<!-- Start of picture text --> 3.5 The Global Distribution of Vascular Plants<br>Borgelt et al. (2022 — henceforth Borgelt) have recently developed spatial density maps for vascular plants<br>they identify “native regions” from a web-scraping exercise using the Plants of the World Online (POWO)<br>database, with regional identification standardized from the World Geographical Scheme for Recording<br>Plant Distributions (WGSRPD). Typically, the resulting “native regions” are the boundaries of small<br>countries or provinces (GADM level-1 administrative units) in large countries.<br>Borgelt estimates the models using GBIF occurrence data with restrictive prior conditions. The data are<br>confined to the period 2000-2020 to preserve compatibility with the environmental variables used for<br>Maxent estimation. For each species, georeferenced occurrence reports are pruned to exclude all<br>observations outside of pre-identified “native regions”. Maxent-estimated species distributions are also<br>confined to native regions. This approach has the advantage of guaranteeing the exclusion of spurious<br>observations from entities like botanical gardens and private collections in other regions. However, it also<br>incurs the cost of excluding potentially-large numbers of occurrence observations that lie outside pre-<br>identified native regions that are arbitrarily defined by national or provincial boundaries.<br>Our exercise draws on a longer time period (1970-2023) because we are not constrained by the need for<br>compatibility with environmental modeling variables. In addition, we impose no prior geographic<br>restrictions on the data. As we explained previously, our methodologies estimate occurrence map<br>boundaries after removing spurious single outliers and small isolated occurrence clusters.<br>We have identified 32,339 vascular plant species that are in both databases. As before, we rasterize our<br>occurrence maps and compute cell counts at 5 km resolution. Borgelt provides species maps in a raster<br>stack with much coarser resolution (50 km). We extract raster layers for the 32,339 common species and<br>add across layers to obtain relative incidence scores for the 50 km grid cells. Then we use mean smoothing<br>to approximate the effect of higher resolution.<br>Figure 5 provides the comparative results, displayed as ranks in 10 groups. Inspection of the two maps<br>reveals essentially the same density pattern, with the exception of somewhat more extensive high-ranking<br>In this section, we have compared our estimated GBIF occurrence maps with species-matched sets of<br>expert maps from recent publications for mammals, ants and vascular plants. In all three cases, the<br>comparative global patterns of species density are quite similar. Where the patterns diverge, the<br>maps and expert “native range” maps are attributable to “undershooting”, where the expert map<br>boundaries exclude many GBIF occurrences, or “overshooting”, where GBIF occurrences are persistently<br>absent in parts of the native range maps. For ants, where the research also employs aphahull estimation,<br>the differences are attributable to differences in the source databases and the relative conservatism of our<br>approach to map estimation. For plants, where the research employs GBIF occurrences and the global<br>pattern similarity is most striking, the few discrepancies are attributable to temporal and spatial<br>restrictions imposed by the expert research team.<br><!-- End of picture text -->