- Research article
- Open Access
Phylogeography and dispersal in the velvet gecko (Oedura lesueurii), and potential implications for conservation of an endangered snake (Hoplocephalus bungaroides)
© Dubey et al.; licensee BioMed Central Ltd. 2012
- Received: 15 March 2012
- Accepted: 2 May 2012
- Published: 14 May 2012
To conserve critically endangered predators, we also need to conserve the prey species upon which they depend. Velvet geckos (Oedura lesueurii) are a primary prey for the endangered broad-headed snake (Hoplocephalus bungaroides), which is restricted to sandstone habitats in southeastern Australia. We sequenced the ND2 gene from 179 velvet geckos, to clarify the lizards’ phylogeographic history and landscape genetics. We also analysed 260 records from a longterm (3-year) capture-mark-recapture program at three sites, to evaluate dispersal rates of geckos as a function of locality, sex and body size.
The genetic analyses revealed three ancient lineages in the north, south and centre of the species’ current range. Estimates of gene flow suggest low dispersal rates, constrained by the availability of contiguous rocky habitat. Mark-recapture records confirm that these lizards are highly sedentary, with most animals moving < 30 m from their original capture site even over multi-year periods.
The low vagility of these lizards suggests that they will be slow to colonise vacant habitat patches; and hence, efforts to restore degraded habitats for broad-headed snakes may need to include translocation of lizards.
- Landscape genetics
To conserve an endangered species, we need to provide suitable habitat, shelter, prey items, and other resources (see e.g. [1–4]). Prey availability may be one of the most critical issues, especially for predators with specialized diets [5, 6]. If management plans for endangered species include the restoration of habitat, we need to know if the endangered taxon itself is vagile enough to locate and colonise the newly-available sites. Evaluating the likelihood that significant prey species also will colonise restored areas is also important; if they do not do so (perhaps because of poor dispersal capacity), otherwise-suitable habitat may be unable to support populations of the endangered taxon.
The Broad-headed snake (Hoplocephalus bungaroides, Elapidae) is a small elapid snake restricted to rocky areas (sandstone plateaux) within a 200 km radius of Sydney, in south-eastern Australia . These snakes were abundant at the time of European colonisation 200 years ago, but have now disappeared from most of its former range [7, 8]. The threatening processes include habitat degradation and fragmentation resulting from the removal and destruction of critical shelter sites (especially, exfoliated rock that forms thermally-suitable retreat sites during the coldest parts of the year: ), forest overgrowth [3, 4, 9] and illegal collection of animals for the pet trade . Efforts at habitat restoration have produced encouraging results, with the snakes and their lizard prey rapidly colonising sites by themselves where artificial rocks have replaced stolen natural rocks  and where trimming of vegetation has allowed increased sunlight penetration [3, 4]. However, these studies have focused on sites very close to extant populations of snakes and their prey; the prospectus for successful colonisation of more distant sites remains unclear.
For relatively isolated habitat patches to be colonised, both the snakes and their prey must be able to reach them. Landscape-genetic analyses have confirmed that broad-headed snakes often move between adjacent outcrops (distance between outcrops: 0.9 to 10.7 km), and thus are likely to rapidly find any restored habitat patches . The probability of colonisation by the snakes’ prey species has not been studied, and is the subject of the present paper. Broad-headed snakes consume a diversity of vertebrate prey taxa, but the most important taxon (especially during cooler months of the year, when the snakes are restricted to rock outcrops) is the velvet gecko (Oedura lesueurii, Diplodactylidae: ). Indeed, velvet geckos comprised 70% of prey items consumed by juvenile H. bungaroides. Like H. bungaroides, O. lesueurii is restricted to rock outcrops [13, 14]. The predator–prey interaction between these two taxa presumably has been a long-running one, because geckos from populations sympatric with this snake species are reported to display a suite of antipredator tactics not seen in conspecific geckos from populations allopatric to broad-headed snakes (; but see  for data that challenge this conclusion). Local coadaptation is likely only when gene flow is restricted between populations (e.g. [15, 17, 18]), allowing the evolution of spatial heterogeneity in relevant traits.
