). The strict consensus tree with bootstrap values is shown in

Figure 4.3. Analysis excluding outgroups (L. genimaculata and L. impura) found eight trees (length = 218, CI = 0.81, RI = 0.91), the strict consensus of which (not shown) was identical to the ingroup topology shown in Figure 4.3. Analysis excluding the third codon positions found four trees (length = 92 steps, CI = 0.74, RI = 0.85). The strict consensus tree (not shown) was similar to Figure 4.3, differing only in there being no resolution within the L. moorei/L. cyclorhyncha clade. Bootstrap support for many of the clades was reduced, however.

ML analysis of the complete data using the TrN+I+G model of nucleotide substitution

(Tamura and Nei 1993) produced one tree, which in many respects was consistent with the

MP tree (Fig. 4.4). For example, in both cases the monophyly of L. aurea is well supported

(MP bootstrap 100%; ML bootstrap 94%) with L. raniformis resolved as its sister group

(MP bootstrap 81%; ML bootstrap 64%), L. moorei and L. cyclorhyncha form a well supported clade (MP bootstrap 100%; ML bootstrap 66%) but are not resolved as distinct groups, and L. dahlii is sister to a clade (MP bootstrap 78%; ML not supported) which includes all other bell frog taxa plus L. genimaculata. The ML and MP trees differ in the positions of the L. moorei/L. cyclorhyncha group and L. genimaculata within this clade.

On the ML tree the L. moorei/L. cyclorhyncha clade is sister to the rest of the bell frog group (excluding L. dahlii) whereas in the MP tree L. genimaculata occupies this position

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(Fig. 4.3). However, ML analysis excluding the third codon position (using HKY85+G) produced a tree that was consistent with the pattern of relationships resolved in the parsimony tree (tree not shown), however, there was no bootstrap support for the placement of L. genimaculata. Analysis of the full data but excluding the outgroups (L. genimaculata and L. impura), using TrN+I, produced a tree that was consistent with the pattern of relationships among ingroup taxa resolved in the MP tree (tree not shown) with strong bootstrap support (> 80%) for all major clades except the L. moorei/L. cyclorhyncha group

(65% bootstrap support).

Phylogenetic analyses failed to support the inclusion of L. dahlii in a bell frog complex

(Figs 4.3; Fig 4.4). Consequently, statistical support for the shortest alternative topology was tested using the Kishino-Hasegawa and non-parametric tests in PAUP. Although the shortest tree found consistent with bell frog monophyly was 7 steps longer than the best unconstrained tree, this constrained tree was not significantly worse according to the

Kishino-Hasegawa and non-parametric tests (Wilcoxon signed-rank test, winning-sites test) at the 5% level. A comparison of the constrained tree and the ML tree produced a similar result using the Shimodaira-Hasegawa test. Therefore, although phylogenetic analysis does not resolve bell frog monophyly using either MP or ML methods, tree topology tests indicate that such a clade cannot be rejected using the available data.

The seven L. aurea individuals collected from the purported L. aurea-L. raniformis hybrid zone exhibited two distinct haplotypes (Table 4.1). As expected phylogenetic analysis strongly grouped these haplotypes with L. aurea haplotypes from outside this zone (MP bootstrap 100% and ML bootstrap 94%).

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Figure 4.3: Strict consensus tree of eight most parsimonious trees of length 382 steps; bootstrap values (1000 pseudoreplicates) are shown if >50%. Bars designate phylogenetic groups discussed in text.

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Figure 4.4: ML tree resulting from estimation using TrN+I+G model of evolution; bootstrap values (500 pseudoreplicates) shown if > 50%. Bars designate phylogenetic groups discussed in text.

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Discussion

L. aurea species-group

Phylogenetic analyses of ND4 sequences failed to support monophyly of the bell frogs: L. dahlii does not cluster with the other sampled members of the group (L. aurea, L. cyclorhyncha, L. moorei and L. raniformis). Although topology tests (Kishino-Hasegawa, non-paramteric methods, and Shimodaira-Hasegawa) indicate that a bell frog clade

(including L. dahlii) cannot be rejected, this failure to confirm a long-held and widely accepted taxonomic concept was unexpected and raises some questions as to its validity.

Litoria dahlii was transferred from Cyclorana based on evidence from morphology and chromosomes which suggested an affinity with the L. aurea species-group (Tyler et al.

1978). This relationship was supported by phylogenetic analysis of MC’F data which placed L. dahlii sister to a clade comprising L. aurea, L. cyclorhyncha, L. moorei and L. raniformis (Maxson et al. 1982; 1985). However, parsimony analysis of the ND4 sequence data does not support this placement, suggesting instead that L. genimaculata is sister to the

L. aurea clade (78% bootstrap support; Fig. 4.3). ML analysis resolved L. genimaculata within the L. aurea clade (Fig. 4.4) without a high level of bootstrap support. The geographical distribution of L. dahlii also distinguishes it from the other bell frogs. Litoria dahlii is a tropical frog, distributed from north-eastern Western Australia, across the northern part of the Northern Territory and in the western portion of the Cape York

Peninsula (Fig. 4.1). The other bell frogs, however, are found in the temperate zone of south-western (L. cyclorhyncha, L. moorei) and south-eastern (L. aurea, L. raniformis)

Australia (Fig. 4.1). Litoria genimaculata is found in eastern Queensland (Cogger 2000).

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These results suggest that L. dahlii may not be a bell frog, but mitochondrial data provide information on maternal genealogy only. The possibility exists that this species may have arisen via ancient hybridisation with the paternal parent being a member of the bell frog lineage. A phylogenetic analysis of nuclear data would be required to evaluate this hypothesis. Other potential factors, which may also account for our results include rapid diversification, the use of distant outgroups and low signal strength.

L. aurea - L. raniformis clade

Monophyly of both L. aurea and L. raniformis is supported by all analyses, validating the current taxonomy of these two species. A sister group relationship between them is also strongly supported (Fig. 4.3; Fig. 4.4), concordant with MC’F studies which show the albumins of L. aurea and L. raniformis are almost indistinguishable and quite distinct from those of other bell frogs (Maxson et al. 1982). These two species are the only extant members of the bell frog group which are found in south-eastern Australia and they are thought to hybridise where they are sympatric in eastern Victoria, although there is little evidence to support this (Fig. 4.1) (reviewed in Pyke & White 2001). In view of the close similarity of their albumins and their reported ability to hybridise, the mean ND4 sequence divergence between the two species was surprisingly high (14.4 %; Table 4.3) and analysis suggests the species’ are phylogenetically distinct (Fig. 4.4).

Analysis of ten samples from throughout the L. aurea range revealed little phylogenetic structure (Fig. 4.3; Fig. 4.4), probably a result of the low sequence divergence observed among the samples (0.2−1.7%; data not shown). The ND4 locus is not overly informative

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at this level in the bell frogs. A more detailed study on L. aurea phylogeography incorporating an additional mitochondrial gene (cytochrome oxidase 1) is currently underway (Burns et al., in prep; Chapter 5).

L. cyclorhyncha - L. moorei clade

Phylogenetic analyses support the monophyly of the south-western Australian bell frogs L. cyclorhyncha and L. moorei (MP bootstrap100%, ML bootstrap 66%; Fig. 4.3 and Fig.

4.4), a relationship also supported by MC’F data (Maxson et al. 1982). However, reciprocal monophyly of L. moorei and L. cyclorhyncha was not supported by the analyses

(Fig. 4.3; Fig. 4.4) and there was a much lower level of sequence divergence observed between these two taxa (0.8%; Table 4.3) compared with that observed between the eastern bell frogs, L. aurea and L. raniformis (14.4%, Table 4.3). These results suggest that the

Western Australian radiation may have occurred much more recently than the eastern

Australian radiation, assuming rates of nucleotide subsitution are relatively comparable between the two lineages. Alternatively, species barriers between L. cyclorhyncha and L. moorei may be relatively permeable, allowing some gene flow between the species to occur, resulting in introgression of the mitochondrial genome of one into the other. Further work on the phylogeography of these species using more rapidly evolving DNA markers may help to distinguish these hypotheses.

Divergence of south-eastern and south-western species

A number of pairs of closely related frog species found in south-eastern and south-western

Australia have been recognised based on external morphology, male call structure and

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MC’F comparisons of serum albumin (Main 1957, 1968; Littlejohn 1961, 1967; Lee 1967;

Roberts & Maxson 1985). These species pairs include the south-eastern bell frogs (L. aurea and L. raniformis) and the south-western bell frogs (L. cyclorhyncha and L. moorei).

The time of divergence of the eastern and western groups has been a matter of debate.

Early workers suggested that this divergence occurred during the Pleistocene (e.g. Main et al. 1958; Littlejohn 1961, 1967; Lee 1967; Main 1968), when postulated periods of high rainfall and low sea levels correlated with ice ages (Main et al. 1958; Littlejohn 1961), and which may have allowed frog migration across southern Australia (see also Roberts &

Maxson 1985).

