Assessing spatial discreteness of Hudson Bay polar bear populations using telemetry and genetics

• Published in: Ecosphere
• Main Authors: Viengkone, Michelle, Derocher, Andrew E., Richardson, Evan S., Obbard, Martyn E., Dyck, Markus G., Lunn, Nicholas J., Sahanatien, Vicki, Robinson, Barry G., Davis, Corey S.
• Other Authors: Alberta Innovates - Technology Futures, ArcticNet, Churchill Northern Studies Centre, Natural Sciences and Engineering Research Council of Canada, Quark Expeditions, World Wildlife Fund
• Format: Article in Journal/Newspaper
• Language: English
• Published: Wiley 2018
• Subjects: Canada; Hudson; Hudson Bay; Ursus maritimus
• Online Access: http://dx.doi.org/10.1002/ecs2.2364; https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fecs2.2364; https://esajournals.onlinelibrary.wiley.com/doi/pdf/10.1002/ecs2.2364

Abstract Identifying biologically meaningful populations is essential to the conservation and management of at‐risk species. Natural populations can be delineated using a variety of methods including tag recoveries, telemetry, stable isotopes, and population genetics, but understanding the processes that lead to and maintain the demographic and genetic distinctiveness of populations is also important. We combined telemetric and genetic data from three adjacent polar bear ( Ursus maritimus ) populations in Hudson Bay, Canada, to compare two methods of defining structure. We compared the population structure inferred from utilization distributions (UDs) of 62 adult female polar bears tracked by satellite telemetry during the mating season by grouping individuals in two ways: (1) by the management population in which individuals were sampled (capture location), and (2) by population genetic assignment of individuals using marker data (genetic assignment). We found that space‐use overlap varied depending on how individuals were grouped. We found 19.1–34.4% UD overlap when capture locations were used to group individuals, but there was no UD overlap for bears across different genetic groupings. Wildlife management objectives should include consideration of genetic diversity and differentiation, and we found that using genetic assignment to augment analyses from telemetric data provided additional insights on population delineation.