Mathematician Modeller

Modelling Collective Animal Movement

The ability to predict and understand the movement of large groups of animals is crucial for effective control of locust outbreaks.

Effective control of locust outbreaks relies on the early detection and monitoring of locust hopper bands before flying swarms form. To reduce the environmental impact of locust control operations, there has been a shift from blanket spraying to targeted application of barrier treatment using biopesticides.

This project will focus on modelling the collective movement of locust hopper bands. We will improve current models through inclusion of variation of individual animal characteristics such as hunger and epigenetic phase (solitary vs gregarious) and resource distribution (notably food and water).

We will use field and laboratory observations to tune the model's parameters and validate its predictive efficacy by applying techniques from data science. Our data-informed models will be able to predict the behaviour of the bands in response to different control measures.

The student will work as part of the national Analytics for the Australian Grains Industry initiative providing extended collaborative opportunities and professional development activities.