DOI: 10.5061/dryad.qbzkh18h9
title: Native range estimates for red-listed vascular plants

description: Besides being central for understanding both global biodiversity patterns
 and associated anthropogenic impacts, species range maps are currently
 only available for a small subset of global biodiversity. Here, we provide
 a set of assembled spatial data for terrestrial vascular plants listed at
 the global IUCN red list. The dataset consists of pre-defined native
 regions for 47,675 species, density of available native occurrence records
 for 30,906 species, and standardized, large-scale Maxent predictions for
 27,208 species, highlighting environmentally suitable areas within
 species’ native regions. The data was generated in an automated approach
 consisting of data scraping and filtering, variable selection, model
 calibration and model selection. Generated Maxent predictions were
 validated by comparing a subset to available expert-drawn range maps from
 IUCN (n = 4,257), as well as by qualitatively inspecting predictions for
 randomly selected species. We expect this data to serve as a substitute
 whenever expert-drawn species range maps are not available for conducting
 large-scale analyses on biodiversity patterns and associated anthropogenic
 impacts.
description: The dataset includes spatial data for 47,675 species at different
 levels of detail. In total, range estimates (i.e. relative environmental
 suitability within native regions) have been predicted for 27,208 species
 using maximum entropy modelling (Maxent), for 30,906 species native
 occurrence records from the <em>global biodiversity information
 facility</em> (GBIF) are provided, and for 47,675 species the
 spatial extent of its native regions, retrieved from <em>Plants of
 the World online</em> and based on the world geographical scheme for
 recording plant distributions (WGSRPD), is provided.
description: All
 gathered and generated data are stored in netCDF files and can be called
 by specifying a <i>varname</i>. The suggested data is stored
 in folder <i>basic</i>, containing two netCDF files (default
 output and raw output). These files assemble the best performing Maxent
 prediction (<i>varname</i>: Maxent prediction) for each
 species selected based on the highest harmonic mean between AUC and
 AUC<sub>PR</sub>, along with number of occurrence records per
 cell (<i>varname</i>: Presence cells) and rasterized native
 WGSRPD-<i>regions</i> (<i>varname</i>: Native
 region). The folder
 <i>advanced</i> contains two netCDF files (default output and
 raw output). These files contain one Maxent prediction for each occurrence
 data type (<i>varname</i>: Model 1, Model 2 or Model 3),
 instead of best performing Maxent prediction (i.e.
 <i>varname</i> Maxent prediction is not applicable). Number of
 occurrence records per cell (<i>varname</i>: Presence cells)
 and rasterized native WGSRPD-<i>regions</i>
 (<i>varname</i>: Native region) are identical to the data
 stored in the folder <i>basic</i>. Each band in all netCDF files assembles the mentioned variables for one species. The corresponding bands can be looked up in the corresponding metadata (i.e. <i>speciesID</i>). Furthermore, the metadata can be used to select appropriate cut-off thresholds for generating binary range maps, filter models based on species, performance, or desired datatypes, and to lookup the relevant study extent for masking individual predictions.