Invasion success of a global avian invader is explained by within-taxon niche structure and association with humans in the native range.
Aim: To mitigate the threat invasive species pose to ecosystem functioning, reliable risk assessment is paramount. Spatially explicit predictions of invasion risk obtained through bioclimatic envelope models calibrated with native species distribution data can play a critical role in invasive species management. Forecasts of invasion risk to novel environments, however, remain controversial. Here, we assess how species' association with human-modified habitats in the native range and within-taxon niche structure shape the distribution of invasive populations at biogeographical scales and influence the reliability of predictions of invasion risk. Location: Africa, Asia and Europe. Methods: We use ∼1200 native and invasive ring-necked parakeet (Psittacula krameri) occurrences and associated data on establishment success in combination with mtDNA-based phylogeographic structure to assess niche dynamics during biological invasion and to generate predictions of invasion risk. Niche dynamics were quantified in a gridded environmental space while bioclimatic models were created using the biomod2 ensemble modelling framework. Results: Ring-necked parakeets show considerable niche expansion into climates colder than their native range. Only when incorporating a measure of human modification of habitats within the native range do bioclimatic envelope models yield credible predictions of invasion risk for parakeets across Europe. Invasion risk derived from models that account for differing niche requirements of phylogeographic lineages and those that do not achieve similar statistical accuracy, but there are pronounced differences in areas predicted to be susceptible for invasion. Main conclusions: Information on within-taxon niche structure and especially association with humans in the native range can substantially improve predictive models of invasion risk. To provide policymakers with robust predictions of invasion risk, including these factors into bioclimatic envelope models is recommended.