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.