Examining the Patterns and Processes of Speciation and Species Diversity in Australian Gehyra Gecko Lizards

Examining the patterns and processes of speciation and species diversity in Australian Gehyra gecko lizards

Mark J. Sistrom

A thesis submitted for the degree of Doctor of Philosophy

School of Earth and Environmental Sciences The University of Adelaide September, 2011

“The footsteps of Nature are to be trac'd, not only in her ordinary course, but when she seems to be put to her shifts, to make many doublings and turnings, and to use some kind

of art in endeavouring to avoid our discovery.”

— Robert Hooke, Micrographia (1665, reprint 2008), 17.

Declaration

This work contains no material which has been accepted for the award of any other degree or diploma in any university or other tertiary institution to Mark Sistrom and, to the best of my knowledge and belief, contains no material previously published or written by another person, except where due reference has been made in the text.

I give consent to this copy of my thesis when deposited in the University Library, being made available for loan and photocopying, subject to the provisions of the

Copyright Act 1968. The author acknowledges that copyright of published works contained within this thesis resides with the copyright holder(s) of those works.

I also give permission for the digital version of my thesis to be made available on the web, via the University’s digital research repository, the Library catalogue, the

Australasian Digital Theses Program (ADTP) and also through web search engines, unless permission has been granted by the University to restrict access for a period of time.

This work was funded by an ARC Environmental Futures Network travel award

(2008), an Adelaide University postgraduate travel award (2010) and a BushBlitz capacity building grant (2011) awarded to the author. Core project funding was provided by Australian Biological Resources Study grant 207-43 awarded to Dr. Mark Hutchinson and Professor Steve Donnellan.

Mark Sistrom 4

Contents Chapter 1: General introduction p. 10

Chapter 2: Sistrom M.J.; Hutchinson M.N.; Hutchinson R.G.; Donnellan S.C. 2009. Molecular phylogeny of Australian Gehyra (Squamata: Gekkonidae) and taxonomic revision of Gehyra variegata in south-eastern Australia. Zootaxa 2277:14-32. p. 18

Chapter 3: Sistrom M.J; Donnellan S.C.; Hutchinson M.N. 2011. Species delimitation paper. p. 52 Chapter 4: Sistrom M.J.; Hutchinson M.N.; Bertozzi T.; Donnellan S.C.; (in review). Estimating species trees and testing evolutionary hypotheses despite high levels of gene tree discordance in Australian Gehyra geckos. Systematic Biology p. 101 Chapter 5: Sistrom M.J.; Edwards D.L.; Hutchinson M.N.; Donnellan S.C. (in review). Morphological differentiation correlates with ecological but not genetic divergence in a Gehyra gecko. Evolution p. 129 Chapter 6: General Discussion p. 165 Appendix 1. Table outlining sample details for Chapter 1. p. 178

Appendix 2: Table outlining sample details for Chapter 2. p. 202 Appendix 3: Table outlining sample details for the dating analysis of Chapter 3 p. 206

Appendix 4: Table outlining sample details for the species tree analysis of Chapter 3 p. 212 Appendix 5: Individual gene trees taken from the species tree analysis of Chapter 3. p. 216 Appendix 6: Table outlining sample details for Chapter 4 p. 223 5

Abstract

Understanding the process of speciation and the nature of relationships between species is one of the fundamental aims of evolutionary biology. These processes are integral to the study of species delimitation and taxonomy, phylogenetic reconstruction and evolutionary history and the study of speciation processes. Under this premise I evaluate a recently evolved and taxonomically challenging group– the Gehyra geckos of

Australia, to gain a better understanding of how the process of speciation and species relationships have developed in this genus.

My research has three main aims:

1) Explore the adequacy of current taxonomy in accounting for species diversity in the group and improve it where necessary: Gehyra have proven taxonomically troublesome historically, with extensive and geographically complex arrangements of genetic diversity apparently not associated with patterns of morphological diversity. I explored species delimitation and the taxonomic status of lineages within the arid- adapted Gehyra variegata species complex using multi-locus (mtDNA, nuclear loci, karyotypes) genetic, distribution and morphological data, generating the first comprehensive phylogenetic framework for the genus. I describe one new species and identify an additional five putative species. I support previously hypothesized high levels of cryptic diversity in the group and present a concentrated effort in taxonomically resolving the genus.

2) Evaluate previously proposed evolutionary scenarios for the diversification of the Australian Gehyra and propose a comprehensive evolutionary history of the group:

Using a multi-locus dataset (one mtDNA locus, six nuclear loci), I generated a calibrated 6 species tree of the group, which showed support for a late-Eocene to mid Miocene introduction of the genus to Australia from Asia and for the division of the Australian

Gehyra into a tropically-adapted Gehyra australis species complex and a generally arid- adapted Gehyra variegata species complex containing morphologically transitionary species in the Kimberley region. My analyses did not support a previously suggested model of chromosomally driven speciation in Australian Gehyra and assert that diversification of both species complexes occurred simultaneously from the late Micoene through to the present.

I undertook a quantitative evaluation of gene tree discordance in Gehyra, showing a high degree of discordance between genes for the group, further supporting the recent diversification of the group.

3) Examine possible processes of speciation in Australian Gehyra: I investigated a case study in which a geographically constrained, distinct population of Gehyra was shown to be morphologically and ecologically distinct but genetically indistinguishable from a comparatively widespread, geographically parapatric species. This indicates a scenario of emergent, ecological speciation and presents a model system in which the process of ecological speciation could be observed. It also contrasts previous studies highlighting allopatric speciation driving the Australian Gehyra radiation, showing ecological speciation may play an important role.

In carrying out these studies, I have both explored the use of emergent methods for delimiting species and evaluating relationships between species, and significantly increased our understanding of the Australian Gehyra radiation. This body of work represents an ideal framework for rapid and effective evaluation of novel Gehyra species 7 and will greatly assist in discovering and documenting the diversity of this problematic radiation in the future. 8

Acknowledgements

I thank my supervisors for their advice, support and encouragement - and occasional mad dash to a hospital bedside to make sure I hadn’t rattled loose all of my marbles. I also express deep gratitude to many of the students and staff at Australian

Centre for Evolutionary Biology and Biodiversity (ACEBB) for their time, advice and friendship over the course of my PhD – namely, but not limited to Paul Oliver, Annabel

Smith, Terry Bertozzi, Kathy Saint, Alison Fitch, Lizzie Perkins, Jaro Guzinski, Duncan

Jardine, Gaynor Dolman, Adam Skinner, Christina Adler and many others. I especially express my deep gratitude to Kate Sanders and Ralph Foster for their professional and personal advice, friendship and for putting a roof over my head when I had none.

I also thank Lacey Knowles and her lab group for allowing me to visit for several months and putting up with me being the dumb kid in lab meetings which hauled my development as a scientist forward in leaps and bounds.

I express a profound level of debt and gratitude to my parents and family for nurturing my passion for the natural world from a young age and going above and beyond in providing me the best education possible – even when I was too myopic and stubborn to appreciate your efforts.

Last and certainly not least I thank my wife, Dan Edwards. You have been my closest confidant, by most scathing critic and adherent supporter throughout this journey.

Whenever I’ve needed support, you’ve been there and I am forever in your debt.

Without you all I would not have succeeded in completing the work within.

This work has been supported by funding from Australian Biological Resources Study,

ARC Environmental Futures Network, BushBlitz and The University of Adelaide. 9

Notes on chapter styles

Chapter 1 is published in the journal Zootaxa and thus follows that journal format precisely. Chapter 2 is intended for submission in the journal Molecular Phylogneetics and Evolution and is thus formatted in the style prescribed by that journal. Chapter 3 is intended for submission in the journal Systematic Biology and thus follows that journal’s style precisely. Chapter 4 is published in the Journal of Evolutionary Biology and thus follows that journal’s style precisely.

A statement declaring co-author contributions prefaces each chapter submitted or intended for publication.

The format of this thesis complies with that outlined in “Specifications for Thesis

2011” provided by the University of Adelaide Graduate Centre: http://www.adelaide.edu.au/graduatecentre/pdf/specifications_thesis_2011.pdf 10

General Introduction

“I was much struck how entirely vague and arbitrary is the distinction between species and varieties” - Charles Darwin (On the Origin of Species 1859 p.48)

Speciation, evolutionary history and taxonomy in recent radiations

The species problem (Hey 2001) is a long running and pervasive debate in the biological sciences. Discussion regarding the intrinsically linked and simultaneously distinct questions regarding what constitutes a species and how they are detected predates

Darwin (e.g. Ray 1686) and continues today (e.g. Bauer et al. 2011; Fujita & Leaché

2011). Despite this, “species” remains the most universally accepted and widely used measure of organismal diversity both within the general public and scientific community, forming a foundation for our understanding of the biota of Earth. Understanding what constitutes a species, how to identify these entities and describe the relationships between them is fundamental to both our basic understanding of biological diversity and further studies of biological function.

As a result of the difficulties in defining the term species and the variety of methodologies in identifying species, numerous definitions have been developed and applied to the categorization of the biota of Earth (summarized in Mayden 1997). Often, these concepts have been in conflict with one another (De Quieroz 2005) in that the application of different concepts resulted in differential numbers of, and assignment to species (De Quieroz 2005). However, since Simpson (1951) most species definitions have used a form of the biological species concept (Mayr 1942) in an attempt to identify independently evolving lineages of organisms. After many years and a vast quantity of published discussion refining the concept of species, recent conceptual breakthroughs in 11 the generation of the general lineage concept of species (De Queiroz 2007) which defines species as segments of evolutionary lineages and allows for their identification and delimitation using a variety of secondary characteristics. This conceptual consensus on the biological definition of what a species is has led to a renaissance in methodological advancement in delimiting species (e.g. O’Meara 2010; Yang and Rannala 2010).

As biological diversification is an effectively continuous process (Wu 2001) recently evolved species often represent extremely challenging scenarios for species delimitation, taxonomy and systematics. This is due to young species not having accumulated the characters generally used for the detection, description and subsequent analyses of species relationships such as reproductive isolation, fixed apomorphies, and reciprocal gene-tree monophyly (Shaffer & Thompson 2007). Furthermore, recently radiated species may accumulate these differences in a manner that results in confounding and complex patterns of diversity, which result in differential delimitation and classification dependent on which characters are analysed (De Quieroz 2007).

Finally, the discordance between gene trees and species trees observed in many recent radiations considerably complicates phylogenetic reconstructions of species relationships.

This makes it exceptionally challenging to both resolve taxonomically and study patterns of evolutionary diversification in recent radiations. Despite the difficulties, recently evolved species offer opportunities to study the process of speciation and patterns of evolutionary divergence between related species that are not offered by older, better- resolved groups of organisms. Understanding the processes by which organisms diversify and therefore the conditions under which species are generated is key to basic biological studies (Rowe et al. 2011). 12

An introduction to Gehyra

Gehyra are one of the more speciose genera of lizards from the Gekkonidae (Han et al. 2004; Russell & Bauer, 2002; Underwood, 1954). Gehyra currently comprises 36 species, covering a wide range of habitats and distributed from Thailand through most of the Oceanian and Melanesian islands and continental Australia (King 1979; Russell &

Bauer, 2002). However the “epicenter” of Gehyra diversity is represented by an

Australian radiation, comprising 19 largely endemic species (Horner 2005; Sistrom et al.

2009). Gehyra are climbing geckos and there is evidence that some species are substrate specialists, preferring either rocky or vegetative habitats, where as others are more generalist (Bustard 1968; King 1979; Moritz 1987). There is also evidence that members of the genus are particularly good colonizers of newly available habitat, and may be responsible for displacing other lizards, due to their territorial nature (Moritz 1987).

However it appears that once a territory has been established, Gehyra have a tendency towards site philopatry (Bustard 1968). Gehyra show a marked ability to persist in fragmented habitats but a degree of sensitivity to temperature, with a limited tolerance to cold (Bustard 1967; King 1983; Moritz 1992).

The systematics of Gehyra has been long recognised as problematic (King 1979;

1984; Moritz 1984), however it has been established that they form a monophyletic clade within the Gekkonidae (Han et al. 2004).

Since the first description of Gehyra australis (Gray 1834), several revisions have been made to the taxonomy of the Australian Gehyra radiation, the most recent being the description of Gehyra koira (Horner 2005). Gehyra has proven to be taxonomically 13 troublesome in the past as many osteological and morphometric characters are continuously variable (King 1979; Moritz 1992). As such, considerable karyotypic and allozyme variation does not manifest in easily catgegorised morphological variants.

Many of the species descriptions are based on characters that vary continuously between species such as back pattern (King 1979) and as such, samples collected in the field are often not placed into any recognized species with certainty. Many species comprise many morphological isolates and distinct chromosome races and allozyme OTU’s (Adams unpublished work; Donnellan unpublished work; King 1979; 1982; 1983; 1984; Moritz

1984; 1988; 1992). Despite widespread taxonomic uncertainty, previous work has supported the separation of Australian Gehyra into a predominately small bodied and arid adapted G. variegata species complex (King 1979; Mitchell 1965) and a relatively large bodied and tropically adapted G. australis species complex (King 1983; Mitchell 1965).

The widespread presence of intermediate morphological states between genetic and chromosomal types, in concert with the phylogenetic position of the genus is indicative of a relatively recent evolutionary history. In light of this, King proposed that the diversification of Australian Gehyra had been driven by the process of chromosomal rearrangement and posed a detailed evolutionary scenario to account for the observed patterns of chromosomal diversity in the group. In addition to general criticisms of chromosomal models of speciation (Rieseberg 2001) attributing the diversification of the

Australian Gehyra to processes of chromosomal speciation are somewhat premature given the lack of data relevant to reproductive isolation of races (Sites & Moritz 1987;

Moritz 1992). As such, the evolutionary processes by which Gehyra radiated in Australia are largely unknown. 14

A single comparative, population-level genetic study has been conducted of G. nana - a habitat specialist reliant on isolated rocky outcrops in central Australia and G. variegata - a habitat generalist using allozyme and chromosomal data (Moritz 1987). It revealed very low levels of genetic population structure within G. variegata in comparison with G. nana, suggesting higher levels of migration in the hypothesized generalist species than the hypothesized specialist species. He also concluded that genetic diversification within each of these two species did not occur over significantly different temporal scales (Moritz 1987).

In summary, the Australian Gehyra radiation is a recently radiated group, with complex patterns of diversity that present a challenging biological system for taxonomic resolution of species boundaries, species delimitation and the reconstruction of species relationships and subsequent understanding of the mechanisms of diversification in the group. While past research has been relatively extensive, it has led to only partial understanding of these aspects for the group.

Advances in species delimitation and the reconstruction of species relationships

The recent conceptual advances in regards to the species problem, in concert with the increasing ease with which large quantities of molecular genetic data can be acquired have fueled a methodological renaissance in taxonomy, species delimitation and the phylogenetic reconstruction of species relationships. The development of these methods is allowing for genomic level tools to be brought to bear on questions regarding species delimitation, assignment, description and relationships and while such techniques are not 15 without their caveats, they represent a major step forward over the previous generation of techniques.

The advent of integrative taxonomy (Avise & Wollenberg 1997; Schlick-Steiner et al. 2010) introduces the concept of a multisource approach to traditional taxonomy in an effort to increase the speed and rigor of identifying and classifying species. Closely related to species delimitation methods, integrative taxonomy seeks to use genetic, ecological morphological, distribution and other relevant data in order to describe, define and assign individuals to species (Cardoso et al. 2009). However the validity and roles of varying data types in these processes is still debated (Bauer et al. 2011; Fujita & Leaché

2011).

In close association with taxonomic advances, developments in species delimitation methods based on molecular data have allowed for quantitative testing of gene flow between putative species (e.g. Beerli & Felsenstein 2001; Hey 2010) and the validity of assumptions of independent evolutionary histories by combining species phylogenies and gene genealogies via ancestral coalescent processes (Yang & Rannala

2010) or through simulation approaches (O’Meara 2010). While these methods allow for quantitative testing of the evolutionary hypotheses that are fundamental to contemporary species concepts and greatly increase the efficacy of identifying morphologically and ecologically cryptic species (Rissler & Apodaca 2007; Carstens & Dewey 2010), they can still yield misleading results in recently evolved species complexes which remain highly challenging to delimit and therefore to describe (Schaffer & Thompson 2007).

Traditional phylogenetic approaches to reconstructing species relationships and history relied upon concatenating data from different genes to effectively create a 16

“supergene” – a method that has been shown to be considerably inaccurate under circumstances where gene trees are discordant (Knowles & Carstens 2007; Chung & Ané

2011). A methodological paradigm shift has occurred recently with the development of species tree methods which consider the reconstruction of gene trees and species trees independently (Knowles & Carstens 2007). These methods promise to be a considerably more accurate method of estimating species relationships and histories especially in groups where gene trees are highly discordant with one another due to processes such as incomplete lineage sorting and horizontal gene transfer – processes which are particularly prevalent in recently evolved lineages (Chung & Ané 2011). In concert with advances in the application of fossil calibrations and molecular clocks to infer timing in species trees

(Drummond & Rambaut 2007), species tree methods promise to allow for a more accurate estimation of relationships among species and the timing of diversification between them, therefore allowing for a more accurate understanding of the evolutionary processes driving diversification.

As a final note, recent and continuing developments in next-generation genomic sequencing (Hudson 2008; Prosperi et al. 2011) mean that more and more genetic data are being brought to bear on these analyses. While these methods are still in their infancy and the implementation of these data is still being developed, rapidly increasing levels of genetic power and thus analytical rigor is being applied through these methods, making it an ideal time to revisit many troublesome and partially resolved groups of organisms, both to further our understanding of these groups and refine emergent analytical approaches with challenging empirical scenarios.

Resolving the systematics of Gehyra – an ideal time

Biologically, Gehyra represent a recently evolved radiation that presents considerable challenges to taxonomy, species delimitation and phylogenetic reconstruction. Despite these difficulties, in many respects Gehyra represent a model system in which to explore the evolutionary biology of recent radiations. Gehyra geckos are highly abundant and easy to collect – which has resulted in a significant body of voucher specimens and associated tissues (n ≈ 8500) for combined morphological and genetic study covering the majority of the known range of the group in Australia.

While past chromosomally based investigations into the diversity of the group met with only partial success, they have yielded a significant level of understanding of the complexity of the group, not apparent from a cursory examination of the morphological diversity present in Australian Gehyra. They have also led to the development of hypotheses regarding the origins, species relationships and modes of diversification that led to this diversity. As such, the significant body of past work on

Australian Gehyra provides a strong platform on which to base future studies of the group on.

Finally, the recent development of new molecular genetic data acquisition and analytical techniques allows for more rigorous evaluation of the group than ever before.

Complimentary to this, the Australian Gehyra radiation provides a challenging but ideal group of organisms on which to empirically test these new methodologies. As such, it is presently advantageous to revisit the diversification of the Australian Gehyra geckos.

Molecular phylogeny of Australian Gehyra (Squamata:

Gekkonidae) and taxonomic revision of Gehyra variegata in

south-eastern Australia

Mark J. Sistrom1, Mark N. Hutchinson1, Rhonda G. Hutchinson2 & Stephen C.

Donnellan1,3

1 South Australian Museum, North Terrace, Adelaide SA 5000, and School of Earth and

Environmental Sciences, University of Adelaide SA 5005, Australia

2 Dept of Genetic Medicine, Women's and Children's Hospital, North Adelaide SA 500x, and School of Molecular and Biomedical Sciences, University of Adelaide SA 5005,

Australia

3 Australian Centre for Evolutionary Biology and Biodiversity, University of Adelaide SA

5005, Australia

Zootaxa (2009) 2277: 14-32. 19

Statement of Authorship

This chapter is a published research article and is reproduced with kind permission of

Magnolia Press (see Appendix 1)

Mark J. Sistrom (candidate)

Corresponding author: Responsible for molecular laboratory work, analysis and interpretation, participated in manuscript preparation, produced Figures 2 and 8 and oversaw manuscript revision.

Signed…………………………………………………………..Date……………

Mark N. Hutchinson

Sought and won funding, co-supervised direction of study, responsible for morphological data collection, analysis and interpretation, participated in manuscript preparation, took photographs for Figures 5 and 7 and produced Figure 6.

I give consent for M.J. Sistrom to include this paper for examination towards the degree of Doctor of Philosophy.

Signed: Date: 16/09/2011

Rhonda G Hutchinson

Responsible for chromosomal laboratory work and interpretation, produced Figure 4.

I give consent for M.J. Sistrom to include this paper for examination towards the degree of Doctor of Philosophy.

Signed: Date: 14/09/2011

Stephen C. Donnellan

Sought and won funding, co-supervised direction of project, allozyme data collection, analysis and interpretation, participated in manuscript preparation, produced figures 1 and

I give consent for M.J. Sistrom to include this paper for examination towards the degree of Doctor of Philosophy.

Signed: Date:16/09/2011

Abstract

We provide the first phylogenetic hypothesis for the Australian species of the gekkonid genus Gehyra, based on 1044bp of the mitochondrial ND2 gene. Species representing the Asian, Melanesian and Australian radiations are resolved as separate clades, indicating relative isolation and independence of each of these evolutionary lines.

Within the Australian radiation, the arid zone species form a monophyletic subgroup distinct from the remaining species found in tropical and warm mesic habitats. Extensive chromosome variation and highly variable external morphology have made species recognition difficult within Gehyra, exacerbated by the likely presence of numerous undescribed cryptic species. Three species of Gehyra are currently recognized in the southeastern inland of Australia, G. variegata, G. montium and G. purpurascens. We redescribe a fourth species, G. lazelli, to include those populations long referred to informally as the 2n=44 chromosome ‘race’ of Gehyra variegata. Gehyra lazelli widely overlaps the distribution of G. variegata in South Australia and the southern inland of

New South Wales, with no suggestion of intergradation in morphology, mitochondrial

DNA, allozyme variation or karyotype.

Key words: Lizards, speciation, Australia, phylogeny, taxonomy, mitochondrial DNA 22

Introduction Gehyra is a large genus of climbing geckoes, ranging across Asia and into the

Pacific and with a large centre of endemism in Australia (Mitchell 1965). Gehyra is a member of the clade traditionally treated as the subfamily Gekkoninae (Kluge 1987), more recently treated as a family Gekkonidae, distinct from several other gekkonoid families (Han et. al. 2004; Gamble et. al. 2007). Gehyra species share a distinctive toe morphology, possessing elliptical, subterminal, adhesive toe pads and clawless first digits on the fore and hind feet. Eighteen species are currently recognised from Australia. The genus is conservative in morphology and many of its species differ only subtly in external appearance. Nevertheless the group shows considerable chromosomal heterogeneity and the present tally of species is probably an underestimate.

King (1979) published the first of a series of studies on chromosomal variation within Gehyra, addressing populations referred to the species Gehyra punctata (Fry

1914) and G. variegata (Duméril and Bibron 1836). Six chromosome groups were recognised within the two nominal species. Populations of ‘G. variegata’ included a 2n

=44 karyotype and two 2n=40 (40a and 40b) karyotypes, while G. ‘punctata’ included populations with diploid numbers of 44, 42 and 38. King further expressed the view that disjunct populations of some chromosome groups had diverged in morphology to the point where they may represent distinct species. Thus there were two allopatric 2n=42 populations (central Northern Territory (NT) and central west of Western Australia

(WA)) and three allopatric populations of the 2n=44 karyotype (northern NT, central NT and southern South Australia (SA)). In all, there was prima facie evidence for nine species in this species complex.

Moritz (1986) reviewed this group, including consideration of work by Storr (1982) 23 and King (1982b) who had begun to revise the taxonomy of Gehyra. Moritz pointed out that the attempts to delineate species within the central and northern Australian area where populations with differing karyotypes overlapped had been only partly successful, and his extensive sampling of central Australian populations revealed a complex and confusing pattern of morphological and chromosomal variation. This situation was confusing to subsequent workers because King and Moritz each used different sets of criteria to define entities. King distinguished groups (putative species) by karyotypes only whereas Moritz used a combination of karyotypes and unspecified morphological variation. As an example, Moritz (1986) recognized three morphological groups in central Australia that all shared the 2n=42a karyotype as “2n=42a montium”, 2n=42a montium/variegata” and “2n=42a variegata”.

Based on the work of King, Moritz and Storr, there are three species of Gehyra in the south-eastern interior of Australia. These are G. variegata, with two chromosomal groups, the widespread 2n=40a and the 2n=44 (referred to as the 2n=44f group by

Moritz), G. purpurascens Storr 1982 (2n=40c) and G. montium Storr 1982. The last species has been associated with a 2n=38 karyotype by Storr (1982), but populations from the vicinity of the type locality of G. montium, Mt Lindsay in remote northwestern

SA, have not been karyotyped, and Moritz has recorded Gehyra populations with a variety of karyotypes in the ranges straddling the SA-WA-NT borders, including 2n=40a,

2n=42a and 2n=42b, but not the 2n=38 karyotype, which was only reported from the central ranges of the NT.

Resolution of the species identity of all of the populations assigned to either G. montium or G. variegata will require careful programs of field sampling and correlated 24 morphological and chromosomal study to detect species boundaries. Here we begin this process by dealing initially with the taxonomy of Gehyra from the south-eastern interior of Australia where there is evidence for four chromosomal groups 25

Materials and methods

Specimens from the collection of the South Australian Museum, Adelaide (SAMA) form the basis of our study, including a few of the specimens karyotyped by King (1979).

Locations of Australian sites sampled for molecular and karyotype analyses are shown in

Fig. 1. Details of the specimens used for the molecular genetic analyses are presented in

Appendix 1.

Morphology. The Australian species of Gehyra are distinguished morphologically using a relatively small set of qualitative characters (e.g. see Storr 1979; 1982, King

1982b). The condition of the expanded subdigital lamellae (fully divided as opposed to undivided or merely notched) is a primary feature separating typically arid zone species from tropical/mesic species. Colour pattern, whether spotted, lined or weakly marked, and overall colour hue (reddish versus greyish) is also used, even though colour shades and patterns are unstable in preserved specimens. Informative scalation features include the shape of the rostral scale (angular at its dorsal apex, or flat) and the number and relative sizes of the scales surrounding the nostril. The set of scales surrounding the nostril comprises the rostral, which has a partial mediodorsal vertical division ('rostral crease'), a large anterior supranasal, a smaller posterior supranasal, and two postnasals, each usually about the same size as the posterior supranasal, and the first infralabial. The two anterior supranasals may contact or be separated by one or more smaller scales.

Enlarged chin shields always comprise a pair of elongate postmentals that contact only the first infralabial, flanked by a pair of shields that contact the first and second infralabials. Sometimes there is a third pair of chin shields that contacts the second or the second and third infralabials. The presence and contacts of this third pair varies between 26 species. In all four of the Gehyra discussed below, a secondary scale row (the sublabials,

King 1982b) is developed, ventral and parallel to the infralabials, starting from a notch in either the second or third infralabial.

We assessed all of these features in the populations that occur across South

Australia and the adjacent inland of New South Wales (NSW), Victoria (Vic) and southwestern Queensland (Qld). All length measures are in mm.

FIGURE 1. Map showing distribution of Australian sample locations for molecular and karyotype analyses. Key to symbols: australis ; borroloola ; catenata ; dubia ; 27 ipsa G; koira D; lazelli ; minuta ; montium ; nana ; occidentalis F; pamela ^; pilbara ; punctata ; purpurascens ; robusta ; variegata ; xenopus .

We assessed all of these features in the populations that occur across South

Australia and the adjacent inland of New South Wales (NSW), Victoria (Vic) and southwestern Queensland (Qld). All length measures are in mm.

Mitochondrial DNA sequencing. The nucleotide sequence of the entire NADH dehydrogenase subunit 2 (ND2) was determined for 70 individuals representing all currently recognized species of Gehyra from Australia, four species from Oceania and

Melanesia and three outgroups from the genera Cyrtodactylus, Hemiphyllodactylus and

Lepidodactylus [Aaron Bauer pers. comm.]. DNA was extracted from frozen and alcohol preserved liver tissue stored in the Australian Biological Tissue Collection (ABTC) at the

South Australian Museum (SAMA) using a PuregeneTM DNA Isolation Tissue Kit D-

7000a (Gentra Systems) following the manufacturer's guidelines. ND2 and partial flanking tRNA's were amplified using the primers M112F (5'-

AAGCTTTCGGGGCCCATACC- 3') and M1123R (5'-

GCTTAATTAAAGTGTYTGAGTTGC - 3') designed in the flanking methionine and alanine tRNA's. Amplifications were carried out in 25μL volumes using standard buffer and MgCl2 concentrations, 0.1 mM each dNTP, 0.2 μM each primer, 0.75 U AmpliTaq

Gold® DNA Polymerase (Applied Biosystems) and approximately 100ng of genomic

DNA. Thermocycler profiles were: 9 min at 94oC, then 35 cycles of: 45 s at 94oC, 45 s at

60oC and 1 min at 72oC for 1 min with a final extension step of 6 min at 72oC. The PCR product was purified using a Millipore Montage® PCR384

Cleanup Kit (Millipore Corporation) following the manufacturer’s guidelines. 28

One microlitre of purified product was used as template for a BigDye Terminator sequencing reaction, which was carried out in 20μL reactions, consisting of 1μL of

BigDye (Applied Biosystems), 7μL of 2.5x buffer and 1μL of 5pmol/μL primer.

Sequenced products were separated on an Applied Biosystems 3730xl capillary sequencer.

The protein-coding region of ND2 was translated into amino acid sequences using the vertebrate mitochondrial genetic code and was compared to Gekko gecko (GenBank accession EU054288) translations to check for unexpected stop codons and frame shifts.

We obtained both forward and reverse sequences for each PCR product. Sequence alignments were carried out using Geneious version 3.8.5 (Drummond et al. 2008).

GenBank accession numbers for the ND2 sequences are: GQ257742-GQ257811.

Phylogenetic analysis. Phylogenetic analyses used maximum likelihood (ML) and Bayesian methods. Aligned sequences were partitioned according to codon position and Modeltest version 3.06 (Posada & Crandall 1998) was used to evaluate different models of nucleotide substitution. The model GTR+I+G was selected for codon positions

1 and 2, with the model GTR+I selected for 3rd codon positions. ML analysis with 100 bootstrap replicates was carried out using the RAxML BlackBox web server (Stamatakis

2006; Stamatakis et. al. 2008). Bayesian analysis was conducted using MrBayes version

3.1 (Ronquist & Huelsenbeck 2003). Data were partitioned for each codon position and branch lengths unlinked. Convergence was assessed from multiple ruins and plots of likelihood against generation. For the final analysis, 5 million MCMC chains were run, sampled every 100 generations, with the first 5000 samples discarded as burn-in, leaving

95 000 trees for construction of a majority rule consensus. 29

The number of net nucleotide substitutions per site between populations (Da value) (Nei 1987) for ND2 sequences of 2n=40a and 2n=44f variegata samples was calculated using the program DnaSP 4.90 (Rozas et. al. 2003) in order to assess nucleotide divergence.

Allozyme electrophoresis. Allozyme electrophoresis of liver homogenates was conducted on cellulose acetate gels (“Cellogel”, Chemetron) according to the methods of

Richardson et al. (1986). The proteins and enzyme products of 31 presumed loci were scored (Table 1). Alleles were identified by comparison with samples that were repeatedly included on each gel (internal controls) and through critical side-by-side comparisons (line-ups; see Richardson et al. 1986).

Karyotypes. We obtained karyotypes from tissue cultures prepared from reproductive tract epithelia (oviducts in females, efferent ducts in males). Tissues were cultured at 32o C using AmnioMAX-11 (Gibco) complete media. Standard tissues culture methods were used to establish cultures, harvest and stain metaphase spreads for karyotypic analysis (Freshney 2000). 30

Results

Mitochondrial nucleotide sequences. Fig. 2 shows the phylogenetic relationships among ND2 sequences of Gehyra and three outgroups as determined by

Bayesian inference. The tree also indicates nodes where Bayesian posterior probabilities and maximum likelihood non-parametric bootstrap proportions where the values were >

95% and >70% respectively.

