Spatiotemporal Distribution and Driving Factors of Net Primary Productivity of Vegetation in Guizhou Province: Based on an Improved LPJ Model

<p indent="0mm"> Guizhou Province is a crucial part of the ecological barrier in southwestern China. Exploring the spatiotemporal distribution and driving factors of Net Primary Productivity (NPP) in Guizhou is of great significance for ecological quality assessment and climate change response. Current models have limited applicability in complex terrains and could not account for topographic influences. In this study, a slope radiation model was constructed and coupled with the LPJ model (Lund-Potsdam-Jena) to improve the NPP estimation in complex terrain. Using the improved model, we analyzed the spatiotemporal distribution characteristics of NPP and its key driving factors in Guizhou Province from 2003 to 2023. Results show that incorporating topographic factors significantly improved the simulation accuracy of solar radiation. The coefficient of determination (<italic>R</italic>²) between the simulated NPP and reported literature values increased from 0.07 to 0.4. During 2003 to 2023, the mean annual NPP was 526.27 gC/(m²·a), showing an overall fluctuating upward trend. Spatially, the NPP exhibited higher values in the southwest and southeast, and lower values in the north and central regions. Geographical detector analysis show that the single-factor <italic>q</italic> values ranked as follows: solar radiation &gt; precipitation &gt; temperature &gt; elevation &gt; slope &gt; aspect, which suggests that solar radiation mostly influenced NPP spatial variation in Guizhou Province. All two-factor interactions exhibit enhancement effects, especially the solar radiation - precipitation interaction (<italic>q</italic> value 0.8). The research results can provide a scientific basis for ecological protection and climate change response in Guizhou Province.