The association between climate-smart agriculture practices adoption and farm income and wealth of small-scale urban crop farmers in eThekwini municipality, with implications for food and nutrition security.

Introduction: South Africa is particularly vulnerable to the effects of climate change due to its reliance on climate-sensitive livelihoods and limited adaptive capacity. Climate-smart agriculture (CSA) emerges as a key adaptation strategy to climate change, while enhancing agricultural productivity and improving income security with direct or indirect implications for food and nutrition security. Therefore, this study assessed the association between CSA practices used by small-scale urban crop (SSUC) farmers and farm income and wealth in the eThekwini (ETH) Municipality. Methods: The CSA adoption relied on a composite index computed from various practices and their intensities, including agroforestry (A), conservation agriculture (CA), crop diversification (CD), crop rotation (CR), cover crop (CC) use, drought-tolerant (DT) crops, mulching (M), organic manure (OM) use, wetland (W) use, and soil conservation (SC). The study collected data from 412 SSUC farmers selected through a multi-stage sampling procedure, with purposive selection and snowball sampling applied at the final stage. The study utilised descriptive analysis and conditional mixed processes (CMP) to analyse data. Results: Descriptive results underscore constraints imposed by demographic and institutional factors on SSUC farmers. The CMP model demonstrates a significant and positive association between CSA practices and the wealth index and farm income, jointly modelling adoption and welfare outcomes while accounting for potential selection bias. The CSA adoption showed a positive association with the wealth index and farm income. However, the estimated association between CSA practices adoption and income are relatively modest. They should be noted with caution, as substantial income gains and asset accumulation may become apparent in the long term, along with enhanced resilience to climate variability. Several socio-economic characteristics also showed significant associations, some with counterintuitive associations, for example, agricultural training, off-farm income, and hired labour, which warrant further exploration of the UA dynamics. Conclusion: The paper underscores the need to improve access to context-specific and outcome-oriented agricultural training and extension services, provided that existing training shows a weak association with income-enhancing CSA implementation, alongside strengthening economically productive farmer groups and continued research into CSA adoption to enhance farm income and wealth outcomes among small-scale urban farming households.