Shijia Peng, Aaron M Ellison, Charles Davis 

Conventional species distribution models (SDMs) typically consider only abiotic factors, thus overlooking critical biotic dimensions, including functional traits that play an important role determining species’ distributions in changing environments. Process-based models explicitly incorporate functional traits and have been applied to SDMs. However, their parameterization can be complex and require data that are unavailable for most species. Recently developed hierarchical trait-based models use widely available data and facilitate the incorporation of traits into SDMs at broad temporal, spatial, and taxonomic scales. Despite their promise, however, existing hierarchical trait-based models fail to accommodate changing trait spaces under different climate conditions. Here, we provide a new, simplified framework for hierarchical trait-based SDMs that integrate individuals’ trait responses into forecasts of species range shifts in response to ongoing climate changes. We further discuss the utility of phylogenetic information for building trait-based SDMs and holistically enhancing our understanding of species responses to global changes. This work will contribute to an improved understanding of how traits affect species distributions along environmental and temporal gradients and facilitate the application of trait-based SDMs across large temporal, spatial and taxonomic scales.