Genetic structure in large, continuous mammal populations: the example of brown bears in northwestern Eurasia

Abstract

Knowledge of population structure and genetic diversity and the spatio-temporal demographic processes affecting populations is crucial for effective wildlife preservation, yet these factors are still poorly understood for organisms with large continuous ranges. Available population genetic data reveal that widespread mammals have for the most part only been carefully studied at the local population scale, which is insufficient for understanding population processes at larger scales. Here, we provide data on population structure, genetic diversity and gene flow in a brown bear population inhabiting the large territory of northwestern Eurasia. Analysis of 17 microsatellite loci indicated significant population substructure, consisting of four genetic groups. While three genetic clusters were confined to small geographical areas-located in Estonia, southern Finland and Leningrad oblast, Russia-the fourth cluster spanned a very large area broadly falling between northern Finland and the Arkhangelsk and Kirov oblasts of Russia. Thus, the data indicate a complex pattern where a fraction of the population exhibits large-scale gene flow that is unparalleled by other wild mammals studied to date, while the remainder of the population appears to have been structured by a combination of demographic history and landscape barriers. These results based on nuclear data are generally in good agreement with evidence previously derived using mitochondrial markers, and taken together, these markers provide complementary information about female-specific and population-level processes. Moreover, this study conveys information about spatial processes occurring over multiple generations that cannot be readily gained using other approaches, e.g. telemetry.

Evidence of rapid change in genetic structure and diversity during range expansion in a recovering large terrestrial carnivore

“…R. Soc. B 282: 20150092 a century ago led to at least two different populations [31,47]. Conservation-minded changes in legislation during the second part of the last century led to a controlled harvest of the species and, accompanied by immigration from Russia, resulted in increasing numbers of bears, which dispersed further north and west over time [31,63].…”

“…Since earlier studies have shown a restricted number of genetic clusters in Finland [31][32][33]47], we used a maximum number of K ¼ 10 clusters, and assumed population admixture and correlated allele frequencies within the population. Ten independent runs for each K-value between one and 10 were performed.…”

Brown and Polar Bear Y Chromosomes Reveal Extensive Male-Biased Gene Flow within Brother Lineages

“…Polar bears exhibit low levels of population differentiation at biparentally inherited and mitochondrial markers throughout their range (Paetkau et al 1999;Cronin and MacNeil 2012;Miller et al 2012;Campagna et al 2013). Brown bears, in contrast, show considerable phylogeographic structuring at mitochondrial markers (Davison et al 2011;Edwards et al 2011;Hirata et al 2013;Keis et al 2013), and population structuring can also be discerned at biparentally inherited microsatellites (Paetkau et al 1997;Tammeleht et al 2010;Kopatz et al 2012). Most mtDNA clades are confined to certain geographical regions and are not shared between continents, although one brown bear clade is widespread throughout Eurasia and extends into North America (Korsten et al 2009;Davison et al 2011).…”

“…Surprisingly, all range-wide phylogeographic studies on brown bears have so far relied on mtDNA. Studies of autosomal markers were regionally restricted to either North America or Eurasia (Paetkau et al 1997;Tammeleht et al 2010;Kopatz et al 2012;Cahill et al 2013), and no phylogeographic study of Y chromosome markers in bears exists. However, analysis of male-specific markers is crucial to understand bear evolution in the light of their well-documented male-biased dispersal (McLellan and Hovey 2001;Zedrosser et al 2007).…”

Detecting black bear source–sink dynamics using individual-based genetic graphs

“…For example, our method may find utility in wide-ranging and elusive species where source-sink dynamics has gone undetected (e.g. fur-bearing species, carnivores, marine mammals [46][47][48]). Undetected source-sink dynamics has potentially negative consequences, particularly for harvested species.…”