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Nature Food
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Occurrence of crop pests and diseases has largely increased in China since 1970

Nature Foodvolume 3, pages57–65 (2022)Cite this article

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Abstract

Crop pests and diseases (CPDs) are emerging threats to global food security, but trends in the occurrence of pests and diseases remain largely unknown due to the lack of observations for major crop producers. Here, on the basis of a unique historical dataset with more than 5,500 statistical records, we found an increased occurrence of CPDs in every province of China, with the national average rate of CPD occurrence increasing by a factor of four (from 53% to 218%) during 1970–2016. Historical climate change is responsible for more than one-fifth of the observed increment of CPD occurrence (22% ± 17%), ranging from 2% to 79% in different provinces. Among the climatic factors considered, warmer nighttime temperatures contribute most to the increasing occurrence of CPDs (11% ± 9%). Projections of future CPDs show that at the end of this century, climate change will lead to an increase in CPD occurrence by 243% ± 110% under a low-emissions scenario (SSP126) and 460% ± 213% under a high-emissions scenario (SSP585), with the magnitude largely dependent on the impacts of warmer nighttime temperatures and decreasing frost days. This observation-based evidence highlights the urgent need to accurately account for the increasing risk of CPDs in mitigating the impacts of climate change on food production.

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Fig. 1: Spatial and temporal pattern ofOr.
Fig. 2: Occurrence of different CPDs from 1970 to 2016.
Fig. 3: Correlations between anomaly of potential driving factors and anomaly ofOr.
Fig. 4: Contribution of climate change to change ofOr from 1970 to 2016.
Fig. 5:Or projection from 2020 to 2100 under two scenarios.

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Data availability

The CRU TS 4.01 climate dataset is publicly available athttps://catalogue.ceda.ac.uk/uuid/58a8802721c94c66ae45c3baa4d814d0. Two future scenario datasets in CMIP6 are publicly available athttps://www.isimip.org/gettingstarted/input-data-bias-correction/. Agricultural data at the provincial scale is publicly open athttps://data.stats.gov.cn/english/. The CPD dataset is available athttps://doi.org/10.6084/m9.figshare.16866736.v2. Source data are provided with this paper.

Code availability

All data were processed using MATLAB v2018b. Most of statistical analysis was carried out in MATLAB v2018b. The Bayesian hierarchical analysis was carried out in R studio (based on R version 3.5.2) with the Open BUGS API. The figures were produced in Origin Pro 2020b and ArcGIS 10.7. Figure2 was produced with MATLAB code (https://www.mathworks.com/matlabcentral/fileexchange/45639-hexscatter-m). Other codes are available upon request.

Change history

  • 01 February 2023

    In the version of this article originally published, the name of Jay Ram Lamichhane in the Peer review acknowledgements was incomplete and has now been amended in the HTML and PDF versions of the article.

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Acknowledgements

This study was supported by the National Natural Science Foundation of China (42171096). We thank M. He, Q. Liu and L. Jin for their help in preparing the manuscript. T. Pugh acknowledges support from BECC and MERGE.

Author information

Authors and Affiliations

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

    Chenzhi Wang, Xuhui Wang, Ling Huang, Yuan Zhang & Shilong Piao

  2. Department of Bioproducts and Biosystems Engineering, University of Minnesota-Twin Cities, Minnesota-Twin, MN, USA

    Zhenong Jin

  3. Climate Resilience, Potsdam Institute for Climate Impact Research, Member of the Leibniz Association, Potsdam, Germany

    Christoph Müller

  4. Department of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden

    Thomas A. M. Pugh

  5. School of Geography, Earth and Environmental Science, University of Birmingham, Birmingham, UK

    Thomas A. M. Pugh

  6. Department of Biology and Graduate Degree Program in Ecology, Colorado State University, Fort Collins, CO, USA

    Anping Chen

  7. Key Laboratory of Alpine Ecology, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China

    Tao Wang & Shilong Piao

  8. Center for Excellence in Tibetan Earth Science, Chinese Academy of Sciences, Beijing, China

    Tao Wang & Shilong Piao

  9. Laboratoire de Météorologie Dynamique, Sorbonne Université, CNRS, IPSL, Paris, France

    Laurent X. Z. Li

Authors
  1. Chenzhi Wang
  2. Xuhui Wang
  3. Zhenong Jin
  4. Christoph Müller
  5. Thomas A. M. Pugh
  6. Anping Chen
  7. Tao Wang
  8. Ling Huang
  9. Yuan Zhang
  10. Laurent X. Z. Li
  11. Shilong Piao

Contributions

X.W. designed the study. C.W. collected data and performed analyses. C.W., X.W., Z.J., C.M. and S.P. wrote the manuscript. All authors contributed to the interpretation of the results and manuscript revisions.

Corresponding author

Correspondence toXuhui Wang.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review informationNature Food thanks Daniel Bebber, Nathaniel Newlands and Jay Ram Lamichhane for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Supplementary Figs. 1–17 and Tables 1–4.

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Source Data Fig. 5

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Wang, C., Wang, X., Jin, Z.et al. Occurrence of crop pests and diseases has largely increased in China since 1970.Nat Food3, 57–65 (2022). https://doi.org/10.1038/s43016-021-00428-0

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