Abstract
Improving nutrition security in sub-Saharan Africa under increasing climate risks and population growth requires a strong and contextualized evidence base. Yet, to date, few studies have assessed climate-smart agriculture and nutrition security simultaneously. Here we use an integrated assessment framework (iFEED) to explore stakeholder-driven scenarios of food system transformation towards climate-smart nutrition security in Malawi, South Africa, Tanzania and Zambia. iFEED translates climate-food-emissions modelling into policy-relevant information using model output implication statements. Results show that diversifying agricultural production towards more micronutrient-rich foods is necessary to achieve an adequate population-level nutrient supply by mid-century. Agricultural areas must expand unless unprecedented rapid yield improvements are achieved. While these transformations are challenging to accomplish and often associated with increased greenhouse gas emissions, the alternative for a nutrition-secure future is to rely increasingly on imports, which would outsource emissions and be economically and politically challenging given the large import increases required.
| Original language | English |
|---|---|
| Pages (from-to) | 37-47 |
| Number of pages | 11 |
| Journal | Nature Food |
| Volume | 5 |
| Early online date | 2 Jan 2024 |
| DOIs | |
| Publication status | Published - Jan 2024 |
Bibliographical note
For the purpose of open access, the author has applied a Creative Commons Attribution (CC BY) licence to any Author Accepted Manuscript version arising from this submission.This work was supported by the Biotechnology and Biological Sciences Research Council through UK Research and Innovation as part of the Global Challenges Research Fund, AFRICAP programme, grant number BB/P027784/1. This work was carried out with support from the CGIAR Initiative on Climate Resilience, ClimBeR. We would like to thank all funders who supported this research through their contributions to the CGIAR Trust Fund: https://www.cgiar.org/funders/.
Data Availability Statement
Source data supporting conclusions are shown in Supplementary Tables 1-4. Input data used in this study are from publicly available sources and referenced in Jennings et al. (2022). In summary, these consist of: the cumulative distribution function transform bias-corrected CMIP5 data over Africa at http://amma2050.ipsl.upmc.fr/ (to access the data, users must contact the lead author at moflod@locean-ipsl.upmc.fr); FAOSTAT yield and area and Food Balance Sheet data from https://www.fao.org/faostat/; soil data from the Regridded Harmonized World Soil Database v 1.2 at https://daac.ornl.gov/SOILS/guides/HWSD.html and gridded area data from Land-Use Harmonization II and World Database on Protected Areas. Source data are provided with this paper.Code availability
The methods used have been previously fully described in Jennings et al. (2022). The General Large Area Model for annual crops was used for the crop yield simulations. An older version of this model is available online at https://licensing.leeds.ac.uk/product/general-large-area-model-for-annual-crops-glam. The version (version number 79e1615) used for the simulations in this paper is available upon reasonable request. The ECOSSE model (Estimating Carbon in Organic Soils-Sequestration and Emissions) provided projections of greenhouse gas emissions, soil organic carbon and nitrogen dynamics associated with agriculture in each future scenario, taking into account yield and land-use changes. A spatial version of ECOSSE-Global ECOSSE (version 6.2b) was used. More information is available at https://soil-modeling.org/resources-links/model-portal/ecosse. An Excel spreadsheet was developed for nutrition data analysis and is available upon reasonable request.
Access to Document
- Jennings_etal_NF_Stakeholder_Driven_Transformative_VOR
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