Global intraspecific diversity of marine forests of brown macroalgae predicted by past climate conditions.
Journal:
Communications biology
PMID:
40348884
Abstract
Global patterns of intraspecific genetic diversity are key to understanding evolutionary and ecological processes. However, insights into the distribution and drivers of genetic diversity remain limited, particularly for marine species. Here, we explain and predict the genetic diversity of cold and temperate brown macroalgae using genetic data from 29 species and a machine-learning algorithm that incorporates contemporary and past climate conditions during the Last Glacial Maximum (~20,000 years ago) based on the niche centroid hypothesis. We apply this model to the distribution of 280 species and predict their global genetic diversity. Our results show reduced genetic diversity away from the niche centroid, identifying past climate conditions as key drivers of contemporary genetic diversity. Regions with high genetic diversity for multiple species emerge, matching biogeographic patterns of species richness. The mapped diversity hotspots establish timely baselines for brown macroalgae biogeography, evolutionary potential and conservation, contributing to the Post-2020 Global Biodiversity Framework.