This fully-funded studentship will remain open only until filled, and so we recommend applying immediately.
Mathematical models play a central role in determining the population size of fish and other marine organisms that are caught for human consumption. By statistically fitting population models to annual data on commercial catches scientists are able to estimate the abundance of stocks. This is known as analytical stock assessment, and the results are essential in determining whether fishing is sustainable, or whether changes in fishing effort are required to ensure that overexploitation is avoided. Typically, the difference equation models used require the ages of fish in the catch to be known. Since this information is very costly, it is only obtained for the largest commercial stocks, for example North Sea cod. Consequently many important fish stocks remain without standard analytical stock assessments. Other approaches are desperately needed.
In this project you will develop and test an assessment model that is length-based rather than age-based. By contrast to age data, information on the sizes of fish in the population is much more readily available, and scientific surveys routinely measure the lengths of the fish they catch. The basic idea is for a discrete time matrix model that yields annual updates of the population length distribution. The model will then be fitted to data on the total annual landings and, optionally, discards (fish caught but not landed) as well as length distributions provided by research vessel survey samples. The use of survey data rather than fishery catch data means that the new model will not be restricted to those species for which age-data or fishery catch-at-length data is available. The parameter estimation will use Bayesian inference through Hamiltonian Monte Carlo sampling.
You will apply the assessment model to fishery data for the Firth of Clyde stocks of whiting, haddock, cod, and scallops. The Clyde ecosystem has been heavily exploited (Heath & Speirs 2012, Hunter, Speirs & Heath 2015, 2016), but despite the fishery remaining commercially important there are currently no regular analytical assessments for any stocks. Your work will therefore deliver key information in identifying measures to improve sustainable harvests from the region. You will have the opportunity to spend time in the Fisheries Division of Marine Scotland in Edinburgh in order to interact directly with civil servants who are operationally responsible for managing fisheries regulation in the Clyde.
Applicants should have or expect to obtain a good honours degree (1, 2.1, or equivalent) in applied mathematics, statistics, or a highly quantitative science. Experience of numerical modelling and/or programming in R would be highly beneficial. Some experience in mathematical ecology/modelling is desirable, but not essential.
If you are interested in this PhD project then please contact one of the supervisors by phone or email to discuss it.
Formal application is via the University of Strathclyde postgraduate research application process at https://but.mis.strath.ac.uk/pguserprofile/control/enterDetailsPage
making sure that you clearly state your interest in this project with the named supervisors.
Heath, M.R., Speirs, D.C. (2012) Changes in species diversity and size composition in the Firth of Clyde demersal fish community (1927-2009). Proc. R. Soc. B 279, 543-552.
Hunter, A. Speirs, D.C., Heath, M.R. (2015) Fishery-induced changes to age and length dependent maturation schedules of three demersal fish species in the Firth of Clyde. Fish. Res. 170, 14-23.
Hunter, A., Speirs, D.C., Heath, M.R. (2016) Investigating trends in the growth parameters of five demersal fish species in the Firth of Clyde and wider western shelf of Scotland. Fish. Res. 177, 71-81.