Impacts of invasive plants on carbon pools depend on both species' traits and local climate.

Invasive plants can alter ecosystem properties, leading to changes in the ecosystem services on which humans depend. However, generalizing about these effects is difficult because invasive plants represent a wide range of life forms, and invaded ecosystems differ in their plant communities and abiotic conditions. We hypothesize that differences in traits between the invader and native species can be used to predict impacts and so aid generalization. We further hypothesize that environmental conditions at invaded sites modify the effect of trait differences and so combine with traits to predict invasion impacts. To test these hypotheses, we used systematic review to compile data on changes in aboveground and soil carbon pools following non-native plant invasion from studies across the World. Maximum potential height (Hmax ) of each species was drawn from trait databases and other sources. We used meta-regression to assess which of invasive species' Hmax , differences in this height trait between native and invasive plants, and climatic water deficit, a measure of water stress, were good predictors of changes in carbon pools following invasion. We found that aboveground biomass in invaded ecosystems relative to uninvaded ones increased as the value of Hmax of invasive relative to native species increased, but that this effect was reduced in more water stressed ecosystems. Changes in soil carbon pools were also positively correlated with the relative Hmax of invasive species, but were not altered by water stress. This study is one of the first to show quantitatively that the impact of invasive species on an ecosystem may depend on differences in invasive and native species' traits, rather than solely the traits of invasive species. Our study is also the first to show that the influence of trait differences can be altered by climate. Further developing our understanding of the impacts of invasive species using this framework could help researchers to identify not only potentially dangerous invasive species, but also the ecosystems where impacts are likely to be greatest.