| Shifts in distribution and abundance in response to climate change have been documented in a wide array of species and ecosystems. Contemporary methods for predicting how a species will respond to climate change have focused on creating correlative species distribution models of a species current range and projecting that into future climate scenarios. This method has generally been successful at identifying distributions at a broad scale, however, it is unable to assess fine scale distribution, due to a mismatch in spatial scale between climate data and the scale at which most species experience their environment. As a species that is physiologically limited to areas with cool, moist climate, the endangered Point Arena mountain beaver (PAMB; Aplodontia rufa nigra) is a model organism for studying range restrictions based on microclimate variables. Using temperature data loggers and LiDAR, I created downscaled climate layers and used them to create fine-scale distribution models for PAMB. Additionally, I used broad scale distribution models to compare the climatic niche of the seven subspecies of mountain beaver across the range. The fine scale models will help define critical habitat and comparing distribution models of the different subspecies may provide insight on how the species has responded to past climate change. |