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Quantifying airborne dispersal routes of pathogens over continents to safeguard global wheat supply

Nature Plantsvolume 3pages780786 (2017) | Download Citation

Abstract

Infectious crop diseases spreading over large agricultural areas pose a threat to food security. Aggressive strains of the obligate pathogenic fungus Puccinia graminis f.sp. tritici (Pgt), causing the crop disease wheat stem rust, have been detected in East Africa and the Middle East, where they lead to substantial economic losses and threaten livelihoods of farmers. The majority of commercially grown wheat cultivars worldwide are susceptible to these emerging strains, which pose a risk to global wheat production, because the fungal spores transmitting the disease can be wind-dispersed over regions and even continents1,2,3,4,5,6,7,8,9,10,11. Targeted surveillance and control requires knowledge about airborne dispersal of pathogens, but the complex nature of long-distance dispersal poses significant challenges for quantitative research12,13,14. We combine international field surveys, global meteorological data, a Lagrangian dispersion model and high-performance computational resources to simulate a set of disease outbreak scenarios, tracing billions of stochastic trajectories of fungal spores over dynamically changing host and environmental landscapes for more than a decade. This provides the first quantitative assessment of spore transmission frequencies and amounts amongst all wheat producing countries in Southern/East Africa, the Middle East and Central/South Asia. We identify zones of high air-borne connectivity that geographically correspond with previously postulated wheat rust epidemiological zones (characterized by endemic disease and free movement of inoculum)10,15, and regions with genetic similarities in related pathogen populations16,17. We quantify the circumstances (routes, timing, outbreak sizes) under which virulent pathogen strains such as ‘Ug99’5,6 pose a threat from long-distance dispersal out of East Africa to the large wheat producing areas in Pakistan and India. Long-term mean spore dispersal trends (predominant direction, frequencies, amounts) are summarized for all countries in the domain (Supplementary Data). Our mechanistic modelling framework can be applied to other geographic areas, adapted for other pathogens and used to provide risk assessments in real-time3.

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Acknowledgements

The authors are very grateful for financial support from the Bill & Melinda Gates Foundation, BBSRC, Friedrich-Ebert-Stiftung and DFID, UK. We thank all in-country field scientists who have contributed information on wheat cropping patterns and disease surveys. We acknowledge very useful discussion and support from members of the Epidemiology & Modelling Group in Cambridge.

Author information

Affiliations

  1. Epidemiology and Modelling Group, Department of Plant Sciences, University of Cambridge, Cambridge, CB2 3EA, UK

    • M. Meyer
    • , J. A. Cox
    • , M. D. T. Hitchings
    •  & C. A. Gilligan
  2. Atmospheric Dispersion and Air Quality (ADAQ), Met Office, Exeter, EX1 3PB, UK

    • L. Burgin
    •  & M. C. Hort
  3. International Maize and Wheat Improvement Center (CIMMYT), PO Box 5689, Addis Ababa, Ethiopia

    • D. P. Hodson

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Contributions

C.A.G. conceived the original project and modelling approach. M.M., J.A.C. and M.D.T.H. developed, tested and implemented the modelling framework, and performed the simulations and data-analysis in close collaboration with L.B. and M.C.H. and other members of the Epidemiology & Modelling Group in Cambridge. D.P.H. provided field survey data and wheat rust expertise and contacted international surveillance experts. M.M. wrote the manuscript and created the figures in collaboration with other authors. L.B., D.P.H. and C.A.G supervised the project.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to M. Meyer or C. A. Gilligan.

Electronic supplementary material

  1. Supplementary Information

    Supplementary Figures 1–11; Supplementary Tables 1–4; Supplementary Methods; Supplementary Notes.

  2. Life sciences reporting summary

    Life sciences reporting summary

  3. Supplementary Data 1

    Seasonal Pgt spore dispersal trends from key wheat stem rust disease locations in Southern/East Africa, the Middle East and Central/South Asia.

  4. Supplementary Data 2

    Pgt spore dispersal frequencies and amounts amongst wheat producing countries in Southern/East Africa, the Middle East and Central/South Asia.

  5. Supplementary Video 1

    Main wheat stem rust seasons in countries in Southern/East Africa, the Middle East and Central/South Asia.

  6. Supplementary Video 2

    3D animation of atmospheric dispersal simulations of Pgt spores.

  7. Supplementary Video 3

    Time-lapse of daily Pgt spore deposition patterns resulting from daily simulation of spore release from the Bale Zone, Ethiopia, during the main wheat season of 2014.

  8. Supplementary Video 4

    Time-lapse of hourly meteorological surface fields (relative humidity) used to drive the environmental suitability calculations.

  9. Supplementary Video 5

    Time-lapse of the daily binary environmental suitability score obtained from the environmental suitability.

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DOI

https://doi.org/10.1038/s41477-017-0017-5