Spatial heterogeneity and nonlinear drivers regulate vegetation productivity in Hubei Province China

Rising global carbon emissions have intensified the greenhouse effect and placed growing pressure on terrestrial ecosystems. Understanding the spatiotemporal variability of vegetation net primary productivity (NPP) is therefore essential for assessing environmental quality, quantifying carbon source-sink dynamics, and guiding ecological restoration. This study examined the spatial heterogeneity and nonlinear controls of NPP in Hubei Province, China, from 2001 to 2024 using the MOD17A3HGF dataset, GeoDetector, and geographically weighted regression (GWR). NPP showed a clear spatial gradient, with high values in the western mountains, intermediate values in the eastern hilly areas, and low values in the central plains. Annual mean NPP increased significantly during the study period and exhibited quasi-periodic fluctuations at approximately 3-, 6-, and 12-year intervals. Driver analysis showed that altitude was the dominant factor, while climate, human activity, and their interactions had strong spatially heterogeneous and nonlinear effects. Greening and browning areas differed markedly in their controlling mechanisms, and factor interactions amplified NPP variation beyond the effects of individual drivers. GWR further revealed strong spatial non-stationarity in driver-NPP relationships. These findings clarify the coupled human-natural mechanisms regulating vegetation productivity and provide a basis for targeted ecological restoration, land-use planning, and climate-adaptive management in subtropical regions.