POPULATION STRUCTURE AND GENETIC DIVERSITY OF SOUTHEAST QUEENSLAND POPULATIONS OF THE WALLUM FROGLET, CRINIA TINNULA (TSCHUDI). Juanita Renwick B. App. Sci. (Hons) School of Natural Resource Sciences Queensland University of Technology Brisbane, Australia This dissertation is submitted as a requirement of the Doctor of Philosophy Degree 2006
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POPULATION STRUCTURE AND GENETIC DIVERSITY OF
SOUTHEAST QUEENSLAND POPULATIONS OF THE
WALLUM FROGLET, CRINIA TINNULA (TSCHUDI).
Juanita Renwick
B. App. Sci. (Hons)
School of Natural Resource Sciences
Queensland University of Technology
Brisbane, Australia
This dissertation is submitted as a requirement of the
Doctor of Philosophy Degree
2006
ii
KEYWORDS
Crinia tinnula; population genetic structure; phylogeography; Pliocene; mitochondrial DNA;
12S; COI; wallum; southeast Queensland.
iii
ABSTRACT
Genetic diversity is a fundamental attribute that contributes to a species evolutionary
survival. In recent times, conservation managers have recognized the need to preserve
genetic diversity of declining species, and have also acknowledged the utility of genetic
markers for describing genetic and ecological relationships within and among populations.
Information obtained from genetic studies can be used in conjunction with information on
population demography, land use patterns and habitat distribution to develop effective
management strategies for the conservation of species in decline.
The wallum froglet, Crinia tinnula, is one of Australia’s smallest habitat specialist anurans.
In recent years there has been a dramatic decrease in population numbers of this species.
The habitat to which C.tinnula is endemic (‘wallum’ habitat) is restricted to low coastal
plains along the southeast Queensland and northern New South Wales coastline. As human
populations in this region expanded, the coastal areas have undergone significant
development and large areas of wallum habitat have been cleared. The effect has been to
convert once largely continuous patches of coastal heathland in to a matrix of small habitat
patches within an area undergoing rapid urban expansion.
This study aimed to document levels and patterns of genetic diversity and to define the
population structure of C.tinnula populations within southeast Queensland, with the
objective of defining possible conservation management units for this species. Results from
12S and COI mitochondrial markers clearly showed that two distinct evolutionary lineages
of C.tinnula are present within southeast Queensland. The high level of divergence between
lineages and strict geographic partitioning suggests long term isolation of C.tinnula
populations. It is hypothesized that ancestral C.tinnula populations were once confined to
wallum habitat refugia during the Pliocene resulting in phylogeographic delineation of
‘northern’ and ‘southern’ C.tinnula clades.
Populations within each geographic region show evidence of range contraction and
expansion, with subsequent restricted gene flow. Levels of genetic diversity appear, largely,
to be the product of historical associations rather than contemporary gene flow. A revision of
the current systematics of C.tinnula is required to ensure that discrete population groups are
recognized as distinct evolutionary lineages and will therefore be protected accordingly.
3.2 Materials and methods.............................................................................................. 47
3.2.1 Sampling localities and sample numbers ........................................................... 47
3.2.2 DNA extraction and amplification of 12S rRNA mitochondrial DNA fragment .......................................................................................................................... 48
3.2.3 Temperature gradient gel electrophoresis (TGGE), Heteroduplex analysis (HA) and Sequencing..................................................................................................... 49
3.2.4 Data analysis ...................................................................................................... 50
3.4.1 Broad scale population structure........................................................................ 73
3.4.2 Population structure within regions ................................................................... 77
3.4.3 Evolution of C.tinnula ....................................................................................... 80
Chapter Four: Local Scale Population Structure and Gene Flow Inferred from Mitochondrial Cytochrome oxidase subunit I (COI) Sequence Data.................................................82
4.2 Materials and methods.............................................................................................. 85
4.2.1 Sample localities and sample numbers .............................................................. 85
4.2.2 DNA extraction and amplification of COI mitochondrial DNA fragment ........ 86
4.2.3 Temperature gradient gel electrophoresis (TGGE), Heteroduplex analysis (HA) and Sequencing...................................................................................................... 87
4.2.4 Data analysis ...................................................................................................... 89
FOLD OUT REFERENCE MAP OF SOUTHEAST QUEENSLAND C.TINNULA
POPULATIONS INCLUDED ON LAST PAGE
viii
LIST OF FIGURES
Figure 2.1. Habitat structure of wallum heathlands in southeast Queensland ..............................16
Figure 2.2. Habitat characteristics of wallum heathland in southeast Queensland .......................18
Figure 2.3. Conservative summary of the phylogenetic relationships among Crinia species’ based on combined ND2 and 12S sequence data .......................................................22
Figure 2.5. Southeast Queensland sampling sites for C.tinnula. ................................................26
Figure 2.6. Example of a parallel TGGE .....................................................................................34
Figure 3.1. Alignment of variable sites from the 362bp of mitochondrial 12S sequenced for C.tinnula .....................................................................................................................55
Figure 3.2. Locations of C.tinnula samples obtained from the South Australian museum...........62
Figure 3.3. Neighbour-joining (NJ) tree showing inferred phylogenetic relationships among C.tinnula 12S mtDNA haplotypes..............................................................................66
Figure 3.4. Nested cladogram of southeast Queensland and northern New South Wales C.tinnula 12S mtDNA haplotypes..............................................................................69
Figure 3.5. 12S mtDNA mismatch distribution for southern mainland and Bribie Island populations .................................................................................................................72
Figure 3.6. mtDNA haplotype frequencies of Oxleyan Pygmy Perch populations from southeast Queensland .................................................................................................75
Figure 4.1. Alignment of variable sites from the 543bp of mitochondrial COI sequenced for C.tinnula .....................................................................................................................92
Figure 4.2. Alignment of amino acid sequence for 543bp mitochondrial COI sequenced for C.tinnula .....................................................................................................................93
Figure 4.3. Nested Cladogram for northern C.tinnula COI mtDNA haplotypes ........................102
Figure 4.4. Nested Cladogram for southern C.tinnula COI mtDNA haplotypes ........................105
Figure 4.5. COI mtDNA mismatch distribution for southern mainland and Bribie Island populations ...............................................................................................................106
Figure 4.6. Neighbour-joining tree showing inferred phylogenetic relationships among C.tinnula COI mtDNA haplotypes ...........................................................................108
Figure 4.7. Channels of Brisbane and Pine Rivers across the Moreton Bay plain......................113
Figure 4.8. Sea level fluctuations over the last 200 000 years. ...................................................113
ix
LIST OF TABLES
Table 2.1. Collection sites and sample size for C.tinnula populations .........................................28
Table 3.1. C.tinnula populations and sample sizes for 12S mtDNA analyses..............................47
Table 3.2. Pairwise nucleotide differences among C.tinnula and C.parinsignifera TGGE reference samples .......................................................................................................50
Table 3.3. Average nucleotide frequencies for myobatrachid 12S mtDNA sequences ................53
Table 3.4. Distribution of 12S mtDNA haplotypes for southeast Queensland populations of C.tinnula .....................................................................................................................57
Table 3.5. 12S mtDNA haplotype diversity and nucleotide diversity ...........................................58
Table 3.6. Pairwise genetic distances for C.tinnula 12S mtDNA haplotypes................................59
Table 3.7. AMOVA showing partitioning of 12S mtDNA variation within and among regions of southeast Queensland populations of C.tinnula ........................................61
Table 3.8. Range of pairwise genetic distances for New South Wales C.tinnula 12S mtDNA haplotypes...................................................................................................................63
Table 3.9. Average genetic distances between C.tinnula population groups.................................64
Table 3.10. Pairwise genetic distances for C.parinsignifera and C.signifera 12S mtDNA haplotypes...................................................................................................................65
Table 3.11. Permutational chi-squared probabilities for geographical structure of clades ...........70
Table 4.1. C.tinnula populations and sample sizes for COI mtDNA analyses ..............................85
Table 4.2. Average pairwise differences within and between C.tinnula population groups..........88
Table 4.3. Average nucleotide frequencies for myobatrachid COI mtDNA sequences................90
Table 4.4. Average genetic distances between C.tinnula population groups.................................95
Table 4.5. AMOVA showing partitioning of variation within and among regions of southeast Queensland populations of C.tinnula. ........................................................................96
Table 4.6. Distribution of COI mtDNA haplotypes for C.tinnula populations..............................97
Table 4.7. COI mtDNA haplotype diversity and nucleotide diversity..........................................98
Table 4.8. Pairwise genetic distances for C.tinnula COI mtDNA haplotypes .............................100
Table 4.9. AMOVA showing the partitioning of variation within and among southern population groups of C.tinnula.................................................................................104
Table 4.10. Permuational chi-squared probabilities for geographical structure of southern clades ........................................................................................................................106
x
Table 4.11. Haplotype diversity and nucleotide diversity for 12S and COI mtDNA haplotypes.................................................................................................................115
xi
LIST OF APPENDICES
Appendix 1: Microsatellite Chapter: Fine Scale Population Structure and Contemporary Gene Flow Among Wallum Froglet Populations .....................................................129
Appendix 2: Alignment of myobatrachid frogs to check the mitochondrial 12S sequenced for C.tinnula is not a nuclear insert ................................................................................137
Appendix 3: Alignment of variable sites from 12S mitochondrial sequence data for southeast Queensland and New South Wales C.tinnula samples.............................................139
Appendix 3.1: Pairwise genetic distances for 12S mtDNA southeast Queensland and New South Wales haplotypes ...........................................................................................140
Appendix 4: Permuational chi-squared probabilities for geographical structure of the clades identified in Figure 3, Chapter 4...............................................................................144
xii
STATEMENT OF ORIGINAL AUTHORSHIP
This work has not been previously submitted for a degree or diploma at any other
educational institution. To the best of my knowledge, this thesis contains no material from
another source except where due reference is made.
