Sustainable soil management has been proposed as an effective nature-based solution to enhance the delivery of nature’s contributions to people (NCP). Sustainable soil management principles are at the core of organic farming. The European Commission has set a target of at least 25% of the EU’s agricultural land to be under an organic farming system by 2030 under the European Green Deal. To reach this target, farmers and policy makers need to be able to make informed decisions on what sustainable soil management practices to implement.

We present a framework to understand how soil management practices and key external drivers, like climate change and soil degradation, influence the delivery of NCPs. We developed a set of conceptual evidence chains that link management practices, key drivers, soil biodiversity, ecosystem properties, functions, and goods. For each of these linkages we performed a literature search to determine the direction of effect and the strength of evidence. This set of evidence chains provided the basis for informed data-driven analyses of these linkages between individual components in the system to quantify the effects. This operationalization was constrained by the availability of observational data to train the models that make up the linkages, as well as spatial data to predict at a European scale.

Here, we illustrate this framework with a case study, where we predict the effect of converting farm management from a conventional to an organic system on the delivery of NCPs including climate regulation, water quantity and flow regulation, and food production, and their economic valuation, across Europe. These models also enable exploration of different climate and policy scenarios. Furthermore, as the models are based on the conceptual evidence chains that include strength of evidence, each model output is associated with a level of confidence, related to the scientific consensus and the availability and quality of data, that can be reported along with the results. This modelling framework and its model predictions can support farmers and policy makers in understanding trade-offs and synergies that are associated with soil management practices to make informed decisions.