Modelling mixed crop-livestock systems and climate impact assessment in sub-Saharan Africa
Abstract Climate change significantly challenges smallholder mixed crop-livestock (MCL) systems in sub-Saharan Africa (SSA), affecting food and feed production. This study enhances the SIMPLACE modeling framework by incorporating crop-vegetation-livestock models, which contribute to the development...
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Main Authors: | , , , , , , , , , , , , , |
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Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2025-01-01
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Series: | Scientific Reports |
Online Access: | https://doi.org/10.1038/s41598-024-81986-8 |
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Summary: | Abstract Climate change significantly challenges smallholder mixed crop-livestock (MCL) systems in sub-Saharan Africa (SSA), affecting food and feed production. This study enhances the SIMPLACE modeling framework by incorporating crop-vegetation-livestock models, which contribute to the development of sustainable agricultural practices in response to climate change. Applying such a framework in a domain in West Africa (786,500 km2) allowed us to estimate the changes in crop (Maize, Millet, and Sorghum) yield, grass biomass, livestock numbers, and greenhouse gas emission in response to future climate scenarios. We demonstrate that this framework accurately estimated the key components of the domain for the past (1981–2005) and enables us to project their future changes using dynamically downscaled Global Circulation Model (GCM) projections (2020–2050). The results demonstrate that in the future, the northern part of the study area will likely experience a significant decline in crop biomass (up to -56%) and grass biomass (up to -57%) production leading to a decrease in livestock numbers (up to -43%). Consequently, this will impact total emissions (up to -47% CH4) and decrease of -41% in milk production, and − 47% in meat production concentrated in the Sahelian zone. Whereas, in pockets of the Sudanian zone, an increase in livestock population and CH4 emission of about + 24% has been estimated, indicating that variability in climate change impact is amplifying with no consistent pattern evident across the study domain. |
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ISSN: | 2045-2322 |