Distribution data for individual species (e.g. range maps) is central for understanding both global biodiversity patterns and associated anthropogenic impacts. Our aim is to provide a comprehensive set of spatial data for a large number of, so far unmapped, vascular plant species, supporting the development of future assessments of global biodiversity impacts and distributions.
The dataset consists of native regions retrieved from
Plants of the World online
for 47,675 species, density of available native occurrence records retrieved from
for 30,906 species, and standardized, large-scale
predictions for 27,208 species, highlighting environmentally suitable areas within species' native regions.
Spatial predictions were generated by fitting k-fold cross-validated MaxEnt models using three differently treated occurrence data types (i.e. different degree of spatial filtering: no filter, presence cells, thinned presence cells). Up to 96 different models were fitted for each species to find optimal predictors (out of bioclimatic & landcover variables), model settings and data type. The best prediction was selected for each species based on common performance metrics.
A complete description of dataset and methods is published in Scientific Data: