Optimal foraging by a large ungulate in an extreme environment: Wild mountain reindeer select snow-free feeding habitats in winter

Optimal foraging models predict that individual animals will optimize net energy gain by intensifying forage activity and/or reducing forage energy cost. Then, the free distribution model predicts an animal's distribution in a patchy landscape will match the distribution of the resources. If not modified by other factors, such patterns may be expected to be particularly explicit in variable and extreme, forage-limited, and patchy environments, notably alpine and Arctic environments during winter. The large ungulate wild mountain reindeer (Rangifer tarandus tarandus) surviving in such environments is used as a model during the forage-limited winter season. The largest wild reindeer area in Western Europe (Hardangervidda, 8130 km2) is actively managed to sustain 10,000–12,000 wild reindeer. Since 2001, 104 different individuals have been GPS-tracked at 3-hr intervals. In winter, mountain reindeer may either choose to seek out and forage in patchy snow-free habitats, typically on top of wind-blown ridges, or use energy-demanding digging through the snow to reach ground forage (cratering). We use late April satellite data from Landsat 5 and 8 (30 × 30 m), airborne laser scanning subsampling (processed to 1 × 1 m grid), and topographic information (1 m resolution) derived from digital aerial photographs (0.25 × 0.25 m resolution) to delineate snow-free patches, constituting less than 694 km2. By overlaying recorded wild reindeer GPS positions winters 2001–2017 (188,942 positions), we document a strong positive selection for snow-free patches, which were used about four times more frequently than expected from a “random walk” model. On a daily basis, the preference for snow-free areas was slightly stronger in the evenings. In the sustainable management of wild mountain reindeer, the area of snow-free patches is an important predictor of winter forage availability and important winter source areas. It may be derived from remote sensing data