___________________
Juanita Renwick
January 2006
xiii
ACKNOWLEDGEMENTS
I would like to thank my supervisor Associate Professor Peter Mather for all his time,
patience and words of encouragement throughout my PhD candidature. To all those in the
Ecology department and the genetics lab, a huge thank you for all the support and guidance,
especially Nat Baker for all the endless hours of listening and more than welcome advice.
To crazy ADD and Ang Duffy – thanks for keeping me sane. To Shaun Meredith, thanks for
all your support and for helping me to believe that one person can change the world. A big
thank you to all the willing (and not so willing) people that helped out in the field; Amanda,
Danny, Dave, Pete, Shaun, Paul, Traci Jo, Adam, Ed Meyer, Jo, Craig, Geoff, Grant, Simon,
….I apologise, once again, for the leeches and the sandflies, and I assure you that Crinia
tinnula are not just a figment of my imagination. Thank you to Rod Hobson, Omar and all
the rangers on Fraser Island that always made us feel welcome, you guys do a fantastic job!
Thank you to Harry Hines at the EPA for helping with permits and to Dr. Mike Mahony for
allowing me to use the SA museum C.tinnula samples. Thank you to my Mildura family and
friends, who gave me love, support and encouragement when I needed it the most. Thank
you to my family who have endured many of the long hours and late nights, and also the
highs and the lows of this journey. A very special thank you to my Nana Beck, who has
always been an inspiration, and who showed me that no mountain is too high or too steep to
climb. This is for Kahlua.
Chapter One: General Introduction
1
CHAPTER ONE
1 GENERAL INTRODUCTION
1.1 RELEVANCE OF GENETICS TO CONSERVATION BIOLOGY
Understanding genetic and ecological relationships among populations is important for
effective management of natural systems and the development of appropriate conservation
strategies for declining species. In the past, management strategies for threatened species
have focused primarily on protecting declining populations and on maintaining areas of
natural habitat in an attempt to alleviate decreases in population numbers due to
demographic and/or environmental stochasticity (Marcot 1992; Richards et al. 1993). At
this time, it was believed that demographic and environmental factors were likely to have a
greater influence on extinction probability of natural populations before genetic deterioration
imposed a serious threat (Lande 1988). There is now compelling evidence, however, to
support the argument that genetic changes in small populations can play a significant role in
determining population survival (Frankham 1995; Saccheri et al. 1998). Consequently, over
the last decade substantial efforts have been directed towards conserving the genetic
diversity of species and using genetic information to make more informed decisions about
how threatened species should be managed (McNeely et al. 1990; Driscoll 1998; Gaudeul et
al. 2000).
Genetic diversity is a fundamental attribute that contributes to a species evolutionary
longevity (Frankham et al. 2002; Hansson and Westerberg 2002; Reed and Frankham 2003).
Genetic variation is important for maintaining high levels of fitness and allows populations
to adapt to changing environmental conditions (Mitton and Grant 1984; Frankham 1995,
1996). Studies have shown that in small, relatively isolated populations, loss of genetic
diversity and genetic factors associated with small population size can contribute to a
population’s risk of extinction via factors such as susceptibility to disease and a decline in
fitness associated with increased homozygosity (Frankel and Soule 1981; Quattro &
Vrijenhoek 1989; Newman and Pilson 1997; Saccheri et al. 1998; Eldridge et al. 1999). A
primary aim of present-day conservation management strategies therefore, is to preserve
genetic diversity to increase a species chance of long term survival.
Conservation genetic studies use genetic markers to describe levels and patterns of diversity,
which in turn can identify populations with greater levels of genetic variation and also
identify populations of concern (with respect to inbreeding and loss of diversity). Genetic
markers can also be useful for describing population structure and to identify appropriate
Chapter One: General Introduction
2
genetic management units for conservation, and also to provide information on a species’
biology. The availability of a wide range of markers which differ in mode of inheritance,
rate of evolution, selective neutrality and applicability for use at various levels of scale (e.g.
population level versus species level) means that many questions relating to a species
biology and ecology can be answered using genetic data. Information obtained from genetic
data can then be used in conjunction with information on population demographics, land use
patterns and habitat distribution to develop effective management strategies for the
conservation of species in decline (Kretzmann et al. 1997; Morales et al. 1997; Shaffer et al.
2000).
1.2 POPULATION GENETIC STRUCTURE
One of the more important advances in the field of conservation genetics has been the move
away from quantifying genetic diversity at the species level to recognising that genetic
diversity also needs to be documented at the level of the population. Populations often show
some degree of spatial structure (discontinuity) across their natural range (Andrewartha and
Birch 1954; Harrison 1989; Bos and Sites 2001). Spatial structure in conjunction with
natural heterogeneity of landscapes and inherent population dynamics (genetic drift,
selection, inbreeding), interact to produce varying levels and patterns of genetic diversity
among populations (Frankham et al. 2002).
For populations which have been affected by habitat fragmentation, the variability in levels
and patterns of genetic diversity among populations is often increased. Fragmentation of
natural habitat commonly results in the formation of remnant patches of habitat surrounded
by human altered environments (McKenzie and Cooper 1995; Briggs 1996). The change in
habitat and population spatial dynamics is often associated with increased isolation among
populations and reductions in population size; both of which can contribute to a loss of
genetic diversity. In conjunction with loss of diversity, fragmentation may also cause a
change in how genetic variation is partitioned. Allele frequencies within populations can
change via processes such as population bottlenecks (Allendorf 1986) and different
populations consequently may retain different alleles and haplotypes. The spatial isolation
of populations caused by fragmentation can also lead to genetic differentiation due to
fixation of different alleles in different populations via the process of genetic drift (Wright
1931; Avise 1994).
Chapter One: General Introduction
3
Recent studies have identified that levels and patterns of genetic variation can also vary
naturally depending on the geographic positioning of populations in relation to the species
natural range. Hoffman and Blouin (2004) showed that peripheral populations of the
Northern leopard frog, Rana pipiens, tended to posses lower diversity than did interior
populations owing to isolation, founder effects and chronically smaller population sizes.
In many cases it is not possible (or cost effective) to conserve all populations of a threatened
species and therefore, it is necessary to determine where management would be most
effective for ensuring the continued survival of a species. Describing genetic variation at the
population level allows a better understanding of the levels of diversity within a species and
a comprehensive understanding of how that diversity is distributed spatially across a species
range (Moritz 1994).
Describing genetic variation at the population level has also been beneficial in studies where
there may be taxonomic uncertainty. Since genetic analysis has become more common in
ecological research there have been many studies which have shown that designation of
species based on morphological or biogeographical data do not always correspond to
observed patterns of genetic differentiation (e.g. the existence of cryptic species; Green et al.
1996, 1997; Gleeson et al. 1999; Burbidge et al. 2003). If taxonomic relationships are
questionable, it is possible that subspecies or populations of evolutionary significance may
go undetected and result in inadequate management and loss of diversity that cannot be
replaced. Sampling at the population level is more likely to highlight genetic anomalies
which may identify cryptic species, particularly for species which exist in sympatry. It is
necessary for effective conservation management that we understand what it is we are
attempting to conserve.
