Modelling and forecasting of salmon parasites
Dr T Adams
Prof K Davidson
Dr P Gillibrand
No more applications being accepted
Funded PhD Project (European/UK Students Only)
Salmon aquaculture is a key component of the Scottish economy, and has now seen steady growth over several decades. However, there are several factors limiting further expansion. The most important of these are parasitic sea lice, which have both environmental and economic impacts. Understanding how these parasites spread, and the factors that lead to outbreaks, has become a key concern for the industry.
To gain this understanding, this project will take a novel approach to link the outputs from state-of-the-art computer models (which describe coastal currents and potential dispersal of sea lice in Scottish waters) with the factors that govern how lice populations develop on fish farm sites themselves. The project will integrate a range of unique data sources, including up-to-date weekly sea lice counts and associated physical parameters, and will allow development of a prototype forecasting tool. This will allow a leap forward in our understanding of the parasite’s ecology, offering benefits such as reduced chemical treatment and lower environmental impacts.
This PhD project is an opportunity for a numerate student interested in the interactions between physical and ecological processes to make a real impact in the way salmon farms are managed in Scotland and globally. The project is co-supervised by staff from SAMS (academic), Marine Harvest Scotland (industry) and Marine Science Scotland (regulator). The student will collaborate closely with colleagues in these organisations and have the opportunity to spend an extended period based at Marine Harvest in Fort William.
Dr Thomas Adams
Prof Keith Davidson
Dr Philip Gillibrand (Marine Harvest Scotland – industrial partner)
Dr Sandy Murray (Marine Scotland Science)
The project will involve the use of computer programming, mathematical models and data from a range of sources.
The physical and environmental processes affecting sea lice will be reviewed. Simple models incorporating these processes will be developed, based on existing models. Models will be applied to a specific case study based within a sea loch.
The sea loch case study will be used as a basis to derive parameter estimates for temporal dependence between sea lice counts. This will include connectivity between sites, management activities, and an estimated background infection rate. Model skill will be tested in a different sea loch environment. Subject to progress, the model domain will be expanded to encompass the Scottish west coast region.
The developed and validated models will be applied at a larger spatial scale. A package of computer code will be produced which allows the prediction of lice counts across the region. It will also be used to investigate management strategies for lice control, and investigate options for the future development of the industry.
The project is expected to start 2019, a start date will be discussed at interview.
Applicants must possess a minimum of an Honours degree at 2:1 and/or a Master’s Degree (or International equivalent) in a relevant subject.
To apply please complete the standard application form, attaching supporting documentation and send to: [Email Address Removed]
This project is co-funded by MASTS/The Data Lab and the Scottish Aquaculture Innovation Centre, including a stipend and UK/EU fees. For further details, please contact Dr Tom Adams ([Email Address Removed]).
The studentship covers fees at the Home/EU/International rate only, plus a stipend at the UKRI-RCUK level, for a total of 42 months (including writing-up time). Funding is available for students worldwide, however non UK/EU students will be liable for the difference between home/EU and international fees (value TBC)
Students must be domiciled in the Highlands and Islands transition region during the course of their study to be eligible for funding.
Applications require TWO references. Applications will not be reviewed without references.
How good is research at University of the Highlands and Islands in Earth Systems and Environmental Sciences?
FTE Category A staff submitted: 32.45
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