The Melanesian and New Guinean species included in the phylogeny, G. baliola

(Duméril and Duméril 1851), G. membranacruralis King and Horner 1989, G. mutilata

(Wiegmann 1835) and G. oceanica (Lesson 1830), are highly distinct from the Australian taxa. The analysis indicates a relationship between G. baliola and G. oceanica, however the relationships among the deeply divergent clades within the genus are not resolved with our data. 31

FIGURE 2. Bayesian majority rule consensus phylogenetic tree showing relationships among mitochondrial ND2 haplotypes in Gehyra. Asterisks indicate nodes that had

Bayesian posterior probabilities > 95% and non-parametric bootstrap proportions from

1000 ML pseudoreplicates of > 70%. The outgroups Cyrtodactylus, Hemiphyllodactylus and Lepidodactylus were used to root the tree. See Appendix for specimen numbers

(either ABTC [no letter at beginning of specimens number] or WAM registration number

[begins with W]) and other details.

The Australian taxa fall into two clades with G. australis, G. borroloola, G. catenata, G. dubia, G. ipsa, G. koira, G. occidentalis, G. pamela and G. robusta forming one and G. minuta, G. montium, G. pilbara, G. punctata, G. purpurascens, two nominal groups of G. variegata, and G. xenopus forming the other. These represent the G. australis complex (King 1983a) and G. variegata-punctata complex (King 1979), respectively, with considerable accuracy.

The phylogenetic analyses show that four distinct clades of Gehyra exist in south- eastern Australia, representing G. montium, G. purpurascens and two nominal groups of

G. variegata representing the 2n=40a and the 2n=44f karyotype groups. A considerable level of divergence between the latter is evident, as shown by the Da value between

2n=40a sequences and 2n=44f sequences being 0.159 ± 0.027 (Nei 1987).

Given the partially sympatric distribution of clades, the high level of phylogenetic structure among the south-eastern Australian haplotypes is strongly indicative of a significant period of reproductive isolation and therefore potentially speciation between the G. variegata 2n=40a and 2n=44f karyotype groups and between these and the other 33 two south-eastern Australian species. Furthermore the G. variegata 2n=44f karyotype group is the sister clade to not just all of the other south-eastern Australian clades but also to G. minuta, G. nana, G. pilbara and G. punctata, which is prima facie evidence that two G. variegata karyotype groups are separate species under a phylogenetic species concept.

Allozyme Electrophoresis. We collected specimens of G. variegata in sympatry at

Lancoona Station, northeast of Hillston, NSW, where Moritz (pers. com.) had earlier recorded individuals with both the 2n=40a and 2n=44f karyotypes,. The external morphology of these was the same as in the South Australian populations (see below), and a subsequent collection of a further four specimens with the colour pattern of the

2n=40a group and three with that of the 2n=44f group was used to examine the possibility of gene flow between the two. We also included a selection of other Gehyra taxa from SA and adjacent areas of WA and the NT for comparative purposes.

Table 1 shows the allele frequencies for the 31 loci among the 10 operational taxonomic units (OTUs) genotyped. See Appendix 1 for locations included in each OTU. The specimens from Lancoona matching the two chromosome races were also unambiguously separated by allozymes. The two colour pattern types showed fixed differences at nine loci (Acoh-2, Gapdh, Aat-2, Idh-1, Idh-2, PepB-1, PepB-2, PepD, Iddh), and almost fixed differences at three others (Acoh-1, Fbp, Gpdh). Considering only the nine loci showing fixed differences, the probability that only a single species is represented by the seven specimens can be calculated. Population allelic frequencies, p and q from the Hardy-

Weinberg theorem, for each locus are notionally 0.57 and 0.43. If a single freely interbreeding population is present, then the probability of obtaining no heterozygotes 34 among seven individuals at nine loci by chance is (1–2 x 0.57 x 0.43)7 x 9 = 3.7 x 10-19.

Accordingly, the hypothesis of a single species at this site is very unlikely, and a reasonable alternative is that two genetically independent species are present.

TABLE 1. Allele distributions (frequencies expressed as percent) among 10 OTUs of

Gehyra based on 31 enzyme loci. See Appendix 1 for locations included in each OTU.

The abbreviations for proteins/loci used and Enzyme Commission numbers are listed in

Murphy et al. (1996). Numbers in brackets are sample sizes. The following loci were invariant: Ca, Gpi, Ldh-1, Ldh-2, Mdh-2, Pgam, Pk, Sod, and Tpi.

minuta 2n=42a 2n=40a purpurascens 2n=44f variegata OTU 1 2 3 4 5 6 7 8 9 10 Locus (5) (6) (4) (9) (4) (11) (4) (3) (9) (3) Aat-2 c c c(75) c(94) a c b c b b b(25) a(6) Acoh-1 c b b b c b b b(67) a a a(17) c(17) Acoh-2 d b(50) d(50) c(50) e(83) c(86) c(63) c e d(50) c(33) c(38) d(33) d(17) e(14) d(25) e(50) a(8) b(12) b(17) e(12) d(9) Adh-2 c c c c c c c(63) c(88) c(89) c(67) a(25) d(12) b(11) b(33) b(12) Eno a a a a a(83) a a a a a b(17) Fbp a a(80) a a(83) b a a a(88) a(94) a b(20) b(17) b(12) b(6) Gapdh a a a a b a a a a a Gpdh a a(62) a(38) b(88) b(83) a a(83) a b a(83) b(38) b(62) a(12) a(17) b(17) b(17) 35

Gtdh a a a a a a a a a a(83) b(17) Iddh a a a a(78) a a a b b b b(22) Idh-1 a a a a b a a a b b Idh-2 b a(92) a a(88) b a a a b b c(8) c(12) Lgl b a(8) b(88) b(94) b b b b b b b(84) c(12) a(6) d(8) Mdh-1 b b b(75) b b(83) b a b b b a(25) a(17) Mpi b(90) b(83) b(88) b(89) b b(95) b b(88) b b a(10) c(17) a(12) a(11) a(5) a(12) PepA a a a a a a(82) a a a a b(18) PepB-1 e c(50) c c(89) a c c(50) c a a f(33) b(11) b(38) g(17) d(12) PepB-2 b(50) a a(88) a c(67) a b a c c a(40) b(12) d(33) c(10) PepD a(10) b b(88) b(94) c b b(50) b b c(83) b(90) d(12) d(6) c(38) b(17) d(12) Pgdh b(80) a(50) a(62) b(61) a(67) a a(75) a(50) a a(50) a(20) b(50) b(38) a(39) b(33) b(25) b(50) b(50) Pgm a a a a a a a(62) a a a b(38)

FIGURE 3. Neighbour-joining network of Cavalli-Sforza chord distances among OTUs based on frequencies. See Appendix 1 for locations included in each OTU.

Morphology and karyotypes. We obtained karyotypes from populations where published data (King 1979; Moritz 1984, 1986) indicated that more than one karyotype was present, in order to determine the degree to which a particular karyotype correlated with external morphology.

In each case we found that the karyotype was correlated with morphology. The

2n=40c specimen (SAMA R51606) was consistent with the description of G. purpurascens (Storr 1982) and the 2n=42 specimens were consistent with Storr’s (1982)

G. montium.

The remaining two karyotypes (2n=40a, 2n=44f – Fig. 4) pertain to populations traditionally referred to G. variegata. We confirmed syntopy of animals with the the 37

2n=40a (SAMA R51832) and 2n=44f (SAMA R51801) karyotypes at Mudlapena Spring,

Flinders Ranges, SA, to add to the syntopy already recorded by Moritz at Lancoona

Station, NSW (e.g. SAMA R38942 and R38943, respectively).

Animals with each karyotype consistently differed in colour pattern. The colour pattern of the 2n=40a animals varied, but consistently included continuous temporal lines and dark markings that often formed continuous longitudinal and transverse lines, which were coordinated with light markings that acted as edges or highlights for the dark lines

(Fig. 7). In contrast, 2n=44f animals had no continuous dark, light edged lines. Instead the dark markings were present as short, irregular dark speckles and ‘squiggles’, varying from sparse to so continuous as to form a reticulum over the dorsal surface. White markings were present as discrete circular spots, arranged independently of the dark markings (Figs 5, 7). Other morphological features (scalation) were generally similar in these two, as they are in G. purpurascens, but the males showing the colour pattern associated with the 2n=44f karyotype had consistently higher numbers of preanal pores than those showing the colour pattern seen in the 2n=40a males. 38

FIGURE 4. A. Metaphase karyotypes of the two chromosomal forms occurring in the

Flinders Ranges, South Australia: G. lazelli (2n=44f), SAMAR52012, Warden Hill, and

G. variegata (2n=40a), SAMAR51962, Moosha Bore. Boxes in B show the two chromosome pairs (5 and 7) that King (1979) suggested were fusion products from a primitive 2n=44 kartyotype like that shown in A.

Systematics. There is now extensive evidence available to show that populations traditionally referred to Gehyra variegata that have the 2n=44f karyotype belong to a distinct species. The phylogenetic relationships shown by the mitochondrial nucleotide sequence data unambiguously show that the two karyotypic groups are independent lineages, with the 2n=44f species branching close to the base of the arid zone radiation 39 within Gehyra, while 2n=40a G. variegata is nested among several other morphologically and karyotypically distinct species. In areas of sympatry (Flinders

Ranges, SA; Lancoona, NSW;) the absence of heterozygotes for allozyme markers and chromosome rearrangements indicate the absence of gene flow between the two karyotypic groups, and the colour patterns and other aspects of morphology are consistently distinguishable. The holotype (and only) specimen of Wells and

Wellington’s (1983) Dactyloperus lazelli shows the colour pattern and preanal pore count of the 2n=44f species, and we therefore assign the G. variegata 2n=44f to this species and redescribe it. The 2n=40a populations are left in G. variegata for the present, as the large task of genetic sampling across the range of G. variegata, both the 2n=40a and

2n=40b groups of King (1979) is still in progress.

Gekkonidae

Gehyra lazelli (Wells & Wellington, 1985) Southern Rock Dtella Figs. 5–8

Dactyloperus lazelli Wells & Wellington, 1985: p. 11. Holotype: AMS R116972

(formerly AMS Field Series 16793), adult male, from “Mt Colley”, Cocoparra National

Park, near Griffith, N.S.W. (Fig. 5a).

Dactyloperus annettae Wells & Wellington, 1985: p. 11. Holotype: AMS

R116971 (formerly AMS Field Series 16789), adult female, from Willandra National

Park, near Hillston, N.S.W. (Fig. 5b). 40

FIGURE 5. The type specimens of A) Dactyloperus lazelli and B) D. annettae.

Diagnosis. A moderate sized Gehyra (max. Snout-vent length (SVL) 59 mm) with divided subdigital lamellae, two or three pairs of enlarged chin shields, a dorsal pattern combining small pale spots and irregular, dark spots or short wavy lines, and a diploid chromosome number of 44. Most similar to G. nana, from which it differs in grey to brown rather than rufous dorsal colouring with more prominent black flecks and lines.

Gehyra lazelli is sympatric or parapatric with two other species, G. variegata (2n=40a form) and G. purpurascens. Distinguished from G. variegata by fine spotted rather than ladder-like colour pattern, the white spots not margining the dark markings, slightly larger size, higher preanal pore counts and (in syntopy) rock- dwelling rather than arboreal habits. Distinguished from G. purpurascens (2n=40c) by bolder spotted pattern, with larger black flecks and wavy lines and numerous white spots present in adults, and smaller size (max. SVL of G. purpurascens 65 mm) .

Description. SVL36–59 mm (mean 51.2, n= 46). Length of tail 46–49 mm (mean

92% SVL, n=3).

Rostral flat dorsally to weakly gabled, with a median groove descending to about

50% of the height of the scale. Nostril surrounded by rostral, first supralabial, two subequal postnasals and a larger supranasal. Internasals 0 to 3, mode 1. Supralabials 8–

10, mode 9. Infralabials 8–10, mode 9. Two pairs of enlarged chin shields always present; a third pair sometimes present and contacting the second infralabial but not the third (Fig.

6). Sublabial scale row starts at a notched infralabial, the second or third with similar frequencies. Lamellae under pad of fourth toe divided, 7 pairs showing obvious surface architecture of fine hairscales. Preanal pores in males 12–18 (mean=15, n=22), arranged in a chevron with median pore anteriormost. 42

In preservative (Fig. 6a), dorsum light grey to light brown with irregular dark spots, short wavy lines or streaks and numerous small, circular, white to pale grey spots. Spots usually forming regular transverse series around (original) tail but arranged more haphazardly on the head and body. White and black markings mostly not contacting one another.

In life (Fig. 7), the dorsal background colour during the day can be considerably darker grey-brown to brown. At night, in common with most Gehyra, the contrast in the colour pattern is greatly reduced and paler overall.

FIGURE 6. Chin shield scalation and rostral-nasal scalation in Gehyra lazelli. A) tip of snout of SAMA R56407 showing typical arrangement of scales. This specimen has one internasal scale wedged between the supranasals; rostral apex is almost flat in this 43 specimen. B) chin shield arrangement of the holotype (AMS R116972) showing one of the common arrangements. C) chin shields of another specimen (SAMA R63427) showing an additional small chin shield pair contacting the second infralabial. In both, the sublabial row starts at the notched second infralabial. Abbreviations: cc: chin shields

(excluding postmentals), il: infralabials, m: mental, pm: postmental, pn: postnasal, r: rostral, sbl: sublabials, sl: supralabials, sn: supranasal.

Distribution. Rocky ranges and outcrops in the Gawler, Flinders and Mt Lofty

Ranges of South Australia, extending eastwards into south-central New South Wales and southwest to the coast of the Great Australian Bight as far west as Ceduna and the Nuyts

Archipelago (Fig. 8).

Comments. Wells & Wellington (1985) described three species of Gehyra (as

Dactylopterus (Fitzinger 1843)) from western NSW. Dactyloperus annettae (type locality near Hillston, NSW), is a female that has greatly faded in preservative, but its colour pattern is still discernible, consisting of scattered small dark flecks that fail to form lines or continuous series. Dactyloperus lazelli, from near Griffith, NSW, is a male in much better condition, with a colour pattern of blackish speckles forming a reticulum over the entire head and body, with no continuous light-edged lines on the head or back, and 17 preanal pores. Neither specimen preserves any white markings, but this is a frequent artifact in preserved specimens of Gehyra. Their third new species, D. kingi, from

Walgett, was synonymized by Bauer and Henle (1994) with G. variegata, but our examination of the type shows it to be indistinguishable from populations currently referred to Gehyra dubia (Macleay, 1877) (Cogger 2000; King 1983). 44

FIGURE 7. Live specimens of A) G. lazelli from the Middleback Range, SA, and B) G. variegata from Merbein, Victoria.

The original descriptions of both D. annettae and D. lazelli list a series of character states for the two holotypes, but do not provide differential diagnoses. We regard these two specimens and the 2n=44f chromosome group as conspecific. Of the two, described on the same page in the same publication, we propose that the holotype of D. lazelli, with its better preserved colour pattern and diagnostic preanal pore count, is the more unambiguous choice in applying a name to the 2n=44f chromosome group (Fig. 5).

Accordingly we propose that the 2n=44f variegata should be known as Gehyra lazelli

(Wells & Wellington, 1985), new combination, with Dactyloperus annettae as a junior synonym. The stated collecting locality, Mount Colley, could not be found in a gazetteer for any landmarks in the Cocoparra National Park or adjacent area. However there is a

Mount Caley within the park, which may be the correct name for the type locality. Mount

Caley is 25 km ENE of Griffith, at 34° 10’ 48’ S, 146° 17’ 23” E.

One other older name that we considered was Gecko grayi Steindachner, 1867. The holotype specimen (NMW 19800:1) was said to have come from New South Wales, but with no other data (Steindachner 1867; Cogger et al. 1983; Tiedemann et al. 1994). The name was regarded by Tiedemann & Häupl (1980) and Tiedemann et al (1994) as a synonym of G. australis Gray, 1845, by Cogger et al. (1983) as a synonym of Gehyra variegata (Duméril & Bibron, 1836), while Bauer & Henle (1994) considered it a possible senior synonym of Gehyra dubia (Macleay, 1877). The specimen is in poor condition (photographs provided by F. Tiedemann and H.G. Cogger), with only traces of colour pattern visible on the body, and some weak dark transverse lines on the tail

(detached). However the specimen can be excluded from either lazelli or variegata by virtue of its notched but mostly undivided toe pad lamellae and its chin shield 46 arrangement (Fig. 3 in Steindachner 1867, Tafel I), the third pair of chin shields being relatively large and wedged between the second and third infralabials, the sublabial row starting from a notched fourth infralabial. This combination is seen on some eastern

Australian species presently referred to G. dubia and some G. catenata, but not on

Gehyra from the south-eastern interior of Australia.

FIGURE 8. Distribution map of museum specimens identified as G. lazelli.

Gehyra in the south-eastern interior of Australia. Four nominal species are now known from this region, namely G. lazelli, G. montium, G. purpurascens and G. variegata. All overlap to some degree in morphology and distribution, so that in most areas at least two and sometimes three species can occur in close proximity.

The difficulty in allocating specimens to species is made somewhat easier because three of the species, G. lazelli, G. montium and G. purpurascens, show a limited amount of morphological variation and are fairly tightly associated with particular microhabitats.

The confusion is generally due to variation in G. variegata, which shows a wide variety of colour pattern variants and overlaps in size and habits with each of the other three. In practice, difficulty is experienced most often in distinguishing between juvenile and subadult G. purpurascens and G. variegata as these two may at times be found on the same tree, and G. lazelli and G. variegata, which overlap widely. The distinctions between G. lazelli and G. variegata are noted above in the re-description of G. lazelli, while most G. purpurascens can be recognized by a combination of a relatively broader rostral, fewer preanal pores and weaker colour pattern, especially the dark markings being small, numerous and scattered rather than bolder and more continuous. However, some preserved specimens from among these three species may not be certainly identifiable from morphology alone. Where species identity is essential, our data show that each of the three is readily separable by ND2 sequences. 48

Discussion

Gehyra has long been considered as a relatively ‘recent’ arrival in Australia with its origins in South-East Asia supported by the presence there of species assigned to the genus (Cogger & Heatwole 1981; Taylor 1963). Recent broad phylogenetic comparisons across gekkonines support an Asian relationship, but within this broader region, Gehyra seems to be anchored close to Australia; the sister taxa of Gehyra are Perochirus and

Hemiphyllodactylus, both centered on the Indonesia-Malaysia-Philippines region rather than the southeast Asian mainland itself (A. M. Bauer, pers. comm.). As might be expected from this relationship, most of the morphological variation, and nearly all of the species, are found in Australia and Melanesia with only a minor group of small species resembling G. mutilata being typical of mainland South-East Asia. The results of our initial survey of the relationships among the nominal Australian species, and representatives from outside Australia, are in accord with geography. We find five major clades within our sampling of Gehyra: the Asian G. mutilata, two clades among the

Melanesian samples (one comprising only G. membranacruralis alone, and the other G. baliola and G. oceanica), a clade of tropical Australian species and a clade of predominantly semi-arid to arid zone species. While these five clades are well supported, the branching order is not robust at present.

Results from phylogenetic analyses suggest several details regarding the evolutionary history of the group within Australia. The genetic distinctiveness of the

Australian and Melanesian Gehyra clades suggest that, while sharing a common ancestry, speciation has proceeded independently within the two regions. This pattern may be an artifact of under-sampling in New Guinea, but Gehyra from the two regions show 49 divergent trends in morphology. Melanesian species are generally large in size (and include all of the largest species), characteristically have very loose skin with baggy skin folds in the legs and flanks. Their skin is easily mechanically damaged and shed in pieces if the lizard struggles against restraint. Australian species are medium to small in size, with less of the fragile loose skin, and include many species that have adapted successfully to the arid zone. Furthermore the two Australian Gehyra clades display distinctively different evolutionary patterns. Members of the G. australis species complex

(King 1983b) which generally lay two- egg clutches are associated with Australia’s tropical regions while the taxa representing the G. variegata species complex (King

1979), which generally lay single-egg clutches, are associated primarily with the

Australian arid zone.

Despite allowing some insight into the evolutionary history of Gehyra within southern Australia, it is worth noting that this analysis is based on a single mitochondrial locus. A forthcoming multilocus nuclear and mitochondrial gene based phylogenetic analysis will allow a more thorough and robust examination of the evolutionary history of the genus in Australia.

The current morphological set of taxonomic characters that are used to define the species of Gehyra is difficult to apply in practice. Several characters used in the taxonomy of Gehyra are more variable and are more difficult to interpret than would appear to be the case according to the original species descriptions. The shape of the rostral is one such character, whether rising to a median angular apex (‘gabled’) or with its dorsal margin horizontal. Most Australian Gehyra have a rostral that is best described as ‘moderately gabled’, seldom appearing horizontal as described for, e.g. G. 50 purpurascens, and often not especially sharply gabled as described for e.g. G. variegata.

The chin shields are usually expressed as simply two pairs or three pairs, but the number difference is less important than the arrangement of these scales relative to the infralabials, especially their contacts with the second and third infralabials and whether the second or third infralabial is notched for the start of the sublabial scale row. Colour pattern is useful, especially in live animals, but it is often difficult to determine in preserved specimens, as these geckos frequently fade a short time after preservation, especially specimens preserved under field conditions where heat and light accelerate fading.

All of the above difficulties have clearly had an adverse effect on the ability of workers to identify species confidently in the field and in preserved collections using either existing species descriptions or keys derived from them. We became acutely aware of this problem during the course of the current study as the observed position in the mitochondrial DNA tree of a high proportion of specimens did not match their position expected from their initial identification. Our subsequent morphological analyses, however, were consistent with the molecular placements.

Four species of Gehyra can be recognized now in the south-eastern interior of

Australia, but there are taxonomic issues remaining to be clarified. First, the type population of Gehyra montium has yet to be karyotyped, leaving the precise identity of the species uncertain as two karyotypic groups of small rock- dwelling Gehyra are known from the central ranges of northwestern SA, southwestern NT and eastern WA (2n=42a and 42b; Moritz 1986). Second, while we continue to use G. variegata for both the eastern 2n=40a and western 2n=40b populations, it is still uncertain whether these 51 karytotypic groups are indeed conspecific. Thus there is a need for further combined karyotypic, molecular and morphological analyses incorporating typotypic material.

Acknowledgments

We thank Craig Moritz (University of California, Berkeley) for specimens and data on karyotypes, Paul Horner (Northern Territory Museum) and Pat Couper (Queensland

Museum) for the loan of specimens. Dr Franz Tiedemann of the

Naturhistorischesmuseum Wien and Hal Cogger provided photographs, information and observations on the type of G. grayi. The study was funded in part by Australian

Biological Resources Study grant 207-43 to MNH and SCD. 52

Delimiting species in recent radiations with low levels of

morphological divergence: a case study in Australian Gehyra

geckos

Mark Sistrom1,2,3, Steve Donnellan2,3 & Mark Hutchinson2,3.

1 - School of Earth and Environmental Sciences, University of Adelaide, Adelaide,

Australia, 5005.

2 - South Australian Museum, North Terrace, Adelaide, Australia 5000.

3 - Australian Centre for Evolutionary Biology and Biodversity, University of Adelaide,

Adelaide, Australia, 5005.

Corresponding author: [email protected]

This chapter is formatted in a style appropriate for submission to the Proceedings of the

Royal Society Series B: Biological Sciences with the exception of the in text references which are maintained in a “Chicago manual of style” format for consistency within the thesis. 53

Statement of Authorship

Mark J. Sistrom (candidate)

Corresponding author: Responsible for molecular data collection, analysis and interpretation, conducted morphological analysis, drafted manuscript, produced all figures, oversaw manuscript revision.

Signed…………………………………………………………..Date……………

Mark N. Hutchinson

Sought and won funding, co-supervised direction of study, responsible for morphological data collection, provided morphological data collection methods section.

I give consent for M.J. Sistrom to include this paper for examination towards the degree of Doctor of Philosophy.

Signed: Date: 16/09/2011

Stephen C. Donnellan

Sought and won funding, co-supervised direction of project, provided assistance in analysis selection and manuscript revision.

I give consent for M.J. Sistrom to include this paper for examination towards the degree of Doctor of Philosophy.

Signed: Date: 16/09/2011

Abstract

Recent conceptual and methodological advances have led to an increased ability to apply a multifaceted approach to delimiting species, which is particularly useful in delimiting recently diversified species where a single lines of evidence lead to incorrect species delimitation or assignment of individuals to species (e.g. cryptic, morphological species and paraphyletic, hybridizing species). The species of the Australian Gehyra gecko radiation have historically proven difficult to delimit due to the uniform, almost continent wide distribution of the group and conservative morphology that contrasts with high levels of chromosomal and genetic diversity within the group Using an integrated approach to species delimitation and taking advantage of morphological, geographic distributional and multi-locus genetic data, we investigated the diversity within three taxonomically challenging Gehyra species from the G. variegatata group from the

Australian arid zone. We found that these three species represent up to eight distinct phylogenetic lineages, which display different patterns of morphological distinction and reproductive isolation. Using a recently developed Bayesian species delimitation method, we also find different levels of support for putative species dependent on the priors on population size and timing of diversification assumed. Our results show that the current taxonomy does not adequately account for the diversity of the group and we describe an additional three Gehyra species. The discrepancies between the different lines of evidence considered indicate that the diversification in the examined species is recent and ongoing thus posing challenges for both species concepts and the delimitation of species.

Keywords: species delimitation, speciation, gecko, Australia, arid zone. 56

Introduction

Accurate delimitation of species is of fundamental importance for the majority ecological, evolutionary and conservation studies. In light of current threats to global biodiversity, expeditious species delimitation is additionally of increasing importance for a large portion of earth’s biota, as the need to identify species before they become extinct is recognized (Koh et al. 2004) However, it is often difficult to delimit recently evolved species as fixed differences in characters allowing for consistent diagnosis may not have accumulated, and potential admixture between species can produce individuals with phenotypically and genetically intermediate states which generate conflict between different data types (Shaffer & Thompson 2007). As such, species can lack the traits typically used for delimitation and variation between species can be masked by similar levels of variation within species.

Whilst species concepts are numerous (De Queiroz 1998; 2007) there has been some consensus that the general aim of species delimitation is to identify separately evolving lineages and describe them (De Queiroz 2007). This general lineage concept of species defines species as “separately evolving metapopulation lineages” and defines the properties of those metapopulations; such as reciprocal monophyly, reproductive isolation, fixed morphological differences, differentiated ecological niches, etc as

“operational criteria” that allow for the identification of species though a variety of methods (De Queiroz 2007). Resultantly, this conceptual approach overcomes some of the challenges faced when singular lines of evidence provide incomplete delimitation of species and allow for the resolution of problematic species groups using a multifaceted approach. 57

Methods of delimiting species have increasingly employed molecular data.

Despite contention regarding the role of molecular data in the detection and description of species (DeSalle et al. 2005; Leaché & Fujita 2010; Bauer et al. 2011; Fujita & Leaché

2011) molecular genetic data can provide information on recent and ancient gene flow, the level of hybridization and the phylogenetic relationships between potential species

(Neilsen & Wakeley 2001; Hey & Neilsen 2007; Hey 2010). Rapid advances in the collection and associated analysis of molecular genetic data has meant that collecting and analyzing large numbers of loci from large numbers of individuals is increasingly achievable and fast, new methods for conducting species delimitation using molecular genetic data are emerging (O’Meara 2010; Yang & Rannala 2010).

King (1983) recognized two major lineages in the Australian gecko genus Gehyra, the G. australis species complex, associated with the higher rainfall subtropical far north and the G. variegata species complex (King 1979), associated with the Australian arid zone. These two lineages show some morphological and developmental differentiation

(King 1979; 1983; Moritz 1992). However, within each of these groups, the distinction between species is confounded by complex and confusing geographic and morphological patterns – likely due a recent history of diversification from a conservative morphological

“template” (Shaffer & Thompson 2007). Members of the G. variegata complex (King

1979) are the most abundant climbing geckos in the Australian arid biome, occupying all climbing habitats throughout it and extending into adjacent dry temperate and seasonally arid tropical habitats. Morphological variation across arid zone Gehyra taxa is limited and some characters used to differentiate currently recognized species, such as back pattern, are continuously variable between species (King 1979). Some G. variegata 58 complex species show habitat specialization in that they are predominately found on rocky outcrops, while others are restricted to trees (Mitchell 1965; Bustard 1968; King

1979). However, most ecological data for these species are anecdotal or local, in addition to which ecological requirements are difficult to determine in the face of the genus's incomplete taxonomy.

Several efforts have been made in the past to clarify the taxonomy and investigate the recent history of Gehyra (King 1979; 1982a; 1982b; 1983; Moritz 1986; Horner

2005; Sistrom et al. 2009). Of note is the high level of chromosomal variation within arid zone Gehyra - with up to nine chromosome races found within the G. variegata species complex (King 1979; Moritz 1986) and a high level of allozyme variation within rock dwelling populations (Moritz 1992). However due to the remote locations of many populations, sampling density was low and the ability to investigate gene flow between nominal species using chromosomal data is limited (Sites & Moritz 1987; Moritz 1992) and thus despite revealing potential taxonomic difficulties among arid zone Gehyra, such studies only led to partial taxonomic resolution of the complex.

We have chosen to examine three nominal species of Gehyra variegata complex geckos – G. minuta, G. montium and G. variegata (King 1979; Mortiz 1992; Sistrom et al. 2009). These species are known to display a complex arrangement of chromosome races with equally complex geographic distributions (King 1979; Moritz 1986; 1992). In addition, these species display conserved, overlapping morphologies that do not allow for clear classification of specimens into species (Moritz 1986; 1992). Due to the complexity of these arrangements of various lines of evidence for species boundaries, we intend to use an integrated approach, taking advantage of existing karyotypic data in addition to a 59 phylogenetic approach, assessments of gene flow between putative species, geographic distributions, morphology and a recently developed species tree approach to delimiting species (Yang & Rannala 2010). By utilizing an integrated approach and using multiple analyses to inform one another we intend to delimit potential species within this complex under the general lineage concept.

Methods

Sampling and laboratory methods

DNA was extracted from frozen and alcohol preserved liver tissue stored in the

Australian Biological Tissue Collection (ABTC) at the South Australian Museum

(SAMA) using a Puregene™ DNA Isolation Tissue Kit D-7000a (Gentra Systems) following the manufacturer's guidelines. Sequence data from was collected for 220 individuals representing all currently recognized species of Gehyra from Australia, four species from Oceania and Melanesia and three outgroups from Cyrtodactylus,

Hemiphyllodactylus and Lepidodactylus [Aaron Bauer pers. comm.]. This sampling also comprehensively covers the ranges of all arid zone Gehyra taxa and samples consistent with current taxonomic descriptions were included from corresponding type localities of all arid zone taxa. Due to the relatively high rates of misidentification of Gehyra specimens in all Australian collections (Sistrom et al. 2009) only tissues with corresponding voucher specimens available for verification of identification were used.

Histone cluster 3 gene along with the contained exon region (H3) (517 bp) were amplified using primers developed by aligning Gekko japonicus cDNA sequence available on GenBank to the Anolis genome in order to identify exon-primed, intron- 60 crossing (EPIC) primer sites using the tool BLAT (Kent 2002). Primers developed using this method were G1600F (5’ - TGGAGCAGGAAARACAACYAT – 3’) and G1601R

(5’ – RAGCTCAGACTTYGAAATKCC – 3’). Prolactin receptor (PRL-R) (544 bp) was amplified using primers PRLR_f1 (5′ - GACARYGARGACCAGCAACTRATGCC - 3′) and PRLR_r3 (5′ - GACYTTGTGRACTTCYACRTAATCCAT - 3′) (Townsend et al.

