1

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

2

“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.

3

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

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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

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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

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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

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and will greatly assist in discovering and documenting the diversity of this problematic

radiation in the future.

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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.

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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

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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

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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).

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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

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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.

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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

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“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.

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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.

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Molecular phylogeny of Australian Gehyra (Squamata:

Gekkonidae) and taxonomic revision of Gehyra variegata in

south-eastern Australia

Mark J. Sistrom1, Mark N. Hutchinson

1, Rhonda G. Hutchinson

2 & 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

20

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

3.

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

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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 re-

describe 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

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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)

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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

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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 ; koira ; 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.

G D ^

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

32

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

variegata

purpurascens 2n=44f

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)

36

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.

41

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.

45

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.

47

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 south- east 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: mark.sistrom@adelaide.edu.au

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.

54

Signed: Date: 16/09/2011

55

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 94

oC, 45 s at 55

oC

and 1 min at 72oC for nuclear genes and 40 cycles of: 45 s at 94

oC, 45 s at 60

oC and 1

min at 72oC with a final extension step of 6 min at 72

oC. 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, 2

nd,3

rd and 1

st and 2

nd 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

ranging from m=0.1 to m=1x10-4

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

with m=0.1 for θ and m=1x10-4

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

69

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

72

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

distribution of m=0.1 for θ and m=1x10-4

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 =

0.1, 2: means = 0.01, 3: means = 0.005, 4 means = 1 x 10-4

and 5: mean θ =0.1 and mean T0= 1 x 10-4

.

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

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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.

83

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.

84

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

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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.

91

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.

92

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.

95

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.

97

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.

98

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,).

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 8-11, mode 9. Infralabials 7-10, mode 9.

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 Donnellan

2,3

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: mark.sistrom@adelaide.edu.au

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.

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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,

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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;

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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-

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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)

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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.

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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.

Locus Primer Sequence BP Samples

No

species

No

Haplotypes

GC

content e

Tajima's

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

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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.

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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.

Node

Lognormal Prior

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

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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

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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

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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

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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.

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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

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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).

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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

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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.

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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

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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.

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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

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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.

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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

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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

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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

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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.

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Morphological differentiation correlates with ecological but

not genetic divergence in a Gehyra gecko.

Mark Sistrom1, 2, 4

, Danielle Edwards3, Steve Donnellan

1, 4 and Mark Hutchinson

2.

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: mark.sistrom@adeliade.edu.au

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.

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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

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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).

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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.

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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

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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

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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

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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

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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

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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).

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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

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(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

unit

N Ho He Fis P Ho He Fis P

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

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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

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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

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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

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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

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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.

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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.

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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

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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

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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

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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

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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.

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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**

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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

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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

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(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

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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

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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.

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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.

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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

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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

References

1. Adler G.H., Levins R. 1994. The island syndrome in rodent populations. Q.

Rev. Biol. 69:473-490.

2. Avise J.C. & Wollenberg K. 1997. Phylogenetics and the origin of species. Proc.

Natl. Acad Sci. U.S.A. 94:7748-7755.

3. Barbuti, R. Maggiolo-Schettini, A. & Milazzo, P. 2009. A methodology for

stochastic modeling and simulation of sympatric speciation by sexual selection. J.

Biol. Syst. 17:349-376.

4. Barton, N. H. & Gale, K. S. 1993. Genetic analysis of hybrid zones In Hybrid

zones and the evolutionary process (ed. Harrison, R. G.), U.S.A.: Oxford

University Press.

5. Bauer A.M., Henle K. 1994. Gekkonidae (Reptila, Sauria). Part I. Australia and

Oceania. Das Tierreich 109:1–222.

6. Bauer A.M., Parham J.F., Brown R.M., Stuart B.L., Grismer L. Papenfuss T.J.,

Böhme W., Savage J.M., Carranza S., Grismer J.L., Wagner P., Schmitz A.,

Ananjeva N.B., Inger R.F. 2011. Availability of new Bayesian-delimited gecko

names and the importance of character-based species descriptions. Proc. R. Soc.

Biol. Sci. Ser. B. 278:490-492.

7. Beck, R. M. 2008. A dated phylogent of marsupials using a molecular

supermatrix and multiple fossil constraints. J. Mamm. 89:175-189.

8. Beerli P., Felsenstein J. 2001. Maximum likelihood estimation of a migration

matrix and effective population sizes in n subpopulations using a coalescent

approach, Proc. Natl. Acad. Sci. USA 98:4563–4568.

179

9. Berner, D., Grandchamp, A. & Hendry, A.P., 2009. Variable progress toward

ecological speciation in parapatry: stickleback across eight lake-stream

transitions. Evolution 63:1740-1753.

10. Bickford, D., Lohman, D. J., Sodhi, N. S., Ng, P. K. L., Meier, R., Winker K.,

Ingram, K. K. & Das, I. 2006. Cryptic species as a window on diversity and

conservation. Trends. Ecol. Evol. 22:148-155.

11. Burbrink F.T., Pyron A.R. 2011. The impact of gene-tree/species tree discordance

on diversification rate estimation Evolution 65:1851-1861.

12. Bustard, H.R. 1968. The ecology of the Australian gecko, Gehyra variegata, in

northern New South Wales. J. Zool. (Lond.) 154:113–138.

13. Butlin, R.K. 2010. Population genomics and speciation. Genetica 138:409-418.

14. Byrne M., Yeates D.K., Joseph L., Kearney M., Bowler J., Williams M.A.J.,

Cooper S., Donnellan S.C., Keogh J.S., Leys R., Melville J., Murphy D.J., Porch

N., Wyrwoll K-H. 2008. Birth of a biome: insights into the assembly and

maintenance of Australian arid zone biota. Mol. Ecol. 20:4398-4417.

15. Camargo A., Sinervo B., Sites J.W. 2010. Lizards as model organisms for

linking phylogeographic and speciation studies. Mol. Ecol. 19:3250-3270.

16. Cardoso A., Serrano A., Vogler, A.P. 2009. Morphological and molecular

variation in tiger beetles of the Cicindela hybrida complex: is an ‘integrative

taxonomy’ possible? Mol. Ecol. 18:648–664.

17. Carlsbeek R., Smith T.J. 2006. Probing the adaptive landscape using

experimental islands: density-dependent natural selection on lizard body size.

Evolution 61:1052-1061.

180

18. Carstens B.C., Dewey T. 2010 Species delimitation using a combined coalescent

and information-theoretic approach: an example from North American Myotis

bats. Syst. Biol. 59:400-414.

