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The uncertainty of crop yield projections is reduced by improved temperature response functions

Nature Plants volume 3, Article number: 17102 (2017) Cite this article

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An Author Correction to this article was published on 27 September 2017

An Erratum to this article was published on 03 August 2017

This article has been updated

Abstract

Increasing the accuracy of crop productivity estimates is a key element in planning adaptation strategies to ensure global food security under climate change. Process-based crop models are effective means to project climate impact on crop yield, but have large uncertainty in yield simulations. Here, we show that variations in the mathematical functions currently used to simulate temperature responses of physiological processes in 29 wheat models account for >50% of uncertainty in simulated grain yields for mean growing season temperatures from 14 °C to 33 °C. We derived a set of new temperature response functions that when substituted in four wheat models reduced the error in grain yield simulations across seven global sites with different temperature regimes by 19% to 50% (42% average). We anticipate the improved temperature responses to be a key step to improve modelling of crops under rising temperature and climate change, leading to higher skill of crop yield projections.

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Figure 1: Temperature response functions in 29 wheat simulation models.
Figure 2: Comparison of multi-model simulations against observations and average growing season temperature.
Figure 3: Uncertainty in simulated wheat responses due to variations in the temperature response functions of phenological development and biomass growth (RUE).
Figure 4: Derived temperature responses of various physiological processes.
Figure 5: Comparison of Q10 for respiration derived from the temperature response function in Fig. 4c to the temperature dependence of the Q10 of foliar respiration rates17.

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Change history

  • 27 September 2017

    In the original version of this Article, the name of one co-author was omitted. This has now been corrected by the addition of Benjamin Dumont to the author list.

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Acknowledgements

The authors thank D. Lobell for useful comments on an earlier version of the paper. E.W. acknowledges support from the CSIRO project ‘Enhanced modelling of genotype by environment interactions’ and the project ‘Advancing crop yield while reducing the use of water and nitrogen’ jointly funded by CSIRO and the Chinese Academy of Sciences (CAS). Z.Z. received a scholarship from the China Scholarship Council through the CSIRO and the Chinese Ministry of Education PhD Research Program. P.M., A.M. and D.R. acknowledge support from the FACCE JPI MACSUR project (031A103B) through the metaprogram Adaptation of Agriculture and Forests to Climate Change (AAFCC) of the French National Institute for Agricultural Research (INRA). A.M. received the support of the EU in the framework of the Marie-Curie FP7 COFUND People Programme, through the award of an AgreenSkills fellowship under grant agreement No. PCOFUND-GA-2010-267196. S.A. and D.C. acknowledge support provided by the International Food Policy Research Institute (IFPRI), CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS), the CGIAR Research Program on Wheat and the Wheat Initiative. C.S. was funded through USDA National Institute for Food and Agriculture award 32011-68002-30191. C.M. received financial support from the KULUNDA project (01LL0905 L) and the FACCE MACSUR project (031A103B) funded through the German Federal Ministry of Education and Research (BMBF). F.E. received support from the FACCE MACSUR project (031A103B) funded through the German Federal Ministry of Education and Research (2812ERA115) and E.E.R. was funded through the German Federal Ministry of Economic Cooperation and Development (Project: PARI). M.J. and J.E.O. were funded through the FACCE MACSUR project by the Danish Strategic Research Council. K.C.K. and C.N. were funded by the FACCE MACSUR project through the German Federal Ministry of Food and Agriculture (BMEL). F.T., T.P. and R.P.R. received financial support from the FACCE MACSUR project funded through the Finnish Ministry of Agriculture and Forestry (MMM); F.T. was also funded through the National Natural Science Foundation of China (No. 41071030). C.B. was funded through the Helmholtz project ‘REKLIM-Regional Climate Change: Causes and Effects’ Topic 9: ‘Climate Change and Air Quality’. M.P.R. and PD.A. received funding from the CGIAR Research Program on Climate Change, Agriculture, and Food Security (CCAFS). G.O'L. was funded through the Australian Grains Research and Development Corporation and the Department of Economic Development, Jobs, Transport and Resources Victoria, Australia. R.C.I. was funded by Texas AgriLife Research, Texas A&M University. B.B. was funded by USDA-NIFA Grant No: 2015-68007-23133.

