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Influence of extreme weather disasters on global crop production


In recent years, several extreme weather disasters have partially or completely damaged regional crop production1,2,3,4,5. While detailed regional accounts of the effects of extreme weather disasters exist, the global scale effects of droughts, floods and extreme temperature on crop production are yet to be quantified. Here we estimate for the first time, to our knowledge, national cereal production losses across the globe resulting from reported extreme weather disasters during 1964–2007. We show that droughts and extreme heat significantly reduced national cereal production by 9–10%, whereas our analysis could not identify an effect from floods and extreme cold in the national data. Analysing the underlying processes, we find that production losses due to droughts were associated with a reduction in both harvested area and yields, whereas extreme heat mainly decreased cereal yields. Furthermore, the results highlight ~7% greater production damage from more recent droughts and 8–11% more damage in developed countries than in developing ones. Our findings may help to guide agricultural priorities in international disaster risk reduction and adaptation efforts.

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Figure 1: Influence of EWDs on national cereal production.
Figure 2: Influence of EWDs on national cereal yields and harvested area.
Figure 3: A regional analysis of the influence of drought.
Figure 4: The influence of drought and extreme heat on maize, rice and wheat.
Figure 5: A temporal analysis of the influence of drought.

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We thank R. Below, who is in charge of the EM-DAT project at the Centre for Research on the Epidemiology of Disasters, for sharing the data. We thank C. Champalle for testing the original idea using data over East Africa in a class project. This research was supported by a Discovery Grant from the Natural Science and Engineering Research Council of Canada to N.R.

Author information

Authors and Affiliations



This research was designed and coordinated by N.R. All authors performed analyses, discussed the results, and wrote the manuscript.

Corresponding author

Correspondence to Navin Ramankutty.

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Competing interests

The authors declare no competing financial interests.

Extended data figures and tables

Extended Data Figure 1 Distributions of individual responses to drought and extreme heat.

af, Histograms of disaster-year differences from means of 1,000 resampled controls for drought (n = 222) (ac) and extreme heat (n = 32) (df). A preponderance of moderately negative values (falling towards the right of the red shaded areas) underlies the negative mean disaster year signals, with a limited influence of extreme cases (those at the left of the red shaded areas).

Extended Data Figure 2 The influence of sample size on estimated disaster effects.

a, b, Estimated mean 16-cereal aggregated production deficit for extreme heat (a) and drought (b) in 200 sub-samples with size of (1, 2, …, n) (points). Dotted grey line shows the final estimated mean production deficit (9.1% for extreme heat, 10.1% for drought). Most of the initial variability at low sample sizes dissipates into the mean at well below the actual sample size (n = 39 for extreme heat, n = 247 for drought).

Extended Data Figure 3 Seasonal weather anomalies of drought and extreme heat disasters in EM-DAT.

ac, Normalized composite mean growing season temperature for extreme heat (n = 32) (a) and drought (n = 222) (b), and total precipitation for drought (c). Box plots depict the distributions of 1,000 false-disaster control composites, with red crosses denoting extreme outliers and red dashes denoting medians. Years with extreme heat correspond to seasonal temperature anomalies of 1.2 °C, while drought years have only 0.15 °C warmer temperatures, with no significant precipitation anomaly.

Extended Data Figure 4 Time series of the number of extreme heat and drought disasters per year from the EM-DAT database.

The EM-DAT database is based on a compilation of disaster reports gathered from various organizations including United Nations agencies, governments and the International Federation of Red Cross and Red Crescent Societies. The time series of reported disasters per year exhibits an increasing trend, probably the result of more complete disaster reporting in more recent decades with a possible contribution from increasing disaster incidence. There is also large inter-annual variability in the number of disasters.

Extended Data Table 1 Statistical significance of 16-cereal aggregate analysis
Extended Data Table 2 Sample sizes for individual crop and 16-cereal aggregate analyses
Extended Data Table 3 Statistical significance of regional analysis
Extended Data Table 4 Sample sizes for regional analysis
Extended Data Table 5 Statistical significance of individual crop analysis
Extended Data Table 6 Kruskal–Wallis assumptions test results for group comparison analyses

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Supplementary information

Supplementary Information

This file contains a Supplementary Discussion and additional references. We discuss the relative influence of larger and smaller EWD impacts, the effect of sample size, the implications of trends in the number of reported disasters per year, the application of comparative statistics and relevant assumptions, and the limitations of comparison to previous studies. (PDF 326 kb)

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Lesk, C., Rowhani, P. & Ramankutty, N. Influence of extreme weather disasters on global crop production. Nature 529, 84–87 (2016).

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