For conservation purposes it is important to document not only the levels of variation within
a species but also to understand how genetic variation is partitioned spatially among
populations, i.e. to determine population genetic structure. Describing population genetic
structure enables us to make inferences about levels and patterns of dispersal among
populations, the potential for diversification and differentiation among populations and the
evolutionary history of populations (Avise 1992; Bossart and Prowell 1998). It is also
important to understand the ecological and evolutionary processes which may have shaped
the patterns of population structure (Avise 1989; Moritz 1994b, 1995).
Population genetic structure is defined by the partitioning of genetic variation among
populations (often defined by geographic boundaries) and results from the product of both
Chapter One: General Introduction
4
contemporary and historical gene flow. The level and pattern of gene flow among
populations influences the potential for differentiation (Avise et al. 1987) and can also affect
local population persistence (Harrison et al. 1988). Populations in different habitat patches
may be completely isolated, partially isolated, effectively a single population, or a matrix of
interconnected populations (e.g. metapopulation), depending on the extent of gene flow and
population extinction rates (Lavery et al. 1995; Boulton et al. 1998; Frankham et al. 2002)
The amount of gene flow among populations is primarily determined by the inherent
dispersal capability of a species in conjunction with geographic, ecological and geological
impediments to movement. These factors can have varying affects across a species range
and consequently population structure across a species distribution can vary in terms of the
level of structuring e.g. broad scale versus fine scale (Barber 1999a, 1999b) and the pattern
of structuring among populations i.e. because levels and patterns of dispersal are not always
uniform across a species distribution, populations may exhibit panmixia in one area of their
range (high levels of gene flow) and isolation by distance in another area (via restricted gene
flow) (Lavery et al. 1995). Quantifying levels of genetic variation among populations at
different spatial scales permits inferences to be made about patterns of population structure
and gene flow across the species distribution (Slatkin 1985a; 1987).
Traditionally, spatial analysis of variation in gene frequencies has been the approach adopted
for estimating population genetic structure and there has been a long history of model
development to infer the extent of gene flow from gene frequency data (e.g. FST and Nm
values which were derived to quantify levels of gene flow among populations; Wright 1931,
Slatkin 1987). The best known model is Wright’s (1931) Island model of population
structure which is based on the assumption that dispersal is equal among equal sized
‘islands’ or populations. Few natural population systems adhere, however, to the
assumptions of the Island model so variations on this model and alternate models of gene
flow have been proposed which relax and/or modify certain parameters to better fit the
dynamics of wild populations.
Alternative models of gene flow include Source-sink models (a source population provides
migrants to a number of smaller sink populations, Gyllenberg and Hanski 1992; Gaggiotti
1996); the Stepping Stone model (exchange of individuals is limited to adjacent populations
either in a one-, two- or three-dimensional pattern; Kimura and Weiss 1964); Isolation by
Distance models (describe a model of population structure in which populations are
distributed relatively continuously over a large area and individuals living nearby tend to be
more alike than those living far apart; Wright 1943; Slatkin 1993) and Metapopulation
Chapter One: General Introduction
5
models that describe dispersal among sets of conspecific populations existing in a balance
between extinction and recolonisation (Levins 1970; Hanski and Gilpin 1991).
Identifying population structure and relative gene flow gives an indication as to how
populations interact through dispersal and also identifies ecological barriers to dispersal and
inherent limitations to dispersal. This information allows managers to plan how to
effectively manage population systems and potentially preserve areas which may maintain
higher levels of diversity (NSW National Parks and Wildlife Service 2003; Department of
Environment and Conservation [NSW] 2005). This is important also for assessing how
populations will be affected by changes to their surrounding environments e.g. habitat loss or
fragementation. For example, populations which exhibit traditional metapopulation models
may be more at risk from processes such as habitat fragmentation because patches within a
metapopulation rely on colonisation from other populations. Barriers to dispersal among
patches and increased isolation among populations may limit the potential for recolonisation
particularly for those species which have small dispersal ranges or limited dispersal ability
(e.g. pool frog Rana lessonae; Sjogren 1991a, 1991b).
The effect of fragmentation on population structure will inevitably depend on the dispersal
capability of a species (Frankham et al. 2002). Small terrestrial species, such as amphibians,
are particularly vulnerable to habitat fragmentation because they often show poor vagility
and may require highly specialised habitats (Hitchings and Beebee 1998; Vos et al. 2001).
Species are also likely to be impacted differently by habitat fragmentation subject to how
dependent they are on a particular type of habitat as a corridor for dispersal. Overall,
generalist species tend to be opportunistic and can therefore potentially overcome habitat
changes (loss and fragmentation of patches) given a wider range of available suitable
breeding habitat (Dynesius and Jansson 2000). Specialists in contrast, are often endemic to a
particular type of habitat and are therefore habitat restricted. The requirement for specific
habitat attributes commonly means that populations are already isolated to a degree and may,
as a result be small in size. Populations with these characteristics may be particularly
sensitive to further loss of habitat and to habitat change. Increased habitat fragmentation can
lead to the complete isolation of populations and to significant reductions in population size
(Frankham 1998).
Chapter One: General Introduction
6
1.2.1 EARTH HISTORY EVENTS THAT SHAPE POPULATION STRUCTURE
Since the late 1980’s, studies have demonstrated the importance of identifying historical
barriers to gene flow that may have influenced population structure (Avise 1992). Studying
patterns of genetic variation in a geographical context via gene trees (i.e phylogeography)
has contributed considerably to the understanding of potential factors that may have
influenced population structure and species divergence (e.g. Avise 1994).
Genetic differentiation among populations may be initiated by geographical isolation related
to physical or ecological barriers. Much of the genetic variation present within a widespread
species may be a consequence of vicariant isolation and subsequent divergence resulting
from large-scale climatic cycles or geological events (Printzen et al. 2003; Veith et al. 2003).
A number of studies have shown that past glacial periods and related eustatic oscillations
have had a significant effect on the current population structures of a range of animal and
plant species (Avise 1992; Hewitt 1996; Wong et al. 2004). Climate oscillations in the past
have repeatedly confined many animal and plant species to habitat refugia. During glacial
periods many species as a consequence, evolved distinct phylogeographical lineages
(Taberlet et al. 1998; Hewitt 1999).
The effect of climatic fluctuations on population genetic structure has been studied
extensively in a wide range of species, particularly across the European continent. Studies
have shown that conspecific populations which were restricted to separate habitat isolates
during glacial periods experienced significant genetic divergence (Bowen and Avise 1990;
Avise 1992; Hewitt 2000; Hewitt 2001). Interglacial periods and the onset of more stable
climatic conditions during the Holocene resulted in many plant and animal species
expanding their ranges into areas which were previously unoccupied during glacial periods.
These range expansions had a number of genetic consequences. In some species narrow
hybrid zones produced by the meeting of two divergent genomes have formed subsequently
as populations have expanded their ranges from separate habitat refugia (e.g. European
meadow grasshopper; Cooper et al. 1995). In other species postglacial expansion resulted in
parapatric distributions of divergent mtDNA and allozymes (e.g. European hedgehogs;
Santucci et al. 1998) and for some species, e.g. the Natterjack toad, Bufo calamita, genetic
analysis revealed that range expansions caused a loss of genetic diversity and an increase in
homozygosity in colonising populations as a result of rapid long distance range expansion
and founder events (Ibrahim et al. 1996; Beebee & Rowe 2000). Genetic structures that
developed due to glacial isolation and post-glacial range changes are thus important factors
Chapter One: General Introduction
7
that have contributed to the broad-scale distribution of genetic diversity (Comes and
Kadereit 1998; Hewitt 2001).
In recent years, population genetic models based on coalescent theory (Kingman 1982a,
1982b) have provided a statistical framework for estimating demographic parameters, such
as migration rates, population expansion and divergence times. Coalescent theory describes
the genealogical process of a sample of selectively neutral genes from a population looking
backward in time. The rapidly growing field of ‘statistical phylogeography’ (Knowles and
Maddison 2002) has produced a number of models which can explicitly test particular
phylogeographic hypotheses for simple population structures (Takahata et al.. 1995; Beerli
and Felsenstein 1999; Wakeley 2001; Excoffier 2004).
Using coalescent theory, methods such as Nested Clade Analysis and analysis programs such
as Geodis (Templeton et al. 1995; Posada et al. 2000) aim to distinguish among a diverse
array of historical processes to describe how current population structure may have formed.
