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  StockDNA: Combining molecular and acoustic approaches to improve pelagic stock assessment.


   School of Environment & Life Sciences

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  Prof S Mariani, Dr K Yates  No more applications being accepted  Funded PhD Project (Students Worldwide)

About the Project

The studentship is with the University of Salford and CEFAS, in collaboration with the University of Bristol

Academic Supervisor: Prof. Stefano Mariani (Salford)
Academic Co-Supervisor: Dr Katherine Yates (Salford)
Industrial Supervisors: Dr Veronique Creach and Dr Jeroen van der Kooij (CEFAS)
Academic Collaborator: Dr Martin Genner (Bristol)

The studentship is supported by the Natural Environment Research Council (NERC) and includes:

• Postgraduate Fee cover
• A Research Council standard rate stipend for four years
• Generous bench fees and consumable costs
• Funds specifically allocated for conference travel

Final date for applications: Friday, 8th December 2017

Interviews will be held on: sometime mid-January 2018

The candidate must be in a position to register by October 2018

Description:
The sustainable use of natural resources, such as fisheries stocks, depends on our ability to i) maintain population biomass at adequate levels, ii) understand distribution patterns and life cycles, and iii) ensure ecosystem health. All of this requires regular monitoring activities, some of which rely on examining fish catch records, while others are independent of fishing operations. Pelagic stocks can typically be investigated using hydroacoustics, yet sonar data cannot accurately identify fish species and composition, therefore acoustic data must be verified by carrying out trawling. Trawling, however, requires significant gear, personnel, time and financial investments, and the obtained catch composition is not always representative of the biological community, due to inter-specific variation in catchability.

Innovative monitoring methods should be able to reduce costs and effort, while providing monitoring agencies and fisheries organisations with accurate biological information. One such method that has received considerable attention in recent years is environmental DNA (eDNA), which is based on the notion that by simply sampling the water column, it is possible to retrieve traces of DNA belonging to the organisms present in the sampled water mass. The present project specifically aims to assess the efficacy of eDNA sampling as a tool complementary to acoustic surveying of pelagic fish stocks, in view of reducing/removing the need for trawling activities. The project also aims to develop statistical models of species presence and community composition by contrasting the performance of eDNA- and trawl-based predictive distribution models. The overall goal of "StockDNA" is to significantly reduce the costs and ecological impacts of monitoring activities and potentially revolutionising the way fishery-independent surveys are conducted.

The successful PhD candidate will possess at least a high 2.1 BSc honours degree in marine biology/ecology or similar, and ideally Master-level education. The project will require a broad understanding of fisheries science and basic knowledge of molecular tools currently employed in ecological analysis. The project offers unique opportunities to become proficient in a wide range of cutting-edge marine biodiversity assessment approaches, which will include the participation in sampling campaigns aboard the CEFAS Endeavour vessel, the molecular methods for eDNA analysis, and the complex computational approaches required to interpret, analyse and compare acoustic, trawling, metabarcoding and spatial data, in an interdisciplinary framework.

For further information on the research team, visit: www.marianilab.org
Information of Student Eligibility can be found here: http://www.rcuk.ac.uk/documents/documents/termsconditionstraininggrants-pdf/

Enquiries: Informal enquiries may be made to Prof Stefano Mariani by email: [Email Address Removed]

Curriculum vitae and a supporting statement explaining their interest should be sent to [Email Address Removed]


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 About the Project