The Pleistocene hypothesis was later disputed (Roberts & Maxson 1985) on the basis of more recent evidence that indicated that rather than there being periods of increased rainfall and lowered sea levels, glacial maxima during the Pleistocene were probably periods of severe aridity in Australia. The Nullarbor is an exposed limestone plain with generally poor soil development and there is little evidence of significant surface water even during the relatively moist interglacial periods (Lowry & Jennings 1974). Therefore, the Nullarbor was likely unsuitable for frog migrations during the Pleistocene. The most recent period that would have allowed for east-west migration (i.e. sustained humid climates) was probably the late Miocene, declining into the early Pliocene (Roberts & Maxson 1985; see also Bowler 1982). This alternative hypothesis was tested by comparing serum albumins of southeastern and southwestern frog species pairs using an albumin molecular clock

(Roberts & Maxson 1985). The results suggested that there were at least two periods of connection between south-eastern and south-western frog faunas: the Oligocene, and the

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late Miocene - early Pliocene. The separation of L. moorei and L. raniformis was estimated to have occurred between 8.3 and 9.0 MYBP (Roberts & Maxson 1985).

Molecular dating of divergences is contentious (e.g. Hoelzer et al. 1998; Hewitt 1999) but can provide useful evidence on the evolutionary history of lineages particularly where the fossil record is inadequate. I tested the above hypothesis using the rate of sequence change estimated for Bufo bufo mtDNA of 0.69% per lineage per million years (Macey et al.

1998). This same approach was taken recently by Schauble and Moritz (2001) to estimate the dates of major divergences within the eastern Australian myobatrachid frogs

Limnodynastes peronii and Lim. tasmaniensis. Using this estimate, the results (based on average K2P distance, consistent with Schauble & Moritz 2001) suggest that south-eastern and south-western bell frogs diverged approximately 10.8 MYBP (± 1.2 MYBP). This estimate is greater than that of Roberts & Maxson (1985) but still supports a mid to late

Miocene split, which is consistent with suggestions that much of the major differentiation and radiation of the Australian biota predated the Quaternary (Nix 1982; Barendse 1984;

McGuigan et al. 1998; Schauble & Moritz 2001). This estimate, however, should be interpreted with caution because the rate of sequence divergence estimated by Macey et al.

(1998) was not based on the ND4 gene but on an approximate 1 kbp of mtDNA from the

ND1, tRNAIle, tRNAGln, tRNAMet, ND2 region; the rate for this section of mtDNA may not be comparable to the rate of sequence divergence for ND4.

Conclusions

The results fail to support the current notion of the bell frogs: a clade comprised of the temperate species L. aurea, L. raniformis, L. moorei, and L. cyclorhyncha is strongly

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supported, but the tropical L. dahlii is not confirmed as a member of this group. Within this clade, the eastern (L. aurea, L. raniformis) and western (L. moorei, L. cyclorhyncha) species are reciprocally monophyletic, with divergence of these two lineages estimated to have occurred during the late Miocene. The results presented here will be useful in directing future studies of the bell frogs and of phylogenetic relationships within Hylidae more generally.

Publication Information

This chapter has been submitted to Molecular Phylogenetics and Evolution for consideration of publication.

Reference: Burns EL, Crayn DM (submitted) Phylogenetics and Evolution of Bell Frogs

(Litoria aurea Species-Group, Anura: Hylidae) Based on Mitochondrial ND4 Sequences.

Molecular Phylogenetics and Evolution.

Author contribution: My contribution to this paper included sample collection, laboratory work, data analyses and writing. My co-supervisor Darren Crayn assisted in the compilation of this paper. Darren’s help and guidance in mastering PAUP and phylogenetics more generally was invaluable.

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Chapter Five

Low phylogeographic structure in a widely spread endangered Australian frog Litoria aurea (Anura: Hylidae)

Abstract

The green and golden bell frog (Litoria aurea) has a widespread distribution in south- eastern Australia. The species’ range, however, is now highly fragmented and remaining populations are predominately isolated and restricted to the coastline. Previously, the range extended further inland and L. aurea was considered common. Here I report a study designed to identify the phylogeographic and conservation genetic parameters of L. aurea.

Mitochondrial DNA sequences (COI and ND4) were examined from 263 individuals sampled from 26 locations using both phylogenetic and population analyses. Despite a general consensus that amphibians are highly structured, I found no phylogeographic divisions within this species, however there was significant structure amongst extant populations (FST = 0.385). Patterns of haplotype relatedness, high haplotypic diversity

(mean h = 0.547) relative to low nucleotide diversity (mean = 0.003) and mismatch distribution analysis supported a Pleistocene expansion hypothesis with continued restricted dispersal and gene flow. I conclude that the genetic structure of the species may permit

‘well managed’ intervention to mediate gene flow amongst isolated populations and provide some guidelines for the implementation of such conservation strategies.

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Introduction

An understanding of the evolutionary history and genetic structure of species is of critical importance when designing conservation strategies. This knowledge allows for the definition of management units (e.g. Moritz 1994a) and the design of strategies aimed at minimising genetic erosion whilst preserving genetic distinctiveness (Hedrick 2001).

Historical and contemporary processes shape the genetic structure of species and therefore a combination of analyses targeted at different temporal scales is needed to help delineate not only genetic structure but also the historic and contemporary processes that have shaped it (Godoy et al. 2004; Althoff & Pellmyr 2002).

Cyclical climatic fluctuations, particularly during the Pleistocene, have been highly influential in shaping the current distribution and population genetics of many plants and animals (Hewitt 2000). During the colder, more arid cycles of glacial maxima mesic habitats retracted into refugia, which is believed to have fostered allopatric divergence between isolated populations (Avise 2000). In the Northern Hemisphere a major feature of the Quaternary was the descent and retreat of large ice sheets, and numerous phylogeographic studies have now illustrated the effect of this period on the genetic structure of current biota (reviewed in Hewitt 2000). In contrast, Australia experienced limited glaciation (Markgraf et al. 1995; McKinnon et al. 2004) but nevertheless glacial- interglacial fluctuations in sea level, rainfall, humidity and temperature caused significant changes in vegetation communities resulting in complex patterns of habitat fragmentation, expansion and contraction across the continent (Kershaw 1981; Nix 1982; Schauble &

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Moritz 2001). Typically, mesic habitats retracted to coastal regions and previous studies in coastal Queensland (QLD) and far northern New South Wales (NSW) have shown that rainforest restricted species show intraspecific genetic structuring strongly influenced by historical contractions of rainforests in response to climate change (Joseph et al. 1995;

McGuigan et al. 1998; Schneider et al. 1998).

Relative to rainforest species little is known about the phylogeography of other coastal south-eastern Australian fauna, especially terrestrial vertebrates. Addressing this deficiency, Schauble and Moritz (2001) recently investigated the phylogeography of two frog species Limnodyastes peronii and Lim. tasmaniensis and compared resulting phylogenies to an initial study in Litoria fallax (James & Moritz 2000). However, the sampling effort in NSW was very limited in both these studies. Despite this, Schauble and

Moritz (2001) did detect a phylogenetic break positioned somewhere south of the

McPherson Range (at the NSW/QLD border) and north of Sydney. James and Moritz

(2001), however, did not find a break in this area for L. fallax.

It is difficult to predict what phylogeographic structure may be found in L. aurea.

Typically amphibians are expected to show pronounced phylogeographic structure because they are small bodied and presumed to be relatively immobile (Avise 2000; Palo et al.

2004). However, limited phylogeographic structure has been detected in frog species (or other terrestrial vertebrates) south of the McPherson Range and from what is known of L. aurea (see Burns et al. 2004; Chapter 3) little phylogeographic structure may be expected.

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L. aurea inhabits wetlands, open forest and grassland habitat. Breeding sites characteristics vary but generally consist of still, relatively unshaded water bodies low in salinity (Pyke et al. 2002). The species is thought to have a high dispersal capability with recorded movement in excess of 10km from known breeding ponds (Pyke & White 2001) but most frequent capture-recapture data is within a 500m radius (Christy 2001; Pyke & White

2001). A previous microsatellite study detected significant population structuring throughout the species range, however the authors also found evidence of weak genetic structuring within areas of continuous habitat (Burns et al. 2004; Chapter 3).

Historically the distribution of L. aurea extended from northern NSW, as far as Ballina, to

East Gippsland in Victoria, with inland populations as far west as Bathurst and Tumut

(Goldingay 1996; White & Pyke 1996). Through to the early 1980s L. aurea was considered common but since has undergone dramatic declines with disappearances reported from 80% of its former range (White & Pyke 1996 as cited in Pyke et al. 2002).

Remaining populations are mostly fragmented and typically restricted to the coastline, extending from Yuraygir National Park (northern NSW) to East Gippsland (Victoria); the two most inland populations are from the Southern Tablelands near Queanbeyan and the

Upper Hunter near Mt. Owen (A. White and R. Wellington pers. com.; see also Pyke &

White 2001; Figure 5.1; Table 5.1). Currently L. aurea is listed as ‘Vulnerable’ nationally

(Environmental Protection and Biodiversity Conservation Act 1999) and ‘Endangered’ in

New South Wales (Threatened Species Conservation Act 1995).