19. Chung Y., Ané C. 2011. Comparing two Bayesian methods for gene tree/species

tree reconstruction: Simulations with incomplete lineage sorting and horizontal

gene transfer. Syst. Biol. 60:261-275.

20. Cogger, H.G. 2000. Reptiles and amphibians of Australia. 6th ed. Reed New

Holland, Sydney, Australia

21. Cogger H.G., Cameron E.E., Cogger H.M. 1983. Zoological catalogue of Australia.

Vol 1. Amphibia and Reptilia. Bureau of fauna and flora, Canberra. 313.

22. Cogger H.G., Heatwole, H. 1981. The Australian reptiles: origins biogeography,

distribution patterns and island evolution. In Keast, A. (ed.), Ecological

Biogeography of Australia. W Junk, The Hague, Vol. 3:1333–1373.

23. Covacevich J., Couper, P. 1991. The reptile records. In Raven R. J., Ingram G. J.

(eds) An atlas of Queensland's frogs, reptiles birds and mammals. Queensland

Museum, Brisbane. 45–140.

24. Cranston K.A. 2010. Summarizing gene tree incongruence at multiple

phylogenetic depths. In Knowles L.L., Kubatko L.S (eds) Estimating species

trees: practical and theoretical aspects. Wiley-Blackwell, N.Y. U.S.A. 129-142.

25. Crisp, M., Cook, L., Steane D. 2004. Radiation of the Australian flora: what can

comparisons of molecular phylogenies across multiple taxa tell us about the

evolution of diversity in present-day communities? Philos. Trans. R. Soc. Lond. B

Biol. Sci. 359:1551-1571.

181

26. Dasmahapatra, K. K., Elias, M., Hill, R. I., Hoffman, J. I. & Mallet, J. 2010.

Mitochondrial DNA barcoding detects some species that are real, and some

that are not. Mol. Ecol. 10:264-273.

27. Dayan T., Simberloff D. 2005. Ecological and community-wide character

displacement: the next generation. Ecol. Lett. 8:875-894.

28. Daza J.D., Herrera A., Thomas R., Claudio H.J. 2009. Are you what you eat?

A geometric morphometric analysis of gekkotan skull shape. Biol. J. Linn.

Soc. 97:677-707.

29. Degnan J.H., Rosenberg N.A. 2009. Gene tree discordance, phylogenetic

inference and the multispecies coalescent. Trends Ecol. Evol. 24:332-340.

30. De Queiroz, K. 1998. The general lineage concept of species, species criteria and

the process of speciation. In Endless forms: species and speciation (eds. Howard,

D. J. & Berlocher, S. H.) pp. 57-65. London: Oxford University Press.

31. De Queiroz K. 2005. Ernst Mayr and the modern concept of species. Proc. Natl.

Acad. Sci. U.S.A. 102:6600–6607

32. De Queiroz K. 2007. Species concepts and species delimitation. Syst Biol. 56:879-

86.

33. DeSalle, R., Egan M. G. & Siddall M. 2005. The unholy trinity: taxonomy,

species delimitation and DNA barcoding. Proc. Roy. Soc. Sci. Ser. B. 360:1905-

1916.

34. Drummond A.J., Rambaut A. 2010. BEAST v1.6. Available from

http://beast.bio.ed.ac.uk/ Last accessed 26 April 2011.

182

35. Drummond A.J., Ashton B., Buxton S., Cheung M., Cooper A., Duran C., Field

M., Heled J., Kearse M., Markowitz S., Moir R., Stones-Havas S., Sturrock S.,

Thierer T., Wilson A. 2010. Geneious v5.3. Available from www.geneious.com.

Last accessed 15 July 2011.

36. Drummond A.J., Rambaut A. 2007. BEAST: Bayesian evolutionary analysis by

sampling trees. BMC Evol. Biol. 7:214.

37. Earl D.A. 2011. Structure Harvester v0.6, Available at

http://users.soe.ucsc.edu/~dearl/software/struct_harvest/. Last accessed

December 12, 2010.

38. Edgar R.C. 2004. MUSCLE: Multiple sequence alignment with high accuracy and

high throughput. Nucliec Acid Res. 32:1792-1797.

39. Ellegren H. 2008. Comparative genomics and the study of evolution by natural

selection. Mol. Ecol. 17:4586–4596.

40. Elmer K.R., Lehtonen T.K., Kautt A.F., Harrod C., Meyer, A. 2010. Rapid

sympatric ecological differentiation of crater lake cichlid fishes within historic

times. BMC Biol. 8:60.

41. Evanno G., Regnaut S., Goudet J. 2005. Detecting the number of clusters of

individuals using the software STRUCTURE: a simulation study. Mol. Ecol.

14:2611–2620.

42. Everitt B.S., Dunn G. 1991. Applied Multivariate Data Analysis 2nd ed. John

Wiley and Sons, London, U.K.

43. Faircloth B.C. 2000. MSATCOMMANDER: detection of microsatellite repeat

arrays and automated, locus-specific primer design. Mol. Ecol. Res. 8:92–94.

183

44. Fraley C., Raftery A.E. 2006. MCLUST version 3 for R: Normal mixture

modeling and model-based clustering, Technical Report No. 504, Dept.

Statistics, Univ. Washington, Seattle, U.S.A.

45. Freshney R.I. 2000. Culture of Animal Cells (4th edn). Wiley-Liss Inc, New York.

577.

46. Fujita,M.K., McGuire, J.A., Donnellan, S.C., Moritz, C. 2007. Diversification and

persistence at the arid–monsoonal interface: Australia-wide biogeography of

Bynoe's gecko (Heteronotia binoei: Gekkonidae). Evolution 64:2293–2314.

47. Fujita M.K., Leaché A.D. 2011. A coalescent perspective on delimiting and

naming species: a reply to Bauer et al. Proc. R. Soc. Biol. Sci. Ser. B. 278:493-

495.

48. Gamble T.P., Bauer A.M., Greenbaum E., Jackman T.R. 2008a. Out of the blue: a

novel trans-Atlantic clade of geckos (Gekkota, Squamata). Zool. Scr. 37:355-366.

49. Gamble T.P., Bauer A.M., Greenbaum E., Jackman T.R. 2008b. Evidence for

Gondwanan vicariance in an ancient clade of gecko lizards. J. Biogeog. 35:88-

104.

