Data from: Steep and deep: Terrain and climate factors explain brown bear (Ursus arctos) alpine den site selection to guide heli-skiing management ...

Winter recreation and tourism continue to expand worldwide, and where these activities overlap with valuable wildlife habitat, there is greater potential for conservation concerns. Wildlife populations can be particularly vulnerable to disturbance in alpine habitats as helicopters and snowmachines a...

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Bibliographic Details
Main Authors: Crupi, Anthony, Gregovich, David, White, Kevin
Format: Dataset
Language:English
Published: Dryad 2020
Subjects:
Online Access:https://dx.doi.org/10.5061/dryad.dr7sqv9vm
https://datadryad.org/stash/dataset/doi:10.5061/dryad.dr7sqv9vm
Description
Summary:Winter recreation and tourism continue to expand worldwide, and where these activities overlap with valuable wildlife habitat, there is greater potential for conservation concerns. Wildlife populations can be particularly vulnerable to disturbance in alpine habitats as helicopters and snowmachines are increasingly used to access remote backcountry terrain. Brown bears (Ursus arctos) have adapted hibernation strategies to survive this period when resources and energy reserves are limited, and disturbance could negatively impact fitness and survival. To help identify areas of potential conflict between helicopter skiing and denning brown bears in Alaska, we developed a model to predict alpine denning habitat and an associated data-based framework for mitigating disturbance activities. Following den emergence in spring, we conducted three annual aerial surveys (2015–2017) and used locations from three GPS-collared bears (2008–2014) to identify 89 brown bear dens above the forest line. We evaluated brown bear ... : Brown bear den sites were located by aerial survey where latitude and longitude coordinates were collected on handheld GPS. Additional den sites were located by brown bears instrumented with GPS collars. Habitat factors were extracted from the IfSAR dataset and standardized (x-͞x /SD(x)) prior to analysis. To estimate resource availability, we generated randomly distributed locations at the scale of the study area (second-order selection) [82, 83] at a mean density of 500 locations per km2 [84]. ...