While ever-larger syntheses of Anthropocene species distributions have demonstrated that species are shifting their ranges, individual responses are often context-dependent and we have yet to fully understand the general processes driving these dynamics. To advance the field, this session will bring together two historically divergent approaches to building generalizable knowledge about range shifts. First, ecological theory is designed to abstract away from system details in ways that provide useful insight of broad utility. Second, the explosion of data on where and when species have been found and new approaches to data science provide opportunities for testing general processes and principles across taxa, ecosystem, and realms. However, most of the first generation of big data approaches to understanding dynamic species distributions left much of ecological theory behind other than concepts of the Grinnellian niche. This approach implicitly assumes that species remain in equilibrium with their habitat. In contrast, ecological theory makes clear that species and communities are rarely at equilibrium, that transient dynamics are common, and that ecology and evolution often operate on similar timescales. How can we move beyond equilibrium and non-evolutionary assumptions in understanding species ranges and their dynamics across space and time? This session will focus on novel efforts to integrate ecological theory with big data to understand how, why, and when species ranges move and how this information can be used to guide societal decisions and climate adaptation. We will start with novel ecological theory for dynamic environments, explore approaches to integrating data with mechanistic ecological models, and end with the applications to decision making.