Covariates
We divided the year into two seasons, “spring” and “autumn”. Spring was defined as ordinal day 1 (1st January) to ordinal day 212 (1st August in non-leap years), and autumn for the rest of the year. Ordinal day 212 was chosen as all mountain hares had moulted to their summer brown coats by this date and had not started moulting back to winter white. Altitude and latitude were extracted based on camera trap positions. We obtained altitude from a digital elevation model (DEM) with 50 m2 resolution (Kartkatalogen 2007) (Suppl. 2) using the raster package’s (Hijmans 2022) extract function. We obtained climate zone as a continuous variable with a resolution of 1 km2 from Bakkestuen et al (2008) (Suppl. 1). We converted climate zone vector data to a raster using the fasterize (version 1.0.4) package (Ross 2020). Bakkestuen et al (2008) mapped climate zones by conducting principal component analysis (PCA) using terrain data, climatic data, hydrological data, and geological data. A positive PCA value indicates a continental climate whereas a negative value indicates a coastal climate.