
Long-Term Prediction of Soybean Rust Entry into the Continental United States
Author(s) -
Zaitao Pan,
X. B. Yang,
Shimon Pivonia,
Lulin Xue,
Robert W. Pasken,
John O. Roads
Publication year - 2006
Publication title -
plant disease
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.663
H-Index - 108
eISSN - 1943-7692
pISSN - 0191-2917
DOI - 10.1094/pd-90-0840
Subject(s) - biological dispersal , phakopsora pachyrhizi , soybean rust , biology , dispersion (optics) , environmental science , ecology , atmospheric sciences , climatology , botany , geology , demography , physics , population , sociology , optics , fungicide
This special report demonstrates the feasibility of long-term prediction of intercontinental dispersal of Phakopsora pachyrhizi spores, the causal agent of the devastating Asian soybean rust (SBR) that invaded the continental United States in 2004. The climate-dispersion integrated model system used for the prediction is the combination of the particle transport and dispersion model (HYSPLIT_4) with the regional climate prediction model (MM5). The integrated model system predicts the trajectory and concentration of P. pachyrhizi spores based on three-dimensional wind advection and turbulent transport while incorporating simple viability criteria for aerial spores. The weather input of the model system is from a seasonal global climate prediction. The spore source strength and distribution were estimated from detected SBR disease severity and spread. The model system was applied to the known P. pachyrhizi spore dispersal between and within continents while focusing on the disease entry into the United States. Prediction validation using confirmed disease activity demonstrated that the model predicted the 2004 U.S. entry months in advance and reasonably forecast disease spread from the south coast states in the 2005 growing season. The model also simulated the dispersal from Africa to South America and from southern South America to Columbia across the equator. These validations indicate that the integrated model system, when furnished with detailed source distribution, can be a useful tool for P. pachyrhizi and possibly other airborne pathogen prediction.