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A meta-analysis of crop yield under climate change and adaptation

Nature Climate Change volume 4, pages 287291 (2014) | Download Citation


Feeding a growing global population in a changing climate presents a significant challenge to society1,2. The projected yields of crops under a range of agricultural and climatic scenarios are needed to assess food security prospects. Previous meta-analyses3 have summarized climate change impacts and adaptive potential as a function of temperature, but have not examined uncertainty, the timing of impacts, or the quantitative effectiveness of adaptation. Here we develop a new data set of more than 1,700 published simulations to evaluate yield impacts of climate change and adaptation. Without adaptation, losses in aggregate production are expected for wheat, rice and maize in both temperate and tropical regions by 2 °C of local warming. Crop-level adaptations increase simulated yields by an average of 7–15%, with adaptations more effective for wheat and rice than maize. Yield losses are greater in magnitude for the second half of the century than for the first. Consensus on yield decreases in the second half of the century is stronger in tropical than temperate regions, yet even moderate warming may reduce temperate crop yields in many locations. Although less is known about interannual variability than mean yields, the available data indicate that increases in yield variability are likely.

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  1. 1.

    et al. What next for agriculture after durban?. Science 335, 289–290 (2012).

  2. 2.

    , & Food security and global environmental change: Emerging challenges. Environ. Sci. Policy 12, 373–377 (2009).

  3. 3.

    et al. in Climate Change 2007: Impacts, Adaptation and Vulnerability (eds Parry, M. L., Canziani, O. F., Palutikof, J. P., van der Linden, P. J. & Hanson, C. E.) Food, fibre and forest products. 273–313 (Cambridge Univ. Press, 2007).

  4. 4.

    et al. The top 100 questions of importance to the future of global agriculture. Int. J. Agr. Sustain. 8, 219–236 (2010).

  5. 5.

    et al. Food security: The challenge of feeding 9 billion people. Science 327, 812–818 (2010).

  6. 6.

    The global supply and demand for agricultural land in 2050: A perfect storm in the making?. Amer. J. Agr. Econom. 93, 259–275 (2011).

  7. 7.

    , , & Crop and pasture response to climate change. Proc. Natl Acad. Sci. USA 104, 19686–19690 (2007).

  8. 8.

    , & Climate trends and global crop production since 1980. Science 333, 616–620 (2011).

  9. 9.

    , , , & Crops and climate change: Progress, trends, and challenges in simulating impacts and informing adaptation. J. Exp. Botany 60, 2775–2789 (2009).

  10. 10.

    & Transformational adaptation: Agriculture and climate change. Crop Pasture Sci. 63, 240–250 (2012).

  11. 11.

    , , & Methodologies for simulating impacts of climate change on crop production. Field Crops Res. 124, 357–368 (2011).

  12. 12.

    et al. Adapting agriculture to climate change. Proc. Natl Acad. Sci. USA 104, 19691–19696 (2007).

  13. 13.

    , , & Climate change impacts on crop productivity in Africa and South Asia. Environ. Res. Lett. 7, 034032 (2012).

  14. 14.

    , , & Climate change risks for African agriculture. Proc. Natl Acad. Sci. USA 108, 4313–4315 (2011).

  15. 15.

    , , , & Adapting to climate change: Agricultural system and household impacts in East Africa. Agr. Systems 103, 73–82 (2010).

  16. 16.

    & Global scale climate-crop yield relationships and the impacts of recent warming. Environ. Res. Lett. 2, 004000 (2007).

  17. 17.

    & in Advances and applications for management and decision making (eds Zerger, A. & Argent, R. M.) 170–176 (Modelling and Simulation Society of Australia and New Zealand, 2005).

  18. 18.

    et al. Are there social limits to adaptation to climate change?. Climatic Change 93, 335–354 (2009).

  19. 19.

    et al. The impacts of climate change on water resources and agriculture in China. Nature 467, 43–51 (2010).

  20. 20.

    , & Improving the use of modelling for projections of climate change impacts on crops and pastures. J. Ext. Bot. 61, 2217–2228 (2010).

