IDEAS home Printed from https://ideas.repec.org/a/nat/natcli/v3y2013i10d10.1038_nclimate1945.html
   My bibliography  Save this article

Prediction of seasonal climate-induced variations in global food production

Author

Listed:
  • Toshichika Iizumi

    (National Institute for Agro-Environmental Sciences)

  • Hirofumi Sakuma

    (Research Institute for Global Change, Yokohama Institute for Earth Sciences
    Application Laboratory, Yokohama Institute for Earth Sciences)

  • Masayuki Yokozawa

    (National Institute for Agro-Environmental Sciences)

  • Jing-Jia Luo

    (Centre for Australian Weather and Climate Research, Bureau of Meteorology)

  • Andrew J. Challinor

    (Institute for Climate and Atmospheric Science, School of Earth and Environment, University of Leeds
    CGIAR-ESSP Program on Climate Change, Agriculture and Food Security (CCAFS), Faculty of Science, University of Copenhagen)

  • Molly E. Brown

    (Biospheric Sciences Branch, NASA Goddard Space Flight Center)

  • Gen Sakurai

    (National Institute for Agro-Environmental Sciences)

  • Toshio Yamagata

    (Application Laboratory, Yokohama Institute for Earth Sciences)

Abstract

Increasing volatility in food markets and the rising incidence of climatic extremes could lead to more frequent spikes in food prices. A global assessment of the reliability of crop simulations in reproducing past failures in major crop types suggests that seasonal forecasts can be useful for monitoring global food production.

Suggested Citation

  • Toshichika Iizumi & Hirofumi Sakuma & Masayuki Yokozawa & Jing-Jia Luo & Andrew J. Challinor & Molly E. Brown & Gen Sakurai & Toshio Yamagata, 2013. "Prediction of seasonal climate-induced variations in global food production," Nature Climate Change, Nature, vol. 3(10), pages 904-908, October.
    • Handle: RePEc:nat:natcli:v:3:y:2013:i:10:d:10.1038_nclimate1945
    DOI: 10.1038/nclimate1945
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/nclimate1945
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1038/nclimate1945?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Toreti, A. & Maiorano, A. & De Sanctis, G. & Webber, H. & Ruane, A.C. & Fumagalli, D. & Ceglar, A. & Niemeyer, S. & Zampieri, M., 2019. "Using reanalysis in crop monitoring and forecasting systems," Agricultural Systems, Elsevier, vol. 168(C), pages 144-153.
    2. Cao, Juan & Zhang, Zhao & Tao, Fulu & Chen, Yi & Luo, Xiangzhong & Xie, Jun, 2023. "Forecasting global crop yields based on El Nino Southern Oscillation early signals," Agricultural Systems, Elsevier, vol. 205(C).
    3. Phong V. V. Le & James T. Randerson & Rebecca Willett & Stephen Wright & Padhraic Smyth & Clément Guilloteau & Antonios Mamalakis & Efi Foufoula-Georgiou, 2023. "Climate-driven changes in the predictability of seasonal precipitation," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    4. Nazan An & Mustafa Tufan Turp & Murat Türkeş & Mehmet Levent Kurnaz, 2020. "Mid-Term Impact of Climate Change on Hazelnut Yield," Agriculture, MDPI, vol. 10(5), pages 1-20, May.
    5. Anwar, Muhuddin Rajin & Liu, De Li & Farquharson, Robert & Macadam, Ian & Abadi, Amir & Finlayson, John & Wang, Bin & Ramilan, Thiagarajah, 2015. "Climate change impacts on phenology and yields of five broadacre crops at four climatologically distinct locations in Australia," Agricultural Systems, Elsevier, vol. 132(C), pages 133-144.
    6. Kung, Chih-Chun & Cao, Xiaoyong & Choi, Yongrok & Kung, Shan-Shan, 2019. "A stochastic analysis of cropland utilization and resource allocation under climate change," Technological Forecasting and Social Change, Elsevier, vol. 148(C).
    7. Kung, Chih-Chun, 2019. "A stochastic evaluation of economic and environmental effects of Taiwan's biofuel development under climate change," Energy, Elsevier, vol. 167(C), pages 1051-1064.
    8. Erin Coughlan de Perez & Maarten van Aalst & Richard Choularton & Bart van den Hurk & Simon Mason & Hannah Nissan & Saroja Schwager, 2019. "From rain to famine: assessing the utility of rainfall observations and seasonal forecasts to anticipate food insecurity in East Africa," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 11(1), pages 57-68, February.
    9. Qing Sun & Yi Zhang & Xianghong Che & Sining Chen & Qing Ying & Xiaohui Zheng & Aixia Feng, 2022. "Coupling Process-Based Crop Model and Extreme Climate Indicators with Machine Learning Can Improve the Predictions and Reduce Uncertainties of Global Soybean Yields," Agriculture, MDPI, vol. 12(11), pages 1-15, October.
    10. Kung, Chih-Chun & Wu, Tao, 2021. "Influence of water allocation on bioenergy production under climate change: A stochastic mathematical programming approach," Energy, Elsevier, vol. 231(C).
    11. Nazan An & M Tufan Turp & M Tufan Turp & Murat Türkeş & M Levent Kurnaz & Murat Türkeş & M Levent Kurnaz, 2020. "Climate Change Effects on Agricultural Production- A Short Review," Current Investigations in Agriculture and Current Research, Lupine Publishers, LLC, vol. 8(3), pages 1097-1099, March.
    12. Saeed Nosratabadi & Sina Ardabili & Zoltan Lakner & Csaba Mako & Amir Mosavi, 2021. "Prediction of Food Production Using Machine Learning Algorithms of Multilayer Perceptron and ANFIS," Agriculture, MDPI, vol. 11(5), pages 1-13, May.
    13. Kukal, M.S. & Irmak, S., 2020. "Impact of irrigation on interannual variability in United States agricultural productivity," Agricultural Water Management, Elsevier, vol. 234(C).
    14. Dana Cordell & Elsa Dominish & Mohamed Esham & Brent Jacobs & Madhuri Nanda, 2021. "Adapting food systems to the twin challenges of phosphorus and climate vulnerability: the case of Sri Lanka," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 13(2), pages 477-492, April.
    15. Saeed Nosratabadi & Sina Ardabili & Zoltan Lakner & Csaba Mako & Amir Mosavi, 2021. "Prediction of Food Production Using Machine Learning Algorithms of Multilayer Perceptron and ANFIS," Papers 2104.14286, arXiv.org.
    16. Kim, Daeha & Chun, Jong Ahn & Inthavong, Thavone, 2021. "Managing climate risks in a nutrient-deficient paddy rice field using seasonal climate forecasts and AquaCrop," Agricultural Water Management, Elsevier, vol. 256(C).
    17. Villoria, Nelson B. & Delgado, Michael, 2017. "Worldwide Crop Supply Responses to El Niño Southern Oscillation," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258564, Agricultural and Applied Economics Association.
    18. García-León, David & Contreras, Sergio & Hunink, Johannes, 2019. "Comparison of meteorological and satellite-based drought indices as yield predictors of Spanish cereals," Agricultural Water Management, Elsevier, vol. 213(C), pages 388-396.
    19. Akinmutimi Al & Ukonu A, 2020. "Comparative Effects of Wood Ash and Poultry Manure on Soil Ph and Potassium Release from an Acid Ultisol in Umudike, Abia State, Nigeria," Current Investigations in Agriculture and Current Research, Lupine Publishers, LLC, vol. 8(2), pages 1063-1068, February.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcli:v:3:y:2013:i:10:d:10.1038_nclimate1945. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.