To evaluate the history of this predator–prey interaction, we need to know the timeline not only for the predator’s evolution  but also for the prey’s evolution (current study). Because O. lesueurii is an important prey species for H. bungaroides, we also need to evaluate the potential for O. lesueurii to colonise newly restored areas of rocky habitat. We can clarify this issue with a study of landscape genetics (e.g., what are the spatial scales of current and historical rates of gene flow?) and direct measures of dispersal, based on mark-recapture fieldwork.
Phylogenetic analyses and molecular dating
Dating analyses based on the secondary calibration points revealed a first divergence within O. lesueurii about 5.68 million years ago (Ma; 95% HPD: 2.73 – 10.76), with a split between haplotypes within lineages occurring 2.94 Ma (95% HPD: 1.21 – 5.18), 1.07 (95% HPD: 0.28-0.94), and 1.58 (95% HPD: 0.50 – 2.96) for A, B, and C respectively. Dating analyses based on a standard divergence rate of 1.3% (derived from numerous previous studies; see Methods section) gave similar results, with a first divergence within the species about 5.00 Ma (95% HPD: 2.88 – 8.06), with a split between haplotypes within lineages occurring 2.36 Ma (95% HPD: 1.30 – 3.96), 0.83 Ma (95% HPD: 0.30 – 1.83), and 1.25 Ma (95% HPD: 0.56 – 2.53) for A, B, and C respectively.
Population and landscape genetic analyses
Overall, the ϕST between populations varied from 0 to 1.0 (see Additional file 2, with a mean value of 0.81. The mean of the pairwise ϕST value within each lineage was 0.62, 0.52, and 0.24 for A, B, C respectively.
Results of mantel and partial mantel test of landscape genetics of the gecko Oedura lesueurii, with a listing of variables included in the models (number of rivers [River] and number of roads [Walking track; Dirt Road; Paved Road; All road] between sites, minimum elevation between sites sites [min. elevation], mean elevation of sites minus the minimum elevation between sites [Mean elevation - min. elevation], straight-line distance [Distance] and true distance between sites [True distance]), the number of parameters per model, R 2 (total variance explained by the model), coefficient of correlation, P-value of parameters (The level of significance for our tests was set at α = 0.0028 (Bonferroni correction; i.e. 0.05/18 = 0.0028, where 18 represents the number of tests performed), AIC, Δ AIC, and AIC weight
Distance & min. elevation
River & Min. elevation & distance
River & Dirt road & Distance & Min. Elevation
Min. elevation & Dirt road & distance
Distance & mean - min. elevation & min. elevation
Mean - min. elevation
Min. elevation & mean - min. elevation
Mean - min. elevation
Distance & mean elevation - min. elevation
Mean elevation - min. elevation
Distance & river
Distance & dirt road
The samova revealed high FCT(among population groups) values for all the groups and small FSC(within population group) values in cases of 9 to 19 groups, indicating very high population structure. For example, at K = 9 the majority of variation (94.32%) is among groups, although 0.03% of variation at the level of among populations within groups still represents highly significant population structuring in the remaining population groups (P < 0.001). At K = 2, the two clusters identified were the populations of lineage B (Morton) vs lineages A (Putty, Malabar, and Cape Banks) and C (Dharawal and Royal NP), and at K = 3, the three clusters were the populations of lineage A, B, and C.
Dispersal distances of free-ranging geckos
In both of these taxa, a southern lineage (restricted to Morton NP) differs significantly from conspecifics in the Sydney area. Sumner et al.  suggested that the break between the southern and northern clade of H. bungaroides occurs in a geologically distinctive area where volcanic soils cover the sandstone plateaux , acting as a barrier to gene flow. The same may be true of other sandstone specialist species such as O. lesueurii. The strong genetic structure observed in this study is consistent with general patterns observed in various taxa distributed in eastern Australia  and could be attributed to the ancestral position of the mesic biome (which dominates eastern Australia), and hence allowed localized endemism from long term persistence of populations through multiple climatic cycles . Finally, the observed gradient of genetic diversity in O. lesueurii throughout the study area (decreasing diversity with increasing latitude) may be the result of harsher historical conditions in the southern part of the range (Last Glacial Maximum; ). The species reaches its current southern distributional limit close to our study sites in Morton NP .
