Abstract: Focusing on 4 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 usig regional-scale data to systematically evaluate the direct and indirect impacts of climate, soil, human activities, and topographyon 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) exhibited a strong negative correlation (path coefficient: −0.704). Although topography has a relatively weak direct effect (−0.020), it indirectly influences the spatial distribution of carbon storage by modulating climate and soil conditions. Spatially, Pinus yunnanensis exhibits the highest carbon storage, covering a total area of 55476.60 km². Carbon density in Class I and Class II regions accounts for 30951.55, 20313.32 km², respectively, significantly exceeding those of other pine forest types. This study elucidates the synergistic effects of human activities and natural factors on the spatial pattern of carbon storage, providing theoretical support and data for optimizing mountain forest carbon storage management, carbon sink zoning, and the formulation of ecological protection policies.