Grizzly bear response to fine spatial and temporal scale spring snow cover in Western Alberta

Abstract

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 dynamics. This study examines grizzly bear ( Ursus arctos ) spring habitat selection and use across western Alberta, Canada. Made possible by newly available fine-scale snow cover data, this research tests a hypothesis that grizzly bears select for locations with less snow cover and areas where snow melts sooner during spring (den emergence to May 31 st ). Using Integrated Step Selection Analysis, a series of models were built to examine whether snow cover information such as fractional snow covered area and date of snow melt improved models constructed based on previous knowledge of grizzly bear selection during the spring. Comparing four different models fit to 62 individual bear-years, we found that the inclusion of fractional snow covered area improved model fit 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, including fractional snow covered area, date since snow melt, elevation, and distance to road. Results 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. This study is an example of how fine spatial and temporal scale remote sensing data can be used to improve our understanding of wildlife habitat selection and use in relation to key environmental attributes.

Detecting changes in understorey and canopy vegetation cycles in West Central Alberta using a fusion of Landsat and MODIS

“…Berman et al () adapted these techniques to accurately assess inter‐annual change in regional snow cover at a fine spatial scale with greater than 80% accuracy when compared to ground cameras. Results were further used to model grizzly bear response to varying snow conditions (Berman, Coops, Kearney, & Stenhouse, ). These proof‐of‐concept studies highlight the opportunity to use dynamic time warping to model vegetation dynamics over a large region at a fine spatial scale.…”

Changing spring snow cover dynamics and early season forage availability affect the behavior of a large carnivore

“…When considering bear activity in spring, two seasonally dynamic variables are likely the most influential factors governing variationsnow melt (Berman, Coops, Kearney, & Stenhouse, 2019;Pigeon et al, 2016) and forage availability (Roberts et al, 2014 (Roberts et al, 2014). Our results suggest that while bear activity is either unchanged or becoming earlier across the study area, the "wait time" between when individuals become active and when early season forage becomes available is remaining unchanged or decreasing.…”

Denning in brown bears

“…Thus, changes in climate could reduce the duration of hibernation in bears and lead to advanced den exit (Berman, Coops, Kearney, & Stenhouse, 2019;Johnson et al, 2017;. It has been reported how brown bears emerge from winter dens when the ambient temperature reaches a certain level (3.7 ± 1.3 C in Evans et al, 2016), and since warmer springs may promote earlier first den exits (e.g., Delgado et al, 2018;González-Bernardo et al, in press), bears are expected to emerge from dens earlier as the climate continues to warm (Johnson et al, 2017;.…”