Quantifying “demographic independence” is a vital step in establishing potential conservation units for a species in that it effectively distinguishes migration from within‐population reproduction. This is an important aspect because it allows for an accurate estimate of recruitment. For example, populations may be designated as 'management units' (=MUs) if indeed population growth results from local demography rather than immigration. Of additional interest is the calculation of immigrant ancestry and ascertainment of the temporal context over which immigration occurred. This is because MUs depend largely upon local (self‐sustaining) birth and death rates, and the quantification of ancestry is necessary to validate demographic independence. Dispersal rate is also of immediate interest to conservation biologists, and can be assessed by quantifying genetic divergence among populations. The capacity with which to gauge these benchmarks has now been extended herein to genome‐wide molecular data, in an attempt to adjust an analytical tool that was until now intractable for the next generation sequencing data. In this study, a popular legacy program for migrant detection (i.e. BayesAss3) has been modified to accept SNP (single nucleotide polymorphism) data. We validated BA3‐SNPs using empirical data to demonstrate its suitability for both high‐performance and desktop computing environments. We also facilitate high analytical throughput by presenting a binary search algorithm that automates MCMC (Markov chain Monte Carlo) parameter tuning. Our BA3‐SNPs‐autotune program required five or fewer rounds of optimization for 99% of input files, with acceptable mixing parameters derived in 100% of our test cases. Runtime for BA3‐SNPs is a function of the number of loci analysed. Benchmarking yielded an average runtime <32 hr (10 million MCMC generations) for datasets containing thousands of SNPs. The BA3 algorithm remains a viable option for analysing modern SNP datasets. Source code (C++ and Python) is released publicly under the GNU General Public License v3.0, and is available for download (Linux and Mac OSX) from the following URL: .

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Hybridization occurs differentially across the genome in a balancing act between selection and migration. With the unprecedented resolution of contemporary sequencing technologies, selection and migration can now be effectively quantified such that researchers can identify genetic elements involved in introgression. Furthermore, genomic patterns can now be associated with ecologically relevant phenotypes, given availability of annotated reference genomes. We do so in North American box turtles (Terrapene) by deciphering how selection affects hybrid zones at the interface of species boundaries and identifying genetic regions potentially under selection that may relate to thermal adaptations. Such genes may impact physiological pathways involved in temperature-dependent sex determination, immune system functioning and hypoxia tolerance. We contrasted these patterns across inter-and intraspecific hybrid zones that differ temporally and biogeographically. We demonstrate hybridization is broadly apparent in Terrapene, but with observed genomic cline patterns corresponding to species boundaries at loci potentially associated with thermal adaptation. These loci display signatures of directional introgression within intraspecific boundaries, despite a genome-wide selective trend against intergrades. In contrast, outlier loci for interspecific comparisons exhibited evidence of being under selection against hybrids. Importantly, adaptations coinciding with species boundaries in Terrapene overlap with climatic boundaries and highlight the vulnerability of these terrestrial ectotherms to anthropogenic pressures.

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Chronic-wasting disease (CWD) is a prion-derived fatal neurodegenerative disease that has affected wild cervid populations on a global scale. Susceptibility has been linked unambiguously to several amino acid variants within the prion protein gene (PRNP). Quantifying their distribution across landscapes can provide critical information for agencies attempting to adaptively manage CWD. Here we attempt to further define management implications of PRNP polymorphism by quantifying the contemporary geographic distribution (i.e., phylogeography) of PRNP variants in hunter-harvested white-tailed deer (WTD; Odocoileus virginianus, N = 1433) distributed across Arkansas (USA), including a focal spot for CWD since detection of the disease in February 2016. Of these, PRNP variants associated with the well-characterized 96S non-synonymous substitution showed a significant increase in relative frequency among older CWD-positive cohorts. We interpreted this pattern as reflective of a longer life expectancy for 96S genotypes in a CWDendemic region, suggesting either decreased probabilities of infection or reduced disease progression. Other variants showing statistical signatures of potential increased susceptibility, however, seemingly reflect an artefact of population structure. We also showed marked heterogeneity across the landscape in the prevalence of 'reduced susceptibility' genotypes. This may indicate, in turn, that differences in disease susceptibility among WTD in Arkansas are an innate, populationlevel characteristic that is detectable through phylogeographic analysis.