Understanding soil organic carbon (SOC) dynamics is pivotal for global change research, as soils are one of the largest carbon pools and a small change in SOC content could therefore substantially intensify, or mitigate, current atmospheric CO2 increase. However, the release or increase in SOC is a slow process originating from a SOC pool with a large spatial variability. The processes determining the balance between accumulation and decomposition of SOC are complex, and regional scale inventories of the CO2 fluxes resulting from these processes are still surrounded with large uncertainty. This is largely because SOC consists of fractions with different ages resulting in different turnover times from years to millennia. Some of these fractions react to the present carbon balance, whereas others are inherited under different conditions. Different techniques exist to obtain regional estimates: extrapolation of point measurements of soil respiration and CO2 fluxes, sequential inventories of SOC stocks and simulation of SOC stocks using process based carbon dynamics models. However, as more studies become available, the discrepancies between the outcomes using different techniques also emerge. A crucial problem is therefore the linkage between the scale at which we understand processes and develop models (profile scale, short term) and regional scale observations at longer time scales: the spatial aggregation of current approaches induces averaging out of soil conditions and therefore does not allow to incorporate effects of past land management, lateral fluxes of water and/or carbon (the latter not leading to exchange of CO2 with the atmosphere) within the spatial units for which the models are run or the SOC values are averaged (usually polygons of 10-40 kmÂ²). Such landscape processes will need to be reflected in both regional SOC inventories and modelling.
In this session, we welcome regional studies on SOC dynamics using extrapolation of measured CO2 fluxes, SOC inventories or applications of SOC dynamics models. Intercomparison of the approaches in order to increase the confidence in the SOC dynamics models or to understand the driving forces behind observed SOC changes are particularly welcome.