Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Letter
  • Published:

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

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.

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Airborne dispersal routes of Pgt-spores causing wheat stem rust.
Fig. 2: Risk of atmospheric transmission of Pgt-spores to South Asia.
Fig. 3: The Rift Valley Pgt-spore incursion pathway.

Similar content being viewed by others

References

  1. Hovmøller, M. S., Walter, S. & Justesen, A. F. Escalating threat of wheat rusts. Science 329, 369 (2010).

    Article  PubMed  Google Scholar 

  2. Stokstad, E. Deadly wheat fungus threatens world’s breadbaskets. Science 315, 1786–1787 (2007).

    Article  CAS  PubMed  Google Scholar 

  3. Bhattacharya, S. Deadly new wheat disease threatens Europe’s crops. Nat. News 542, 145–146 (2017).

  4. Pardey, P. G. et al. Right-sizing stem-rust research. Science 340, 147–148 (2013).

    Article  CAS  PubMed  Google Scholar 

  5. Singh, R. P. et al. Emergence and spread of new races of wheat stem rust fungus: continued threat to food security and prospects of genetic control. Phytopathology 105, 872–884 (2015).

    Article  Google Scholar 

  6. Singh, R. P. et al. The emergence of Ug99 races of the stem rust fungus is a threat to world wheat production. Annu. Rev. Phytopathol. 49, 465–481 (2011).

    Article  CAS  PubMed  Google Scholar 

  7. Singh, R. P. et al. Will stem rust destroy the world’s wheat crop? Adv. Agron. 28, 271–309 (2008).

    Article  Google Scholar 

  8. Singh, R. P. et al. Current status, likely migration and strategies to mitigate the threat to wheat production from race Ug99 (TTKS) of stem rust pathogen. CAB Rev. Perspect. Agric. Vet. Sci. Nutr. Nat. Resour. 1, 13 (2006).

    Google Scholar 

  9. Nagarajan, S., Kogel, K. H. & Zadoks, J. C. Epidemiological analysis of the damage potential of Pgt-Ug99 in Central East, North East Africa; Iran and Punjab (India). Indian Phytopathol. 67, 26–32 (2014).

    Google Scholar 

  10. Nagarajan, S. Is Puccinia graminis f. sp. tritici - virulence Ug99 a threat to wheat production in the north west plain zone of India? Indian Phytopathol. 65, 219–226 (2012).

    Google Scholar 

  11. Roelfs, A. P., Singh, R. P. & Saari, E. E. (eds) Rust Diseases of Wheat: Concepts and Methods of Disease Management (CIMMYT – International Maize and Wheat Improvement Center,  Mexico D.F., 1992).

  12. Brown, J. K. M. & Hovmøller, M. S. Aerial dispersal of pathogens on the global and continental scales and its impact on plant disease. Science 297, 537–541 (2002).

    Article  CAS  PubMed  Google Scholar 

  13. Nathan, R. et al. Mechanisms of long-distance dispersal of seeds by wind. Nature 418, 409–413 (2002).

    Article  CAS  PubMed  Google Scholar 

  14. Nathan, R. Long-distance dispersal of plants. Science 313, 786–788 (2006).

    Article  CAS  PubMed  Google Scholar 

  15. Saari, E. E. & Prescott, J. M. in The Cereal Rusts: Diseases, Distribution, Epidemiology, and Control (eds Roelfs, A. P. & Bushnell, W. R.) Ch. 9 (Academic Press, Orlando, London, 1985).

    Google Scholar 

  16. Terefe, T. G., Visser, B. & Pretorius, Z. A. Variation in Puccinia graminis f. sp. tritici detected on wheat and triticale in South Africa from 2009 to 2013. Crop Prot. 86, 9–16 (2016).

    Article  Google Scholar 

  17. Pretorius, Z. A. et al. Races of Puccinia triticina detected on wheat in Zimbabwe, Zambia and Malawi and regional germplasm responses. Australas. Plant Pathol. 44, 217–224 (2015).

    Article  Google Scholar 

  18. You, L., Wood-Sichra, U., Fritz, S. & See, L. Spatial production allocation model 2005 v2.0 (2005); http://mapspam.info/.

  19. RustTracker: A Global Wheat Rust Monitoring System (CIMMYT, 2017); http://rusttracker.cimmyt.org/.

  20. Jones, A. R., Thomson, D. J., Hort, M., Devenish, B. in Air Pollution Modeling And Its Application XVII (eds Borrego, C. & Norman, A.-L.) Ch. 62 (Springer, New York, 2007).

  21. Olivera, P. et al. Phenotypic and genotypic characterization of race TKTTF of Puccinia graminis f. sp. tritici that caused a wheat stem rust epidemic in southern Ethiopia in 2013/14. Phytopathology 105, 917–928 (2015).

    Article  Google Scholar 

  22. Walters, D. et al. The Met Office Unified Model Global Atmosphere 6.0/6.1 and JULES Global Land 6.0/6.1 configurations. Geosci. Model Dev. 10, 1487–1520 (2017).

    Article  Google Scholar 

  23. Rosvall, M. & Bergstrom, C. T. Maps of random walks on complex networks reveal community structure. Proc. Natl Acad. Sci. USA 105, 1118–1123 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Ali, S. et al. Origin, migration routes and worldwide population genetic structure of the wheat yellow rust pathogen Puccinia striiformis f.sp. tritici. PLoS Pathog. 10, e1003903 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  25. Nagarajan, S., Singh, H., Joshi, L. M. & Singh, E. E. Meteorological conditions associated with long-distance dissemination and deposition of Puccinia graminis tritici uredospores in India. Phytopathology 66, 198–203 (1976).

