Factors that are strongly causal to NPP across diverse climate regions in China

While Net Primary Productivity (NPP) driving mechanisms have been widely studied through correlation analysis, precisely quantifying causal relationships remains challenging. This study investigates causal effects of climatic and topographic factors on NPP across five Chinese climatic regions using Geographic Convergent Cross Mapping (GCCM). Our results reveal several strong-causality-yet-weak-correlation patterns: terrain relief with NPP in SE and NE China; DEM in SW and SE China; and sunshine radiation in SW and SE China. Crucially, we identify optimal operative intervals for these causal factors: DEM (511-607 m), terrain relief (22-128 m), temperature (16.2-18.1 °C), and sunshine radiation (1.24-1.36×10ˆ7 J/m 2 ). By integrating GCCM with Geodetector analysis, we further uncover the underlying mechanisms, demonstrating topography's role as an integrator in ecosystem processes. These insights provide valuable scientific support for optimizing NPP modeling parameters and formulating regional ecological restoration strategies. • Proposes Geographic Convergent Cross Mapping (GCCM) to identify topographic factors as key causal drivers of NPP beyond correlation analysis. • Determines optimal operative intervals: elevation (511–607 m), relief (22–128 m), solar radiation (1.24–1.36×10 7 J/m 2 ), temperature (16.2–18.1 °C). • Reveals region-specific mechanisms: DEM integrates topography, energy, and hydrology in SW China; relief couples with ET in SE and precipitation–vegetation in NE. • Uncovers coexisting "strong causality–weak correlation" (e.g., terrain) and "strong causality–strong correlation" (e.g., NDVI) patterns. • Offers a scientific basis for optimizing NPP modeling and designing spatially tailored ecological restoration strategies.