50. Gamble T.P., Bauer A.M., Colli G.R., Greenbaum E., Jackman T.R., Vitt L.J.,

Simons A.M. 2010. Coming to America: multiple origins of New World geckos.

J. Evol. Biol. 24:231-244.

51. Gavrilets, S. & Losos, J.B. 2009 Adaptive radiation: contrasting theory with data.

Science 323:732-737.

52. Goddard, C. 1996. Pitjantjara / Yunkunytjatjara to English Dictionary. IAD

Press, Alice Springs, 306 pp.

184

53. Gower, J.C. 1971. A general coefficient of similarity and some of its

properties. Biometrics 27:857–874.

54. Gray J.E. 1834. A new genus of Geckotidae. Proc. Zool. Soc. Lond. 2:99-101.

55. Gross M.R. 1984. Sunfish, salmon and the evolution of alternative

reproductive strategies and tactics in fishes. In Wootton, R. and Potts G (eds)

Fish Reproduction: Strategies and Tactics. Academic Press, London, U.K. 55–

75.

56. Gross M.R. 1985. Disruptive selection for alternative life histories in salmon.

Nature 313:47–48.

57. Gross M.R. 1996. Alternative reproductive strategies and tactics: diversity

within sexes. Trends Ecol. Evol. 11:92-98.

58. Han D., Zhou K., Bauer A.M. 2004 Phylogenetic relationships among gekkotan

lizards inferred from C-mos nuclear DNA sequences and a new classification of

the Gekkota. Biol. J. Linn. Soc. 83:353-368.

59. Harmon, L.J., Melville, J., Larson, A. & Losos J.B. 2008. The role of geography

and ecological opportunity in the diversification of day geckos (Phelsuma). Syst.

Biol. 57:562-573.

60. Harr B. 2006. Genomic islands of differentiation between house mouse

subspecies. Genome Res. 16:730-737.

61. Hayden M.J., Nguyen T.M., Waterman A., Chalmers K.J. 2008. Multiplex-

Ready PCR: A new method for multiplexed SSR and SNP genotyping. BMC

Genomics 9:80.

185

62. Heled J., Drummond A.J. 2010. Bayesian inference of species trees from

multilocus data. Mol. Biol. Evol. 27:570-580.

63. Henle K. 1990. Population ecology and life history of the arboreal gecko

Gehyra variegata in arid Australia. Herpetol. Monogr. 4:30–60.

64. Hennig C., Hausdorf B. 2010. Prabclus: Functions for clustering of presence-

absence, abundance and multilocus genetic data. R package version 2.2-2

http://CRAN.R-project.org/package=prabclus. Last accessed December 10,

2010.

65. Hey J. 2001. The mind of the species problem. Trends Ecol. Evol. 16:326-329.

66. Hey, J. & Neilsen, R. 2007. Integration within the Felsenstein equation for

improved Markov chain Monte Carlo methods in population genetics. Proc. Natl.

Acad. Sci. U.S.A. 104:2785-2790.

67. Hey J. 2010 Isolation with migration models for more than two populations. Mol.

Biol. Evol. 27:905-920.

68. Horner P.P. 2005. Gehyra koira sp. nov. (Reptilia: Gekkonidae), a new species of

lizard with two allopatric subspecies from the Ord-Victoria region of north-

western Australia and a key to the Gehyra australis species complex. Beagle

21:165-174.

69. Herczeg G., Gonda A., Merila J. 2009. Evolution of gigantism in nine-spined

sticklebacks. Evolution 63:3190-3200.

70. Herrel A., Meyers J.J., Vanhooydonck B. 2001. Correlations between habitat

use and body shape in a phrynosomatid lizard (Urosaurus ornatus): a

population-level analysis. Biol. J. Linn. Soc. 74:305–314.

186

71. Herrel A., Huyghe K., Vanhooydonck B., Backeljau T., Breugelmans K.,

Grbac I., Van Damme R., Irschick D.J. 2008. Rapid large-scale evolutionary

divergence in morphology and performance associated with exploitation of a

different dietary resource. Proc. Nat. Acad. Sci. U.S.A. 105:4792–4795.

72. Hibbits T.J., Pianka E.R., Huey R.B., Whiting M.J. 2005. Ecology of the

common barking gecko (Ptenopus garrulus) in Southern Africa. J. Herpetol.

39:509-515.

73. Higham T.E., Russell A.P. 2010. Divergence in locomotor performance,

ecology, and morphology between two sympatric sister species of desert-

dwelling gecko. Biol. J. Linn. Soc. 101:860-869.

74. Horner, P. 2005. Gehyra koira sp. nov. (Reptilia: Gekkonidae), a new species of

lizard with two allopatric subspecies from the Ord-Victoria region of north-

western Australia and a key to the Gehyra australis complex. The Beagle 21:165-

174.

75. Huang H., He Q., Kubatko L.S., Knowles L.L. 2010. Sources of error inherent in

species-tree estimation: Impact of mutational and coalescent effects on accuracy

and implications for choosing among different methods. Syst. Biol. 59:573-583.

76. Hudson M.E. 2008. Sequencing breakthroughs for genomic ecology and

evolutionary biology. Mol. Ecol. Resour. 8:3–17.

77. Hudson, R. R. & Kaplan, N. L. 1985. Statistical properties of the number of

recombination events in the history of a sample of DNA sequences. Genetics

111:147-164.

187

78. Hugall, A.F. & Lee, M.S.Y. 2004. Molecular claims of Gondwanan age for

Australian agamid lizards are untenable. Mol. Biol. Evol. 21:2102-2110.

79. Jakobsson M., Rosenberg N.A. 2007. CLUMPP: a cluster matching and

permutation program for dealing with label switching and multimodality in

analysis of population structure. Bioinformatics (Oxf.) 23:1801-1806.

80. Kent, J. W. 2002. BLAT – The BLAST-like alignment tool. Genome Res.

12:656-664.

81. Keogh S.J., Scott I.A., Hayes C. 2005. Rapid and repeated origin of insular

gigantism and dwarfism in Australian tiger snakes. Evolution 59:226-233.

82. King M. 1979. Karyotypic evolution in Gehyra (Gekkonidae: Reptilia) I. The

Gehyra variegata-punctata complex. Aust. J. Zool. 27:373-393.

83. King M. 1982a. Karyotypic evolution in Gehyra (Gekkonidae: Reptilia). II. A

new species from the Alligator Rivers region in northern Australia. Aust. J. Zool.

30:93–101.