  21. 21.

    , , , & Increased crop failure due to climate change: Assessing adaptation options using models and socio-economic data for wheat in China. Environ. Res. Lett. 5, 034012 (2010).

  22. 22.

    , , & Integrating pests and pathogens into the climate change/food security debate. J. Exp. Botany 60, 2827–2838 (2009).

  23. 23.

    et al. The effects of climate variability and the color of weather time series on agricultural diseases and pests, and on decisions for their management. Agr. Forest Meteorol. 170, 216–227 (2013).

  24. 24.

    et al. Implication of crop model calibration strategies for assessing regional impacts of climate change in Europe. Agr. Forest Meteorol. 170, 32–46 (2013).

  25. 25.

    et al. Methods and resources for climate impacts research: Achieving synergy. Bull. Amer. Meteorol. Soc. 90, 825–835 (2009).

  26. 26.

    , , & Calibration and bias correction of climate projections for crop modelling: An idealised case study over Europe. Agr. Forest Meteorol. 170, 32–46 (2013).

  27. 27.

    et al. The Agricultural Model Intercomparison and Improvement Project (AgMIP): Protocols and pilot studies. Agr. Forest Meteorol. 170, 166182 (2013).

  28. 28.

    , & Perception of climate change. Proc. Natl Acad. Sci. USA 109, 14720–14721 (2012).

  29. 29.

    et al. Severe Weather and UK Food Chain Resilience. Detailed appendix to synthesis report (Biotechnology and Biological Sciences Research Council, 2012);

  30. 30.

    et al. Increasing influence of heat stress on French maize yields from the 1960s to the 2030s. Glob. Change Biol. 19, 937–947 (2013).

  31. 31.

    , , , & Projections of climate change impacts on potential C4 crop productivity over tropical regions. Agr. Forest Meteorol. 170, 89–102 (2012).

  32. 32.

    , , & Modelling the impacts of weather and climate variability on crop productivity over a large area: A new super-ensemble-based probabilistic projection. Agr. Forest Meteorol. 149, 1266–1278 (2009).

  33. 33.

    & Climate change, high-temperature stress, rice productivity, and water use in eastern china: A new superensemble-based probabilistic projection. J. Appl. Meteor. Climatol. 52, 531–551 (2013).

  34. 34.

    & Climate change, wheat productivity and water use in the North China Plain: A new super-ensemble-based probabilistic projection. Agric. Forest Meteorol. 170, 146–165 (2013).

  35. 35.

    , , & Projected temperature changes indicate significant increase in interannual variability of U.S. maize yields. Climatic Change 112, 525–533 (2012).

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The study was financially supported by the NERC EQUIP programme http://www.equip.leeds.ac.uk and the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS), with the financial assistance of the European Union, Canadian International Development Agency, World Bank, New Zealand Ministry of Foreign Affairs and Trade and Danida and with the technical support of IFAD. S. Hodkinson contributed to the data set. B. Parkes produced one supplementary figure.

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  1. School of Earth and Environment, University of Leeds, Leeds LS2 9AT, UK

    • A. J. Challinor
    • , J. Watson
    •  & D. R. Smith
  2. CGIAR Research Programme on Climate Change, Agriculture and Food Security (CCAFS), Cali, Columbia 6713, South America

    • A. J. Challinor
  3. Stanford University, 473 Via Ortega Stanford, California 94305, USA

    • D. B. Lobell
  4. CSIRO, GPO Box 1700 Canberra, Australian Capital Territory 2601, Australia

    • S. M. Howden
  5. Arizona State University, Consortium for Science, Policy, and Outcomes, PO Box 874401 Tempe, Arizona 85287-4401, USA

    • N. Chhetri


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All authors contributed to the data set, discussed the results and commented on the manuscript. J.W. analysed the data. D.R.S. and D.B.L. carried out the statistical analysis. A.C., D.L. and M.H. designed the study and wrote the paper.

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The authors declare no competing financial interests.

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Correspondence to A. J. Challinor or D. R. Smith.

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