Network models for soybean rust epidemics: Adapting to aerially-dispersed pathogens

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People

PIs: Shawn Hutchinson (geography) , Karen Garrett (Agric); co-PI: Caterina Scoglio (ECE); student: Sweta Sutrave (ECE).

Abstract

Modeling plant disease epidemics at large scales calls for several adaptations of network models. For example, information about soybean rust is typically available from sentinel plots that function to represent a larger area such as a county. Furthermore, many plant pathogens are capable of long-distance aerial dispersal, so that distant nodes may be connected with a small but non-zero probability. We have already begun developing network models to forecast soybean rust in the US using the sentinel plot data for model construction and validation.

Presentations & Publications

- Sueta Sutrave, Karen Garrett, Phillip Schumm, Caterina Scoglio “Analysis of Soybean Rust Epidemics Using Complex Network Models” Work in progress.

- Margaret Margosian, Karen Garrett, Shawn Hutchinson, and Kimberly With. 2008. Connectivity of the American agricultural landscape: Assessing the national risk of crop pest and disease spread. BioScience. In press.

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