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Seasonal forecasts coupled with crop models can potentially enhance decision-making in smallholder farming in Africa. The study sought to inform future research through identifying and critiquing crop and climate models, and techniques for integrating seasonal forecast information and crop models. Peer-reviewed articles related to crop modelling and seasonal forecasting were sourced from Google Scholar, Web of Science, AGRIS, and JSTOR. Nineteen articles were selected from a search outcome of 530. About 74% of the studies used mechanistic models, which are favored for climate risk management research as they account for crop management practices. European Centre for Medium-Range Weather Forecasts and European Centre for Medium-Range Weather Forecasts, Hamburg, are the predominant global climate models (GCMs) used across Africa. A range of approaches have been assessed to improve the effectiveness of the connection between seasonal forecast information and mechanistic crop models, which include GCMs, analogue, stochastic disaggregation, and statistical prediction through converting seasonal weather summaries into the daily weather. GCM outputs are produced in a format compatible with mechanistic crop models. Such outputs are critical for researchers to have information on the merits and demerits of tools and approaches on integrating seasonal forecast and crop models. There is however need to widen such research to other regions in Africa, crop, farming systems, and policy.

Climate-resilient crops and crop varieties have been recommended as a way for farmers to cope with or adapt to climate change, but despite the apparent benefits, rates of adoption by smallholder farmers are highly variable. Here we present a scoping review, using PRISMA-P (Preferred Reporting Items for Systematic review and Meta-Analysis Protocols), examining the conditions that have led to the adoption of climate-resilient crops over the past 30 years in lower- and middle-income countries. The descriptive analysis performed on 202 papers shows that small-scale producers adopted climate-resilient crops and varieties to cope with abiotic stresses such as drought, heat, flooding and salinity. The most prevalent trait in our dataset was drought tolerance, followed by water-use efficiency. Our analysis found that the most important determinants of adoption of climate-resilient crops were the availability and effectiveness of extension services and outreach, followed by education levels of heads of households, farmers’ access to inputs—especially seeds and fertilizers—and socio-economic status of farming families. About 53% of studies reported that social differences such as sex, age, marital status and ethnicity affected the adoption of varieties or crops as climate change-adaptation strategies. On the basis of the collected evidence, this study presents a series of pathways and interventions that could contribute to higher adoption rates of climate-resilient crops and reduce dis-adoption., Climate-resilient crops are essential for farmers to adapt to climate change. This scoping review identifies extension services and outreach as the most important factors for their adoption by small-scale producers in low- and middle-income countries.

Climate change is already posing a major threat to agriculture in sub-Saharan Africa (SSA); threats may intensify in the near future. This book has presented and assessed various approaches to assessing climate change risks and adaptation in Africa. These assessments are approached from multiple lenses that include climate model-linked biophysical modeling, multilogit analysis, and social approaches (e.g., focus group discussions and interviews). The focus of the book was predominantly dryland agricultural systems in which resource-constrained smallholder farmers operate. The results from different cases highlighted in the book give a strong indication that climate change is already having significant impacts on agricultural systems in SSA, especially smallholder crop and pastoral farming systems. However, it is apparent that there are considerable differences in the impacts from one place to the other and across farming systems, states, crops, etc. As such, although it is clear that adaptation is imperative, the direction and scope of such actions should not only be guided by regional and national imperatives, but also take into account local specificities. For smallholder crop farmers and livestock keepers, climate change is experienced within the context of their livelihood, which is tied to their past, present, and future. They have historically had to deal with the vagaries of climate and have developed several strategies to cope with and adapt to climate change and variability.

The unpredictable rains and droughts in the Kigezi Highlands of Uganda have been attributed to a changing climate. This chapter presents findings of a study that explored the adaptation and coping strategies under climate change and variability in the Kigezi Highlands by rural farmers for enhanced agricultural productivity and conservation of natural resources. The chapter particularly explores perceptions of rural farmers of climate change and variability, the types of crops they grow, and planting times. A total of 199 respondents were involved from the two subcounties Muko and Bufundi in Kabale District. Household questionnaires, focus group discussions, and interviews with key informants were conducted. Data on crops grown and their calendars were collected in two successive planting seasons of the years 2012 and 2013. The findings showed that rural farmers in the area have experienced significant impacts of climate change and variability, and they practice elaborate adaptation and coping strategies in response, including planting quickly maturing, improved crop varieties; practicing small-scale irrigation; and varying planting dates.

