Investigating grizzly bear responses to spring snow dynamics through the generation of fine spatial and temporal scale snow cover imagery in Alberta, Canada

Snow dynamics influence seasonal behaviors of wildlife, such as denning patterns and habitat selection related to the availability of food resources. Under a changing climate, characteristics of the temporal and spatial patterns of snow are predicted to change, and as a result, there is a need to be...

Full description

Bibliographic Details
Main Author: Berman, Ethan
Format: Thesis
Language:English
Published: University of British Columbia 2019
Subjects:
Online Access:http://hdl.handle.net/2429/68302
Description
Summary:Snow dynamics influence seasonal behaviors of wildlife, such as denning patterns and habitat selection related to the availability of food resources. Under a changing climate, characteristics of the temporal and spatial patterns of snow are predicted to change, and as a result, there is a need to better understand how species interact with snow. Through the generation of fine-scale snow cover data, this thesis examines grizzly bear (Ursus arctos) spring habitat selection and use in the Yellowhead Bear Management Area, Alberta, Canada. First, a new approach was developed to create a daily time-series of 30-m resolution snow cover observations (called SNOWARP). SNOWARP was derived from daily Moderate Resolution Imaging Spectroradiometer (MODIS) data to capture the temporal dynamics of snow cover and Dynamic Time Warping to re-order historical Landsat observations to account for inter-annual variability. The SNOWARP product was produced for 2000-2018 and calibrated against a network of time-lapse cameras and snow pillows. Results indicate the root mean squared error of the fractional product ranges from 31.3% to 68.3%, while F score of the binary product ranges from 87.7% to 98.6%. Second, data from SNOWARP and other environmental variables were combined with GPS collar locations from grizzly bears to test the hypothesis that grizzly bears select for locations with less snow cover and areas where snow melts sooner during spring. Using Integrated Step Selection Analysis, a series of models were built to examine weather snow variables improved models constructed based on previous knowledge of grizzly bear selection during the spring. Comparing four different models fit to 62 individual bear-years, it was found that the inclusion of fractional snow covered area (fSCA) improved model accuracy 60% of the time based on Akaike Information Criterion tallies. Probability of use was then used to evaluate grizzly bear habitat use in response to snow and environmental attributes. The results of this thesis provide one example of the application of newly derived daily 30-m fSCA and indicate grizzly bears select for lower elevation, snow-free locations during spring, which has important implications for management of threatened grizzly bear populations in consideration of changing climatic conditions. Forestry, Faculty of Graduate