Human activities affect the future suitability of alien urban landscape species in China under climate change.

Ecologists have paid considerable attention to the adaptation and distribution of urban landscape species in China amid rapid urbanization and climate change, given the essential role of urban species in human activities, urban planning, and sustainable development. However, existing studies primarily concentrate on the effects of climate change on the distribution of native species, creating a research gap regarding alien species. We compiled 5261 distribution data points for 538 alien woody landscape species (WLS) (non-native to China) from 179 cities with populations over one million in China and utilized the MaxEnt model to assess the future distribution and migration patterns of 27 most commonly introduced evergreen broad-leaved, evergreen coniferous, and deciduous broad-leaved species under present, 2041-2060, and 2081-2100 periods according to the Representative Concentration Pathway (RCP) 4.5 and RCP 8.5 climate scenarios. The results indicated that deciduous broad-leaved species were widely distributed in Southwest China, East China, Central China and North China regions, had a broad climate niche and greater adaptability to climate change, while the suitable area of evergreen species were expected to be lower than that of the present stage after 2100. The preserved suitable areas of evergreen species were mainly concentrated in the East China and Central China regions, and the lost suitable areas of evergreen coniferous species were in South China and southern East China regions. We also noted that human activities were the most important factor influencing the species distribution, not only in terms of the differences in suitable areas, but also the spatial diversity patterns. Our study revealed the future distribution patterns of three vegetation types and highlighted the importance of preventing the transformation of alien WLS into invasive species, which can provide valuable guidance for urban planning and development.