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The impact of future climate change and potential adaptation methods on Maize yields in West Africa

  • Ben Parkes
  • Benjamin Sultan
  • Philippe Ciais
Article

Abstract

Maize (Zea mays) is one of the staple crops of West Africa and is therefore of high importance with regard to future food security. The ability of West Africa to produce enough food is critical as the population is expected to increase well into the twenty-first century. In this study, a process-based crop model is used to project maize yields in Africa for global temperatures 2 K and 4 K above the preindustrial control. This study investigates how yields and crop failure rates are influenced by climate change and the efficacy of adaptation methods to mitigate the effects of climate change. To account for the uncertainties in future climate projections, multiple model runs have been performed at specific warming levels of + 2 K and + 4 K to give a better estimate of future crop yields. Under a warming of + 2 K, the maize yield is projected to reduce by 5.9% with an increase in both mild and severe crop failure rates. Mild and severe crop failures are yields 1 and 1.5 standard deviations below the observed yield. At a warming of + 4 K, the results show a yield reduction of 37% and severe crop failures which previously only occurred once in 19.7 years are expected to happen every 2.5 years. Crops simulated with a resistance to high temperature stress show an increase in yields in all climate conditions compared to unadapted crops; however, they still experience more crop failures than the unadapted crop in the control climate.

Notes

Acknowledgements

The authors also wish to thank Julian Ramirez-Villegas for his help in developing the experimental methods.

Funding information

The research leading to these results has received financial support from the European Union Seventh Framework Programme FP7/2007-2013 under grant agreement no 603864. (HELIX: High-End cLimate Impacts and eXtremes; http://www.helixclimate.eu). PC is financially supported by the European Research Council Synergy grant ERC-2013-SyG-610028 IMBALANCE-P.

Supplementary material

10584_2018_2290_MOESM1_ESM.pdf (203 kb)
(PDF 203 KB)

