Mapping herbivore habitat quality with high-resolution imagery from unmanned aerial systems
When selecting habitats, herbivores must balance the risk of starvation associated with poor quality foods with the risk of predation and thermal stress associated with poor quality cover. Assessing habitat quality is a primary goal of resource managers and conservation agencies, and surveys of density and cover of vegetation, and availability of forage can provide valuable information about suitability of habitats. Translating assessments of physical characteristics into measurements of functional quality can be difficult and resource intensive, particularly when generalizing to broader spatial and temporal scales. Our objective was to use imagery collected by an unmanned aerial system (UAS) to map multiple dimensions of habitat quality and to predict habitat use by pygmy rabbits (Brachylagus idahoensis) in the sagebrush-steppe.
We flew a UAS over three study sites in Idaho during two seasons (summer and winter), and compared UAS-derived digital surface models (DSMs) with terrestrial LiDAR-derived DSMs. We used high-resolution color imagery and DSMs to classify habitat types into those with relatively high and low food availability, refuge from predators and thermal stress. Future work will compare resource heterogeneity between seasons and examine how differences in habitat quality affect habitat selection of pygmy rabbits.