Social Capital, Crop Differences, and Farmers’ Climate Change Adaptation Behaviors: Evidence from Yellow River, China

Against the backdrop of global climate change, enhancing farmers&rsquo: adaptive capacity to reduce crop production risks has emerged as a critical concern for governments and researchers worldwide. Drawing on social capital theory, this study develops a four-dimensional measurement framework comprising social networks, social trust, social norms, and social participation, utilizing survey data from 1772 households in the Yellow River Basin. We employ factor analysis to construct comprehensive social capital scores and apply ordered Probit models to examine how social capital influences farmers&rsquo: climate adaptation behaviors, with particular attention to the moderating roles of agricultural extension interaction and digital literacy. Key findings include: (1) Adoption patterns: Climate adaptation behavior adoption remains low (60%), with technical adaptation measures showing particularly poor uptake (13%): (2) Direct effects: Social capital significantly promotes adaptation behaviors, with social trust (p &lt: 0.01), networks (p &lt: 0.01), and participation (p &lt: 0.05) demonstrating positive effects, while social norms show no significant impact: (3) Heterogeneous effects: Impact mechanisms differ by crop type, with grain producers relying more heavily on social networks (+, p &lt: 0.01) and cash crop producers depending more on social trust (+, p &lt: 0.01): (4) Moderating mechanisms: Agricultural extension interaction exhibits scale-dependent effects, negatively moderating the relationship for large-scale farmers (p &lt: 0.05) while showing no significant effects for smaller operations: digital literacy consistently demonstrates negative moderation, whereby higher literacy levels weaken social capital&rsquo:s promotional effects (p &lt: 0.01). Policy recommendations: Effective climate adaptation strategies should integrate strengthened rural social organization development, differentiated agricultural extension systems tailored to farm characteristics, and enhanced rural digital infrastructure investment.