Environmental variation can drive spatial and temporal changes in predator-prey encounter dynamics, with downstream consequences for prey vulnerability and predator foraging decisions. As such, understanding how the environment influences fine-scale spatiotemporal partitioning of prey and subsequent predator movement is critical for determining changes in predation. Here, we explore how predator-prey-environment interactions unfold between mule deer (Odocoileus hemionus), federally endangered Sierra Nevada bighorn sheep (Sierra bighorn; Ovis canadensis sierrae), and mountain lions (Puma concolor) with a strong environmental driver (climate) throughout the eastern Sierra Nevada mountains of California. We assessed the extent to which mule deer movement provides a shifting resource surface that attracts mountain lions to predictable, seasonally specific ranges that closely align to those of deer, and vary in their proximities to Sierra bighorn. We developed an integrated spatial model using GPS and demographic data to predict spatiotemporally varying mule deer densities by combining connectivity (modeled through an environmentally-informed integrated step selection analysis) with local population growth (through an environmentally-informed population model). We then estimated the strength of mountain lion movement responses to those densities using an integrated Bayesian hierarchical model. Ultimately, this model will provide insight into selecting management strategies that reduce predation risk on Sierra bighorn.