This approach is based on the findings that different patterns of population growth, dispersal
and biogeographical history leave distinct signatures in current spatial patterns of neutral
genetic variation (Hutchison and Templeton 1999).
Describing historical population structure and determining factors that affect dispersal
capacity can provide an indication as to how contemporary dispersal may be affected by
current barriers and impediments to movement, in particular how species and populations
may react to future fragmentation or loss of habitat. It also allows us to understand, (1) how
the observed population structure of a species evolved and (2) the evolutionary relationships
among constituent populations. It is important to identify evolutionary lineages in order to
retain maximum genetic diversity.
1.3 THE USE OF MOLECULAR MARKERS TO DESCRIBE GENETIC VARIATION AND
POPULATION STRUCTURE
Neutral genetic markers have been used in many studies over the last 40 years to describe the
population structures of many species and to characterise levels and patterns of genetic
diversity. Although a variety of genetic markers have been developed, mitochondrial (mt)
DNA has proven invaluable for use in many population systems (Neigel 1997). MtDNA is a
circular, haploid, molecule which is inherited maternally in most animal species (Wilson et
al. 1985, Avise 1992). MtDNA has a comparatively higher net mutation rate than nuclear
Chapter One: General Introduction
8
DNA, does not undergo recombination and has ¼ the effective population size1 (as it is
haploid and maternally inherited). Consequently, it is far more sensitive than nuclear DNA
to reductions in population size due to processes such as founder effects and population
bottlenecks, making it a suitable marker for detecting the effects of stochastic processes
(Wilson et al. 1985; Harrison 1989; Brookes et al. 1997). The higher net mutation rate also
means that differentiation should be greater at mtDNA loci than at equivalent nuclear loci
(Birky et al. 1989).
MtDNA markers have been used successfully in a wide range of organisms to describe broad
scale historical population genetic structure and, even at the relatively fine spatial scales of
gene flow mtDNA markers have allowed greater understanding of interactions among local
populations (Nagata et al. 1998; Barber 1999b). Phylogenies derived from mtDNA
sequence data have proved to be invaluable for exploring evolutionary process and
demographic events in a species past (Avise et al. 1987; 1992).
Nuclear markers such as microsatellites and amplified fragment length polymorphisms
(AFLP) have also become increasingly popular in genetic studies because of the high level
of variability commonly observed at these loci. Microsatellites have advantages over other
DNA markers as they combine high variability with co-dominant inheritance and they can be
typed following non-invasive sampling. Microsatellites are relatively short, tandomly
repeated (1-4bp) stretches of DNA that occur ubiquitously throughout the genome of most
organisms (Scribner and Pearce 2000). Microsatellite loci often have larger number of
alleles and higher heterozygosity than other equivalent nuclear loci such as allozymes
(Reusch et al. 1999) and as such they have been used in a large number of studies to assess
genetic diversity. Microsatellite markers are particularly valuable for examining fine scale
population structure and for estimating the extent of contemporary gene flow.
Both mitochondrial and nuclear markers have been used to address conservation genetic
questions in a wide variety of organisms (Jones et al. 1996; Gonzales et al. 1998; Gaudel et
al. 2000; Bos and Sites 2001; Burns et al. 2004) and when they are used together they can be
invaluable for examining contemporary and historical patterns of genetic diversity and
population genetic structure (Monsen and Blouin 2003). Concordant results among markers
can provide strong support for hypotheses on a species evolutionary history (Cummings et
1 Note: This holds true as long as there is equal effective population size for each sex.
Chapter One: General Introduction
9
al. 1995), alternatively, findings of incongruent patterns can also be valuable because they
may provide a better understanding of important evolutionary processes such as introgressive
hybridization, sex-biased dispersal or the effects of selection (Fitzsimmons et al. 1997;
Rieseberg 1998; Sumida et al. 2000). Independent markers which differ in their rates of
mutation and heritability can also be useful for describing population structure over different
temporal and spatial scales (e.g. Ryan et al. 1996; Rafinski and Babik 2000; Lampert et al.
2003; Babik et al. 2004).
1.4 DECLINING FROG POPULATIONS
Anuran populations have been the subject of much discussion over the last decade as a result
of concerns about apparent worldwide declines in many species. While general hypotheses
including climate change, microbial pathogens and natural long term population fluctuations
(Blaustein and Wake 1990; Phillips 1990; Lips 1999; Pounds et al. 1999) have been
proposed as likely causes, of primary importance in many anuran population declines has
been loss and/or fragmentation of natural habitat (Ferraro and Burgin 1993a, 1993b; Bell and
Bell 1994; Brown 1994; Green 1994). Factors associated with habitat changes, e.g.
infrastructure (roads, railways) and changes in habitat quality and structure, have also been
demonstrated to cause declines in frog populations (Marsh and Pearman 1997).
Most frog species are ground dwelling and have relatively low individual dispersal capability
(Beshkov and Jameson 1980; Sinsch 1990). Gene flow among populations will depend on
the distance between suitable habitat patches and on the relative resistance of the intervening
landscape to dispersal among patches (Hitchings and Beebee 1997, 1998). Hitchings and
Beebee (1998) observed that measures of genetic diversity and survival of populations were
significantly lower in small, urban populations of the Common Toad, Bufo bufo than in
larger, rural populations in the same region. Genetic analysis and autecology of this species
indicated that the causal mechanism was random genetic drift arising from barriers to
dispersal among habitat patches as a result of urban development.
Because anurans often show limited dispersal capabilities and can exhibit site fidelity
(Berven and Grudzien 1990; Semlitsch and Bodie 2002) even a relatively small degree of
habitat fragmentation can effectively isolate populations. Most studies of genetic population
structure in anurans support the hypothesis that populations tend to be relatively isolated
from other populations (Shaffer et al. 2000) and exhibit significant differentiation even at
fine spatial scales (Waldman et al. 1992; Driscoll 1998; Shaffer et al. 2000). Vos et al.
Chapter One: General Introduction
10
(2001) examined the correlation between genetic distance and geographical distance in the
moor frog, Rana arvalis and found a significant positive association. Dispersal rates among
populations decreased with distance and barriers to dispersal such as roads and railways
affected the dispersal rate to a much greater extent than did geographic distance alone. Other
studies have shown similar isolation-by-distance effects on dispersal among frog populations
and that anthropogenic modification of landscapes can have a negative impact on dispersal
(Reh and Seitz 1990; Hitchings and Beebee 1997, 1998; Vos and Chardon 1998; Rowe et al.
2002;).
Studies of a wide range of frog species have shown that patterns of genetic diversity in
current populations are often determined by past geological and glacial events (Barber
1999a; Crawford 2003; Masta et al. 2003). Frogs, like many other animal and plant species,
exhibit patterns of range contraction and expansion from glacial refugia, hybridisation due to
postglacial range expansions and distinct phyogeographic lineages associated with
geological and ecological earth history events (McGuigan et al. 1998; Schneider et al. 1998,
Beebee and Rowe 2000, James and Moritz 2000; Pagano et al. 2001; Crawford 2003).
Many of Australia’s anuran populations, like anuran populations around the world, have
experienced recent declines in population numbers. Many of these declines have been
attributed to dramatic environmental change including deforestation and reclamation of low
lying land by humans (Tyler, 1979). In Australia many frogs are confined to areas of
sufficient, reliable precipitation (Woinarske et al. 1999). These environments are generally
restricted to the edges of the Australian continent, which is also the area of greatest human
occupation. This means that many of Australia’s native anurans are potentially very
vulnerable to deleterious effects associated with the results of human-mediated habitat
modification.
The frog fauna of Australia consists of five families; Hylidae (tree frogs), Ranidae (true
frogs), Microhylidae (narrow-mouthed frogs); Myobatrachidae (southern frogs) and
Bufonidae (true toads, introduced species). The Myobatrachidae are the only family that is
restricted solely to Australia and Papua New Guinea and they represent 57 percent of
Australian frog species. Members of the family display considerable diversity in
morphology, life cycles and ecology. Many species within the Family Myobatrachidae are
listed as endangered or vulnerable and three species are recognised as extinct.
