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 and often cited (typically for single-species
studies), and its species are frequently reported in global biodiversity
databases. 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 databases; 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; R2 =
0.87). Cumulative occurrence was strongly related to anthropocentric
effects (R2 = 0.62). We extract five lessons for invasive species
biogeography; foremost is 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.