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Biophysical models in humans and nature

Biophysical models are developed to represent key processes in humans and nature, from the electrophysiology of the human heart, to calcium carbonate skeleton production of coral reefs.In this project, we will explore biophysical model development across multiple fields, to identify commonalities, strengths and weaknesses, and identify analysis techniques ubiquitous in one field that can be immediately exploited to improve science in another field.

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

Mathematical modelling of ecosystem tipping points in Antarctica

Slight variations in the seasonal timing of Antarctic ice melt can drastically shift the composition of local shallow-water ecosystems from being dominated by invertebrates to algae instead. Such "tipping point" events may become commonplace in the future due to climate change, not just in Antarctica but in many ecosystems worldwide.This project seeks to develop mathematical models of the interactions between Antarctic environmental conditions and the local shallow-water ecosystem states. These models could then be used to make predictions about the …

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

Using mathematical models to detect alternative stable states in ecology

This project seeks to use mathematical models to detect "alternative stable states" in ecology - a behaviour in which the ecosystem can get "stuck" in one state (e.g. pristine) or another (e.g. irreversibly degraded).

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

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

Fairy circle landscapes formed in the Great Barrier Reef…but how?

Destabilising feedbacks between ecology and the local physical environment yield spatial pattern formation in various contexts throughout nature. For example, these feedbacks can lead to ring-shaped pattern formation in the spatial distribution of submerged aquatic plants. Recently, unusual crater-like structures have been identified in a large area of the Great Barrier Reef where the algae genus Halimeda constructs mounds called 'bioherms'.This project seeks to use partial differential equation models of the spatial growth of Halimeda to identify whether its long-term …

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

Designing efficient sampling algorithms for ensemble ecosystem modelling

This project seeks to use a combination of matrix algebra and advanced Monte Carlo methods for rare-event simulation to identify efficient algorithms for ensemble ecosystem modelling in large ecosystems. This project has the potential to significantly change the methods that researchers useto investigate complex ecosystems for the purposes of environmental management and future predictions.Ensemble ecosystem modelling (EEM) is a novel and increasingly popular method for generating predictions of future species abundance in complex ecosystems represented by generalisations of the Lotka-Volterra …

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

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

Uncertainty quantification in mathematical ecology

In this project, we will explore uncertainty quantification in mathematical ecology via a number of different methods. The project will involve application to ecological dynamics in the Great Barrier Reef.

Study level
Honours, Vacation research experience scheme
Faculty
Faculty of Science
School
School of Mathematical Sciences

Predicting alternative states induced by multiple interacting feedbacks: seagrass ecosystems as a case study

This project seeks to explore the complex dynamics that might arise from multiple interacting feedbacks in marine ecosystems, by designing ordinary and/or partial differential equation models of these feedbacks and analysing the steady states and/or temporal dynamics of the proposed model(s).It has been hypothesised that many social and ecological systems exhibit alternative stable states due to feedback processes that keep the ecosystem in one state or the other. The result can be tipping points, which are difficult to predict but …

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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