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US Soybean Rust Detection and Aerobiological Modeling November, 2004

US Soybean Rust Detection and Aerobiological Modeling November, 2004. Dan Borchert, Glenn Fowler and Roger Magarey (USDA-APHIS-PPQ-CPHST-PERAL) Daryl Jewett (USDA-APHIS) Annalisa Ariatti (UIUC) Scott Isard (PSU) Manuel Colunga and Stewart Gage (MSU)

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US Soybean Rust Detection and Aerobiological Modeling November, 2004

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  1. US Soybean Rust Detectionand Aerobiological ModelingNovember, 2004 Dan Borchert, Glenn Fowler and Roger Magarey (USDA-APHIS-PPQ-CPHST-PERAL) Daryl Jewett (USDA-APHIS) Annalisa Ariatti (UIUC) Scott Isard (PSU) Manuel Colunga and Stewart Gage (MSU) Glenn Hartman and Monte Miles (ARS and NSRL) Thomas Keever and Charlie Main (NCSU) Jeff Grimm, Aaron Hunt and Joe Russo (ZedX, Inc.)

  2. Methods • The Integrated Aerobiology Modeling System (IAMS) was used to simulate daily soybean rust spore movement (Isard et al., 2004) • Viable spore deposition (logarithmic) is modeled from September 15 to 19, 2004 in association with Hurricane Ivan • Uncertainty is associated with spore source strength and the absolute quantity of spores

  3. Aerobiological Model Assumptions • Source area (17,000 sq Km) was from soybean production areas in northwestern South America • Spores were released near midday from August 30 to September 9, 2004 • 25% of the source area was infested with soybean rust • 6 million spores were released per day per heavily infected soybean plant with a planting density of 500,000 plants/ha • 33% of these spores were released near midday • 15% of the released spores were able to escape from the canopy • Mortality due to UVB radiation exposure in the air was proportional to cloud-adjusted surface total incoming solar radiation • Wet deposition of viable spores was proportional to the observed surface precipitation total

  4. Computational Procedure • Model domain was divided into 14 km2 grid cells • NWS reanalysis 2 dataset was used to calculate the most likely downwind direction for 6 pressure levels (altitudes) at 6 hr intervals • Spores were moved up or down among pressure levels in accordance to the vertical component of the wind • Mortality due to UV exposure and rainout of spores was calculated for each time step after downwind movement • Deposition of spores was accumulated for all days in the calculations and is given as the number of spores per hectare

  5. US Planted Soybean Acreage per County

  6. September 15, 2004

  7. September 16, 2004

  8. September 17, 2004

  9. September 18, 2004

  10. September 19, 2004

  11. Planted Soybean Acreage per County

  12. Kudzu Area per County

  13. Soybean Rust Spore Deposition

  14. Soybean Rust Spore Deposition and Planted Soybean Acreage per County

  15. Soybean Rust Spore Deposition and Kudzu Area per County

  16. Data Sources • Kudzu: Raw data Daryl Jewett (USDA-APHIS) unpublished data. Kudzu map Annalisa Ariatti and Scott Isard (PSU/UIUC). • Soybean Acreage: NASS, 2003; National Land Cover Data, 1992; Colunga, 2004 • Spore Deposition: Isard, S., Main, C., Keever, T., Magarey, R., Redlin, S, and Russo, J. (2004) Weather-Based Assessment of Soybean Rust Threat to North America. Final Report to APHIS http://www.aphis.usda.gov/ppq/ep/soybean_rust/

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