2008). NADH dehydrogenase subunit 2 (ND2) and partial flanking tRNA's (1136 bp) were amplified using the primers M112F (5'- AAGCTTTCGGGGCCCATACC- 3') and

M1123R (5'- GCTTAATTAAAGTGTYTGAGTTGC - 3') (Sistrom et al. 2009).

Amplifications were carried out in 25µL volumes using standard buffer and MgCl2 concentrations, 0.1 mM each dNTP, 0.2 µM each primer, 0.75 U AmpliTaq Gold® DNA

Polymerase (Applied Biosystems) and approximately 100ng of genomic DNA.

Thermocycler profiles were: 9 min at 94oC, then 45 cycles of: 45 s at 94oC, 45 s at 55oC and 1 min at 72oC for nuclear genes and 40 cycles of: 45 s at 94oC, 45 s at 60oC and 1 min at 72oC with a final extension step of 6 min at 72oC. The PCR product was purified using a Millipore Montage® PCR384 Cleanup Kit (Millipore Corporation) following the manufacturer's guidelines. One microlitre of purified product was used as template for a

BigDye Terminator sequencing reaction, which was carried out in 20µL reactions, consisting of 1µL of BigDye (Applied Biosystems), 7µL of 2.5x buffer and 1µL of

5pmol/µL primer. Sequenced products were separated on an Applied Biosystems 3730xl capillary sequencer.

Alignment and Phylogenetic analysis

The MUSCLE alignment algorithm (Edgar 2004) was used to align sequences via a plugin in Geneious v. 4.8.5 (Drummond et al. 2010) which were refined by eye. The 61 protein-coding region of ND2 was translated into amino acid sequences using the vertebrate mitochondrial genetic code and was compared to Gekko gecko (GenBank accession EU054288) translations to check for stop codons and frame shifts. The heterozygote plugin in Geneious was used to identify heterozygous sites in sequences of

PRL-R and H3, in addition to visual inspection. For the purposes of phylogenetic reconstruction, these base pairs were coded using IUPAC ambiguity codes. Due to the low relative diversity and large number of indels in the H3 data, indels were coded as presence – absence data.

MacClade v. 4.08 (Maddison & Maddison 2005) was used to identify redundant sequences, which were removed from the dataset for phylogenetic analyses and the determination of gametic phase. We conducted Bayesian and Maximum Likelihood (ML) analyses on each locus independently and on a concatenated dataset of all three loci. jModeltest v. 0.1.1 (Posada 2008) was used to evaluate models of evolution for all loci.

The tRNA sequences were removed from ND2 before partitioning it according to codon position (1st, 2nd,3rd and 1st and 2nd combined). As RaxML is unable to accommodate presence-absence data, the H3 gap partition was not used in the ML analysis. ML analysis with 1000 bootstrap replicates was carried out using the RAxML BlackBox web server (Stamakis et al. 2008). Bayesian analysis was conducted for 5 million step MCMC chains were run, sampling every 1000 generations, with the first 500 samples discarded as burn-in, leaving 4500 trees for construction of a majority rule consensus using

MrBayes v. 3.1 (Ronquist & Huelsenbeck 2003). TRACER v. 1.4.1 (Rambaut &

Drummond 2010) was used to confirm acceptable mixing, likelihood stationarity of the

MCMC chain and adequate effective sample sizes for each parameter (~200). 62

Morphological Analysis

In order to assess phenotypic differences between putative species, a number of morphological characters were taken from specimens with associated tissue samples.

This analysis excluded Clade 3, Clade 4 and G. minuta due to low sample sizes (n<3).

Measurements were carried out using digital calipers to the nearest 0.01mm and counts carried out by eye. Characters evaluated were: number of preanal pores in males (PP), clutch size in females (CL), tail length (TL), head length (HL), head width (HW), eye to naris distance (EN), snout height (SH), femur length (FEM), height of the rostral groove

(RG), number of internasal scales (IN), ratio upper to lower postnasal scale (PN), number of supralabial scales (SL), number of infralabial scales (IL) number of chin shield scales

(CS), number of infralabials contacted by the first chin shield scale (CS1), interorbital distance (IL) and the number of subdigital lamellae on the fourth toe of the right rear foot

(SDL). A small number of measurements which could not be collected due to specimen damage (2 individuals) were imputed using the within species mean.

All subsequent analyses of morphological data were conducted using the R statistical package (R Core Development Team, 2011). Each character was tested for sexual dimorphism by regressing values for male and female specimens by SVL as a proxy for body size (except for SVL which was regressed by EN) using the lm function of the base R package. The slopes of male and female regression lines were compared for significant differences using an F test implemented with the var.test function of the base R package. When slopes were found to not be significantly different an Analysis of Covariance (ANCOVA) was carried out on male and female 63 regression lines using the lm function of the base R package to determine if sexual dimorphism was present.

Data found to be free of sexual dimorphism were log transformed and corrected for body size using the methods described by Lleonardt (2000) using SVL as a measure for body size (except in the case of SVL where EN was used). Principle components analysis was then carried out on the corrected data using the dudi.pca function of the vegan package (Oksanen et al. 2011). Multivariate analysis of variance (MANOVA) was used to test whether PC axes showed significant differences between species and axes that displayed which showed significant differences were further evaluated using an analysis of variance (ANOVA) in conjunction with Tukey’s honestly significant difference (HSD) tests (Yandell 1997) to evaluate the significant differences observed between specific putative species. A visualization of the mean PC scores of putative species along axes which showed significant differences between groups is shown in Fig.

3 and the results of Tukey’s HSD tests is shown in Table 1.

Inference of Gene flow

For both nuclear loci, heterozygous individuals needed to be resolved for the purpose of analysing gene flow. For individuals with only a single heterozygous base pair this was done manually. For individuals with multiple heterozygous sites we used the program PHASE v. 2.10 (Stephens et al. 2001; Stephens & Scheet 2005) and retained the most probable alleles with support values >90%. In order to test reproductive isolation between existing and putative novel species with overlapping geographic ranges and where no fixed morphological differentiation could be found, rates of migration between them were estimated using the program Ima2 (Hey 2010). Despite IMa2 having the 64 capability to test multiple populations, the amount of data required and computational expense increases dramatically with the addition of each population (Hey 2010) so tests of gene flow between proposed species were carried out in a pairwise fashion. Data was divided into non-recombining blocks using the algorithm of Hudson and Kaplan (1985) implemented in DNAsp v. 5 (Librado & Rozas 2009) and the infinite sites model used for

IMa2 analyses. The burn in was conducted using a geometric heating model with 40 independent chains and parameters optimized to maximize mixing between chains throughout the run. Burn in was run until trendplots had stabilized and ESS values for all parameters had reached >50. After burn in, each run was conducted under default settings for 30 million generations. The estimated number of migrants per mutation (m) in both directions was plotted against its respective p value for migration in both directions (Fig.

4). In cases where the most probable number of migrants in at least one direction was zero, we were able to support restricted gene flow between putative species and therefore support that putative species as a distinct evolutionary lineage.

Bayesian Estimation of Species Delimitation

We tested validity of putative and existing species using reverse-jump MCMC methods implemented in the program BPP v. 2.0 (Yang & Rannala 2010). Due to possible bias in the phylogenetic analysis used to identify putative species induced by high relative signal in the ND2 dataset compared to the nuclear loci, the analysis was conducted both with this data included and excluded. In addition, as prior values for ancestral population size (θ) and branch lengths (T0) can have a significantly misleading effect if they are incorrect and too strict, we implemented a range of 5 diffuse priors

-4 ranging from m=0.1 to m=1x10 for θ and T0 in order to assess the impact of these priors 65 on support for species hypotheses presented by the guide tree. We also included a model

-4 with m=0.1 for θ and m=1x10 for T0, as this model assumes relatively large ancestral population sizes and short branch lengths, which represents a conservative scenario favoring fewer speciation events. The rjMCMC analysis was run for 500 000 generations, sampled every 5 and with a burn in period of 10 000 generations. We used algorithm 0 with a fine-tuning parameter of Ɛ = 5.0. Each speciation event was given equal prior probability.

Results

Phylogenetic analysis

For the ND2 alignment, the model GTR+I+Γ was selected for all codon partitions.

For the H3 dataset, HKY+Γ was selected for the sequence data and MrBayes uses an F-

81 model for binary coded gap data. For the PRL-R dataset, the model GTR+I+Γ was selected. Phylogenetic analysis using Bayesian and Maximum Likelihood methodologies resulted in identical tree topology. The results of the ML phylogenetic analysis are presented in Fig. 1. Phylogenetic analysis confirmed the genetic distinction of all known species and revealed an additional 5 monophyletic clades that represent putative species not currently recognized by the taxonomy. The validity of existing species and these putative novel taxa was tested in subsequent analyses. 66

Figure 1: Maximum likelihood tree of the concatenated ND2, H3 and PRLR data for all samples. Asterisks denote nodes with >95 Bayesian posterior probability and >70 ML bootstrapping score. Existing names are used for clades which contain samples of 67 specimens from the type locality of the relevant description and numbers after lineages denotes karyotype where known.

Figure 2: Map of Australia showing the sampling localities of putative species evaluated.

Grey lines represent 50m elevation contour lines.

Morphological Differentiation of Clades

Sexual dimorphism was detected in Clade 1 individuals for RG and in Clade 5 individuals for HL and HW. As such, these characters were removed from further analyses. Significant differences between putative species was detected in PC axes 1, 2 and 3, which cumulatively explained >95% of the variation in the data. Using Tukey’s

HSD to evaluate the significant differences between putative species pairs, the only 68 putative species pair that is shown to be morphologically indistinct is G. variegata and

Clade 5 (see Table 1).

Table 1: Results of Tukey’s HSD test showing significant morphological differences between putative species. D represents the differences in mean PC values between each species along each PC axis and P represents the corresponding P value. * significant to

95%, ** significant to 99%.

PC Axis 1 PC Axis 2 PC Axis 3 Comparison D P D P D P Clade 1 - Clade 2 0.392 0.76 -2.146 0.00** -0.182 1 Clade 1 - Clade 5 -2.481 0.00** -0.239 0.91 0.759 0.05* Clade 1 - G. montium 1.349 0.00** -0.023 1 1.567 0.00** Clade 1 - G. variegata -1.711 0.00** -0.212 0.96 1.059 0.01* Clade 2 - Clade 5 -2.873 0.00** 1.907 0.00** 0.778 0.1 Clade 2 - G. montium 0.956 0.05 2.122 0.00** 1.585 0.00** Clade 2 - G. variegata -2.104 0.00** 1.934 0.00** 1.077 0.02* Clade 5 - G. montium 3.829 0.00** 0.215 0.95 0.808 0.05* Clade 5 - G. variegata 0.769 0.12 0.027 1 0.299 0.86 G. montium - G. variegata -3.06 0.00** -0.189 0.98 -0.508 0.53

Figure 3: A graphical depiction of mean morphological distance between putative species. Points represent mean PC scores for each of the tested putative species, error bars represent 95% confidence intervals. 70

Inference of Gene flow

The potential for gene flow between putative species identified using phylogenetic analysis was evaluated using the program IMa2 (Hey 2010). Using phased nuclear data, migrations per substitution (m) were estimated in both directions between putative and known species where either geographic ranges or morphological characters were overlapping. To evaluate the likelihood of gene flow between putative species we plotted values of m against their respective p values (Fig. 4). In cases where the most probable value of m was zero in at least one direction between two putative species, we concluded that restricted gene flow between them was supported.

Using this approach, we are able to support restricted gene flow between Clade 1 and 2, Clade 1 and 5, Clade 1 and G. minuta, Clade 2 and G. minuta, Clade 3 and 4,

Clade 3 and 5, Clade 4 and 5, Clade 4 and G. minuta and between G. minuta and G. montium. Gene flow was predicted between Clade 1 and G. montium, Clade 2 and G. montium, Clade 3 and G. variegata, Clade 4 and G. variegata, Clade 5 and G. minuta,

Clade 5 and G. montium and between G. montium and G. variegata. Inference between

Clade and G. montium, Clade 3 and G. variegata and between Clade 4 and G. montium were inconclusive. It is important to note that as a rate of mutation was not inferred, gene flow was not quantified and its presence does not necessarily call for rejection of a putative species. 71

Figure 4: Results of Ima2 analyses. M – the number of migrants is plotted on the x axis and its corresponding P value is plotted on the y axis. For each analysis carried out, M is recorded for migration in both directions and reported as separate distributions, which are plotted as the two lines in each graph. A hypothesis of restricted gene flow was considered supported if the highest value for P was at m=o in at least one direction. 73

Bayesian Species Delimitation

Results for Bayesian species delimitation is shown in Fig. 5. All species in the guide tree are well supported when a prior distribution of m=0.1 for θ and T0, however support for the most derived species splits (namely between G. minuta, Clade 4 and

Clade 5) becomes very low as values for m decrease and even more so when a prior

-4 distribution of m=0.1 for θ and m=1x10 for T0. When the mtDNA is included (Fig. 5b) this pattern is still observed though nodal support is higher overall. Low support for the

G. purpurascens/G. punctata and G. nana/G. occidentalis splits indicates that the low representative sample size for these species is having an effect on the support they are given in the analysis. 74

Figure 5: Bayesian species delimitation results with a) mtDNA excluded and b) mtDNA included. Each node of the tree is labeled with posterior probabilities of the species split under different combinations of prior distributions of θ and T0 in the order 1: means =

-4 -4 0.1, 2: means = 0.01, 3: means = 0.005, 4 means = 1 x 10 and 5: mean θ =0.1 and mean T0= 1 x 10 . 75

Discussion

Integrative species delimitation

Species delimitation is a decision making process and the general lineage concept allows for making these decisions based on a number of different approaches and data types (Schlick-Steiner et al. 2010; Yeates et al. 2010). Integrative approaches are more thorough and likely to yield robust results than delimiting species with a singular line of evidence (Schlick-Steiner et al. 2010). However, integrative species delimitation is made difficult when different lines of evidence yield conflicting results, as is likely with recently radiated groups (Shaffer & Thompson 2007) and is apparent in the arid zone

Gehyra geckos evaluated in this study.

The use of phylogenetic analysis, particularly with mitochondrial DNA, is widespread as a preliminary investigation of the evolutionary diversity of organismal groups that have proven taxonomically challenging using traditional taxonomic methods

(Moritz 1994). While it is possible for species to go undetected using such an approach when processes such as incomplete lineage sorting or horizontal gene transfer obscure genetic differentiation between species (Knowles & Carstens 2007), it is a demonstrably effective approach in discovering difficult to distinguish and cryptic species (Bickford et al. 2006; Dasmahapatra et al. 2010). Phylogenetic analysis of the arid zone Gehyra confirmed the genetic distinctiveness of all currently described species and identified a further five previously undiscovered putative species, despite considerable past efforts in delimiting species in the group using morphological and chromosomal techniques. The phylogenetic clusters detected using this approach represent the most divergent delimitation model possible for the group based on current knowledge. 76

Reinvestigating the chromosomal evidence in light of the phylogeny shows that all putative species with the exception of Clade 5 represent a single karyotpyic arrangement. This has three implications: 1) Fixed differences in chromosomal arrangements between putative species, where evident add additional support to the separation of these species. 2) The fact that several putative and currently described species share the same karyotype highlights that in some cases, this marker is uninformative in the identification of species and emphatically shows the difficulties faced by previous researchers. 3) The multiple chromosome races found in Clade 5 may indicate that a speciation event not detected by phylogenetic analysis may have occurred.

This potentially warrants further investigation that is beyond the scope of the current study. While karyotype is an informative character in detecting and identifying Gehyra species, when used in isolation it only yields to partial resolution of the group.

Despite the complex nature of the geographic distribution of Gehyra lineages, the geographic distribution of some putative species provides information relevant to their status as species. Many putative species have geographic ranges that are either completely or partially sympatric (see Fig. 2 and Table 2) indicating that the evolutionary distinction observed in other lines of evidence persists despite the potential for contemporary gene flow (Petit & Excoffier 2009). In other cases, geographic distributions of species are coherent with known biogeographic regions within the

Australian arid zone (Byrne et al. 2008, Fujita et al. 2010), suggesting that speciation in these populations has been affected by the same historical processes that have acted on other elements of the biota of these regions - e.g. Clade 1 is restricted to the MacDonnell

Ranges – a region noted for high endemism in plants (Woinarski et al 1996) and 77 invertebrates (Morton et al. 1995) and Clade 2 is restricted to the Central Ranges – a distribution shared with the agamid Ctenophorus rufescens and skink Lerista speciosa

(Wilson & Swan 2008) (see Fig. 2). A significant finding of our study is that G. montium has a much wider westerly distribution than previously thought (Storr 1982), extending throughout the Pilbara and central Western Australia. Without doubt, this is due to the morphological similarity among these geckos, such that southern Pilbara specimens of G. montium were assigned to either G. variegata or G. punctata, depending on the degree to which the colour pattern was reticulate or spotted (respectively). The G. variegata clade has a widespread western distribution, while the distribution of Clade 5 is split into eastern and central sections . Contact between the variegata clade and Clade 5 must occur in the eastern Nullarbor Plain region. The exact nature of this contact remains unknown but would be informative in relation to their evolutionary isolation. It is worth noting that sampling in remote regions of Australia such as the Tanami Desert and large portions of northern Australia is grossly inadequate and apparent gaps in distribution of several species, or lack of geographic overlap between species in some areas, may merely represent gaps in sampling.

Despite extreme difficulty in identifying and characterizing morphological differences between Gehyra species without prior genetic groupings and using traditional qualitative taxonomic methods (King 1979; 1983; Moritz 1986), almost all of the putative species identified by the phylogenetic analysis show significant differences in morphology using multivariate methods, with the exception of Clade 5 and G. variegata.

Unfortunately, low sample size prevents a morphological assessment of Clade 3, 4 and a reassessment of G. minuta. Cursory examination of Clade 3 and Clade 4 specimens 78 suggests morphological crypsis with respective sympatric lineages G. variegata and

Clade 5 indicating that determining the phenotypic distinction of these putative species requires further investigation once adequate information is available on live colour patterns and more sampling of populations in the overlap zones between these clades and their nearest relatives. The status of G. minuta as a distinct species is not in question at this point, but species assignments for the poorly studied populations of small, spotted rock-dwelling geckos from the northern half of the arid zone are doubtful, and we defer further consideration of this species and its geographic and morphological limits to a future time when better sampling of this region has been undertaken. Tests for gene flow

(summarized in Fig. 4) between putative species provided support for some otherwise difficult to distinguish putative species showing limited morphological divergence or undetermined/identical chromosomal states. For example, restricted gene flow between

Clade 4 and 5 was detected despite preliminary examination of specimens showing limited morphological divergence, entirely sympatric distribution and the undetermined chromosomal state of Clade 4 meaning that support for the separation was otherwise low.

Coalescent estimates of gene flow were useful in supporting some putative species splits, however in some cases restricted gene flow between putative species supported by other lines of evidence was not supported – e.g. restricted gene flow between G. montium and

G. variegata. It is important to note a number of conditions when interpreting the results of coalescent migration analyses used in this manner. As the mutation rate of the loci used for the analyses was not estimated due to the associated error in estimating mutation rates potentially leading to type 1 error in species delimitation (Kuhner 2009; Strasburg

& Reiseberg 2010), the magnitude of gene flow between putative species when predicted 79 also cannot be estimated. This renders the test highly conservative in cases where low levels of gene flow between true species may be present. In addition, the use of coalescent estimation of migration for this purpose does violate an assumption of the test by comparing putative species which may not be sister species. While multiple population models can be carried out using IMa2, the required genomic coverage to yield robust results increases in a non-linear fashion and simulation studies show that gene flow estimates are unlikely to be significantly affected by low to moderate gene flow with an unsampled intermediate population (Strasberg & Reiseberg 2010).

Bayesian Species delimitation using BPP (Yang & Rannala 2010) provided conflicting results when different prior distributions of θ and T0 were assumed despite these distributions being set deliberately diffuse in that splits between the most derived putative species – G. minuta, G. montium, Clade 3, Clade 4 and Clade 5 show decreasing levels of support for decreasing prior means of θ and T0 with the lowest support seen when the prior distribution of θ is assumed to be high relative to the prior distribution of

T0. Support for the more derived species splits in arid zone Gehyra are supported under some evolutionary scenarios but not others, highlighting that prior knowledge of likely evolutionary scenarios may be important for accurate delimitation using this method. In addition, support for the species G. punctata and G. purpurascens is low and highly variable, despite the relative placement of these species being uncontroversial (King

1979; Storr 1982; Sistrom et al. 2009). As they are only represented in the analysis by small, representative sampling it may suggest that small, disproportionate samples can lead to low support values for otherwise distinct species. Given the small relative samples sizes of Clade 4 and G. minuta this may be playing a role in the low support values for 80 these terminal species. Finally, posterior support values were higher with the inclusion of mtDNA, however patterns of support were similar to those observed when only nuclear loci were analysed, suggesting that mtDNA is not providing contradictory signal which would lead to an erroneous result in the combined analysis.

Status of putative species.

Our results show significant support for all currently described central Australian

Gehyra species and indentify five additional putative species, with varying levels of support for each under the general lineage concept using an integrative approach. Clade 1 and Clade 2 prove to be genetically and morphologically distinct, with discrete geographic ranges indicating that traditional taxonomic description of these species to be relatively straightforward and appropriate. Clade 3 and Clade 4 are shown to be genetically distinct and may warrant description as new species, pending additional samples being either detected by targeted genetic screening of museum held samples or further specimens collected in the now known distributions of these clades to characterize the morphology of these putative species. The phylogenetic and chromosomal distinction of Clade 5 from G. variegata, in concert with the parapatric distribution initially suggests that these two clades represent distinct species however their morphologically cryptic nature and the gene flow between them indicate that the scenario may be more complex.

Additional sampling in the zone of contact in western South Australia, in concert with analysis using appropriate markers to detect and assign potential hybrids such as microsatellites (Barton & Gale 1993) would provide a clearer understanding of the interactions between these two putative species.

variegata montium minuta Clade 1 Clade 2 Clade 3 Clade 4 81 montium B M C S minuta B C B M I S Clade 1 B M C B M C S B C I S Clade 2 B M C B M C S B C I S B M C I Clade 3 B S B I B C I B B Clade 4 B I B S I B B B I Clade 5 B C B M C S C S B M C I S B M C S B I I S

Table 2: Summary of evidence for species delimitation of phylogenetic clades. B – Bayesian species delimitation supports the split under multiple scenarios. M – Significant morphological differences detected. C – Fixed chromosomal difference detected. I – Restricted gene flow detected S – The geographic ranges of species overlap.

Conclusions

Our study clearly shows that the current taxonomy of central Australian Gehyra

under-represents the number of species within the group, and identifies a number of novel

species worthy of description or further investigation. While the general lineage concept

of species allows the reconciliation of multiple lines of evidence when evaluating the

potential of these putative species, this approach offers a considerably more powerful and

universal method of identifying and defining species than traditional methods, however

many data types – such as genetic data and categorical morphological data are difficult to

evaluate using similar analytical frameworks. As such, when datasets are in conflict, as is

the case in the Gehyra group analyzed and typical of many recently evolved groups,

decisions regarding species delimitation become qualitative judgments. While

frameworks for making these decisions have been posed (Schlick-Steiner et al. 2010;

Yeates et al. 2010 the development of a statistical approach for evaluating multiple lines

of evidence for species delimitation would be considerably more desirable. Despite this,

the fact that speciation is a continuous biological process (De Queiroz 2007; Shaffer & 82

Thompson 2007) delimitation of species in groups like the Central Ranges Gehyra is likely to always be difficult.

Species Descriptions

Our OTU designations are formalized here, with restriction and redefinition of two of the three nominal species, and descriptions of three new species. All descriptions are based solely on specimens that have been typed using DNA sequences. Two of our

OTUs, Clade 3 and Clade 4 are not formally described as they lack karyotypic data and information on life colour pattern variation, and for both sampling is currently inadequate to assess the degree to which they are consistent across their range. Further collections and analyses will be necessary to fill these gaps in knowledge.

Gehyra variegata (Duméril & Bibron, 1836)

Figure 6: Gehyra variegata. A) SAMA R63256, Eyre Highwy at Fraser Range, WA. B)

SAMA R63283, 57 km ENE Balladonia Rock, WA. C) SAM R65162, Maralinga, SA.

D) SAM R65161, Maralinga, SA.

Hemidactylus variegatus Duméril & Bibron, 1836: p. 353 Syntypes: MNHP 254 (3 specimens), from “Tasmania” (in error), and MNHP 2295 from Shark Bay, W.A.

Specimens examined: See supplementary material.

Diagnosis. Distinguished from other Australian Gehyra by a combination of 8 divided scansors under the expanded portion of the fourth toe, moderate size, generally two pairs of enlarged chin shields, second infralabial notched and a dorsal pattern in which dark lines and white markings coordinate to produce a pattern of dark lines and bars with white trailing edges. Not distinguishable by external morphology from G. versicolor sp. nov. (see below), but distinguished karyotypically by the unique 2n=40b arrangement (King 1979).

Description. Snout-vent length 41-49 mm (mean = 47.5 mm, n = 19). Length of tail

43 mm (105% SVL, n = 1).

Nostril surrounded by rostral, first supralabial, supranasal and two subequal post nasals. Generally a single moderate internasal separates the supranasals above the rostrol, but supranasls In medial contact in a minority of specimens. Supralabials 9 or 10 (mode

9). Infralabials 7-10 (mode 9). Usually 2 pairs chin shields, anterior pair in contact with only the first infralabial. Chin shields separated from the third and succeeding infralabials by the interpolation of a series of enlarged scales (parinfralabials) that margin the ventral edge of the infralabials. Usually second infralabial notched where this parinfralabial scale row starts. Scansors under pad of fourth toe divided, 6-8 (mode 8).

Preanal pores in males 11-14 (mean 12.3, n=8). 85

The karyotype is 2n=40b, (King 1979, Moritz 1984).

In life, dorsally light to medium grey or brown, generally with a complex reticulation of white-edged black lines. These usually include several temporal streaks and often form continuous paravertebral and transverse dorsal irregular lines, forming a vaguely ladder-like pattern. Some specimens, especially from rock-dwelling populations have the dark markings more discontinuous, but dark markings continue to appear as white-edged lines and bars rather than separate black markings and white circular spots as in other rock-dwelling species of Gehyra. Colour pattern is variable both within and between populations. In preservative, the colour pattern is often greatly reduced in contrast and can be hard to discern.

Distribution. Widespread through the southern half of Western Australia, from the

Carnarvon basin east to the Central Ranges and southeast to the western interior of South

Australia (Maralinga).

Comments. The combination Gehyra variegata has long been applied Australia-wide to populations of morphologcally similar Gehyra species with similarly generalist habits.

Our study makes it clear that the well-established karyotypic differences between western and eastern populations are evidence that the two are not part of the same gene pools.

Indeed, the two are not even sister lineages.

The type localities associated with the syntypes of Hemidactylus variegatus in the

MNHP collection are Shark Bay, WA (one specimen) and Tasmania (four specimens). 86

No Gehyra occur in Tasmania (Wilson and Swan 2011), and the Baudin expedition on which these types were collected did not make collections from any localities where the eastern populations (2n=40a karyotype) occur. However they did make extensive collections from many areas of the west coast in WA, including Shark Bay, where the western karyotypic group (2n=40b) occurs. Thus the Shark Bay specimen likely represents a real collecting locality for the type series and specimen MNHP 2295 is the logical candidate for lectotype. This leads us to conclude that the name variegata properly applies to the western populations.

As our study shows, morphology alone cannot distinguish between the two karyotypic groups and In addition, the lectotype cannot now be found (I. Ineich, pers. com.), while the 'Tasmanian' paralectotypes are all completely faded (pers.obs.). All are small Australian type Gehyra geckos, but little further can be said about them.

One aspect of our study conflicts with published Information. King (1979) mapped Gehyra in the Maralinga area of western South Australia as belonging to his

2n=40a karyotype group (fusion products are chromosome pairs 5 and 7). However, in a sample of seven specimens karyotyped from three locations in the Maralinga area and on the northern Nullarbor Plain, all were 2n=40b (fusion products pairs 3 and 6; our Clade

5). We are unable to account for this discrepancy. However, our karyotypic data are confirmed by DNA sequence data from the same specimens that indicate membership of the variegata clade. King's data would predict the presence of Clade 5 in this area, but all of our samples from the far west of South Australia belong to the variegata clade, our only recovery of a Clade 5 animal in the western half of South Australia being in the 87 north-western ranges. We note that the size distinctions between chromosome of these two variants are small and might readily be confused in the absence of close scrutiny.

Gehyra montium Storr, 1982

Figure 7: Gehyra montium. SAMA R61924, Morgan Range, WA.

Gehyra montium Storr, 1982: p. 56. Holotype: WAM R31732, from Mt Lindsay

[Watarru], Birksgate Range, north-western South Australia, 27º 02’ S, 129º 53’ E.

Specimens examined: See supplementary material.

Diagnosis: Distinguished from other Australian Gehyra by a combination of modally 7 divided subdigital lamellae, small to moderate size generally two pairs of enlarged chin shields, second infralabial notched, a dorsal colour pattern combining grey-brown to rufous colouring (in life) patterned by small pale spots interspersed in a continuous network of irregular, dark lines, and a karyotype of 2n=42a (Moritz 1986).

Diagnosis: Distinguished from other Australian Gehyra by a combination of 88 modally 7 divided scansors under the expanded portion of the fourth toe, small to moderate size generally two pairs of enlarged chin shields, second infralabial notched, a dorsal colour pattern combining grey-brown to rufous colouring (in life) patterned by small pale spots interspersed in a continuous network of irregular, dark lines, and a karyotype of 2n=42a (Moritz 1986).

Description. Adult snout-vent length 36-49 mm (mean = 40.3 mm, n=21 ). Length of tail 41-48 mm ( mean = 110% SVL, n=4,).

Nostril surrounded by rostral, first supralabial, supranasal and two post nasals, the upper usually markedly larger than the lower (as noted by Storr 1982). 1-3 (modally 1) moderate internasal scales separate the supranasals above the rostral. Supralabials 8-11, mode 8. Infralabials 7-9, mode 8. Consistently 2 pairs chin shields, anterior pair in contact with only the first infralabial. Chin shields separated from the third and succeeding infralabials by the interpolation of a series of enlarged scales (parinfralabials) that margin the ventral edge of the infralabials. Second infralabial notched where this parinfralabial scale row starts. Scansors under pad of fourth toe divided, 7-8 (mode 7).

Preanal pores in males 10-13, mean 11.1 (n=12).

The karyotype is 2n=42a (King 1979). This karyotype is shared with a number of

Gehyra species, including G. minuta and populations currently assigned to G. punctata in

Western Australia

In life, dorsally light grey-brown to to reddish brown to pinkish, the entire dorsal surface patterned by a reticulum of blackish grey. Scattered over the dorsal surface are small circular pale spots, often only contrasting weakly with the dorsal background 89 colour. In preservative any rusty colour tones and pale spots tend to disappear leaving the specimens greyish with a dark reticulum.

Distribution. Rocky mountain ranges of north-western South Australia extending to adjacent areas of the south-western Northern Territory and west into central Western

Australia, as far northwest as the southern Pilbara.

Comments. Throughout arid areas of central and northern Australia, rock outcrops may harbour relatively small Gehyra species, typically with rufous colouring and a pattern including pale spots. The name G. montium has often been applied to many such populations, but our study reveals that this species only just extends east of the Western

Australian border, to the Tomkinson Ranges and Birksgate Ranges in South Australia.

Our current knowledge suggest that G. montium does not occur in the Northern Territory nor in most of north-western South Australia. The fact that the species was not recognised hitherto as extending westward as far as the Pilbara possibly reflects a tacit assumption that G. montium was a central Australian species, as well as the superficial similarity of pattern in preserved G. montium and G. variegata.

