An Agent-Based Model of UK Farmers’ Decision-Making on Adoption of Agri-environment Schemes

Abstract

Agri-environment schemes (AES) are government-funded voluntary programs that incentivise farmers and land managers for environmental friendly farming practices. Understanding farmers’ decision-making process and its impact on AES adoption can aid policy makers in designing AES schemes that meet adoption goals and environmental targets. Farmers’ decision-making is complex and involves a range of social, behavioural, economic and ecological factors. In this paper, we present a spatially explicit agent-based model (ABM)—BESTMAP-ABM-UK that simulates farmers’ decision-making process, inclusive of farmers’ social, behavioural and economic factors, on adopting buffer strips, cover crops, grassland management and arable land conversion to grassland schemes in the UK. The model produces farmers’ AES adoption under varied AES scheme designs in term of the contract length, the offered payment level, the bureaucracy level and the required minimal area. We apply the Morris screening method to analyse the importance of the model parameters in a status quo scenario, in which current UK AES designs are used. The results show that the average accepted payments of farmers for buffer strips and grassland management and farmers’ intrinsic openness to buffer strips have the most significant impact on the farm adoption rate in the model.