84. King M. 1982b. A new species of Gehyra (Reptilia: Gekkonidae) from central

Australia. Trans. R. Soc. S. Aust. 106:155–158.

85. King M. 1983a. Karyotypic evolution in Gehyra (Gekkonidae: Reptilia) III. The

Gehyra australis complex. Aust. J. Zool. 31:723–741.

86. King M. 1983b. The Gehyra australis species complex (Sauria: Gekkonidae).

Amphib-Reptilia 4:147–169.

87. King M. 1984. Karyotypic evolution in Gehyra Gekkonidae Reptilia IV:

chromosome change and speciation. Genetica (Dordr.) 64:101-114.

88. Kloser R.J., Ryan T., Sakov P., Williams A., Koslow J.A. 2002. Species

188

identification in deep water using multiple acoustic frequencies. Can. J. Fish.

Aquat. Sci. 59:1065-107.

89. Kluge A.G. 1987. Cladistic relationships in the Gekkonoidea (Squamata, Sauria).

University of Michigan Museum of Zoology, Miscellaneous Publications. 173:1–

54.

90. Knesel K.M., Cohen B.E., Vasconcelos P.M., Thiede D.S. 2008. Rapid change in

drift of the Australian plate records collision with Ontong Java plateau. Nature

454:754-758.

91. Knowles L.L., Carstens B.C. 2007. Delimiting species without monophyletic gene

trees. Syst. Biol. 56:400-411.

92. Koh, L. P., Dunn, R. R., Sodhi, N. S., Colwell, R. K., Proctor H. C. & Smith, V.

S. 2004. Species coextinctions and the biodiversity crisis. Science 305:1632-1634.

93. Kubatko L.S., Degnan J.H. 2007. Inconsistency of phylogenetic estimates from

concatenated data under coalesence. Syst. Biol. 56:17-24.

94. Kubatko L.S., Carstens B.C., Knowles, L.L. 2009. STEM: Species tree estimation

using maximum likelihood for gene trees under coalescence. Bioinformatics

(Oxf.) 25:971-973.

95. Kuhner, M. K. 2009. Coalescent genealogy samplers: windows into population

history. Trends Ecol. Evol. 24:86-93.

96. Langerhans B.R., Layman C.R., Langerhans A.K, Dewitt T.J. 2003. Habitat-

associated morphological divergence in two Neotropical fish species, Biol. J.

Linn. Soc. 80:689–698.

189

97. Larget B.R., Kotha S.K., Dewey C.N., Ané C. 2010 BUCKy: Gene tree/species

tree reconciliation with Bayesian concordance analysis. Bioinformatics 26:2910-

2911.

98. Leaché, A. D. & Fujita, M. K. 2010. Bayesian species delimtation in west

African forest geckos (Hemidactylus fasciatus). Proc. Roy. Soc. Sci. Ser. B.

277:3071-3077.

99. Legendre A., Anderson M.J. 1999. Distance-based redundancy analysis:

testing multispecies responses in multifactorial ecological experiments. Ecol.

Monogr. 69:1-24.

100. Librado, P. & Rozas, J. 2009. DnaSP v5: A software for comprehensive analysis

of DNA polymorphism data. Bioinformatics 25:1451-1452.

101. Liu L., Pearl D.K. 2007. Species trees from gene trees: Reconstructing Bayesian

posterior distributions of a species phylogeny using estimated gene tree

distributions, Syst. Biol. 56:504-514.

102. Liu L., Yu L. 2011. Estimating species trees from unrooted gene trees. Syst. Biol.

(in press) DOI: 10.1093/sysbio/syr027

103. Lleonart J., Salat J., Torres G.J. 2000. Removing allometric effects of body

size in morphological analysis. J. Theor. Biol. 205:85-93.

104. Losos J.B. 1990. Ecomorphology, performance capability and scaling of West

Indian Anolis lizards: an evolutionary analysis. Ecol. Monogr. 60:369–388.

105. Losos J.B., Warheitt K.I., Schoener T.W. 1997. Adaptive differentiation

following experimental island colonization in Anolis lizards. Nature 387:70-

73.

190

106. Losos J.B., Creer D.A., Glossip D., Goellner R., Hampton, A., Roberts G.,

Haskell, N., Taylor P. & Ettling J. 2000. Evolutionary implications of phenotypic

plasticity in the hindlimb of the lizard Anolis segrei Evolution 54:301-305.

107. Louis, E.J. 2011. Population genomics and speciation in yeasts. Fungal Biol. Rev.

In press doi:10.1016/j.fbr.2011.06.001

108. Maddison W.P. 1997. Gene trees in species trees. Syst Biol. 46:523-536.

109. Maddison, D. R. & Maddison, W. P. 2005. MacClade 4: Analysis of phylogeny

and character evolution. Version 4.08a. Available from http://macclade.org.

110. Maechler M., Rousseeuw P., Struyf A., Hubert M. 2005. Cluster analysis

basics and extensions, http://cran.r-project.org/web/packages/cluster/ Last

accessed 10 December 2010.

111. Martin H.A. 2006. Cenozoic climatic changes and the development of the arid

vegetation of Australia. J. Arid Environ. 66:533–563.

112. Marroig G., Cheverud J.M. 2009. Size and shape in callimico and marmoset

skulls: allometry and heterochrony in the morphological evolution of small

Anthropoids In Ford, S.M., Davis, L.C. and Porter, L.M. (eds) The Smallest

Anthropoids: The Marmoset/Callimico Radiation. Springer N.Y. U.S.A. 331-

353.

113. Mayden R.L. 1997. A hierarchy of species concepts: The denouement in the saga

of the species problem. In: Claridge M.F., Dawah H.A., Wilson M.R. (eds)

Species: The units of biodiversity. London: Chapman and Hall. 381-424.

114. Mayr E. 1942. Systematics and the origin of species, Columbia University Press

Sussex, U.K.

191

115. McArdle B., Anderson M.J. 2001. Fitting multivariate models to community

data: a comment on distance based redundancy analysis. Ecology 82:290-297.

116. McCormack J.E., Heled J., Delaney K.S., Peterson A.T., Knowles, L.L. 2010.

Calibrating divergence times on species trees versus gene trees: implications for

speciation history of Aphelocoma jays. Evolution 65:184-202.

117. McCormack J.E., Smith T.B. 2008. Niche expansion leads to small-scale adaptive

divergence along an elevation gradient in a medium-sized passerine bird, Proc. R.