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Table 5.1: Summary of samples used in this study. Geographical coordinates of sampled locations in Australian Map Grid units (zone 56 Easting and Northing) and the number of individuals sampled (n) per location are detailed. Sample location abbreviations are given in parentheses. Sample Location Region AMG AMG n Easting (m) Northing (m) Yuraygir National Park (YNP), NSW Upper North Coast 523600 6687400 2 Crescant Head (CH), NSW Upper North Coast 501009 6558000 13 Broughton Island (BI), NSW Lower North Coast 436400 6391100 15 Kooragang Island (KIS), NSW Hunter 379700 6363500 10 Sandgate (SAND), NSW Hunter 378586 6362935 10 Maitland (MAT), NSW Hunter 343947 6409566 7 Upper Hunter (UH), NSW Hunter 321857 6412214 2 North Avoca (NA), NSW Central Coast 354488 6296251 11 Homebush (HB), NSW Sydney 321700 6253700 25 Newington (NEW), NSW Sydney 321500 6255500 18 Enfield Brickpit (EB), NSW Sydney 321242 6247237 2 Rosebery (R), NSW* Sydney 333569 6247461 5 Arncliffe (A), NSW** Sydney 329250 6242800 9 Kurnell (K), NSW Sydney 331300 6233700 10 Port Kembla (PK), NSW Illarwarra 306800 6181350 19 Incitec-Port Kembla (INC), NSW Illarwarra 307840 6182781 5 Coomonderry Swamp (CS), NSW Shoalhaven 291833 6145613 10 Brundee Swamp (SB), NSW Shoalhaven 286168 6132202 16 Greenwell Point (GP), NSW Shoalhaven 292100 6134400 10 Culburra (CU), NSW Shoalhaven 296416 6131281 9 Sussex Inlet (SX), NSW Shoalhaven 279300 6105600 10 Lake Meroo (LM), NSW Shoalhaven 262947 6070124 10 Captain-Flat Queanbeyan (Q), NSW Southern Tablelands 171196 6074574 10 Point Hicks-Cann River (PH), VIC North East Victoria 162147 5846114 10 Alcox-Bemm River (AX), VIC North East Victoria 145846 5814335 10 Evans-Bemm River (EV), VIC North East Victoria 146101 5815053 5

* All captive individuals held at Taronga Zoo, Sydney.

**5 samples from captive individuals held at Taronga Zoo, Sydney

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Here, a comprehensive intraspecific phylogeny of L. aurea is generated. Extant populations are examined from throughout the species’ current range and the resulting pattern of haplotype relatedness, in conjunction with demographic analyses, is used to infer the recent evolutionary history of the species. Population structure is also analysed to further investigate current genetic structuring and the history of dispersal. Finally, the findings are used to make conservation recommendations.

Materials and Methods

Tissue sampling and outgroup choice

Litoria aurea tissue samples (toe clips) were collected from 263 individuals from 26 locations. Sampling was extensive, covering nine regions from throughout the species’ range from the far north coast of New South Wales (NSW) to East Gippsland in Victoria

(Fig. 5.1; Table 5.1). These geographical regions were proposed by the NSW National

Parks and Wildlife Service (NPWS) for conservation management (NSW NPWS 2002).

In the phylogenetic analyses, Litoria raniformis was used as the outgroup taxon based on the findings of Burns and Crayn (submitted; Chapter 4) which demonstrated that L. aurea and L. raniformis are sister taxa.

Mitochondrial DNA extraction, amplification and sequencing

Total genomic DNA was extracted using a standard phenol-chloroform extraction protocol

(Sambrook et al. 1989), or a High Pure PCR Template Preparation Kit (Roche Applied

Science, Australia) following the manufacturer’s instructions.

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Two protein-coding genes cytochrome oxidase 1 (COI) and NADH dehydrogenase subunit

4 (ND4) were chosen for sequencing because both had previously proven informative in studies of frog phylogeography (James & Moritz 2000; McGuigan et al. 1998; Schauble et al. 2000; Mahony et al. 2001). These genes were therefore expected to be evolving at rates appropriate to provide sufficient information to investigate phylogenetic relationships among L. aurea samples. Two genes were considered necessary because initial analyses of

ND4 indicated comparatively low levels of variation in L. aurea (Burns & Crayn, submitted; Chapter 4).

COI was amplified for ten L. aurea and two L. raniformis samples using primers COX and

COY described in Schneider et al. (1998). These sequences were then used to design internal L. aurea specific primers COI-smallF (Forward primer 5’-

TTGGCCTGCTAGGTTTTATTG-3’) and COI-smallR (Reverse primer 5’-

CAAATACGGCCCCCATAGAT-3’), which amplified an approximate 330bp product.

ND4 was amplified using species specific primers described in Burns & Crayn (in press;

Chapter 4. The target regions for both COI and ND4 were sequenced for all 263 L. aurea sampled. Target DNA was usually amplified in 25µL PCR reactions, which were comprised of the following: template DNA (∼50-200 ng), 2.5µL 10x reaction buffer, 3 mM

+ MgCl2, 1 mM dNTPs, 0.5 mM each primer and 0.5 U Tth (Biotech Australia) DNA polymerase. Most often the following MJ Research PTC-100 ‘step down’ thermal cycling profile was employed with the hot lid enabled: (1) initial 2 min denaturation at 94 °C, (2)

37 cycles of denaturation (30 sec at 94 °C), annealing (1 min at 60°C – 2 cycles; 58°C - 2 cycles; 56°C - 10 cycles; 54°C - 23 cycles), and extension (45 sec at 72 °C), (3) 5 mins at

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72 °C. Amplified products were visualised by ethidium bromide staining of 1% agarose gels.

Following purification by PEG precipitation, sequencing reactions were performed in both directions using the BigDye™ Terminator Cycle Sequencing Ready Reaction Kit (Applied

Biosystems v3.1, Foster City, USA) according to the manufacturer’s specifications, on a

MJ Research PTC-100 (GeneWorks, Hindmarsh, Australia). Sequencing reactions were purified by ethanol precipitation and visualised using an ABI 3730 capillary sequencer

(Applied Biosystems v3.1). For each individual forward and reverse sequences were evaluated and a consensus derived using AUTOASSEMBLER™ 1.3.0 (Applied

Biosystems).

Sequence alignment and haplotype designation

Consensus sequences were aligned by eye and trimmed to 324bps (COI) and 524pbs

(ND4); there were no internal gaps so the alignment for both genes was not problematic.

Variable sites were identified from the chromatograms and sequences translated (using

MacClade version 4.0 Maddison & Maddison 2000) and aligned in accordance with previously deposited Litoria sequences in GenBank (for example COI –AF198261-347, published in James & Moritz 2000; ND4 - AF282598-608, published in Mahony et al.

2001). Haplotypes for each gene and both genes combined were identified using MacClade version 4.0. Sequence data for both genes was assumed to be mitochondrial and not nuclear homologs because of the absence of stop codons, the bias against guanine, a notable third codon bias and an overall conservation of codons among the 263 ingroup samples and two outgroup samples. To test for substitutional saturation, plots of pair-wise uncorrected

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(‘p’) distances against maximum likelihood (ML) distances (model TrN+I; Tamura and Nei

1993) were generated for the third codon position of both genes.

Phylogenetic analyses

Phylogenetic relationships among mtDNA haplotypes of COI, ND4 and combined data were estimated under maximum parsimony (MP), maximum-likelihood (ML) and neighbour-joining (NJ) criteria; analyses were performed using PAUP* 4.0 (version b10)

(Swofford 1998). MP analyses were conducted using heuristic searches under the Fitch model (in which all character-state changes are equally weighted) (Fitch 1971) with tree-bi- section-reconstruction (TBR) branch swapping; 100 random taxa addition replicates were also run to search for multiple islands of optimal trees (Maddison 1991). For ML and NJ analyses I employed MODELTEST (Posada & Crandall 1998) to select the simplest model of character evolution (and associated model parameter values) that adequately explained the data, as determined by the hierarchical likelihood ratio test. For ML analysis, a heuristic search was employed with 10 random taxa addition replicates, employing TBR branch swapping.

For all resulting phylogenies, non-parametric bootstrap analyses (1000 pseudoreplicates for

MP, NJ and single gene ML analyses; 500 pseudoreplicates for combined data ML analyses) were performed to assess relative node support (Felsenstein 1985). In addition,

MP and NJ analyses were repeated (for the combined dataset only) excluding outgroup samples to further assess ingroup topology.

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Population analyses

All population-based analyses were performed using the combined sequence data for L. aurea. Haplotype and nucleotide diversity along with all other analyses were calculated using Arlequin 2.0 (Schneider et al. 2000); and where appropriate the K2P model (Kimura

1980)ZLWKJDPPDFRUUHFWLRQ . ZDVFKRVHQ(YLGHQFHRIJHQHWLFVWUXFWXUHZDV assessed with consideration of molecular distance (-ST) and for haplotype frequencies only

(FST). Under both conditions a number of different methods were employed: (1) analysis of molecular variance (AMOVA; Excoffier et al. 1992); (2) FST-ST values between pairs of populations and regions; (3) an exact test for population differentiation (Raymond &

Rousset 1995a); and (4) isolation by distance using linearised pairwise differentiation

(FST/-ST) and geographical distance (ln km). For AMOVA, only sites with five or more samples were used and significance was tested using 20,000 permutations. For pairwise

FST-ST and exact tests, only sites with five or more samples were used for population- based analyses but all samples were used for region-based analyses, and significance for these was tested using 10,000 permutations. The significance of the log-linear association for isolation by distance analysis was tested using Mantel’s procedure (Mantel 1967) with

10,000 permutations of the data, in GENEPOP (Raymond & Rousset 1995b).

