Study level

  • PhD
  • Master of Philosophy
  • Honours


Topic status

We're looking for students to study this topic.


Dr Kate Helmstedt
Research Fellow (DECRA)
Division / Faculty
Faculty of Science
Professor Kerrie Wilson
Pro Vice-Chancellor, Sustainability
Division / Faculty
Academic Division


Species and ecosystems in Antarctica are threatened. Optimal biodiversity conservation is an interdisciplinary field combining mathematical modelling and optimisation with ecology and conservation. We can use mathematics to understand the system, model how management actions might impact it, and then optimise which actions should be used. For example, we can explore where protected areas should be placed, how species should be managed, or how tourist impacts should be reduced. However, the complexities of conservation in Antarctica necessitate the application of new mathematical approaches. Specifically, risks and uncertainties are ubiquitous in Antarctica, and mathematical modelling and decision science offer opportunities to tackle both issues.

Optimal conservation planning requires describing an objective function, quantifying costs, modelling ecosystem responses to actions under different scenarios, understanding and measuring uncertainties in the system, and optimising the system. Each of these components are more complex in an Antarctic context. Data is expensive to collect in Antarctica, so it may be patchy or noisy. Objectives are not always clear, since governance of Antarctica is complicated. Ecosystems are rapidly changing due to climate change, and ecosystem interactions span land and sea.

Research activities

In this project we will explore how existing approaches to conservation and environmental planning will not be sufficient to tackle the risks, dynamics, and uncertainty in Antarctic systems. We will model the ways that the dynamic, changing environment in Antarctica – and the high uncertainty – affect how we should design and implement biodiversity conservation in an Antarctic setting.


We will build new models and methodologies to capture these complexities, building a framework for future decision-making.

Skills and experience

Background in mathematics, statistics, computer science, or related quantitative disciplines. Programming skills in any language. An interest in studying complex environmental systems. Strong communication skills and an interest in communicating with interdisciplinary scientific teams.

We are particularly interested in applicants from groups that are underrepresentation in academia, mathematics, and STEM, based on gender, sexuality, race, culture, disability status. You will join two active and diverse research groups lead by the supervisors, and we have a strong focus on supporting your research development.


You may be eligible to apply for a research scholarship.

Explore our research scholarships



Contact the supervisor for more information.