Genetic Monitoring of Brown Bear

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Brown bear female with two cubs in the Pasvik River Valley. Photo: Steinar Wikan (NIBIO Svanhovd).

The research group and genetic lab at NIBIO Svanhovd has been instrumental in advancing monitoring methods and research on brown bears in Norway and Fennoscandia. Today, the Department of Ecosystems in the Barents Region at Svanhovd houses a collection that contains scat and hair samples with sampling efforts ongoing.

This formerly widespread and common species in Fennoscandia was almost exterminated in the early 20th century due to excessive hunting. Nowadays, ~150 individuals are found in Norway and close annual monitoring of the population is conducted to assess the recovery status. Brown bears are an elusive species and it is difficult to obtain demographic data with conventional means.

With the advancements of molecular tools, a scat collection program was initiated in 2006 and demographic data like individual identification and sex are determined by genetic methods. This approach is also advantageous because no handling of animals is involved (i.e., non-invasive) and hence, bears are not disturbed.

In addition, regular hair snare projects are undertaken to non-invasively collect hairs from brown bears in Pasvik.

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Bear going under barbed wire leaving hair behind. Illustration: Leif Ollila.

The research group and genetic lab at NIBIO Svanhovd has been instrumental in advancing monitoring methods and research on brown bears in Norway and Fennoscandia. Today, the Department of Ecosystems in the Barents Region at Svanhovd houses a collection that contains scat and hair samples with sampling efforts ongoing.

This detailed sampling scheme combined with the application of molecular tools (Andreassen et al. 2012, Bidon et al. 2013) has also enabled research in the recovering Fennoscandian brown bear populations (Hagen et al. 2015, Schregel et al. 2012, 2015, 2017) describing spatial connectivity and differentiation patterns. Brown bears in Fennoscandia belong to two different populations, with the population in northern Norway being more closely related and connected to the Russian bear populations (Kopatz et al. 2014). Finally, the recent recolonization event allows for the testing of theoretical biological models that help to understand dynamics in recovering natural populations (Hagen et al. 2015).

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Abstract

The degree of gene flow within and among populations, i.e. genetic population connectivity, may closely track demographic population connectivity. Alternatively, the rate of gene flow may change relative to the rate of dispersal. In this study, we explored the relationship between genetic and demographic population connectivity using the Scandinavian brown bear as model species, due to its pronounced male dispersal and female philopatry. Thus, we expected that females would shape genetic structure locally, whereas males would act as genetic mediators among regions. To test this, we used eight validated microsatellite markers on 1531 individuals sampled noninvasively during country-wide genetic population monitoring in Sweden and Norway from 2006 to 2013. First, we determined sex-specific genetic structure and substructure across the study area. Second, we compared genetic differentiation, migration/gene flow patterns, and spatial autocorrelation results between the sexes both within and among genetic clusters and geographic regions. Our results indicated that demographic connectivity was not a reliable indicator of genetic connectivity. Among regions, we found no consistent difference in long-term gene flow and estimated current migration rates between males and females. Within regions/genetic clusters, only females consistently displayed significant positive spatial autocorrelation, indicating male-biased small-scale dispersal. In one cluster, however, males showed a dispersal pattern similar to females. The Scandinavian brown bear population has experienced substantial recovery over the last decades; however, our results did not show any changes in its large-scale population structure compared to previous studies, suggesting that an increase in population size and dispersal of individuals does not necessary lead to increased genetic connectivity. Thus, we conclude that both genetic and demographic connectivity should be estimated, so as not to make false assumptions about the reality of wildlife populations.

To document

Abstract

Noninvasively collected genetic data can be used to analyse large-scale connectivity patterns among populations of large predators without disturbing them, which may contribute to unravel the species’ roles in natural ecosystems and their requirements for long-term survival. The demographic history of brown bears (Ursus arctos) in Northern Europe indicates several extinction and recolonization events, but little is known about present gene flow between populations of the east and west. We used 12 validated microsatellite markers to analyse 1580 hair and faecal samples collected during six consecutive years (2005–2010) in the Pasvik Valley at 70_N on the border of Norway, Finland and Russia. Our results showed an overall high correlation between the annual estimates of population size (Nc), density (D), effective size (Ne) and Ne ⁄Nc ratio. Furthermore, we observed a genetic heterogeneity of _0.8 and high Ne ⁄Nc ratios of _0.6, which suggests gene flow from the east. Thus, we expanded the population genetic study to include Karelia (Russia, Finland), Va¨sterbotten (Sweden) and Troms (Norway) (477 individuals in total) and detected four distinct genetic clusters with low migration rates among the regions. More specifically, we found that differentiation was relatively low from the Pasvik Valley towards the south and east, whereas, in contrast, moderately high pairwise FST values (0.91–0.12) were detected between the east and the west. Our results indicate ongoing limits to gene flow towards the west, and the existence of barriers to migration between eastern and western brown bear populations in Northern Europe.