Abstract

CONTEXTEnhancing farm resilience has become a key policy objective of the EU's Common Agricultural Policy (CAP) to help farmers deal with numerous interrelated economic, environmental, social, and institutional shocks and stresses. A central theme in resilience thinking is the role of the unknown, implying that knowledge is incomplete and that change, uncertainty, and surprise are inevitable. Important strategies to enhance resilience are exploiting social capital and learning as these contribute to improved knowledge to prepare farmers for change. OBJECTIVEThis paper explores how social capital and learning relate to farm resilience along the dimensions of robustness, adaptation, and transformation. METHODSWe study the resilience of Dutch arable farmers from the Veenkoloniën and Oldambt using a combination of four methods. Qualitative data from semi-structured farmer interviews, focus groups, and expert interviews are combined with quantitative data from farmer surveys. The qualitative data are analysed using thematic coding. Non-parametric tests are used to analyse the quantitative data. Based on methodological triangulation, we mostly find convergence in our qualitative and quantitative datasets increasing the validity of our findings. RESULTS AND CONCLUSIONSThe results reveal that social capital and learning help farmers to adapt and are, in certain cases, also related to robustness and transformations. Robust farmers often learned by exploiting farmers' informal social networks, primarily relying on bonding social capital to acquire knowledge about agriculture or develop financial skills. Farmers undertaking adaptation are characterised by bonding and bridging social capital obtained by formal and informal networks, are early adopters of innovation, and have high self-efficacy. Combinations of bridging and linking social capital from formal networks could foster farmers to learn new ideas and critically reflect on current farm business models. These learning outcomes relate to farm transformations. SIGNIFICANCEThis study provides some early results on the dynamic relationship between farmers' social capital and learning and how these concepts are associated with resilience. Our findings are relevant for agricultural policy makers, as we provide recommendations on how social capital and learning have some potential to facilitate farm adaptation and transformation and improve information exchange in Agricultural Knowledge and Innovation Systems (AKIS).

Highlights

  • In an unpredictable world where farmers face numerous economic, environmental, institutional, and social shocks and stresses, enhancing resilience has become a key policy objective of the European Union (EU)'s Common Agri­ cultural Policy (European Commission, 2020)

  • The results reveal that social capital and learning help farmers to adapt and are, in certain cases, related to robustness and transformations

  • This study provides some early results on the dynamic relationship between farmers' social capital and learning and how these concepts are associated with resilience

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Summary

Introduction

In an unpredictable world where farmers face numerous economic, environmental, institutional, and social shocks and stresses, enhancing resilience has become a key policy objective of the EU's Common Agri­ cultural Policy (European Commission, 2020). Farmers need various antici­ pating, coping, and responding strategies to deal with shocks and stresses across economic, environmental, and social dimensions (Mathijs and Wauters, 2020). Developing these strategies requires learning and social capital, as these contribute to improving knowledge and prepar­ ing farmers for change, uncertainty, and surprise (Cundill et al, 2015). We define farm resilience as a farm's ability to provide functions (i.e. public and private goods) while facing shocks and stresses through the resilience capacities of robustness, adaptability, and transformability (Meuwissen et al, 2019). The required mix of the three complementary resilience capac­ ities is context-dependent

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