Utilising a terrestrial observation predictive system for emergency plant pest incursion management

Weiss, J., White, M. and McKirdy, S. (2007) Utilising a terrestrial observation predictive system for emergency plant pest incursion management. In: Oxley, L. and Kulasiri, D. (eds) MODSIM 2007 International Congress on Modelling and Simulation, 10 - 13 December, Christchurch, New Zealand pp. 1376-1380.

Abstract

Australia's management of bushfires illustrates how we should respond to major incidents. With up to date weather information, GIS, models predicting hotspots, outbreaks and potential control lines on the time scale of hours to days, agencies have an enhanced ability to manage fires.

However for other major incursions, such as emergency plant pest outbreaks, our technological ability and support is far less advanced. This project aims at investigating the use of the NASA Terrestrial Observation and Prediction System (TOPS) for management of Emergency Plant Pest (EPP) incursions in Australia.

In theory, by combining the daily environmental and climatic parameters (soil moisture, soil type, temperature, light exposure, aspect, etc.) with the host’s biology, one can predict what the photosynthetic rate (in terms of gC/m2/day) or fitness of a crop is. By combining the crop fitness with pest biology and host parameters, predictive climate-based simulations can then lead to estimates of the stages of pest outbreaks and guide the selection of feasible and effective containment or management options.

A large computational resource will be required to do these three way interactions for any large scale mapping in a reasonable time. NASA’s supercomputers will initially be used to assist the process of modelling photosynthetic rates or GPP for Victoria and southwest West Australian. Initially one or two defined EPPs, such as the Glassy-winged sharpshooter, will be piloted with the project aiming to produce a more generic template model for other pest species.

Item Type:	Conference Paper
Publisher:	Modelling and Simulation Society of Australia and New Zealand
URI:	http://researchrepository.murdoch.edu.au/id/eprint/32534

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