Integrative Demographic Modelling Reduces Uncertainty in Estimated Rates of Species' Historical Range Shifts

Aim: Biogeographers have used three primary data types to examine shifts in tree ranges in response to past climate change: fossil pollen, genetic data and contemporary occurrences. Although recent efforts have explored formal integration of these types of data, we have limited understanding of how integration affects estimates of range shift rates and their uncertainty. We compared estimates of biotic velocity (i.e. rate of species' range shifts) using each data type independently to estimates obtained using integrated models.Location: Eastern North America.Taxon: Fraxinus pennsylvanica Marshall (green ash).Methods: Using fossil pollen, genomic data and modern occurrence data, we estimated biotic velocities directly from 24 species distribution models (SDMs) and 200 pollen surfaces created with a novel Bayesian spatiotemporal model. We compared biotic velocity from these analyses to estimates based on coupled demographic-coalescent simulations and Approximate Bayesian Computation that combined fossil pollen and SDMs with population genomic data collected across the F. pennsylvanica range.Results: Patterns and magnitude of biotic velocity over time varied by the method used to estimate past range dynamics. Estimates based on fossil pollen yielded the highest rates of range movement. Overall, integrating genetic data with other data types in our simulation-based framework reduced apparent uncertainty in biotic velocity estimates and resulted in greater similarity in estimates between SDM- and pollen-integrated analyses.Main Conclusions By reducing uncertainty in our assessments of range shifts, integration of data types improves our understanding of the past distribution of species. Based on these results, we propose further steps to reach the integration of these three lines of biogeographical evidence into a unified analytical framework.