Impacts of land surface processes on soil organic carbon dynamics in a mountainous area

Abstract:

Soil is the largest reservoir of carbon in the terrestrial ecosystem. Disturbances on land surfaces -- such as land cover change, anthropogenic activities, and, extreme weather events -- can result in high CO₂ fluxes exchanging with the atmosphere and can affect carbon cycling. Many studies have focused on the biogeochemical transformations of SOC, but the physical transport of SOC, driven by soil erosion, overland flow, and soil deposition has not been sufficiently studied. Here we combine a mechanistic-based modeling approach with field sampling data to quantify SOC dynamics in hillslopes in a mountainous area within the East River Watershed in Colorado. We sampled soil properties at multiple depths, as well as soil thickness, over 60 sites throughout a north-facing and a south-facing hillslope. We used a machine learning approach (random forests) to predict the SOC content profiles at all other unsampled 2-D grid boxes with topographic matrix information, such as vegetation cover, elevation, slope, curvature, NDVI, etc.. This provides spatial maps of soil thickness, surface SOC content and SOC stock. To predict SOC dynamics under various weather conditions in the future, we developed a process-based model that couples surface runoff, soil erosion/deposition, SOC redistribution, and biogeochemical transformation. This allows us to explore the influences of surface topography, rainfall, vegetation cover, overland flow, and topographic aspects on SOC dynamics, and disentangle the physical and biogeochemical processes associated with SOC fluxes. This study not only helps us understand the evolution of SOC profiles in a watershed but can also serve as an instrument to develop practical means for protecting carbon loss under future climate shifts.