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In Africa, the mixed crop–livestock farming systems and the people who live in them will be particularly challenged in the coming decades by climate change, through increasing temperatures, changes in the start and length of growing seasons, and increasing climate variability. In places they will also face considerable and increasing labour and land constraints. There is enormous diversity in the mixed systems, in relation to their current characteristics and the climate challenges posed (Figs 1 and 3). To target bundles of adaptation options that are locally appropriate but amenable to large-scale investment and scaling up, evaluation of options at the farm scale are needed. To do this effectively, several things need to be in place so that adaptation alternatives can be appropriately assessed in these integrated systems.

Appropriate biophysical models. We need appropriate biophysical models that can represent the interactions between crops and livestock adequately, so that evaluations of the mixed systems are more robust. In contrast to earlier thinking on the topic (including our own), we are not confident that increasing the complexity of already complex crop and livestock models through strong integration is an appropriate approach; rather, we should be looking for weak integration between robust and well-tested models. In particular, the spatial and temporal dimensions needed provide considerable challenges. Most modelling work has been done on the primary cereals (particularly maize, rice and wheat) and legumes (groundnut, soybean), but more often than not, adaptation will be about adding lesser-known or alternative crops into existing cropping patterns. Models for such crops need to be developed together with models for other important smallholder crops, including perennial crops⁵⁵.

Appropriate whole-farm models. We need appropriate whole-farm models, because we need to track flows of cash and the interactions of financial and physical resources in the farm household system. There is widespread appreciation of the need for approaches that combine simulation modelling with deliberative processes involving decision-makers and other stakeholders⁵⁶. Trade-offs between the benefits and costs to a range of stakeholders are inevitable, and these need to be quantified. There is also growing appreciation of the need to combine bottom-up, qualitative social research with farmers and communities, and top-down, quantitative biophysical modelling, to gain more in-depth understanding of farming systems and their potential to adapt to a changing climate⁵⁷. Whole-farm modelling at the level of the farming system in African conditions is constrained by a serious lack of systems data, even on such basic variables such as cropland area, livestock numbers, breeds, crop varieties and management information such as planting dates and fertilizer use. Crowd sourcing, mobile telephony and 'citizen science'^{58, 59} offer intriguing prospects for data collection and monitoring at massive scale to help rectify this situation. Other essential extensions to the household modelling work include lifecycle analyses and value-chain modelling. As the agenda necessarily develops from a focus on agriculture and food security to the whole food system, the roles of different actors in the value chain, all with their climate change impacts, adaptation and mitigation needs, will need to be considered explicitly in order to develop robust adaptation and mitigation plans for food systems. The explicit inclusion of human nutrition with its appropriate metrics, as a key link between human welfare, farm diversity and land use and environmental performance, is also essential. These areas of work are still in their infancy.

Appropriate scenarios of the future. The future of smallholder mixed systems in Africa is highly uncertain. One view is that smallholder systems in general must intensify production in a sustainable way⁶⁰ and remain a kingpin of food production; another view is that they will become largely redundant as smallholdings are aggregated into much more intensive and specialized systems, following the evolutionary process illustrated in Fig. 2. The Boserupian model, arguing that population changes will largely drive changes in agricultural systems, has been heavily criticized on various grounds⁶¹. Many different processes are possible, and as noted above, probably multiple processes will occur simultaneously in different parts of the continent, driven by regional and local factors and contexts. Participatory regional, national or local socio-economic scenarios, which may or may not be linked with appropriate future climate scenarios, are a highly effective tool for exploring future uncertainties and decision spaces with stakeholders, as well as providing a platform for using the outputs from such work^{12, 62}. The formulation of national visions of how these systems might evolve, supported by relevant policy documents on adaptation actions, may be heavily influenced by the outcomes from such processes, and the adaptation agenda could be advanced significantly thereby.

Appropriate measures of adaptation success. What will adaptation success actually look like in the mixed farming systems of sub-Saharan Africa? Vulnerability and adaptive capacity cannot be directly observed, hence the dependence on sets of indicators⁶³. Many have been proposed, although a recent systematic review⁶⁴ concludes that it is not possible to identify empirically supported patterns of climate vulnerability determinants in the literature. Instead, an approach is proposed that tracks vulnerability and adaptive capacity using a set of indicators that combine objective asset or poverty measures at the household level with more subjective governance and policy factors at the community and national levels⁶⁴. There is ongoing activity in defining appropriate metrics for climate-smart agriculture^{65, 66}. Indicators are very much needed, not least to be able to identify when farming system adaptation is not enough and much more transformational approaches are needed. Such information is critical when looking into the future to try to guide adaptation planning and investment.

The full adaptation potential of African smallholder mixed farming systems is not yet known, although from a technical standpoint, there is likely to be considerable scope for modifying these systems to improve the livelihoods of smallholder farmers, even in the face of climate change. Given the enormous population-fuelled pressures on land and natural resources that will be building up in the coming decades, this is a critical knowledge gap that deserves serious attention. There are considerable uncertainties concerning appropriate economic development pathways and consumption patterns for most of the agriculturally dependent countries of sub-Saharan Africa; but identifying those that balance national policy objectives with enhanced livelihoods and food security could be enormously beneficial for the hundreds of millions of people living in urban and rural settings. We need to improve our understanding of how African farming systems may change and adapt in response to global change, and how policy and governance frameworks can most effectively provide the enabling environment required.