Letter

Plausible rice yield losses under future climate warming

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Published online:

Abstract

Rice is the staple food for more than 50% of the world's population1,​2,​3. Reliable prediction of changes in rice yield is thus central for maintaining global food security. This is an extraordinary challenge. Here, we compare the sensitivity of rice yield to temperature increase derived from field warming experiments and three modelling approaches: statistical models, local crop models and global gridded crop models. Field warming experiments produce a substantial rice yield loss under warming, with an average temperature sensitivity of −5.2 ± 1.4% K−1. Local crop models give a similar sensitivity (−6.3 ± 0.4% K−1), but statistical and global gridded crop models both suggest less negative impacts of warming on yields (−0.8 ± 0.3% and −2.4 ± 3.7% K−1, respectively). Using data from field warming experiments, we further propose a conditional probability approach to constrain the large range of global gridded crop model results for the future yield changes in response to warming by the end of the century (from −1.3% to −9.3% K−1). The constraint implies a more negative response to warming (−8.3 ± 1.4% K−1) and reduces the spread of the model ensemble by 33%. This yield reduction exceeds that estimated by the International Food Policy Research Institute assessment (−4.2 to −6.4% K−1) (ref. 4). Our study suggests that without CO2 fertilization, effective adaptation and genetic improvement, severe rice yield losses are plausible under intensive climate warming scenarios.

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Author information

Affiliations

  1. Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China

    • Chuang Zhao
    • , Shilong Piao
    • , Xuhui Wang
    • , Mengtian Huang
    • , Xu Lian
    • , Yongwen Liu
    • , Shushi Peng
    •  & Zhenzhong Zeng
  2. Key Laboratory of Alpine Ecology and Biodiversity, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100085, China

    • Shilong Piao
    •  & Tao Wang
  3. Center for Excellence in Tibetan Earth Science, Chinese Academy of Sciences, Beijing 100085, China

    • Shilong Piao
    •  & Tao Wang
  4. State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China

    • Yao Huang
  5. Laboratoire des Sciences du Climat et de l'Environnement, CEA-CNRS-UVSQ, Gif-sur-Yvette 91191, France

    • Philippe Ciais
  6. University of Chicago Computation Institute, Chicago, Illinois 60637, USA

    • Joshua Elliott
  7. Department of Biology, University of Antwerp, Universiteitsplein 1, 2610 Wilrijk, Belgium

    • Ivan A. Janssens
  8. International Rice Research Institute, Los Baños, 4031 Laguna, Philippines

    • Tao Li
  9. Potsdam Institute for Climate Impact Research, 14473 Potsdam, Germany

    • Christoph Müller
  10. CREAF, Cerdanyola del Valles, Barcelona 08193, Catalonia, Spain

    • Josep Peñuelas
  11. CSIC, Global Ecology Unit CREAF-CEAB-CSIC-UAB, Cerdanyola del Valles, Barcelona 08193, Catalonia, Spain

    • Josep Peñuelas

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Contributions

S. Piao designed the research, C.Z. performed the analysis and all authors contributed to the interpretation of the results and the writing of the paper.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Shilong Piao.

Supplementary information

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  1. 1.

    Supplementary Information

    Supplementary Methods, Supplementary References, Supplementary Figures 1-12, Supplementary Table 1, Appendix 1-3.