Abstract ID: 3.13673 | Accepted as Poster | Poster | TBA | TBA

Cold regions store the largest terrestrial soil carbon pools, yet their stability is increasingly uncertain due to rising temperatures. In Alpine mountain regions, we still lack a status-quo quantification of total soil organic carbon (SOC) stocks above the treeline. To address this gap, we compiled SOC stock measurements from over 350 sites across the Swiss Alps, spanning elevations from 1,750 to 3,150 m asl characteristic of the heterogenous Alpine landscape. While topsoil carbon contents and fine earth densities down to 20cm depth were measured using replicated soil cores, deeper SOC stocks (>20 cm) were estimated by applying pedotransfer functions derived from corresponding soil properties measured at 16 representative soil pits reaching bedrock. We developed a predictive spatial model using random forest regression, integrating spatial covariates such as topography, NDVI, climate, and soil pH information. The model demonstrated good predictive power, enabling the first SOC stock map for unmanaged land from the treeline to permafrost regions in Switzerland. This study highlights the role of alpine grasslands as substantial carbon pools in national inventories and represents a crucial step in monitoring changes in the Alpine soil carbon budget.