High-resolution assessment and attribution of vegetation net primary productivity dynamics under changing socio-ecological conditions in the Zhengzhou Metropolitan Area, China

Vegetation is essential to terrestrial ecosystems and sensitive to climate change and human activities. Accurately quantifying the relative contributions of natural and anthropogenic behind vegetation dynamics，particularly in urbanized regions, remains a challenge in ecosystem response research. Focusing on the rapidly urbanizing Zhengzhou metropolitan area（ZMA）, this study estimated net primary productivity (NPP) and analyzed NPP spatiotemporal characteristics over the period 2000-2020 using the high-resolution NDVI data fused. Additionally, based on the framework of decomposition and attribution of multiple drivers，the relative contributions of climate change, human activities, and residual factors were quantified, and their dominant roles were identified. The results indicate that: (1) the fused high-resolution NDVI effectively enhances the temporal continuity and spatial distribution detail of vegetation dynamics, and improved the accuracy and reliability of NPP estimation; (2) NPP exhibited an overall slight increasing trend, with 2010 as a turning point—shifting from a significant decline (with the rate of -4.12 gC/(m²·a) during 2000-2010) to a rapid increase (with the rate of 8.21 gC/(m²·a)during 2010-2020) ; (3) spatially, degradation and restoration coexisted in urban centers, while ecological barriers experienced widespread restoration; (4) human activities consistently served as the dominant driver of vegetation dynamics, with the relative contribution rising from 46.99% to 53.57%. The impact shifted from being dominated by vegetation degradation (impacting 32.27% of areas) to restoration (51.12%). These findings underscore the growing impact of human activities. Accordingly, the scientific planning and effective management of human activities are crucial to achieving sustainable development in both urbanization and ecosystem within the ZMA.