Chapter One: General Introduction
11
1.5 CASE STUDY: THE WALLUM FROGLET (CRINIA TINNULA)
The wallum froglet, Crinia tinnula, is one of Australia’s habitat-specialist myobatrachid
anurans that in recent years, has suffered a dramatic decline in local population numbers
(Ehmann 1997). It is one of fourteen species in the endemic genus Crinia (Straughan and
Main 1966; Cogger 1996; Read et al. 2001). C.tinnula is restricted to coastal wallum
heathland and associated Melaleuca swamps in southeast Queensland and north-eastern New
South Wales. Along with three Litoria species (L.cooloolensis, L.olongburensis, and
L.freycineti), C.tinnula is commonly referred to as an ‘acid’ frog, because it is found in
association with acidic waters (pH <5) of lake, creek and swamp systems of the wallum
heath.
C.tinnula was first recognised as a distinct species in 1966 by Robert Straughan and Ian
Main. The species is very similar morphologically to other Crinia species, in particular
C.parinsignifera and C.signifera, and exhibits polymorphism for back colour and patterns
characteristic of the Crinia genus. C.tinnula produce relatively small clutches of eggs
(approximately 80 per clutch, range of 33 – 118; Straughan and Main 1966), and breeding
follows the passage of cold fronts bearing rain during the winter months. C.tinnula is the
only species of acid frog to breed predominantly in winter.
The patchy distribution of populations, winter breeding activity and morphological similarity
to other Crinia species has resulted in some populations only being discovered recently
(Ehmann 1997; Hero et al. 2000). In a report in 1997, the species was suggested to be absent
from Fraser Island, however, several populations have since been found on the island.
Although ‘new’ populations have been found relatively recently there are many sites which
in the past were known to support wallum froglet populations and now apparently no longer
do so (Ehmann 1997).
The species is not generally associated with disturbed areas. Ehmann (1997) noted that
C.tinnula was absent from areas of habitat that had been disturbed by sandmining, pasture
improvement, cane farming and landfill activities. The habitat to which C.tinnula are
endemic, (“wallum” habitat) is restricted to low coastal plains behind sand dunes in
southeast Queensland and northern New South Wales. As human populations in this region
have grown, coastal areas have become prime areas for development for agriculture,
residential property and large commercial pine plantations. Throughout the greater Brisbane
region, the Sunshine Coast and the Gold Coast areas wallum habitat has been significantly
reduced, modified or subject to disturbance from anthropogenic activities (Coaldrake 1962;
Chapter One: General Introduction
12
Hero et al. 2000).
Reduction of natural habitat is considered to be the major cause of declines in the acid frog
populations. Local extinctions and reductions in population numbers has resulted in the
listing of all four acid frog species in the Queensland Nature Conservation (Wildlife)
Regulation (1994, 2004) as either Vulnerable (L.freycineti, L.olongburensis, C.tinnula) or
rare (L.cooloolensis). C.tinnula is also listed as Vulnerable under the New South Wales
Threatened Species Conservation Act (1995, 2002). All four species are protected under the
Federal Environment Protection and Biodiversity Conservation Act (1999).
A landuse study carried out in the early 1970’s described wallum as largely ‘useless’ and
suggested that modification of wallum habitat would allow for expansion of beef cattle
production in the south east Queensland region (Bullen, 1970). Between 1974 and 1989,
over 50% of Melaleuca forest and 34% of the heathland that was present in south-eastern
Queensland were cleared (Catterall and Kingston 1993) and over the last fifteen years, large
areas of coastal heathland have been destroyed for agriculture, mining and residential
development (Hines et al. 1999). The effect has been to convert a once largely continuous
patch of coastal heathland and Melaleuca swamps into a matrix of small patches, within an
area undergoing rapid urban expansion.
Much of the wallum is now recognised as both of evolutionary and ecological significance
and this habitat type has been protected on some offshore sand islands in the region (Fraser
and Moreton Islands), however, mainland areas and populations on other sand islands (e.g.
Bribie Island and Stradbroke Island) are still under threat, particularly from urban
development (Hero et al. 2000). Long term survival of the wallum froglet will require
implementation of conservation management plans to ensure persistence of these species in a
region subject to ongoing rapid environmental change.
To plan effective management strategies for the conservation of C.tinnula populations it is
first necessary to understand the species population structure and levels and patterns of
genetic diversity within and among extant populations. Relative conservation status of each
population can then be determined and this information can be used to develop appropriate
management plans for the species.
Chapter One: General Introduction
13
1.6 THESIS STRUCTURE AND AIMS
Existing information on ecology of C.tinnula populations is very limited and is restricted
largely to basic distributional data. Nothing is known about movement patterns or the extent
of interactions among natural populations across the species distribution. Neither is anything
known about genetic diversity or population genetic structure of this species. While
populations are protected under the Nature Conservation Act (1992) currently there are no
specific conservation management plans for this species. Given the rapid rate of clearing
and fragmentation of wallum habitat in southeast Queensland due to human population
expansion, it is likely that conservation management plans will be necessary for C.tinnula
populations in the near future.
This study aimed to document levels and patterns of genetic diversity and to define the
population structure for C.tinnula populations across the natural distribution in southeast
Queensland. Specific aims of the project were; to use mitochondrial markers to describe
patterns of historical population structure, to determine how current patterns of genetic
diversity evolved and what processes may have influenced the evolution of C.tinnula
populations. It is hypothesized that sea level fluctuations during the Pleistocene may have
influenced the distribution and connectivity of wallum habitat in eastern Australia and this
may have consequently influenced the dispersal patterns and population structure of
C.tinnula populations. Describing patterns of historical population structure will be useful
for defining evolutionarily significant units for conservation of C.tinnula, and historical
patterns of gene flow may also give an indication as to the dispersal capacity of C.tinnula.
Historical population structure may also provide insight into patterns of colonisation of the
major sand islands in the region.
The project also aimed to describe contemporary levels and patterns of gene flow and
genetic diversity using microsatellite markers. In particular, to look at local scale dispersal
patterns among populations to infer potential impacts that habitat fragmentation could have
on modern population structures and levels of genetic diversity.
The genetic information obtained in this study can be used to assist in assigning relative
conservation status to populations or groups of populations based on levels and patterns of
diversity, genetic structure and evolutionary significance. In conjunction with genetic data,
information on land use patterns, distribution of remaining wallum habitat and current
information on population distribution data can then be used to develop effective
management strategies for C.tinnula in southeast Queensland.
Chapter One: General Introduction
14
General methods used in the present study are described in Chapter 2, where information
regarding the sampling design, location of collection sites, laboratory methods and statistical
analysis are given. Specific methodological information is also provided in Chapters 3 and
4. Chapter 3 describes the broad-scale population structure of C.tinnula. Chapter 4
describes local population structure and genetic diversity within regions. Chapter 6
examines the patterns of genetic diversity and population structure and the implications for
C.tinnula conservation management.
Chapter Two: General Methods
15
CHAPTER TWO.
2 GENERAL METHODS
2.1 THE STUDY AREA
2.1.1 BIOGEOGRAPHY OF THE WALLUM
Sites sampled for this study are located in southeast Queensland within the biogeographic
region known as the Coastal Lowlands (Coaldrake 1961). The coastal lowlands are a natural
system extending from Gladstone in Queensland to Coffs Harbour in NSW and form part of
a discontinuous belt of lowland country extending along the eastern and southern coasts of
Australia (Coaldrake 1961).
Within southeast Queensland and northern NSW, coastal lowlands are also known as
“wallum”. The word ‘wallum’ is an aboriginal word which was used to describe the small
woody tree, Banksia aemula (Harrold 1994). Over time, the use of the term has been
extended to describe other plant communities found in the coastal lowlands in the
Queensland region, in particular heathlands, which tend to be dominated by Banksia aemula
and other similar Banksia species.
The coastal lowlands are distributed across low lying undulating alluvial plains
(approximately 1 to 10 metres above sea level) found in behind coastal dune systems. The
lowlands have a mild subtropical climate with a marked dominance of summer rainfall and a
small but significant winter rainfall. The winter rainfall provides the temporary water bodies
that C.tinnula utilise for breeding. The sandy soils of the wallum are low in fertility except
in areas where volcanic influences have added nutrients to the soil. Typical plant
communities of the wallum include open woodland forests of Melaleuca quinquenervia
associated with heath understory (Banksia alliances) and wet and dry heath (Southeast QLD
Bioregion - Regional Ecosystems 12.2.9; 12.2.15; 12.3.5; Sattler and Williams 1999).
