This project will develop a range of computational models that can be used for testing various strategies relating to surveillance and management of fungal pathogens that undergo aerial dispersal. The research will also explore the effectiveness and feasibility of ongoing surveillance for the arrival of novel fungal pathogens in the Western Australian wheat belt and the effect of resistant cultivar selection on the genetic structure of fungal meta-populations. Finally the project will identify optimal strategies for the regional management of resistant cultivars.

What is the biosecurity problem?

A number of fungal plant pathogens of interest to biosecurity agencies undergo wind-assisted dispersal. This mode of transport allows pathogens to spread quickly and easily, and can result in rapid occurrence of multiple site infections. Deployment of resistant cultivars can be effective in controlling the spread of disease, however careful management is required to avoid breakdown of resistance leading to subsequent epidemics.

The main outputs of this project are to create?

• a model of wind-assisted dispersal able to simulate the dispersal of fungal pathogens across a given landscape under a given set of environmental conditions
  
• a surveillance model that allows rapid assessment of surveillance strategy capabilities to detect the movement of airborne fungal spores into or out of a given area
  
• an assessment of the feasibility and likely benefits of ongoing surveillance in the Western Australian wheat belt
  
• a spatially explicit, dynamic model of population genetic structure for fungal pathogens undergoing aerial dispersal in a fragmented landscape, and
  
• an assessment of optimal strategies for the spatial and temporal management of resistant cultivars.

Who will be the end-users of your research?

This research will be used to inform policy development relating to the detection of invasive organisms. The models constructed as part of this research will also be employed for further research into the genetic structure and dynamics of meta-populations in agricultural environments.