Climate change impact assessments on agriculture in Southern Africa are mostly carried out at large spatial scales, risking missing out on local impacts and adaptation potential that reflect the range of multiple and unique bio-physical and agronomic conditions under which farmers in the region operate. This study investigated how climate change may affect yields of various major food crops in specific locations in the region; maize and sorghum (Mohale’s Hoek – Lesotho and Big Bend – Swaziland), maize and groundnut (Lilongwe – Malawi). Using statistically downscaled climate projections from nine GCMs and the DSSAT crop model and simulating selected agronomic strategies practiced in each location, the study confirmed that impacts of climate change on crop yields in Southern Africa vary across locations and crops. Despite various uncertainties associated with such assessments, the results showed that crop yields were predominantly projected to decline in Big Bend (maize (−20%); sorghum (−16%)) and Lilongwe (maize (−5%); groundnut (−33%)). However, crop yields in Mohale’s Hoek, located in a high altitude region historically prone to cold related crop yield losses were on average projected to increase (maize (+8%) and sorghum (+51%)). The geographical variation of yield projections highlights the importance of location specific climate change impact assessments. The exploration of local agronomic management alternatives revealed prospects for identifying locally relevant adaptation strategies, which cannot easily be captured at larger scales.

This chapter details the common biophysical approach used to assess the impact of climate change on local crop production and critiques it to highlight usefulness and limitations in informing climate change response action. The chapter reviews various location-specific climate change impact studies in southern Africa and details their results in the context of the methodologies and tools applied. Ultimately lessons for improvements in future research are drawn. The chapter advocates future research efforts that will provide useful information for stakeholders in the agricultural sector to better respond to climate change as it affects vulnerable farmers, via improved local impact assessment and the incorporation of nonphysical local perspectives (i.e., going beyond biophysical impacts).

This chapter introduces the volume by setting the scene for the agriculture and climate change nexus in sub-Saharan Africa (SSA). It shows that agriculture is central to economies and livelihoods in SSA, yet considerably vulnerable to climate change and variability. The impacts of climate change are expected to be severe in SSA agricultural systems, calling for urgent adaptive and resilience-building actions. However, nonclimatic factors present considerable stress to the agricultural systems and these need to be fully considered in all actions that seek to address the challenges presented by climate change. These include the peculiar circumstances of rural men, women, and youth. An enabling policy environment is thus fundamental to overcoming barriers to adaptive actions, as it determines farmers’ access to agricultural inputs, including knowledge, and the degree of their participation in agriculture value chains.

Conservation agriculture (CA) is a climate change adaptation measure being promoted for small-scale farmers in Zambia. CA is touted as a sustainable adaptation practice that can improve productivity in marginal farming areas. This chapter presents a study that analyzed CA practices in Kalomo District, Zambia, i.e., practices applied and associated challenges in management and implementation, from the perspective of agricultural extension workers and organizations promoting CA in the district. Results showed that farmers in Kalomo District do not apply all CA principles, owing to a number of limitations that range from governmental interventions, cultural beliefs, and poor access to extension services. These factors are likely to affect productivity and expose farmers to climate change and will need to be addressed.

This chapter presents the findings of a study on gendered vulnerability of farmers to climate change in two regions of Eritrea—the subregion Berik, Central Highlands (Tigrinya ethnic group), and the subregion Sosona/Barentu, Lowlands Gash-Barka (Kunama ethnic group). Eritrea regularly suffers food shortages due to climate- and non-climate-related stressors on agriculture and limited adaptive capacity. The stressors include erratic rainfall, a shortage of male labor, gender inequality, and the lack of agricultural inputs. The chapter outlines the similarities and differences faced by farmers in both study regions. It highlights the complex nature of vulnerability of farming communities and households based on culture, ethnicity, gender, and sociopolitical circumstances. The chapter recommends that to properly support adaptation to climate change and variability, contextual specificities that underlie vulnerability need to be explicitly considered.