Wallum habitat throughout southeast Queensland is similar floristically but can differ quite
markedly in structure (see Figure 1 and 2). Wallum habitat associated with the perched lake
systems of the Fraser Island-Cooloola sand masses and those of Moreton and North
Stradbroke Islands generally consists of extensive, dense reed beds in shallow areas of the
lakes and the fringing areas of the lake support stands of M.quiquenervia.
Chapter Two: General Methods
16
Figure 1. Habitat structure of wallum heathlands in southeast Queensland. A Wallum
heathland (Ungowa Fens) on Fraser Island. Wet heathland consisting mainly of sedges,
outer edges of the heath are composed of Melaleuca and Eucalypt woodland. B. Honeyeater
Lake, Moreton Island. Perched lake surrounded by dry heath. Dense stand of reeds form in
the shallow areas of the lake. C. Amity Point, Stradbroke Island. Wallum Freshwater
swamp (recently burnt out by fires).
A.
B.
C.
Chapter Two: General Methods
17
Wallum habitat also includes freshwater swamps and wallum plains which comprise wet and
dry heaths. The dry heaths are a prominent feature of the older dune systems of the coastal
sand masses. In areas exposed to the wind, vegetation is generally less than one metre in
height and consists of small woody shrubs and sedges but where vegetation is more
protected small trees are present. Temporary water bodies, formed from winter rains,
provide the favoured breeding habitat for C.tinnula. These areas may also be associated with
creek catchments and lake systems, with the dry heaths forming on elevated soils.
The wet heaths (varying degrees of ‘wet’) are generally very simple in plant structure,
usually devoid of tree and shrub species (small stands of paperbarks may be found on the
outer edges of the heathland). They form in the catchments of creeks and drain water from
the neighbouring dunes and usually support dense sedge-like vegetation. During periods of
high rainfall these areas are inundated with water and can support large breeding populations
of C.tinnula.
One of the most distinctive features of wallum is the tea-like colour and low pH of the water
bodies associated with this habitat (Figure 2). Water colour is due in part to the amount of
decaying organic matter in the water. Acidity of the water is affected by input from
vegetation, the age of the soils and the nature of the organic layer on which the water body
forms (Bayly 1964; Ingram and Corben 1975). pH levels can range from as low as 2.8 to
5.5. It is the adaptation to low pH levels and the ability of the larvae of acid frogs to develop
in these relatively acidic environments that has led to the recognition of the acid frogs as a
specialist ecological group.
Coaldrake (1962) suggests that the development of the present wallum ecological pattern
dates from varying periods during the Pliocene. It is certain that much of the wallum has
been within the range of eustatic oscillations of the Pleistocene (Coaldrake 1961, 1962;
Thom et al. 1994). A drop of about 28 metres would move the present south eastern
Queensland coastline east of Moreton and Stradbroke Islands (approximately 40km) and link
the major areas of now disjunct wallum existing across the mainland and the coastal sand
islands (Willmott and Stephens 1992). It is unknown, however, whether wallum formed a
semi-continuous distribution from the mainland to the island wallum areas during lower sea
levels or whether wallum habitat on the islands has formed as disjunct isolated patches.
Chapter Two: General Methods
18
Figure 2. Habitat characteristics of wallum heathland in southeast Queensland. A & B.
Dense reed beds associated with the perched lakes and wet heath systems. C. Characteristic
tea colour water of wallum habitat.
A.
B.
C.
Chapter Two: General Methods
19
Human population growth in southeast Queensland is causing rapid changes to established
land use patterns. Town planning for the region aims to accommodate a total population of
2.5 million by 2011 (BCC1990). It is estimated that 29% of Australia’s population growth
between 1991 and 2011 will occur within this area (Kordas et al. 1993). Large tracts of land
have already been drained and cleared on the Sunshine Coast for pine plantations (Pinus
spp.) and housing developments (Batianoff and Elsol 1989).
In the Brisbane region, much of the pre-European wetland habitat has been cleared or is
currently under threat from rural or residential development. Within the area under Brisbane
City Council authority, it has been estimated that more than 95% of wetland habitat has
already been cleared (ES&S 1989). In particular, very few areas of wet heathland remain
within the Brisbane region. Most of the remaining wet heathland habitat is restricted to the
sand islands and the Cooloola region.
One of the most significant patches of remaining wallum habitat in the Brisbane region is
found in Karawatha Forest. Within Karawatha, a small patch of wallum heathland exists in
the seasonally wet floodplain of the Scrubby Creek catchment system. This small area is of
high local and regional significance, containing both a high diversity of herbaceous species
and sedges and a number of relatively uncommon species (Kordas et al. 1993). Karawatha
forms an important core habitat area with links to significant areas of bushland remnants in
the Brisbane area (Kordas et al. 1993).
2.1.2 BIOGEOGRAPHY OF THE COASTAL SAND ISLANDS OF SOUTHEAST QUEENSLAND
At present, many of the protected areas of wallum habitat occur on the sand islands adjacent
to southeast Queensland. These islands are relatively young in geological time and going by
Coaldrake’s (1962) estimates of how old wallum habitat is, the sand deposits (from which
the islands developed), were established after the appearance of wallum habitat on the
mainland. Populations of wallum froglets have been found on all of the major sand islands
(Fraser Island, Bribie Island, Moreton Island, North and South Stradbroke Islands).
The larger sand islands (Fraser Island, Moreton Island and North and South Stradbroke
Islands) are believed to have been formed from a series of parabolic dunes constructed
episodically during the period of fluctuating sea levels in the late-Quaternary (Ward 1977;
Clifford & Specht 1979). Fraser Island is situated approximately 200km north of Brisbane
and is currently separated from the mainland (at its most southern point) by a distance of
Chapter Two: General Methods
20
approximately 1.5km. It is the world’s largest sand island, stretching 123km along the
southern coast of Queensland. Geological evidence suggests that the dunes of Fraser Island
formed synchronously with the Cooloola sandmass during the last million years (Thompson
1992; Longmore 1997). The oldest dune deposits of Cooloola date back to 700 000 years
before present (Tejan-Kella et al. 1990) and sedimentary sequences from Lake Coomboo, a
relic perched lake in the oldest dune system on the western side of Fraser Island, date back to
600 000 years before present (Longmore and Heijnis 1997). Geological studies suggest
Fraser Island would have been linked to the mainland for the majority of the last one million
years except for relatively brief interglacial periods (Longmore 1997).
Wallum heaths and swamps are associated with the oldest dune systems of Fraser Island and
the Cooloola sandmass (Walker et al. 1981) and represent a retrogressive stage of vegetation
development (vegetation succession reaches a climax ‘high nutrient and biomass’ stage
followed by a nutrient deficient, low biomass stage characterised by dwarf woodland
communities adapted to fire and low nutrient status; wallum habitat forms a major part of
this retrogressive vegetation). The majority of wallum habitat is distributed along the
western side of Fraser Island, with small patches associated with the freshwater lakes found
on the central dune ridge and some patches of wallum found on the eastern side of the island.
Moreton Island is Queensland’s second largest sand island and is situated approximately
30km east of the mainland. The island can be divided up into 3 main sections based on
regional topographic differences; northern, central and southern. The northern part of the
island supports large expanses of wallum heath and swamp and contains many of the
freshwater lakes on the island. The central part of Moreton Island is composed of large dune
ridges and there is very little wallum habitat through this part of the island. The southern
area is a low undulating coastal sand plain which is quite exposed. There are extensive
Melalueca quiquenervia swamps in this area with little to no heath or sedge understory.
North Stradbroke Island and Moreton Island are thought to have evolved synchronously with
the Fraser-Cooloola sand mass (Tejan-Kella et al. 1990; Jones 1992), however, geological
data for North Stradbroke Island suggests that this is a younger island. Clifford and Specht
(1979) proposed that the formation of North Stradbroke Island began during a glacial period
approximately 400 000 – 500 000 years ago. The formation of Moreton Island may also
have begun around this time (Jones 1992).
Moreton Island and North Stradbroke Island formed around small rocky pinnacles of what
are currently Dunwich, Point Lookout and Cape Moreton. These pinnacles acted as groynes
Chapter Two: General Methods
21
on the continental shelf to anchor the build up of sand spits. At times of highest sea levels,
Moreton Bay spilled around behind these growing spits to convert them into islands
(ancestors of North Stradbroke and Moreton Islands) (Jones 1992). Geological evidence
suggests that sea levels would have reached their present height approximately 6 000 years
ago.
