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African mixed crop–livestock systems are vulnerable to climate change and need to adapt in order to improve productivity and sustain people’s livelihoods. These smallholder systems are characterized by high greenhouse gas emission rates, but could play a role in their mitigation. Although the impact of climate change is projected to be large, many uncertainties persist, in particular with respect to impacts on livestock and grazing components, whole-farm dynamics and heterogeneous farm populations. We summarize the current understanding on impacts and vulnerability and highlight key knowledge gaps for the separate system components and the mixed farming systems as a whole. Numerous adaptation and mitigation options exist for crop–livestock systems. We provide an overview by distinguishing risk management, diversification and sustainable intensification strategies, and by focusing on the contribution to the three pillars of climate-smart agriculture. Despite the potential solutions, smallholders face major constraints at various scales, including small farm sizes, the lack of response to the proposed measures and the multi-functionality of the livestock herd. Major institutional barriers include poor access to markets and relevant knowledge, land tenure insecurity and the common property status of most grazing resources. These limit the adoption potential and hence the potential impact on resilience and mitigation. In order to effectively inform decision-making, we therefore call for integrated, system-oriented impact assessments and a realistic consideration of the adoption constraints in smallholder systems. Building on agricultural system model development, integrated impact assessments and scenario analyses can inform the co-design and implementation of adaptation and mitigation strategies.F

AbstractSmallholder farmers in sub‐Saharan Africa (SSA) currently grow rainfed maize with limited inputs including fertilizer. Climate change may exacerbate current production constraints. Crop models can help quantify the potential impact of climate change on maize yields, but a comprehensive multimodel assessment of simulation accuracy and uncertainty in these low‐input systems is currently lacking. We evaluated the impact of varying [CO2], temperature and rainfall conditions on maize yield, for different nitrogen (N) inputs (0, 80, 160 kg N/ha) for five environments in SSA, including cool subhumid Ethiopia, cool semi‐arid Rwanda, hot subhumid Ghana and hot semi‐arid Mali and Benin using an ensemble of 25 maize models. Models were calibrated with measured grain yield, plant biomass, plant N, leaf area index, harvest index and in‐season soil water content from 2‐year experiments in each country to assess their ability to simulate observed yield. Simulated responses to climate change factors were explored and compared between models. Calibrated models reproduced measured grain yield variations well with average relative root mean square error of 26%, although uncertainty in model prediction was substantial (CV = 28%). Model ensembles gave greater accuracy than any model taken at random. Nitrogen fertilization controlled the response to variations in [CO2], temperature and rainfall. Without N fertilizer input, maize (a) benefited less from an increase in atmospheric [CO2]; (b) was less affected by higher temperature or decreasing rainfall; and (c) was more affected by increased rainfall because N leaching was more critical. The model intercomparison revealed that simulation of daily soil N supply and N leaching plays a crucial role in simulating climate change impacts for low‐input systems. Climate change and N input interactions have strong implications for the design of robust adaptation approaches across SSA, because the impact of climate change in low input systems will be modified if farmers intensify maize production with balanced nutrient management.