A modelling framework to assess climate change and adaptation impact on heterogeneous crop-livestock farming communities

Climate change will impact the productivity of maize-based crop-livestock systems and the livelihoods of smallholders depending on them in semi-arid Zimbabwe. The large diversity in resource endowment and production objectives in rural communities differentially influences this impact and the adaptation potential of households. Also, crops and livestock are affected differently by climate change. Information on the effects on whole-farm productivity, income and food self-sufficiency is scarce and knowledge on the disaggregated benefits of climate-smart interventions for heterogeneous farmer populations is needed to better target decision support. Linking climate with dynamic crop and livestock models, and an economic model, an integrated multi-model framework was developed for analyzing the sensitivity of current systems to climate change and the potential for future systems to adapt. Information on assets and farm management from 160 households in Nkayi district allowed distinguishing categories of low, medium and high resource endowment. Results of 20 GCMs indicated that by mid-century Nkayi will become warmer with a reduction in early-season rainfall. The APSIM and DSSAT crop models predicted a 1-9% and >15% decline in actual and potential maize yield respectively. Using crop model results as input, the LivSim livestock model indicated small impacts on milk and animal production that varied strongly across farms. Integrating crop and livestock model outputs in the whole-farm economic model TOA-MD, we predicted that 60% of Nkayi farmers will be adversely impacted by climate change. Fertilizer and leguminous forages can mitigate climate change effects on crop and livestock production and reduce the proportion of vulnerable households to 20%. Benefits differ by farm type: with small benefits (200-500 US$) from adaptation options, small and medium farms remain poor, while better-off farms increase income more substantially (by 1200 US$). Our integrated modelling framework allows ex-ante impact assessment of incremental but also more transformative climate-smart interventions on heterogeneous farming communities vulnerable to climate change.