Overall, the diversification of Australian geckos is ancient and may have originated from a Gondwanan vicariance (e.g. about 70 Ma for the diplodactyloids: Oliver and Sanders, 2009). In this respect the geckos differ from most other squamates, which colonized Australia from Asia more recently (e.g. [25–28]). Similarly, Australian geckos show relatively ancient intraspecific diversification (see e.g. [29–32]; this study). The diversification of at least one of the gecko’s major predators (the broad-headed snake H. bungaroides) is much more recent, as the split between the genera Hoplocephalus and Paroplocephalus occurred less than 3 Ma , and the oldest split between H. bungaroides lineages about 0.8 Ma . Consequently, O. lesueurii was established across much of its current range in southeastern Australia long before the evolutionary origin of H. bungaroides. Our results support the plausibility of the conditions required for natural selection to produce adaptive local differentiation in geckos: that is, genetic variation among populations and low gene flow between them [33, 34].
From a conservation perspective, the low dispersal rates of O. lesueurii have two main implications. The first is that this gecko will be slow to recolonise any local areas from which it is extirpated (perhaps by chance abiotic events, predators, or human disturbance). Thus, habitat suitability for the endangered broad-headed snake may be spatially heterogeneous as a result of relatively ancient local events that reduced gecko numbers. Second, the low dispersal rates of the geckos need to be considered in any management plan that includes the restoration of degraded habitat previously hosting H. bungaroides. The poor dispersal capacity of O. lesueurii (unlike H. bungaroides itself; ) likely will delay or prevent natural recolonisation of geckos in restored areas, unless those areas are very close to extant populations. Consequently, we may need to reintroduce O. leseurii to such areas in order to guarantee successful habitat restoration for H. bungaroides.
Number of tissue samples of the gecko Oedura lesueurii, and the longitude, latitude, and elevation, length and width of the collecting site, the number of samples and of haplotypes, and the nucleotide diversity at that site
Dharawal Site 6_
Dharawal Site 12
Dharawal Site 13
Dharawal Site 15
Dharawal Site 18
Yarramunmun site 1
Yarramunmun site 4
Yarramunmun site 2
DNA extraction and PCR amplification
We placed tissues in 200 mL of 5% Chelex containing 0.2 mg/mL of proteinase K, incubated them overnight at 56°C, boiled them at 100°C for 10 min, and centrifuged them at 13,300 g for 10 min. The supernatant, containing purified DNA, was then removed and stored at −20°C.
Double-stranded DNA amplifications of NADH dehydrogenase 2 (ND2) were performed with the primer pairs AT4882 (5’caacatgacaaaaattrgcccc 3’; see )/ND2R2 (5’ ratctaggaggccttakc 3’; specifically designed for this study). Amplification conditions included a hot start denaturation of 95°C for 3 min, followed by 35 cycles of 95°C for 1 min, 55°C annealing temperature for 1 min, 72°C for 1 minute 45 seconds. We then performed a final extension of 72°C for 7 min and visualized the sequence reactions on a 3730 xl DNA Analyzer (Applied Biosystems, CA, USA).
2.3 Phylogenetic analyses
We aligned sequences using BioEdit  and assessed them by eye. A sequence of Crenadactylus ocellatus ([GenBank:AY369016]; the basal species of the Diplodactylidae according to ) was used to root the tree. Additional sequences of Diplodactylidae were included in the analyses: Pseudothecadactylus lindneri [GenBank:AY369024], Rhacodactylus chahoua [GenBank:DQ533741], Oedura marmorata [GenBank:AY369015], Diplodactylus taenicauda [GenBank:AY369006], Diplodactylus intermedius [GenBank:AY369001], and Strophurus williamsi [GenBank:AY369007].
We performed ML heuristic searches and bootstrap analyses (1000 replicates) with phyml  and we selected the model of DNA substitution using jModelTest 0.1.1 [37, 38]. The HKY + G model  best fitted the dataset with a Bayesian Information Criterion (BIC; ). Finally, we used Paup* 4.0b10  to perform maximum parsimony (MP) analyses using 100 random additions of sequences followed by tree bisection and reconnection branch swapping, and retaining at most 100 trees at each replicate. We estimated branch support using 1000 bootstrap replicates with the same heuristic settings.
