A global long-term ecoregion-level dataset of biodiversity indicators for terrestrial vertebrates under climate and habitat change

Abstract. Climate and habitat change are reshaping global biodiversity, yet long-term, spatially explicit datasets that capture these dynamics across ecologically meaningful regions remain limited. Here, we present a global spatiotemporal dataset of ecoregion-level biodiversity indicators for terrestrial vertebrates derived from species-specific Area of Habitat (AOH). By integrating species occurrence records, expert-derived range maps, climate data, and temporally explicit habitat maps, we reconstructed distributions for 19146 species of amphibians, birds, mammals, and reptiles. We then derived four complementary biodiversity indicators—species richness, threatened species richness, species endemism, and AOH density—for global terrestrial ecoregions at five time points (1990, 2020, 2030, 2050, and 2100), with future projections under SSP245 and SSP585. Validation at both species and dataset levels demonstrated good performance. Predicted AOH consistently assigned higher suitability to independent occurrence records than to the broader range background, and estimated richness closely reproduced the major spatial patterns of occurrence-derived richness across ecoregions. In 2020, the four indicators showed distinct but broadly concordant spatial patterns, with the highest overall values concentrated in tropical ecoregions. Future projections revealed marked spatial heterogeneity, with declines in multiple indicators concentrated in many tropical ecoregions by 2100 and generally becoming stronger under SSP585. This dataset provides a globally consistent and ecologically meaningful resource for biodiversity monitoring, macroecological analysis, and conservation assessment under ongoing climate and habitat change. The dataset supporting this study is publicly available at https://doi.org/10.5281/zenodo.20119261.