A minimum-spanning network (MSN) (Excoffier & Smouse 1994) was also constructed using all samples to depict phylogenetic, geographical and potential ancestor-descendant relationships among haplotypes (Eizirik et al. 2001). Networks were constructed with a

.3 . PDWUL[ DQG DQ DEVROXWH GLIIHUHQFH Patrix using the program MINSPNET included in Arlequin 2.0 package.

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Inference of past population expansion events was tested using mismatch distribution

(Rogers & Harpending 1992; Rogers 1995; Schneider & Excoffier 1999), Tajima’s D test for selective neutrality (Tajima 1989a; Tajima 1989b) and Fu’s Fs (Fu 1997) which detects excesses of low-frequency alleles in growing populations as compared to the expected number in stationary populations. Each of these analyses was conducted using the total sample combined in Arlequin 2.0. I also estimated the time of demographic expansion by

WKH PRGH RI PLVPDWFK GLVWULEXWLRQ 2 µt where t is the expansion time in number of generations and µ is the mutation rate per generation for the whole sequence (Rogers 1995).

I used a generation time of 18 months (Pyke & White 2001) and the rate of sequence change estimated for Bufo bufo mtDNA of 0.69% per lineage per million years (i.e. pairwise divergence rate of 1.38% per million years) (Macey et al. 1998), see also Burns and Crayn (submitted; Chapter 4) for discussion of limitations.

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Results

COI phylogeny

Sequence variation. The COI dataset consisted of 324 bp of sequence from 263 L. aurea samples (ingroup) and two L. raniformis samples (outgroup). A total of 19 ingroup haplotypes and one outgroup haplotype were observed (GenBank accession numbers

AY835886-AY835905). The geographical spread of these haplotypes for L. aurea is shown in the Appendix. Levels of sequence divergence among ingroup samples ranged from 0.3%-1.5% (average 0.8% ± SE 0.002). There were 13 variable sites and of these six were parsimony informative. Intraspecific sequence divergence was low compared to previous studies of Litoria species employing this gene where up to 12.1% (James &

Moritz 2000) and 6.8% (McGuigan et al. 1998) were detected.

Across the complete dataset there were 25 variable sites (4% first position and 96% third position) of which 9 were parsimony informative; levels of sequence divergence ranged from 0.3%-8.6%, with a mean sequence divergence between ingroup and outgroup haplotypes of 7.9% ± SE 0.013. Transversions were only detected when comparing ingroup to outgroup sequences; mean pairwise ti/tv ratios = 5.43 (excluding comparisons where no transversions were detected). Base composition (A = 24%, C = 22%, G = 19% and T = 35%) indicated base G was slightly depauperate and base T bias. Saturation plots of the third position (data not shown) showed no evidence of saturation (i.e there was a linear relationship between exact pairwise distance and ML corrected distance).

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Phylogenetic analyses. Very weak phylogenetic signal was detected for all COI phylogenetic analyses (MP, ML and NJ). In each case consensus trees were poorly resolved with low bootstrap support [data not shown; 11526 most parsimonious trees, 53 steps, CI (excluding uninformative characters) = 0.321, RI = 0.000; ML and NJ analysis under the TrN+I model of evolution (Tamura & Nei 1993)]. Of these analyses, the NJ tree was the more resolved but still was poorly supported (data not shown). This, however, is not unexpected given that a NJ approach produces only one tree.

ND4 phylogeny

Sequence variation. The ND4 dataset consisted of 524 bp of sequence from 263 L. aurea samples (ingroup) and two L. raniformis samples (outgroup). A total of 26 ingroup haplotypes and two outgroup haplotypes were observed (GenBank accession numbers

AY755415-27; AY835906-21). The geographical spread of ND4 haplotypes for L. aurea is detailed in the Appendix. Levels of sequence divergence among ingroup samples ranged from 0.19%-2.1% (average 0.96% ± SE 0.002). There were 28 variable sites and of these

15 were parsimony informative. Similarly to COI, intraspecific sequence divergence in

ND4 was low compared to a previous study of two Limnodynastes species employing this gene where up to 17% sequence divergence was detected. However, the maximum divergence was greater than that reported for an elapid snake Hoplocephalus stephensii

(1.7%; Keogh et al. 2003).

Across the complete dataset there were 90 variable sites (12.2% first position, 4.4% second position and 83.3% third position) of which 81 were parsimony informative; levels of sequence divergence ranged from 0.19%-15.1%, with a mean sequence divergence between

88 Chapter Five

ingroup and outgroup haplotypes of 14.35% ± SE 0.015. Mean pairwise ti/tv ratios = 7.51

(excluding comparisons where no transversions were detected) and as with COI base composition (A = 28.47%, C = 27.09%, G = 11.14% and T = 33.3%) indicated base G was slightly depauperate and a base T bias. Saturation plots of the third position (data not shown) indicated there was no evidence of saturation.

Phylogenetic analyses. Phylogenetic analyses (MP, ML and NJ) of ND4 haplotypes revealed greater signal and resolution than analyses of COI but resulting trees were still poorly supported (data not shown; eight most parsimonious trees, 103 steps, CI = 0.894, RI

= 0.927; ML and NJ analysis under the TrN+I model).

Combined data phylogeny

Sequence variation. All unique COI and ND4 sequences (848 bp) were combined, resulting in a total of 51 ingroup haplotypes (Table 5.2) and two outgroup haplotypes. The geographical distribution of the combined data haplotypes across regions for L. aurea is shown in Table 5.3. Across all data there were 125 variable sites of which 113 were parsimony informative. Levels of sequence divergence ranged from 0.12%-12.3%, with a mean sequence divergence between ingroup and outgroup haplotypes of 11.99% ± SE

0.011. Across ingroup sequences there were 41 variable sites and 25 sites were parsimony informative; levels of sequence divergence ranged from 0.12%-1.3% (average 0.65% ± SE

0.001).

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Table 5.2: Variable sites in 848 bases of Green and Golden Bell Frog mitochondrial DNA from ND4 and COI genes. Numbers (N) at the end of each haplotype (HAP) indicates the frequency of that haplotype. The geographical distribution of these haplotypes across regions is given in Table 5.3 HAP ND4 (524bp) COI (324bp) N HAP ND4 (524bp) COI (324bp) N H 1 CTCCAACCATACAACCTAACAGAAAAAA CCATCATCTTACT 2 H 1 CTCCAACCATACAACCTAACAGAAAAAA CCATCATCTTACT H 2 T...... T...... G. ....T...... 2 H 28 T...... T.G.....G..G...... G...... C 2 H 3 ...... G...... 9 H 29 ...... G...G...... G.T..... 1 H 4 ...... A...... G...... 2 H 30 ...... G...G...G...... 1 H 5 ...T...... T...... G...... 15 H 31 ...... C...... G...G...... 5 H 6 ...... G...G...... 36 H 32 ...... G...G. T..C...... 1 H 7 T...... T...... T....G..G..G...... G.T..... 41 H 33 T...... T...... T...... G..G...... G.T..... 1 H 8 T...... T...... G..G...... G.....T. 7 H 34 T...... T...... T....G..G..G. ....T...... 1 H 9 TC...... T...... G..G...... G.....T. 7 H 35 TC...... T...... G..G. ....T...... 1 H 10 T...... T.G.....G..G. .T...G...... 4 H 36 TC...... T...... G..G...... 1 H 11 T...... G.T...... G..G...... GC..C... 9 H 37 T...... T...... T....G..G..G...... G.T...T. 1 H 12 T...... T...... T....G..G..G...... 2 H 38 T...... G.T...... G..G...... G.T..... 1 H 13 T...... T...... G..G...... 2 H 39 T..T...... T...... G...... G.T..... 1 H 14 T...... T...... G..G...... G...... 15 H 40 T...... T...... T....G..G..G...... G...... 1 H 15 T...... T...... G..G. .T...G.....T. 5 H 41 T...... G.T...... G..G. T....G...C... 1 H 16 T...... T...... GG.G...... G...C... 3 H 42 T...... T...... G..G. T....G...C... 1 H 17 T...... T...... G..G...... G...C... 4 H 43 T.T....T...... T....G..G..G. T....G.T..... 1 H 18 T...... G.T...... G..G...... G...C... 15 H 44 T...... T...... T....G..G..G. ..G..G.T..... 1 H 19 T.....T..C.....T.G...A.G..GG .....G...... 3 H 45 T...... T...... GG.G. T....G...C... 1 H 20 T...... T.G.....G..G. ..G..G...... 4 H 46 T...... T...... G..G. T....G...... 1 H 21 T...... G....T.G.....G.GG...... G...... 4 H 47 T...... T...... T....G..G..G...... G.TC.... 1 H 22 T...... T.G.....G..G...... G...... 15 H 48 T....T.T...... T....G..G..G...... G.T..... 1 H 23 T.....T..C.T...T.G...A.G..GG .....G...... 3 H 49 T...... T.G.....G..G...... G...C... 1 H 24 T...G...... G.T...... G..G...... G...C... 8 H 50 T...... T...... G..G...... G.T..... 1 H 25 T...G...... G.T...T...G..G...... G...C... 3 H 51 T...... TT.G.....G..G...... G...... 1 H 26 T.....T..C.....T.G.....G..GG .....G...... 9 H 27 T...... T.G.....G..G...... G....G.. 4

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Table 5.3: Geographical distribution of 51 L. aurea haplotypes (combined data) summarised across regions. Haplotype Region H H H H H H H H H H H H H H H H H H H H H H H H H H 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 Upper North Coast 2 2 9 2 Lower North Coast 15 Hunter 22 Central Coast 8 2 Sydney 6 17 5 7 4 8 2 2 5 5 Illawarra 3 8 2 2 7 Shoalhaven 19 2 1 2 1 3 8 3 4 4 6 3 1 Southern Tablelands 7 3 Northeast Victoria 9 9 Haplotype Region H H H H H H H H H H H H H H H H H H H H H H H H H 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 Upper North Coast Lower North Coast Hunter 1 1 5 Central Coast 1 Sydney 1 1 1 1 1 1 1 1 Illawarra 1 1 Shoalhaven 1 1 1 1 1 1 1 1 Southern Tablelands Northeast Victoria 4 2 1

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Phylogenetic analyses. Phylogenetic analyses (MP, ML and NJ) of the combined dataset also did not support the existence of any major intraspecific phylogeographic breaks or well supported clusters (Figure 5.2). However, when MP and NJ analyses were repeated excluding the outgroup samples, greater nodal support was provided to ingroup topology

(Figure 5.2). In both analyses a clade excluding haplotypes 19, 23 and 26 was strongly supported (94%). These haplotypes are from the southern regions Shoalhaven and Victoria.

