Modelling cereal crops to assess future climate risk for family food self-sufficiency in southern Mali

Traore, B and Descheemaeker, K and van Wijk, M T and Corbeels, M and Supit, I and Giller, K E (2017) Modelling cereal crops to assess future climate risk for family food self-sufficiency in southern Mali. Field Crops Research, 201. pp. 133-145. ISSN 03784290

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Abstract

Future climate change will have far reaching consequences for smallholder farmers in sub-Saharan Africa, the majority of whom depend on agriculture for their livelihoods. Here we assessed the farm-level impact of climate change on family food self-sufficiency and evaluated potential adaptation options of crop management. Using three years of experimental data on maize and millet from an area in southern Mali representing the Sudano-Sahelian zone of West Africa we calibrated and tested the Agricultural Production Systems sIMulator (APSIM) model. Changes in future rainfall, maximum and minimum temperature and their simulated effects on maize and millet yield were analysed for climate change predictions of five Global Circulation Models (GCMs) for the 4.5 Wm−2 and 8.5 Wm−2 radiative forcing scenario (rcp4.5 and rcp8.5). In southern Mali, annual maximum and minimum temperatures will increase by 2.9 °C and 3.3 °C by the mid-century (2040–2069) as compared with the baseline (1980–2009) under the rcp4.5 and rcp8.5 scenario respectively. Predicted changes in the total seasonal rainfall differed between the GCMs, but on average, seasonal rainfall was predicted not to change. By mid-century maize grain yields were predicted to decrease by 51% and 57% under current farmer’s fertilizer practices in the rcp4.5 and rcp8.5 scenarios respectively. APSIM model predictions indicated that the use of mineral fertilizer at recommended rates cannot fully offset the impact of climate change but can buffer the losses in maize yield up to 46% and 51% of the baseline yield. Millet yield losses were predicted to be less severe under current farmer’s fertilizer practices by mid-century i.e. 7% and 12% in the rcp4.5 and rcp8.5 scenario respectively. Use of mineral fertilizer on millet can offset the predicted yield losses resulting in yield increases under both emission scenarios. Under future climate and current cropping practices, food availability is expected to reduce for all farm types in southern Mali. However, large and medium-sized farms can still achieve food self–sufficiency if early planting and recommended rates of fertilizer are applied. Small farms, which are already food insecure, will experience a further decrease in food self-sufficiency, with adaptive measures of early planting and fertilizer use unable to help them achieve food self-sufficiency. By taking into account the diversity in farm households that is typical for the region, we illustrated that crop management strategies must be tailored to the capacity and resource endowment of local farmers. Our place-based findings can support decision making by extension and development agents and policy makers in the Sudano-Sahelian zone of West Africa.

Item Type:	Article
Divisions:	Research Program : West & Central Africa
CRP:	CGIAR Research Program on Dryland Systems
Uncontrolled Keywords:	Crop simulation modelling; Planting date; Fertilizer use; APSIM; Sub-Saharan Africa; Climate change
Subjects:	Others > Crop Modelling Others > Cereals Others > Climate Change Others > Food Security Others > Mali
Depositing User:	Mr Ramesh K
Date Deposited:	02 Dec 2016 11:02
Last Modified:	24 Jul 2018 09:38
URI:	http://oar.icrisat.org/id/eprint/9804
Official URL:	http://dx.doi.org/10.1016/j.fcr.2016.11.002
Projects:	UNSPECIFIED
Funders:	International Development Research Centre (IDRC) and Department for International Development (DFID)
Acknowledgement:	We thank the International Development Research Centre(IDRC) and Department for International Development (DFID) forfunding through the Climate Change Adaptation in Africa (CCAA)Grant to the University of Zimbabwe. Additional funding from theInstitut D’Economie Rurale du Mali is gratefully acknowledged. Wethank the World Climate Research Programme’s Working Groupon Coupled Modelling, which is responsible for CMIP, and theclimate modelling groups (CNRM-CM5, ECEARTH, HADGEM2-ES,IPSL-CM5A-LR, MPI-ESM-LR) for making available their model out-put. We are grateful to Neil Huth, Myriam Adam, IrenikatcheAkponikpè and Dilys MacCarthy for help with the APSIM model.
Links:	Google Scholar

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