The smaller sand island, Bribie Island, was also formed during the Pleistocene but is most
likely younger than the other sand islands. Geological evidence suggests that the older dunes
of Bribie Island were formed approximately 100 000 years ago from sand barriers (dune
systems) developed during the Pleistocene and the younger dunes on the island were formed
approximately 6 000 to 12 000 years ago from sand barriers developed during the Holocene
(Batianoff and Elsol 1989).
2.2 THE STUDY SPECIES; CRINIA TINNULA
2.2.1 SYSTEMATICS
The high level of morphological similarity among a number of Crinia species resulted in
delineation of species being based on male calls and/or experiments that tested reproductive
compatibility between different ‘populations’. The recognition of C.tinnula as a distinct
species was based on morphology and call discrimination tests among C.signifera,
C.parinsignifera and Crinia sp. nov [C.tinnula] individuals that were collected in the same
creek system (Straughan and Main, 1966). C.tinnula females were found to discriminate in
favour of conspecific calls against C.parinsignifera or C.signifera calls and in vitro crosses
of C.tinnula with C.parinsignifera and C.signifera resulted in both abnormalities of tadpoles
and death of tadpoles shortly after hatching (Straughan and Main 1966). The designation of
C.tinnula as a distinct species was therefore based on results of reproductive incompatibility
and male call structure.
The Crinia genus has been subject to a number of taxonomic revisions since the late 1950’s
based on information relating to male call structure, hybridization experiments, morphology,
biogeography and most recently molecular systematics (Main 1957; Blake 1973; Heyer and
Liem 1976; Thompson 1981; Heyer et al. 1982; Read et al. 2001).
Apart from a temporary name change (which saw all but two of the Crinia species
reassigned to the subgenus Ranidella), C.tinnula has not experienced any major taxonomic
Chapter Two: General Methods
22
‘reshuffling’ during the revisions, its taxonomic position as a distinct sister taxon to other
Crinia species has remained relatively consistent. This is most likely due to the fact that
C.tinnula has never been included in either of the Crinia species’ groups (“C.insignifera
species group” and “C.signifera species group”) described by Main (1957). The
relationships among species within these groups have been the main source of contention in
Crinia systematics.
The most recent taxonomic revision, based on a molecular phylogenetic assessment of two
mtDNA regions, was the first study to include and compare all Crinia species (Read et al.
2001). The molecular phylogeny supports the position of C.tinnula (and an unidentified
Crinia sp.) as a sister clade to C.parinsignifera and suggests a basal trichotomy for the
Genus Crinia (Figure 3).
Figure 3. Conservative summary (bootstrap support of 70% or more) of the phylogenetic
relationships among 11 of the 14 described Crinia species’ based on combined ND2 and 12S
sequence data. Reproduced from Read et al. (2001).
2.2.2 MORPHOLOGY
The physical appearance of the wallum froglet is characteristic of the Crinia genus, with
individuals highly polymorphic for back colour and pattern (classified as lyrate, ridged or
smooth), small size (20mm- 25mm) and granular belly pattern (Figure 4). Specific
distinguishing morphological attributes include a midline of white dots down the throat
(occurs on some C.signifera), pointed snout and a distinctive high pitched call, described by
Straughan and Main (1966) as ‘like the tinkling of a small bell’ from where the aboriginal
term ‘tinnula’ (tinkling) comes from.
halla
This figure is not available online. Please consult the hardcopy thesis available from the QUT Library
Chapter Two: General Methods
23
Figure 4. Wallum froglet, Crinia tinnula. A. Adult froglet next to a matchstick. Adults
range in size from 16mm to 24mm. B, C & D show the polymorphic back patterns and
colours characteristic of C.tinnula.
A.
B.
C. D.
Chapter Two: General Methods
24
C.tinnula is very similar in appearance to both C.parinsignifera and C.signifera. In optimal
wallum habitat, both C.parinsignifera and C.signifera are absent and so identification of
C.tinnula is non-problematic (C.tinnula is significantly morphologically different from other
acid frog species). In disturbed habitats, however, where C.parinsignifera and C.signifera
may be present, it can be very difficult to identify the three species based on external
phenotype, especially in the metamorph stages. Male calls are generally used to distinguish
the species, however, while all three species have somewhat distinctive calls, when males are
calling in a chorus it can be very difficult to identify which call belongs to which frog. In
some cases (e.g. at the Karawatha and Caboolture sites) it was only possible to distinguish
the species using genetic markers.
2.3 SAMPLING DESIGN AND SAMPLE COLLECTION
The design of the sampling regime was intended to document the pattern of broad scale
genetic structure for C.tinnula populations within southeast Queensland as well as to
describe the extent of local dispersal among populations. Approximately 27 sites were
chosen originally, including at least two sites on each of the major sand islands (sites were
restricted to those approved by the EPA under the sampling permit).
An inherent difficulty in studying a declining species is finding suitable sites (as populations
are often small and isolated) and obtaining adequate numbers of samples for analysis. At
least ten sites were visited along the mainland which had previously been known to, or
thought to support C.tinnula populations and frogs could not be heard calling or found after
intensive searching. Several of these sites were visited multiple times over the four year
sampling period. The difficulty in finding suitable sample sites produced geographical gaps
in the sampling regime.
As wallum habitat is coastal it forms a linear distribution pattern along the southeast
Queensland coastline. Sampling sites are also therefore, relatively linear in distribution.
The described distribution for C.tinnula within southeast Queensland stretches along the
coastline from Littabella National Park, Bundaberg down to Coolongatta on the Gold Coast.
In the current study, fourteen sites were sampled; Wathumba Creek (Fraser Island), Ungowa
Table 1. Collection sites and sample size for C.tinnula populations. Latitude and longitude
coordinates are shown in decimal degrees.
2.4 LABORATORY METHODS: MITOCHONDRIAL DNA TECHNIQUES
Two regions of the mtDNA genome, 12S ribosomal DNA and Cytochrome oxidase subunit
one (COI), were screened to document patterns of genetic diversity and to determine
population structure within and among sampled wallum froglet populations. The 12SrRNA
region was chosen to describe deep (historical) phylogenetic relationships among
populations because rRNA genes generally evolve slowly relative to other mtDNA genes,
and are therefore useful for applications such as inferring patterns of deeper evolutionary
divergence (Kumazawa and Nishida 1993). Conserved primers for this region were known
to amplify without problem across a diverse range of organisms (birds, reptiles and crayfish)
and had shown genetic variation in these organisms.
The COI region was used to document local population structure and also to describe relative
genetic diversity levels within populations. Substitutions at the 3rd codon position of the
amino acid are less constrained as they do not change amino acid sequences, therefore
Population Identification Code
Location Latitude Longitude
Sample Number
Wathumba Creek
Wc Fraser Island -24.98 153.23 30
Ungowa Un Fraser Island -25.45 153.00 27 Barga Lagoon Bg Fraser Island -25.50 153.05 27 Rainbow Beach Rb Rainbow Beach Rd -25.94 153.08 18 Cooloola Co Cooloola-Rainbow Rd -26.01 153.08 24 Noosa Ns North Shore Noosa -26.38 153.05 02 Peregian Pg Old Emu Road, Peregian -26.43 153.10 05 Beerwah Bw Scientific Area No 1,
Beerwah -26.84 153.01 04
White Patch WP Bribie Island -27.03 153.14 30 Bellara Bell Bribie Island -27.07 153.17 30 Caboolture Ct Porters Road, Caboolture -27.07 153.00 03 Honeyeater Lake
MI Moreton Island -27.09 153.44 11
Amity Point SI Stradbroke Island -27.40 153.45 16 Karawatha Kw Logan, Brisbane -27.64 153.11 35
Chapter Two: General Methods
29
synonymous substitutions evolve approximately 8-10 times faster than second position sites
and 2-4 times faster than first position sites in vertebrates (Kocher and Carleton 1997) and
can be used for estimating genetic diversity within and among populations (Bermingham et
al. 1997).
2.4.1 OUTGROUP SPECIES
C.parinsignifera and C.signifera were used as outgroup species for phylogenetic analyses in
this study because of their close genetic relationship to C.tinnula and also because parapatric
populations of these species are found in disturbed areas of wallum making access to tissue
samples relatively easy.
2.4.2 DNA EXTRACTION
A modified chelex extraction protocol was used to obtain genomic DNA (Walsh et al. 1991).
The chelex protocol provided a rapid method for extracting DNA for polymerase chain
reaction (PCR) amplification from the small amount of tissue available.