In the adjacent rocky ranges of north-western South Australia and the south- eastern Northern Territory, G. montium is shown by our study to be replaced by geckos of Clades 2 and 1, respectively, and these are described below as new species.

When describing this species Storr (1982) suggested it might represent the 2n=38 karyotypic group of King (1979). However, our and Moritz’s karyotype data show that 90 all populations conspecific with the type population of montium have the 2n=40a karyotype.

Gehyra minuta King, 1982

See King.

Comments. King described his new species from a small number of localities and more recent knowledge has not suggested any broader distribution for this species. We did not have significant sampling of this species and so suggest that until further data prove the contrary, it should be regarded as an endemic inhabitant of the scattered rocky ranges centred around Tennant Creek, Northern Territory, and characterised by very small size, speckled colour pattern, 2n=42a karyotype and restriction to rocky microhabitats.

Gehyra moritzi sp. nov

Figure 8: Gehyra moritzi. A) SAMA R65937, Emily Gap, NT. B) SAMA R65935,

Rainbow Valley, NT. C) SAMA R65945 20 km S of Barrow Creek, NT. D) SAMA

R65943, 2 km S of Devils Marbles, NT.

Gehyra 2n=44 "nana-montium" Moritz, 1986: p. 48.

Holotype: SAMA R65941, from Emily Gap, East MacDonnell Ranges, Northern

Territory, 23° 44' 23.0" S, 133° 57' 02.5" E, collected by M. Hutchinson, P. Oliver, G.

Armstrong & S. South on 9 January 2011.

Paratypes: 18 specimens in the collections of the South Australian Museum, Adelaide and the Northern Territory Museum and Art Gallery, Darwin (see supplementary material).

Diagnosis: Distinguished from other Australian Gehyra by a combination of either

7 or 8 divided scansors under the expanded portion of the fourth toe, small to moderate size generally two pairs of enlarged chin shields, second or third infralabial notched, dorsal colour pattern combining pinkish grey to rufous colouring (in life) patterned by entirely by black and whitish spots, and a karyotype of 2n=44 (Moritz 1986).

Description. Adult snout-vent length 36-49 mm (mean = 42.0 mm, n=19). Length of tail 38-51 mm (mean = 106% SVL, n=5).

Nostril surrounded by rostral, first supralabial, supranasal and two subequal postnasals. Either a single internasal scale separates the supranasals above the rostral (9 specimens) or supranasals in median contact (9 specimens). Supralabials 8-10, mode 9.

Infralabials 7-9, mode 8. 2, less frequently 3, pairs chin shields, anterior pair in contact 93 with only the first infralabial. Chin shields separated from the fourth, or third, and succeeding infralabials by the interpolation of a series of enlarged scales (parinfralabials) that margin the ventral edge of the infralabials. Third, less frequently second, infralabial notched where this parinfralabial scale row starts. Scansors under pad of fourth toe divided, 7-8 (mode 8). Preanal pores in males 11-16 (mean 14.4, n=11).

The karyotype is 2n=44, (pers. obs and Moritz 1986).

In life, dorsally light pinkish grey to reddish brown, the entire dorsal surface patterned by spots. Dark spots are larger and more irregular, pale spots tend to be more precisely circular in shape.

Distribution. Rocky mountain ranges of the south-central Northern Territory, centred on the MacDonnell Ranges and south to the James Range, west to the Kings Canyon area and north to the Devils Marbles.

Comments. The above description refers to specimens from the central and southern parts of the species' range. The northernmost sample, from rocky hills south of the

Devils Marbles, is distinctly different in morphology but is not distinguishable by either

DNA sequence data or karyotype. This series of eight specimens is consistently smaller

(largest specimens only 40 mm SVL), males have fewer preanal pores (range 8-11) and the spotted colour pattern consists of relatively very small spots each covering only a few dorsal scales. All have seven rather enlarged scansors rather than the 8 usual for the other populations. For the present we refer this sample to G. moritzi but exclude it from the paratype series. Further genetic studies of gecko populations along the middle 94 sections of the Stuart Highway would be useful to clarify the genetic relationships among

G. moritzi populations.

The specific name recognises the contribution of Craig Moritz (University of

California, Berkeley) in revealing the high level of karyotypic diversity among central

Australian populations of Gehyra.

Gehyra pulingka sp. nov

Figure 9: Gehyra pulingka. A) SAMA R65248, Umuwa, SA. B) SAMA R61926,

Kurtjuntari Rockhole, WA.

Gehyra 2n=42b "nana-montium" Moritz, 1986: p. 48.

Holotype: SAMA R652481, from Umuwa, Musgrave Ranges, South Australia, 23° 44'

23.0" S, 133° 57' 02.5" E, collected by M. Hutchinson, on 25 May 2010.

Paratypes: 16 specimens in the collections of the South Australian Museum, Adelaide

(see supplementary material).

Diagnosis: Distinguished from other Australian Gehyra by a combination of modally 7 or 8 divided scansors, small to moderate size, generally three pairs of enlarged chin shields, third infralabial notched, dorsal colour pattern a light to medium brown dorsum (in life) patterned by a pattern of irregular thin black lines and circular pale spots, and a karyotype of 2n=42b (Moritz 1986).

Description. Adult snout-vent length 38-49 mm (mean = 43.3 mm, n=14). Length of tail 43-56 mm (mean = 117% SVL, n=6,).

Nostril surrounded by rostral, first supralabial, supranasal and two subequal postnasals. Usually a single internasal scale (occasionally 2 or none) separates the supranasals above the rostral. Supralabials 7-10, mode 8. Infralabials 7-9, mode 8. Three pairs chin shields, outer (third) pair small or absent in a three specimens, anterior pair in contact with only the first infralabial. Chin shields separated from the fourth and succeeding infralabials by the interpolation of a series of enlarged scales that margin the ventral edge of the infralabials. Third infralabial notched where this parinfralabial scale row starts. Scansors under pad of fourth toe divided, 7-8 (mode 8). Preanal pores in males

12-16 (mean 13.9, n=7). 96

The karyotype is 2n=42b is unique for this species, differing from the 2n=42a karyotype via a secondary constriction on pair 11 (Moritz 1986 and pers. obs.).

In life, dorsally light pinkish grey to reddish brown, the entire dorsal surface patterned by spots. Dark spots are larger and more irregular, pale spots tend to be more precisely circular in shape.

Distribution. Rocky mountain ranges of the south-central Northern Territory, centred on the MacDonnell Ranges and south to the James Range, west to the Kings

Canyon area and north to the Devils Marbles.

Comments. Long included in G. montium, G. pulingka is consistently distinguishable in morphology, karyotype and DNA sequence data. In the field, the colour pattern of blackish squiggles and prominent spots can be used to distinguish this species from true G. montium, which has a more continuous black dorsal network and small, weakly contrasting spots. Additional distinctions in chin shields (3 versus 2) and higher male preanal pore counts will provide extra support if genetic data are lacking.

The specific name is from the Pitjantjatjara language (Goddard 1996) from the roots puli, rock, or rocky hill, and the suffix -ngka meaning pertaining to, alluding to the habits of the species and its distribution confined to the desert areas occupied by the speakers of Pitjantjatjara and related dialects. Specific name would not change with gender of the genus.

Gehyra versicolor sp. nov

Figure 10: Gehyra versicolor. A) SAMA R-----, New Years Gift Bore, Borefield Road,

SA. B) SAMA R-----, Gregory Creek crossing, Borefield Road, SA. C) SAMA R-----,

New Years Gift Bore, Borefield Road, SA D) SAMA R-----, New Years Gift Bore,

Borefield Road, SA.

Gehyra 2n=40a "variegata", 38b "variegata-montium", Moritz, 1986: p. 48.

Holotype: SAMA R51968.

Paratypes: 29 specimens in the collection of the South Australian Museum, Adelaide (see supplementary material).

Diagnosis: See G. variegata, above, from which G. versicolor is indistinguishable in external morphology, but is distinguishable by karyotype (2n=40a or 2n=38).

Description. Adult snout-vent length 37-54 mm (mean = 46.7 mm, n=30). Length of tail 40-58 mm (mean = 110% SVL, n=6,).

Usually two pairs chin shields, sometimes a small outer (third) pair, anterior pair in contact with only the first infralabial. Chin shields separated from the third and succeeding infralabials by the interpolation of a series of enlarged scales (parinfralabials) that margin the ventral edge of the infralabials. Second infralabial notched where this parinfralabial scale row starts. Scansors under pad of fourth toe divided, 7-8 (mode 8).

Preanal pores in males 10-14 (mean 11.9, n=15).

Most populations have the 2n=40a karyotype first reported by King (1979), but our samples from the Macdonnell Rangesd and adjacent southern interior of the Northern

Territory have 2n=38 karyotypes. These specimens branch in at least two distinct areas of the tree, interspersed with animals from 2n=40a populations, and thus behave as if they are not genetically different from them.In case further cryptic species are demonstrated 99 among these populations, we have confined our type series for G. versicolor to animals from 2n=40a populations only.

Distribution. Widespread from the Murray Valley of northern Victoria north and east through New South Wales west of the Great Dividing Range and similar areas of

Queensland north to about the level of the latitude of Hughenden. Extends west into most of South Australia, with the exception of the southern and western Eyre Peninsula and the Great Victoria Desert, and north west into southern and central Northern

Territory. Not currently known to occur in Western Australia. Found in both rocky and arboreal situations, as well as on human dwellings and other buildings.

Comments. This species is the only one where we find two karyotypic groups appearing to belong to a single taxon. Moritz reported both 2n=40a and 2n=38 (a and b) from the

MacDonnell Ranges and adjacent central Northern Territory, and at present our data suggests all belong to a single lineage, our clade 5. As with the variable populations of

G. moritzi, further detailed study combining the same multiple approaches used here are desirable to clarify the gene flow among these chromosomally different populations.

Similar detailed studies are needed in central and western Queensland to better understand the distribution and variation of G. versicolor and Clade 4 where they co- occur, and the potential contact or overlap between G. variegata and G. versicolor in central western South Australia. However, it is clear that over the great majority of its distribution this is a single species, consistently different from other Gehyra. Virtually all of the extensive literature pertaining to “Gehyra variegata” actually applies to this species. 100

Given the very wide distribution of the species, it is somewhat surprising that no name appears to be available for it in the synonymy of G. variegata. Cogger et al. (1983) listed several synonyms of Gehyra variegata. Subsequently, these have proven to be based on specimens attributable to other Australian Gehyra species groups, especially eastern species related to G. australis (Bauer and Henle 1994). Other possible synonyms were discussed by Sistrom et al. (2009) in reference to G. lazelli; none apply to our Clade

5. The specific name chosen here is from Latin root meaning ‘variable in colour’, appropriate for a species that shows considerable individual and geographic variation.

Acknowledgements

This work was funded by ABRS grant 207-43 awarded to M. Hutchinson and S.

Donnellan. We thank R. Hutchinson, Department of Cytogenetics and Molecular

Genetics, Women’s and Children’s Hospital, North Adelaide, South Australia, for confirmation of the karyotypes of several populations sampled for DNA comparison. We also thank P. Doughty and B. Maryan (W. A. Museum, Perth), P. Horner and G. Dally

(N. T Museum and Art Gallery, Darwin) and I. Ineich (Museum Nationale d’Histoire

Naturelle, Paris) for the loan of type specimens and other reference material. We thank P.

Doughty at the Western Australian Museum for providing tissue samples. 101

Estimating species trees and testing evolutionary hypotheses

despite high levels of gene tree discordance in Australian

Gehyra (Reptilia: Gekkonidae).

Mark Sistrom1,2,3, Mark Hutchinson 2, 3 Terry Bertozzi2 and Steve Donnellan2,3

1 School of Earth and Environmental Sciences, The University of Adelaide, Adelaide,

Australia 5005.

2 South Australian Museum, North Terrace, Adelaide, Australia 5000.

3 Australian Centre for Evolutionary Biology and Biodiversity, The University of

Adelaide, Australia 5005.

Corresponding author: [email protected]

102

Mark J. Sistrom (candidate)

Corresponding author: Responsible for data collection, analysis and interpretation, drafted manuscript, produced all figures, oversaw manuscript revision.

Signed…………………………………………………………..Date……………

Mark N. Hutchinson

Sought and won funding, co-supervised direction of study and assisted in selection of fossil calibrations and assisted in manuscript revision.

I give consent for M.J. Sistrom to include this paper for examination towards the degree of Doctor of Philosophy.

Signed: Date: 16/09/2011

Terry Bertozzi

Assisted in marker design and assisted in manuscript revision.

I give consent for M.J. Sistrom to include this paper for examination towards the degree of Doctor of Philosophy.

Signed: Date: 14/09/2011

103

Stephen C. Donnellan

Sought and won funding, co-supervised direction of project, provided assistance in analysis selection and manuscript revision.

I give consent for M.J. Sistrom to include this paper for examination towards the degree of Doctor of Philosophy.

Signed: Date: 16/09/2011 104

Abstract

The advent of recent developments in methods of reconstructing species trees are addressing previous impediments to the estimation of species relationships and timing of diversification in rapid radiations with high levels of gene tree discordance. Using a multi-locus dataset, comprising one mitochondrial and six nuclear loci, and undertaking calibrated species tree estimation, we are able to estimate the species relationships among

Australian Gehyra and test previous hypotheses regarding the evolutionary history of the group. We find support for previous hypotheses suggesting a recent Asian origin for the group and the division of it into a large bodied and tropically adapted G. australis species complex and a small bodied and arid adapted G. variegata species complex, We are unable to support a previously suggested model for allopatric speciation driven by chromosomal rearrangement in the group. A Bayesian concordance analysis revealed high levels of gene tree discordance at various levels within the diverse and recently radiated Australian Gehyra lineage. Our analysis of the effects of gene tree discordance and incomplete taxon sampling revealed that gene tree discordance was high whether terminal taxon or gene sampling was maximized – indicating that high levels of discordance due to biological processes characterize the group, as is expected in recently diversified groups of organisms. 105

Introduction

Recent advances in both molecular genetic data acquisition and phylogenetic analysis have led to an ability to generate significantly more sophisticated phylogenetic reconstructions than in the past, such as species trees inferred from multiple gene trees

(Heled & Drummond 2010; Kubatko et al. 2009; Liu & Pearl 2007) and time calibrated phylogenies (Drummond & Rambaut 2007). These new methodological approaches aim to overcome some of the limitations of traditional phylogenetic reconstruction by better accounting for discordance between gene trees (Degnan & Rosenberg 2009) and allow for hypotheses regarding the evolutionary history, timing of speciation and relationships between organisms to be tested in a rigorous framework.

One of the difficulties in the inference of species trees from multiple gene trees is overcoming situations in which individual gene trees differ from one another, a situation that poses significant challenges for traditional methods of combing information from multiple loci via concatenation (Huang et al. 2010; Kubatko & Degnan 2007).

Discordance between gene trees can be caused by both stochastic (e.g..incorrect gene tree estimation) and technical (e.g., paralogous sequences) errors (Chung & Ané 2011). A number of biological processes, such as incomplete lineage sorting (ILS) and horizontal gene transfer (HGT) are known to create further discordance between gene trees

(Maddison 1997) and with the underlying species tree. Species tree methods represent a conceptual shift in phylogenetics in that gene tree and species tree estimation are considered separately. These methods aim to account for discordance between gene trees in the estimation of species trees but make varying inferences regarding the source of the discordance (Chung & Ané 2011). In addition to accounting for gene tree discordance, 106 the advent of fossil calibrated phylogenies utilizing multiple genes and individuals for each species can significantly increase support when linking biogeographic events to the diversification of species (Drummond & Rambaut 2007; McCormack et al. 2010) although discordance between gene trees can have an adverse effect on the ability to estimate rates of divergence and thus, divergence dates (Burbrink & Pyron 2011). It is because of this ability to deal with certain levels of gene tree discordance, that species tree methods are also particularly useful for reconstructing the evolutionary history of recent and rapid radiations which have historically been problematic to reconstruct using more traditional phylogenetic methods (McCormack et al. 2010; Rowe et al. 2010).

Gehyra, a large genus of geckos from the family Gekkonidae (Han et al. 2004;

Russell & Bauer 2002), currently comprises 36 species, which occupy a wide range of habitats from Indochina throughout most of Oceania and Melanesia and Australia (King

1979; Russell & Bauer 2002). The Australian Gehyra radiation makes up the bulk of the group’s diversity with 19 largely endemic species (Horner 2005; Sistrom et al. 2009).

The Australian Gehyra radiation has proven to be taxonomically troublesome in the past, as considerable karyotypic and allozyme variation does not manifest in easily recognizable morphological variation. Thus, many species comprise multiple morphological isolates, distinct chromosome races, allozyme OTU’s and mitochondrial clades (King 1979; 1982; 1983; 1984; Moritz 1984; 1986; 1992, Sistrom et al. 2009;

Sites & Moritz 1987).

Despite the lack of complete taxonomic resolution of the genus, several characteristics of the evolutionary patterns and history of Gehyra have been inferred by past researchers, often with limited levels of empirical justification. King (1979; 1983; 107

1984) summarized many of these assumptions in his work, asserting a recent Asian origin for Gehyra (King 1984) and supporting the hypothesis put forward by Mitchell (1965) that the Australian Gehyra form two major species complexes – the Gehyra variegata complex characterized by small bodied, species associated with the arid regions of the continent (King 1979) and the Gehyra australis species complex characterized by larger bodied animals associated with the tropical, subtropical and monsoonal regions of the continent (King 1983). King (1984) also proposed that radiation within these two complexes was due to allopatric divergence and chromosomal rearrangement with a radiation of allopatrically derived 2n=44 chromosome species, followed by a similar radiation of 2n=42 chromosome species, then by 2n=40 and 2n=38 chromosome species simultaneously. However, King’s proposal was criticized as somewhat premature given the incomplete taxonomy of the genus and lack of data relevant to reproductive isolation of allopatric chromosome races (Moritz 1992; Sites & Moritz 1987).

Using a multi-locus species tree approach we sought to evaluate hypotheses regarding the evolutionary patterns and history of the Australian Gehyra radiation.

Through the reconstruction of species relationships, we sought to test the hypotheses that

Australian Gehyra originated from Melanesian Gehyra and diversified into two species groups – the G. variegata and the G. australis species groups (Mitchell 1965; King 1979;

King 1982). The King and Mitchell hypotheses were not enunciated in modern phylogenetic terms so we restate them as three discrete hypotheses; 1) The Australian

Gehyra result from a single, recent colonization event from a Melanesian ancestor. In this case, the Australian radiation will form a monophyletic clade, nested within a broader

Melanesian Gehyra species assemblage. 2) The Australian radiation consists of a large- 108 bodied, tropically adapted australis group and small-bodied, arid-adapted variegata species group, in which case we would expect to find two reciprocally monophyletic clades corresponding to Mitchell and King’s proposed species complexes. 3) The diversification of the Australian Gehyra was driven by chromosomal rearrangement in allopatric populations. If King’s proposal regarding chromosomal speciation is correct,

2n=44 chromosome species would be expected to be oldest, with the origin of 2n=42 chromosome animals being temporally intermediate and 2n=38 and 2n=40 chromosome lineages being the most recently derived species. We sought to evaluate these three hypotheses using a combination of species tree reconstruction and molecular dating methods.

Methods

Sampling

All tissue samples were obtained from Australian museum collections (Australian

Biological Tissue Collection [ABTC] at the South Australian Museum [SAMAR],

Western Australian Museum [WAM]) or sequences were available on GenBank

(Appendix 1 – GenBank accession numbers will be added upon acceptance). DNA was extracted using a Puregene™ DNA Isolation Tissue Kit D-7000a (Gentra

Systems USA) following the manufacturer's guidelines. Standard PCR methods were used to amplify the coding region of the mitochondrial gene NADH dehydrogenase subunit 2 (ND2), portions of the nuclear coding genes recombination-activating gene

1 (RAG1), prolactin receptor (PRL-R), melanocortin 1 receptor (MC1R), the first and second intron of the histone cluster 3 gene along with the contained exon region (H3) 109 and two anonymous nuclear loci (A1 and A2). Anonymous loci were developed from the analysis of DNA fragments generated from a partial shotgun library using GS-

FLX 454 sequencing (Roche USA), isolated using the methods described in Bertozzi et al. (in prep) (A1 and A2). A summary of primers used is provided in Table 1. PCR products were sequenced using the ABI PRISM BigDye Terminator Cycle

Sequencing Ready Reaction Kit and an ABI 3730 automated sequencer. Sequences were edited by eye and aligned at first using the Muscle plug-in in Geneious v5.3.1

(Biomatters, New Zealand) (Drummond et al. 2010; Edgar 2004) then refined by eye.

Unalignable regions were determined by eye and excluded from further analysis and heterozygous sites were coded using IUPAC ambiguity codes. 110

Table 1: Summary of loci used for species tree analysis. Summary statistics were calculated using DNAsp v5.0 (Rozas 2009) Primers

are listed from 5’ end to 3’ end, BP – base pair length of alignment, /site – nucleotide diversity per site, /sequence – Watterson’s

theta be sequence, * after Tajima’s D statistic indicates significance of the statistic to p < 0.05, model refers to the model of nucleotide

substitution chosen for the locus using AIC.

No No GC Tajima's Locus Primer Sequence BP Samples species Haplotypes content e D Model Reference ND2 F:AAGCTTTCGGGGCCCATACC 1049 123 32 110 0.453 0.22 0.14 -0.77 GTR + I + Γ Sistrom et al 2009 R:GCTTAATTAAAGTGTYTGAGTTGC H3 F:TGGAGCAGGAAARACAACYAT 442 100 32 30 0.453 0.04 0.09 -2.20* TrN + Γ This paper R:RAGCTCAGACTTYGAAATKCC PRLR F:GACARYGARGACCAGCAACTRATGCC 526 103 32 20 0.46 0.03 0.08 -2.17* GTR + Γ Townsend R:GACYTTGTGRACTTCYACRTAATCCAT MC1R F:GGCNGCCATYGTCAAGAACCGGAACC 608 34 23 19 0.56 0.04 0.05 -0.37 HKY + I Pinho et al 2009 R:CTCCGRAAGGCRTAAATGATGGGGTCCAC RAG1 F:CTAAGACTGATAAAGAGAAAG 756 24 24 22 0.432 0.01 0.03 -1.82* GTR + I + Γ Sanders & Oliver 2009 R:CTTCACATCTCCACCTTCTTC A1 F:CCGCTTGAACCGATGGTGCTCT 658 42 20 34 0.432 0.06 0.13 -1.9* GTR + Γ This paper R:ACGTAACACAGCATGAGTTTTGGAGTG A2 F:ACGAGCCAGTAACCACTGATCAGGAA 529 42 25 13 0.497 0.03 0.06 -1.90* GTR + Γ This paper R:CCGTCGTTTGGCCGTCAGAAAT

111

from further analysis and heterozygous sites were coded using IUPAC ambiguity codes.

Estimation of Rates of Evolution within Gehyra

Divergence times between representatives of major Gehyra lineages were estimated from the RAG1 data (see Appendix 1) using Bayesian inference implemented in BEAST v1.6.1 (Drummond & Rambaut 2010). Monophyly of the Gekkotans in relation to other squamates is well established (e.g. Gamble et al 2010, Oliver & Sanders

2008) and was thus assumed assumed a priori. Model selection was determined using the

Akaike Information Criterion (AIC) carried out using jModeltest v0.1.1 (Posada 2008). A

Yule branching process with a uniform prior was adopted. A relaxed clock was used and rate variation across adjacent branches was assumed to be uncorrelated. Model parameter values were unlinked and the analysis run for 50 million generations, with the first 15 million discarded as burn in and every 1000th tree sampled thereafter. Output was evaluated using TRACER v1.4.1 (Drummond & Rambaut 2010) to confirm acceptable mixing, stationarity of the MCMC parameter sampling, and adequate effective sample sizes (>200). Due to the lack of Gekkotan fossils which can be placed with enough phylogenetic precision to act as molecular clock calibrations (Gamble et al. 2010; Oliver

& Sanders 2009; Sanders et al. 2007), a number of robust external fossil calibrations were used. Our chosen calibrations are similar to those of Sanders et al. (2007) and are summarized in Table 2. All calibrations were treated as being uncertain and given lognormal distribution, in order to reflect known bias in the fossil record (Sanders & Lee

2007). A liberal, uniform prior of 160 – 250 ma was placed on the base of the tree to prevent the analysis becoming stuck in an unrealistic parameter space (Drummond et al. 112

2006). The posterior set of trees was summarized using TreeAnnotator (Drummond &

Rambaut 2010) before being visualized using FigTree v1.4.0 (Rambaut 2009).

Table 2: Summary of calibrations used for the dating analysis. A fuller justification for the use of these calibrations is available in Sanders & Lee (2007). Apart from the basal split between Gekkotans and the rest of the squamates, all calibrations were given a lognormal distribution, which has a hard minimum bound slightly younger than the minimum age of the oldest known fossil, peak probability at the estimated age of the oldest known fossil and a long tail of possible older dates to reflect known bias in the fossil record. Dates presented represent the median date and upper and lower 95% confidence intervals.

Lognormal Prior Node Distribution References Scolecophidians and alethinophidians 97 (92-120) Sanders & Lee 2007 Shinisaurus and Varanus 83 (77-105) Sanders & Lee 2007 Henophidians and caenophidians 93.5 (85-116) Molnar 2000 Iguanians and anguimorphs 168 (155-190) Wiens et al. 2006 Scincomorphs and lacertoids + Toxicoferans 168 (155-190) Sanders & Lee 2007 Gekkotans and other squamates 165 -251 [flat prior] Sanders & Lee 2007

Species Tree Reconstruction and Divergence Estimation within Australian Gehyra

Sampling for the reconstruction of species relationships was based on a total of

123 individuals and the seven genes listed above. Taxon sampling included five individuals from all recently discovered species (using mtDNA screening, morphological analysis and species boundary assessment – Sistrom et al. in prep.), all described Gehyra species, and selected representatives of Melanesian Gehyra (G. baliola, G. barea, G. membranacruralis, G mutilata and G. oceanica) to determine the phylogenetic placement of the Australian Gehyra in relation to Melanesian taxaWe undertook locus sampling in a 113 hierarchical manner using faster evolving loci for more detailed individual sampling compared to markers traditionally used to resolve deeper phylogenetic relationships (see

Appendix 1 for details on the scheme for locus sampling for each individual). Attempts were made to sequence at least one individual per species for each locus, however where this was not achieved, data were coded as missing in the input file. Although this approach considerably increases the MCMC sampling required to reach convergence in

Bayesian analysis and thus computational expense, it allows a sequence to be placed anywhere in the tree and thus is the most conservative approach to dealing with missing information from a species. Collecting sequence data in this manner is expected to have a minimal impact on analytical power (Wiens & Morrill 2011) whilst reducing sequencing cost. We used a conservative approach in estimating the rate of sequence evolution by placing a normally distributed prior on the substitution rate of the RAG1 dataset (see above), taken from the 95% C.I. for rate estimation along each branch among the Gehyra in the dating analysis.

Bayesian estimation of the species level phylogeny was undertaken using

*BEAST (Heled & Drummond 2010). * BEAST utilizes a single step approach to simultaneously estimate gene trees from individual sequence alignments and the overall species tree simultaneously. Substitution models for individual genes were determined using the AIC carried out using jModeltest v0.1.1 (Posada 2008) (see Table 1) and all related parameters were estimated in *BEAST. A Yule branching process with a uniform prior was adopted and a relaxed clock was used and rate variation across adjacent branches was assumed to be uncorrelated for all gene trees. The mutation rate for the

RAG1 gene tree was given a lognormal prior distribution with upper and lower rates 114 representing the fastest and slowest rates observed in the broader dating analysis as represented by the 95% confidence intervals of all branches within Gehyra in that analysis and the mean representing the average of all observed rates within Gehyra.

Model parameter values were unlinked and the analysis run for 100 million generations, with the first 25 million discarded as burn in and every 10 000th tree sampled thereafter.

Output was evaluated using TRACER v1.4.1 (Drummond & Rambaut 2010) as for the higher level analysis. To ensure adequate searching of the parameter space, the analysis was repeated five times. A maximum clade credibility species tree was produced by combining the trees remaining after burn in from all runs using LogCombiner

(Drummond & Rambaut 2010) and summarized using TreeAnnotator (Drummond &

Rambaut 2010) before being visualized using FigTree v1.4.0 (Rambaut 2009).

Gene Tree Discordance Analysis As gene trees inferred from different loci are often incongruent (Chung & Ané

2011; Cranston 2010; Degnan & Rosenberg 2009), it is important to investigate the level of potential discordance between gene trees. As an initial examination of discordance, individual gene trees from each of the five *BEAST runs were combined with

LogCombiner (Drummond & Rambaut 2010) and summarized using TreeAnnotator

(Drummond & Rambaut 2010), once 25% of the trees had been removed as burn in. Tree files were visualized using FigTree v1.4.0 (Rambaut 2009) (Appendix 2).

Like other species tree approaches (e.g., STEM, BEST, MDC), *BEAST accounts for potential discordance between trees by attributing the discordance between trees to incomplete lineage sorting (ILS) (Larget et al. 2010). Consequently, if discordance is a result of horizontal gene transfer (HGT), the method may incorrectly produce a smaller 115 distance between lineages than expected under the coalescent model (Liu & Yu 2011).

This is of particular concern in Gehyra where admixture between species cannot be ruled out. In order to investigate the role of potential sources of gene tree incongruence, a

Bayesian concordance analysis (BCA) was used to estimate gene tree discordance

(Larget et al. 2010) without making assumptions with regard to the source of that discordance. Methods for measuring gene tree discordance are still in development and require congruent sampling of individuals and species across loci (Cranston 2010). In order to meet this requirement, we used a hierarchical approach to testing our data. As the

RAG1 gene tree has the most minimal sampling, all other gene trees were trimmed to match RAG1 taxon sampling (n=30). At the next level, A7, A8 and MC1R had similar sampling, so all gene trees excluding RAG1 were trimmed to have identical sampling

(n=44). Finally, as ND2, H3 and PRL-R all had near complete individual sampling, as a final step in our hierarchical approach, these were trimmed to have identical sampling

(n=76). Models were determined using the AIC implemented in jModeltest v0.1.1

(Posada 2008) and all model parameters were unlinked. For each tier, individual gene trees were estimated using MrBayes v3.1 (Ronquist & Huelsenbeck 2003). Each analysis was run for 15 million generations sampled every 1000 generations. Using the program mbsum (Larget et al. 2010), tree files from the two chains for each Bayesian analysis were combined once the first 10% of trees had been discarded as burn in. Once complied,

BUCKy v1.4.0 (Larget et al. 2010) was used to conduct BCA analysis. Each BCA analysis comprised two independent runs with four chains each for two million generations sampled every 100 generations. The primary concordance tree for each BCA analysis was visualized using FigTree v1.4.0 (Rambaut 2009), with the concordance 116 factor (CF) for each node displayed on the tree. If discordance is the result of sampling method, it would be expected that maximizing either taxon or gene sampling would increase CFs.

Results

Estimation of Rates of Evolution in Gehyra The results of the analysis of rate estimation using the RAG1 dataset and a

Bayesian uncorrelated relaxed clock with five external fossil calibrations (Table 2) are presented in Figure 1. Divergence dates across squamates and geckos were largely concordant with previous studies (Gamble 2008; 2010; Sanders et al. 2007). This indicates that date estimates for splits within Gehyra are likely to be reasonable given the available calibrations. Divergence of G. oceanica from G. australis and G. variegata had a point estimate of 29.74 ma (95% C.I. 45. 05 – 17.22 ma), and divergence between G. variegata and G. australis had a point estimate of 11.24 ma (95% C.I. 21.32 – 3.95 ma).

