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Eucalyptus has become a major plantation crop in southern China, with a carbon sequestration capacity significantly higher than that of other species. However, its long-term carbon sequestration capacity and regional-scale potential remain highly uncertain due to commonly applied short-rotation management practices. The InTEC (Integrated Terrestrial Ecosystem Carbon) model is a process-based biogeochemical model that simulates carbon dynamics in terrestrial ecosystems by integrating physiological processes, environmental drivers, and management practices. In this study, the InTEC model was enhanced with an optimized eucalyptus module (InTECeuc) and a data assimilation module (InTECDA), and driven by multiple remote sensing products (Net Primary Productivity (NPP) and carbon density) to simulate the carbon budgets of eucalyptus plantations from 2003 to 2023. The results indicated notable improvements in the performance of the InTECeuc model when driven by different datasets: carbon density simulation showed improvements in R2 (0.07–0.56), reductions in MAE (5.99–28.51 Mg C ha−1), reductions in RMSE (8.1–31.85 Mg C ha−1), and improvements in rRMSE (12.37–51.82%), excluding NPPLin. The carbon density-driven InTECeuc model outperformed the NPP-driven model, with improvements in R2 (0.28), MAE (−8.15 Mg C ha−1), RMSE (−9.43 Mg C ha−1), and rRMSE (−15.34%). When the InTECDA model was employed, R2 values for carbon density improved by 0–0.03 (excluding ACDYan), with MAE reductions between 0.17 and 7.22 Mg C ha−1, RMSE reductions between 0.33 and 12.94 Mg C ha−1 and rRMSE improvements ranging from 0.51 to 20.22%. The carbon density-driven InTECDA model enabled the production of high-resolution and accurate carbon budget estimates for eucalyptus plantations from 2003 to 2023, with average NPP, Net Ecosystem Productivity (NEP), and Net Biome Productivity (NBP) values of 17.80, 10.09, and 9.32 Mg C ha−1 yr−1, respectively, offering scientific insights and technical support for the management of eucalyptus plantations in alignment with carbon neutrality targets.
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1 Fujian Provincial Key Laboratory for Subtropical Resources and Environment, Fujian Normal University, Fuzhou 350117, China; [email protected] (Z.L.); [email protected] (M.Z.), Institute of Geography, Fujian Normal University, Fuzhou 350007, China
2 Yuanling State Forestry Farm, Yunxiao County, Zhangzhou 363300, China