Abstract: This study focuses on Pu'er City, a representative mountainous region in Southwest China. Using forest management inventory data, forest AGB was estimated through biomass conversion factors and classified into coniferous, broadleaf, and mixed forest types. By integrating topographic and climatic variables, SHAP was applied to identify key drivers, and a structural equation model was developed to further clarify the environmental pathways shaping AGB variations among forest types. The results indicated that forest AGB in Pu'er City follows a distinct spatial pattern of higher in the south and lower in the north, with elevation as the core topographic driver. Key climatic factors included the mean temperature of the coldest month (total effect 0.483), precipitation of the driest quarter (total effect 0.390), and mean temperature ofthe driest quarter (total effect 0. 252). Climatic factors primarily exert direct effects, while topographic factors mainly act through indirect pathways. The response mechanisms differ among forest types: coniferous forests are sensitive to temperature-related factors; broadleaf forests are sensitive to precipitation-related factors; and mixed forests exhibit the most complex response, combining the sensitivities of both coniferous and broadleaf forests to climatic factors. This study reveals the multi-factor driving pathways of forest AGB spatial variation in Pu'er City and the differentiation patterns among forest types, providing scientific support for regional forest carbon stock assessment and differentiated management.