From this analysis we used the average branch rate of evolution of 0.0007 mutations per year (95% C.I. 0.0002 – 0.0019) for further species tree analyses. 117

Figure 1: Dating analysis using fossil calibrations from Table 2. Node bars represent the

95% confidence interval of divergence dates in years and node labels represent posterior probabilities. Calibrated node bars are shown in black. Gehyra are shown to be a monophyletic member of the subfamily Gekkoninae, the split between Australian Gehyra 118 and G. oceanica is shown to have occurred approximately 29.74 ma. (95% C.I. 45. 05 –

17.22 ma.).

Species Tree Reconstruction and Divergence Estimation within Australian Gehyra

The results of Bayesian species tree analysis across Australian and some

Melanesian Gehyra are presented in Figure 2. Overall, posterior probabilities across the species tree appear relatively low and BCA results confirm a high degree of discordance in the data. This could indicate uncertainty in the observed species tree and suggests that interpretations be undertaken with caution. However as our analyses considers a more extensive parameter space considered by species tree analysis than traditional phylogenetic analyses (i.e. concatenated Bayesian analysis) and thus the support values are not directly comparable to those obtained by such methods and “no rule of thumb” regarding acceptable support values is established. We consider our tree to represent the best estimate of topology given the data at hand. The species tree analyses (i.e. *BEAST and BCA) find a basal split of Australian Gehyra into two clades, but the content of the two groups differs from those proposed by King. Two species, G. occidentalis and G. xenopus, that were regarded as members of the australis group by King fall in with members of his variegata group. In addition, one Melanesian species, G. membranacruralis, branches at the base of our australis group rather than with the other

Melanesian species (G. oceanica, G. baliola and G. barea).

A comparison of the divergence estimates for the basal splits within our revised

G. variegata and G. australis clades revealed near identical estimates: G. variegata – 6.8 ma (95% C.I. 17.8 – 1.9 ma) and G. australis –7.0 ma (95% C.I. 18.0 – 1.9 ma) with broad overlap of the estimates of splits within each clade (see Fig. 2). 119

Figure 2: Species tree estimation based on one mitochondrial and six nuclear genes across Gehyra. Terminal labels are Gehrya species names and the numbers in grey following them represent the chromosome race of species where known. Node bars 120 represent the 95% confidence interval of divergence dates in years and node labels represent posterior probabilities.

Gene Tree Discordance Analysis

A visual inspection of individual gene trees from the *BEAST analysis reveals considerable discordance between genes (Appendix 3). Analysis of hierarchically trimmed gene trees showed CFs (a measure the percentage of gene trees which support a particular node) were low overall, indicating a high level of gene tree discordance (see

Fig. 3). The deeper relationships between taxa in the BCA analysis at different sampling levels are considerably variable – further supporting high levels of gene tree discordance.

However, the topology of the species tree attained using BCA and containing all genes shows a high degree of similarity with the *BEAST species tree reconstruction. The topologies of these trees support the basal position of the Melanesian species relative to the Australian species groups and the New Guinean G. membranacruralis, reciprocal monophyly of the G. australis and G. variegata clades and species membership of each. 121

Figure 3: Results of BUCKy species tree estimation and BCA. a- sampling of 30 individuals and seven genes b – sampling of 44 individuals and six genes c- sampling of 76 individuals and 3 genes. Terminal labels represent Gehyra species and node labels 122 represent concordance factors – a measure of the number of gene trees across the sample that support a node. CFs were generally low regardless of whether gene or taxon sampling were maximized.

Discussion Our results clarify the taxonomic placement of the Australian Gehyra, provide confirmation of the phylogenetic relationships and the timing of speciation within

Australian Gehyra and quantify the high levels of gene tree discordance observed within this recent and rapid radiation. The time calibrated RAG1 phylogeny places

Gehyra as a monophyletic group within the subfamily Gekkoninae, consistent with the current taxonomic nomenclature. The time calibrated RAG1 phylogeny and species tree analysis show that the Australian Gehyra species are largely monophyletic and nested with a broadly distributed assemblage of Melanesian Gehyra species.

The exception to this is G. membranacruralis, a Melanesian species from southern New Guinea, which is nested within the Australian Gehyra clade in the most probable tree topology. However this relationship is weakly supported (pp=0.45 on the branch linking it to the australis group, See fig. 2). One possibility is back migration of an australis group member, but on the face of it this would indicate a species with the relatively conservative Australian style external morphology re-adopting an extreme version of the Melanesian Gehyra. morphology (fragile skin, extensive folds of skin on body and limbs, extremely large size). An alternative could be that G. membranacruralis is close to the common ancestor of the Australian radiation, such that the molecular signal on the ordering of the splits between Melanesian and

Australian lineages is relatively weak and noisy. 123

Regardless of the precise branching position of G. membranbacruralis, the basal split separating the Australian clade from the other Melanesian assemblage occurred between the mid-Eocene and the early Miocene. Our divergence estimate for the split between the G. australis and G. variegata clades dates between the early Miocene and the mid Pliocene. Finally, BCA investigation of gene tree discordance reveals high levels of discordance between gene trees across the dataset indicating that discordance is due to biological processes rather than sampling artifacts, but that the general tree shape is congruent with our other analyses.

Hypothesis 1 - Recent Asian Origin of the Australian Gehyra

Our analyses support previous evidence (Sistrom et al. 2009; Oliver et al. 2010) that the Australian Gehyra radiation is monophyletic and derived in relation to

Melanesian Gehyra, with the exception of the southern New Guinean species – G. membranacruralis. As species tree methods differ from traditional phylogenetic approaches in that they do not employ tree rooting with outgroups (Knowles & Carstens

2007), temporal hypotheses regarding divergence between reciprocally monophyletic basal groups are not possible to test. However as the Australian Gehyra clade is nested within a broader, paraphyletic Melanesian assemblage, it is possible to infer,that the

Australian clade is derived relative to other Melanesian taxa. The estimated time of divergence of the Australian clade from the rest of the Melanesian assemblage covers a very wide interval, from the mid-Eocene to the early Miocene. This makes attributing a particular biogeographic event to the introduction of Gehyra to Australia difficult, however the timing of the split of the Australian clade from the Melanesian assemblage overlaps with the collision of the Australian tectonic plate with the Ontong Java plateau 124

23-26 ma (Knesel et al. 2008) at a period when Australia was likely to be warm and humid (Byrne et al. 2008, Martin 2006). Therefore the invasion of a tropically adapted, ancestral Gehyra from the Asian/Melanesian region at this time is plausible. The placement of G. membranacruralis within the G. australis clade indicates a link between

Australian and New Guinea that is not unexpected given the long term periodical connection of the two landmasses throughout the Plio-Pleistocene (Voris 2000). In contrast with the other Australian Gekkotan lineages which have a Gondwanan origin, the divergence between Australian and Melanesian Gehyra is more recent (Gamble et al.

2008b; Oliver & Sanders 2009) as is consequently the diversification within Australian

Gehyra.

Hypothesis 2 – Tropically Adapted and Arid Adapted Species Complexes

All of our analyses find two clades within the Australian radiation, as do previous molecular studies (Sistrom et al. 2009, Oliver et al. 2010). The content of our two groups mostly matches the subdivision proposed by Mitchell and King. However, it is important to note that two of King’s australis group species, G. occidentalis and G. xenopus fall into our variegata clade. Species contained within the initial concepts of the G. australis clade (Fig. 2) were on average larger bodied taxa (Horner 2005; King 1983) associated with the tropical, subtropical and monsoonal tropics of Australia and southern New

Guinea, while the G. variegata clade comprised smaller bodied species associated with the arid and semi-arid zones (King 1979; Moritz 1986). Both G. occidentalis and G. xenopus are relatively large bodied (maximum SVL greater than 65 mm), both are confined to the monsoonal Kimberley region of Western Australia, and both branch near the base of the G. variagata clade. While it is true that many of the members of the G. 125 variegata clade are smaller-bodied than those in the G. australis clade, body size appears to be somewhat labile in this group with larger species branching close to smaller species.

The one consistent aspect of body size appears to be that the smallest species (max SVL

< 45 mm) are confined to the variegata group, but no general conclusion applies to medium and larger body sizes. Similarly, the tropical-arid dichotomy is weakened by the likely plesiomorphic nature of tropical adaptations and the fact that the G. variegata clade includes tropical species.

Hypothesis 3 – Evaluation of Chromosomal Speciation Patterns

King hypothesized that the diversification of the Australian Gehyra was driven by chromosomal speciation and proposed a detailed evolutionary scenario by which this may have occurred (King 1984). However, this scenario came under considerable scrutiny

(Sites & Moritz 1987) due to the inconclusive nature of assumptions regarding the allopatric distribution of chromosome races and reproductive isolation between them.

Our framework provides a time calibrated, multi-locus framework with which to re- evaluate this scenario that is considerably more robust than the information that was available to King (1984). A prediction of King’s (1984) proposed evolutionary scenario, is that reproductively isolated chromosome races should be arranged phylogenetically in a linear fashion reflecting their historical divergence. It is clear from the distribution of chromosome races in our analysis that this is not the case. Furthermore, the placement of

G. occidentalis in the G. variegata clade means that the assumption that the 2n=44 chromosome karyotype is the ancestral state of the Australian Gehyra is questionable.

Given our phylogeny, either the independent evolution of karyotypes (such as 2n=42a) or reversal (to 2n=44) are necessary to explain the observed karyotypes, but neither 126 phenomenon was countenanced in King’s model. King’s work undoubtedly revealed the fact of large-scale cryptic speciation in Gehyra, but the mechanism he proposed has not proven to be a sufficient explanation.

Evolutionary History of the Australian Gehyra Radiation

Based on our analyses, we are able to pose a new scenario for the diversification of the Australian Gehyra. The paraphyletic relationship with and timing of the Australian

Gehyra clade in relation to Melanesian Gehyra assemblage makes an introduction of the group to Australia during the collision of the Australian tectonic plate with the Ontong

Java plateau and subsequent close proximity to Melanesia approximately 23-26 ma plausible. At this time, Australia’s climate was warm, wet and stable (Byrne et al. 2008;

Martin 2006), which would have been ideal conditions for a tropically adapted gecko to capitalize on newly available habitat. Estimation of the divergence of the G. variegata and G. australis clades is imprecise, making the inference of a particular biogeographic event causing the divergence to be difficult. However, the confidence intervals of divergence estimates between species within each clade show that diversification of both clades occurred simultaneously over a period ranging from the Late Miocene to the present, in which the Australian continent has undergone a significant contraction of mesic habitat and simultaneous expansion of the arid biome (Byrne et al. 2008). As such, series of complex vicariant and adaptive events are likely to be associated with the diversification of both groups.

Complex patterns of morphology, chromosomal diversity, evidence of incomplete lineage sorting and reproductive isolation (Sistrom et al. in prep) indicate that expansion 127 and diversification of Australian Gehyra, particularly in the G. variegata clade is ongoing. Finally, G. xenopus and G. occidentalis, which are found in the Kimberley region of northwest Australia, display morphological properties akin to the G. australis clade, but are phylogenetically members of the G. variegata clade, indicating that this region could have played a key role in the initial diversification of the two groups.

The Impact of Gene Tree Discordance

Gene tree discordance is problematic for the inference of species relationships using a concatenation approach (Huang et al. 2010; Cranston 2010; Kubatko & Degnan

2007). Species tree approaches more accurately model uncertainty in the data and thus are less prone to type 1 error than concatenation approaches, thus making them more suitable for the estimation of species relationships when gene tree discordance is high

(Chung & Ané 2011; Huang et al. 2010; Kubatko & Degnan 2007). Despite the large number of samples that we used for species tree estimation, posterior probabilities of tree nodes are low overall. As such, it is likely that discordance between gene trees accounts for the low support, consistent with our BCA results (Fig. 3). While increasing both taxon and gene sampling undoubtedly would improve the power of the analysis, the hierarchical approach to BCA we have undertaken shows that CFs remain low regardless of whether taxon or gene sampling is maximized, indicating that in this case, increasing the density of individual sampling is unlikely to improve analytical power, at least over the range of sample sizes that we investigated. As *BEAST assumes all discordance arises from ILS, and HGT is a potential cause of discordance, it is possible that the distance between species are incorrectly assumed to be shorter than they truly are. For this reason, our substitution rates are deliberately conservative and thus the error bars 128 surrounding nodes in the species tree are more likely to encompass the true divergence times of species than a more restrictive prior. Distinguishing between ILS and HGT is a significant hurdle in the estimation of species trees and the determination of evolutionary relationship between species and development of methods to distinguish between these two processes is ongoing (Chung & Ane 2011).

Acknowledgements

This work was funded by ABRS grant 207-43 awarded to M. Hutchinson and S.

Donnellan The authors would like to thank K Sanders and M.S.Y. Lee for advice on suitable calibrations for divergence estimation, S. Edwards for advice on sampling design, H. Lainer and D. Edwards for reviewing and improving the manuscript. 129

Morphological differentiation correlates with ecological but

not genetic divergence in a Gehyra gecko.

Mark Sistrom1, 2, 4, Danielle Edwards3, Steve Donnellan1, 4 and Mark Hutchinson2.

1 Ecology and Evolutionary Biology Department, School of Earth and Environmental

Sciences, The University of Adelaide, Adelaide, Australia.

2 Department of Herpetology, South Australian Museum, Australia.

3 Department of Ecology and Evolutionary Biology, University of Michigan, Ann

Arbor, MI, USA.

4 Evolutionary Biology Unit, South Australian Museum, Adelaide, Australia.

Corresponding author: [email protected]

Journal of Evolutionary Biology (in review) 130

Mark J. Sistrom (candidate)

Corresponding author: Conducted field collection, responsible for molecular and genetic data collection, analysis and interpretation, drafted manuscript, produced all figures, oversaw manuscript revision.

Signed…………………………………………………………..Date……………

Dan Edwards

Developed and assisted in environmental analytical approach, provided methods for environmental data collection and analysis and assisted in manuscript revision.

I give consent for M.J. Sistrom to include this paper for examination towards the degree of Doctor of Philosophy.

Signed: Date:13/09/2011

Stephen C. Donnellan

Sought and won funding, co-supervised direction of project, provided assistance in analysis selection and manuscript revision.

I give consent for M.J. Sistrom to include this paper for examination towards the degree of Doctor of Philosophy.

131

Signed: Date: 16/09/2011

Mark N. Hutchinson

Sought and won funding, co-supervised direction of study, assisted in field collection and assisted in manuscript revision.

I give consent for M.J. Sistrom to include this paper for examination towards the degree of Doctor of Philosophy.

Signed: Date: 16/09/2011 132

Abstract

Body size affects life history, the ecological niche of an organism and its interactions with other organisms. Resultantly, marked differences in body size between related organisms are often an indication of a species boundary. This is particularly evident in the Gehyra variegata species complex of geckos, which displays differential body sizes between genetically divergent species, but high levels of intra-specific morphological conservatism. We report on a Gehyra population that displays extraordinary body size differentiation in comparison with other G. variegata species. We used morphological and environmental data to show this population is phenotypically and ecologically distinct from its parapatric congener G. lazelli and that morphology and ecology are significantly correlated. Contrastingly, mtDNA analysis indicates paraphyly between the two groups and allele frequencies at six microsatellite loci show no population structure concordant with morpho/eco-type. These results suggest either ecological speciation or environmentally induced phenotypic polymorphism, in an otherwise morphologically conservative group. 133

Introduction

Body size is one of the most important ecological and evolutionary attributes of an organism. The size of an organism influences its energetic requirements (Nagy, 2005), ability to exploit resources (Schluter, 2000) as well as influencing the interactions it will have with other organisms (Schluter, 2010). Resultantly, differences in body size are the predominant way in which related organisms can avoid direct resource competition thus allowing for assemblages of related organisms to occupy an environment (Dayan &

Simberloff, 2005), similarly size selective predation can be a primary organizing force in a community assembly (Palkovacs & Post, 2009). Body size places important constraints on how an organism interacts with its environment and the magnitude, manner and symmetry of its interactions with other species (Schluter, 2000). While, the ecological impacts of shifts in body size have implications for macro- and micro ecological interactions, evolutionary changes in body size can also be an important component of speciation processes.

Differential body size can arise through differential environmental selection, interspecific interactions or intraspecific phenotypic plasticity (Schluter, 1994).

Differential body sizes between species are hypothesized to have arisen through two distinct processes (Losos, 1990). The first is character displacement, which is an evolutionary response to divergent selection pressure (Nagel & Schluter, 1998; Pfennig &

Pfennig, 2010). The second is through pre-mating selection either through divergent mate selection or reduced hybrid fitness (Rundle & Schluter, 1997, Nagel & Schluter, 1998).

As such, divergent body size can lead to the development and subsequent reinforcement 134 of species boundaries following secondary contact of divergent populations that have arisen either in sympatry or allopatry.

Studies of model organisms such as Anolis lizards have shown that rapid morphological change can occur in a very small number of generations when divergent selection pressure is high (Losos et al., 1997) although the role of phenotypic plasticity in such adaptation is thought to be significant (Losos et al., 2000). In addition, stickleback fishes show both ecologically divergent selection and assortative mating in relation to body size providing evidence for an adaptive shift in body size being fundamental in recent speciation (Nagel & Schluter, 1998). In species pairs that have undergone recent and rapid divergence, genome wide divergence would be expected to accumulate at a slower rate, under the “genomic islands of speciation” model, demonstrated in several recent studies (e.g., Anopheles - Turner et al., 2005, Mus – Harr, 2006, Drosophila - Ting et al., 1998). As such, rapid, recent speciation associated with strong diversifying selection can produce phenotypically distinct species that are not necessarily differentiated when examined using neutrally evolving genetic markers. As a result of the important role that body size can play in the development and maintenance of species boundaries, when a marked difference in body size between populations is observed it is often a robust indicator of the presence of multiple species, particularly when population distributions are adjacent or overlapping (e.g. Sota et al., 2000). While some taxa do display significant intra-specific plasticity in body size within population, this is typically partitioned by sex as a result of selection on mating systems (e.g., male size differentiation in frogs - Smith & Roberts, 2003, lizards – Stuart-Smith et al 2007, and fishes – Gross, 1984; Gross, 1985). 135

Geckos of the Gehyra variegata species complex (King, 1979; King, 1983;

Sistrom et al., 2009) display a number of interspecific body size shifts. Body size (snout- vent length - SVL) of species within the complex ranges from an average of 45mm in G. minuta to 79mm in G. xenopus (see Fig. 1). Pairs of sister species can differ by as much as 17% (G. purpurascens and G. nana) despite displaying size variation between species, members of the Gehyra variegata complex show a narrow range of variation of body size within species and no member of the genus is known to include obvious multiple size classes (King, 1979). In addition to intra-specific conservatism of body size, members of the G. variegata complex historically have proven taxonomically challenging due to conservatism in other morphological characters, particularly body shape and scalation

(King, 1979; King, 1983; Moritz, 1986), despite significant genetic and karyotypic divergence (King, 1979; King, 1983; Moritz, 1986; Sistrom et al., 2009). As such, body size differences among populations of Gehyra are generally a good indicator of species boundaries, especially when populations are sympatric.

136

Figure 1: Phylogenetic tree adapted from Sistrom et al. (2009) of the Gehyra variegata complex showing body size transitions. Body size measurements represent average SVL of each species (Wilson and Swan 2008) and silhouettes are to scale.

As part of a systematic revision of southern Australian Gehyra, we discovered a population of exceptionally large and robust Gehyra in the far northern Flinders

Ranges of southern Australia, where two smaller species Gehyra lazelli and G. variegata also occur (Fig. 2). As substantial body size differences typically indicate 137 different species in Gehyra, we carried out an investigation of the status of this large- bodied population (henceforth referred to as LP) using both morphological and genetic data to address the patterns of morphological change.

Figure 2: Representative preserved vouchers of A) G. lazelli [R64427 and R64944], B)

LP [R58254 and R56408] and C) G. variegata [R59379 and R58593] from the Flinders

Ranges, southern Australia showing the variation in body size and robustness.

Through extensive field surveys we sought to determine if LP and G. lazelli occur sympatrically or allopatrically across a broad distributional area centred on known locations where LP occurred. At an early stage we became aware of substantial discordance between morphological data, which tended to confirm the distinctiveness of

LP, and the mitochondrial phylogeny, that indicated no differentiation and in fact seemed to suggest polyphyly of LP compared to G. lazelli. In this paper, we explore possible scenarios underlying the discordance between genetic and morphological patterns of 138 variation by assessing morphological, genetic and environmental evidence. Specifically, we assess if morphological divergence is associated with genetic divergence by testing for genetic differentiation between the morphotypes using six microsatellite markers, extended mtDNA screening and karyotype analysis. Further, we determine if the morphological divergence between the morphotypes is associated with environmental distinction by testing the levels to which morphological variation could be explained by variation in climate, elevation, rock-type and vegetation-type. We also examine the relative merit of alternative hypotheses for the evolution of this pattern, including allopatric speciation, ecological speciation and phenotypic plasticity.

Materials and Methods

Sample selection and field collections

Field surveys of the Terrapinna Springs and surrounding areas were undertaken in the Northern Flinders ranges for a total of 3 weeks over the summer of 2008/2009 and

2009/2010, which resulted in the collection of 22 specimens characteristic of LP morphotype – adults of this form were noticeably larger than surrounding populations of

G. lazelli and G. variegata (Fig. 2), departing from the morphological conservatism typical of the genus (King, 1979; Moritz, 1986; Sistrom 2009)and was only found granite gorge and rock outcrop habitats. Frozen and alcohol preserved tissue samples were deposited in the Australian Biological Tissue Collection (ABTC) and whole specimens were deposited at SAMA (See Appendix 1 for specimen collection details and museum numbers – Genbank Accession number and Dryad DOI’s will be added to Appendix 1 following acceptance). Populations of G. lazelli were at most within 5km of LP 139 specimens but were never syntopic. We expanded our G. lazelli sampling to include specimens collected in the vicinity of the contact with LP, and a representative sampling across the known distribution of G. lazelli in order to make a comparison with the intra- specific diversity of G. lazelli.

Figure 3: Collection locations of specimens used for morphological and molecular 140 genetic analyses. Grey circles are collection sites for G. lazelli specimens, black stars are collection sites for LP specimens. Numbers refer to locality data in Figure 4, summarized in Appendix 1, site without numbers represent samples for which only microsatellite and morphological data was collected. Grey contours are at 50m elevation intervals.

Karyotyping

Two individuals collected from Terrapinna Springs (R64103 (female) and

R64104 (male)), both with the LP morphotype, were karyotyped using standard methods as described in Sistrom et al. (2009) in order to determine the chromosome complement of the LP individuals.

mtDNA molecular protocols

Genomic DNA was extracted using a Puregene™ DNA Isolation Tissue Kit D-

7000a (Gentra Systems) following the manufacturer's guidelines. The mitochondrial gene

NADH dehydrogenase subunit 2 (ND2) and partial flanking tRNA's (1136 bp) were used for initial screening to determine the placement of the LP individuals within the broader

Gehyra phylogeny. Mitochondrial ND2 fragments were amplified using the primers

M112F (5'- AAGCTTTCGGGGCCCATACC- 3') and M1123R (5'-

GCTTAATTAAAGTGTYTGAGTTGC - 3'). Amplifications were carried out in 25ML volumes using standard buffer and MgCl2 concentrations, 0.4 mM dNTPs, 0.2 MM each primer, 0.75 U AmpliTaq Gold® DNA Polymerase (Applied Biosystems) and approximately 100ng of genomic DNA. Thermocycler profiles were: 9 min at 94oC, then

45 x: 45 s at 94oC, 45 s at 55oC and 1 min at 72o C with a final extension step of 6 min at 141

72o C. The PCR product was purified using a Millipore Montage® PCR384 Cleanup Kit

(Millipore Corporation) following the manufacturer's guidelines. Standard cycle sequencing was carried out according to the standard BigDye Terminator (Applied

Biosystems) requirements and cleaned products were read on an Applied Biosystems

3730xl capillary sequencer.

Phylogenetic analyses

Bayesian and Maximum Likelihood (ML) phylogenetic analyses of the ND2 data were undertaken to ascertain the phylogenetic placement of the LP specimens. The program jModeltest v0.01 (Posada, 2008) was used to evaluate different models of nucleotide substitution. The ND2 data were partitioned according to codon position and corrected-AIC criterion selected the GTR + I + Γ model for all codon positions. ML analyses were carried out using the RAxML BlackBox web server (Stamatakis et al.,

2008) and branch support was assessed with 1000 bootstrap replicates. Bayesian analyses were undertaken using MrBayes v3.1 (Ronquist & Huelsenbeck, 2003). For Bayesian analyses the data were partitioned for each codon position, as described above, with parameters for each partition unlinked. Four-incrementally heated MCMC chains were run for five million generations, sampling every 1000 generations, with the first 10% samples discarded as burn-in. Convergence of posterior probabilities and stationarity of likelihood scores were confirmed through examination of the trace and effective sample sizes (ESS) of parameters using Tracer v1.4 (Rambaut & 156 Drummond, 2007).

142

Microsatellite locus development and genotyping

Given the lack of monophyly for mtDNA, the level of genetic distinctiveness of the LP specimens was examined using microsatellite loci. Microsatellite markers were developed using a next generation sequencing approach. Total genomic DNA was extracted from a tissue sample from a single G. lazelli individual (R52962) using the methods described above. Shotgun sequencing was performed at the Australian Genomic

Research Facility in Brisbane, Australia where samples were prepared according to standard GS-FLX Titanium Library procedure, with the exception that species-specific oligonucleotide adapters (IDT, Iowa, USA) were ligated to the sheared DNA, as multiple species were included in the 454 run. The G. lazelli sample occupied 12% of the plate, which resulted in 87,899 individual reads of which 2.18% contained microsatellites.

The program MSATCOMMANDER v0.81 (Faircloth, 2008) was used to search raw sequences for microsatellites with at least eight repeat units and design appropriate primers. The program MicroFamily (Meglécz, 2007) was used to screen the flanking regions of the reads selected by MSATCOMMANDER for similarities that would prevent successful PCR amplification of the fragments in question. Twenty-four primer pairs were selected for screening across a representative sample of six individuals.

Forward and reverse Multiplex-Ready Technology (MRT) tags were added to the locus specific primers and loci were amplified using PCR protocols as specified in Hayden et. al. (2008). PCR reactions were carried out in 12μL volumes, containing of 10ng genomic

DNA and 20nM of forward and reverse locus specific primers.

A total of eight primer pairs amplified successfully and were polymorphic in the representative sample and these loci were used for full screening across 95 individuals 143

(63 G. lazelli, 22 LP specimens). Gehyra lazelli samples were taken from specimens collected in the area immediately surrounding Terrapinna Springs and extending across the distribution of this species. Electrophoresis of amplified products was carried out using an ABI Prism 3730 Genetic Analyzer (Applied Biosystems) and scored with

GENEMAPPER v3.7 (Applied Biosystems). Two loci proved unscoreable due to a high level of non-amplification. The primers for the remaining six loci used for further analysis are documented (Table 1). The six loci used for analysis were checked for null alleles, large allele dropout and stuttering using MICRO-CHECKER (Oosterhout et al.,

2004). Deviations from Hardy-Weinberg Equilibrium (HWE) and linkage disequilibrium were investigated using Genepop 4.0 (Rousset, 2008).

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Table 1: Summary of microsatellite marker properties and variation. The first set of summary statistics is for the dataset as whole and

the second represents the dataset split into the LP specimen cluster (bottom figures) observed for the corrected data and the G. lazelli

(top figures). N is the number of individuals scored for each locus, Ho is the observed level of heterozygosity, He is the expected

heterozygosity under HWE, Fis is the F statistic with the corresponding P value resulting from Fisher’s exact test implemented in

Genepop 4.0 (Rouseet 2008).

Locus Direction/Sequence Length Repeat N Ho He Fis P Ho He Fis P unit

Geh1 F-ACCTTGAGGGTCCAGTTGTC 178 – 302 (GT)14 70 0.8 0.93 0.1412 0.007* 0.78 0.91 0.163 0.000* R-TCAGGTGGAGATGCCAAGG 0.81 0.96 0.088 0.235

Geh2 F-ACCATTAGCTGTTTGTGGATTGC 156 - 348 (AC)15 45 0.89 0.96 0.0795 0.571 0.76 0.92 0.167 0.001* R-CACAGGCTGGTCCCACAG 0.75 0.93 -0.089 1

Geh3 F-ATGTATCCTTGGTGTCTCCGC 221 – 345 (GT)25 42 0.76 0.96 0.2065 0.004* 0.88 0.94 0.208 0.000* R-GTGTCTGCCGCTCTTAACC 0.8 0.95 0.195 0.002*

Geh4 F-AAAAAGGGGCAGAGCTCAAG 180 – 338 (ATCT)13 76 0.8 0.93 0.1381 0.000* 0.83 0.91 0.202 0.000* R-AATGATCCCCTCCTGCCTC 1 0.92 0.017 0.11

Geh5 F-AGCTGTTCAAGGAACGAATGC 160 – 356 (CTTT)14 78 0.86 0.94 0.0862 0.040* 0.76 0.94 0.064 0.001* R-TGCAGAGGTGGGTAATGGC 0.92 0.94 0.153 0.006*

Geh6 F-ATGACTGGGAGAAAGACAAAGC 195 – 263 (ATCT)15 65 0.78 0.96 0.1718 0.000* 0.81 0.95 0.166 0.000* R-GCAGGATGATCAGTGCAAGC 0.75 0.9 0.087 0.082 145

Genetic Clustering Methods

An individual-based clustering approach, implemented in STRUCTURE v2.3.3

(Pritchard et al., 2000) was used to determine how individuals grouped into genetic clusters. This dataset was run with the inclusion and exclusion of loci for which there was a high degree of missing data. Each STRUCTURE analysis was run for 10 million generations, with the first one million discarded as burn-in at k ranging from 1-10 with 20 replicates for each value of k. The program HARVESTER (Earl 2011) was employed to calculate Δk using the approach of Evanno et al. (2005). In this way, we determine the number of clusters most likely and generated input files for CLUMPP (Jakobsson &

Rosenberg, 2007) so that results from the 20 runs could be combined for visualization using the program DISTRUCT (Rosenberg, 2004).

Morphology and Ecology

A total of 83 adult specimens were selected for morphological analysis (see list -

Appendix 1), with 19 morphometric and 5 meristic characters measured. Morphometric data comprised measurements for head length (HL), head width (HW), head depth (HD), inter-nasal width (IN), inter-orbital width (IO), eye to ear distance (EE), ear to snout distance (ES), forebody length (FBL), axilla-groin length (AGL), humerus length (HU), forelimb length (FL), femur length (FEL), hindlimb length (HIL), snout-vent length

(SVL), tail length (TL), mental scale length (ML), mental scale width (MW), rostral scale height (RH) and rostral scale width (RW). Morphometric measurements were measured to the nearest 0.5mm using digital calipers. Meristic characters measured included characters traditionally used to assess species boundaries in geckos, including pre-anal 146 pore counts (PP), and scale counts for supralabial scales (UL), sublabial scales (SL) lamellae on 4th rear toe pad (LL) and chin shield scales (CS).

All subsequent analyses of morphological and environmental data were conducted using the R statistical package (R Development Core Team, 2011). Each character was tested for sexual dimorphism by regressing values for male and female specimens by

SVL (except for SVL which was regressed by HL) using the lm function of the base R package (R Development Core Team, 2011). The slopes of male and female regression lines were compared for significant differences using an F test implemented with the var.test function of the base R package (R Development Core Team, 2011). When slopes were found to not be significantly different an Analysis of Covariance (ANCOVA) was carried out on male and female regression lines using the lm function of the base R package (R Development Core Team, 2011) to determine if sexual dimorphism was present.

Characters that did not show sexual dimorphism were used to conduct a principal component analysis (PCA) using the prcomp function of the base R package (R

Development Core Team, 2011). Prior to PCA analyses data were log transformed and

PCA was undertaken with data both uncorrected and with non-meristic traits corrected for body size (Lleonardt 2000), taking the first principal component (PC) of the uncorrected analysis as a measure for body size (Marroig and Cheverud 2009).

