Changes in leaf and root carbon allocation of global vegetation simulated by the optimally integrated ecosystem models

Carbon allocation in vegetation, particularly to leaves and roots responsible for resource assimilation, plays a crucial role in regulating the global carbon cycle and is highly sensitive to environmental changes. However, due to the limited observational data, the response of carbon allocation—particularly between resource-acquiring organs—to rapid global environmental changes remains unclear for global vegetation. State-of-the-art ecosystem models provide valuable insights into the spatiotemporal patterns of carbon allocation across global vegetation. In this study, we developed a weighted model average (WMA) by optimally integrating ecosystem models based on their performance in simulating the spatiotemporal changes in root and leaf carbon. The WMA well captured the satellite-observed leaf carbon trend and the spatial variations in root carbon along climate gradients (R² = 0.82). The WMA suggested global vegetation has increasingly allocated more carbon to roots than leaves (the trend of allometric scaling relations between leaf and root: 0.0014 ± 0.0013 g g^-1 yr^-1, p < 0.05) during 1982–2018. Elevated atmospheric CO₂ concentration was the dominant driver of changes in root/leaf carbon allocation globally (0.0010 ± 0.0005 g g^-1 yr^-1, p < 0.05), particularly in tropical regions. Climate change influenced carbon allocation in vegetation differently across regions, contributing to increased root carbon allocation in the Northern Hemisphere and enhanced leaf carbon allocation in tropical areas. Land use change led to more carbon being allocated to leaves than roots (-0.0003 ± 0.0006 g g^-1 yr^-1, p < 0.05). Overall, we tentatively quantified the changes in the carbon allocation to the leaf and root across global terrestrial vegetation under the dramatic environmental change based on WMA, which helps further understanding of the changes in the functioning of the terrestrial ecosystem and reasonable projection of changes in the future global carbon cycle.