Developing a length-based stock assessment methodology for Firth of Clyde finfish and scallops

Ideally this project will start in January 2018.

Finfish and shellfish fisheries in the Clyde Sea are a significant revenue source for the Scottish economy and beyond. The Clyde ecosystem has been heavily affected by fishing in the past (Heath & Speirs 2012), but there are still no analytical stock assessments for finfish, nor any regular assessments for king scallop. This project will use modern population modelling methods to deliver key information in identifying measures that may improve sustainable harvests from this region.

The project will use fishery data for the Firth of Clyde stocks of whiting, haddock, cod, and scallops, together with a length-based Bayesian stock assessment model developed at Strathclyde University. The underlying population model is a length-structured matrix model yielding annual updates of the population length distribution. The model is fitted to data on the total annual landings and (optionally) discards as well as length distributions provided by research vessel survey samples, and uses modern Bayesian inference through Hamiltonian Monte Carlo sampling for the parameter estimation. The model code is implemented in the STAN platform run from the ‘R’ software environment. In contrast to most length-based stock assessments, information on the length structure of the stock is provided by scientific surveys instead of fishery catch data. Thus, use of the length-based model that has been developed is not restricted to those species for which age-data or fishery catch-at-length data is available; the data required to fit the model is more ubiquitous. Another novel feature of the proposed length-based model is that it can account for temporally varying growth rates. This is important because the growth rates of some Clyde populations have declined substantially in recent decades (Hunter, Speirs & Heath 2015, 2016), and models that do not account for these declines are less likely to produce reliable abundance estimates.

By the end of the project a protocol for annual stock assessments of fish species in the Clyde will be in place. The guidelines and code for this will be held in the Scottish Government and at the University of Strathclyde. The methodology will be based on inputs from the Marine Scotland annual research vessel trawl surveys, monitoring data on the quantities landed of each species, and stakeholder data on the by-catch rates in the fishing fleets. The latter aspect will be a breakthrough in stakeholder involvement, and transform the process of stakeholder engagement in developing a fisheries management and ecosystem enhancement plan for the Clyde. The student will spend time in the Fisheries Division of Marine Scotland at Victoria Quay, Edinburgh, in order to interact directly with civil servants who operationally responsible for managing fisheries regulation in the Clyde.

Applicants should have or expect to obtain a good (I or II(i)) honours degree in applied mathematics, statistics, or 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://www.strath.ac.uk/studywithus/postgraduateresearch/howtoapply/

making sure that you clearly state your interest in this project with these supervisors.