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Uncertainty in simulating wheat yields under climate change

Nature Climate Change volume 3, pages 827–832 (2013)Cite this article

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Abstract

Projections of climate change impacts on crop yields are inherently uncertain1. Uncertainty is often quantified when projecting future greenhouse gas emissions and their influence on climate2. However, multi-model uncertainty analysis of crop responses to climate change is rare because systematic and objective comparisons among process-based crop simulation models1,3 are difficult4. Here we present the largest standardized model intercomparison for climate change impacts so far. We found that individual crop models are able to simulate measured wheat grain yields accurately under a range of environments, particularly if the input information is sufficient. However, simulated climate change impacts vary across models owing to differences in model structures and parameter values. A greater proportion of the uncertainty in climate change impact projections was due to variations among crop models than to variations among downscaled general circulation models. Uncertainties in simulated impacts increased with CO2 concentrations and associated warming. These impact uncertainties can be reduced by improving temperature and CO2 relationships in models and better quantified through use of multi-model ensembles. Less uncertainty in describing how climate change may affect agricultural productivity will aid adaptation strategy development andpolicymaking.

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Figure 1: Wheat model–observation comparisons.
Figure 2: Variability in impact model uncertainty.
Figure 3: Sensitivity of simulated and observed wheat to temperature and CO2 change.
Figure 4: Size of model ensembles and impact model uncertainty.

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Author notes

  1. Passed away in 2011 while this work was being carried out

Authors and Affiliations

  1. Agricultural and Biological Engineering Department, University of Florida, Gainesville, Florida 32611, USA

    S. Asseng, J. W. Jones & D. Cammarano

  2. Institute of Crop Science and Resource Conservation INRES, University of Bonn, 53115, Germany

    F. Ewert & C. Angulo

  3. NASA Goddard Institute for Space Studies, New York, New York 10025, USA

    C. Rosenzweig, A. C. Ruane & R. Goldberg

  4. National Laboratory for Agriculture and Environment, Ames, Iowa 50011, USA

    J. L. Hatfield

  5. Department of Agronomy, University of Florida, Gainesville, Florida 32611-0500, USA

    K. J. Boote

  6. CSIRO Ecosystem Sciences, Dutton Park, Queensland 4102, Australia

    P. J. Thorburn

  7. Plant Production Research, MTT Agrifood Research Finland, FI-50100 Mikkeli, Finland

    R. P. Rötter & T. Palosuo

  8. INRA, UMR0211 Agronomie, F-78 750 Thiverval-Grignon, France

    N. Brisson

  9. AgroParisTech, UMR0211 Agronomie, F-78 750 Thiverval-Grignon, France

    N. Brisson

  10. Department of Geological Sciences and W. K. Kellogg Biological Station, Michigan State University East Lansing, Michigan 48823, USA

    B. Basso & I. Shcherbak

  11. INRA, UMR1095 Genetic, Diversity and Ecophysiology of Cererals (GDEC), F-63 100 Clermont-Ferrand, France

    P. Martre

  12. Blaise Pascal University, UMR1095 GDEC, F-63 170 Aubière, France

    P. Martre

  13. CCAFS, IWMI, NASC Complex, DPS Marg, New Delhi 12, India

    P. K. Aggarwal

  14. INRA, US1116 AgroClim, F-84 914 Avignon, France

    P. Bertuzzi & D. Ripoche

  15. Institute of Soil Ecology, Helmholtz Zentrum München—German Research Center for Environmental Health, Neuherberg, D-85764, Germany

    C. Biernath & E. Priesack

  16. Institute for Climate and Atmospheric Science, School of Earth and Environment, University of Leeds, Leeds LS2 9JT, UK

    A. J. Challinor

  17. CGIAR-ESSP Program on Climate Change, Agriculture and Food Security, International Centre for Tropical Agriculture (CIAT), A.A. 6713, Cali, Colombia

