Spatial heterogeneity of soil organic carbon in response to snow cover on the Tibetan Plateau

Soil organic carbon (SOC) is critical for terrestrial carbon cycling processes. Snow cover days (SCD) and snow depth (SD) on the Tibetan Plateau have changed significantly over the past decade and are associated with SOC patterns. However, current field studies lack the spatial resolution to capture the spatial heterogeneity of snowpack effects on soil organic carbon across high-altitude regions, and the relative importance of snow cover has also remained unquantified within the context of complex multifactor interactions. In this study, we aim to fill these knowledge gaps, through machine learning models and structural equation models, using remote sensing data of snow and soil datasets from 2015 to 2023. The results indicate that under the multiple environmental factors, snow cover (SD and SCD) is associated with 32.03 percent of the relative contribution to SOC. The SOC response to snow cover varies significantly across different ecosystem types. Specifically, snow cover influences SOC through both soil temperature (ST) and soil moisture (SM) in alpine meadows, whereas ST is the dominant pathway in alpine steppe and alpine desert. Overall, the spatial patterns averaged from 2015 to 2023 show SM associations at low SCD and ST associations at more persistent SCD. The findings clarify the significance of snow cover in high elevation regions over the past decade for SOC, enhancing our understanding of the terrestrial carbon cycle and carbon balance on the Tibetan Plateau.