National parks are the cornerstone of modern conservation efforts. They now cover more than 10% of the Earth’s land surface and are found on every continent and sea.
We can prove that these national parks stop human destruction of habitat. We can prove that they benefit the lives and livelihoods of people who visit and surround them. However, we can't yet prove that they have stopped the extinction of a single species. This isn't because we don’t believe that they've helped. Instead, it’s because it’s difficult to prove a negative – that a species avoided extinction because it was protected by national parks.
Recent research produced large, complex machine learning tools (boosted regression trees) that predict a species’ threat level (as defined by the International Union for the Conservation of Nature). They can also predict the probability that a species will become more threatened or go extinct. We'll use this new technique to answer important and outstanding questions in conservation science.
The project will extend existing statistical methods to predict the conservation status of the same threatened animal species in both:
- the presence of the existing international reserve system
- the reserve system's absence
These different predictions will help us understand the degree to which national park systems have saved species from extinction.
The project will begin by focusing on mammalian predators in Africa. Examples can include:
- wild dogs
The project will offer training in new statistical methods (e.g., machine learning tools). It will introduce the candidate to ideas in conservation science, including spatial conservation prioritisation. The project will be undertaken in collaboration with the Wildlife Conservation Society, and will therefore result in experience working with and understanding the goals of international conservation organisations and modern conservation science.
The project will estimate the contribution of the Earth’s national parks to the conservation of threatened species. Given the central role of national parks to global conservation, these results will offer important support for their current and future existence.
Skills and experience
Candidates must have, or be undertaking, a degree in mathematics or a similar quantitative field.
We particularly welcome applications for groups that are underrepresented in STEM, including:
- students who identify as Indigenous Australians
- students who identify as people of colour.
You may be eligible to apply for a research scholarship.
Contact the supervisor for more information.