RESUMEN
Trait-based approaches are becoming extremely common in ecological modeling and the availability of traits databases is increasing. However, data availability is often biased towards particular regions and taxa, with many taxa (e.g., bats) often under-represented. Here, we present the AfroBaT dataset, a compilation of trait data on 320 African bat species containing 76,914 values for 86 traits focusing on morphology, reproduction, life-history, trophic ecology, and species distributions. All data were gathered from published literature following the ecological trait-data standard procedure. Missing data for both numerical and categorical traits were imputed with a machine learning approach including species phylogeny. Trophic ecology traits showed the highest coverage in the literature (72% of the species averaged over all traits), while reproductive traits the lowest. Our data imputation improved the coverage of AfroBaT especially for reproductive traits, going from 27% to 58% of the species covered. AfroBaT has a range of potential applications in macroecology and community ecology, and the availability of open-access data on African bats will enable collaboration and data-sharing among researchers.