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Predator-prey co-occurrence in harvest blocks

Citation

McKay, Tracy (2022), Predator-prey co-occurrence in harvest blocks, Dryad, Dataset, https://doi.org/10.5061/dryad.3n5tb2rmn

Abstract

Forest harvesting alters habitat, impacts wildlife, and disrupts ecosystem function. Across the boreal forest of Canada, forest harvesting affects ungulate prey species and their predators, with cascading impacts on other species, including threatened woodland caribou. We used camera and vegetation data and occupancy modeling to investigate what characteristics in and around forestry harvest blocks influenced the occupancy and co‐occurrence of primary prey (elk, moose, mule deer, white‐tailed deer) and predators (black bear, cougar, grizzly bear, wolf) in harvest blocks. Occupancy was linked to forage, the surrounding habitat and anthropogenic disturbance, and silviculture practices. Black and grizzly bear occupancy was influenced by the presence of deer, and bear–deer co‐occurrence was influenced by site‐specific silviculture practices and surrounding anthropogenic disturbance. In the context of caribou recovery, our results indicate that forestry within caribou ranges could consider site‐specific silviculture practices and landscape‐level planning to reduce use of harvest blocks by primary prey. Future caribou recovery efforts may also consider the roles of deer and bears in caribou predation risk. Our study provides the first insights into the impacts of forestry and silviculture on boreal forest predator–prey co‐occurrence and provides practical management applications to mitigate the impacts of anthropogenic activities on the boreal forest ecosystem into the future.

Methods

Wildlife (detection) data were collected using remote cameras and processed using detectionHistory in camtrapR to generate detection histories. Site data include forest stand characteristics, hiding cover, and forage (vegetation) collected at vegetation survey plots, and silviculture data obtained from forestry partners. Camera data were processed using camtrapR. All datasets were processed and analyzed in R Studio.

Usage Notes

Any program that can open csv files. R Studio is required to analyze datasets.

Funding

Alberta Conservation Association, Award: 030-00-90-305

Forest Resource Improvement Association of Alberta, Award: FFI-17-004

Sustainable Forestry Initiative, Award: 2018-003

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Project Learning Tree

West Fraser Timber Co. Ltd

Weyerhaeuser Company