Background: The habitat use of wild ungulates is determined by forage availability, but also the avoidance of predation and human disturbance. They should apply foraging strategies that provide the most energy at the lowest cost. However, due to data limitations at the scale of movement trajectories, it is not clear to what extent even well-studied species such as red deer (Cervus elaphus) trade-off between forage quality and quantity, especially in heterogeneous alpine habitats characterized by short vegetation periods.
Methods: We used remote sensing data to derive spatially continuous forage quality and quantity information. To predict relative nitrogen (i.e. forage quality) and biomass (i.e. forage quantity), we related field data to predictor variables derived from Sentinel-2 satellite data. In particular, our approach employed random forest regression algorithms, integrating various remote sensing variables such as reflectance values, vegetation indices and optical traits derived from a radiative transfer model. We combined these forage characteristics with variables representing human activity, and applied integrated step selection functions to estimate sex-specific summer habitat selection of red deer in open habitats within and around the Swiss National Park, an alpine Strict Nature Reserve.
Results: The combination of vegetation indices and optical traits greatly improved predictive power in both the biomass (R2 = 0.60, Root mean square error (RMSE) = 88.55 g/m2) and relative nitrogen models (R2 = 0.34, RMSE = 0.28%). Both female and male red deer selected more strongly for biomass (estimate = 0.672 ± 0.059 SE for normalised values for females, and 0.507 ± 0.061 for males) than relative nitrogen (estimate = 0.124 ± 0.062 for females, and 0.161 ± 0.061 for males, respectively). Females showed higher levels of use of the Swiss National Park.
Conclusions: Red deer in summer habitats select forage quantity over quality with little difference between sexes. Females respond more strongly to human activities and thus prefer the Swiss National Park. Our results demonstrate the capability of satellite data to estimate forage quality and quantity separately for movement ecology studies, going beyond the exclusive use of conventional vegetation indices.
Keywords: Cervus elaphus; Biomass; Foraging ecology; Habitat selection; Integrated step selection functions; Machine learning; Nitrogen; PROSAIL; Sentinel-2.
© 2024. The Author(s).