Smallholder farmers' social networks and resource-conserving agriculture in Ghana: a multicase comparison using exponential random graph models

Abstract

We examined what type of information network structures lie within rural cooperatives and what these structures mean for promoting resource-conserving agriculture. To better understand whether and how environmental outcomes are linked to these microlevel social relations or network structures, we quantified individual farm- and community-level biomass accumulation and carbon stocks associated with the adoption of agroforestry, a set of farming techniques for climate change mitigation, adaptation, and resilience. We also collected social network data on individual farmers across five communities. This empirical evidence was derived from primary fieldwork conducted in the Ghanaian semideciduous cocoa (Theobroma cacao)-growing region. This data set was examined using standard network analysis, combined with exponential random graph models (ERGMs). The key findings suggest that farmers with more biomass accumulation from the adoption of agroforestry practices also tend to be popular advisers to their peers at the local level. Presumably, farmers seek peers who demonstrate clear signs of achieving successful land management goals. Using ERGMs, we also show that commonly observed individual-level results might not scale to the collective level. We discuss how our individual-scale findings could be leveraged to foster farmer-to-farmer social learning and knowledge exchange associated with resource-conserving agricultural practices. However, we also highlight that effective whole networks, such as cooperative collectives in these communities, remain elusive.

Keywords

• agroforestry
• climate change adaptation and mitigation
• ergms
• resource-conserving agriculture
• social network analysis
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