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Climate change poses a severe threat to global agricultural production and rural livelihoods, and since agriculture itself is a significant source of greenhouse gas (GHG) emissions, it can also play an important role in climate change mitigation. This article investigates how farmers’ social networks influence the adoption of on-farm mitigation strategies. More precisely, we use a network autocorrelation model to explore the relationship between a farmer’s own mitigation behavior and the mitigation behavior and knowledge of his fellow farmers. The analysis is based on a regional case study in Switzerland and uses data obtained from personal network interviews combined with survey and census data of 50 farmers. Half of them are members of a local collective action initiative for agricultural climate change mitigation, while the others do not participate in the initiative. We find that, on average, farmers with a larger network adopt more mitigation measures, and furthermore, mitigation adoption is linked with the level of knowledge within farmers’ networks. Indeed, the likelihood that non-members will adopt mitigation measures increases if they are closely associated with members of the collective action, suggesting a local spillover effect. It follows that strengthening knowledge exchange among farmers and supporting local farmers’ initiatives can potentially contribute to the diffusion of agricultural climate change mitigation practices.

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Reducing agricultural greenhouse gas (GHG) emissions is key to achieve overall climate policy goals. Effective and efficient policy instruments are needed to incentivize farmers' adoption of on‐farm climate change mitigation practices. We compare action‐ and results‐based policy designs for GHG reduction in agriculture and account for farmers' heterogeneous behavioral characteristics such as individual farming preferences, reluctance to change and social interactions. An agent‐based bio‐economic modeling approach is used to simulate total GHG reduction, overall governmental spending and farm‐level marginal abatement cost of Swiss dairy and beef cattle farms under both action‐ and results‐based policy designs. We find that total governmental spending associated with the compared policy designs depends on the cost and benefits of the considered measures as well as behavioral characteristics of farmers. More precisely, if farmers are reluctant to change, additional incentives are needed to increase adoption of a win‐win measure. In such a case, targeting the payment on the cost of that particular measure (action‐based design) instead of paying a uniform amount for abated emissions (results‐based design) can lower governmental spending for agricultural climate change mitigation. Farm‐level marginal cost of reducing GHG emissions are lower with results‐based payments independent of the cost of measures. Moreover, we find that farmers' individual preferences and reluctance to change substantially lower the adoption of mitigation measures and hence overall GHG reduction potential of farms.