Biogeography of the world's worst invasive species has spatially-biased knowledge gaps but is predictable

The world's "100 worst invasive species" were listed in 2000. The list is taxonomically diverse, often cited (typically for single -species studies), and its species are frequently reported in global biodiversity data bases. We acted on the principle that these notorious species should be well -reported to help answer two questions about global biogeography of invasive species (i.e., not just their invaded ranges): (1) "how are data distributed globally?" and (2) "what predicts diversity?" We collected location data for each of the 100 species from multiple data bases; 95 had sufficient data for analyses. For question (1), we mapped global species richness and cumulative occurrences since 2000 in (0.5 degree)(2) grids. For question (2) we compared alternative regression models representing non-exclusive hypotheses for geography (i.e., spatial autocorrelation), sampling effort, climate, and anthropocentric effects. Reported locations of the invasive species were spatially -biased, leaving large gaps on multiple continents. Accordingly, species richness was best explained by both anthropocentric effects not often used in biogeographic models (Government Effectiveness, Voice & Accountability, human population size) and typical natural factors (climate, geography; R-2 = 0.87). Cumulative occurrence was strongly related to anthropocentric effects (R-2 = 0.62). We extract five lessons for invasive species biogeography; foremost are the importance of anthropocentric measures for understanding invasive species diversity patterns and large lacunae in their known global distributions. Despite those knowledge gaps, advanced models here predict well the biogeography of the world's worst invasive species for much of the world.