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Prediction of seasonal climate-induced variations in global food production

Abstract

Consumers, including the poor in many countries, are increasingly dependent on food imports1 and are thus exposed to variations in yields, production and export prices in the major food-producing regions of the world. National governments and commercial entities are therefore paying increased attention to the cropping forecasts of important food-exporting countries as well as to their own domestic food production. Given the increased volatility of food markets and the rising incidence of climatic extremes affecting food production, food price spikes may increase in prevalence in future years2,3,4. Here we present a global assessment of the reliability of crop failure hindcasts for major crops at two lead times derived by linking ensemble seasonal climatic forecasts with statistical crop models. We found that moderate-to-marked yield loss over a substantial percentage (26–33%) of the harvested area of these crops is reliably predictable if climatic forecasts are near perfect. However, only rice and wheat production are reliably predictable at three months before the harvest using within-season hindcasts. The reliabilities of estimates varied substantially by crop—rice and wheat yields were the most predictable, followed by soybean and maize. The reasons for variation in the reliability of the estimates included the differences in crop sensitivity to the climate and the technology used by the crop-producing regions. Our findings reveal that the use of seasonal climatic forecasts to predict crop failures will be useful for monitoring global food production and will encourage the adaptation of food systems toclimatic extremes.

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Figure 1: Timing of cropping predictions.
Figure 2: The upper limits of reliability when moderate-to-marked yield losses of maize, soybean, rice and wheat were hindcasted using reanalysis data.
Figure 3: The reliability of the within-season hindcasts of the moderate-to-marked (5% more) yield losses for maize, soybean, rice and wheat.
Figure 4: The dominant climatic factors affecting the year-to-year variations in the yields of maize, soybean, rice and wheat.
Figure 5: The capture reliability of the year-to-year relative wheat yield variations (ΔY) for the reliable areas in four major wheat-exporting countries (the USA, France, Canada and Australia).

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Acknowledgements

We thank R. C. Stone, P. McIntosh, H. Kanamaru and M. Otsuka for helpful comments on the earlier version of this manuscript. T.I. was supported by the Japan Society for the Promotion of Science (JSPS) Grant-in-Aid for Research Activity Start-up (23880030). T.I, M.Y. and G.S. were supported by the Environment Research and Technology Development Fund (S-10-2) of the Ministry of the Environment, Japan. The Science and Innovation Section of the British Embassy in Tokyo provided us with the opportunity to conduct this study through a UK–Japan workshop arrangement.

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T.I. was responsible for the study design, data analysis and manuscript preparation. J-J.L. contributed seasonal climatic forecasting and assisted in manuscript preparation. G.S. provided the computational code used to optimize the crop yield modelling. H.S., M.Y., A.J.C., M.E.B and T.Y. assisted with the study design and helped write the manuscript.

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Correspondence to Toshichika Iizumi.

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The authors declare no competing financial interests.

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Iizumi, T., Sakuma, H., Yokozawa, M. et al. Prediction of seasonal climate-induced variations in global food production. Nature Clim Change 3, 904–908 (2013). https://doi.org/10.1038/nclimate1945

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