    A. J. Challinor

  18. Cantabrian Agricultural Research and Training Centre (CIFA), 39600 Muriedas, Spain

    J. Doltra

  19. WESS-Water and Earth System Science Competence Cluster, University of Tübingen, 72074 Tübingen, Germany

    S. Gayler

  20. Department of Renewable Resources, University of Alberta, Edmonton, Alberta T6G 2E3, Canada

    R. Grant

  21. IAEA, Vienna, Austria

    L. Heng

  22. Agriculture Department, University of Reading, Reading RG6 6AR, UK

    J. Hooker

  23. Department of Plant Agriculture, University of Guelph, Guelph, Ontario, N1G 2W1, Canada

    L. A. Hunt

  24. Institute of Soil Science and Land Evaluation, Universität Hohenheim, 70593 Stuttgart, Germany

    J. Ingwersen & T. Streck

  25. Joint Global Change Research Institute, College Park, Maryland 20740, USA

    R. C. Izaurralde

  26. Institute of Landscape Systems Analysis, Leibniz Centre for Agricultural Landscape Research, 15374 Müncheberg, Germany

    K. C. Kersebaum & C. Nendel

  27. Potsdam Institute for Climate Impact Research, 14473 Potsdam, Germany

    C. Müller & K. Waha

  28. Centre for Environment Science and Climate Resilient Agriculture, Indian Agricultural Research Institute, IARI PUSA, New Delhi 110 012, India

    S. Naresh Kumar

  29. Department of Primary Industries, Landscape and Water Sciences, Horsham 3400, Australia

    G. O’Leary

  30. Department of Agroecology, Aarhus University, 8830, Tjele, Denmark

    J. E. Olesen

  31. NCAS-Climate, Walker Institute, University of Reading, RG6 6BB, UK

    T. M. Osborne

  32. Computational and Systems Biology Department, Rothamsted Research, Harpenden AL5 2JQ, UK

    M. A. Semenov & P. Stratonovitch

  33. FAO, Rome, Italy

    P. Steduto

  34. Biological Systems Engineering, Washington State University, Pullman, Washington 99164-6120, USA

    C. Stöckle

  35. Plant Production Systems and Earth System Science-Climate Change, Wageningen University, 6700AA Wageningen, The Netherlands

    I. Supit & J. Wolf

  36. Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Science, Beijing 100101, China

    F. Tao

  37. Institute for Climate and Water, INTA-CIRN, 1712 Castelar, Argentina

    M. Travasso

  38. INRA, UMR 1248 Agrosystèmes et développement territorial (AGIR), 31326 Castanet-Tolosan Cedex, France

    D. Wallach

  39. Arid-Land Agricultural Research Center, Maricopa, Arizona 85138, USA

    J. W. White

  40. Texas A&M University, Temple, Texas 76502, USA

    J. R. Williams

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  1. S. Asseng
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  2. F. Ewert
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Contributions

S.A., F.E., C.R., J.W.J., K.J.B. and J.L.H. motivated the study; S.A. and F.E. coordinated the study; S.A., F.E., D.W., P.M., D.C. and A.C.R. analysed data; D.C., A.C.R., K.J.B., P.J.T., R.P.R., N.B., B.B., D.R., P.B., P.S., L.H., M.A.S., P.S., C.S., G.O.L., P.K.A., S.N.K., R.C.I., J.W.W., L.A.H., R.G., K.C.K., T.P., J.H., T.O., J.W., I.S., J.E.O., J.D., C.N., S.G., J.I., E.P., T.S., F.T., C.M., K.W., R.G., C.A., I.S., C.B., J.R.W. and A.J.C. carried out crop model simulations and discussed the results; M.T. and S.N.K., provided experimental data; S.A., F.E., C.R. and J.W.J. wrote the paper.

Corresponding author

Correspondence to S. Asseng.

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Asseng, S., Ewert, F., Rosenzweig, C. et al. Uncertainty in simulating wheat yields under climate change. Nature Clim Change 3, 827–832 (2013). https://doi.org/10.1038/nclimate1916

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