Net Primary Productivity Is Driven by Aridity Index and Phenological Phase in Forest Region of China

Net primary productivity (NPP) is a key indicator for assessing carbon fixation capacity. Understanding the mechanisms of carbon sequestration capacity of forest ecosystems is critical in the context of global climate change. Research on the influencing factors and driving mechanisms of NPP in forest areas of China is still insufficient, especially the lack of systematic analysis on the role of climate and phenology. Forest cover in China has been increasing in recent decades due to natural forest expansion and planted forests. It is significant to clarify the underlying drivers of the forest NPP in China. To address this issue, we collected annual NPP, biomass, phenology, temperature, and precipitation data in China from 2002 to 2021, then applied the general linear mixed effect model (GLMM) and Bayesian structural equation models to conduct a comprehensive analysis of the influencing factors of NPP. The results have shown that influencing factors all exert a significant positive influence on NPP through bivariate relationship analysis. The GLMM revealed that forest NPP was significantly positively affected by biomass, aridity index, temperature, and phenology. Among these, the aridity index (AI) (58.39%) and temperature (27.21%) were identified as having the highest contributions to NPP. The direct and indirect effects on NPP were evaluated using Bayesian structural equation models (SEMs), and the interactions between the factors and their comprehensive regulatory mechanisms on NPP were revealed. This study is crucial for understanding the impact of climate change on regulating forest carbon sequestration and providing strategies for effective forest management.