Spatiotemporal Dynamics and Driving Mechanisms of Vegetation Net Primary Productivity in Hainan Tropical Rainforest, China

Vegetation net primary productivity (NPP) is a key indicator of ecosystem functioning in tropical rainforests and has important implications for carbon cycling and ecosystem stability. Examining the spatial and temporal variation in vegetation NPP and the factors associated with it can help inform ecosystem management and responses to climate change. In this study, Hainan Tropical Rainforest National Park (HTR), China, was selected as a representative tropical rainforest ecosystem. MODIS NPP data, Landsat imagery, meteorological variables, topographic factors, soil data, and socioeconomic indicators were integrated to analyze the spatiotemporal evolution of vegetation NPP from 2000 to 2023. The Theil–Sen Median trend analysis and Mann–Kendall test were applied to detect temporal trends, while the Optimal Parameter Geographical Detector (OPGD) model was used to identify dominant driving factors and their nonlinear interactions. The results showed that vegetation NPP in HTR exhibited an overall increasing trend during the study period, although short-term fluctuations occurred. Spatially, NPP was higher in the west and south and lower in the east and north. Elevation, soil type, and land use type were the main variables associated with this pattern. Moreover, interactions between natural and human-related factors accounted for more of the spatial variation in NPP than individual factors considered separately. These findings improve the understanding of vegetation productivity dynamics in tropical rainforest ecosystems and provide scientific insights for carbon sequestration enhancement, ecological conservation, and sustainable ecosystem management in tropical rainforests under global climate change.