Unraveling climate and human drivers of vegetation productivity dynamics in Yunnan Province, China: a structural equation modeling approach with empirical orthogonal function analysis

Vegetation net primary productivity (NPP) serves as a critical indicator of ecosystem health and carbon sequestration capacity in ecologically fragile mountainous regions. This study analyzes NPP spatiotemporal dynamics in Yunnan Province, China from 2005–2020 using MODIS NPP products (MOD17A3HGF V6.1) combined with trend analysis, empirical orthogonal functions (EOF), and structural equation models (SEMs). Results show: (1) NPP exhibited higher values in west and south regions, with forestland averaging 1091.07 gC/m²/year, followed by cultivated land (942.49 gC/m²/year) and grassland (936.17 gC/m²/year). (2) EOF analysis revealed the first two modes explained 55.13% of total variance, with NPP patterns shifting every five years. The northwest region showed highest sensitivity, with the first mode (39.64% variance) having temporal coefficients ranging from −217.40 to +431.36. (3) SEM analysis demonstrated climate change as the primary NPP driver (standardized path coefficient: 0.87), while topography (−0.51) and socioeconomic activities (−0.63) showed significant negative effects. Region-specific SEMs revealed distinct driving mechanisms across ecogeographical zones. These findings provide critical insights for sustainable ecosystem management and regional policy development in Yunnan Province's complex mountainous environment.