Soc. B. 275:2155-2164.

118. Meglécz E. 2007. MicroFamily: A computer program for detecting flanking

region similarities among different microsatellite loci. Mol. Ecol. Notes 7:18-

20.

119. Michel A.P., Sim S., Powell T.H.Q., Taylor M.S., Nosil P., Feder J.L. 2010.

Widespread genomic divergence during sympatric speciation. Proc. Natl.

Acad. of Sci. U.S.A. 107:9724-9729.

120. Mitchell F.J. 1965. Australian geckos assigned to the genus Gehyra GRAY.

(Reptilia, Gekkonidae). Senck. Biol. 46:287-319.

121. Moritz C.M. 1984. The evolution of a highly variable sex chromosome in Gehyra

purpurascens (Gekkonidae). Chromosoma 90:111-119.

122. Moritz C.M. 1986. The population biology of Gehyra (Gekkonidae):

Chromosome change and speciation. Syst. Biol. 35:46-67.

123. Moritz C.M. 1992. The population biology of Gehyra (Gekkonidae) III. Patterns

of microgeographic variation. J. Evol. Biol. 5:661-676.

124. Mortiz, C M. 1994. Defining “evolutionarily significant units” for conservation.

192

Trends Ecol. Evol. 9:373-375.

125. Morton, S.R., Short, J, and Barker, R.D. 1995. Refugia for biological diversity in

arid and semi-arid Australia. Biodiversity Series Paper No 4. Biodiversity Unit.

Department of Environment, Sports and Territories. Australian Federal

Government.

126. Murphy R.W., Sites J.W., Buth D.G., Haufler, C.H. 1996. Proteins I: Isozyme

electrophoresis. In: Hillis, D. M., Moritz C. & Mable B. (eds). Molecular

Systematics. Sinauer Associates, Sunderland, 51–120.

127. Nagel L., Schluter D. 1998. Body size, natural selection and speciation in

sticklebacks. Evolution 52:209-218.

128. Nagy K.A. 2005. Field metabolic rate and body size. J. Exp. Biol. 208:1621-

1625.

129. Neumann N.L., 2001. Geochemical and isotopic characteristics of South

Australian Proterozoic granites: implications for the origin and evolution of

high heat-producing terrains. Ph.D. thesis (unpublished). Univ. Adelaide,

Australia.

130. Nei M. 1987. Molecular Evolutionary Genetics. Columbia University Press, New

York, 375.

131. Neilsen, R. & Wakeley, J. 2001. Distinguishing migration from isolation: a

Markov chain Monte Carlo approach. Genetics 158:885-896.

132. Nosil P., Crespi B.J. 2006. Experimental evidence that predation promotes

divergence in adaptive radiation, Proc. Natl. Acad. Sci. U.S.A. 103:9090 –

9095.

193

133. Oksanen J., Blanchet, G.F., Kindt R., Legendre P., O’Hara R.B., Simpson

G.L., Solymos P., Stevens H.H., Wagner H. 2011. Vegan: Community ecology

package, R package version 1.17-7 http://CRAN.R–

project.org/package=vegan. Last accessed 5 January 2011.

134. Oliver P.M., Sanders K.L. 2009. Molecular evidence for Gondwanan origins of

multiple lineages within a diverse Australasian gecko radiation. J. Biogeogr.

36:2044-2055.

135. Oliver P.M., Sistrom M.J., Tjaturadi B., Keliopas K. 2010. On the status and

relationships of the Gecko species Gehyra barea (Kopstein 1926), with

description of new specimens and a range extension. Zootaxa 2354:45-55.

136. O’Meara, B. C. 2010. New heuristic methods for joint species delimitation and

species tree inference, Syst. Biol. 59:59-73.

137. Oosterhout C.V., Hutchinson D., Wills P.M., Shipley P. 2004. MICRO-

CHECKER: software for identifying and correcting genotyping errors in

microsatellite data. Mol. Ecol. Notes 4:535-538.

138. O'Meara B.C. 2010. New heuristics methods for joint species tree inference and

species delimitation. Syst. Biol. 59:59-73.

139. Palkovacs E.P., Post D.M. 2009. Experimental evidence that phenotypic

divergence in predators drives community divergence in prey. Ecology

90:300-305.

140. Petit, R. J. & Excoffier, L. 2009. Gene flow and species delimitation. Trends

Ecol. Evol. 24:386-393.

194

141. Pfennig D.W., Pfennig K.S. 2010. Character displacement and the origins of

diversity. Am. Nat. 176:26-44.

142. Posada, D., Crandall, K.A. 1998. Modeltest: testing the model of DNA

substitution. Bioinformatics 14:817–818.

143. Posada D. 2008. jModelTest: Phylogenetic Model Averaging. Mol. Biol. Evol.

25:1253-1256.

144. Primary Industries and Resources South Australia (PIRSA) 2009. Seeking a

balance: Conservation and resource use in the Northern Flinders Ranges,

Adelaide: Government of South Australia

145. Pritchard J.K., Stephens M., Donnelly P. 2000. Inference of population

structure using multilocus genotype data. Genetics 155:945–959.

146. Prosperi M.C., Prosperi L., Bruselles A., Abbate I., Rozera G., Vincenti D.,

Solmone M.C., Capobianchi M.R., Ulivi G. 2011. Combinatorial analysis and

algorithms for quasispecies reconstruction using next-generation sequencing.

BMC Bioinformatics 12:5.

147. Rambaut A. 2009. Figtree v1.4. Available from http://tree.bio.ed.ac.uk/ Last

accessed 28 May 2011.

148. Rambaut, A., Drummond, A.J. 2007. Tracer v1.4.

http://beast.bio.ed.ac.uk/Tracer. Last accessed 30 November 2010.

149. Ray, J. 1686. Historia Plantarum. In Lankester (ed). The correspondence of John

Ray, 1842. The Ray Society, London.

150. R Core Development Team. 2011. R: A Language and Environment for

Statistical Computing, R Foundation for Statistical Computing, Vienna,

195

Austria. http://www.R-project.org Last accessed 7 September 2011.

151. Reisberg L.H. 2001. Chromosomal rearrangements and speciation, Trends

Ecol. Evol. 16:351:358.

152. Rhymer J.M., Simberloff D. 1996. Extinction by hybridization and

introgression. Annu. Rev. Ecol. Syst. 27:83-109.

153. Rice A.M., Pfennig D.W. 2010. Does character displacement initiate

speciation? Evidence of reduced gene flow between populations experiencing

divergent selection. J. Evol. Biol. 23:854-865.

