Impact of reduced-representation sequencing protocols on detecting population structure in a threatened marsupial.

Reduced-representation sequencing methods have wide utility in conservation genetics of non-model species. Several methods are now available that reduce genome complexity to examine a wide range of markers in a large number of individuals. We produced two datasets collected using different laboratory techniques, comprising a common set of samples from the greater bilby (Macrotis lagotis). We examined the impact of differing data filtering thresholds on downstream population inferences. We found that choice of restriction enzyme and data filtering thresholds, especially the rate of allowable missing data, impacted our ability to detect population structure. Estimates of FST were robust to alterations in laboratory and bioinformatic protocols while principal coordinates and STRUCTURE analyses showed variation according to the number of loci and percent missing data. We advise researchers using reduced-representation sequencing in conservation projects to examine a range of data thresholds, and follow these through to downstream population inferences. Multiple measures of population differentiation should be used in order to fully understand how data filtering thresholds influence the final dataset, paying particular attention to the impact of allowable missing data. Our results indicate that failure to follow these checks could impact conclusions drawn, and conservation management decisions made.

A Tasmanian devil breeding program to support wild recovery.

Tasmanian devils are threatened in the wild by devil facial tumour disease: a transmissible cancer with a high fatality rate. In response, the Save the Tasmanian Devil Program (STDP) established an 'insurance population' to enable the preservation of genetic diversity and natural behaviours of devils. This breeding program includes a range of institutions and facilities, from zoo-based intensive enclosures to larger, more natural environments, and a strategic approach has been required to capture and maintain genetic diversity, natural behaviours and to ensure reproductive success. Laboratory-based research, particularly genetics, in tandem with adaptive management has helped the STDP reach its goals, and has directly contributed to the conservation of the species in the wild. Here we review this work and show that the Tasmanian devil breeding program is a powerful example of how genetic research can be used to understand and improve reproductive success in a threatened species.

High blood lead concentrations in captive Tasmanian devils (Sarcophilus harrisii): a threat to the conservation of the species?

BACKGROUND: The Tasmanian devil (Sarcophilus harrisii) is the world's largest extant marsupial carnivore. Since the emergence of devil facial tumour disease in 1996, the species has undergone a severe population decline. The insurance population (IP) was established in 2006 to build a disease-free captive population to maintain 95% of the wild Tasmanian devil genetic diversity for 50 years. Captive and semi-wild Tasmanian devils are fed with possum and wallaby meat provided by local hunters, who use lead ammunition. Lead ingestion can cause acute toxicity, including ataxia, coma and death, or chronic subclinical deleterious effects including decreased fertility. METHODS: We determined blood lead concentrations in 26 captive and 133 wild Tasmanian devils from various sites across Tasmania. RESULTS: Captive Tasmanian devils showed significantly higher blood lead concentrations than their conspecifics in the wild. In captivity, older animals had higher blood lead concentrations than young animals, which suggested regular exposure, as lead can accumulate in a living organism in the blood, soft tissues and bones. After a response measure was implemented by removing the heads and wounds containing lead from the diet, blood concentrations significantly decreased in animals at one of the captive study sites, supporting the suspicion of food as the source of lead. CONCLUSION: This study highlights the need to ensure meat fed to captive carnivores is not contaminated by lead, especially in the context of a conservation program breeding individuals in captivity, as for Tasmanian devils.

AlleleRetain: a program to assess management options for conserving allelic diversity in small, isolated populations.

Preserving genetic health is an important aspect of species conservation. Allelic diversity is particularly important to conserve, as it provides capacity for adaptation and thus enables long-term population viability. Allele retention is difficult to predict beyond one generation for real populations with complex demography and life-history traits, so we developed a computer model to simulate allele retention in small populations. AlleleRetain is an individual-based model implemented in r and can be applied to assess management options for conserving allelic diversity in small populations of animals with overlapping generations. AlleleRetain remedies the limitations of similar existing software, and its source code is freely available for further modification. AlleleRetain and its supporting materials can be downloaded from https://sites.google.com/site/alleleretain/ or CRAN (http://cran.r-project.org).

Multimodel inference in ecology and evolution: challenges and solutions.

Information theoretic approaches and model averaging are increasing in popularity, but this approach can be difficult to apply to the realistic, complex models that typify many ecological and evolutionary analyses. This is especially true for those researchers without a formal background in information theory. Here, we highlight a number of practical obstacles to model averaging complex models. Although not meant to be an exhaustive review, we identify several important issues with tentative solutions where they exist (e.g. dealing with collinearity amongst predictors; how to compute model-averaged parameters) and highlight areas for future research where solutions are not clear (e.g. when to use random intercepts or slopes; which information criteria to use when random factors are involved). We also provide a worked example of a mixed model analysis of inbreeding depression in a wild population. By providing an overview of these issues, we hope that this approach will become more accessible to those investigating any process where multiple variables impact an evolutionary or ecological response.