Modeling Soybean Rust Spore Escape from Infected Canopies: Model Description and Preliminary Results

David Andrade Saint Louis University, St. Louis, Missouri

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Zaitao Pan Saint Louis University, St. Louis, Missouri

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William Dannevik Saint Louis University, St. Louis, Missouri

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Jeremy Zidek The Pennsylvania State University, State College, Pennsylvania

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Abstract

Asian soybean rust, caused by Phakopsora pachyrhizi, an airborne fungal pathogen, is an annual threat to U.S. soybean production. The disease is spread during the growing season by fungal spores that are transported from warm southern locations where they overwinter. Current models of long distance spore transport treat spore sources as constant emitters. However, evidence suggests that the spore escape rate depends on 1) the interaction between spores and turbulence within and above an infected canopy and 2) the filtering capacity of the canopy to trap upward-traveling spores. Accordingly, a theoretically motivated yet computationally simple forecast model for escape rate is proposed using a simple turbulence closure method and a parameterization of the canopy porosity. Preliminary escape-rate forecasts were made using the friction velocity, an estimate of initial spore concentrations inside an infected canopy, and the canopy’s leaf area distribution. Sensitivity tests were conducted to determine which biological and meteorological variables and parameters most impact modeled spore escape rates. The spore escape model was integrated with a large-scale spore transport model that was used to forecast spore deposition over U.S. soybean production regions. Preliminary results suggest that varying meteorological conditions significantly impact escape rates and the spread of the disease.

Corresponding author address: Zaitao Pan, Saint Louis University, 3642 Lindell Blvd., St. Louis, MO 63108. Email: panz@eas.slu.edu

Abstract

Asian soybean rust, caused by Phakopsora pachyrhizi, an airborne fungal pathogen, is an annual threat to U.S. soybean production. The disease is spread during the growing season by fungal spores that are transported from warm southern locations where they overwinter. Current models of long distance spore transport treat spore sources as constant emitters. However, evidence suggests that the spore escape rate depends on 1) the interaction between spores and turbulence within and above an infected canopy and 2) the filtering capacity of the canopy to trap upward-traveling spores. Accordingly, a theoretically motivated yet computationally simple forecast model for escape rate is proposed using a simple turbulence closure method and a parameterization of the canopy porosity. Preliminary escape-rate forecasts were made using the friction velocity, an estimate of initial spore concentrations inside an infected canopy, and the canopy’s leaf area distribution. Sensitivity tests were conducted to determine which biological and meteorological variables and parameters most impact modeled spore escape rates. The spore escape model was integrated with a large-scale spore transport model that was used to forecast spore deposition over U.S. soybean production regions. Preliminary results suggest that varying meteorological conditions significantly impact escape rates and the spread of the disease.

Corresponding author address: Zaitao Pan, Saint Louis University, 3642 Lindell Blvd., St. Louis, MO 63108. Email: panz@eas.slu.edu

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