Integrating population ecology and decision theory to inform invasive species management
A huge amount of resources are spent annually on controlling established pest species. Eradicating pest populations can potentially save significant ongoing management costs. Eradication is relatively simple when a pest is detected early and its entire population can be treated at once. The problem becomes substantially more difficult, however, when a pest species is established across a large area. Feasibility and optimal spatiotemporal allocation of resources over large areas will depend on population growth and dispersal, habitat suitability, and efficacy of removal/detection tools. Lacking is a robust quantitative basis for synthesising information about new incursions to provide prompt evidence-based guidance for policy/management decisions.
This research will develop and apply spatiotemporal simulation tools to identify appropriate response strategies for invasive species with varying life history traits. Simulation models will integrate ecological, detection and removal, and decision processes across spatial scales. These models will be calibrated by literature review and data analysis from past and current biosecurity responses. The student will emerge from this program with a strong foundation in theoretical and applied population ecology, and quantitative skills to address complex research questions.
The successful candidate will join the Population Biology and Genomics group at Curtin University (https://popbiolgenomics.org/) in Perth, Western Australia. The group provides a supportive learning and research environment, and has a strong track record with publications and grants. The group is well connected to the biosecurity research and management community and is working with state government around current incursion responses.
The student will be under the direct supervision of Prof. Ben Phillips, with co-supervision, collaboration and travel opportunities provided with leading applied ecologists in Australia and New Zealand. These opportunities allow the student to build their network and provide important training opportunities around the simulation and statistical modelling required for the work. The Ph.D. position will be fully funded to cover tuition fees, with a (tax free) living allowance of $42,000 per annum for 3.5 years.
Applications are open now.
Send enquiries to Prof Ben Phillips.