Abstract: Focusing on four typical pine forests in Yunnan Province—Yunnan pine (Pinus yunnanensis), Simao pine (Pinus kesiya var. langbianensis), alpine pine (Pinus densata), and Chinese white pine (Pinus armandii)—a structural equation model (SEM) was constructed based on regional-scale data to systematically evaluate the direct and indirect impact pathways of four categories of factors—climate, soil, human activities, and topography—on carbon storage. The results show that human activities and climate are the primary driving factors. Specifically, distances to roads, villages, and county towns have a direct negative impact on carbon storage, with a path coefficient of −0.079. Climate factors, such as isothermality (bio_3) and precipitation of the wettest quarter (bio_16), exhibit a significant direct path coefficient of −0.232. Soil gravel content (t_gravel) is strongly negatively correlated with carbon storage (path coefficient: −0.704). Although topography has a relatively weak direct effect (−0.020), it indirectly regulates the spatial distribution of carbon storage by influencing climate and soil conditions. Spatially, Pinus yunnanensis exhibits the highest carbon storage, covering a total area of 55,476.60 km², with carbon density Class I and Class II regions accounting for 30,951.55 km² and 20,313.32 km², respectively, significantly exceeding other pine forest types. This study clarifies the synergistic effects of human disturbances and natural factors on the spatial pattern of carbon storage, providing theoretical support and data references for optimizing mountain forest carbon storage management, carbon sink zoning, and ecological protection policy formulation..