Abstract

Plant diseases cause significant loss of valuable food crops throughout the world and are, in part, responsible for the suffering of 800 million who lack adequate food. Mathematical models of plant diseases can be used to assess the risk of pathogen introduction into new regions; guide disease detection efforts in the field with limited resources; and inform the design of optimal disease control strategies. Wind borne dispersal of pathogen inoculum is fundamental to the progress of many important plant diseases, such as wheat rust, citrus canker and sudden oak death. However, the physical transport of inoculum is either ignored in predictive models or included in an overly simplistic way involving the use of static, isotropic dispersal kernels. The aim of this work is two-fold:

(i) To challenge the current usage of overly-simplistic dispersal in predictive plant disease models by exposing the sensitivity of epidemic dynamics to the underlying pathogen dispersal mechanism.

(ii) To develop an improved paradigm of plant pathogen dispersal through the integration of sophisticated atmospheric dispersion models with a metapopulation epidemic model.

In this talk I will (a) present results from atmospheric dispersion simulations that demonstrate anisotropy and time-dependence of pathogen dispersal and (b) present metapopulation epidemic simulation results that quantify the link between dispersal mechanisms and epidemic dynamics.