Objective  This study aims to reveal the spatio−temporal variation patterns of the net primary productivity (NPP) of vegetation in the Huang−Huai−Hai Plain from 2001 to 2022, quantify the relative contributions of climate change and human activities to the changes in NPP, and deeply analyze its internal driving mechanisms, with the expectation of providing a scientific basis for regional ecological management, vegetation restoration, and the improvement of carbon sink capacity.

Methods  Based on multi−source data such as MODIS NPP data, meteorological observation data and land use, methods such as trend analysis, partial correlation analysis and multiple regression residual analysis were comprehensively applied to analyze the spatio−temporal dynamics of NPP and its response to climatic factors; Further, the enhanced regression tree (BRT) model was adopted to evaluate the relative importance and partial dependence of multiple factors such as climate change (temperature, precipitation) and human activities (land use degree, population density, etc.) on the changes in NPP.

Results  From 2001 to 2022, the NPP of vegetation in the Huang−Huai−Hai Plain generally showed a significant growth trend (with a growth rate of 5.19 gC·m⁻²·a⁻¹), and spatially presented a pattern of being higher in the south and lower in the north. NPP is significantly positively correlated with precipitation, and precipitation is the main climatic factor affecting NPP. The changes in vegetation NPP are mainly driven by both climate change and human activities, with their contribution rates being 41.81% and 39.24% respectively. The results of the BRT model show that precipitation, land use degree and population density are the key factors influencing the spatial differentiation of NPP in 2020.

Conclusions  The changes in vegetation NPP in the Huang−Huai−Hai Plain are the result of the combined effect of natural factors and human intervention. The rational regulation of precipitation resources and the optimization of land use structure are the key paths to maintain and enhance the productivity of the regional ecosystem. This study provides quantitative support for understanding the driving mechanism of vegetation dynamics and formulating regional ecological security strategies.