ProjectFrom 08/2021 to 07/2024
Principal Investigator: Nele Meyer
Staff: Bettina Haas
The mineralization of soil organic carbon (SOC) is a key component of the global carbon cycle, which regulates the balance between CO2 efflux and SOC sequestration. Patterns of SOC mineralization in space, depth, and time (4D) across a landscape, however, are still poorly understood. This is mainly because SOC mineralization rates are driven by a complexity of regulators, mechanisms, and their nonlinear interactions, that is beyond human perception. The aim of “Carbon4D” is the development of a data-driven 4D model of SOC mineralization on a landscape scale that accounts for highly complex and nonlinear relationships. To reach this aim, measurements of SOC mineralization rates and of their controlling factors (SOC stocks, soil moisture and temperature) are combined with multi-source remote sensing data and weather- and soil information in a machine learning approach. Based on the learned relationships, 4D predictions are made for a typical German low mountain landscape located in Central Hesse that serves as the test area for Carbon4D. On the basis of the 4D model, a detailed analysis of temporal, spatial, and vertical patterns of SOC mineralization rates and their controlling factors will be conducted. Hence, Carbon4D will provide a first approach of a near real-time monitoring framework of SOC mineralization rates and soil CO2 efflux in all 4 dimensions, which will provide new insights into patterns and controlling factors.