Data from: Spatiotemporally variable snow properties drive habitat use of an Arctic mesopredator ...

• Main Authors: Glass, Thomas W., Robards, Martin D.
• Format: Dataset
• Language: English
• Published: Movebank Data Repository 2023
• Subjects: Gulo gulo; animal movement; animal tracking; Arctic; GPS; light-level logger; satellite telemetry; wolverine; Climate change
• Online Access: https://dx.doi.org/10.5441/001/1.290; https://datarepository.movebank.org/handle/10255/move.1651

Climate change is rapidly altering the composition and availability of snow, with implications for snow-affected ecological processes, including reproduction, predation, habitat selection, and migration. How snowpack changes influence these ecological processes is mediated by physical snowpack properties, such as depth, density, hardness, and strength, each of which is in turn affected by climate change. Despite this, it remains difficult to obtain meaningful snow information relevant to the ecological processes of interest, precluding a mechanistic understanding of these effects. This problem is acute for species that rely on particular attributes of the subnivean space, for example depth, thermal resistance, and structural stability, for key life-history processes like reproduction, thermoregulation, and predation avoidance. We used a spatially explicit snow evolution model to investigate how habitat selection of a species that uses the subnivean space, the wolverine, is related to snow depth, snow ...