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Methods and policy pathways to optimize production of multiple interacting fish stocks

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  • Full or part time
    Dr A Rossberg
    Dr R Thorpe
  • Application Deadline
    No more applications being accepted
  • Funded PhD Project (UK Students Only)
    Funded PhD Project (UK Students Only)

Project Description

Global environmental issues related to food security, biodiversity, and use of antibiotic, pesticide and fertilizers suggest use of smart mixtures of crops/stocks in agriculture, forestry, farming, and ranching: so called polycultures. A barrier to this is, however, the complexity of polycultures compared to monocultures. Not only do different species naturally interact, ecological theory (Rossberg 2013, ISBN 9-780470973-55-4) predicts that the sensitivity of the composition of polycultures to external pressures, e.g. fertilization, climate, or pests, increases steadily with the number of co-existing species, both in the wild and in managed systems. Hence there is a need for methods (1) to set attainable management objectives for polycultures in light of inherent trade-offs, (2) to identify corresponding optimal mixtures, and (3) to understand the predictability of outcomes, and of the management intensity required to attain optima in view of inherent uncertainties. When stakeholders with different roles participate in management and use of the polyculture one also needs to (4) understand agreeability of objectives, e.g. in terms of inherent incentives to collaborate. A good model system to develop solutions addressing these challenges is the intensely managed mixed fishery of the North Sea. It is well described by ecological models and the benefits of managing it as a polyculture (rather than as a set of independent “wild” stocks) are acknowledged amongst stakeholders. Through our project partner we have opportunities to put ideas into practice by directly influencing marine management in a fast-moving policy context.


Aim of this project is to develop the prototype of a management plan, addressing the four problem areas enumerated above, to be used in future fisheries management.

Training Opportunities and Skills

This project combines innovative research and direct contributions to the development of environmental policy. The training will be conducted jointly between Queen Mary University of London and the Centre for Environment, Fisheries and Aquaculture Science (Cefas), a research institute belonging to the UK’s environmental ministry (Defra). The successful candidate will work with the project team to define the research approach and methodology. Specific transferable skills that the student will develop and use in addressing the project’s objectives include (1) theoretical and applied marine ecology, (2) decision and control theory, (3) programming skills, (4) statistical methods, (5) people skills in a business environment, (6) influencing of policy processes, (7) committee work, and (8) engagement of stakeholders with diverse backgrounds.

Attributes of Successful Candidates

Candidates must have a university science or maths degree and demonstrated programming and modelling skills. Experience in any of the eight skill areas listed above is of advantage.
For enquiries about the project, please contact Dr Axel Rossberg ([Email Address Removed]).

Application Deadline

Applications must be complete, including both references, by 11th January 2019 at 5pm

Funding Notes

Fully funded place including home (UK) tuition fees and a tax-free stipend in the region of £16,777, plus an annual stipend enhancement of £1,400. Students from the EU are welcome to submit an application for funding, any offers will be subject to BBSRC approval and criteria.


• Farcas, A. and Rossberg, A. G. (2016). Maximum sustainable yield from interacting fish stocks in an uncertain world: Two policy choices and underlying trade-offs. ICES J. Mar. Sci., 73(10), 2499—2508.
• Fung, T., Farnsworth, K. D., Reid, D. G., and Rossberg, A. G. (2015). Impact of biodiversity loss on production in complex marine food webs mitigated by prey-release. Nature Communications, 6, 6657.

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