Habitat selection and movement are key mechanisms by which animals can respond to and potentially cope with highly variable and rapidly changing environmental conditions. Optimal responses likely vary, however, depending on the severity and scope of limiting conditions. We tested this hypothesis using a facultative migrant species, the Great Gray Owl (Strix nebulosa), which exhibits high inter- and intra-individual variation in the timing, direction, and distance of winter movements. Specifically, we evaluated whether espisodic, spatiotemporally variable “locked-pasture” snow conditions, which restrict access to subnivean food, prompted shifts in habitat selection or long-distance movements by owls. We GPS-tracked 42 owls across the annual cycle within the Greater Yellowstone Ecosystem, USA during 2017–2022. We used a novel ecological application of SnowModel, a snow evolution modeling system, to estimate fine-scale, physical snow properties likely to influence prey access. Variables included snow depth, snow crusts produced by wind, and ice crusts produced by melt-freeze and rain-on-snow events. Owls proximately avoided deeper snow and more severe, heterogeneously distributed wind crusts via local shifts in habitat selection. However, more widely distributed and persistent ice crusts elicited long-distance movements away from affected home ranges. Ultimately, the specific behavioral tactics employed varied with the severity, spatial extent, and duration of limiting environmental conditions. Our results provide a clear demonstration of behavioral flexibility in response to extremely limiting, highly variable environmental conditions. Such behavioral responses determine species distribution, with implications for community dynamics in spatiotemporally variable systems. Such understanding of responses to environmental variability is increasingly important given the scope of on-going global change.

We used GPS tracking and remotely-sensed environmental data to evaluate whether breeding-season habitat selection by adult male Strix nebulosa (Great Gray Owls) (n = 19) varied across diel periods (dawn, day, dusk, and night). We focused specifically on male owls because their breeding habitat selection remains largely unknown despite the critical role they play as food provisioners. To address knowledge gaps related to nocturnal habitat, we also evaluated finer-scale, microhabitat selection by male owls at night. Generally, S. nebulosa are associated with mature forests for nesting and meadows for foraging. Yet, in our study, owls avoided herbaceous wetlands during the day but strongly selected them at dawn, dusk, and at night, indicating time-dependent habitat selection. Moreover, owls avoided dry meadows at all times of the day, suggesting that wet rather than xeric meadows are important for foraging. Owls also preferred nighttime microhabitats that facilitated foraging, such as those with presence of primary prey and open understories dominated by graminoids and forbs. During the daytime, owls preferred higher canopy cover and areas with increased soil moisture, which likely provided suitable roosting habitat. Across taxa, understanding of habitat preferences across sexes, behaviors, activity periods, temporal windows, and other contexts can improve the identification and conservation of critical habitat for wildlife. Our work contributes to understanding of how animals balance resources related to food provisioning versus safety, both of which are critical for individual fitness and population persistence.

Pregnant polar bears (Ursus maritimus) excavate maternal dens in seasonal snowdrifts during fall along Alaska’s Beaufort Sea coast to shelter their altricial young during birth and development. With recent sea ice decreases, bears are denning more frequently on land. Each year, the weather and blowing-snow conditions control the creation of snowdrifts across the landscape, and the available snowdrift den habitat can vary widely from one year to the next, depending on the late fall and early winter air temperature, snowfall, and wind speed and direction. We implemented a physics-based, spatiotemporal, polar bear snowdrift den habitat model (SnowDens-3D) across the eastern Alaska Beaufort Sea coast (an area of approximately 17,000 km^2^). High-resolution (2.0 m) topography data were provided by the ArcticDEM, and daily meteorological forcings were provided by NASA’s MERRA-2 reanalysis. A 21-year (2000–2020) SnowDens-3D simulation was performed, and model outputs were compared with 91 historical polar bear den locations. The year-specific simulations produced viable den habitat for 98% of the observed den locations. The interannual variation in den habitat area over the 21-year period increased by approximately a factor of three from the minimum year (2001; 554 km^2^) to the maximum year (2017; 1,566 km^2^). This data archive provides the key den and den-habitat datasets produced, used, and analyzed by this project.