Predicting undetected native vascular plant diversity at a global scale

Vascular plants are diverse and a major component of terrestrial ecosystems, yet their geographic distributions remain incomplete. Here, I present a global database of vascular plant distributions by integrating species distribution models calibrated to species’ dispersal ability and natural habitats to predict native range maps for 201,681 vascular plant species into unsurveyed areas. Using these maps, I uncover unique patterns of native vascular plant diversity, endemism, and phylogenetic diversity revealing hotspots in under-documented biodiversity-rich regions. These hotspots, based on detailed species-level maps, show a pronounced latitudinal gradient, strongly supporting the theory of increasing diversity towards the equator. I trained random forest models to extrapolate diversity patterns under unbiased global sampling and identify overlaps with modelled estimations but unveiled cryptic hotspots that were not captured by modelled estimations. Only 29-36% of extrapolated plant hot..., Experimental design
The experimental design is divided into six steps (Fig. S1) that include: (i) Source data, the raw occurrence data used to produce the global species’ range polygons; (ii) Data cleaning, which describes how errors and inconsistencies were minimized in the input data; (iii) Geographic modeling of polygons, describing how alpha hull polygons were generated from point occurrences; (iv) Species dispersal capacity and calibration area, describes how I incorporated species-specific dispersal ability in defining a calibration area for modeling the species distributions; (v) Background points, describes how background points were selected for the species distribution modeling; and (v) Species distribution modeling, describes the estimation of species distributions based on environmental conditions that correlate with known occurrences, and calibrated to species’ realized niche.
Step1: Source data. The primary source of occurrence data used in this study was downloaded from G..., , # Data from: Predicting undetected native vascular plant diversity at a global scale

**Data description within the folder:**
This folder includes the R scripts for the figures and a subset of the data for Daru (2024) paper.

1. `plant_presab_wag4.csv` : Community dataframe of species distributions in long format
2. `RESULTS`: Folder with all results
**a. correlations**
\* /wag4: Folder with results and maps projected under the Wagner IV projection.
/spatialreg: Folder with spatial correlation tests for various diversity metrics
\+ /endemism: Contains correlation test results for different test sets focused on weighted endemism (corr_test_set1.csv to corr_test_set28.csv).
\+ /PD: Contains correlation test results for different test sets focused on phylogenetic diversity (corr_test_set1.csv to corr_test_set28.csv).
\+ /PE: Contains correlation test results for different test sets focused on phylogenetic endemism (corr_test_set1.csv to corr_test_set28.csv).
\+ /richn...