However, other haplotypes from these two regions were also nested within the major clade.

There was also weak support (MP 55%; NJ 60%) for a clade consisting of haplotypes from

Sydney and regions north of Sydney, however samples from these regions also cluster outside this clade (Figure 5.2).

Minimum spanning network and demographic history

The MSN (Figure 5.3) of mtDNA haplotypes provided further support to the phylogenetic analyses. The network depicts a high number of common haplotypes found across multiple regions with little obvious geographical clustering. There was some clustering of northern regions however haplotype 6 was also detected in Sydney and haplotype 7, the most common haplotype, was found across a large portion of the range from the Central Coast to the Shoalhaven. Although there was some tendency for geographic structuring between the regions north of Sydney versus the regions south of Sydney the signal was weak and this level of structuring was poorly supported by phylogenetic analyses (Figure 5.2; Fig. 5.3).

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Figure 5.2: Phylogenetic relationships among L. aurea MtDNA haplotypes based on combined (COI and ND4) sequence data. (A) Neighbour-joining (NJ) tree based on the TrN+I+G (Tamura & Nei 1993) model of evolution with bootstrap (1000 pseudoreplicates) values >50% shown above the branches. This tree was re- drawn without the outgroup samples to better represent ingroup topology, the distance from outgroup samples to the first node was 0.535. NJ analysis excluding outgroup samples was also performed (under the HKY+I+G model (Hasegawa et al. 1985) and bootstrap values >50% are shown under the branches. (B) MP bootstrap (1000 pseudoreplicates) consensus tree with support values >50% shown above the branch in bold. MP analysis revealed 1078 most parsimonious trees, 61 steps, CI = 0.556, RI = 0.833. As with the NJ tree values below a branch indicate bootstrap (1000 pseudoreplicates) support (>50%) for analysis excluding the outgroup samples (which found 1076 trees, 160 steps, CI = 0.784, RI = 0.864). The ML tree for the data including outgroup samples (using the TrN+I+G model) was similar in topology to the above trees with bootstrap support >50% (500 pseudoreplicates) found for three clades only: Hap19, Hap 23, Hap 26 (58%); Hap 24, Hap 25 (59%); and Hap 16, Hap 45 (57%) (data not shown).

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Figure 5.3: Minimum-spanning network depicting relationships among L. aurea haplotypes based on combined sequence data. The area of the circle is proportional to the haplotype frequency, and the length of the connecting OLQHLVSURSRUWLRQDOWRWKHJHQHWLFGLVWDQFH .3. EHWZHHQKDSORW\SHV'DVKHGOLQHVLQGLFDWH alternative topologies. Shadings indicate what region each haplotype was detected in and if a haplotype was detected in more than one region the area of shading is proportional to its relative abundance. Analysis using the raw number of nucleotide differences among haplotypes produced a concordant result.

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The overall picture of haplotype relatedness implied from resulting trees, and the MSN is one of limited structure, suggesting a recent origin for most haplotypes and a relatively recent population expansion (Eizirik et al. 2001; Althoff & Pellmyr 2002). This pattern is suggestive of a widespread species that originated from a small number of individuals

(Avise 2000).

Mismatch distribution analysis further supports a sudden expansion hypothesis as the parameters of the mismatch distribution did not differ significantly from the sudden expansion model (P = 0.648). This was consistent with a significant Fu’s Fs (-23.92, P <

0.001), however, Tajima’s D (-0.657), although negative was not significantly different from the simulated data (P = 0.298).

The approximate timing of the demographic expansion, estimated by the mode of mismatch

GLVWULEXWLRQ 2 &, -10.8), was 213,000 years ago (95% CI = 73,000-

360,000 years ago). When considering the lower and upper 95% confidence limits this places the time of the estimated population expansion during the late Pleistocene.

Genetic diversity and population structure

Genetic diversity. Overall the mitochondrial sequences of L. aurea exhibited high haplotype diversity relative to low nucleotide diversity (Table 5.4). At four sampled sites

(YUR, BI, UH and R) only single haplotypes were detected. In general centrally located regions (Sydney, Illawarra and Shoalhaven) showed the highest levels of diversity (Table

5.4).

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Table 5.4: Diversity measures for sample locations and regions of L. aurea using combined sequence data DQG.3 . VXEVWLWXWLRQPRGHO1XPEHUVLQSDUHQWKHVHVJLYHVWDQGDUGGHYLDWLRQV Sample No. of No. of No. of Haplotype Nucleotide Region Location samples haplotypes polymorphic sites diversity diversity x10-3 Upper North Coast 15 4 5 0.623 (0.124) 1.779 (0.001) YUR 2 1 0 0 0 CH 13 3 2 0.513 (0.144) 0.717 (0.001) Lower North Coast BI 15 1 0 0 0 Hunter 29 4 4 0.406 (0.101) 0.652 (0.001) KIS 10 2 2 0.200 (0.154) 0.552 (0.001) SAND 10 2 1 0.200 (0.154) 0.255 (0.0004) MAT 7 2 1 0.476 (0.171) 0.595 (0.001) UH 2 1 0 0 0 Central Coast NA 11 3 10 0.473 (0.162) 6.827 (0.004) Sydney 69 18 18 0.899 (0.020) 7.424 (0.004) HB 25 6 10 0.793 (0.046) 6.681 (0.004) NEW 18 11 10 0.941 (0.033) 6.276 (0.004) EB 2 2 4 1.000 (0.500) 6.510 (0.005) R 5 1 0 0 0 A 9 6 11 0.833 (0.123) 6.040 (0.003) K 10 2 5 0.533 (0.095) 4.729 (0.002) Illarwarra 24 7 7 0.804 (0.015) 3.028 (0.001) PK 19 6 7 0.795 (0.060) 3.420 (0.002) INC 5 3 2 0.700 (0.218) 1.337 (0.001) Shoalhaven 65 21 22 0.886 (0.023) 7.508 (0.003) CS 10 6 13 0.778 (0.137) 7.450 (0.004) SB 16 9 12 0.850 (0.077) 6.859 (0.004) GP 10 3 5 0.733 (0.076) 4.355 (0.003) CU 9 4 7 0.778 (0.110) 3.761 (0.002) SX 10 6 13 0.889 (0.075) 11.01 (0.006) LM 10 7 8 0.933 (0.062) 4.850 (0.003) Southern Tablelands Q 10 2 1 0.467 (0.132) 0.595 (0.001) Victoria 25 5 6 0.737 (0.051) 2.976 (0.001) PH 10 2 4 0.200 (0.154) 1.302 (0.001) AX 10 2 1 0.356 (0.159) 0.453 (0.001) EV 5 3 2 0.800 (0.164) 1.613 (0.001)

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Genetic structure. Population-based analyses indicated that haplotypes were not distributed randomly with respect to geography as was alluded to in the phylogenetic analyses.

AMOVA analysis considering the 9 geographical regions and 23 sampling locations (sites with VDPSOHV UHYHDOHGVLJQLILFDQWJHQHWLFVWUXFWXULQJDFURVVDOOKLHUDUFKLFDOOHYHOV 3

0.0001) whether or not nucleotide differences were taken into account. Over all, 52.15% of genetic variance was observed among regions (-CT = 0.52), with 13.3% observed among sampled sites within regions (-SC = 0.28) and 34.6% observed among individuals within sampled sites (-ST = 0.65). However, when frequency data was used without consideration of molecular distance, the result varied considerably with 17.94% of genetic variance observed among regions (FCT = 0.179), 20.57% among sampled sites within regions (FSC =

0.251) and 61.49% among individuals within sampled sites (FST = 0.385).

Pairwise FST and -ST analyses and exact tests (P < 0.0001) also indicated significant structuring between regions though there were also non-significant comparisons (Table

5.5). For pairwise population based analyses (i.e. not pooled) 159 out of 276 comparisons were significant after corrections (151/276 for -ST comparisons). For FST comparisons BI

(all significant), PH (2 not significant), CH (3 not significant) and Q (5 not significant) were the most differentiated (data not shown), while for -ST comparisons BI (all significant), Q (2 not significant), CH (3 not significant) and PH (4 not significant) were the most differentiated (data not shown).