    Article  Google Scholar 

  26. GIEWS Country Briefs (FAO, 2016); http://www.fao.org/giews/countrybrief/.

  27. Draxler, R. et al. World Meteorological Organization’s model simulations of the radionuclide dispersion and deposition from the Fukushima Daiichi nuclear power plant accident. J. Environ. Radioact. 139, 172–184 (2015).

    Article  CAS  PubMed  Google Scholar 

  28. Webster, H. N. et al. Operational prediction of ash concentrations in the distal volcanic cloud from the 2010 Eyjafjallajökull eruption. J. Geophys. Res. Atmospheres 117, 1–17 (2012).

    Article  Google Scholar 

  29. Wang, H., Yang, X. B. & Ma, Z. Long-distance spore transport of wheat stripe rust pathogen from Sichuan, Yunnan, and Guizhou in southwestern China. Plant Dis. 94, 873–880 (2010).

    Article  Google Scholar 

  30. Isard, S. A., Gage, S. H., Comtois, P. & Russo, J. M. Principles of the atmospheric pathway for invasive species applied to soybean rust. BioScience 55, 851–861 (2005).

    Article  Google Scholar 

  31. Aylor, D. E. Spread of plant disease on a continental scale: role of aerial dispersal of pathogens. Ecology 84, 1989–1997 (2003).

    Article  Google Scholar 

  32. Roelfs, A. P. Gradients in horizontal dispersal of cereal rust uredospores. Phytopathology 62, 70–76 (1972).

    Article  Google Scholar 

  33. Aylor, D. E. & Taylor, G. S. Escape of Peronospora tabacina spores from a field of diseased tobacco plants. Phytopathology, 73, 525–529 (1983).

    Article  Google Scholar 

  34. Isard, S. A., Russo, J. M. & Ariatti, A. The Integrated Aerobiology Modeling System applied to the spread of soybean rust into the Ohio River valley during September 2006. Aerobiologia 23, 271–282 (2007).

    Article  Google Scholar 

  35. Aylor, D. E. A framework for examining inter-regional aerial transport of fungal spores. Agric. For. Meteorol. 38, 263–288 (1986).

    Article  Google Scholar 

  36. Aylor, D. E., Schmale, D. G., Shields, E. J., Newcomb, M. & Nappo, C. J. Tracking the potato late blight pathogen in the atmosphere using unmanned aerial vehicles and Lagrangian modeling. Agric. For. Meteorol. 151, 251–260 (2011).

    Article  Google Scholar 

  37. Prussin, A. J., Szanyi, N. A., Welling, P. I., Ross, S. D. & Schmale, D. G. Estimating the production and release of ascospores from a field-scale source of Fusarium graminearum inoculum. Plant Dis. 98, 497–503 (2014).

    Article  Google Scholar 

  38. Maddison, A. C. & Manners, J. G. Sunlight and viability of cereal rust uredospores. Trans. Br. mycol. Soc. 59, 429–443 (1972).

    Article  Google Scholar 

  39. Kim, K. S. & Beresford, R. M. Use of a spectrum model and satellite cloud data in the simulation of wheat stripe rust (Puccinia striiformis) dispersal across the Tasman Sea in 1980. Agric. For. Meteorol. 148, 1374–1382 (2008).

    Article  Google Scholar 

  40. de Vallavieille-Pope, C., Huber, L., Leconte, M. & Goyeau, H. Comparative effects of temperature and interrupted wet periods on germination, penetration, and infection of Puccinia recondita f. sp. tritici and P. striiformis on wheat seedlings. Phytopathology 85, 409–415 (1995).

    Article  Google Scholar 

  41. Magarey, R. D., Sutton, T. B. & Thayer, C. L. A simple generic infection model for foliar fungal plant pathogens. Phytopathology 95,92–100 (2005).

    Article  CAS  Google Scholar 

  42. Pfender, W. F. Prediction of stem rust infection favorability, by means of degree-hour wetness duration, for perennial ryegrass seed crops. Phytopathology 93, 467–477 (2003).

    Article  CAS  Google Scholar 

  43. Tollenaar, H. Uredospore germination and development of some cereal rusts from south-central Chile at constant temperatures. J. Phytopathol. 114, 118–125 (1985).

    Article  Google Scholar 

  44. Sentelhas, P. C. et al. Suitability of relative humidity as an estimator of leaf wetness duration. Agric. For. Meteorol. 148, 392–400 (2008).

    Article  Google Scholar 

Download references

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

Authors and Affiliations

Authors

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.

Corresponding authors

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

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Additional information

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

Electronic supplementary material

Supplementary Information

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

Life sciences reporting summary

Life sciences reporting summary

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.

Supplementary Data 2

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

Supplementary Video 1

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

Supplementary Video 2

3D animation of atmospheric dispersal simulations of Pgt spores.

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.

Supplementary Video 4

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

Supplementary Video 5

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

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Meyer, M., Cox, J.A., Hitchings, M.D.T. et al. Quantifying airborne dispersal routes of pathogens over continents to safeguard global wheat supply. Nature Plants 3, 780–786 (2017). https://doi.org/10.1038/s41477-017-0017-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

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

This article is cited by

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing