%0 Generic %D 2009 %T Real time spatial - temporal modeling of pest insect dispersal: Can TOPS improve predictions? %A Weiss, J %A McCarthy, M %A McKirdy, S %X

Predicting the dispersal of exotic insect pests is critically important in managing and restricting their impact. Insects disperse to resources or hosts that are often highly patchy and variable in distribution and quality. Host selection involves not only choosing the right species of plant, but also selecting an individual plant within that species that is, or will be, suitable for feeding, survival and development. Insects need to detect their host from a distance usually utilising visual or olfactory cues or both. Many phytophagous insects are attracted by greens and yellows, although other wavelengths can also be attractive. By using NASA’s Terrestrial Observation Prediction System - Gross Primary Production model (TOPS GPP) to model daily photosynthetic rates of vegetation types for south eastern Australia we hope to measure their suitability to particular pests.

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 the photosynthetic rate (in terms of gC uptake/m²/day) or suitability to a pest of a vegetation type. By then combining this measure of suitability with a pest’s biology, climate-based simulations can then predict pest outbreaks and help identify feasible and effective containment or management options.

We will compare TOPS predictive pest dispersal model with models run on a static landuse layer to determine which has better predictive power. The Queensland fruit fly, the Australian plague locust and the Currant lettuce aphid, will be piloted, with the project aiming to produce a more generic template model for other pests.