| Summary: | The effective population size (Ne) could be the ideal parameter for monitoring populations of conservation concern as it conveniently summarizes both the evolutionary potential of the population and its sensitivity to genetic stochasticity. However, tracing its change through time is difficult in natural populations. We applied four new methods for estimating Ne from a single sample of genotypes to trace temporal change in Ne for bears in the Northern Dinaric Mountains. We genotyped 510 bears using 20 microsatellite loci, and determined their age. The samples were organized into cohorts with regard to the year when the animals were born and yearly samples with age categories for every year when they were alive. We used the Estimator by Parentage Assignment (EPA) to directly estimate both Ne and generation interval for each yearly sample. For cohorts, we estimated the effective number of breeders (Nb) using Linkage Disequilibrium, Sibship Assignment and Approximate Bayesian Computation methods, and extrapolated these estimates to Ne using the generation interval. The Ne estimate by EPA is 276 (183-350 95% CI), meeting the inbreeding-avoidance criterion of Ne > 50 but short of the long-term minimum viable population goal of Ne > 500. The results obtained by the other methods are highly consistent with this result, and all indicate a rapid increase in Ne probably in the late 1990s and early 2000s. The new single-sample approaches to estimation of Ne provide efficient means for including Ne in monitoring frameworks, and will be of great importance for future management and conservation. Genotypes of bears from SloveniaThe dataset contains genotypes of 510 brown bears genotyped on 22 microsatellite loci. They were obtained by genotyping tissue samples of legally killed bears between 2003 and 2008. Genotype on locus G10H is unrealiable (genotyping problems), and locus Mu26 has null alleles. Both were excluded from analysis, and have some missing data. All genotypes are complete on all other loci. Additional ...
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