Population and landscape genetic analyses
We estimated population structure between all sites sampled by calculating ϕST, taking into account haplotype frequencies and the genetic distance between haplotypes, in Arlequin 3.0 . We used the Kimura two-parameter genetic distance (K2P; ) as our genetic model.
We performed Mantel and partial Mantel tests  using the software fstat Version 18.104.22.168 , with genetic distance as the dependent variable. The independent variables were the number of intervening rivers (River; i.e. the number of rivers crossing the strait-line distance between two locations) and roads (Walking track; Dirt Road; Paved Road; All roads) between sites, the minimum elevation between sites, the mean elevation of sites minus the minimum elevation between sites, the straight-line distance and true distance between site (i.e., by calculating the surface length of a line connecting each pair of sites while incorporating an underlying digital elevation model at a resolution of 25 m; implemented using the 3D Analyst Tool in ArcMap 9.3, 9). P-values were calculated after 10,000 randomizations. The level of significance for our tests was set at α = 0.0028 (Bonferroni correction; i.e. 0.05/18 = 0.0028, where 18 represents the number of tests performed). Based on the results of the Mantel and partial Mantel tests, we selected the best model using Akaike’s information criterion (AIC; ; based on the variance of the residuals). We compared each candidate model based on its AIC scores and weights. The best supported models are those with high Akaike weights, and that deviate from the best model by less than two units (i.e., ∆AIC < 2; ).
We used the program samova 1.0  to characterise population structure and to define groups of populations using genetic criteria. Given an a priori number of clusters (K), the software uses a simulated annealing procedure to define the cluster composition in which populations within a cluster are as genetically homogeneous as possible (FSC minimised) and clusters are maximally differentiated from each other (FCT maximised; ). The analysis was run for K = 2 to K = 19 and the significance of fixation indices was tested by 1023 permutations.
We performed dating analyses using Beast 1.6.2  with an uncorrelated lognormal relaxed clock and a coalescent tree prior. The coefficient of variation frequency histogram did not abut against zero, meaning that there was among-branch rate heterogeneity within our data . Consequently, as suggested by Drummond et al. , we used a relaxed molecular clock.
We used two secondary calibration points from a robust phylogeny focusing on Australasian geckos : (1) The oldest split within the Diplodactylidae (i.e. between Crenadactylus ocellatus and the other members of the family: 66.2 Ma [95% HPD: 46.6-87.0]) and (2) the split between Pseudothecadactylus and the New Caledonian Rhacodactylus chahoua and the remaining members of the Diplodactylidae (60.3 Ma [95% HPD: 41.5-79.2]).
The analysis was performed with two independent chains and 20 million generations; chains were sampled every 1000 generations with a burn-in of 2 million generations. Additional simulations were run with the same dataset and the same models, but strictly based on a rate of divergence of 1.3% derived from numerous studies as e.g. Zamudio & Greene’s  study on snake mtDNA and from Macey’s et al. (; also used in e.g. [35, 53, 54]) work on lizards.
Dispersal distances of free-ranging geckos
We conducted mark-recapture surveys on velvet geckos by turning rocks and measuring, individually marking (by toe-clipping) and releasing any geckos found. These studies were conducted in and around Morton National Park (Morton) on a monthly basis between March 2007 and October 2009, and in Dharawal Conservation area (Dharawal) and Yengo and Wollemi National Park (collectively, Putty) from March 2008 until November 2010. We classified geckos as adult males if they were > 40 mm snout-vent length (SVL) with overt hemipenial bulges; adult females if they were > 40 mm SVL and without such bulges; and juveniles if they were < 40 mm SVL. We determined the distance between rocks used by individual O. lesueurii using GPS co-ordinates imported into ArcGIS 10.0 .
We thank the Australian Research Council and the Swiss National Science Foundation for funding, and Reid Tingley for assistance with GIS analyses. The work was authorized by the University of Sydney Animal Care and Ethics Committee.
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