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Table 5.5: Genetic differentiation between L. aurea regions (sampled sites pooled). Pairwise FST (lower left hand matrix based on haplotype frequencies) and -ST values are shown (upper right hand matrix based on PROHFXODUGLVWDQFHXVLQJ.3. 1RQ-significance comparisons are shown in bold. Significance levels were evaluated by 10,000 permutations and then adjusted for multiple tests using Bonferroni Correction. UNC LNC HUNT CC SYD ILLAW SHOAL ST VICT UNC - 0.765 0.605 0.168 0.504 0.760 0.593 0.920 0.813 LNC 0.686 - 0.910 0.607 0.666 0.880 0.723 0.990 0.903 HUNT 0.503 0.744 - 0.161 0.650 0.873 0.718 0.969 0.899 CC 0.443 0.796 0.024 - 0.450 0.648 0.550 0.802 0.735 SYD 0.212 0.414 0.268 0.184 - 0.090 0.076 0.474 0.369 ILLAW 0.276 0.540 0.403 0.319 0.095 - 0.075 0.554 0.538 SHOAL 0.220 0.423 0.321 0.232 0.032 0.071 - 0.460 0.250 ST 0.443 0.809 0.573 0.530 0.260 0.333 0.261 - 0.797 VICT 0.312 0.572 0.434 0.371 0.174 0.230 0.154 0.370 -_

An isolation by distance pattern was detected over all sampled sites and regions when using linearised pairwise -ST differentiation estimates (Fig. 5.4), and over all sampled sites using linearised pairwise FST estimates (data not shown, P < 0.001). However, this pattern was not observed across regions when using linearised pairwise FST estimates (data not shown,

P = 0.71).

98 Chapter Five

(A) 36 R2 = 0.0998 32 28 24 20 16 12 8

) 4

ST 0

- - 4 4.5 5 5.5 6 6.5 7

/(1

ST (B) - 39 R2 = 0.1182

-1 -0.5 0.5 1.5 2.5 3.5 4.5 5.5 6.5 7.5

Ln Distance (km)

Figure 5.4: Isolation by distance plots of -ST /(1--ST ) plotted against the natural log of geographical distance (km) for all samples pooled into regions (A) and sampled sites with greater than 5 samples (B). In both analyses BI was excluded because of its isolation from gene flow and the -ST matrix was formulated based on WKH.3 . VXEVWLWXWLRQPRGHO7KHVROLGOLQHUHSUHVHQWVWKHEHVW-fit linear regression based on all points. For both analyses Mantel’s test was significant (regions: P < 0.05; all sampled sites: P < 0.001).

99 Chapter Five

Discussion

L. aurea phylogeography

Analyses of the phylogeographic structure of L. aurea showed no evidence of major geographical partitions or substantial barriers to historical gene flow throughout the species’ range (Figure 5.2). The lack of structure was unexpected in light of previous studies that have detected strong phylogenetic structure in frog species (e.g. Bos & Sites

2001; Austin et al. 2002; Palo et al. 2004). It is also generally accepted that frog species have limited vagility and are therefore thought to be insufficiently mobile to cross moderate barriers of unfavourable habitat. However, a recent microsatellite study of L. aurea found comparatively low genetic structuring and cautioned against such generalisations (Burns et al. 2004; Chapter 3).

At present, extensive habitat fragmentation would limit dispersal of L. aurea. However, in the past, if habitat were relatively continuous and climatic conditions favourable, there would have been few barriers to gene flow. And our current understanding of the ecology of this species (see introduction and Pyke & White 2001) and the findings of Burns et al.

(2004; Chapter 3) supports this idea.

To my knowledge I have produced the first terrestrial vertebrate phylogeographic study with relatively continuous sampling from the far north coast (NSW) to East Gippsland

(Vic) (Fig. 5.1). There is, therefore, a paucity of relevant datasets with which to compare the results. However, a limited number of studies have either sampled sparsely across this

100 Chapter Five

range (Schauble & Moritz 2001) or sampled from the mid or far north coast only (James &

Moritz 2000; Keogh et al. 2003).

Most notably, Schauble and Moritz (2001) conducted a phylogeographic study of

Limnodynastes peronii and Lim. tasmaniensis. Their sampling covered the whole of the

NSW and Victorian southeast coastline; however, their sampling effort south of the

McPherson Range to East Gippsland was extremely limited (Schauble & Moritz 2001).

The phylogeographic structure of Lim. peronii is particularly relevant to L. aurea because both species inhabit similar habitats (Pyke et al. 2002) and are often recorded at the same water bodies (E. Burns pers. obs.). In their study, Schauble and Moritz (2001) detected a distinct phylogenetic break positioned between the south of the McPherson Range (at the border of NSW and QLD) and north of Sydney. No other beaks were detected along the

NSW and Victorian south-eastern coastline and the detected break was more pronounced in

Lim. peronii than Lim. tasmaniensis (Schauble & Moritz 2001).

Schauble and Moritz (2001) speculate that the genetic break may constitute geographically shifted breaks that once centred on the McPherson Range or may be positioned in one of two areas. 1) The Clarence River, which has a tidal reach extending 100km inland

(Schauble & Moritz 2001) and where Donnellan et al. (1999) previously recorded a mtDNA lineage split in the Litoria citropa species-group; or 2) the Hunter Valley, which has been suggested as a boundary between southern and northern coastal faunal elements

(Cracraft 1991).

101 Chapter Five

The data failed to support the Hunter Valley as a potential biogeographic barrier, and unfortunately my sampling of extant L. aurea populations was south of the Clarence River

(most northern population at YNP; Fig. 5.1). L. aurea has historically been recorded as far north as Ballina (White & Pyke 1996) and museum samples may permit further examination of the Clarence River hypothesis. Two other studies that sampled either side of the Clarence River did not have concordant results. Litoria fallax showed little phylogenetic structure south of the McPherson Range (James & Moritz 2000); however,

Hoplocephalus stephensii (elapid snake) showed support (87%) for a Lismore based clade excluding Coffs Harbour and Newcastle samples (Keogh et al. 2003). If the Clarence River does constitute a long-term barrier to gene flow, then based on my data and that of the aforementioned studies, it may constitute the only distinctive break along the south-eastern coastline of NSW and Victoria.

Recent evolutionary history of L. aurea

The phylogeographical pattern in L. aurea mtDNA was characterised by a diverse and shallow phylogeny where common haplotypes were widespread and to a limited extent closely related haplotypes were geographically clustered, albeit on a large geographic scale

(Figure 5.2; Fig. 5.3). This phylogeographic pattern, according to Avise (2000), intimates contemporary gene flow between populations that are tightly connected in history, where common haplotypes are likely ancestral (plesiomorphic) and rare haplotypes apomorphic.

Relative to other intraspecific Australian frog studies, employing COI or ND4 genes, the level of sequence divergence in L. aurea was low (see Results for specific comparisons). It is commonly accepted that a shallow phylogeny in conjunction with high haplotype

102 Chapter Five

diversity, relative to low nucleotide diversity, as found in L. aurea, is indicative of a recent population expansion (e.g. Eizirik et al. 2001; Althoff & Pellmyr 2002; Joseph et al. 2002;

Stamatis et al. 2004). Mismatch distribution analysis and Fu’s Fs test support an expansion hypothesis and the estimated date of expansion was approximately 213,000 years ago with upper and lower bounds of 73,000 and 360,000 years respectively (see Results for further information). If this time estimate is realistic, the expansion occurred during the late

Pleistocene but prior to the last glaciation maximum 18,000 years ago (Markgraf et al.

1995); and the reduction in the species range may have occurred in the early-mid

Pleistocene and could have continued until expansion became possible.

During the Pleistocene the Australian environment, unlike the Northern Hemisphere

(reviewed in Markgraf et al. 1995; Hewitt 2000), experienced limited glaciation with ice sheets confined to the Snowy Mountains (Barrows et al. 2001) and sections of Tasmania

(reviewed in McKinnon et al. 2004). However, during this period the continent experienced increased aridity and climatic oscillations with wetter climates during the interglacial periods and more arid environments during the glacial maxima (Bowler 1982).

This resulted in the expansion and contraction of arid habitats, reducing Australia’s more mesic habitats that dominated the Tertiary (Kemp 1981), to minimal areas along coastal strips (Kershaw 1981; Nix 1982).

It is difficult to determine to what extend these events would have impacted on L. aurea.

This species is not a habitat specialist, however, like most amphibians it is dependent on freshwater bodies for breeding and wet conditions for dispersal (ecology reviewed in Pyke

& White 2001). So it is likely that the arid cycles during the Pleistocene would have

103 Chapter Five

limited dispersal, colonization, breeding activity and recruitment and could have resulted in some localised extinctions.

This is one of the first studies to sample extensively throughout the NSW/Victorian coastline. There is therefore a lack of biogeographic and/or phylogeographic literature to help us better understand historically what potential factors may have influenced and/or impacted on the current phylogeography of L. aurea. Previous studies have predominately focused on the arid zone, or the far north or far south coast of eastern Australia (e.g.