Using significant PC axes from both PCA analyses, we undertook both model based and hierarchical clustering on each of the two datasets (i.e., corrected or uncorrected for body size). This was due to model based clustering providing an estimate of the most likely number of clusters, and hierarchical clustering being able to provide 147 support values via bootstrapping. For Gaussian model-based clustering we used the mclust function in R package Mclust (Fraley & Rafterty, 2006). Mclust implements a

Poisson process to handle noisy data, for which an initial noise estimate was obtained using a nearest-neighbor method implemented by the nnclean function in the R package prabclus (Hennig & Hausdorf, 2010). For hierarchical clustering we used the pvclust function in the R package pvclust (Suzuki & Shimodaira 2006) using Euclidean distance and the Ward clustering method (Ward 1963) with 100 000 bootstrap replicates. To determine which morphological characters were most important in the clustering analysis, a discriminant function analysis (DFA) and an ANCOVA were carried out using the clustering of individuals as the independent variable and the morphological measurements as the dependent variables using the R package MASS (Venables &

Ripley, 2002). For the ANCOVA, SVL was used as the covariate, except in the case of

SVL for which HL was used. In addition, we constructed classification trees to determine the most influential parameters in individual assignment to clusters for both corrected and uncorrected datasets using the cltree function in the R package tree (Ripley, 2010).

Homogeneity was measured using the generalised Gini index (Therneau & Atkinson,

2002 – equation 3) to ensure that the precautionary principle applied and that the omission errors are fewer than the commission errors where possible. The recursive partitioning model was run with cross-validation to provide for better accuracy assessments and therefore better final model fit.

To gain some insight into whether the observed morphological differentiation has an ecological basis, an analysis of environmental variables for all of the animals used in the morphological and microsatellite analyses (Appendix 1) was undertaken. ArcGIS v10 148 was used to extract values from the 19 climatic variables available through Worldclim

(http://www.worldclim.org/), a 90m Digital Elevation Model available through Diva-GIS

(http://srtm.csi.cgiar.org/), categorical surface geology and categorical vegetation type

(Geoscience Australia) for each specimen using the Multiple Values to Points tool.

Bioclimatic variables and elevation were standardized (by subtracting the mean and dividing by the standard deviation) and reduced to PC scores using the methods described above. The first two principal components were taken as a measure of climatic conditions in order to avoid autocorrelation between individual climatic variables. As environmental variables included categorical variables, pvclust cannot be applied due to permutations being conducted by re-estimation of the distance matrix. As an alternative method, the daisy function of the R package cluster (Machler et al., 2005) was used to produce a dissimilarity matrix of environmental data using Gower’s coefficient (Gower, 1971).

Hierarchical clustering of the environmental dissimilarity matrix was implemented using the Ward method using the hclust function of the R package cluster (Machler et al., 2005)

– as this is the method implemented by pvclust – meaning the methods are comparable aside from the use of bootstrapping. Classification tree construction was carried out using the methods described above.

To evaluate the relationship between morphological and environmental variables full and partial distance-based redundancy analyses (dbRDA) were undertaken. Distance- based redundancy analysis is a multivariate method that allows testing of the influence of environmental factors on values in a linearly dependent dissimilarity matrix (in this case, morphological distance) via permutation testing (Legendre & Anderson, 1999; McArdle

& Anderson, 2001). Partial dbRDA allows for the fitting of covariates to take into 149 account the potential confounding effects of these values. In this case, both genetic distance and geographical co-ordinates have been fitted in order to account for the influence of genetic structure and isolation by distance on the relationship between environment and morphology in partial dbRDA analyses. Geographic distance matrices were calculated from individual latitude and longitude data using the earth.dist function of the Fossil package (Vavrek, 2010). Values were standardized using logarithmic transformation and converted to a continuous rectangular dataset using principal coordinates analysis via the npcm function of the Vegan package (Oksanen et al., 2010) for further analyses. A genetic distance matrix of Fst scores was calculated from the 6 microsatellite loci using Genepop 4.0 (Rousset, 2008) Missing values were imputed using the mean Fst value. The influence of each environmental variable (climate PC1, climate

PC2, elevation, rock type, vegetation type) on the morphological distance matrix was also tested. All dbRDA analyses were conducted using the ‘capscale’ function of the R package vegan (Oksanen et al., 2011). The significance of dbRDA analyses was assessed using multivariate F statistics with 9999 permutations in the ANOVA function of the base package included in the R statistical Package (R core development team, 2011).

Results

Karyotyping

The diploid number of the two LP specimens karyotyped was 2n=44 and chromosome morphology was indistinguishable from that of G. lazelli (Sistrom et al.,

2009). As such, LP is not chromosomally differentiated from G. lazelli.

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Mitochondrial phylogenetic analyses

Results from both Bayesian and ML phylogenetic methods of the ND2 sequences were congruent. Figure 4 shows the ML phylogram, with asterisks marking nodes with high support from both phylogenetic methods (ML bootstrap values >70 and Bayesian posterior probability >0.95). The analysis confirmed that LP specimens are polyphyletic within two major G. lazelli clades (D and E in Fig 4). These two clades are distributed broadly throughout the Flinders Ranges and east into western NSW. The southern and western extent of the G. lazelli distribution falls into 3 other distinct clades (A, B and C), which are basal relative to clade D and E. Clades D and E are well supported as distinct however the branching order of these clades is poorly resolved by phylogenetic analysis of the mtDNA. 151

Figure 4: Phylogenetic ML of preliminary mtDNA screen of LP specimens Stars represent nodes highly supported by both ML bootstrap support (>70) and Bayesian posterior probability (>95%). Numbers refer to collection locations (Fig. 2, Appendix 1) and letters designate major clades referred to in the text. Samples labeled ‘LP” refer to LP specimens. 152

Morphological Analyses

A basic overview of morphology is displayed in Figure 3. LP specimens show a significantly larger and more robust body size in comparison with G. lazelli and sympatric G. variegata, which are similar in body shape and size in comparison. All three species show considerable intraspecific variation in back pattern, however fixed differences in color pattern and meristic measurements between G. variegata and G. lazelli are documented in Sistrom et al. (2009). The average SVL of pre-designated LP specimens based on geographic location and general body size and shape was 62.7mm

4.83mm. In comparison, the average SVL of G. lazelli samples used in this study was

47.8mm 5.53mm (Fig. 2). Less than half of the specimens had intact original tails and as such, TL was excluded from further analysis. Sexual dimorphism was detected in HW and FEL measurements, as a result these were also removed from further analyses.

For the PCA analyses on data not corrected for body size, the first and second

Principal Components (PC) accounted for 69% and 10.0% of the variance respectively, while each of the remaining components explained less than 5% of the variance.

Hierarchical and model-based clustering both yielded identical individual assignments.

As hierarchical clustering provides approximate unbiased bootstrap values as a measure of statistical support for clusters, the results of this analysis is presented (Fig. 5). Model- based clustering yielded two well-supported clusters, with cluster one comprising solely

LP individuals and cluster two comprising a mixture of LP (18% of individuals) and G. lazelli. Both DFA and ANCOVA indicated a high level of influence due to HL, ES and

SVL, which are measurements that would logically be associated with body size (Table

2). Results of the classification tree analysis showed the most accurate number of groups 153 to be two and SVL to be the most important clustering element, with the misclassification error at 0.01 (Fig. 5). These results suggest that two size classes of individuals occur in the data set corresponding to distinct, but not mutually exclusive groups associated with

LP and G. lazelli.

When PCA was carried out on morphological data corrected for body size, the first four PCs accounted for 32.2%, 18.1%, 14.4% and 5.5% of the variance respectively

(Fig. 5). Hierarchical and model-based clustering both produced comparable results.

Model-based clustering of the size corrected data yielded four well-supported clusters, one of which contained all of the LP individuals. In the hierarchical clustering R20377, a sample collected in 1979, was an outlier to allmajor clusters. In addition, two G. lazelli specimens, R52982 and R51801, fell into the LP cluster. Results of the standardized corrected cluster DFA and ANCOVA (Table 2) indicated a high level of influence due to five measurements associated with head shape (mental and rostral scale shape, IO,IN,

EE). Results of the classification tree analysis suggest that the most accurate number of groups is four, and that SVL and CS are the most important clustering elements, with a misclassification error of 0.08 (Fig. 5). As all of these metrics are associated with variation in head shape, these analyses indicate head shape significantly differentiates the

LP cluster.

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Table 2: Summary of morphological analysis. The first set of data represent the analysis of data uncorrected for body size and the second set represent results from the analysis of data corrected for size using equation 13 from Lleonardt (2000), taking the first PC1 of

PCA analysis on uncorrected data as a measurement of body size. Numbered roots are standardized coefficients of significant canonical roots resulting from DFA. F and P values are taken from ANCOVA analysis of variables using SVL as the covariant, except in the case of SVL itself for which HL was used as the covariant.

Uncorrected Corrected Root 1 ANCOVA Root 1 Root 2 Root 3 ANCOVA F P F P Wilk's λ 0.000 0.000 0.000 0.004 Proportion of Trace 100 0.6263 0.2458 0.1279 DF 79 79 79 79 HL -2.923 28.176 0.000 * 1.333 2.117 -1.991 3.122 0.081 HD 0.356 1.364 0.247 -1.113 -0.412 0.031 0.929 0.338 IO -0.186 1.585 0.212 0.547 -1.036 0.565 14.546 0.000 * IN 1.237 0.677 0.413 -0.206 -1.235 1.830 17.832 0.000 * EE 0.260 4.628 0.035 * -0.036 0.651 0.287 5.580 0.021 * ED -0.086 3.237 0.076 -0.357 -0.554 0.111 2.882 0.093 ES -1.877 23.213 0.000 * 0.746 -0.323 -2.072 3.268 0.075 FBL 0.726 3.856 0.053 -0.699 0.045 -0.043 0.397 0.531 AGL 0.817 1.340 0.251 -0.630 -1.740 0.271 2.468 0.120 SVL 2.045 8.204 0.005 * -3.043 0.062 1.956 12.702 0.001 * HU -0.501 0.563 0.456 0.359 -0.057 -1.218 0.004 0.950 FL -0.427 13.938 0.000 * 0.198 -1.184 0.201 0.778 0.381 HI 0.013 2.308 0.133 -0.804 0.410 -0.470 0.484 0.489 ML 0.341 1.056 0.307 -0.329 -0.224 0.444 6.310 0.014 * MW 0.261 0.020 0.889 0.019 -0.883 0.901 26.057 0.000 * RW 0.137 1.959 0.166 0.794 -0.130 0.529 13.796 0.000 * RH -0.224 2.976 0.089 1.536 0.253 -0.254 13.837 0.000 * SL 0.083 0.733 0.394 -0.508 1.154 -0.651 0.264 0.609 UL -0.035 0.052 0.820 0.901 -0.927 -0.485 1.479 0.228 CS -0.226 7.493 0.008 * 0.669 1.824 0.429 2.047 0.157 LL 0.206 0.847 0.360 0.621 0.973 -0.370 0.360 0.550

155

Figure 5: Dendrograms produced by hierarchical clustering of Euclidean distances from

PCA scores of the morphometric data on specimens A) not corrected for size, and B) corrected for body size. Asterisks indicate nodes with high approximate unbiased bootstrap support (>70). Grey highlighting designates LP specimens, with G. lazelli individuals un-highlighted. The height scale represents within-dataset Euclidean distance.

Notations are the results of classification tree analysis which looks for the parameter in 156 the dataset which groups individuals into the designated clusters most accurately, SVL – snout-vent length, CS – chin shield scale count, measurements are based on corrected and scaled values.

Genetic clustering

Microsatellite loci were free of deviation from HWE due to stuttering, null alleles and large allele dropout, however a heterozygote deficiency was detected in all loci when

G. lazelli and LP specimens were combined (see Table 1). When samples were separated into two groups based on morphological assignment to group (uncorrected analysis), four of the six loci in the LP group conformed with HWE, but all loci in G. lazelli group significantly departed from HWE. This result could be caused by several genetic populations represented within G. lazelli (i.e., a Wahlund effect) however genetic structure within LP and G. lazelli warrants further investigation. The STRUCTURE analysis indicated that a single cluster (Δk=1) had the highest likelihood. In order to show the lack of genetic structure corresponding to morphology, STRUCTURE results from the K=2 analysis are visualized in Figure 6.

Figure 6: Structure output when results for K=2 are visualized. Numbers represent specimens of G. lazelli characteristic morphology (1) and LP (2). No structure 157 corresponding with morphology is evident from the analysis.

The relationship between ecology and morphology

In the PCA analysis of the environmental data, the first two PC scores accounted for 53.4% and 32.0% of the variance respectively. Clustering of individuals based on ecological data (Fig. 7) yielded four major clusters. LP specimens fell into two of the four clusters, with 17 individuals from nine locations in one cluster (along with four G. lazelli individuals from 3 locations) and five from two locations in a second cluster (along with

14 G. lazelli individuals from 4 locations). Results of DFA and ANCOVA carried out using environmental data (Table 3) show a high level of influence due to climate PC1, elevation and geology. The classification tree analysis showed the most accurate number of groups to be four with geology, elevation and vegetation type to be the most important clustering elements, and a misclassification error of 0.05 (Fig. 7). In contrast, classification tree analysis using assignment to cluster, based on corrected morphological data as the response variable and environmental dissimilarity as the predictor, found that vegetation type and geology were the most important clustering elements. This contradicted an anecdotal field observation that rock type might be an important factor, however the misclassification rate was relatively high (0.28). The results of dbRDA analysis showed a significant correlation between morphological distance and climate

PC1 – dominated by a mix of precipitation and temperature variables (results not shown), elevation, rock type and vegetation type, which remained significant when genetic and geographic distance were used as covariates (Table 4). This result strongly supports a correlation between morphological distance and environmental variables. 158

Table 3: Summary of the environmental analysis. The numbered roots are standardized coefficients of significant canonical roots resulting from DFA. F and P values are taken from ANCOVA analysis of variables using climate PC2 as the covariate, except in the case of climate PC2 itself for which climate PC1 was used as the covariate.

Root 1 Root 2 Root 3 ANCOVA Proportion of Trace 0.7363 0.1659 0.0978 F P P 0.000* 0.001* 0.02* DF 79 79 79 Climate PC1 -0.888983321 -1.254541176 0.203014541 19.97 0.000* Climate PC2 -0.26919125 0.848787353 0.463819838 0.92 0.34 Elevation 0.066624143 1.182484706 -1.761558243 8.23 0.006* Geology 1.673184893 -0.303018824 0.41957223 490.22 0.000* Vegetation -0.54852125 -0.428909118 0.647961419 0.89 0.35

Table 4: Summary of dbRDA analysis, testing for correlation between environmental measurements and morphological distance. F and corresponding P values are presented for each environmental variable when no covariate is used, when a genetic distance matrix based on Fst is used and when a geographic distance matrix based on longitudinal and latitudinal co-ordinates is used. 19 bioclim variables were used but condensed to two principle components to avoid autocorrelation. A significant correlation between morphology and Climate PC1, elevation, rock type and vegetation type was found, which was not affected by correction for genetic or geographic distance.

No co-variate Genetic distance Geographic distance F P F P F P Climate PC1 18.92 >0.0001** 19.22 >0.0001** 16.52 >0.0001** Climate PC2 1.35 0.24 1.22 0.279 0.14 0.852 Elevation 8.91 0.001** 8.68 0.002** 4.28 0.031* Rock type 4.71 >0.0001** 4.63 >0.0001** 3.74 >0.0001** Vegetation type 2.96 0.004** 3.05 0.003** 3.69 0.001**

159

Figure 7: Dendrogram produced by hierarchical clustering of Euclidean distances from

PCA scores of the environmental data. Grey highlighting designates LP specimens, with un-highlighted samples being G. lazelli samples. The height scale represents within- dataset Euclidean distance. Notations are the results of classification tree analysis which looks for the parameter in the dataset which groups individuals into the designated clusters most accurately, elev – elevation, lith – rock type (a – igneous felsic intrusive, f – feldspar, g – argillaceous detrital sediment, j – sedimentary carbonate, k – sedimentary siliciclastic, m – metamorphic, x - regolith), veg – vegetation type (a - Casurina, b –

Eucalyptus, c – Chenopodiaceae, d – Melaleuca, f – Acacia and x – other).

Discussion

Gehyra lazelli and the LP are significantly morphologically divergent with both body size and head shape being important distinguishing characteristics. The two morphotypes also utilize different environments, with climate, elevation, vegetation and geology all playing a role in distinguishing their habitats irrespective of geographic or 160 genetic distance. Under the assumption that the morphological variation has a genetic basis, the morphological features together with the evidence that a new distinct habitat has been selected collectively would have uncontroversially resulted in the description of

LP as a separate species. In stark contrast, the mitochondrial and nuclear markers did not show any evidence of population divergence. This result is complemented by the lack of chromosomal differentiation between the two groups. In particular, the polyphyly of LP and G. lazelli mtDNA sequences is striking as LP sequences are distributed broadly within the two major clades (D and E) that are found only in the arid zone. This finding implies that the relationship between the two morphotypes is characterized by either widespread admixture, the retention of ancestral polymorphism over a considerable period of time, or a very recent adaptive shift in body size associated with the occupation of differential habitats.

Morphological and ecological, but not genetic disjunction between LP and G. lazelli

The presence of the distinct LP morphotype provides prima facie evidence for the presence of evolutionarily distinct lineages potentially representing two distinct species, as variation in phenotypes can often represent the first step in adaptive speciation (Herrel et al., 2001). Morphological evidence supports the differentiation of the two groups based on phenotype, as does evidence provided by an analysis of the broad environmental conditions occupied by the morphotypes. A strong, positive correlation between morphotype and climate, elevation, vegetation and rock type is indicative of an adaptive basis to the differentiation and is a good indicator that the two morphotypes represent distinct species, as is the case for many examples of adaptive divergence in lizards

(Herrel et al., 2008), fishes (Nagel & Schluter, 1998; Langerhans et al., 2003) and birds 161

(McCormack & Smith, 2008). However, the conflicting evidence provided by mtDNA, microsatellite and chromosomal data indicates that this explanation is not as straightforward as might be expected. Differential morphotypes within a species are common, however, this is not a condition known from Gehyra, which is a genus characterized by low morphological variation within and between species, particularly in body shape and size (King, 1984).

Mechanisms resulting in differential body size

Both body size (Camargo et al., 2010; Higham & Russell, 2010; Hibbitts et al.,

2005) and head shape (Thorpe and Baez 1987, Vanhoonydonck and van Damme 1999,

Daza et al. 2009), which are the main phenotypic traits that differentiate LP from G. lazelli, have been characterized as adaptive morphological traits in lizards, including geckos. This suggests that the divergence between the LP and G. lazelli is adaptive in nature, which is supported by the significant differences in the habitats utilized by each morphotype (Fig. 6). Theory suggests that adaptively divergent populations would be able to exploit differentiated ecological niches and thus exist in sympatry (Schluter,

2000). Such fine scale partitioning based on body size and locomotive performance has been observed in Anolis lizards (Carlsbeek & Smith, 2006), benthic and limnetic partitioning of large and small stickleback fish species (Nagel & Schluter, 1998) and divergence of body size generated due to the availability of cover from predators in cichlid fishes (Takahashi e.t al, 2009).The parapatric distribution of the two groups indicates that if adaptation is the cause of the morphological divergence, the ecological niches are geographically disjunct. Even though lithology is not identified as a major factor separating LP from G. lazelli in the classification tree analysis, it is notable that LP 162 specimens obligatorily occur on the Terrapinna granite unit, unique to the upper region of the Flinders Ranges (Neuman, 2001) and no G. lazelli samples have been found on this granite unit. Field observation suggests that this rock unit is characterized by very large, continuous rock faces with sparse, but deep fissures which act as refuges for the geckos.

This contrasts with the surrounding rocks, which are far more fissile and provide a habitat with far more refugia and fewer open faces where extensive searching failed to yield LP specimens. This distinct geology has implications for many ecological parameters such as thermoregulatory parameters, surrounding soil type, prey availability and predation pressure and may have resulted in divergent selection for body size. Also, examination of rates of tail loss in LP specimens (70% of observed specimens) and G. lazelli (40.4% of observed specimens) provides a preliminary indication that predation or aggressive within species interactions may be higher in LP specimens, however a more thorough investigation beyond the scope of the current study would be required to make more than a speculative suggestion regarding predation rates.

Evolutionary explanations for the maintenance of body size differentiation

The lack of correspondence between morphotype and genetic structure suggests a scenario in which divergent phenotypes representing allopatric divergence and secondary introgression is unlikely. Under an allopatric scenario, divergence in microsatellite loci would be expected, and given the prevalence of differentiating chromosomal states in closely related Gehyra species (King, 1979; 1983; Moritz, 1986; 1987) a difference in karyotype might additionally be expected. The fact that morphotypes are distributed in adjacent but differentiated environmental conditions provides strong evidence that the 163 nature of morphological divergence is adaptive. Further, considering the lack of support for an allopatric model of divergence, divergence has likely been ecologically driven in sympatry. While the loci used in this study have the ability to detect recent divergence in most scenarios, in some cases of very recent divergence they have not (e.g. Elmer et al.,

2010) and would not be expected to under a “genomic islands of speciation” model of divergence where differentiation only occurs in genes undergoing selection (Turner et al.,

2008). Lack of differentiation in the genetic data means it is not possible to distinguish between incipient speciation with recent adaptive divergence and phenotypic plasticity within a single species. Some species do show sympatric, intra-specific dimorphism of body size in relation to predation (Takahashi et al., 2009) and sexual strategy (Smith &

Roberts, 2003; Stuart-Smith et al., 2007), however in most cases of size dimorphism related to sexual strategy there is a sexual bias to size classes which is not present in this case.

While it is unclear from our data whether or not introgression has occurred between the two groups due to the fact no population differentiation was discerned, the potential for hybridization between them exists. The maintenance of differential morphotypes through reduced hybrid fitness (Rice & Pfennig, 2010) could act to reinforce an already established morphological divergence. Conversely, introgression has the potential to be facilitating the reproductive absorption of the LP morphotype and thus it may disappear through the process of hybridization (Rhymer & Simberloff, 1996). As the role of interbreeding between the two morphotypes could be having significant opposite effects on the process of continued differentiation, this is an interesting and significant facet of this system to be further explored. 164

Acknowledgements

This work was funded by ABRS grant 207-43 awarded to M. Hutchinson and S.

Donnellan. The authors thank the Sheehan and Sprigg families for access to private property for the collection of material and Hailey Lainer, Kate Sanders and Paul Oliver for reviewing and greatly improving the manuscript. Specimens collected in the field were collected under South Australian Dept. of Environment and Natural Resources

Permit #C25661-1 and ethics permit #41-2008. 165

General Discussion

As this thesis is presented as a series of papers, each with its own discussion of specific findings, the general discussion addresses the broader impacts of my work with respect to the overall aims of my thesis, and highlight the likely directions of future evolutionary and systematic studies on Australian Gehyra.

Summary of Aims

My thesis aimed to examine species diversity and patterns of speciation in Australian

Gehyra. In particular it aimed to: 1) Explore the adequacy of current taxonomy in accounting for species diversity in the group and improve it where necessary. 2)

Evaluate previously proposed evolutionary scenarios for the diversification of

Australian Gehyra and propose a comprehensive evolutionary history of the group. 3)

Examine possible processes of speciation in Australian Gehyra.

The taxonomic status of Australian Gehyra and species delimitation.

Chapters 1 and 2 confirm the findings of past researchers (King 1979; 1982a; 1984;

Moritz 1984; 1986) in that the underlying genetic diversity of the Australian Gehyra radiation is not accounted for by the current taxonomy and as such the current taxonomy of the group does not adequately characterize the diversity of the group.

My research has begun to address this by formally describing the long known to be distinct 2n=44 chromosomal race of G variegata (Chapter 1) and the re-description of

G. barea (Appendix 2). In addition I have undertaken a thorough, integrative analysis of the genetic, geographic and morphological diversity of central Australian Gehyra 166

(Chapter 2). My study revealed that patterns of morphological, genetic and geographic distribution are complex and in many cases, conflicting - presenting significant and ongoing challenges to delimiting and describing species. Despite these challenges, my study presents information allowing for a considerably better understanding of the morphological variation and geographical distribution of currently recognized species and identifies five additional putative species and presents evidence for the distinction of their respective evolutionary histories under the general lineage concept (De Quieroz 2007).

As such, my thesis has considerably increased the taxonomic understanding of southern Australian Gehyra, both by increasing the taxonomic resolution of the group and by highlighting the significant and ongoing challenges in describing the group given the conflicting nature of delimiting characters in the group.

Species Relationships within Australian Gehyra

The relationships among Australian Gehyra species have been inferred by past researchers (King 1979; 1984) despite significant data and methodological restrictions

(Mortiz 1992, Sites & Moritz 1987). Significant advances in data acquisition and methodology allowed me to revisit the evolutionary history of Gehyra both to test existing hypotheses and with a much larger level of confidence, infer the evolutionary history and species relationships within Australian Gehyra. In chapter 3 I conducted a multi-locus species tree estimation using external fossil calibrations in order to both test previous theories regarding the species relationships and evolutionary history of 167 the group and in light of the newly available evidence, suggest likely scenarios for the diversification of the group.

As such, we were able to confirm a relatively recent Asian origin for the group, coinciding with the collision of the Australian and Java-Ontong tectonic plates and monophyly of Australian Gehyra in relation to Asian and Melanesian species indicates a single colonization event. Reciprocal monophyly of the previously identified G. australis (Mitchell 1965, King 1979) and G. variegata (Mitchell 1965,

King 1982) groups indicates that these represent morphologically and ecologically distinct species complexes are distinct evolutionary lineages rather than the product of adaptive convergent evolution, and diversification of both complexes has been ongoing since their divergence occurred in the late Miocene.

Further to this, by applying karyotypic data to the phylogenetic framework I have developed, I am unable to support previously suggested scenarios of speciation driven by chromosomal rearrangement in allopatry (King 1979, King 1984) and suggest that while in some cases chromosomal rearrangement may be a factor in the maintenance of species boundaries once acquired, they represent secondary characters of divergence.

Modes of Speciation in Australian Gehyra

Further to the rejection of models of chromosomal speciation driving diversification of the group, the complex geographic patterns of variously overlapping and allopatric 168 genetic and morphological diversity revealed in chapter 2 indicate that equally complex and diverse modes of diversification are involved in the speciation of

Australian Gehyra. In particular, this is the case for G. variegata complex in the

Central Ranges region.

The complex and contrasting patterns of morphological divergence and crypsis in both sympatric and allopatric lineages suggest that both ecologically driven adaptive speciation and allopatric speciation due to vicariance are likely to play roles in the diversification of the group.

In chapter 4, I investigated a particular case study of morphological and ecological divergence between adjacent populations of Gehyra in the northern Flinders Ranges, which contrasts with an observed lack of genetic divergence. We characterized the morphological and ecological divergence between G. lazelli and a large bodied population only found at the northernmost extremity of its range – which displayed a morphology similar to the tropically adapted G. australis species complex. A lack of any detectable genetic differentiation between G. lazelli and the large bodied population in mtDNA and microsatellite markers indicates that the large bodied population represents either environmentally driven morphological plasticity in G. lazelli or an extremely recently evolved species – characterizing potential importance of ecologically driven adaptive speciation in the diversification of the Australian

Gehyra.

As such, the modes of speciation that have resulted in the diversification of Gehyra in

Australia are likely to be complex and challenging to elucidate, but the complexity, 169 apparent diversity and recentness of speciation events evident in the group indicate that such studies could be exceptionally useful in furthering broader studies of the process of speciation.

Limitations

Unexpected levels of complexity

Whilst it was expected and indeed one of the premises for undertaking the study, the level of diversity and complexity uncovered by initial phylogenetic screening was considerably higher than expected. Screening of the areas such as the Central Ranges and Kimberley Plateau revealed that the current taxonomy accounted for less than half of the potential species diversity of these regions. In concert with the unexpectedly high diversity, an assessment of museum samples revealed extremely high rates of misidentification – up to 50% of specimens were discovered not to be representative of the species assigned to them in some cases; a situation was ubiquitous across institutions and collectors. This issue had a number of effects on the study that were not foreseen until it had begun, the first of which was that the identity of tissue samples without corresponding voucher specimens were of limited value due to the low reliability of their identifications. The second was the realized importance of having typotypic material to assess the status of currently named species, which involved additional field collection and sequencing effort. Finally, the level of sampling to establish a basic understanding of the diversity of the group was more extensive than expected.

As such, it became apparent that the scope of the project in terms of budget and time 170 was not sufficient to comprehensively evaluate the diversity of the entire complex, as such my delimitation studies were scaled back to only evaluate the Central Ranges and south-eastern Australia. I have identified the Kimberley and the Pilbara regions as areas in which diversity is in need of further evaluation.

Sampling

Despite extensive sampling of Gehyra across Australia, sampling in the remote northern regions of the continent – notably mainland areas of the Kimberley, northern deserts, Arnhem Land and Cape York is too poor for any reliable assessment of

Gehyra diversity in these regions, especially in light of the unexpected diversity of the group and broader patterns of increased biodiversity in these regions (Moritz et al. unpublished data). Clearly, extensive collection of vouchers and matching tissue samples is required across much of northern Australia for an adequate continent-wide assessment of Gehyra diversity.

Marker Acquisition

The acquisition of nuclear markers is a long-standing difficulty in undertaking multi- locus studies of non-model organisms (Thomson et al. 2010). However emergent next generation sequencing technologies are providing the technological basis for financially and temporally feasible acquisition of larger numbers of nuclear markers than ever before (Thomson et al. 2010). I undertook two novel methods of nuclear marker development. In the first, I aligned cDNAs from Gekko japonicus available on

Genbank with orthologues from the Anolis genome in an attempt to identify exon 171 bound introns with which to develop exon primed, intron crossing (EPIC) loci.

Unfortunately the evolutionary distance between the marker source (Gekko japonicus) the reference (Anolis) and the target (Gehyra) was great enough that this method only developed a small number of loci and despite significant effort, only one of these – a

H3 Histone intron reliably amplified across Gehyra. For the second method, I used

GS-FLX 454 genomic shotgun sequences, BLASTed against themselves and

GenBank nucleotide sequences to identify putative non-coding markers. This generated over 5500 potential loci, but due to financial and time constraints I only tested 11 primer pairs, which yielded two reliably amplifying, highly variable loci.

If I had of undertaken the second method of marker discovery in place of the first, it would have been likely that my suite of useful nuclear loci would have been considerably larger and obtained in a more cost effective manner. As the availability of next generation sequencing with increasing depth and coverage increases and the cost decreases, similar methods are likely to become more effective in the future.

Broader impacts of study

Biodiversity

My work includes the description of four novel species, three potential species worthy of further investigation and considerably clarifies the diversity represented by existing species names. As a result, this work adds significantly to the knowledge of Australian biodiversity, particularly in south eastern Australia and the central arid zone.

Knowledge of basic biodiversity is a fundamental and key to a large variety of downstream scientific studies, general knowledge and conservation policy formation 172 and thus has wide ranging impacts. The identification of new species and areas worthy of further investigation in Gehyra assist in the identification of both biogeographic regions and taxonomic groups for which this basic data is lacking and thus allows for more informed decisions on where to direct future efforts for understanding Australian biodiversity. Finally, my work highlights the need for considerable additional sampling across northern Australia. The high level of misidentification I discovered during my studies shows that our basic knowledge of this group is not at a level where definitive field identification is possible and thus resolving taxonomic and biodiversity issues will require additional specimen collection.

Contrast to other Australian radiations

Many well-known and well-studied Australian organismal groups have Gondwanan origins and as such, are relatively ancient, e.g marsupials (Beck 2008), diplodactyline geckos (Oliver & Sanders 2008), crayfish (Toon et al. 2010), casuarinas (Crisp et al.

