Modelling soil organic carbon stocks and greenhouse gases in European forests with multi-model ensembles

State-of-the-art soil models can be used to monitor and predict the evolution of soil organic carbon (SOC) stocks and greenhouse gas (GHG) fluxes at national, sub-national, and supernational levels. This can help predict the effect of disturbances on the soil and facilitate the development of sustainable management practices to prevent further soil degradation and GHG losses under climate change.

However, model simulations are still highly uncertain due to many factors. For instance, the lack of understanding of many soil processes, the way processes are represented in the models, and the parametrization, initialization, and forcing variables used to run them. One way to consider these uncertainties is to use multi-model ensembles, thus simulating the evolution of SOC stocks and GHG fluxes according to models with different structures and mechanistic assumptions.

In this work, we show a webtool that enables the simulation of SOC stocks and GHG gases in European forests under different climate and land-use change scenarios, using a multi-model ensemble. In the absence of on-site measurements, the webtool directly accesses online databases of pedo-climatic data that is required to run the models.

Models also need to be correctly parameterized and evaluated before their application. For that, we build a map of model parameters that can be used to force the models, and which is evaluated on the European LUCAS database. Uncertainties linked to the initialization method used are also discussed.