Author information

Author notes

  1. Andrea Maiorano

    Present address: European Commission Joint Research Centre, 21 027, Ispra, Italy

  2. Phillip D. Alderman

    Present address: Department of Plant and Soil Sciences, Oklahoma State University, Stillwater, Oklahoma, 74078-6028, USA

  3. Jakarat Anothai

    Present address: Department of Plant Science, Faculty of Natural Resources, Prince of Songkla University, Songkhla, 90112, Thailand

  4. Davide Cammarano

    Present address: James Hutton Institute, Invergowrie, Dundee, DD2 5DA, Scotland, UK

  5. Gerrit Hoogenboom

    Present address: Institute for Sustainable Food Systems, University of Florida, Gainesville, Florida, 32611, USA

  6. Iurii Shcherbak

    Present address: Institute of Future Environment, Queensland University of Technology, Brisbane, Queensland, 4001, Australia

  7. Katharina Waha

    Present address: CSIRO Agriculture and Food, St Lucia, Queensland, 4067, Australia

  8. Enli Wang and Pierre Martre: These authors contributed equally to this work

  9. Reimund P. Rötter: Formerly: Natural Ressources Institute Finland (Luke), 00790 Helsinki, Finland

  10. Pramod K. Aggarwal and Yan Zhu: Authors from P.K.A. to Y.Z. are listed in alphabetical order

  11. Giacomo De Sanctis: The views expressed in this paper are the views of the authors and do not necessarily represent the views of the organization or institution with which they are currently affiliated.

Authors and Affiliations

  1. CSIRO Agriculture and Food, Black Mountain, Australian Capital Territory, 2601, Australia

    Enli Wang & Zhigan Zhao

  2. UMR LEPSE, INRA, Montpellier SupAgro, 2 Place Viala, 34 060 Montpellier, France

    Pierre Martre & Andrea Maiorano

  3. College of Agronomy and Biotechnology, China Agricultural University, 100193, Beijing, China

    Zhigan Zhao & Zhimin Wang

  4. Institute of Crop Science and Resource Conservation (INRES), University of Bonn, 53115 Bonn, Germany

    Frank Ewert & Ehsan Eyshi Rezaei

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

    Frank Ewert, Kurt C. Kersebaum & Claas Nendel

  6. Department of Crop Sciences, University of Goettingen, Tropical Plant Production and Agricultural Systems Modelling (TROPAGS), 37077 Göttingen, Germany

    Reimund P. Rötter

  7. Centre of Biodiversity and Sustainable Land Use (CBL), University of Goettingen, Büsgenweg 1, 37077 Göttingen, Germany

    Reimund P. Rötter

  8. USDA, Agricultural Research Service, U.S. Arid-Land Agricultural Research Center, Maricopa, 85138, Arizona, USA

    Bruce A. Kimball, Gerard W. Wall & Jeffrey W. White

  9. The School of Plant Sciences, University of Arizona, Tucson, 85721, Arizona, USA

    Michael J. Ottman

  10. Global Wheat Program, International Maize and Wheat Improvement Center (CIMMYT) Apdo, 06600 Mexico, D.F, Mexico

    Matthew P. Reynolds & Phillip D. Alderman

  11. CGIAR Research Program on Climate Change, Agriculture and Food Security, Borlaug Institute for South Asia, International Maize and Wheat Improvement Center (CIMMYT), 110012, New Delhi, India

    Pramod K. Aggarwal

  12. AgWeatherNet Program, Washington State University, Prosser, 99350-8694, Washington, USA

    Jakarat Anothai & Gerrit Hoogenboom

  13. Department of Earth and Environmental Sciences and W.K. Kellogg Biological Station, Michigan State University East Lansing, 48823, Michigan, USA

    Bruno Basso, Benjamin Dumont & Iurii Shcherbak

  14. Helmholtz Zentrum München – German Research Center for Environmental Health, Institute of Biochemical Plant Pathology, 85764, Neuherberg, Germany

    Christian Biernath & Eckart Priesack

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

    Davide Cammarano & Senthold Asseng

  16. Institute for Climate and Atmospheric Science, School of Earth and Environment, University of Leeds, LS29JT, Leeds, UK

    Andrew J. Challinor & Ann-Kristin Koehler

  17. CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS), Km 17, Recta Cali-Palmira Apartado Aéreo 6713, Cali, Colombia

