A global assessment of human influence on niche shifts and risk predictions of bird invasions.
Aim: Estimating the strength of niche conservatism is key for predictions of invasion risk. Most studies consider only the climatic niche, but other factors, such as human disturbance, also shape niches. Whether occupation of human habitats in the alien range depends on the native tolerances of species remains unexplored. We assessed niche conservatism in climatic and human spaces for bird species showing different responses to humans in native ranges and evaluated whether considering anthropogenic niche variables affects invasion predictions. Location: Global. Time period: From 500 CE to the present day. Major taxon studied: Birds. Methods: We assessed niche conservatism by comparing the native and alien distributions of 150 bird species. We differentiated "niche expansions" into environments new to the species and "niche unfilling", whereby a species fills its native niche only in part. Global predictions of alien bird distribution were generated using species distribution models (SDMs). Results: Climatic niche similarity was higher than random expectation in 56% of species, and human disturbance niche similarity in 43%. Only 34 and 15% of species had >10% of their alien distribution in climates or human conditions, respectively, different from those of native ranges. Climatic niche expansions mostly involved colonization of colder and less seasonal climates. Human niche expansions involved colonization of more disturbed environments by species not responding positively to human influence in native ranges. Climatic and human niche unfilling was more common than expansions and was lower for species introduced earlier and those responding positively to human influence. Models including human variables do equally well for all species. Main conclusions: Alien birds tend to invade areas with similar climatic and human conditions to their native range, but niche unfilling and expansions occur and relate to species native tolerances to human-modified habitats and first introduction year. Incorporation of human-related variables in SDM results in more accurate predictions for all species.