154. Richardson B., Baverstock P., Adams M. 1986. Allozyme Electrophoresis.

Academic Press, Sydney, 410.

155. Rissler L.J., Apodaca J.J. 2007. Adding more ecology into species delimitation:

Ecological niche models and phylogeography help define cryptic species in the

black salamander (Aneides flavipunctatus). Syst. Biol. 56:924-42.

156. Ronquist F., Huelsenbeck J.P. 2003. MRBAYES 3: Bayesian phylogenetic

inference under mixed models. Bioinformatics 19:1572-1574.

157. Rosenberg N.A. 2004. DISTRUCT: a program for the graphical display of

population structure. Mol. Ecol. Notes 4:137–138.

158. Rousset F. 2008. Genepop'007: a complete reimplementation of the Genepop

software for Windows and Linux. Mol. Ecol. Res. 8:103-106.

159. Rowe K.C., Aplin K.P., Baverstock P.R., Moritz C. 2010. Recent and rapid

speciation with limited morphological diversity in the genus Rattus. Syst. Biol.

60:188-203.

196

160. Rundle H.D., Schluter D. 1997. Reinforcement of stickleback mate

preferences: sympatry breeds contempt. Evolution 52:200-208.

161. Rowe, K.C., Reno, M.L., Richmond, D.M., Adkins, R.M. & Steppan S.J. 2008.

Pliocene colonization and adaptive radiations in Australia and New Guinea

(Sahul): multilocus systematics of the old endemic rodents (Muroidea: Murinae).

Mol. Phylogenet. Evol. 47:84-101.

162. Rozas J. 2009. DNA Sequence Polymorphism Analysis using DnaSP. In Posada

D. (ed) Bioinformatics for DNA Sequence Analysis; Methods. In Molecular

Biology Series Vol. 537. Humana Press, NJ, USA. 337-350.

163. Rozas J., Sánchez-DelBarrio J.C., Messeguer X., Rozas R. 2003. DnaSP, DNA

polymorphism analyses by the coalescent and other methods. Bioinformatics

19:2496–2497.

164. Russell A.P., Bauer, A.M. 2002. Underwood’s classification of the geckos: A 21st

century appreciation. Bull. Br. Mus. (Nat. Hist.) Zool. 68:113-121.

165. Sanders K.L., Lee M.S.Y., Leys R., Foster R., Keogh S.J. 2008. Molecular

phylogeny and divergence dates for Australasian elapids and sea snakes

(Hydrophiinae): evidence from seven genes for rapid evolutionary radiations. J.

Evol. Biol. 21:682-695.

166. Schlick-Steiner, B. C., Steiner, F. M., Seifert, B., Stauffer, C. Christian, E. &

Crozier, R. H. 2010. Integrative taxonomy; a multidisciplinary approach to

exploring biodiversity. Annu. Rev. Entomol. 55:421-438.

167. Schluter D. 1994. Experimental evidence that competition promotes adaptive

divergence, Science 266:798–801.

197

168. Schluter D. 2000. The ecology of adaptive radiation. Oxford Uni. Press, New

York, U.S.A.

169. Schluter D. 2010. Resource competition and coevolution in sticklebacks. Evo.

Edu. Outreach 3:54-61.

170. Shaffer H.B., Thomson R.C. 2007. Delimiting species in recent radiations. Syst.

Biol. 56:896-906.

171. Simpson G.G. 1951. The species concept. Evolution. 5:285-298.

172. Sistrom M., Hutchinson M., Hutchinson R., Donnellan S. 2009. Molecular

phylogeny of Australian Gehyra (Squamata: Gekkonidae) and taxonomic

revision of Gehyra variegata in south-eastern Australia. Zootaxa 2277:14-32.

173. Sites J.R., Moritz C.M. 1987. Chromosomal evolution and speciation revisited.

Syst. Biol. 36:153-174.

174. Skinner, A., Hugall, A.F. & Hutchinson, M.N. 2011. Lygosomine phylogeny and

the origins of Australian scincid lizards. J. Biogeogr. 38:1044-1058.

175. Smith M.J., Roberts J.D. 2003. No sexual size dimorphism in the frog Crinia

georgiana (Anura: Myobatrachidae): An examination of pre- and

postmaturational growth. J. Herpetol. 37:132-137.

176. Smouse P.E., Long J.C., Sokal R.R. 1986. Multiple regression and correlation

extensions of the Mantel test of matrix correspondence. Syst. Zool. 35:627–

632.

198

177. Sota T., Takami Y., Kubota K., Ujiie M., Ishikawa R. 2000. Interspecific body

size differentiation in species assemblages of the carabid subgenus

Ohomopterus in Japan. Popul. Ecol. 42:279-291.

178. Stamatakis A. 2006. RAxML-VI-HPC: Maximum likelihood-based phylogenetic

analyses with thousands of taxa and mixed models. Bioinformatics. 22:2688–

2690.

179. Stamatakis A., Hoover P., Rougemont J. 2008. A rapid bootstrap algorithm for the

RAxML web-servers. Syst. Biol. 75:758–771.

180. Steindachner F. 1867. Part 3. Reptiles, in Wüllerstorf-Urbair, B. von (ed.) Reise

der Österreichischen Fregatte Novara um die Erde in den Jahren 1857, 1858,

1859. Zoologischer Teil. I. Wirbelthiere. State Printer, Vienna.

181. Stephens, M., Smith, N. & Donnelly, P. 2001. A new statistical method for

haplotype reconstruction from population data. Am. J. Hum. Genet. 68:978-989.

182. Stephens, M. & Scheet, P. 2005. Accounting for decay of linkage disequilibrium

in haplotye inference and missing-data imputation. Am. J. Hum. Genet. 76:449-

462.

183. Storr G.M. 1982. Two new Gehyra (Lacertilia: Gekkonidae) from Australia. Rec.

West. Aust. Mus. 10:53–59.

184. Strasburg, J. L. & Reiseberg, L. H. 2010. How robust are “isolation with

migration” analyses to violations of the IM model? A simulation study. Mol.

Biol. Evol. 27:297-310.

185. Stuart-Smith J., Swain R., Wapstra E. 2007. The role of body size in

competition and mate choice in an agamid with female-biased dimorphism,

199

Behaviour 144:1087-1102.

