Winter Space Use of Coyotes in High-Elevation Environments: Behavioral Adaptations to Deep-Snow Landscapes

In the last century, coyotes (Canis latrans) have expanded their range geographically, but have also expanded their use of habitats within currently occupied regions. Because coyotes are not morphologically adapted for travel in deep snow, we studied coyote space use patterns in a deep-snow landscape to examine behavioral adaptations enabling them to use high elevations during winter. We examined the influence of snow depth, snow penetrability, canopy cover, and habitat type, as well as the rates of prey and predator track encounters, on coyote travel distance in high-elevation terrain in northwestern Wyoming, USA. We backtracked 13 radio-collared coyotes for 265.41 km during the winters of 2006–2007 and 2007–2008, and compared habitat use and movement patterns of the actual coyotes with 259.11 km of random travel paths. Coyotes used specific habitats differently than were available on the landscape. Open woodlands were used for the majority of coyote travel distance, followed by mixed conifer, and closed-stand spruce–fir. Prey track encounters peaked in closed-stand, mature Douglas fir, followed by 50- to 150-year-old lodgepole pine stands, and 0- to 40-year-old regeneration lodgepole pine stands. Snowmobile trails had the most variation between use and availability on the landscape (12.0 % use vs. 0.6 % available). Coyotes increased use of habitats with dense canopy cover as snow penetration increased and rates of rodent and red squirrel track encounters increased. Additionally, coyotes spent more time in habitats containing more tracks of ungulates. Conversely, use of habitats with less canopy cover decreased as snow depth increased, and coyotes traveled more directly in habitats with less canopy cover and lower snow penetration, suggesting coyotes used these habitats to travel. Coyotes persisted throughout the winter and effectively used resources despite deep snow conditions in a high-elevation environment