Spatiotemporal Evolution and Influencing Factors of Forest Carbon Storage Based on BIOME-BGC Model and Geographical Detector in Eight Basins of Zhejiang Province in China

As the basic unit of nature, basins concentrate most of the vegetation cover of terrestrial ecosystems and play an important role in forest carbon fixation and regulation of local climates. However, there are obvious differences between different basins in terms of topography, climate, population, economy, and other factors, so it is important to conduct a comparative study on the spatiotemporal patterns of factors affecting forest carbon storage in different basins. The province of Zhejiang is rich in vegetation resources, and there are obvious differences in the natural and economic factors within the province; GDP is higher in the eastern and northern regions, and natural resources are more abundant in the western and southern regions. Therefore, we used the BIOME-BGC model and the Optimal Parameters-based Geographical Detector (OPGD) model to simulate and analyze the spatiotemporal evolution and driving mechanism of forest aboveground carbon (AGC) storage in eight basins of Zhejiang Province over the past 30 years (1984–2014). The results showed that (1) the overall simulation accuracy of AGC in different basins based on the BIOME-BGC model is high, with the overall simulation accuracy ranging from 0.67 to 0.77. (2) The forest AGC of the eight basins showed an increasing trend over the past 30 years, with a growth rate ranging from 0.07 Tg C/10 yr to 3.45 Tg C/10 yr. (3) Climatic conditions (temperature and precipitation) play a dominant role in the variation in AGC, with an explanatory power above 16% in the southern and northern basins, and the explanatory power of human activities on the AGC is secondary, with more than 9% in the central basins. (4) The interaction between natural factors and socio-economic factors (especially the population density factor) has a more obvious effect on the changes in AGC in each basin, and the explanatory power of the interaction is much larger than that of the single factor. (5) The results of the risk detection showed that human activities were negatively correlated with AGC in all basins.