Dataset Information

Genetic Divergence among Regions Containing the Vulnerable Great Desert Skink (Liopholis kintorei) in the Australian Arid Zone.

ABSTRACT: Knowledge of genetic structure and patterns of connectivity is valuable for implementation of effective conservation management. The arid zone of Australia contains a rich biodiversity, however this has come under threat due to activities such as altered fire regimes, grazing and the introduction of feral herbivores and predators. Suitable habitats for many species can be separated by vast distances, and despite an apparent lack of current geographical barriers to dispersal, habitat specialisation, which is exhibited by many desert species, may limit connectivity throughout this expansive region. We characterised the genetic structure and differentiation of the great desert skink (Liopholis kintorei), which has a patchy, but widespread distribution in the western region of the Australian arid zone. As a species of cultural importance to local Aboriginal groups and nationally listed as Vulnerable, it is a conservation priority for numerous land managers in central Australia. Analysis of mitochondrial ND4 sequence data and ten nuclear microsatellite loci across six sampling localities through the distribution of L. kintorei revealed considerable differentiation among sites, with mitochondrial FST and microsatellite F'ST ranging from 0.047-0.938 and 0.257-0.440, respectively. The extent of differentiation suggests three main regions that should be managed separately, in particular the southeastern locality of Uluru. Current genetic delineation of these regions should be maintained if future intervention such as translocation or captive breeding is to be undertaken.

SUBMITTER: Dennison S

PROVIDER: S-EPMC4464518 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Publications

Genetic Divergence among Regions Containing the Vulnerable Great Desert Skink (Liopholis kintorei) in the Australian Arid Zone.

Dennison Siobhan S McAlpin Steve S Chapple David G DG Stow Adam J AJ

PloS one 20150610 6

Knowledge of genetic structure and patterns of connectivity is valuable for implementation of effective conservation management. The arid zone of Australia contains a rich biodiversity, however this has come under threat due to activities such as altered fire regimes, grazing and the introduction of feral herbivores and predators. Suitable habitats for many species can be separated by vast distances, and despite an apparent lack of current geographical barriers to dispersal, habitat specialisati ...[more]

PMID: 26061141

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Project description:Dingoes (Canis lupus dingo) were introduced to Australia and became feral at least 4,000 years ago. We hypothesized that dingoes, being of domestic origin, would be adaptable to anthropogenic resource subsidies and that their space use would be affected by the dispersion of those resources. We tested this by analyzing Resource Selection Functions (RSFs) developed from GPS fixes (locations) of dingoes in arid central Australia. Using Generalized Linear Mixed-effect Models (GLMMs), we investigated resource relationships for dingoes that had access to abundant food near mine facilities, and for those that did not. From these models, we predicted the probability of dingo occurrence in relation to anthropogenic resource subsidies and other habitat characteristics over ∼ 18,000 km(2). Very small standard errors and subsequent pervasively high P-values of results will become more important as the size of data sets, such as our GPS tracking logs, increases. Therefore, we also investigated methods to minimize the effects of serial and spatio-temporal correlation among samples and unbalanced study designs. Using GLMMs, we accounted for some of the correlation structure of GPS animal tracking data; however, parameter standard errors remained very small and all predictors were highly significant. Consequently, we developed an alternative approach that allowed us to review effect sizes at different spatial scales and determine which predictors were sufficiently ecologically meaningful to include in final RSF models. We determined that the most important predictor for dingo occurrence around mine sites was distance to the refuse facility. Away from mine sites, close proximity to human-provided watering points was predictive of dingo dispersion as were other landscape factors including palaeochannels, rocky rises and elevated drainage depressions. Our models demonstrate that anthropogenically supplemented food and water can alter dingo-resource relationships. The spatial distribution of such resources is therefore critical for the conservation and management of dingoes and other top predators.

Dataset Information

Genetic Divergence among Regions Containing the Vulnerable Great Desert Skink (Liopholis kintorei) in the Australian Arid Zone.

Publications

Genetic Divergence among Regions Containing the Vulnerable Great Desert Skink (Liopholis kintorei) in the Australian Arid Zone.

Similar Datasets

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