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Mathematical modelling of the impact of spatial fishery closures on shellfish stocks


Department of Mathematics & Statistics

About the Project

We are looking for a highly motivated student to join our group. This fully-funded 3 year studentship needs to be filled in as soon as possible, so we recommend applying immediately. It is expected that interviews will take place online on July 24, 2020.

This project will use mathematical and statistical modelling methods to answer key questions about the population dynamics of scallop (Pecten maximus). Scallops are the third most economically valuable harvested marine species landed in the UK. The spatial population model developed during the project will be used to explore the demographic consequences of the connectivity, through larval transport, between scallop grounds, and the potential population contribution of scallops within fishery exclusion zones, including those around marine renewable installations in Scottish waters. It is remains unknown whether the expansion of wind turbine installations on scallop grounds will result in positive or negative pressures on the fishery. Negative effects may arise as a result of the loss of access to fishing grounds and displacement of fishing effort, while positive effects may result from enhanced production and resilience through a marine reserve effect. Additional pressure may arise through changes in temperature and subpopulation connectivity resulting from climate-driven changes to the physical environment. The net outcome for the fishery will depend on the balance between all of these. The key research questions are therefore, a) which patches of habitat are sources and sinks, b) what pattern of marine reserves, including those created by wind-farms, would have a net benefit for the stocks and fisheries, and c) how sensitive would this be to variations in connectivity that might result from weather and climate change?

The methods used in the project will include developing a non-spatial Dynamic Energy Budget (DEB) model (see, for example the DEB model for sandeel by Macdonald et al. 2018) for the scallop populations. The model will be validated using biological survey data (on scallops and plankton) collected by Marine Scotland Science (MSS). The locations of potential scallop habitats in Scottish waters, using existing data on stock distribution and habitat mapping techniques developed at Strathclyde (Wilson et al. 2018). Habitat model outputs and potential source and sink locations will be ‘ground-truthed’ with the scallop industry using ‘local ecological knowledge’ (Shepperson et al. 2014). Lagrangian particle tracking using flow fields from the MSS Scottish Shelf Model will establish subpopulation connectivity under past conditions and predicted climate change scenarios. A full spatial population model will combine the DEB model and particle tracking outputs using a spatial transition matrix approach developed at Strathclyde Speirs et al. 2006).

The successful candidate will join a large team of PhD students working in marine population and ecosystem modelling at the University of Strathclyde and Heriot-Watt University, as well as working with the applied research scientists at Marine Scotland Science. The student will develop integrated expert skills in modelling and data management, and will have the opportunity to engage with government & industry stakeholders, participate in international meetings and conferences.

Application Procedure

Initial informal enquiries are strongly encouraged, and should be directed to the lead supervisor Dr Douglas C. Speirs ().

Formal applications are via the online application form from the Apply Now link at

https://www.strath.ac.uk/courses/research/mathematicsstatistics/#apply

remembering to list the title of the project as “Modelling the impact of spatial fishery closures on commercially exploited shellfish stocks”, Dr Douglas C. Speirs as the first supervisor, and SUPER DTP as the source of funding.



Funding Notes

This project is funded by the SUPER-DTP and available to UK/EU nationals who meet the RCUK eligibility criteria.

The studentship provides funding for tuition fees, stipend and a research training and support grant, subject to eligibility.

Candidates should have (or expect to achieve) a minimum of a 2.1 Honours Degree, or international equivalent, in mathematics or statistics, or another degrees (e.g. in physics or biology where there is a substantial quantitative component, and an interest in applying quantitative methods to the real world. No prior knowledge of fisheries biology, scallops, or the specific modelling methods to be used is necessary.

References

Macdonald, A., Speirs, D.C., Greenstreet, S.P.R, & Heath, M.R. (2018). Exploring the influence of food and temperature on North Sea sandeels using a new dynamic energy budget model. Front. Mar. Sci. 5, 339.

Speirs, D.C., Gurney, W.S.C., Heath, M.R., Horbelt, W., & Wood, S.N. (2006). Ocean-scale modelling of the distribution, abundance, and seasonal dynamics of the copepod Calanus finmarchicus. Mar. Ecol. Prog. Ser. 313, 173-192.
Shepperson J., Murray L.G., Cook S., Whiteley H., & Kaiser M.J. (2014). Methodological considerations when using local knowledge to infer spatial patterns of resource exploitation. Biological Conservation 180: 214-223.
Wilson, R., Speirs, D.C., & Heath, M.R. (2018). A synthetic map of the northwest European shelf sedimentary environment for applications in marine science. Earth Syst. Sci. Data 10, 109-130.

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