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Warming reduces global agricultural production by decreasing cropping frequency and yields

Nature Climate Change volume 12, pages 1016–1023 (2022)Cite this article

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Abstract

Annual food caloric production is the product of caloric yield, cropping frequency (CF, number of production seasons per year) and cropland area. Existing studies have largely focused on crop yield, whereas how CF responds to climate change remains poorly understood. Here, we evaluate the global climate sensitivity of caloric yields and CF at national scale. We find a robust negative association between warming and both caloric yield and CF. By the 2050s, projected CF increases in cold regions are offset by larger decreases in warm regions, resulting in a net global CF reduction (−4.2 ± 2.5% in high emission scenario), suggesting that climate-driven decline in CF will exacerbate crop production loss and not provide climate adaptation alone. Although irrigation is effective in offsetting the projected production loss, irrigation areas have to be expanded by >5% in warm regions to fully offset climate-induced production losses by the 2050s.

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Fig. 1: Changes in crop CalP, CF, CalY and cropland area during 1979–2018.
Fig. 2: Response of CF, CalY and CalP to temperature.
Fig. 3: Effect of warming and irrigation on CF, CalY and CalP.
Fig. 4: Projected changes in CF, CalY and CalP for 2031–2070 relative to the reference period 1979–2018.
Fig. 5: Projected irrigation area fraction to offset climate change-induced decline in CalP.

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Data availability

FAO national statistical data was obtained from http://www.fao.org/faostat/en/#data/QC. Agricultural TFP was obtained from the USDA ERS International Agricultural TFP dataset https://www.ers.usda.gov/data-products/international-agricultural-productivity/. The caloric conversion factor is based on the published dataset http://www.fao.org/docrep/003/X9892E/X9892e05.htm#P8217_125315. The bias-corrected climate model outputs are available at https://esg.pik-potsdam.de/search/isimip/.

Code availability

The scripts used to run the regression model are available through zenodo at: https://zenodo.org/record/7038556

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Acknowledgements

P.Z. and P.C. are supported by the CLAND project (grant no. 16-CONV-0003) and ISIPEDIA: The Open Inter-Sectoral Impacts Encyclopedia (grant no. ANR-17-ERA4-0006 - ISIPEDIA). D.M. is supported by the CLAND project (grant no. 16-CONV-0003) and meta-programme CLIMAE-INRAE. L.Y. is supported by Tsinghua University Initiative Scientific Research Programme (2021Z11GHX002, 20223080017). J.B. is supported by NSF/NIFA no. 1639318 INFEWS/T1. J.C. is supported by the National Key Research and Development Programme of China (2021YFE0114500). Q.X. is supported by National Key Research and Development Programme of China (grant no. 2017YFA0604300).

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Authors and Affiliations

  1. Laboratoire des Sciences du Climat et de l’Environnement, CEA CNRS UVSQ Orme des Merisiers, Gif-sur-Yvette, France

    Peng Zhu & Philippe Ciais

  2. Department of Geography, The University of Hong Kong, Hong Kong SAR, China

    Peng Zhu

  3. Guangdong Key Laboratory for Urbanization and Geo-simulation, School of Geography and Planning, Sun Yat-Sen University, Guangzhou, China

    Peng Zhu & Qinchuan Xin

  4. School of Global Policy and Strategy, University of California, San Diego, La Jolla, CA, USA

    Jennifer Burney

  5. College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, China

    Jinfeng Chang

  6. Department of Bioproducts and Biosystems Engineering, University of Minnesota, St. Paul, MN, USA

    Zhenong Jin

  7. Department of Ecosystem Science and Sustainability, Colorado State University, Fort Collins, CO, USA

    Nathaniel D. Mueller

  8. Department of Soil and Crop Sciences, Colorado State University, Fort Collins, CO, USA

    Nathaniel D. Mueller

  9. School of National Safety and Emergency Management, Beijing Normal University, Zhuhai, China

    Jialu Xu

  10. Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing, China

    Le Yu

  11. Ministry of Education Ecological Field Station for East Asian Migratory Birds, Beijing, China

    Le Yu

  12. Université Paris-Saclay, INRAE, AgroParisTech, UMR 518 MIA, Palaiseau, France

    David Makowski

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Contributions

P.Z. designed the study, performed the analysis and led the writing. J.B., J.C., Z.J., N. M., D.M. and P.C. helped the results interpretation. Q.X., J.X. and L.Y. provided additional data for comparison. All authors reviewed the manuscript and contributed to the manuscript writing.

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Correspondence to Peng Zhu.

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Zhu, P., Burney, J., Chang, J. et al. Warming reduces global agricultural production by decreasing cropping frequency and yields. Nat. Clim. Chang. 12, 1016–1023 (2022). https://doi.org/10.1038/s41558-022-01492-5

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