Chapple & Keogh 2004; Joseph et al. 1995; Schneider et al. 1998; McKinnon et al. 2004).

Based on the data, I suggest that there may have been a single large refugium, possibly extending from the Hunter to the Shoalhaven, where the two most common haplotypes were detected (Hap 6 and 7, Table 5.3; Fig. 5.3). This would explain the current high haplotype diversity in this area (Table 5.3; Table 5.4), the central section of the species range, and the tendency for haplotypes to be distributed Sydney-south and Sydney-north.

However, there is also evidence to suggest that there may have been a second refuge area on the far south coast closer to, or within, Victoria. This is based on the strong support

(94%) in phylogenetic analyses (MP and NJ) for a clade excluding haplotypes 19, 23 and

26 (Figure 5.2). These haplotypes were detected in the southern regions Shoalhaven and

Victoria. It is possible that after a period of divergence in isolation, expansion from a southern refugium occurred, with secondary contact with an expansion from the central large refugium. However an overall pattern of isolation by distance does not support this hypothesis (Fig. 5.4).

104 Chapter Five

I am unable to explore extensively if there were non-coastal refugia within the species historic range based on the current data. L. aurea, although today mainly restricted to the coastline, once extended inland as far west as Bathurst and Tumut (reviewed in Goldingay

1996). It is possible that inland populations may have been more phylogeographically structured and examination of museum samples would help determine if this was the case.

In the current study, only samples from extant populations were employed, however, inland samples from the Upper Hunter and the Southern Tablelands failed to indicate any distinct phylogenetic structuring (Figure 5.2; Fig. 5.3).

In summary, the data suggest that Pleistocene glaciation cycles and a relatively recent population expansion (along with lineage sorting and genetic drift) have been influential factors shaping the weak phylogeographic structure in L. aurea. Further to this the data suggest that there had been mostly continuous habitat throughout the species’ range until the European invasion of Australia a little over 200 years ago, a finding consistent with

Keogh et al. (2003).

Population structure and variability

Analyses of population structure on the large geographical scale of regions was performed to further investigate genetic structuring and the history of dispersal throughout the species range (NB. only sampled sites with 5 or more samples were analysed).

Overall population-based analyses indicate that there was significant structuring throughout the species range both within and between regions and in general restricted gene flow was the result of geographic distance (Table 5.5; Figure 5.4). The correlation between genetic

105 Chapter Five

divergence and geographic separation was weak, however (Figure 5.4). As expected the more isolated NSW populations (BI, CH and Q) were highly differentiated (data not shown) and the Victorian populations were not significantly structured, consistent with microsatellite data from an earlier study (Burns et al. 2004; Chapter 3). However,

Victorian populations AX and EV were not significantly different from all NSW populations (data not shown) as was the case for microsatellite data (Burns et al. 2004;

Chapter 3) and this may be due to small sample sizes.

Levels of genetic diversity were generally highest in populations within the centre of the species range (Table 5.4). Interestingly, Victorian populations were not found to be comparatively depauperate as was found in the microsatellite study (Burns et al. 2004).

However, Broughton Island in both studies showed low levels of diversity as would be expected of an island population (Frankham 1997; Table 5.4).

Taken together, phylogenetic and population–based analyses indicate that since a

Pleistocene expansion there has been continued (albeit restricted) dispersal and gene flow which has resulted in a weak isolation by distance pattern and the significant population structure evident today. However, current dispersal is likely to be increasingly restricted or non-existent between fragmented populations (see also Burns et al. 2004; Chapter 3).

Conservation Implications

Phylogeographic analyses of intraspecific sequence variation, coupled with population- based analyses, provide valuable information on how genetic variation is partitioned within species and can therefore aid in the implementation of effective conservation strategies.

106 Chapter Five

The data provide no support for the existence of distinct phylogeographic breaks within the species’ range, implying that there are no historically isolated groups that should be viewed as separate Evolutionary Significant Units (Ryder 1986; Moritz 1994). However, below this level there is significant genetic structuring both within and between the regions nominated for conservation management in the species’ Draft Recovery Plan (NSW NPWS

2002).

AMOVA analysis indicated (when considering molecular distance) these regions account for 52.15% of genetic variance, however when considering frequency data alone, variation amongst regions was reduced to 17.94%. So it is difficult to determine the suitability of these regions based on these data. I prefer not to suggest ‘management units’ for this species but rather give a generalised approach based on the natural dynamic of the species as was suggested by Burns et al. (2004)/(Chapter 3). That is, priority should be given to conserving areas of connecting habitat to promote population connectivity and maintain adaptive diversity and evolutionary potential. Any attempt to designate ‘management units’ should be done in conjunction with the findings of a previous microsatellite study

(Burns et al. 2004; Chapter 3).

The results potentially support ‘well managed’ intervention to mediate gene flow amongst isolated populations, however this should be avoided unless necessary and any plans for artificial movement of frogs and/or tadpoles should source individuals from neighbouring populations as long as diversity levels and population numbers are adequate.

107 Chapter Five

Publication Information

This chapter is currently being prepared for submission to Conservation Genetics.

Reference: Burns EL, Eldridge MDB, Crayn DM, Houlden BA (in prep) Low phylogeographic structure in a widely spread endangered Australian frog Litoria aurea

(Anura: Hylidae). Conservation Genetics.

Author contribution: My contribution to this paper included sample collection, laboratory work, data analyses and writing. Mark Eldridge, Darren Crayn and Bronwyn Houlden supervised the compilation of this paper, providing advice and editorial changes when necessary.

108 Chapter Five

Chapter 5 Appendix: Geographic distribution of COI and ND4 haplotypes

(a) Geographical distribution of 19 L. aurea COI haplotypes summarised across regions COI Haplotype Region a b c d e f g h i j k l m n o p q r s Upper North Coast 13 2 Lower North Coast 15 Hunter 28 1 Central Coast 8 2 1 Sydney 11 2 20 12 4 8 6 5 1 Illawarra 3 8 11 2 Shoalhaven 21 2 1 18 14 1 4 1 1 1 1 Southern Tablelands 10 Northeast Victoria 19 4 2 (b) Geographical distribution of 26 L. aurea ND4 haplotypes summarised across regions ND4 Haplotype

Region A B C D E F G H I J K L M N O P Q R S T U V W X Y Z Upper North Coast 2 2 9 2 Lower North Coast 15 Hunter 23 4 1 1 Central Coast 9 2 Sydney 6 22 17 9 4 9 1 1 Illawarra 3 11 8 2 Shoalhaven 21 9 11 9 2 3 4 3 1 1 1 Southern Tablelands 7 3 Northeast Victoria 15 9 1

109 Chapter Six

Chapter Six

Closing remarks: a conservation management perspective

Introduction

Green and golden bell frogs have undergone population declines and localised extinctions over the last 30-40 years, and many remaining populations are now fragmented (Pyke &

White 2001). To reduce species decline, managers involved in the conservation of L. aurea need to devise and implement conservation strategies.

A primary aim of this thesis was to provide molecular analysis to assist in the formulation of management strategies. In doing so, this thesis has documented the population structure and phylogeography of remaining endemic populations using mitochondrial and nuclear genetic markers. The findings, detailed in the preceding chapters, provide information on genetic relationships among persisting populations and if used correctly will aid in the formulation of effective management practices. However, genetic information can be misinterpreted so careful consideration, preferably on a case-by-case basis, is needed when making management decisions.

My intention in this chapter is to provide an overview of the preceding chapters, particularly chapters three and five, and to discuss management options and provide management guidelines.

110 Chapter Six

Summary of Findings

This thesis details the findings of a large and pioneering study that required extensive laboratory and fieldwork. A substantial part of this research involved the identification and development of four microsatellite markers described in Chapter two. To date these loci constitute the only microsatellites available for any Australian Hylid and are part of a limited number cloned in amphibians worldwide.

The development of these markers was difficult and required intense investigation. A total of 65 positive clones were sequenced and multiple primers were designed for 26 loci. In total, 108 different primers were designed and tested. The difficulty experienced with cloning and primer design may have been due to the enrichment protocol used. For example, the CA regions may have acted as primers during the PCR step of the procedure

(Chapter 2).

Despite the low number of microsatellites used, these four loci did prove highly informative in the study of L. aurea population structure and diversity (Chapter 3). In this study, levels of allelic diversity and heterozygosity were high (uncorrected mean alleles/locus and HE

4.8-8.8 and 0.43-0.8 respectively) and populations were significantly structured (FST 0.172).

However, genetic structuring was relatively low compared to previous amphibian studies employing microsatellites (Table 3.7, Chapter 3) and in addition some areas within continuous habitat showed evidence of weak genetic structuring (data subset FST 0.034).

111 Chapter Six

I concluded from this study that 1) the great majority of dispersal in L. aurea occurs between neighbouring habitat patches with only a few individuals moving longer distances

2) gene flow is sufficiently large in areas of continuous habitat (e.g. Shoalhaven and

Victoria) to prevent significant genetic structuring and 3) prior to decline and fragmentation the natural genetic structure of L. aurea was most likely weak (relative to today and other amphibian studies) due to high dispersal activity. Although ecological studies do support dispersal capability in this species, in one circumstance greater than 10kms (see for review

Pyke & White 2001), the genetic data suggests movement over much larger distances with low genetic structure recorded in areas of continuous habitat covering approximately

80kms (Chapter 3).