Climate change is expected to impact east Africa in the coming decades, with an overall warming trend, but much is still uncertain. Climate researchers working in this field aim to quantify, understand and reduce this uncertainty. On a five to 40 year timescale, climate projections are uncertain because the models used to predict the expected response from greenhouse gas emissions cannot capture all the relevant processes sufficiently well. In addition, many of the standard climate models do not fully consider all regional factors causing local climate change. There are therefore several ‘burning questions’ that scientists hope to address.

article i nfo Concern over future food security in southern Africa has led to various studies that assess the impact of climate change on crops in the region. The results vary according to applied methods and tools. This study reviewed and consolidated results from 19 recent studies which quantitatively project the impact of climate change on crops forthe21stcenturyin southern Africa. Resultswere assessedaccording tocropmodellingtechniques, which includ- ed process-based, statistical and economic (Ricardian) modelling. Studies were assessed for their reporting and rec- ommendations concerning adaptation and CO2 fertilisation. Results suggest that the aggregate impact of climate change on crops in southern Africa will be negative. Maize yields are projected to decline on average by 18%. The collective impact of climate change on all crop yields shows a median decline of �11% and �14% respectively under process-based and statistical methodologies. Median impacts show declining crop yields through the 21st century. No significant change in the near future, �18% for the mid century and �30% for late century. GCM driven Ricardian projections are highly variable. However, uniform climate scenarios project a median revenue decline. Notwithstanding the challenges of such a review; lack of data, bias towards reported methods and tools, uncertain- ty, scale etc., results indicate that climate change may impact southern African crops in important ways thereby making adaptation essential. Adaptation and CO2 fertilisation could potentially moderate the negative impacts of climate change. This implies a need for studies into future adaptation that consider CO2 fertilisation.

Crop models are useful tools for simulating impacts of climate and agricultural practices on crops. Models have to demonstrate the ability to simulate actual crop growth response in particular environments before application. Data limitations in southern Africa frequently hinder adequate assessment of crop models before application. The DSSAT model was used to test the usefulness of crop models under data-limited dryland conditions of southern Africa by validation using data from experimental trial reports and district-wide crop yield estimates. Two crops each were selected in three locations to represent varying cropping and physical conditions in southern Africa, i.e. maize and sorghum (Mohale’s Hoek, Lesotho and Big Bend, Swaziland) and maize and groundnut (Lilongwe, Malawi). DSSAT performs well in simulating crop yields obtained from experimental trials. District-wide simulated mean crop yields were acceptable (relative difference ranged from −12.2% to +2.36%). However, the model’s capture of seasonal yield variation for some locations and crops was uncertain due to climate extremes. It was concluded that satisfactory crop model testing before application is possible and that DSSAT crop models are useful even under data-limited conditions.Keywords: climate, crop modelling, dryland farming, DSSAT, southern Africa

Maize production in marginal tropical regions is at great risk due to rainfall variability and climate change. Climate change is set to increase the variability and uncertainty of inter-annual rainfall. Farmers who depend on rainfed maize production for their livelihoods would therefore benefit from improved climate based forecasting of production likelihood. In this study we developed a simple maize production decision support tool for Masvingo by using seasonal climate forecasts and a crop model to forecast maize yields likelihood prior to the season. We follow up on earlier studies carried out in Zimbabwe which show that the El Nino Southern Oscillation (ENSO) can be used to forecast rainfall and maize yields in Zimbabwe. An ENSO based seasonal climate analysis tool (RAINMAN) was used to produce probabilistic monthly climate forecasts for Masvingo corresponding to the phases of the Southern Oscillation Index (SOI). The climate forecasts were used to run a crop model (AquaCrop) for a variety of scenarios relevant to maize production (monthly rainfall, cultivar selection, planting date, and fertility level). The results of the simulations were similar to those observed by Phillips et al. (1997) and formed the basis for the development of an operational decision support tool. Simulated maize yields varied from 1.2 t/ha to 5.8 t/ha. The simulated yields were higher than expected average yields in a marginal region like Masvingo especially under small holder farming. The work suggested that optimal use of forecasts may lead to improved maize production in Masvingo. The study set a platform for the development of operational climate based maize production decision support tools in Zimbabwe.