Grizzly bears without borders: Spatially explicit capture–recapture in southwestern Alberta

ABSTRACT Local perceptions of grizzly bear ( Ursus arctos ) numbers in southwestern Alberta, Canada are incongruent with their threatened status. We used non‐invasive genetic sampling to estimate grizzly bear density and abundance in southwestern Alberta. We established 899 bear rub objects (e.g., t...

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Bibliographic Details
Published in:The Journal of Wildlife Management
Main Authors: Morehouse, Andrea T., Boyce, Mark S.
Format: Article in Journal/Newspaper
Language:English
Published: Wiley 2016
Subjects:
Online Access:http://dx.doi.org/10.1002/jwmg.21104
https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fjwmg.21104
https://onlinelibrary.wiley.com/doi/full/10.1002/jwmg.21104
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Summary:ABSTRACT Local perceptions of grizzly bear ( Ursus arctos ) numbers in southwestern Alberta, Canada are incongruent with their threatened status. We used non‐invasive genetic sampling to estimate grizzly bear density and abundance in southwestern Alberta. We established 899 bear rub objects (e.g., tree, power pole, fence post) for hair sample collection across the study area by surveying trail networks, using geographic information system layers, and working with >70 landowners to identify priority sampling areas. The study area included 2 management zones: the Recovery Zone where the objective was to recover the grizzly bear population, and a Support Zone intended to maintain those bears not exclusively within the Recovery Zone. We visited rub objects every 3 weeks from late May through early November for 8 visits (7 sampling occasions) per field season. We also allowed for opportunistically collected hair samples (e.g., trapped bears, hair at agricultural bear‐conflict sites). We identified species, individual identity, and sex based on nuclear DNA extracted from hair follicles. From 2013 through 2014, we identified 164 individual grizzly bears. Using spatially explicit capture–recapture models (SECR), we estimated density in 2 ways. First, we estimated density for each sex and year separately (2013: M = 9.2/1,000 km 2 in the Recovery Zone and 8.1/1,000 km 2 in the Support Zone, F = 14.9/1,000 km 2 in the Recovery Zone and 13.6/1,000 km 2 in the Support Zone; 2014: M = 7.2/1,000 km 2 in the Recovery Zone and 5.7/1,000 km 2 in the Support Zone, F = 9.0/1,000 km 2 in the Recovery Zone and 8.5/1,000 km 2 in the Support Zone). Second, we did not allow density to vary across years and instead estimated a single density for the study area (M = 8.0/1,000 km 2 in the Recovery Zone and 7.1/1,000 km 2 in the Support Zone, F = 12.4/1,000 km 2 in the Recovery Zone and 10.0/1,000 km 2 in the Support Zone). Though yearly variation occurred, we derived from our density estimates an expected abundance of approximately 67.4 ...