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Modelling the impact of spatial fishery closures on commercially exploited shellfish stocks

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  • Full or part time
    Dr D C Speirs
    Prof M Kaiser
    Dr Helen Dobby
  • Application Deadline
    No more applications being accepted
  • Funded PhD Project (European/UK Students Only)
    Funded PhD Project (European/UK Students Only)

Project Description

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 involved in addressing these questions will be:

Implementing a non-spatial Dynamic Energy Budget (DEB) model for the scallop populations. DEB modelling (e.g. the model for sandeel by Macdonald et al. 2018) involves representing individual growth as the outcome of the uptake and allocation of energy obtained from feeding. Inputs will be temperature and food from existing biophysical model outputs held at Strathclyde. The model will be validated against MSS survey data, including shell growth rings, and (since spawning may peak at more than one time of year) larval abundance from Continuous Plankton Recorder (CPR) data and the long-term Stonehaven plankton time series.

Identifying 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). Additionally, the locations of existing and proposed marine renewable installations and MPAs will be identified where these overlap with scallop habitat. Habitat model outputs and potential source and sink locations will be ‘ground-truthed’ with the scallop industry using ‘local ecological knowledge’ derived from fishers’ experience of stochasticity of scallop recruitment, growth and habitat associations (Shepperson et al. 2014).

Lagrangian particle tracking to establish subpopulation connectivity. We will use the MSS Scottish Shelf Model, which has spatially-variable horizontal resolution (coastal internode distance of 1km) covering the whole UK shelf. Outputs are available as an annual climatological average (1990-2014) and a future climatology (2038-2062, IPCC high greenhouse gas concentration scenario RCP8.5) thereby allowing the examination of the potential effects of climate change.

Implementing a full spatial population model combining the DEB model and particle tracking outputs. Discrete spatial cells will be connected by larval transport using a spatial transition matrix approach developed at Strathclyde that has been deployed for zooplankton and fish population models (e.g. Speirs et al. 2006).

Model outputs from this project will thereby contribute to the resource management of this valuable stock under the twin challenges of climate change and changing patterns of marine habitat use.

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 spend time with the Fisheries Division of Marine Scotland at Victoria Quay, Edinburgh, in order to interact with civil servants who are operationally responsible for managing fisheries regulation. There will also be opportunities for the student to participate in new data gathering at sea as part of MSS monitoring surveys.

Application Procedure

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

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 is 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 a relevant subject.

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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