Data for: Climate and forest attributes influence aboveground biomass of deciduous broadleaf forests in China
Chen, Guoping et al. (2022), Data for: Climate and forest attributes influence aboveground biomass of deciduous broadleaf forests in China, Dryad, Dataset, https://doi.org/10.5061/dryad.xwdbrv1h9
Forests provide a huge carbon pool, a substantial portion of which is stored in aboveground biomass (AGB). Deciduous broadleaf forests in China are an essential component of global deciduous broadleaf forests, yet the impacts of climate and forest attributes on their AGB are not well understood.
Using a comprehensive forest inventory database available from 772 plots distributed across the temperate and subtropical deciduous broadleaf forests in China (23.51°-42.53° N and 104.24°-128.27° E), we applied variance partitioning analysis, model selection analysis and structural equation models to explore how AGB was associated with climate and forest attributes (species diversity, community-level functional traits, and stand structures) in different climatic regions (semi-arid forests, semi-humid forests and humid forests).
Community-level functional traits and stand structures together explained a great portion of the variance in AGB. The effect of community-level functional traits was greater than that of stand structures in semi-arid forests and semi-humid forests, but smaller in humid forests. Further analyses showed that community-level maximum tree height, stem density and tree size inequality were the best explanatory variables. Although climate and species diversity had only minor effects, the direct positive effect of mean annual precipitation (MAP) was still important, especially in semi-arid forests.
Synthesis. Community-level functional traits but not species diversity were key drivers of AGB, indicating that tree species diversity loss may not impair AGB substantially in deciduous broadleaf forests in China. Moreover, stand structures had also strong effects on AGB in both semi-arid forests and humid forests, highlighting the importance of structural complexity. In addition, MAP had a direct positive effect on AGB in semi-arid forests and semi-humid forests, and a future predicted increase in drought might potentially reduce carbon storage in these forests.
National Natural Science Foundation of China, Award: 31988102
National Key Research and Development Program of China, Award: 2017YFC0503906
Key Research Program of Frontier Science, Chinese Academy of Sciences, Award: QYZDY-SSW-SMC011