Graduate Research School Available Projects Using robotic predator models to understand anti-predator behaviors

Using robotic predator models to understand anti-predator behaviors

Title of Project

Using robotic predator models to understand anti-predator behaviors


Dr Ben Hirsch

College or Research Centre

College of Science & Engineering

Summary of Project

In contrast to sheep and goats, cattle have anti-predator defense behaviors that regularly dissuade wild dog attacks. Some adult cattle develop very nasty dispositions towards dogs (i.e. cows try and kill them) and adult cows with neonates often form crèches that cooperatively protect vulnerable calves from predators. This study proposes to investigate these anti-predator behaviours in cattle in a series of field experiments: 1. Documenting anti-predator behaviours elicited by a robot wild dog in various classes of cattle. 2. Investigating whether the cows that form crèches are closely related which might explain their maternal attitude towards each other’s calves. 3. Evaluating the impact of weaner management practices and the use working dogs on subsequent anti-predator behaviour. These experiments seek to understand how anti-predator behaviors develop, whether they are learned from experienced adult associates and passed on to subsequent generations, and whether cattle husbandry practices facilitate predation loss that could otherwise be avoided. These investigations will improve our understanding of the natural defense behaviors in cattle, and how husbandry might influence predation risk. Field work will be conducted in Northern Queensland on private properties and cattle research stations.

Key Words

dingo; cattle; predation; genetics; behaviour; robotics

Would suit an applicant who

Students with a background in behavioural ecology and/or animal/vet sciences would excel at this project. Experience in dry tropics habitats and cattle stations is a plus. Experience with remote controlled cars and a drone flight license would also be helpful.

Updated: 08 Apr 2020