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Found 29 matching student topics

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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

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

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

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

Sentience and the law (plants and animals)

For centuries the law has operated under the assumption that plants and animals are inert and material objects without the ability to meaningfully determine their future or engage with other living or material things. Plants constantly communicate with each other through fungal (mycorrhizal) networks in the soil and have up to 20 senses as opposed to the five that human beings have. New ways of thinking about plants and animals raise important and deep possibilities for law reform. The supervisors …

Study level
PhD, Master of Philosophy
Faculty
Faculty of Business and Law
School
School of Law

Probing the origins of life on Earth

The history of life on Earth is written in the fossil record. In this project, you will investigate stable isotope evidence for extremely early evolving organisms. Through careful petrography and with the use of isotope ratio mass-spectrometers, you will help unravel the history of microbial metabolisms that powered the ecosystems recorded by 3 billion-year-old microbial fossils.

Study level
Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Faculty of Science
School
School of Earth and Atmospheric Sciences

Searching for Life on Mars on Earth

NASA's newest Mars rover, Perseverance, has just arrived on the red planet. Tasked with searching for ancient life in the geological record of a ~4 billion-year-old crater lake, the mission science team must use our only available analogue - the Earth - as their guide to exploration.

Study level
PhD
Faculty
Faculty of Science
School
School of Earth and Atmospheric Sciences

What do ancient granitic rocks tell about the formation of Earth's crust

The Earth is a dynamic evolving planet that has continually changed throughout its history. This change is recorded in the different rock types preserved in the continental crust and is paralleled by the evolution of life. Study of Archean granitic terranes (4.0-2.5 billion years ago) provides invaluable information on the early Earth when 50% of the present day volume of continental crust was generated. You will help work out how Earth's earliest crust formed through:potential field workpetrographygeochemical analysis.

Study level
PhD, Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Faculty of Science
School
School of Earth and Atmospheric Sciences

Characterisation of a novel protein co-amplified with the n-MYC oncogene

The MYCN oncogene is amplified in a number of tumour types, including Neuroblastoma (NB) and Neuroendocrine Prostate Cancer (NEPC), where it is associated with worse patient prognosis, as compared to non-amplified tumours. However, the high expression of MYCN (encoding the n-MYC protein) alone in non-amplified tumours is associated with better patient prognosis and less aggressive disease. This suggests that other genes co-expressed in MYCN amplified tumours may be responsible for mediating the aggressive traits of n-MYC. Our team has identified …

Study level
Master of Philosophy, Honours
Faculty
Faculty of Health
School
School of Biomedical Sciences

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