Native range estimates for red-listed vascular plants.

Area of Science:

• Biodiversity science
• Conservation biology
• Geographic Information Systems (GIS)

Background:

• Species range maps are crucial for understanding biodiversity patterns and human impacts.
• Existing range maps cover only a small fraction of global biodiversity, limiting large-scale analyses.
• There is a need for comprehensive spatial data for conservation and ecological research.

Purpose of the Study:

• To assemble and generate spatial data for terrestrial vascular plants listed on the IUCN Red List.
• To provide a valuable resource for large-scale biodiversity research and conservation planning.
• To create a substitute for expert-drawn range maps when they are unavailable.

Main Methods:

• Automated data scraping, filtering, and variable selection.
• Species distribution modeling using Maxent for predicting suitable habitats.
• Validation of model predictions against expert-drawn maps and qualitative inspection.

Main Results:

• A dataset including native regions for 47,675 species, occurrence record density for 30,906 species, and Maxent predictions for 27,208 species.
• Standardized, large-scale predictions highlighting environmentally suitable areas within native ranges.
• Validated model predictions demonstrating reliability for broad-scale analyses.

Conclusions:

• The generated spatial data serves as a critical resource for biodiversity research.
• This dataset can facilitate large-scale analyses of biodiversity patterns and anthropogenic impacts.
• The study addresses the data gap for species range information, supporting conservation efforts.