Quantifying the impact of farmers' social networks on the effectiveness of climate change mitigation policies in agriculture.

To reduce agricultural greenhouse gas (GHG) emissions, farmers need to change current farming practices. However, farmers' climate change mitigation behaviour and particularly the role of social and individual characteristics remains poorly understood. Using an agent‐based modelling approach, we investigate how knowledge exchange within farmers' social networks affects the adoption of mitigation measures and the effectiveness of a payment per ton of GHG emissions abated. Our simulations are based on census, survey and interview data for 49 Swiss dairy and cattle farms to simulate the effect of social networks on overall GHG reduction and marginal abatement costs. We find that considering social networks increases overall reduction of GHG emissions by 45% at a given payment of 120 Swiss Francs (CHF) per ton of reduced GHG emissions. The per ton payment would have to increase by 380 CHF (i.e., 500 CHF/tCO2eq) to reach the same overall GHG reduction level without any social network effects. Moreover, marginal abatement costs for emissions are lower when farmers exchange relevant knowledge through social networks. The effectiveness of policy incentives aiming at agricultural climate change mitigation can hence be improved by simultaneously supporting knowledge exchange and opportunities of social learning in farming communities. [ABSTRACT FROM AUTHOR]