Evaluating the suitability of NPP simulation for subtropical forest ecosystems by calibrating the Biome-BGC model: An empirical study at interannual and inter-monthly scales

Subtropical forest ecosystems play a crucial part in the global carbon cycle, and accurately simulating the spatio-temporal distribution of Net Primary Productivity (NPP) is essential for a comprehensive grasp of the carbon balance dynamics in this region. In this study, based on remote sensing observations of NPP, we calibrated specific vegetation ecophysiological parameters required for simulating NPP in four forest types using the Biome-BGC model. Subsequently, the calibrated model was employed to simulate the spatio-temporal distribution of annual and monthly NPP within forest ecosystem of the Poyang Lake Basin (PYLB) in the subtropical region from 1960 to 2022. The results demonstrate that the calibrated model efficiently overcomes the constraints observed in both the original model and the model based on measured physiological parameters, which exhibited significant overestimation or underestimation of forest NPP in certain months. Over the last 63 years, the average forest NPP shows a spatial gradient at the interannual scale, peaking in the southern area and declining to the north. However, when examined at the inter-monthly scale, the monthly average NPP from April to October exhibited a spatial pattern similar between the northern and southern regions. The multi-year average NPPs of Evergreen Needleleaf Forests (ENF), Evergreen Broadleaf Forests (EBF), Deciduous Broadleaf Forests (DBF), and Shrubs were 656.83, 660.83, 660.00, and 403.07 g C m−2 year−1, respectively. For ENF, EBF, and Shrub, their trends of the average NPPs were essentially the same as those of the months. However, the trend of NPP fluctuation with month was significantly larger for DBF, with the mean NPP being highest from May to August (80–102 g C m−2 month−1) and lowest from December to March (≈ 0 g C m−2 month−1). Distinct spatial patterns of forest NPP have been identified at both the inter-monthly and interannual scales in subtropical forest ecosystems of China. Additionally, our methodology can provide a valuable reference for assessing the spatio-temporal dynamics of carbon equilibrium in forest ecosystems across other regions around the world.