Forests absorb and sequester carbon from the atmosphere, and increasing the carbon stock of forests might slow down global warming. To understand the characteristics of forests that accumulate more carbon, we explored how above-ground biomass (AGB) relates to climate, species composition, and functional traits of the composing tree species across Japanese natural forests.
Above-ground biomass of 51 Japanese natural forests was estimated using the tree census data by the Monitoring Site 1000 project. We established a statistical model that predicts AGB from climate, tree species composition (e.g., species richness, conifer dominance, and mycorrhizal types), and functional composition (community weighted mean (CWM) and diversity of functional traits, such as leaf mass per area (LMA) and wood density).
Cedar (Cryptomeria japonica) forests showed the largest AGB among Japanese natural forests, and the relationships of ABG with species composition and functional composition were often strongly affected by the presence of cedar trees. In the best model, temperature and CWM of LMA contributed positively to AGB, and cedar forests showed higher AGB at the given temperature and CWM of LMA (R² = 0.64). While the diversity of functional traits positively correlated with AGB, the effect was not selected in the best model. Our results suggest that producing forests dominated by species with high LMA or cedar forest might be effective in maximizing the AGB of the forest at a given temperature.