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Found 7 matching student topics

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Modelling and managing uncertain Antarctic species networks

Antarctic ecosystems are complex, and data is limited since it is expensive to collect. Species including penguins, seabirds, invertebrates, mosses, and marine species interact in food webs which can be modelled as mathematical networks. These networks can be large, span across terrestrial and marine systems, and are changing in response to environmental changes.These ecological networks can be modelled using differential equation predator prey models like Lotka-Volterra to describe these interactions. However, the relationships between species are not always known, or …

Study level
PhD, Master of Philosophy
Faculty
Faculty of Science
School
School of Mathematical Sciences
Research centre(s)
Centre for Data Science
Centre for the Environment

Mathematical modelling of ecosystem feedbacks and value-of-information theory

Ecosystems respond to gradual change in unexpected ways. Feedback processes between different parts of an environment can perpetuate ecosystem collapse, leading to potentially irreversible biodiversity loss. However, it is unclear if greater knowledge of feedbacks will ultimately change environmental decisions.The project aims to identify when feedbacks matter for environmental decisions, by generating new methods that predict the economic benefit of knowing more about feedbacks. Combining ecological modelling and value-of-information theory, the outcomes of these novel methods will provide significant and …

Study level
PhD, Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Faculty of Science
School
School of Mathematical Sciences
Research centre(s)
Centre for Data Science
Centre for the Environment

Modelling and managing uncertain Antarctic species networks

Antarctic ecosystems are complex, and data is limited since it is expensive to collect. Species interact in food webs which can be modelled as mathematical networks. The relationships between species are not always known, or we might know they interact but not how strongly. Noisy (or imperfect) data can be used to model these species interactions to give more certainty about how the ecosystem works as a whole – although the worse the data is, the less information it contributes. …

Study level
Honours, Vacation research experience scheme
Faculty
Faculty of Science
School
School of Mathematical Sciences
Research centre(s)
Centre for Data Science
Centre for the Environment

Optimal ecosystem management in rapidly changing systems

Delays in acting in collapsing ecosystems can be catastrophic. With every passing year, the chances that the ecosystem has progressed past some point of no return increases. Yet the research and development needed to develop a new technology can take a long time. Balance between these two dynamic processes is needed to determine the optimal length and effort for developing new technologies. This project will develop a method for finding the optimal schedule for developing technological readiness, social acceptability, a …

Study level
PhD, Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Faculty of Science
School
School of Mathematical Sciences
Research centre(s)
Centre for Data Science
Centre for the Environment

Mathematically optimising value of information for biodiversity management

When planning environmental management, data are only valuable if they lead to improved outcomes. As new monitoring technologies and approaches are developed, it is critical that they are used optimally to focus on the most important information gaps.Monitoring technologies should only be adopted if they can deliver improved management utility, and new data should be rapidly gathered in locations where early information could offer warning signals of future ecosystem change. Mathematical and statistical approaches to assessing the value of new …

Study level
Vacation research experience scheme
Faculty
Faculty of Science
School
School of Mathematical Sciences
Research centre(s)
Centre for Data Science
Centre for the Environment

Optimal conservation management in uncertain Antarctic environments

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 …

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Science
School
School of Mathematical Sciences
Research centre(s)
Centre for Data Science
Centre for the Environment

Bayesian inference meets value-of-information: how much more data do we really need for management of ecological networks?

The project involves applying value-of-information analysis across ecosystem models fit to data using Bayesian inference, to yield conclusions that have potentially wide application across the field of community ecology.Ecological networks use generalisations of the Lotka-Volterra model to describe the interactions between species, including predator-prey, mutualism, parasitism and others. Lotka-Volterra models fit to noisy data from synthetic ecological networks using Bayesian inference reveal that the predictions made in these networks carry large uncertainty but they may still be useful for informing …

Study level
PhD, Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Faculty of Science
School
School of Mathematical Sciences
Research centre(s)
Centre for Data Science
Centre for the Environment

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