Tissue was washed in 1 ml of STE for 1 hour to rehydrate and then samples were placed in
500μl of 20 percent chelex solution (20g chelex resin in 80g distilled water) and 5μl of
20mg/ml proteinase K. Samples were then kept at 55oC on a heating block for 3 hours,
gently vortexed every hour, or placed on a rotating wheel in an oven kept at 55oC. After
digestion, samples were placed in boiling water for 8mins (or alternatively on a heat block at
100oC for 8mins) then allowed to cool after which 50µl of TE was added. Samples were
then spun down in a centrifuge at 13000rpm and the supernatant was removed to a new tube
(chelex beads discarded). Samples were stored at –20oC.
2.4.3 POLYMERASE CHAIN REACTION (PCR)
PCR was used to amplify target mtDNA regions. The 12SrRNA mtDNA region was
amplified using general vertebrate primers developed by Kocher et al (1989). The sequences
of the primers were as follows; light strand primer (12sf) 5’-AAA GCT TCA AAC TGG
GAT TAG ATA CCC CAC TAT-3’, heavy strand primer (12Sr) 5’ -TGA CTG CAG AGG
GTG ACG GGC GGT GTG T-3’. The COI mtDNA region was amplified using a
Chapter Two: General Methods
30
combination of general vertebrate (COIaH; Palumbi et al. 1991) and general amphibian
primers (Cox; Schneider et al. 1998). Sequences of the primers were as follows; Cox (light
A pairwise genetic distance matrix (Jukes-Cantor distance) was generated to examine the
genetic relationships among haplotypes. Genetic distance estimates indicated that all
haplotypes found within northern populations were highly divergent from all haplotypes
found within southern populations (Table 6). The distance matrix showed that haplotypes
from the Moreton Island and Stradbroke Island populations were genetically related to other
southern haplotypes.
Genetic distances ranged from 3.7 to 5.7 percent divergence between respective northern and
southern haplotype sets. These estimates were significantly higher than the estimates
calculated for pairwise haplotype differences within regions; values ranged from 0.3 to 1.4
percent within the northern region and from 0.3 to 1.7 percent within the southern region.
An AMOVA was performed and the northern and southern groupings were designated a
priori as a regional partition. The results of the AMOVA supported the differentiation of
northern and southern populations, indicating that the majority of mtDNA variation was
explained by regional differences (87.3%) with only a small percent of variation found
among populations within regions (8.9%) and within populations (3.8%) (Table 7).
In a broad scale context, genetic data analyses clearly support the presence of two
significantly differentiated groups of populations among southeast Queensland C.tinnula.
Chapter Three: 12S mtDNA
59
Table 6. Pairwise genetic distances for C.tinnula 12S mtDNA haplotypes. Outgroup species, C.parinsignifera (Cpar) and C.signifera (Csig), are included at the bottom of the table. Jukes-Cantor pairwise distances are shown below the diagonal. Absolute base-pair differences are shown above the diagonal. The ‘N’ or ‘S’ shown after the haplotype number in the first column indicates whether the haplotype was found in a ‘northern’ (N) or ‘southern’ (S) population.
These results, combined with the observed lack of indels or stop codons and the fact that
there were no sequence ambiguities encountered on alignment of forward and reverse strands
and individuals which were amplified multiple times showed no variability in TGGE
analyses or sequencing, strongly suggests that the COI gene analysed in this studywas
mitochondrial in origin and did not orignate from a pseudogene.
4.3.2 SEQUENCE VARIATION
Analysis of COI sequence data for 244 C.tinnula individuals revealed a total of 25 unique
haplotypes. One hundred and twelve nucleotide sites were variable across the 25 haplotypes
and 83 of these sites were parsimony informative (total sequence length 543bp). The
transition/transversion ratio was 3.2:1.
Figure 1 shows the alignment of the sequenced haplotypes. Of the 25 haplotypes identified,
ten unique haplotypes were present only in northern populations. Among these ten
haplotypes 12 sites were variable, four of which were parsimony informative (one
transversion). Fourteen unique haplotypes were present only in southern populations
(including Tyagarah and Newrybar) and 51 sites were variable, 44 of which were parsimony
Chapter Four: COI mtDNA
91
informative with a transition/transversion ratio of 6.2:1. The Mungo Brush sample showed a
unique haplotype. When the C.parinsignifera sequence was included in the alignment, 139
sites were variable, 93 of which were parsimony informative and the transition/transversion
ratio was 3.2:1. No evidence was found for saturation in transitions or transversions in the
COI data set (graphs not shown).
Conversion of the nucleotide sequence to an amino acid sequence showed that the amino
acid sequence was conserved completely across all C.tinnula samples and the
C.parinisignifera sample (Figure 2). All codon base pair changes were found to occur at 1st
(2.9%) or 3rd (97.1%) position sites. The C.tinnula and Xenopus laevis amino acid sequences
were aligned to determine a comparative level of variability of amino acid sequences among
highly divergent frog species. The alignment produced 13 amino acid changes across a total
of 164 comparative amino acid codons (Figure 2).
Chapter Four: COI mtDNA
92
Figure 1. Alignment of variable sites from the 543bp of mitochondrial COI sequenced for C.tinnula, compared with outgroup species C.parinsignifera (Cpar).
Position of the base substitution included above each nucleotide, identical sites = ‘.’; missing data = ‘?’; CparB = C.parinsignifera Barakula; CparK =
C.parinsignifera Karawatha. An “N” or “S” after the haplotype name signifies a ‘northern’ or ‘southern’ haplotype, respectively.
Figure 2. Alignment of amino acid sequence for 543bp mitochondrial COI sequenced for C.tinnula, compared with outgroup species C.parinsignifera (Cpar).
Xenopus laevis (X.lae) is included at the bottom of the alignment. Sequence is completely conserved. Missing data = '?'. CparB = C.parinsignifera Barakula;
CparK = C.parinsignifera Karawatha. An “N” or “S” after the haplotype name signifies a ‘northern’ or ‘southern’ haplotype, respectively.
4.3.6 LOCAL-SCALE DIVERSITY AND POPULATION STRUCTURE
Northern Region
Levels of diversity within populations were generally low (Table 7). The Rainbow Beach
and Cooloola populations showed the highest levels of haplotype and nucleotide diversity,
however, nucleotide diversity was particularly low in all populations. The Wathumba and
Noosa populations were fixed for a single haplotype.
Table 7. COI mtDNA haplotype diversity (Hd) and nucleotide diversity (πd) within southeast
Queensland populations of C.tinnula. n=number of individuals.
Population n Hd πd Wathumba Ck 29 0.00 0.0000 Ungowa 27 0.14 ± 0.09 0.0009 Barga Lagoon 27 0.14 ± 0.09 0.0009 Rainbow Beach 16 0.35 ± 0.15 0.0012 Cooloola 20 0.43 ± 0.13 0.0017 Noosa 2 0.00 0.0000 North Total 121 0.19 ± 0.05 0.0009 Peregian 5 0.00 0.0000 Beerwah 3 1.00 ± 0.23 0.0025 Caboolture 3 0.00 0.0000 White Patch 27 0.00 0.0000 Bellara 26 0.29 ± 0.12 0.0007 Karawatha 15 0.00 0.0000 Moreton Island 11 0.34 ± 0.17 0.0133 Stradbroke Island 30 0.13 ± 0.08 0.0009 South Total* 122 0.59 ± 0.04 0.0313
*includes Tyagarah and Newrybar sequences.
Based on COI haplotype frequencies and distribution there was little evidence of population
structure within the northern region. A single haplotype (haplotype 001c) was common
across the region and this haplotype was the dominant haplotype in all northern populations.
Apart from this single shared haplotype there was very little sharing of additional haplotypes
among populations. Ungowa and Barga Lagoon were the only populations to share a rare
Chapter Four: COI mtDNA
99
haplotype (haplotype 002c). Most of the rare haplotypes (6 of the 8 found across the
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Genetic pairwise distance estimates suggested that the highest level of observed sequence
divergence among northern haplotypes was 1.1 percent which equated to a six base pair
difference across a total of 543 base pairs (Table 8). The average sequence divergence
among haplotypes was 0.6 percent (3 base pair difference).
Chapter Four: COI mtDNA
100
Table 8. Pairwise genetic distances for C.tinnula COI mtDNA haplotypes. Outgroup species, C.parinsignifera is included at the bottom of the table. Jukes-Cantor
pairwise distances are shown below the diagonal, absolute base-pair differences are shown above the diagonal. ‘N’ = ‘northern’ haplotype, ‘S’ = ‘southern’
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