References

  1. Berg A, de Noblet-Ducoudré N, Sultan B, Lengaigne M, Guimberteau M (2013) Projections of climate change impacts on potential c4 crop productivity over tropical regions. Agric For Meteorol 170:89 – 102.  https://doi.org/10.1016/j.agrformet.2011.12.003, http://www.sciencedirect.com/science/article/pii/S0168192311003406, agricultural prediction using climate model ensemblesCrossRefGoogle Scholar
  2. Biasutti M, Sobel AH (2009) Delayed Sahel rainfall and global seasonal cycle in a warmer climate. Geophys Res Lett 36(23).  https://doi.org/10.1029/2009GL041303
  3. Challinor A, Wheeler T (2008) Use of a crop model ensemble to quantify co2 stimulation of water-stressed and well-watered crops. Agric For Meteorol 148 (6):1062–1077.  https://doi.org/10.1016/j.agrformet.2008.02.006, http://www.sciencedirect.com/science/article/pii/S0168192308000622 CrossRefGoogle Scholar
  4. Challinor A, Wheeler T, Craufurd P, Slingo J, Grimes D (2004) Design and optimisation of a large-area process-based model for annual crops. Agric For Meteorol 124(1):99–120.  https://doi.org/10.1016/j.agrformet.2004.01.002, http://www.sciencedirect.com/science/article/pii/S0168192304000085 CrossRefGoogle Scholar
  5. Challinor A, Wheeler T, Craufurd P, Slingo J (2005) Simulation of the impact of high temperature stress on annual crop yields. Agric For Meteorol 135 (1):180–189.  https://doi.org/10.1016/j.agrformet.2005.11.015, http://www.sciencedirect.com/science/article/pii/S0168192305002509 CrossRefGoogle Scholar
  6. Challinor AJ, Watson J, Lobell DB, Howden SM, Smith DR, Chhetri N (2014) A meta-analysis of crop yield under climate change and adaptation. Nat Clim Chang 4:287.  https://doi.org/10.1038/nclimate2153 CrossRefGoogle Scholar
  7. Challinor AJ, Parkes B, Ramirez-Villegas J (2015) Crop yield response to climate change varies with cropping intensity. Glob Chang Biol 21(4):1679–1688.  https://doi.org/10.1111/gcb.12808 CrossRefGoogle Scholar
  8. Challinor AJ, Koehler AK, Ramirez-Villegas J, Whitfield S, Das B (2016) Current warming will reduce yields unless maize breeding and seed systems adapt immediately. Nat Clim Chang 6:954.  https://doi.org/10.1038/nclimate3061 CrossRefGoogle Scholar
  9. Elliott J, Müller C, Deryng D, Chryssanthacopoulos J, Boote KJ, Büchner M, Foster I, Glotter M, Heinke J, Iizumi T, Izaurralde RC, Mueller ND, Ray DK, Rosenzweig C, Ruane AC, Sheffield J (2015) The global gridded crop model intercomparison: data and modeling protocols for phase 1 (v1.0). Geosci Model Dev 8(2):261–277.  https://doi.org/10.5194/gmd-8-261-2015, https://www.geosci-model-dev.net/8/261/2015/ CrossRefGoogle Scholar
  10. FAOSTAT (2014) Food and Agriculture Organization of the United Nations: FAOSTAT Database. Online resource (http://data.fao.org/database?entryId=262b79ca-279c-4517-93de-ee3b7c7cb553), latest update: 07 Mar 2014
  11. Garcia-Carreras L, Challinor AJ, Parkes BJ, Birch CE, Nicklin KJ, Parker DJ (2015) The impact of parameterized convection on the simulation of crop processes. J Appl Meteorol Climatol 54(6):1283–1296.  https://doi.org/10.1175/JAMC-D-14-0226.1 CrossRefGoogle Scholar
  12. Ghannoum O, Von CS, Ziska LH, Conroy JP (2000) The growth response of c4 plants to rising atmospheric co2 partial pressure: a reassessment. Plant, Cell Environ 23(9):931–942.  https://doi.org/10.1046/j.1365-3040.2000.00609.x CrossRefGoogle Scholar
  13. Grillakis MG, Koutroulis AG, Tsanis IK (2013) Multisegment statistical bias correction of daily GCM precipitation output. J Geophys Res: Atmos 118(8):3150–3162.  https://doi.org/10.1002/jgrd.50323 Google Scholar
  14. Iizumi T, Ramankutty N (2016) Changes in yield variability of major crops for 1981-2010 explained by climate change. Environ Res Lett 11(3):034,003. http://stacks.iop.org/1748-9326/11/i=3/a=034003 CrossRefGoogle Scholar
  15. Iizumi T, Yokozawa M, Sakurai G, Travasso MI, Romanenkov V, Oettli P, Newby T, Ishigooka Y, Furuya J (2014) Historical changes in global yields: major cereal and legume crops from 1982 to 2006. Glob Ecol Biogeogr 23(3):346–357.  https://doi.org/10.1111/geb.12120 CrossRefGoogle Scholar
  16. Knox J, Hess T, Daccache A, Wheeler T (2012) Climate change impacts on crop productivity in Africa and South Asia. Environ Res Lett 7(3):034,032. http://stacks.iop.org/1748-9326/7/i=3/a=034032 CrossRefGoogle Scholar
  17. Leakey AD (2009) Rising atmospheric carbon dioxide concentration and the future of c4 crops for food and fuel. Proc Royal Soc Lond B: Biol Sci 276(1666):2333–2343.  https://doi.org/10.1098/rspb.2008.1517, http://rspb.royalsocietypublishing.org/content/276/1666/2333.full.pdf CrossRefGoogle Scholar
  18. Leakey ADB, Ainsworth EA, Bernacchi CJ, Rogers A, Long SP, Ort DR (2009) Elevated CO2 effects on plant carbon, nitrogen, and water relations: six important lessons from face. J Exp Bot 60(10):2859–2876.  https://doi.org/10.1093/jxb/erp096 CrossRefGoogle Scholar
  19. Lobell DB, Gourdji SM (2012) The influence of climate change on global crop productivity. Plant Physiol 160(4):1686–1697.  https://doi.org/10.1104/pp.112.208298, http://www.plantphysiol.org/content/160/4/1686.full.pdf CrossRefGoogle Scholar
