Predicting the landscape-scale distribution of alien plants and their threat to plant diversity

Invasive alien organisms pose a major threat to global biodiversity. The Ca pe Peninsula, South Africa, provides a case study of the threat of alien pl ants to native plant diversity. We sought to identify where alien plants wo uld invade the landscape and what their threat to plant diversity could be. This information is needed to develop a strategy for managing these invasi ons at the landscape scale. We used logistic regression models to predict t he potential distribution of six important invasive alien plants in relatio n to several environmental variables. The logistic regression models showed that alien plants could cover over 89% of the Cape Peninsula. Acacia cyclo ps and Pinus Pinaster were predicted to cover the greatest area. These pred ictions were overlaid on the current distribution of native plant diversity for the Cape Peninsula in order to quantify the threat of alien plants to native plant diversity. We defined the threat to native plant diversity as the number of native plant species (divided into all species, rare and thre atened species, and endemic species) whose entire range is covered by the p redicted distribution of alien plant species. We used a null model, which a ssumed a random distribution of invaded sites, to assess whether area invad ed is confounded with threat to native plant diversity. The null model show ed that most alien species threaten more plant species than might be sugges ted by the area they are predicted to invade. For instance, the logistic re gression model predicted that P. pinaster threatens 350 more native species , 29 more rare and threatened species, and 21 more endemic species than the null model would predict. Comparisons between the null and logistic regres sion models suggest that species richness and invasibility are positively c orrelated and that species richness is a poor indicator of invasive resista nce in the study site. Our results emphasize the importance of adopting a s patially explicit approach to quantifying threats to biodiversity, and they provide the information needed to prioritize threats from alien species an d the sites that need urgent management intervention.