Coupling fossil records and traditional discrimination metrics to test how genetic information improves species distribution models of the European beech Fagus sylvatica

Species distribution models (SDMs) are widely used to hindcast or forecast suitable habitat conditions during climate change. Although distant populations of a given species may show local adaptations diverging environmental conditions, traditional SDMs disregard intraspecific variation. Yet, incorporating genetic information into could improve predictions. Here we aimed at investigating whether genetically informed would outperform SDMs. Using published on the spatial structure European Beech Fagus sylvatica L. (1753), built lineage-specific for each phylogenetic group species. We then combined all single SDM that compared against approach. finally SDMs’ predictions independent datasets present-day as well fossil data from Mid-Holocene, using six metrics model performance. found aggregating increased performances identify areas currently occupied by F. sylvatica. In comparison SDM, assigned higher probabilities occurrence Mid-Holocene locations where records were found. Aggregating seems approach, especially so when aim is potentially occupancy. This be particularly useful identification cryptic refugia remain undetected Genetically have potential our understanding redistribution under