    Andrew J. Challinor

  18. GMO Unit, European Food Safety Authority (EFSA), Via Carlo Magno, 1A, 43126 Parma, Italy

    Giacomo De Sanctis

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

    Jordi Doltra

  20. Dep. Agronomia, University of Cordoba, Apartado 3048, 14080 Cordoba, Spain

    Elias Fereres & Margarita Garcia-Vila

  21. IAS-CSIC, 14080, Cordoba, Spain

    Elias Fereres & Margarita Garcia-Vila

  22. Institute of Soil Science and Land Evaluation, University of Hohenheim, 70599 Stuttgart, Germany

    Sebastian Gayler & Thilo Streck

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

    Leslie A. Hunt

  24. Department of Geographical Sciences, University of Maryland, College Park, 20742, Maryland, USA

    Roberto C. Izaurralde & Curtis D. Jones

  25. Texas A&M AgriLife Research and Extension Center, Texas A&M University, Temple, 76502, Texas, USA

    Roberto C. Izaurralde

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

    Mohamed Jabloun & Jørgen E. Olesen

  27. National Engineering and Technology Center for Information Agriculture, Key Laboratory for Crop System Analysis and Decision Making, Ministry of Agriculture, Jiangsu Key Laboratory for Information Agriculture, Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China

    Leilei Liu & Yan Zhu

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

    Christoph Müller & Katharina Waha

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

    Soora Naresh Kumar

  30. Department of Economic Development, Landscape & Water Sciences, Jobs, Transport and Resources, 3400, Horsham, Australia

    Garry O'Leary

  31. Natural Resources Institute Finland (Luke), Latokartanonkaari 9, 00790 Helsinki, Finland

    Taru Palosuo & Fulu Tao

  32. INRA, US1116 AgroClim, 84 914 Avignon, France

    Dominique Ripoche

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

    Alex C. Ruane

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

    Mikhail A. Semenov & Pierre Stratonovitch

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

    Claudio Stöckle

  36. PPS and WSG & CALM, Wageningen University, 6700AA Wageningen, The Netherlands

    Iwan Supit & Joost Wolf

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

    Fulu Tao

  38. CSIRO Agriculture and Food, St Lucia, 4067, Queensland, Australia

    Peter Thorburn

  39. INRA, UMR 1248 Agrosystèmes et développement territorial (AGIR), 31 326 Castanet-Tolosan, France

    Daniel Wallach

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  1. Enli Wang
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  2. Pierre Martre
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  3. Zhigan Zhao
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  4. Frank Ewert
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  6. Reimund P. Rötter
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  11. Matthew P. Reynolds
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  13. Pramod K. Aggarwal
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  14. Jakarat Anothai
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  15. Bruno Basso
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  21. Benjamin Dumont
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  55. Yan Zhu
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  56. Senthold Asseng
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Contributions

E.W., P.M., S.A. and F.E. motivated the study; E.W. and P.M. designed and coordinated the study, and analysed the data; E.W., P.M., Z.Z., A.M., L.L. and B.B. conducted model improvement simulations; E.W., P.M., S.A., F.E., Z.Z., A.M., R.P.R.,.K.A., P.D.A., J.A., C.B., D.C., A.J.C., G.D.S., J.D., E.F., M.G.-V., S.G., G.H., L.A.H., R.C.I., M.J., C.D.J., K.C.K., A.-K.K., C.M., L.L., S.N.K., C.N., G.O'L., J.E.O., T.P., E.P., M.P.R., E.E.R., D.R., A.C.R., M.A.S., I.S., C.S., P.S., T.S., I.S., F.T., P.T., K.W., D.W., J.W. and Y.Z. carried out crop model simulations and discussed the results; B.A.K., M.J.O., G.W.W., J.W.W., M.P.R., P.D.A. and Z.W. provided experimental data; E.W. and P.M. analysed the results and wrote the paper.

Corresponding authors

Correspondence to Enli Wang or Pierre Martre.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Information

Supplementary Tables 1–4, Supplementary Figures 1–4, Supplementary References (PDF 2031 kb)

Supplementary Data 1

Extracted data describing the key temperature response functions in each of the 29 wheat models. (XLSX 12620 kb)

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Wang, E., Martre, P., Zhao, Z. et al. The uncertainty of crop yield projections is reduced by improved temperature response functions. Nature Plants 3, 17102 (2017). https://doi.org/10.1038/nplants.2017.102

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