  20. Lobell DB, Burke MB, Tebaldi C, Mastrandrea MD, Falcon WP, Naylor RL (2008) Prioritizing climate change adaptation needs for food security in 2030. Science 319(5863):607–610.  https://doi.org/10.1126/science.1152339, http://science.sciencemag.org/content/319/5863/607.full.pdf CrossRefGoogle Scholar
  21. Monfreda C, Ramankutty N, Foley JA (2008) Farming the planet: 2. Geographic distribution of crop areas, yields, physiological types, and net primary production in the year 2000. Global Biogeochem Cycles 22:GB1022.  https://doi.org/10.1029/2007GB002947 CrossRefGoogle Scholar
  22. Myers SS, Zanobetti A, Kloog I, Huybers P, Leakey ADB, Bloom AJ, Carlisle E, Dietterich LH, Fitzgerald G, Hasegawa T, Holbrook NM, Nelson RL, Ottman MJ, Raboy V, Sakai H, Sartor KA, Schwartz J, Seneweera S, Tausz M, Usui Y (2014) Increasing co2 threatens human nutrition. Nature 510:139.  https://doi.org/10.1038/nature13179 CrossRefGoogle Scholar
  23. Nikulin G, Jones C, Giorgi F, Asrar G, Büchner M, Cerezo-Mota R, Christensen OB, Déqué M, Fernandez J, Hänsler A, van Meijgaard E, Samuelsson P, Sylla MB, Sushama L (2012) Precipitation climatology in an ensemble of CORDEX-africa regional climate simulations. J Clim 25(18):6057–6078.  https://doi.org/10.1175/JCLI-D-11-00375.1 CrossRefGoogle Scholar
  24. Papadimitriou LV, Koutroulis AG, Grillakis MG, Tsanis IK (2016) High-end climate change impact on european runoff and low flows – exploring the effects of forcing biases. Hydrol Earth Syst Sci 20(5):1785–1808.  https://doi.org/10.5194/hess-20-1785-2016, https://www.hydrol-earth-syst-sci.net/20/1785/2016/ CrossRefGoogle Scholar
  25. Parkes B, Defrance D, Sultan B, Ciais P, Wang X (2018) Projected changes in crop yield mean and variability over west africa in a world 1.5 k warmer than the pre-industrial era. Earth Syst Dyn 9(1):119–134.  https://doi.org/10.5194/esd-9-119-2018, https://www.earth-syst-dynam.net/9/119/2018/ CrossRefGoogle Scholar
  26. Parry M, Rosenzweig C, Iglesias A, Livermore M, Fischer G (2004) Effects of climate change on global food production under SRES emissions and socio-economic scenarios. Glob Environ Chang 14(1):53–67.  https://doi.org/10.1016/j.gloenvcha.2003.10.008, http://www.sciencedirect.com/science/article/pii/S0959378003000827, climate ChangeCrossRefGoogle Scholar
  27. Ray DK, Mueller ND, West PC, Foley JA (2013) Yield trends are insufficient to double global crop production by 2050. PLOS ONE 8(6):1–8.  https://doi.org/10.1371/journal.pone.0066428 CrossRefGoogle Scholar
  28. Rippke U, Ramirez-Villegas J, Jarvis A, Vermeulen SJ, Parker L, Mer F, Diekkrüger B, Challinor AJ, Howden M (2016) Timescales of transformational climate change adaptation in sub-saharan african agriculture. Nat Clim Chang 6:605.  https://doi.org/10.1038/nclimate2947 CrossRefGoogle Scholar
  29. Rosenzweig C, Parry ML (1994) Potential impact of climate change on world food supply. Nature 367:133.  https://doi.org/10.1038/367133a0 CrossRefGoogle Scholar
  30. Roudier P, Sultan B, Quirion P, Berg A (2011) The impact of future climate change on west african crop yields: What does the recent literature say?. Glob Environ Chang 21(3):1073 – 1083.  https://doi.org/10.1016/j.gloenvcha.2011.04.007, http://www.sciencedirect.com/science/article/pii/S0959378011000677, Symposium on Social Theory and the Environment in the New World (dis)OrderCrossRefGoogle Scholar
  31. Sultan B, Guan K, Kouressy M, Biasutti M, Piani C, Hammer GL, McLean G, Lobell DB (2014) Robust features of future climate change impacts on sorghum yields in west africa. Environ Res Lett 9(10):104,006. http://stacks.iop.org/1748-9326/9/i=10/a=104006 CrossRefGoogle Scholar
  32. Tubiello FN, Rosenzweig C, Goldberg RA, Jagtap S, Jones JW (2002) Effects of climate change on us crop production: simulation results using two different gcm scenarios. part i: wheat, potato, maize, and citrus. Clim Res 20(3):259–270. https://www.int-res.com/abstracts/cr/v20/n3/p259-270/ CrossRefGoogle Scholar
  33. United Nations DESA (2015) World population prospects: The 2015 revision. In: Volume I: Comprehensive Tables (ST/ESA/SER.A/379), United NationsGoogle Scholar
  34. Vermeulen SJ, Challinor AJ, Thornton PK, Campbell BM, Eriyagama N, Vervoort JM, Kinyangi J, Jarvis A, Läderach P, Ramirez-Villegas J, Nicklin KJ, Hawkins E, Smith DR (2013) Addressing uncertainty in adaptation planning for agriculture. Proc Natl Acad Sci 110(21):8357–8362.  https://doi.org/10.1073/pnas.1219441110, http://www.pnas.org/content/110/21/8357.full.pdf CrossRefGoogle Scholar
  35. Wahid A, Gelani S, Ashraf M, Foolad M (2007) Heat tolerance in plants: an overview. Environ Exper Bot 61(3):199 – 223.  https://doi.org/10.1016/j.envexpbot.2007.05.011, http://www.sciencedirect.com/science/article/pii/S0098847207000871 CrossRefGoogle Scholar

Copyright information

© Springer Nature B.V. 2018

Authors and Affiliations

  1. 1.(UPMC, University of Paris 06)-CNRS-IRD-MNHN LOCEAN/IPSLSorbonne UniversitésParisFrance
  2. 2.ESPACE-DEVUniv. Montpellier, IRD, Univ. Guyane, Univ. Réunion, Univ. Antilles, Univ. AvignonMontpellierFrance
  3. 3.IPSL - LSCE, CEA CNRS UVSQ UPSaclayCentre d’Etudes Orme des MerisiersGif sur YvetteFrance
  4. 4.School of Mechanical, Aerospace and Civil EngineeringUniversity of ManchesterManchesterUK

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