To further investigate population structure and history, a phylogeographic study using mitochondrial DNA was conducted (Chapter 5). However, prior to doing this, I first investigated species relationships among the bell frog species group (Chapter 4). The data, however, failed to support the inclusion of the tropical bell frog Litoria dahlii in this species group. Relationships among the remaining members correlated with geographical distribution: the south-western bell frogs (L. cyclorhyncha, L. moorei) and the south-eastern bell frogs (L. aurea, L. raniformis) were reciprocally monophyletic. Results also suggested that divergence of these two lineages occurred during the late Miocene, which was consistent with results of previous albumin clock analyses (Roberts & Maxson 1985) and with more general assertions that much of the major differentiation and radiation of the

Australian biota predated the Quaternary (Nix 1982; Barendse 1984; McGuigan et al. 1998;

Schauble & Moritz 2001).

112 Chapter Six

Although speciation events in bell frogs may have predated the Quaternary, results from the intraspecific phylogeographic study (Chapter 5) suggest that Pleistocene glaciation cycles and a relatively recent population expansion (along with lineage sorting and genetic drift) were influential factors shaping the structure of L. aurea. In this study, there was no support for the existence of distinct phylogenetic breaks throughout the species’ range.

However, below this level there was significant genetic structuring (FST = 0.385). Results from Chapter five generally corroborated the microsatellite study (Chapter 3), however, due to the different focus, the sampling schemes of the two chapters were not identical.

In Chapter five I suggest that since a Pleistocene expansion there has been continued restricted dispersal and gene flow, which has resulted in an isolation by distance pattern and significant population structure evident today. However, current dispersal is likely to be increasingly restricted or non-existent between fragmented populations. In the absence of dispersal it is likely that, in the long term, levels of genetic diversity within populations will not persist, as decreased migration and drift will result in a loss of genetic diversity and consequently levels of differentiation among populations will increase.

In summary, the results of this thesis indicate that L. aurea is currently a species with relatively weak population and phylogeographic structure compared to other amphibians

(reviewed in Chapters 3 & 5). Levels of genetic variation are predominately higher in central areas of the species’ range and there is no data to suggest that any populations, at this time, require genetic supplementation.

113 Chapter Six

Conservation management

Conservation units

A fundamental tenet in conservation biology is to identify and protect genetically distinct lineages to maintain the evolutionary potential of species. How best to achieve this, however, is hotly debated and focus is often given to the identification of ‘units’ for conservation (e.g. Ryder 1986; Moritz 1994b; Moritz et al. 1995; Moritz 1999; Crandall et al. 2000; Fraser & Bernatchez 2001). The most prominent conservation unit proposed and discussed has been the Evolutionarily Significant Unit (ESU), which is a discrete population unit that has evolved separately for a substantial period of time and merits separate management and high conservation priority (Ryder 1986; Moritz 1994b).

In Chapter five there was no support for the existence of distinct evolutionary lineages within L. aurea, implying that there are no historically isolated populations that should be viewed as separate evolutionary significant units (Ryder 1986; Moritz 1994b). However, below this level there is significant genetic structuring among populations, although not all populations are genetically distinct (Chapters 3 & 5).

Below the level of an ESU, Moritz (1994a) proposes Management Units (MU), which consist of one or more populations showing significant differentiation in their frequencies of nuclear alleles or mitochondrial haplotypes (see also Moritz et al. 1995). MUs are considered the ecological components of an ESU and are similar in concept to stocks previously used in fisheries (Fraser & Bernatchez 2001). MUs may not necessarily be

114 Chapter Six

preserved as separate entities in order to maintain processes and conserve the large ESU

(Moritz 1999).

There are several MUs in L. aurea with a large number of populations showing significant differentiation from other populations based on this criterion (Chapters 3 & 5). However, I prefer not to attempt to ‘group’ multiple populations into MUs but rather observe overall patterns, since there is a continuum throughout the species’ range and distinct ‘groups’ are not apparent. Nevertheless, Broughton Island does warrant special mention, as it was distinct from all other populations for both mitochondrial and microsatellite analyses.

Broughton Island was significantly differentiated and showed comparatively low levels of genetic diversity (Chapters 3 & 5).

Active management: endemic populations

As populations become increasingly fragmented or local extinctions continue then aggressive conservation strategies such as translocations and reintroductions may become necessary. Low phylogeographic structure coupled with evidence for recent gene flow among many sites supports ‘well managed’ intervention of this type. However, there is little evidence to suggest that these strategies are effective in amphibians and consideration of other ecological factors need also to be made which is outside the scope of this discussion chapter (see for review Burke 1991; Dodd & Seigel 1991; Bloxam & Tonge

1995).

In addition, there is no evidence to suggest that supplementation through artificial immigration is necessary at this time, given current levels of genetic variation within

115 Chapter Six

populations (Chapter 3). If however, for demographic and ecological reasons it is thought necessary to supplement or reintroduce populations then there is no genetic evidence to suggest this is an inappropriate management strategy per se. This conclusion, however, is based on the following principles. First, given the overall isolation by distance pattern for microsatellite and mitochondrial data, source populations should be within geographical proximity (i.e. the closest neighbouring population). This will act to reduce impacts of localised adaptations and maintain or restore ‘natural’ levels of gene flow. Second, source populations should have equivalent or greater levels of genetic diversity than the recipient population to prevent a loss of genetic diversity and no single source should be used extensively. Last, source populations should not be so genetically distinct as to significantly alter the genetic integrity of recipient populations by disrupting localised adaptations or resulting in loss of evolutionary potential through a loss of genetic diversity

(see for review Moritz 1999; Storfer 1999; Johnson 2000).

It is also important to note that even if there is no significant structuring between source and recipient populations a failure to detect differentiation using genetic markers does not imply that localised adaptations are not present (Storfer 1999; Johnson 2000). It does, however, suggest that genetic consequences of any supplementation should be minimal if implemented correctly.

Under the above criterion I would suggest that Broughton Island, the Southern Tablelands, and Crescent Head populations should not, under most circumstances, be used as source populations because they are highly differentiated (Chapters 3 & 5). Furthermore, based on microsatellite data, Broughton Island, Kurnell and Victorian populations would not be

116 Chapter Six

appropriate source populations because they have levels of genetic variation that are comparatively depauperate (Chapter 3).

Captive populations

Currently, there are two captive populations held at Taronga Zoo (Sydney, NSW) comprising individuals (and their offspring) originally sourced from Rosebery and

Arncliffe in Sydney. In Chapter five, samples from wild caught individuals in these two captive populations were examined using mtDNA (Table 5.1). Results from this Chapter indicated that only a single haplotype was shared amongst the Rosebery individuals (n = 5) sampled (Table 5.4). However, four haplotypes were detected among the five captive individuals sampled from the Arncliffe population (data not shown). Although further analysis using microsatellite markers is warranted to address specific management options, in the interim, it would be inadvisable to use the Rosebery population for any future reintroduction programs due to low levels of genetic diversity.

Unfortunately, in the past, this population has been used for reintroduction programs (B.

Houlden pers. comm.), and to my knowledge none of these programs have been successful over the longer term (A. White pers. comm.). It is difficult to say why these programs have been unsuccessful but low levels of genetic diversity may have been influential. For example, several studies in a variety of organisms have demonstrated a correlation between low levels of genetic diversity and reduced fitness indicators such as reproductive success and survival (review in Eldridge et al. 2004 and references therein). Furthermore, if these populations did successfully establish they would still be genetically atypical and would not assist in maintaining levels of genetic diversity in the species more generally.

117 Chapter Six

Future Directions

Although the research presented in this thesis constitutes a large base-line study with important implications for species conservation and management, further work and analysis may be required to assess various management options in the future. The microsatellite markers developed, as part of this thesis and the mtDNA genes employed should prove useful in such studies. In particular, I would suggest that careful consideration and further investigation is warranted prior to using captive populations as source stock for future reintroduction programs.

As previously discussed, translocation and reintroduction programs per se may be viable conservation strategies based on the genetic evidence presented in this thesis. However, these strategies should be assessed on a case-by-case basis. Furthermore, the way in which such strategies are implemented is critically important and if not done correctly could result in considerable and irreversible changes to the gene pool. It then follows, that it is important to make specific genetic assessments of recipient and source populations before considering such management strategies to avoid or minimise any potential adverse impacts on species integrity.

I suggest that if translocations and reintroductions are attempted, then strategies should be devised in conjunction with a molecular ecologist to ensure appropriate consideration of genetic implications. It is further recommended that any program incorporate ecological and genetic monitoring over consecutive seasons following augmentation and/or reintroduction.

118 Chapter Six

Closing Remarks

At this time, conservation management in L. aurea should focus on the protection of local populations and habitat to promote population connectivity to ensure processes that maintain adaptive diversity and evolutionary potential are conserved. To this end, efforts should also be made to conserve the species' current ecological amplitude, that is, the range of environments in which populations are currently found (Sherwin et al. 2000). This will require strategies that span across private and government lands since a number of populations currently exist outside of national parks (reviewed in NPWS 2002).

Nevertheless, the preservation of species’ amplitude and the maintenance of dense networks of suitable habitat, whilst maximising local carrying capacity and reproductive output, as well as minimising known threats, are key to securing the long-term survival of the green and golden bell frog.

119 References

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