Geographic patterns of leaf area in global forests and their responses to climate change

Revealing the biogeography of functional traits and their drivers is central to ecology and biogeography. However, few studies have evaluated community-weighted traits in global forests, which dominate biomass and productivity in terrestrial ecosystems. In this study, we used a dataset of tree plots across global forests. Using machine-learning approaches, we assessed the geographic pattern of community-level leaf area of trees, its relationships with environmental drivers, and its projected changes under future climate change scenarios. We found that leaf area of trees exhibits a clear latitudinal gradient, increasing from high to low latitudes. Among the examined climatic variables, temperature showed strong associations with community leaf area in high-latitude boreal forests and low-latitude tropical forests, whereas precipitation was more important in mid-latitude forests and semi-arid forests. Assuming unchanged climate–trait relationships, our projections under the SSP3–7.0 scenario suggest that 82.3% of present-day forests would experience increases in community leaf area by 2070–2100, with the largest relative increases occurring in boreal forests (median: +166%). In contrast, 17.7% of forests, primarily tropical forests in Africa and South America, would show slight decreases. Our map provides important input for ecosystem models by illustrating the potential sensitivity of community leaf area to future climatic change and its possible implications for forest carbon cycling.