Modeling farmer decision-making and biophysical impacts of agrienvironmental schemes under different policy designs

Using model-based approaches for analyzing agricultural systems allows for a systematic assessment of policies under changing environmental, economic, or institutional conditions and the evaluation of the efficiency of different policy designs. When considering the behavior of individual farmers – the crucial actors at the landscape level – agent-based modeling is particularly appropriate. We use this approach in the context of farmers’ decision making on the adoption of agri-environmental schemes (AES). AES are voluntary programs offered as part of the European Union’s Common Agricultural Policy to provide incentives for environmentally friendly farming practices. However, farmers' interest in participation has remained lower than expected with a broad range of economic, ecological and social factors influencing and potentially hindering the adoption of AES. To systematically test how farmer decision-making is shaped by different policy designs and how this effects the adoption rate and the resulting spatial allocation of AES, we designed an agent-based model where decisions of individual farmers on four selected schemes are explicitly included. In the model, farmer behavior is empirically based on data from interviews conducted in five geographically and culturally diverse case studies across Europe. In addition, we rely on the results of a discrete choice experiment to quantify farmers' preferences for specific features of AES contracts. Taking the Mulde River basin in Germany as an example, we use the agent-based model to critically evaluate agricultural policies and analyze how they should be designed to achieve the desired impact. These results feed into a broad range of biophysical analyses to quantify the environmental impacts of AES adoption on biodiversity, water quality or carbon sequestration. In addition, the insights will be transferred from specific case studies to other EU regions to provide stakeholders with an effective tool for assessing the impact of future policies.