186. Suzuki R., Shimodaira H. 2006. Pvclust: An R package for hierarchical

clustering with p-values via multiscale bootstrap resampling, R package

version 1.2-1. http://www.is.titech.ac.jp/~shimo/prog/pvclust/ Last accessed

25 November 2010.

187. Takahashi T., Watanabe K., Munehara H., Ruber L., Hori, M. 2009. Evidence for

divergent natural selection of a Lake Tanganyika cichlid inferred from repeated

radiations in body size. Mol. Ecol. 18:3110-3119.

188. Taylor E.H. 1963. The lizards of Thailand. Univ. Kans. Sci. Bull. 44:687–1076.

189. Tiedemann F., Hãupl M. 1980. Typenkatalog der herpetologischen Sammlung.

Teil 11. Reptilia. Kat. Wiss. Samml. Nathist. Mus. Wien, Vertebrata, 4:1–80.

190. Tiedemann F., Häupl M., Grillitsch H. 1994. Katalog der Typen der

herpetologischen Sammlung nach dem Stand vom 1. Jänner 1994. Kat. Wiss.

Samml. Nathist. Mus. Wien. 10:1–110.

191. Therneau T., Atkinson B. 2002. rpart ver. 3. Mayo Foundation for Medical

Education and Research.

http://www.mayoresearch.mayo.edu/mayo/research/biostat/splusfunctions.cfm

Last accessed 28 November 2010.

192. Thibert-Plante, X. & Hendry, A.P. 2008. Five questions on ecological speciation

addressed with individual-based simulations. J. Evol. Biol. 22:109-123.

193. Thomson, R.C., Wang, I.J. & Johnson, J.R. 2010. Genome-enabled development

of DNA markers for ecology, evolution and conservation. Mol. Ecol. 19:2184-

2195.

200

194. Thorpe R.S., Baez M. 1987. Geographic Variation within an island: univariate

and multivariate contouring of scalation, size, and shape of the lizard Gallotia

galloti. Evolution. 41:256-268.

195. Ting C.T., Tsaur S.C., Wu M.L., Wu C.I. 1998. A rapidly evolving homeobox

at the site of a hybrid sterility gene. Science 282:1501-1504.

196. Toon, A., Perez-Losada, M., Schweitzer, C.E., Feldmann, R.M., Carlson, M.

& Crandall, K.A., 2010. Gondwanan radiation of the Southern Hemisphere

crayfishes (Decapoda: Parastacidae): edvidence from fossils and molecules. J.

Biogeogr. 37:2275-2290.

197. Townsend, T. M., Alegre, E. R., Kelley S. T., Weins, J. J. & Reeder, T. W.

2008. Rapid development of multiple nuclear loci for phylogenetic analysis

using genomic resources: an example from squamate reptiles. Mol.

Phylogenet. Evol. 47:129-142.

198. Turner T.L., Hahn M.W., Nuzhdin S.V. 2005. Genomic islands of speciation

in Anopheles gambiae. PloS Biol. 3:1572-1578.

199. Underwood G. 1954. On the classification and evolution of geckos. Proc. Zool.

Soc. Lond. 124:469-492.

200. Vanhooydonck B., Van Damme R. 1999. Evolutionary relationships between

body shape and habitat use in lacertid lizards. Evol. Ecol. Res. 1:785-805.

201. Vavrek M. 2010. fossil: Palaeoecological and palaeogeographical analysis

tools. R package version 0.3.3 http://CRAN.R –project.org/package=fossil.

Last accessed 12 December 2010.

202. Venables W.N., Ripley B.D. 2002. Modern applied statistics with S. 4th

201

Edition, Springer, N. Y. U.S.A.

203. Voris H.K. 2000. Maps of Pleistocene seas levels in Southeast Asia: shorelines,

river systems and time durations. J. Biogeog. 27:1153-1167.

204. Ward J.H. 1963. Hierarchical grouping to optimize an objective function. J.

Amer. Stat. Assoc. 58:236−244.

205. Wells R., Wellington C.R. 1985. A classification of the Amphibia and Reptilia of

Australia. Aust. J. Herp. Supplementary Series 1-61.

206. Wiens J.J., Morrill M.C. 2011. Missing data in phylogenetic analysis: reconciling

results from simulations and empirical data. Syst. Biol. (in press)

DOI:10.1093/sysbio/syr025

207. Wilson S., Swan G. 2010. A complete guide to reptiles of Australia, 3rd

edition,

New Holland, Australia.

208. Woinarski, J.C.Z., Connors, G., Oliver, B. (1996b) The reservation status of plant

species and vegetation types in the Northern Territory. Aust. J. Bot. 44:673–689.

209. Wu C.I. 2001. The genic view of the process of speciation. J. Evol. Biol. 14:851-

865.

210. Yandell, B. S. 1997. Practical data analysis for designed experiments. London:

Chapman & Hall

211. Yang Z., Rannala B. 2010. Bayesian species delimitation using multilocus

sequence data. Proc. Natl. Acad. Sci. U.S.A. 107:9264-9269.

212. Yeates, D. K., Seago, A., Nelson, L. Cameron, S. L., Joeseph, L. & Truman, J. W.

H. 2011. Integrative taxonomy or iterative taxonomy? Syst. Entomol. 36:209-217.

202

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

Genus species Map

code

mtDNA karyotype Allozyme

OTU

ABTC No. Voucher No. Locality Country State declat declong

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

Station

Australia NT -16.66 135.85

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-

70

SAMAR33529,

R38943–44

Lancoona Station Australia NSW -33.36 145.883

Gehyra lazelli L3 Y 10 ABTC18031-

2

SAMAR38984–6 Middleback Range Australia SA -33.183 137.1

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 -

31.9741666

7

140.3161

Gehyra lazelli L9 Y ABTC89675 SAMAR61563 11.3k NNW

Penong

Australia SA -31.9144 132.892

Gehyra lazelli L10 Y ABTC39325 SAMAR52366 4.7k W Parachilna

Hill

Australia SA -31.1327 138.54916

Gehyra lazelli L11 Y 2n=44 ABTC38861 SAMAR51801 9k SSE

Mudlapena Spring

Australia SA -30.68972 138.81583

Gehyra lazelli L12 Y 2n=44 ABTC39130 SAMAR52012 4.7k NNE Warden

Hill

Australia SA -30.4038 139.2352778

Gehyra lazelli L13 Y ABTC74062 SAMAR52962 Arkaroola Australia SA -30.11861 139.4483

