In response to global change, species must adapt to environmental changes or move to track suitable habitat in order to persist. In this symposium, we present research using interdisciplinary approaches to better understand and predict a population’s ability to track changing environments due to global warming and habitat loss. In response to global warming, species shift their ranges poleward to track suitable habitat for growth, survival, and reproduction. Meanwhile, habitat loss results in the loss of both species and functional diversity. Changes in climate and human land use influence woody plant encroachment in grassy biomes, with implications for biodiversity and ecosystem processes. We can predict the ability of populations to persist and track suitable habitat in response to different global change scenarios by parameterizing mathematical models with data on dispersal and demography. Data on dispersal and demography are intensive to collect; hence, fundamental research on population dynamics and spread often focus on a few well-parameterized case studies. In this symposium, we harness the growing availability and accessibility of data with advances in spatial population models to estimate the vulnerability of species to global warming, habitat loss, and encroachment. While data are becoming more available and accessible, the joint data on dispersal and demography tend to be sparse across species. Connecting population models that consider the individual and joint effects of global warming and habitat loss with available data requires careful consideration of the uncertainty in the data as well as challenges such data sparsity. The symposium discusses several novel approaches to tackle these limitations by synthesizing advances in mathematical models, publicly-available data, and experiments. Bogen et al predict spreading speeds for a range of simulated species that vary in functional traits using a virtual species approach. They synthesize available data in dispersal, demography, and functional traits using Bayesian multivariate methods to generate virtual species. Building on these results, Beckman et al developed a method that predicts the global distribution of spreading speeds and critical patch sizes that depend on the distribution and covariance of dispersal ability and demography across species. However, in these recent projects, climate warming and habitat loss are treated separately. Zhou et al. developed moving habitat models, which is a framework where climate warming and habitat loss may jointly affect species persistence. Finally, Drees et al parameterize these models with experiments to study the encroachment of woody species in grasslands.