2004), which contrast with more recently arrived lineages originating in Asia, e.g. agamids (Hugall & Lee 2004), skinks (Skinner et al. 2011), rodents (Rowe et al.

2008), chenopod shrubs (Crisp et al. 2004). My studies show that Gehyra represent an ideal comparative group for evolutionary and biogeographic studies. Chapter 4 represents a comprehensive species tree reconstruction characterizing the evolutionary history of the Australian Gehyra providing enough information for the group to significantly add to comparative studies of biogeography which contrasts Gondwanan radiations such as the diplodactyline geckos (Oliver & Sanders 2008) and can be compared with other recent Asian colonizers such as the agamids (Hugall & Lee 173

2004) and skinks (Skinner et. al. 2011) in terms of speciation rates, modes and causes.

In addition, my studies show Gehyra to be a promising group for speciation studies, particularly in relation to arid zone radiations, with the likelihood that a variety of speciation drivers have influenced the diversification of the group as evidenced by the role of ecological divergence shown in Chapter 5.

Conservation

My studies have a number of implications regarding conservation research and policy.

The first and most significant is the confirmation or discovery of a number of species displaying restricted ranges. The first is G. minuta, which the comprehensive screening in Chapter 3 confirms as restricted to rocky ranges near Tennant Creek. The newly discovered G. moritzi and G. pulingka represent species restricted to the

MacDonnell Ranges and the Central Ranges respectively and thus previously unknown units of diversity to consider in future conservation assessments. The most startling discovery in terms of short-range endemics within Gehyra is the large-bodied population in the Northern Flinders characterized in Chapter 5. This potential species appears to be restricted to a region of 80km x 20km which is currently being considered for rezoning with respect to mining activity (PIRSA 2009). As a result, this potential species represents an important conservation concern. Finally, G. variegata, previously considered to be a single species with a continent wide distribution has been shown to be two species – G. variegata and the newly discovered G. versicolor with large but much smaller than previously thought ranges, and thus represent distinct entities regarding conservation. 174

Future directions

Taxonomic Resolution

My work has provided a comprehensive framework by which the geographic distribution and genetic and geographic diversity of all currently described species is characterized and thus it allows for the rapid identification and characterization of putative new taxa. Preliminary genetic screening has shown the Gehyra of the

Kimberley region of northwestern Australia to be complex – with several (10-15) putative undescribed species. In addition past allozyme screening (Adams – unpublished data) and mtDNA phylogeographic studies (Pepper – pers. comm.) have identified significant levels of undescribed diversity in the Pilbara region of Western

Australia complimented by high levels of morphological diversity currently recognized as the G. punctata complex (Doughty – pers. comm.). It seems likely that future taxonomic work should focus on these under-investigated centers of Gehyra diversity. It is of important note however that many regions of northern Australia such as the Arnhem Plateau, Cape York and the northern deserts suffer severely from under-collection of both voucher specimens and tissues critical to the evaluation of taxonomic diversity.

Integrative Species Delimitation

Recent conceptual and methodological developments (De Quieroz 2007, Yang and

Rannala 2010, O’Meara 2010) have allowed for integrative detection of species under the general lineage concept using a diverse array of evidence for the independent 175 evolutionary history of lineages. However, a current gap in methodology exists in that a truly integrative framework for delimiting species is not yet available. Analytical development in species delimitation, particularly for difficult groups like the

Australian Gehyra radiation is needed to step beyond a priori methods of identifying putative species and the assignment of individuals to them in situations where patterns of diversity are conflicting and complex, as trying to interpret these patterns individually will inevitably lead to scientists making errors in both species detection and the assignment of individuals to species. The use of comparative distance matrices in an integrative framework has the potential to do this when used in conjunction with validation methods such as BPP (Yang & Rannala 2010). Complex systems where species are inherently difficult to delimit – such as the Australian

Gehyra radiation present both the motivation to develop these methods and ideal models to test their efficacy.

Speciation Studies

As our ability to recover genetic information rapidly increases in concert with the sophistication of associated analyses, it is becoming more and more feasible to analytically investigate the causes, patterns and processes involved in speciation – which could only previously be speculated about. Approaches such as functional genomic (Butlin 2010; Louis 2011) simulation studies (Barbuti et al. 2009: Thibert-

Plante & Hendry 2008) and ecological speciation studies (Berner et al. 2009; Harmon et al. 2008) are allowing researchers to directly investigate speciation as it happens.

However a second key requirement for studies of speciation are systems in which 176 speciation is currently ongoing. The Gehyra radiation in Australia – in particular the

G. variegata species complex has many elements which make it a useful system in which to study the process of speciation. Characters which make it an appropriate model system include many recent diversification events, which include varying levels of genetic, morphological and geographic differentiation allowing for comprehensive, comparative studies, a large body of museum collection and a very high abundance leading to ease of field collection and observation and a lack of conservation concerns which would limit collection and experimentation. However, the slow rate to sexual maturity and low fecundity (1-2 eggs per clutch (Bustard

1968)) relative to other model systems for speciation studies, e.g. Anolis (Gavrilets &

Losos 2009), sticklebacks (Schluter 2010), make the group unsuitable for laboratory based experimental study in addition to impediments associated with the ongoing taxonomic uncertainty in the group. As such, the Australian Gehyra radiation is unlikely to become a classic model system for the study of speciation, but may be an exceptional system for in situ study of the process of speciation in Australia in response to the onset of aridity and fragmentation of mesic habitats (Byrne et. al.

2008) and future development of the system as an Australian model for speciation processes would compliment and assist in taxonomically resolving the group.

Concluding Remarks

In many aspects this work follows in the footsteps of past researchers – in that it makes significant steps to resolving known issues but in the process creates a substantial body of new questions, however much of the most compelling scientific 177 research generates more questions than answers. While my research highlights the unexpectedly high complexity and diversity of the Australian Gehyra and the significant challenges in delimiting and describing species, we also produce a comprehensive genetic framework that will greatly assist in the rapid identification and characterization of new species in the future. My research has also evaluated species relationships and the evolutionary history of Australian Gehyra, confirming some of the assumptions made by previous researchers but rejecting diversity in the group being driven by chromosomal rearrangement. Speciation in the group has been shown to be complex and multifaceted, worthy of further study. I have evaluated one case of complex divergence in Gehyra, finding that ecological parameters are likely to be involved in phenotypic divergence and highlighting the potential role of ecologically driven speciation in the group. While the Australian Gehyra radiation sorely needs more basic diversity work to be carried out, the rewards from understanding the processes that make elucidating this diversity so challenging offer large advances in our understanding of how the diversification of arid species complexes occurs. 178

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Appendix 1. Details of the specimens and samples used for Chapter 2.

Genus species Map mtDNA karyotype Allozyme ABTC No. Voucher No. Locality Country State declat declong code OTU Cyrtodactylus marmoratus ABTC48075 AMSR126126 Cibodas, Java Indonesia Gehyra australis Y ABTC28970 NTMR21022 Black Point Australia NT -11.15 132.15 Gehyra baliola Y ABTC44765 AMSR122405 Waro PNG SHP Gehyra borroloola Y ABTC11883 SAMAR34183 McArthur River Australia NT -16.66 135.85 Station Gehyra catenata Y ABTC77213 SAMAR55893 30k N Tambo Australia Qld -24.65 146.385 Gehyra dubia Y ABTC76885 SAMAR55583 20k NNE Biloela Australia Qld -24.223 150.64472 Gehyra ipsa Y ABTC28493 Bungle Bungles Australia WA -17.3748 128.3913 Gehyra koira Y ABTC30614 NTMR23804 Wickham River, Australia NT -16.842 130.2361 Gehyra lazelli L1 9 SAMAR38950–58 Tungkillo Australia SA -34.82 139.06 Gehyra lazelli L2 2n=44* 8 ABTC03668- SAMAR33529, Lancoona Station Australia NSW -33.36 145.883 70 R38943–44 Gehyra lazelli L3 Y 10 ABTC18031- SAMAR38984–6 Middleback Range Australia SA -33.183 137.1 2 Gehyra lazelli L4 Y ABTC22091 SAMAR28977 Gawler Ranges Australia SA -32.616 136.35 Gehyra lazelli L5 Y ABTC52434 SAMAR28515 120k NE Minnipa Australia SA -32.33 136.283 Gehyra lazelli L6 Y ABTC88098 SAMAR60608 Bimbowrie Station Australia SA -32.07472 140.3283 Gehyra lazelli L7 Y ABTC88097 SAMAR60620 Bimbowrie Station Australia SA -32.06722 140.3333 Gehyra lazelli L8 Y ABTC88094 SAMAR60602 Bimbowrie Station Australia SA - 140.3161 31.9741666 7 Gehyra lazelli L9 Y ABTC89675 SAMAR61563 11.3k NNW Australia SA -31.9144 132.892 Penong Gehyra lazelli L10 Y ABTC39325 SAMAR52366 4.7k W Parachilna Australia SA -31.1327 138.54916 Hill Gehyra lazelli L11 Y 2n=44 ABTC38861 SAMAR51801 9k SSE Australia SA -30.68972 138.81583 Mudlapena Spring Gehyra lazelli L12 Y 2n=44 ABTC39130 SAMAR52012 4.7k NNE Warden Australia SA -30.4038 139.2352778 Hill Gehyra lazelli L13 Y ABTC74062 SAMAR52962 Arkaroola Australia SA -30.11861 139.4483 Gehyra membranacruralis Y ABTC50301 AMSR135529 near Sibilanga PNG SP Mission Gehyra minuta 2n=42a* 1 ABTC31246, CM1235, 1257, 1280, The Granites Australia NT -20.5722 130.3501 103196, 1383, 1391 103199, 103213-4 Gehyra minuta Y ABTC61706 NTMR13647 80k S Renner Australia NT -18.9469 134.1227 Springs Gehyra montium M1 Y 2n=42a ABTC41961- SAMAR48732-3, 5; Mt Lindsay Australia SA -27.025 129.875 2, 4 SAMAR51537, 203

R51540, R51565, R51574 Gehyra montium M2 Y 2 ABTC103204 CM1321 Cavenagh Range Australia WA -26.1705 127.9697 Gehyra montium M3 2n=42a* 3 CM1260, 1319 1342 Warburton Australia WA -26.1505 126.5474 1357 Gehyra montium M4 2n=42a* CM1264 Winburn Rocks Australia WA -26.05 127.51 Gehyra montium M5 2n=42a* 2 CM1339 1348 Blackstone Range Australia WA -26.0156 128.2728 Gehyra montium M6 2n=42a* 4 CM1322 1345 1340 Mt Samuel Australia WA -25.76 125.93 Gehyra montium M7 2n=42a* 4 CM1337 1343 1349 Notabilis Hill Australia WA -25.65 125.55 Gehyra montium M8 2n=42a* 2 CM1298 Mt Fagan Australia NT -25.0904 129.5677 Gehyra montium M9 2n=42a* 4 CM1299 1303 1380 Giles Australia WA -25.03 128.3 1377 Gehyra montium M10 2n=42a* 2 CM1261 CM1338 Rawlinson Ranges Australia WA -24.8077 127.7846 Gehyra mutilata Y ABTC32321 Dumaguete, Philippines Negros Island Gehyra mutilata Y ABTC13940 Krakatau Indonesia Gehyra nana Y ABTC29669 NTMR21783 Litchfield NP Australia NT -13.1317 130.8052 Gehyra occidentalis Y ABTC13488 SAMAR51105 El Questro Station Australia WA -15.966 127.93 Gehyra oceanica Y ABTC49805 AMSR129847 Normanby Island PNG MBP Gehyra oceanica Y ABTC32281 UMMZ182803 Tanna Island Vanuatu Gehyra pamela Y ABTC72525 NTMR26111 Arnhemland Australia NT -13.383 133.383 Plateau Gehyra pilbara Y ABTC11726 SAMAR34053 40k E Mt Newman Australia WA -23.183 119.98 Gehyra pilbara WAM131748 Hamersley Station Australia WA -22.33 117.86 Gehyra punctata WAM164116 250k NNW Australia WA - 118.9552778 Newman 22.2230555 6 Gehyra purpurascens P1 ABTC52233 SAMAR31984 Yumbarra CP Australia SA - 133.4719444 31.7719444 4 Gehyra purpurascens P2 Y ABTC38217 SAMAR50278 7k SSE Mt Australia SA - 138.286944 Deception 30.7602777 8 Gehyra purpurascens Y ABTC38215 SAMAR50277 7k SSE Mt Australia SA - 138.2869444 Deception 30.7602777 8 Gehyra purpurascens P3 ABTC58138 SAMAR45300 Olympic Dam Australia SA -30.383 136.85 Gehyra purpurascens P4 Y ABTC00579 SAMAR36374 23k NE Etadunna Australia SA -28.583 138.816 Gehyra purpurascens P5 Y ABTC41803 SAMAR46147 25k NW Australia SA -26.4877 129.1736111 Kunytjanu Gehyra purpurascens P6 Y ABTC42153 SAMAR50164 14.4k S Sentinel Australia SA -26.21083 132.4427778 Hill Gehyra purpurascens P7 N 7 CM1254 Old Andado Australia NT -25.384 135.4413 Gehyra purpurascens P8 N 7 CM1372 Giles Australia WA -25.03 128.3 Gehyra purpurascens P9 Y 7 ABTC31290 CM1293, 1305 Ti Tree Australia NT -22.1325 133.4205 204

Gehyra purpurascens N 2n=?? SAMAR51606 ENE Mimili, Australia SA Everard Ranges Gehyra robusta Y ABTC11946 SAMAR34227 7k E Mount Isa Australia Qld -20.716 139.55 Gehyra variegata V1 Y 2n=40a* 5 ABTC03666- SAMAR38941–2/45 Lancoona Station Australia NSW -32.366 145.883 7/71 Gehyra variegata V2 Y ABTC89242 SAMAR61010 Bimbowrie Station Australia SA -32.09805 140.281111 Gehyra variegata V3 Y ABTC06813 No voucher 1.5k W Blinman Australia SA -31.1152 138.6779 Gehyra variegata V4 Y ABTC06817 No voucher Chambers Gorge Australia SA -30.95 139.24 Gehyra variegata V5 Y 2n=40a ABTC38899 SAMAR51832 5.8k SE Australia SA -30.64694 138.8480556 Mudlapena Spring Gehyra variegata V6 6 ABTC14117- SAMAR38934–40 Italowie Gap Australia SA -30.56 139.16 24 Gehyra variegata V7 6 ABTC14112 SAMAR38933 Loch Ness Well Australia SA -30.4597 139.1784 Gehyra variegata V8 Y 2n=40a ABTC38986 SAMAR51912 0.5k NW Australia SA - 139.3505556 Nudlamutana Well 30.3741666 7 Gehyra variegata V9 Y ABTC74186 SAMAR53006 Arkaroola Australia SA -30.333 139.36 Gehyra variegata V10 Y 2n=40a ABTC39071 SAMAR51962 2.8k W Moosha Australia SA -30.3211 138.78611 Bore Gehyra variegata V11 Y 2n=40a ABTC39077 SAMAR51968 1.9k SW Reedy Australia SA -30.26527 138.825 Hole Springs Camp Gehyra variegata V12 Y 2n=40a ABTC39173 SAMAR51781-2 10.4k SW Australia SA -30.225 139.19194 Yudnamutana Bore Gehyra variegata V13 Y 2n=40a ABTC39184 SAMAR51790 2.5k WSW Australia SA -30.174166 139.251 Yudnamutana Bore Gehyra variegata V14 Y 2n=40a ABTC39181 SAMAR51760 1.75k W Australia SA -30.17083 139.257 Yudnamutana Bore Gehyra variegata V15 Y 6 ABTC14870- SAMAR38929–31 Yudnamatana Australia SA -30.166 139.283 1/5 Gehyra variegata V16 Y ABTC74203 SAMAR52943 Arkaroola Australia SA -30.1205 139.39861 Gehyra variegata V17 Y ABTC52478 SAMAR28201 1k S Mt Dutton Australia SA -27.816 135.716 Gehyra variegata V18 ABTC58533 SAMAR48599 12.3k NNW Mt Australia SA -27.3142 130.265 Cheesman Gehyra variegata V19 Y ABTC79922 SAMAR56497 5.6k W Mount Australia SA -27.0575 129.6438 Hoare Gehyra variegata V20 Y 2n=40a ABTC42460 SAMAR51607, 9 26.3k ENE Mimili Australia SA -26.91305 132.95083 Gehyra variegata V21 Y 2n=40a ABTC42449 SAMAR51637 30.3k WNW Australia SA -26.86916 133.0225 Indulkana Gehyra variegata 2n=40a SAMAR51842, 51881 Mt Fitton Australia SA Gehyra xenopus Y ABTC13017 SAMAR53962 10k S Cape Australia WA -14.35 125.583 Voltaire 205

Hemiphylloda typhus ABTC32736 No voucher Suva Fiji ctylus Hemiphylloda typhus ABTC49760 BPBM12995 No location ctylus Lepidodactylu lugubris ABTC32735 No voucher Suva Fiji s Lepidodactylu lugubris ABTC50488 AMSR136386 Honiara, Solomon s Guadalcanal Islands

206

Appendix 2: Details of samples and specimens used in Chapter 3.

ABTC Registration Number Number Genus Species Location State Lat Long mtDNA PRLR H3 Morph ABTC48075 AMSR126126 Cyrtodactylus marmoratus Cibodas forest Indonesia Y Y ABTC28970 NTMR21022 Gehyra australis Black Point NT -11.15 132.15 Y Y Y ABTC44765 AMSR122405 Gehyra baliola Waro PNG Y Y Y ABTC11883 SAMAR34183 Gehyra borroloola McArthur River Station NT -16.67 135.85 Y Y Y ABTC77213 SAMAR55893 Gehyra catenata 30k N Tambo on Alpha-Tambo Road Qld -24.65 146.39 Y Y Y ABTC09994 NMVD67708 Gehyra Clade 1 3.6k W Serpentine Gorge turnoff NT -23.77 132.94 Y Y Y ABTC24050 Gehyra Clade 1 MacDonnell Ranges NT -23.72 132.81 Y Y Y ABTC24069 NTMR15358 Gehyra Clade 1 Lawrence Gorge NT -24.01 133.41 Y Y Y Y ABTC24129 Gehyra Clade 1 MacDonnell Ranges NT -23.72 132.81 Y Y Y ABTC24131 NTMR14356 Gehyra Clade 1 6k SSW Claraville HS NT -23.42 134.73 Y Y Y Y ABTC24132 NTMR15356 Gehyra Clade 1 6k SSW Claraville HS NT -23.42 134.73 Y Y Y Y ABTC29428 NTMR20664 Gehyra Clade 1 Finke Gorge NP NT -24.14 132.81 Y Y Y Y ABTC30293 NTMR18310 Gehyra Clade 1 Palm Valley Gas Well, Finke Gorge NP NT -24.01 132.62 Y Y Y ABTC33882 SAMAR41876 Gehyra Clade 2 15k W Mimili SA -27.02 132.57 Y Y Y Y ABTC33938 SAMAR42069 Gehyra Clade 2 29k SW Illintjitja SA -26.34 130.16 Y Y Y Y ABTC41664 SAMAR44892 Gehyra Clade 2 8k SE Mitchell Knob SA -26.19 131.88 Y Y Y ABTC42130 SAMAR50119 Gehyra Clade 2 0.9k SE Sentinel Hill SA -26.09 132.46 Y Y ABTC42343 SAMAR51536 Gehyra Clade 2 35k ESE Amata SA -26.25 131.48 Y Y Y Y ABTC42344 SAMAR51537 Gehyra Clade 2 35k ESE Amata SA -26.25 131.48 Y Y Y ABTC42363 SAMAR51574 Gehyra Clade 2 36.5k ESE Amata SA -26.26 131.49 Y Y Y Y ABTC42403 SAMAR51540 Gehyra Clade 2 35k ESE Amata SA -26.25 131.48 Y Y Y Y ABTC52483 SAMAR28265 Gehyra Clade 2 Kulgera NT -25.83 133.30 Y Y Y Y ABTC58313 SAMAR46009 Gehyra Clade 2 Hunt Peninsula Lake Eyre North SA -28.94 137.40 Y ABTC73410 SAMAR54751 Gehyra Clade 2 Mt Howe SA -26.26 133.44 Y Y Y Y ABTC91737 WAMR166311 Gehyra Clade 2 Morgan Range WA -25.94 128.39 Y Y ABTC105541 WAMR108849 Gehyra Clade 3 Cherralta Homestead WA -21.03 116.82 Y Y Y ABTC105565 WAMR117060 Gehyra Clade 3 Ashburton Valley WA -23.50 117.50 Y Y Y ABTC105571 WAMR119017 Gehyra Clade 3 Sandstone WA -28.00 120.50 Y Y Y ABTC105572 WAMR119018 Gehyra Clade 3 Yuinmery WA -28.52 119.02 Y Y ABTC105580 WAMR126067 Gehyra Clade 3 Mount Magnet WA -28.00 117.83 Y Y Y ABTC105583 WAMR127613 Gehyra Clade 3 Laverton WA -28.63 122.32 Y Y Y ABTC105647 WAMR165853 Gehyra Clade 3 Newman WA -23.29 119.30 Y Y ABTC105651 WAMR170800 Gehyra Clade 3 Mount Elvire WA -21.71 116.77 Y Y Y ABTC59760 AMSR123089 Gehyra Clade 3 Yalgoo tip WA -28.34 116.68 Y ABTC59761 AMSR123090 Gehyra Clade 3 Yalgoo tip WA -28.34 116.68 Y Y Y ABTC09031 SAMAR42789 Gehyra Clade 4 Diamantina Station dump Qld -23.75 141.13 Y 207

ABTC09066 SAMAR42821 Gehyra Clade 4 30k SE Springvale Station Qld -23.68 140.90 Y Y Y ABTC11968 SAMAR34248 Gehyra Clade 4 7k E Mount Isa Qld -20.72 139.72 Y Y Y ABTC29508 NTMR21325 Gehyra Clade 4 Musselbrook Reservoir Qld -18.29 138.48 Y Y 13.4k NNE Hughenden on Kennedy ABTC77005 SAMAR55694 Gehyra Clade 4 Developmental Road Qld -20.79 144.31 Y Y Y 35k S Julia Creek on Julia Creek-Kynuna ABTC77065 SAMAR55751 Gehyra Clade 4 Road Qld -20.96 141.83 Y Y 35k S Julia Creek on Julia Creek-Kynuna ABTC77066 SAMAR55752 Gehyra Clade 4 Road Qld -20.96 141.83 Y Y ABTC77068 SAMAR55749 Gehyra Clade 4 37k SSE Julia Creek Qld -20.98 141.89 Y Y ABTC03666 SAMAR38941 Gehyra Clade 5 Lancoona HS NSW -32.37 145.88 Y Y ABTC03667 SAMAR38942 Gehyra Clade 5 Lancoona HS NSW -32.37 145.88 Y Y ABTC03669 SAMAR33529 Gehyra Clade 5 Lancoona HS NSW -33.37 145.88 Y ABTC03671 SAMAR38945 Gehyra Clade 5 Lancoona HS NSW -32.37 145.88 Y Y Y ABTC03711 SAMAR38946 Gehyra Clade 5 5k E Tooraweenah NSW -31.43 148.92 Y Y ABTC06813 Gehyra Clade 5 1.5k W Blinman SA -31.12 138.71 Y ABTC06816 Gehyra Clade 5 1.5k W Blinman SA -31.12 138.71 Y Y ABTC06817 Gehyra Clade 5 Chambers Gorge SA -30.97 139.22 Y Y Y ABTC06818 Gehyra Clade 5 Chambers Gorge SA -30.97 139.22 Y Y ABTC08930 SAMAR42678 Gehyra Clade 5 138k N Boulia Qld -21.73 139.55 Y Y Y ABTC08954 SAMAR42707 Gehyra Clade 5 Mica Creek, near Mount Isa Qld -20.77 139.48 Y ABTC09204 SAMAR42957 Gehyra Clade 5 Betoota Qld -25.68 140.73 Y ABTC09960 NMVD67573 Gehyra Clade 5 Alice Springs NT -23.69 133.88 Y Y Y ABTC11969 SAMAR34249 Gehyra Clade 5 7k E Mount Isa Qld -20.72 139.72 Y Y Y Y ABTC12603 Gehyra Clade 5 Petermann Creek, George Gill Ranges NT -24.39 131.93 Y Y Y ABTC13998 AMS Gehyra Clade 5 Mootwingee NP NSW -31.24 142.29 Y Y ABTC14006 AMS Gehyra Clade 5 Mootwingee NP NSW -31.24 142.29 Y ABTC14871 SAMAR38930 Gehyra Clade 5 Yudnamatana SA -30.17 139.28 Y Y ABTC14875 SAMAR38931 Gehyra Clade 5 Yudnamatana SA -30.17 139.28 Y Y ABTC15185 SAMAR38954 Gehyra Clade 5 3k E Tungkillo SA -34.82 139.10 Y Y Y ABTC16330 QMJ48538 Gehyra Clade 5 Naccowlah, 36k WNW Jackson Qld -26.49 149.29 Y Y ABTC16331 QMJ48539 Gehyra Clade 5 Naccowlah, 36k WNW Jackson Qld -26.49 149.29 Y Y ABTC22104 SAMAR28954 Gehyra Clade 5 Gawler Ranges SA -32.62 136.22 Y Y ABTC31290 Gehyra Clade 5 Ti Tree NT -22.13 133.42 Y ABTC38215 SAMAR50277 Gehyra Clade 5 7k SSE Mt Deception, Beltana Station SA -30.76 138.29 Y Y Y Y ABTC38217 SAMAR50278 Gehyra Clade 5 7k SSE Mt Deception, Beltana Station SA -30.76 138.29 Y Y Y ABTC38899 SAMAR51832 Gehyra Clade 5 5.8k SE Mudlapena Spring SA -30.65 138.85 Y ABTC38986 SAMAR51912 Gehyra Clade 5 0.5k NW Nudlamutana Well SA -30.37 139.35 Y Y Y ABTC39071 SAMAR51962 Gehyra Clade 5 2.8k W Moosha Bore SA -30.32 138.79 Y Y Y ABTC39077 SAMAR51968 Gehyra Clade 5 1.9k SW Reedy Hole Springs Camp SA -30.27 138.83 Y Y Y ABTC39173 SAMAR51782 Gehyra Clade 5 10.4k SW Yudnamutana Bore SA -30.23 139.19 Y Y Y Y 208

ABTC39181 SAMAR51760 Gehyra Clade 5 1.75k W Yudnamutana Bore SA -30.17 139.26 Y Y Y ABTC39184 SAMAR51790 Gehyra Clade 5 2.5k WSW Yudnamutana Bore SA -30.17 139.25 Y Y Y ABTC39325 SAMAR52366 Gehyra Clade 5 4.7k W Parachilna Hill SA -31.13 138.55 Y Y Y ABTC42449 SAMAR51637 Gehyra Clade 5 30.3k WNW Indulkana SA -26.87 133.02 Y Y Y ABTC51406 AMR129375 Gehyra Clade 5 7k E Mount Isa Qld -20.72 139.55 Y Y Y ABTC52396 SAMAR26185 Gehyra Clade 5 Birdsville Qld -25.90 139.35 Y Y Y Y ABTC52478 SAMAR28201 Gehyra Clade 5 1k S Mt Dutton SA -27.82 135.72 Y ABTC57602 SAMAR42028 Gehyra Clade 5 Lambina Station, E Stuart Highway SA -26.96 130.70 Y Y ABTC59707 AMSR118623 Gehyra Clade 5 Coonbah NSW -32.98 141.62 Y Y Y ABTC59708 AMSR118622 Gehyra Clade 5 Coonbah NSW -32.98 141.62 Y Y 4.5k N Station Creek crossing, Prarie- ABTC72952 SAMAR54530 Gehyra Clade 5 Muttaburra Road Qld -22.04 144.62 Y Y Y 14k NW Longreach on Landsborough ABTC72961 SAMAR54546 Gehyra Clade 5 Highway Qld -23.35 143.20 Y Y Y Y 14k NW Longreach on Landsborough ABTC72962 SAMAR54547 Gehyra Clade 5 Highway Qld -23.35 143.20 Y Y Y ABTC74186 SAMAR53006 Gehyra Clade 5 Arkaroola SA -30.33 139.37 Y ABTC74203 SAMAR52943 Gehyra Clade 5 Arkaroola SA -30.12 139.40 Y 13.4k NNE Hughenden on Kennedy ABTC77006 SAMAR55695 Gehyra Clade 5 Developmental Road Qld -20.79 144.31 Y Y 13.4k NNE Hughenden on Kennedy ABTC77007 SAMAR55696 Gehyra Clade 5 Developmental Road Qld -20.79 144.31 Y Y Y 9k N New South Wales/Queensland border ABTC79486 SAMAR55905 Gehyra Clade 5 on Mitchell Highway Qld -28.96 145.73 Y Y Y ABTC82407 SAMAR55297 Gehyra Clade 5 Phosphate Hill, Mulga Site Qld -21.80 139.91 Y Y ABTC82419 SAMAR55268 Gehyra Clade 5 Phosphate Hill, Snappy Site Qld -21.89 139.99 Y Y Y ABTC76885 SAMAR55583 Gehyra dubia 20k NNE Biloela Qld -24.22 150.64 Y Y Y ABTC28493 Gehyra ipsa Bungle Bungles WA -17.38 128.39 Y Y Y ABTC30614 NTMR23804 Gehyra koira Wickham River, Gregory NP NT -16.84 130.24 Y Y ABTC22091 SAMAR28977 Gehyra lazelli Gawler Ranges SA -32.62 136.35 Y Y Y ABTC52233 SAMAR31984 Gehyra lazelli Yumbarra CP SA -31.77 133.47 Y Y Y ABTC74062 SAMAR52962 Gehyra lazelli Arkaroola SA -30.12 139.45 Y Y Y ABTC50301 AMSR135529 Gehyra membranacruralis near Sibilanga Mission SP Y Y Y ABTC12100 SAMAR38830 Gehyra minuta Hatches Creek Mine NT -20.95 135.22 Y Y Y ABTC61704 NTMR13645 Gehyra minuta 80k S Renner Springs NT -18.95 134.13 Y Y Y ABTC61706 NTMR13647 Gehyra minuta 80k S Renner Springs NT -18.95 134.13 Y Y Y ABTC61707 NTMR13648 Gehyra minuta 80k S Renner Springs NT -18.95 134.13 Y Y ABTC103197 Gehyra montium Brown Range, Warburton WA -26.13 126.57 Y Y Y ABTC103204 Gehyra montium Cavanagh Range WA -26.1705 127.9697 Y Y ABTC103208 Gehyra montium Blackstone Range WA -26.0002 128.1476 Y Y ABTC105323 WAMR131737 Gehyra montium Clutterbuck Hills WA -24.6158 126.2231 Y Y Y 209

