A global analysis of tree pests and emerging pest threats.
Tree pests affect millions of hectares of natural and managed land annually, but we often lack a strong understanding of the factors limiting pest distributions and the drivers that facilitate the expansion of pests outside their hosts' native ranges. Here, we use hierarchical Bayesian regression models to identify the key determinants of pest distributions from a global dataset of > 310,000 pest presences/absences across 206 countries and an additional > 120,000 pest occurrences outside the native host ranges to validate the model. Our results show there are strong, generalizable controls on pest ranges, including effects of host richness and phylogeny, geography, and climate. Remarkably, our model fit to pest distributions in native host ranges was able to predict pest presences outside the host native range with ~79% accuracy. Our work has important implications for predicting regions that may be vulnerable to future pest invasions and understanding the accumulation of pests outside the native ranges of their hosts.