Spatio-Temporal Simulation of the Productivity of Four Typical Subtropical Forests: A Case Study of the Ganjiang River Basin in China

As an important component of the global carbon cycle, the variation patterns and driving mechanisms of the productivity and carbon sink capacity of subtropical forest ecosystems urgently need in-depth research. In this study, taking the forest ecosystem in the Ganjiang River Basin as the research object, the Biome-BGC model was used to simulate the forest productivity at different time scales (annual, seasonal, and monthly) from 1970 to 2021, and its spatio-temporal distribution characteristics and responses to climate change were analyzed. The results showed that the interannual net primary productivity (NPP) of evergreen broad-leaved forests was 771.4 g C m−2 year−1, that of evergreen coniferous forests was 631.6 g C m−2 year−1, that of deciduous coniferous forests was 610.5 g C m−2 year−1, and that of shrub forests was 262.8 g C m−2 year−1. Evergreen broad-leaved forests have greater carbon sink potential under the background of climate change. The forest productivity in the Ganjiang River Basin generally showed an upward trend, but there were obvious differences in spatial distribution, characterized by being higher in the surrounding mountainous areas and lower in the central and northern plains. The methodological framework proposed in this study is beneficial for productivity evaluation and spatio-temporal analysis of carbon balance in subtropical forest ecosystems and provides a scientific reference for model simulation and the application of forest productivity at the regional scale.