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What Is the Evidence Base for Climate-Smart Agriculture in East and Southern Africa? A Systematic Map (lay summary)

This is a lay summary of the article published under the DOI: 10.1007/978-3-319-92798-5_12

Published onApr 30, 2023
What Is the Evidence Base for Climate-Smart Agriculture in East and Southern Africa? A Systematic Map (lay summary)

Look at the bigger picture for “climate smart” agriculture in eastern and southern Africa

Even though there are many research projects about “climate smart” agriculture in eastern and southern Africa, most of them focus on only a few of the many possible options. As a result, farmers and scientists could be missing important information on how to adapt to climate change.

To be considered “climate smart”, farming methods need to meet at least 2 of the following 3 goals. First, they should help farmers to sustainably increase the amount of crops grown and the amount of income their farms make. Second, they should help farmers adapt to changing weather conditions caused by climate change. And third, the methods should reduce the amount of greenhouse gases produced, to help slow the effects of climate change.

While many studies have been done on climate smart practices in different places, scientists don’t have enough information on which practices have been used across the continent, and which ones have been successful. Having this information could help scientists and decision-makers in government to design more effective climate smart initiatives.

In this study, researchers therefore wanted to find out which climate smart practices are being used across eastern and southern Africa. They also wanted to know where these practices are being used, and how they are helping farmers to meet climate smart goals.

The researchers reviewed previous studies involving climate smart practices in the region. To be included in their review, the studies had to meet strict criteria.  For example, they only chose “real world” studies, rather than computer models, and they focused on studies that compared climate smart practices to normal farming practices.

Using this method, they narrowed their search down from over 150 000 studies to 153, focusing on 5 countries: Malawi, Mozambique, Tanzania, Zambia and Zimbabwe. They then mapped out exactly where each study had taken place, which crops or other products the studies focused on, and which climate smart practices were used.

The first thing the researchers found was that many of the studies took place in the same areas, for example within specific parts of Tanzania or Zimbabwe. They said this probably means that only some climate smart options are being explored in the area. For example, not many studies had been done along the coast, which might be an area where different climate smart practices could be used than in farmlands in the middle of a country.  

They also noticed that most of the studies (78%) focused on maize, and there was very little information about other crops like millet or sorghum. These crops could, however, be important to help resist the effects of climate change. Furthermore, the researchers found that only a small percentage of studies (3.5%) focused on livestock.

The researchers also noticed that most of the studies focused on only a handful of climate smart practices. For example, nearly 30% of the studies were about fertiliser usage. Meanwhile, only a small amount of research was done on other practices, like improving crop varieties or genetics.

In terms of the 3 climate smart goals, the researchers said that more than 80% of the studies focused on increasing farm productivity, while only 17.5% were about helping farmers adapt to climate change, and only 0.5% were about how to reduce greenhouse gas emissions.

The findings give other scientists important insights into how climate smart practices are being implemented across the region. The researchers said that the information will also form a baseline for future work about climate smart practices, including what the best practices are and how best to design climate smart initiatives that meet multiple goals.

They added that looking at data across multiple studies could also help scientists understand the effects of specific climate smart practices on a larger scale, as well as whether certain practices lead to trade-offs between different climate smart goals.

The study was a collaboration between scientists working in the Netherlands, Kenya, Italy, the USA and the Democratic Republic of Congo.


More than 500 million USD will soon be invested in climate-smart agriculture (CSA) programmes in sub-Saharan Africa. Improving smallholder farm management is the core of most of these programmes. However, there has been no comprehensive information available to evaluate how changing agricultural practices increases food production, improves resilience of farming systems and livelihoods, and mitigates climate change—the goals of CSA. Here, we present a systematic map—an overview of the availability of scientific evidence—for CSA in five African countries: Tanzania, Malawi, Mozambique, Zimbabwe and Zambia. We conducted a systematic literature search of the effects of 102 technologies, including farm management practices (e.g., leguminous intercropped agroforestry, increased protein content of livestock diets, etc.), on 57 indicators consistent with CSA goals (e.g., yield, water use efficiency, carbon sequestration, etc.) as part of an effort called the “CSA Compendium”. Our search of peer-reviewed articles in Web of Science and Scopus produced 150,567 candidate papers across developing countries in the global tropics. We screened titles, abstracts and full texts against predetermined inclusion criteria, for example that the investigation took place in a tropical developing country and contains primary data on how both a CSA practice and non-CSA control affect a preselected indicator. More than 1500 papers met these criteria from Africa, of which, 153 contained data collected in one of the five countries. Mapping the studies shows geographic and topical clustering in a few locations, around relatively few measures of CSA and for a limited number of commodities, indicating potential for skewed results and highlighting gaps in the evidence. This study sets the baseline for the availability of evidence to support CSA programming in the five countries.


This summary is a free resource intended to make African research and research that affects Africa, more accessible to non-expert global audiences. It was compiled by ScienceLink's team of professional African science communicators as part of the Masakhane MT: Decolonise Science project. ScienceLink has taken every precaution possible during the writing, editing, and fact-checking process to ensure that this summary is easy to read and understand, while accurately reporting on the facts presented in the original research paper. Note, however, that this summary has not been fact-checked or approved by the authors of the original research paper, so this summary should be used as a secondary resource. Therefore, before using, citing or republishing this summary, please verify the information presented with the original authors of the research paper, or email [email protected] for more information.

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