Species distribution models (SDM) are widely used to assess the potential impacts of climate change on biota. Results from SDM-based studies have predicted substantial shifts in geographic distributions and increased extinction risk for many species. However, the ability of these models to accurately represent distributions in novel climatic conditions remains largely unknown. One of the few ways to robustly assess the ability of SDMs to accurately predict climate change impacts is to use temporally independent datasets of species distributions and climatic conditions. When such data are available, it is possible to develop SDMs in one time frame and directly test their ability to predict species distributions in another time frame. In this study, I am using two datasets of vascular plant distributions from the mountain ranges of California, one collected in the 1930’s and one collected in the 2000’s, each containing >13,000 vegetation survey plots. The primary objectives of my study are to 1) describe the effects of recent climate change on the geographic distributions of vascular plants in California, 2) quantify the effects of spatially explicit factors on SDM transferability, 3) determine how disturbance processes, in this case wildfire, affect SDM projections, and 4) quantify the degree to which departures from climatic equilibrium (niche shifts) affect SDM transferability. By linking observed shifts in distributions to spatially explicit estimates of SDM accuracy this study will provide conservation practitioners with a robust framework for determining the conditions under which SDM projections will accurately represent future conditions, and for identifying locations across the landscape where climate change mitigation strategies may be most successful.