Individual-based seasonal habitat selection in a forest-dwelling population of reintroduced bison Bison bison

Mapping habitat selection by threatened species provides critical information for conservation planning. For reintroduced populations, understanding habitat selection is also necessary to predict dispersal and inform selection of new reintroduction sites. Efforts to restore bison Bison bison to the boreal forest hinge on the persistence of geographically isolated populations that occupy diverse landscapes, and for many populations selected habitats are unknown. We used location data from GPS-collared bison to develop seasonal resource selection function (RSF) models and predictive maps for the reintroduced ‘Nahanni’ population. We accounted for variation in individual behaviour by calculating averaged population-level selection coefficients from individual RSFs, and we compared these results to a pooled RSF from all bison. Individual RSFs revealed variation in habitat selection that was not always captured by the pooled RSF, although there were some consistencies. Bison strongly selected forage-rich graminoid-dominated wetlands (fens) during winter, but less so in summer when there were potential tradeoffs with poor footing and biting flies. In summer, bison selected alternative sources of forage such as herbaceous, shrubby and fluvial habitats (i.e. riverine islands and gravel bars). The observed association with fluvial habitat may be an adaptation to low forage availability on this landscape. Bison also selected roads and anthropogenic clearings associated with resource development, demonstrating potential for human–wildlife conflict. Our predictive maps highlight areas of conservation interest, and should be considered in land use planning and environmental assessments. We demonstrate the value of foraging habitat for forest-dwelling bison, particularly in winter. Identifying forage-rich habitat patches, and connectivity between them, is important when considering sites for new reintroductions or expansion of existing populations. More broadly, our approach may be used to identify areas of high conservation interest, where resources do not allow extensive sample sizes of GPS-collared animals.