About the Project
Faecal indicator organisms (FIO) such as E. coli and intestinal enterococci are routinely quantified for water quality assessments to confirm faecal contamination in bathing, drinking, irrigation and shellfish-harvesting waters, and are therefore used to determine the level of risk to human health. Current research primarily focuses on livestock and human sources of FIO, while FIO from wildlife sources are largely unaccounted for and the scarcity of wildlife FIO data has led to uncertainties associated with in-stream FIO risk modelling. In rural environments, wildlife is likely to contribute a large proportion of FIO in a catchment; for example, water courses that are connected to wetland reserves could receive a large contribution of bird-associated FIO, while additional wildlife FIO inputs can come from deer.
The aim of this project is to determine the contribution of wildlife FIO to surface water contamination. This inter-disciplinary project will combine methods in microbiology, molecular biology, biogeochemistry, risk assessment and modelling, thereby providing a breadth of training and skill development. The objectives of the project are to:
1) Develop a novel toolbox for the detection of FIO from wildlife. This will involve exploring the integration of innovative tools and technologies that span multiple disciplines, including: molecular techniques (eDNA, qPCR), sediment tracing (isotopes and biomarkers) and modelling (risk-based, causal Bayesian Belief Networks) for the detection of total FIO and wildlife-specific FIO in a catchment. A suitable sampling design will also be developed to allow integration of different techniques.
2) Test the toolbox approach on a case study catchment. This will involve fieldwork to collect environmental samples in the catchment to test the methods. The fieldwork will be completed over a one-year sampling campaign to account for seasonal variability. Associated environmental and biological parameters will also be measured at the sampling sites to understand the likely FIO inputs from land, the transport mechanisms from source to surface water, and the associated health risk via exposure to pathogens.
3) Explore the suitability of existing models (e.g. SCIMAP-FIO, Bayesian Belief Networks, statistical models) and use the catchment data to model the contribution of wildlife FIO to in-stream water quality risk. The feasibility to extrapolate the case study catchment model to other catchments will also be explored.
Ultimately, this project will develop detection methods and generate data to refine risk assessment models that could potentially transform regulation in the water and environmental sector. Greater understanding of different FIO sources will help to inform future catchment management practices and mitigation strategies to improve water quality, protect human health and deliver multiple benefits to society.
Applicants are strongly advised to make an informal enquiry about the PhD to the primary supervisor well before the final submission deadline. Applicants should have a first-class honours degree in a relevant subject or a 2.1 honours degree plus Masters (or equivalent).
This is a full-time opportunity.
Unfortunately due to COVID restrictions we cannot supply a telephone number for enquiries, in the first instance please email either Moira Maron at the address above or one of the supervisors listed above.
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