ABTC105324 WAMR164289 Gehyra montium Clutterbuck Hills WA -24.5669 126.2544 Y Y Y ABTC105382 WAMR108744 Gehyra montium Gordon Downs Homestead WA -18.6833 128.5833 Y Y ABTC105384 WAMR108948 Gehyra montium Telfer WA -21.8833 122.3667 Y ABTC105545 WAMR111852 Gehyra montium Red Hill WA -23.4908 120.3172 Y Y ABTC105557 WAMR114924 Gehyra montium Nullagine WA -21.6500 120.0833 Y Y Y ABTC105560 WAMR115627 Gehyra montium Cliff Head WA -29.5333 114.9833 Y Y Y ABTC105566 WAMR117145 Gehyra montium Yamarna Station WA -27.9666 123.7667 Y Y ABTC105585 WAMR129901 Gehyra montium West Angelas WA -23.2500 118.6667 Y Y ABTC105591 WAMR131746 Gehyra montium Hamersley Station WA -22.3647 117.8633 Y Y Y ABTC105593 WAMR132551 Gehyra montium Degrey River Station WA -20.2263 119.1794 Y Y Y ABTC105599 WAMR135118 Gehyra montium Bullabulling WA -30.8625 120.9067 Y Y Y ABTC105610 WAMR139610 Gehyra montium Mount Hodgson WA -22.4408 121.128 Y Y ABTC105624 WAMR156600 Gehyra montium Woodie Woodie WA -21.6200 121.2139 Y Y ABTC105626 WAMR156679 Gehyra montium Yarrie Minesite WA -20.6491 114.3031 Y Y ABTC105634 WAMR161141 Gehyra montium Bonney Downs Homestead WA -22.182 119.933 Y Y Y ABTC105649 WAMR170390 Gehyra montium Balfour Downs Homestead WA -22.6111 120.729 Y Y ABTC105652 WAMR170890 Gehyra montium Marble Bar WA -21.4381 119.541 Y Y Y ABTC105653 WAMR77994 Gehyra montium Warburton WA -26.0000 126.7500 Y ABTC13409 SAMAR51087 Gehyra montium Tennant Creek dump NT -19.65 134.18 Y Y Y ABTC31296 Gehyra montium Petermann Range WA -25.01 128.93 Y Y Y ABTC31336 Gehyra montium Giles WA -25.03 128.30 Y ABTC41477 SAMAR44368 Gehyra montium 14k ENE Mt Cooparinna SA -26.34 130.10 Y Y Y ABTC41478 SAMAR44369 Gehyra montium 14k ENE Mt Cooparinna SA -26.34 130.10 Y Y Y ABTC41480 SAMAR44370 Gehyra montium 14k ENE Mt Cooparinna SA -26.34 130.10 Y Y ABTC41553 SAMAR44407 Gehyra montium 8.4k NW Mt Kintore SA -26.50 130.44 Y Y Y Y ABTC41770 SAMAR46107 Gehyra montium 21k ENE Pipalyatjara SA -26.12 129.37 Y Y Y Y ABTC41777 SAMAR46134 Gehyra montium 16k E Pipalyatjara SA -26.16 129.33 Y Y Y Y ABTC41778 SAMAR46135 Gehyra montium 16k E Pipalyatjara SA -26.16 129.33 Y Y Y Y ABTC41794 SAMAR46139 Gehyra montium 40k NE Pipalyatjara NT -25.98 129.48 Y Y Y ABTC41961 SAMAR48732 Gehyra montium Mt Lindsay SA -27.03 129.88 Y Y ABTC41962 SAMAR48733 Gehyra montium Mt Lindsay SA -27.03 129.88 Y Y Y Y ABTC41964 SAMAR48735 Gehyra montium Mt Lindsay SA -27.03 129.88 Y Y ABTC41972 SAMAR48708 Gehyra montium 4k W Mt Lindsay SA -27.03 129.84 Y Y ABTC41982 SAMAR48718 Gehyra montium 4k W Mt Lindsay SA -27.03 129.84 Y Y Y Y ABTC79922 SAMAR56497 Gehyra montium 5.6k W Mount Hoare SA -27.06 129.64 Y Y Y ABTC91567 WAMR166310 Gehyra montium 4.2k SSE Pungkulpirri Waterhole WA -24.6964 128.7628 Y Y ABTC91633 WAMR166321 Gehyra montium 3.4k NE Mt Fanny WA -25.7583 128.5983 Y Y Y Y ABTC91637 WAMR166314 Gehyra montium Kutjuntari Rockhole WA -24.8914 128.7692 Y Y ABTC91656 WAMR166317 Gehyra montium Morgan Range WA -259386 128.3897 Y Y ABTC91658 WAMR166318 Gehyra montium Morgan Range WA -259386 128.3897 Y Y Y ABTC91760 WAMR166312 Gehyra montium Morgan Range WA -259386 128.3897 Y 210

ABTC13940 Gehyra mutilata Krakatau Y Y ABTC32321 Gehyra mutilata Dumaguete, Negros Island Y Y Y 2058 BP02058 Gehyra nana King Edward River Crossing WA -14.45 126.66 Y Y Y ABTC32281 UMMZ182803 Gehyra oceanica Tanna Island Y Y Y ABTC49805 AMSR129847 Gehyra oceanica Guleguleu Normanby Island MBP Y ABTC72525 NTMR26111 Gehyra pamela ~15k S Camp Arnhemland Plateau NT -13.38 133.38 Y Y Y ABTC11726 SAMAR34053 Gehyra pilbara 40k E Mt Newman WA -23.18 119.98 Y Y ABTC31246 Gehyra pilbara The Granites NT -28.04 117.83 Y Y ABTC105474 WAMR165102 Gehyra punctata Millstream Homestead WA -21.518 117.043 Y Y ABTC105480 WAMR170815 Gehyra punctata Old Pilga Homestead WA -21.480 119.414 Y Y ABTC59765 AMSR123098 Gehyra punctata Kalli HS WA 117.12 -26.89 Y Y ABTC59773 AMSR123115 Gehyra punctata Pells Creek crossing WA -25.24 115.53 Y Y Y ABTC62348 WAMR106088 Gehyra punctata Woodstock Station WA -21.61 118.95 Y Y Y ABTC105487 WAMR108683 Gehyra purpurascens Banjawarn Homestead WA -27.72 121.8167 Y Y Y ABTC42153 SAMAR50164 Gehyra purpurascens 14.4k S Sentinel Hill SA -26.21 132.44 Y Y Y ABTC58138 SAMAR45300 Gehyra purpurascens Olympic Dam SA -30.38 136.85 Y Y Y ABTC58533 SAMAR48599 Gehyra purpurascens 12.3k NNW Mt Cheesman SA -27.31 130.27 Y Y Y ABTC11939 SAMAR34220 Gehyra robusta 7k E Mount Isa Qld -20.72 139.55 Y Y ABTC105535 WAMR104995 Gehyra variegata Old Rainy Rocks WA -29.7327 119.6169 Y Y Y ABTC105539 WAMR108602 Gehyra variegata Pannawonica WA -21.7833 116.2500 Y Y Y ABTC105542 WAMR110308 Gehyra variegata Mile Camp WA -22.7073 119.709 Y Y Y ABTC105544 WAMR111848 Gehyra variegata Wheelarra Hill WA -23.3725 120.458 Y Y Y ABTC105547 WAMR113685 Gehyra variegata Dalwallinu WA -30.2833 116.7167 Y ABTC105549 WAMR114039 Gehyra variegata Peron Hs WA -25.8333 113.5500 Y Y ABTC105554 WAMR114499 Gehyra variegata Waggrakine WA -28.7000 114.6667 Y Y Y ABTC105555 WAMR114501 Gehyra variegata Wicherina Dam WA -28.7333 115.0000 Y Y Y ABTC105556 WAMR114915 Gehyra variegata Capricorn Roadhouse WA -23.7166 119.7167 Y Y ABTC105558 WAMR115241 Gehyra variegata Eurardy Station WA -27.5666 114.6667 Y Y Y ABTC105563 WAMR117022 Gehyra variegata Babbage Island WA -24.8666 113.6333 Y Y Y ABTC105564 WAMR117025 Gehyra variegata Bush Bay WA -25.1500 113.7833 Y Y Y ABTC105567 WAMR117153 Gehyra variegata Dead Horse Rocks WA -29.3666 121.2833 Y Y Y ABTC105568 WAMR117168 Gehyra variegata Zanthus WA -31.0666 123.5833 Y Y Y ABTC105573 WAMR119033 Gehyra variegata Wuraga WA -28.4166 116.2833 Y ABTC105581 WAMR126810 Gehyra variegata WA -24.5113 114.6367 Y Y Y ABTC105597 WAMR132901 Gehyra variegata Jilakin Rock WA -32.6666 118.3333 Y Y Y ABTC105604 WAMR136313 Gehyra variegata Muggon WA -26.5269 115.5250 Y Y Y ABTC105605 WAMR136645 Gehyra variegata Lake Mason WA -27.7127 119.4006 Y Y Y ABTC105609 WAMR139014 Gehyra variegata Mandora WA -19.8083 121.4639 Y ABTC105611 WAMR140926 Gehyra variegata Peak Eleanora WA -33.1666 121.2667 Y Y Y ABTC105613 WAMR141662 Gehyra variegata Cape Rose WA -25.7500 113.6583 Y Y Y ABTC105614 WAMR141670 Gehyra variegata Baudin Island WA -26.5166 113.6500 Y 211

ABTC105615 WAMR144114 Gehyra variegata Ora Banda WA -30.3688 121.0675 Y Y ABTC105616 WAMR144777 Gehyra variegata Bungalbin Hill WA -30.4666 119.6000 Y Y ABTC105619 WAMR146951 Gehyra variegata Mount Gibson WA -29.5886 117.4128 Y Y ABTC105623 WAMR156487 Gehyra variegata Goodiadarrie Hills WA -22.6725 118.9367 Y Y Y ABTC105625 WAMR156674 Gehyra variegata North West Coastal Hwy WA -26.8169 114.6153 Y Y Y ABTC105629 WAMR157811 Gehyra variegata Karara Station WA -29.1891 116.7119 Y Y Y ABTC105638 WAMR162450 Gehyra variegata Meekatharra WA -26.591 118.497 Y Y ABTC105641 WAMR163321 Gehyra variegata Neale Junction WA -28.6883 125.8483 Y Y Y ABTC105645 WAMR165160 Gehyra variegata Yanyare River Mouth WA -20.8429 116.367 Y Y Y ABTC105648 WAMR167541 Gehyra variegata Gascoyne Junction WA -25.4936 114.8650 Y Y Y ABTC105681 WAMR168151 Gehyra variegata Camp Creek WA -15.5944 125.1872 Y Y Y ABTC52237 SAMAR31997 Gehyra variegata Mitcherie RH SA -31.49 132.84 Y Y ABTC52238 SAMAR31998 Gehyra variegata Mitcherie RH SA -31.49 132.84 Y Y ABTC64320 SAMAR32281 Gehyra variegata 42.5k N Muckera RH SA -29.70 130.12 Y Y ABTC72576 WAMR141460 Gehyra variegata Faure Island WA -25.90 113.91 Y Y Y Y ABTC72583 WAMR141467 Gehyra variegata Faure Island WA -25.88 113.89 Y Y Y ABTC82613 SAMAR59074 Gehyra variegata Mt Gibson Station - camp WA -29.61 117.41 Y Y ABTC95388 SAMAR57176 Gehyra variegata 48.7k S Vokes Hill Corner SA -28.85 130.48 Y Y BS9064 Gehyra variegata Eyre Hwy, Nullabor Plain SA -32.40 124.46 Y BS9065 Gehyra variegata Eyre Hwy, Nullabor Plain SA -32.40 124.46 Y R64106 SAMAR64106 Gehyra lazelli Terrapinna Springs SA -29.92 139.67 Y Y Y 2072 BP02072 Gehyra occidentalis Manning Gorge WA -16.64 125.91 Y Y Y 2061 BP02061 Gehyra xenpous King Edward River Crossing WA -14.45 126.66 Y Y 2065 Gehyra xenpous King Edward River Crossing WA -14.45 126.66 Y Y Y

ABTC32736 Hemiphyllodactylus typhus Suva Y Y Y ABTC50488 AMSR136386 Lepidodactylus lugubris Honiara, Guadalcanal Y Y Y

212

Appendix 3: Samples used for dating analysis in Chapter 4.

Genus Species Acession No. Aristelliger georgeensis HQ426261 Calotes calotes AY662584 Chondrodactylus angulfier DQ275447 Christinus marmoratus FJ855440 Coleodactylus septentrionalis EU435212 Cordylus polyzonus EU366444 Ctenotus robustus AY662630 Cyrtodactylus loriae EU268289 Cyrtopodion scabrum HQ426275 Dixonius siamensis EU054283 Ebenavia inunguis EF536143 Eremias sp. AY662615 Eublepharis turcmenicus AY662622 Euleptes europea EF534806 Euprepis auratus AY662629 Gehyra australis ABTC28970 Gehyra oceanica ABTC32281 Gehyra variegata ABTC105487 Gekko gecko AY662625 Gloydius halys AY662614 Gymodactylus amarali HQ426288 Haemodracon riebeckii HM212506 Hemidactylus frenatus EU108534 Homonota fasciata EU293629 Homopholis fasciata EU054226 Lepidoblepharis xanthostigma EU435217 Naja naja EU366432 Osteolaemus tetrasips FJ390081 Ramphotyphlops braminus AY444062 Shinisaurus crocodilurus AY662610 Sphenodon punctatus AY487362 Varanus griseus AY662608 Xenopeltis unicolor DQ465564 Xenosaurus grandis AY662607

213

Appendix 4: Details of samples used for species tree analysis in Chapter 4 ABTC Number Species ND2 PRLR H3 MCR A1 A2 Rag ABTC11826 australis Yes Yes Yes ABTC28970 australis Yes Yes Yes Yes Yes ABTC28544 australis Yes Yes Yes ABTC11877 australis Yes Yes Yes ABTC29516 australis Yes Yes Yes Yes Yes ABTC44765 baliola Yes Yes Yes Yes Yes Yes ABTC44485 baliola Yes Yes Yes Yes Yes Yes ABTC90224 barea Yes Yes ABTC90183 barea Yes Yes ABTC11903 borroloola Yes Yes Yes Yes Yes ABTC11809 borroloola Yes Yes ABTC11888 borroloola Yes Yes ABTC29880 borroloola Yes Yes Yes ABTC11887 borroloola Yes Yes ABTC11923 borroloola Yes Yes Yes Yes Yes Yes ABTC29579 borroloola Yes Yes ABTC29556 borroloola Yes Yes Yes Yes ABTC77213 catenata Yes Yes Yes ABTC32130 catenata Yes Yes Yes ABTC32121 catenata Yes Yes Yes ABTC09994 CladeI Yes Yes ABTC30293 CladeI Yes Yes Yes Yes Yes ABTC24050 CladeI Yes Yes Yes ABTC24132 CladeI Yes Yes Yes Yes ABTC91637 CladeII Yes Yes Yes Yes Yes ABTC33882 CladeII Yes Yes ABTC42363 CladeII Yes Yes ABTC73410 CladeII Yes Yes Yes Yes Yes Yes ABTC42130 CladeII Yes ABTC105580 CladeIII Yes Yes Yes Yes Yes Yes ABTC105541 CladeIII Yes Yes ABTC105565 CladeIII Yes Yes ABTC105583 CladeIII Yes Yes ABTC59760 CladeIII Yes Yes Yes Yes Yes Yes ABTC09031 CladeIV Yes Yes Yes ABTC77068 CladeIV Yes Yes Yes ABTC11968 CladeIV Yes Yes Yes ABTC09066 CladeIV Yes Yes ABTC13398 CladeIV Yes Yes Yes Yes Yes Yes ABTC29239 CladeV Yes Yes ABTC23879 CladeV Yes Yes ABTC77006 CladeV Yes Yes Yes Yes Yes Yes ABTC06816 CladeV Yes Yes ABTC03711 CladeV Yes Yes ABTC15185 CladeV Yes Yes Yes Yes Yes ABTC29571 dubia Yes Yes Yes ABTC70702 dubia Yes Yes Yes ABTC77212 dubia Yes Yes Yes ABTC77195 dubia Yes Yes Yes Yes ABTC15115 dubia Yes Yes Yes Yes Yes Yes ABTC16191 dubia Yes Yes Yes Yes ABTC28493 ipsa Yes Yes Yes 214

ABTC28547 ipsa Yes Yes Yes Yes Yes ABTC28490 ipsa Yes Yes Yes ABTC105310 koira Yes Yes Yes Yes Yes ABTC105321 koira Yes Yes Yes ABTC30613 koira Yes Yes Yes ABTC30614 koira Yes Yes Yes Yes Yes ABTC30107 koira Yes Yes ABTC52233 lazelli Yes Yes Yes Yes Yes Yes Yes ABTC74065 lazelli Yes Yes Yes ABTC74197 lazelli Yes Yes Yes Yes Yes ABTC50301 membranacruralis Yes Yes Yes Yes Yes ABTC12100 minuta Yes Yes Yes Yes Yes ABTC61706 minuta Yes Yes ABTC61704 minuta Yes Yes Yes ABTC61707 minuta Yes Yes Yes Yes Yes Yes Yes ABTC105323 montium Yes Yes ABTC41961 montium Yes Yes Yes ABTC105585 montium Yes Yes Yes ABTC105557 montium Yes Yes Yes ABTC41553 montium Yes Yes Yes Yes Yes Yes ABTC32321 mutilata Yes Yes Yes Yes Yes ABTC13940 mutilata Yes Yes Yes Yes Yes ABTC105329 nana Yes Yes Yes Yes Yes 2058 nana Yes Yes Yes 2059 nana Yes Yes Yes Yes Yes ABTC105326 nana Yes Yes Yes ABTC105372 occidentalis Yes Yes Yes Yes ABTC105373 occidentalis Yes Yes Yes 2072 occidentalis Yes Yes Yes Yes Yes ABTC105379 occidentalis Yes Yes ABTC105352 occidentalis Yes Yes ABTC32281 oceanica Yes Yes Yes Yes ABTC49805 oceanica Yes R64106 ornata Yes Yes Yes R64430 ornata Yes ABTC27725 pamela Yes Yes Yes ABTC11872 pamela Yes Yes Yes ABTC72525 pamela Yes Yes Yes ABTC29167 pamela Yes Yes Yes ABTC105408 pilbara Yes Yes Yes ABTC105466 pilbara Yes Yes Yes Yes Yes Yes ABTC105402 pilbara Yes Yes Yes ABTC105403 pilbara Yes Yes Yes Yes ABTC105474 punctata Yes Yes Yes ABTC59773 punctata Yes Yes Yes Yes Yes ABTC59765 punctata Yes Yes Yes ABTC62348 punctata Yes Yes Yes Yes Yes Yes ABTC105480 punctata Yes Yes ABTC42153 purpurascens Yes Yes Yes ABTC58553 purpurascens Yes Yes Yes ABTC105487 purpurascens Yes Yes Yes ABTC58138 purpurascens Yes Yes Yes Yes ABTC00580 purpurascens Yes Yes Yes Yes ABTC08949 robusta Yes Yes ABTC11946 robusta Yes Yes Yes ABTC11939 robusta Yes Yes Yes Yes Yes Yes 215

ABTC72858 robusta Yes Yes ABTC11941 robusta Yes ABTC105539 variegata Yes Yes Yes ABTC105615 variegata Yes Yes Yes ABTC82613 variegata Yes Yes Yes ABTC105547 variegata Yes Yes Yes ABTC105645 variegata Yes Yes Yes Yes Yes 2061 xenopus Yes Yes Yes Yes Yes Yes Yes ABTC105662 xenopus Yes Yes ABTC105659 xenopus Yes Yes Yes ABTC13017 xenopus Yes Yes Yes Yes Yes ABTC105679 xenopus Yes Yes

216

Appendix 5: Individual gene trees extracted from *Beast Species tree analysis.

217 218 219 220 221

222

Appendix 6: Details of the specimens and samples used for Chapter 5.

Map ABTC Regno mtDNA microsatellites morphology species Locality Longitude Latitude No. ABTC40737 SAMAR26491 yes yes lazelli near Yalata Roadhouse 131.27 -31.4 ABTC89675 SAMAR61563 yes lazelli 11.3k NNW Penong 132.8905 -31.8739 4 ABTC17956 SAMAR38988 yes yes lazelli 15k N Witchellina Station 133.58 -32.28 ABTC52233 SAMAR31984 yes lazelli Yumbarra CP 133.67 -31.67 5 ABTC89462 SAMAR61313 yes yes lazelli 8.2k NNW Oak Hill 134.29 -32.15 ABTC95855 SAMAR56567 yes lazelli 5.8k NE Kalbrae 134.92 -33.53 ABTC95873 SAMAR56576 yes yes lazelli 26.5k WSW Minnipa 135.37 -33.01 ABTC52383 SAMAR25435 yes yes lazelli Mt Ive HS 136.07 -32.4 ABTC52434 SAMAR28515 yes lazelli 120k NE Minnipa 136.2833333 -32.3333333 23 ABTC22091 SAMAR28977 yes lazelli Gawler Ranges 136.35 -32.6166667 7 ABTC15382 SAMAR38973 yes lazelli 3k W Cowell 136.85 -33.68 ABTC18031 SAMAR38986 yes lazelli Middleback Range 137.1 -33.1833333 9 ABTC18032 SAMAR38985 yes lazelli Middleback Range 137.1 -33.1833333 9 ABTC57241 SAMAR38570 yes lazelli Middleback Ranges 137.1333333 -33.1666667 8 ABTC33226 SAMAR46283 yes yes lazelli 4.5k NE Mt Brown 138.02 -32.47 ABTC52394 SAMAR25874 yes yes lazelli Witchelina Station 138.05 -30.02 ABTC15326 SAMAR38967 yes yes lazelli Warren Gorge 138.08 -32.07 ABTC70444 SAMAR53259 yes lazelli 4.5k ENE Telowie 138.12 -33.04 ABTC95467 SAMAR56397 yes lazelli 1.1k WNW White Cliff Hill 138.3 -30.14 ABTC70511 SAMAR53080 yes yes lazelli 5k E Mt Elm 138.36 -31.91 ABTC70527 SAMAR53088 yes yes lazelli 5k E Mt Elm 138.36 -31.91 ABTC70422 SAMAR53226 yes yes lazelli 5k W Wilpena Chalet 138.55 -31.53 ABTC39325 SAMAR52366 yes yes lazelli 4.7k W Parachilna Hill 138.55 -31.13 ABTC70412 SAMAR53239 yes yes lazelli 4.3k WSW Wilpena Chalet 138.56 -31.54 ABTC70415 SAMAR53211 yes yes lazelli 1.2k SW Wilpena Chalet 138.59 -31.54 ABTC70423 SAMAR53213 yes yes lazelli 1.2k SW Wilpena Chalet 138.59 -31.54 ABTC74017 SAMAR52674 yes yes lazelli 2k SSE Warraweena HS 138.64 -30.79 2.2k ESE Horn Camp Ruin, Alpana ABTC39291 SAMAR52214 yes lazelli Station 138.6438889 -31.1158333 18 223

ABTC70425 SAMAR53245 yes yes lazelli Appealinna Ruins 138.7 -31.44 ABTC58818 SAMAR51289 yes yes lazelli Finke Creek 138.72 -30.52 ABTC58819 SAMAR51290 yes yes lazelli Finke Creek 138.72 -30.52 ABTC39251 SAMAR52198 yes yes lazelli Patawarta Bore Narrina Station 138.73 -30.94 ABTC39257 SAMAR52189 yes yes lazelli 0.8k S Patawarta Bore Narrina Station 138.73 -30.94 ABTC39258 SAMAR52190 yes yes lazelli 0.8k S Patawarta Bore Narrina Station 138.73 -30.94 ABTC39239 SAMAR52181 yes yes yes lazelli 2.1k SW Malkegna Bore Narrina Station 138.75 -30.96 17 ABTC39250 SAMAR52184 yes yes lazelli 2.1k SW Malkegna Bore Narrina Station 138.75 -30.96 ABTC38861 SAMAR51801 yes lazelli 9k SSE Mudlapena Spring 138.8158 -30.6897 12 ABTC39217 SAMAR51800 yes yes lazelli 9k SSE Mudlapena Spring 138.82 -30.69 ABTC39223 SAMAR52177 yes yes lazelli 9k SSE Mudlapena Spring 138.82 -30.69 ABTC39237 SAMAR51801 yes yes yes lazelli 9k SSE Mudlapena Spring 138.82 -30.69 ABTC58817 SAMAR51288 yes yes lazelli Mt Serle Station 138.88 -30.53 ABTC70047 SAMAR53786 yes yes lazelli 7.5k NNE Strathalbyn 138.92 -35.19 ABTC74104 SAMAR52896 yes yes yes lazelli Gammon Ranges NP 139.04 -30.47 22 ABTC15181 SAMAR38950 yes yes yes lazelli Tungkillo 139.1 -34.8166667 1 ABTC15183 SAMAR38952 yes yes yes lazelli 3k E Tungkillo 139.1 -34.82 2 ABTC15184 SAMAR38953 yes lazelli 3k E Tungkillo 139.1 -34.82 2 ABTC15196 SAMAR38955 yes lazelli Tungkillo 139.1 -34.8166667 1 ABTC74158 SAMAR52911 yes yes yes lazelli Gammon Ranges NP 139.15 -30.43 28 ABTC74160 SAMAR52912 yes yes yes lazelli Gammon Ranges NP 139.15 -30.43 20 ABTC74161 SAMAR52913 yes yes lazelli Gammon Ranges NP 139.15 -30.43 ABTC74072 SAMAR52907 yes yes lazelli Gammon Ranges NP 139.17 -30.42 ABTC74154 SAMAR52900 yes yes yes lazelli Gammon Ranges NP 139.17 -30.42 29 ABTC39130 SAMAR52012 yes yes yes lazelli 4.7k NNE Warden Hill 139.24 -30.4 19 ABTC18043 SAMAR32860 yes yes lazelli 12k N Sedan 139.3 -34.47 ABTC74057 SAMAR52973 yes yes yes lazelli Mt Freeling 139.42 -30.11 26 ABTC74058 SAMAR52974 yes yes lazelli Mt Freeling 139.42 -30.11 ABTC74059 SAMAR52975 yes lazelli Mt Freeling 139.42 -30.11 ABTC74063 SAMAR52988 yes yes yes lazelli Arkaroola 139.42 -30.11 27 ABTC74065 SAMAR52977 yes yes yes lazelli Mt Freeling 139.42 -30.11 26 224

ABTC74186 SAMAR53006 yes yes variegata Arkaroola 139.42 -30.11 R64445 yes variegata 17km E Mt Fitton HS 139.420833 -29.904167 R64446 yes variegata 17km E Mt Fitton HS 139.420833 -29.904167 ABTC74062 SAMAR52962 yes yes yes lazelli Arkaroola 139.45 -30.12 6 ABTC74066 SAMAR52963 yes yes yes lazelli Arkaroola 139.45 -30.12 6 ABTC74197 SAMAR52958 yes yes yes lazelli Arkaroola 139.45 -30.12 6 ABTC74199 SAMAR52960 yes yes yes lazelli Arkaroola 139.45 -30.12 6 ABTC74200 SAMAR52961 yes yes yes lazelli Arkaroola 139.45 -30.12 6 ABTC74198 SAMAR52959 yes lazelli Arkaroola 139.45 -30 ABTC108002 R64937 yes yes variegata Hidden Valley, Arkaroola 139.505565 -30.114661 ABTC108001 R64936 yes yes variegata Hidden Valley, Arkaroola 139.506723 -30.114268 ABTC108007 R64942 yes yes ornata Hidden Valley, Arkaroola 139.5211367 -30.08302185 24 ABTC108015 No voucher yes variegata Hidden Valley, Arkaroola 139.52116 -30.08525 ABTC108004 R64939 yes yes ornata Hidden Valley, Arkaroola 139.5219403 -30.08479939 24 ABTC108005 R64940 yes yes ornata Hidden Valley, Arkaroola 139.5219403 -30.08479939 24 ABTC108006 R64941 yes yes ornata Hidden Valley, Arkaroola 139.5219403 -30.08479939 24 ABTC108024 No voucher yes variegata 2k W Waterlina Bore, Moolawatana 139.54413 -29.8399 ABTC108025 R64950 yes yes ornata 2k W Waterlina Bore, Moolawatana 139.54553 -29.84042 14 ABTC108023 No voucher yes variegata 2k W Waterlina Bore, Moolawatana 139.54585 -29.8405 ABTC108022 R64945 yes yes ornata 2k W Waterlina Bore, Moolawatana 139.54694 -29.84011 14 ABTC108027 R64953 yes yes ornata 2k W Waterlina Bore, Moolawatana 139.54884 -29.84442 14 ABTC108021 R64943 yes yes ornata 2k W Waterlina Bore, Moolawatana 139.54886 -29.83592 14 R64442 yes variegata Mt Fitton HS 139.553611 -29.987222 R64443 yes variegata Mt Fitton HS 139.553611 -29.987222 Pepegoona Gorge, Northen Flinders ABTC108039 R64955 yes yes ornata Ranges 139.60188 -30.08139 10 Pepegoona Gorge, Northen Flinders ABTC108040 R64956 yes yes ornata Ranges 139.60188 -30.08139 10 Pepegoona Gorge, Northen Flinders ABTC108037 R64954 yes yes ornata Ranges 139.60251 -30.08078 10 Pepegoona Gorge, Northen Flinders ABTC108033 R64944 yes yes ornata Ranges 139.60442 -30.08026 10 Pepegoona Gorge, Northen Flinders ABTC108035 No voucher yes variegata Ranges 139.60442 -30.08026 225

R64439 yes variegata 3Km E Mt Fitton HS 139.613611 -29.950278 R64440 yes variegata 3Km E Mt Fitton HS 139.613611 -29.950278 R64441 yes variegata 3Km E Mt Fitton HS 139.613611 -29.950278 R64103 yes yes yes ornata Terrapinna Springs 139.6664 -29.9153 31 R64104 yes yes yes ornata Terrapinna Springs 139.6664 -29.9153 31 R64105 yes yes yes ornata Terrapinna Springs 139.6664 -29.9153 31 R64106 yes yes yes ornata Terrapinna Springs 139.6664 -29.9153 31 R64427 yes yes yes ornata Terrapinna Springs 139.6664 -29.9153 31 R64428 yes yes yes ornata Terrapinna Springs 139.6664 -29.9153 31 SAMAR20377 yes ornata Terrapinna Springs 139.6664 -29.9153 R64097 yes variegata Terrapinna Springs 139.7186 -29.9042 R64098 yes yes yes variegata Terrapinna Springs 139.7186 -29.9042 R64099 yes yes variegata Terrapinna Springs 139.7186 -29.9042 R64429 yes yes yes ornata 5km W Moolawatana HS 139.7186 -29.9042 11 R64430 yes yes yes ornata 5km W Moolawatana HS 139.7186 -29.9042 R64431 yes yes yes ornata 5km W Moolawatana HS 139.7186 -29.9042 11 R64432 yes yes yes ornata 5km W Moolawatana HS 139.7186 -29.9042 ABTC68799 SAMAR52596 yes yes lazelli Tombstone Hill 6k N Plumbago HS 139.91 -32.01 ABTC68800 SAMAR52597 yes yes lazelli Tombstone Hill 6k N Plumbago HS 139.91 -32.01 21 ABTC74093 SAMAR52936 yes yes yes lazelli Gammon Ranges NP 139.97 -30.52 13 ABTC74094 SAMAR52937 yes yes yes lazelli Gammon Ranges NP 139.97 -30.52 13 ABTC74095 SAMAR52938 yes yes lazelli Gammon Ranges NP 139.97 -30.52 ABTC74096 SAMAR52939 yes yes lazelli Gammon Ranges NP 139.97 -30.52 13 ABTC40166 SAMAR41450 yes yes lazelli Saltwell 140.12 -32.6 ABTC89242 SAMAR61010 yes lazelli Old Boolcoomata, Bimbowrie Station 140.28 -32.1 3 ABTC88094 SAMAR60602 yes lazelli 2k SE Calico Bore, Bimbowrie Station 140.3161111 -31.9741667 15 ABTC88098 SAMAR60608 yes lazelli 2k WNW Blue Dam, Bimbowrie Station 140.3283333 -32.0747222 30 ABTC88097 SAMAR60620 yes lazelli 2.5k WSW Blue Dam, Bimbowrie Station 140.3333333 -32.0672222 16 ABTC96429 SAMAR58721 yes yes lazelli 5.9k NNW Nelwood HS 140.92 -33.91 ABTC03671 SAMAR38945 yes yes lazelli Lancoona HS 145.883333 -32.366667 25