Gehyra membranacruralis Y ABTC50301 AMSR135529 near Sibilanga

Mission

PNG SP

Gehyra minuta 2n=42a* 1 ABTC31246,

103196,

103199,

103213-4

CM1235, 1257, 1280,

1383, 1391

The Granites Australia NT -20.5722 130.3501

Gehyra minuta Y ABTC61706 NTMR13647 80k S Renner

Springs

Australia NT -18.9469 134.1227

Gehyra montium M1 Y 2n=42a ABTC41961-

2, 4

SAMAR48732-3, 5;

SAMAR51537,

Mt Lindsay Australia SA -27.025 129.875

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

1357

Warburton Australia WA -26.1505 126.5474

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

1377

Giles Australia WA -25.03 128.3

Gehyra montium M10 2n=42a* 2 CM1261 CM1338 Rawlinson Ranges Australia WA -24.8077 127.7846

Gehyra mutilata Y ABTC32321 Dumaguete,

Negros Island

Philippines

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

Plateau

Australia NT -13.383 133.383

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

Newman

Australia WA -

22.2230555

6

118.9552778

Gehyra purpurascens P1 ABTC52233 SAMAR31984 Yumbarra CP Australia SA -

31.7719444

4

133.4719444

Gehyra purpurascens P2 Y ABTC38217 SAMAR50278 7k SSE Mt

Deception

Australia SA -

30.7602777

8

138.286944

Gehyra purpurascens Y ABTC38215 SAMAR50277 7k SSE Mt

Deception

Australia SA -

30.7602777

8

138.2869444

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

Kunytjanu

Australia SA -26.4877 129.1736111

Gehyra purpurascens P6 Y ABTC42153 SAMAR50164 14.4k S Sentinel

Hill

Australia SA -26.21083 132.4427778

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,

Everard Ranges

Australia SA

Gehyra robusta Y ABTC11946 SAMAR34227 7k E Mount Isa Australia Qld -20.716 139.55

Gehyra variegata V1 Y 2n=40a* 5 ABTC03666-

7/71

SAMAR38941–2/45 Lancoona Station Australia NSW -32.366 145.883

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

Mudlapena Spring

Australia SA -30.64694 138.8480556

Gehyra variegata V6 6 ABTC14117-

24

SAMAR38934–40 Italowie Gap Australia SA -30.56 139.16

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

Nudlamutana Well

Australia SA -

30.3741666

7

139.3505556

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

Bore

Australia SA -30.3211 138.78611

Gehyra variegata V11 Y 2n=40a ABTC39077 SAMAR51968 1.9k SW Reedy

Hole Springs

Camp

Australia SA -30.26527 138.825

Gehyra variegata V12 Y 2n=40a ABTC39173 SAMAR51781-2 10.4k SW

Yudnamutana

Bore

Australia SA -30.225 139.19194

Gehyra variegata V13 Y 2n=40a ABTC39184 SAMAR51790 2.5k WSW

Yudnamutana

Bore

Australia SA -30.174166 139.251

Gehyra variegata V14 Y 2n=40a ABTC39181 SAMAR51760 1.75k W

Yudnamutana

Bore

Australia SA -30.17083 139.257

Gehyra variegata V15 Y 6 ABTC14870-

1/5

SAMAR38929–31 Yudnamatana Australia SA -30.166 139.283

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

Cheesman

Australia SA -27.3142 130.265

Gehyra variegata V19 Y ABTC79922 SAMAR56497 5.6k W Mount

Hoare

Australia SA -27.0575 129.6438

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

Indulkana

Australia SA -26.86916 133.0225

Gehyra variegata 2n=40a SAMAR51842, 51881 Mt Fitton Australia SA

Gehyra xenopus Y ABTC13017 SAMAR53962 10k S Cape

Voltaire

Australia WA -14.35 125.583

205

Hemiphylloda

ctylus

typhus ABTC32736 No voucher Suva Fiji

Hemiphylloda

ctylus

typhus ABTC49760 BPBM12995 No location

Lepidodactylu

s

lugubris ABTC32735 No voucher Suva Fiji

Lepidodactylu

s

lugubris ABTC50488 AMSR136386 Honiara,

Guadalcanal

Solomon

Islands

206

Appendix 2: Details of samples and specimens used in Chapter 3.

ABTC

Number

Registration

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

ABTC77005 SAMAR55694 Gehyra Clade 4

13.4k NNE Hughenden on Kennedy

Developmental Road Qld -20.79 144.31 Y Y Y

ABTC77065 SAMAR55751 Gehyra Clade 4

35k S Julia Creek on Julia Creek-Kynuna

Road Qld -20.96 141.83 Y Y

ABTC77066 SAMAR55752 Gehyra Clade 4

35k S Julia Creek on Julia Creek-Kynuna

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

ABTC72952 SAMAR54530 Gehyra Clade 5

4.5k N Station Creek crossing, Prarie-

Muttaburra Road Qld -22.04 144.62 Y Y Y

ABTC72961 SAMAR54546 Gehyra Clade 5

14k NW Longreach on Landsborough

Highway Qld -23.35 143.20 Y Y Y Y

ABTC72962 SAMAR54547 Gehyra Clade 5

14k NW Longreach on Landsborough

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

ABTC77006 SAMAR55695 Gehyra Clade 5

13.4k NNE Hughenden on Kennedy

Developmental Road Qld -20.79 144.31 Y Y

ABTC77007 SAMAR55696 Gehyra Clade 5

13.4k NNE Hughenden on Kennedy

Developmental Road Qld -20.79 144.31 Y Y Y

ABTC79486 SAMAR55905 Gehyra Clade 5

9k N New South Wales/Queensland border

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.

ABTC Regno mtDNA microsatellites morphology species Locality Longitude Latitude

Map

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

ABTC39291 SAMAR52214 yes lazelli

2.2k ESE Horn Camp Ruin, Alpana

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

ABTC108039 R64955 yes yes ornata

Pepegoona Gorge, Northen Flinders

Ranges 139.60188 -30.08139 10

ABTC108040 R64956 yes yes ornata

Pepegoona Gorge, Northen Flinders

Ranges 139.60188 -30.08139 10

ABTC108037 R64954 yes yes ornata

Pepegoona Gorge, Northen Flinders

Ranges 139.60251 -30.08078 10

ABTC108033 R64944 yes yes ornata

Pepegoona Gorge, Northen Flinders

Ranges 139.60442 -30.08026 10

ABTC108035 No voucher yes variegata

Pepegoona Gorge, Northen Flinders

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