Sustainability and Resilience of the UK Fishing Fleet
Lead Research Organisation:
University of East Anglia
Department Name: Economics
Abstract
Building on the long-standing collaboration between UEA and CEFAS epitomised by the Collaborative Centre for Sustainable Use of the Seas (CCSUS), and the recent review of the methods and indicators for fisheries productivity carried out by the UEA team (Di Maria et al., 2023), this project aims to bring together economics, productivity analysis, fishery management, business insights, and data science to develop advanced models of the UK fishing fleet, bridge the gap identified above and feed directly into topical policy discussions. This research draws on the expert knowledge provided by the University of East Anglia (School of Economics and Business School) and CEFAS, and the industry insights contributed by Seafish to generate selected indicators for the UK fishing fleet, leveraging the data collected by CEFAS, Seafish and MMO.
From the methodological point of view, the project aims to develop and estimate a state-of-the-art model of fishery performance that transparently acknowledges the biological resource base it relies on, the level of technology available within the UK fisheries, and the business decisions of each vessel/fleet segment, following the best practice in the field (e.g. Squires and Walden, 2020). This model allows the identification of the fundamental drivers of the levels of production, profitability, efficiency and productivity for each of the units of analysis, as well as for segments of the fishing fleet while recognizing the biological and environmental limits posed by the resource base.
Combining the biological information on fish stock assessment over time held by CEFAS, the rich data on input costs, vessel characteristics and performance from the Seafish-owned Annual Fleet Survey, and the technical expertise of the UEA team, the PhD candidate will be able to apply the most recent Stochastic Frontier methods and estimate production frontiers for a range of fisheries around the United Kingdom (see Mainardi, 2022; Walden et al., 2022; Kerstens et al., 2023, for recent examples). This is the first attempt of its kind in the UK, constitutes the first work package of this project (WP1), and represents the necessary stepping stone for the rest of the analysis. Besides its academic and scientific merits, this part of the research has the potential to directly feed into policy discussions, for example, by providing clear guidance to policy makers to target specific fisheries or fleet segments with selective interventions aimed at improving their overall performance or to support specific goals. The student's placement within CEFAS offers a unique opportunity for the students to realize this type of impact.
Having developed the methodology discussed above, the second part of the project will demonstrate some of the possible applications of this analytical tool and further contribute to the policy debate both locally and nationally.
While these applications might change depending on the policy landscape, the first suggested application focuses on the impact of offshore wind farms on the profitability and productivity of fishing vessels in areas where large wind farms already operate, e.g. Hornsea OWF or Walney OWF (work package 2, WP2); the second case study aims to use environmental forecasts provided by CEFAS to identify the fisheries/fishery segments most at risk from the environmental changes brought about by global heating, gauge their degree of resilience to the expected changes over the next 30 years, and identify the potential for targeted policy support (work package 3, WP3).
From the methodological point of view, the project aims to develop and estimate a state-of-the-art model of fishery performance that transparently acknowledges the biological resource base it relies on, the level of technology available within the UK fisheries, and the business decisions of each vessel/fleet segment, following the best practice in the field (e.g. Squires and Walden, 2020). This model allows the identification of the fundamental drivers of the levels of production, profitability, efficiency and productivity for each of the units of analysis, as well as for segments of the fishing fleet while recognizing the biological and environmental limits posed by the resource base.
Combining the biological information on fish stock assessment over time held by CEFAS, the rich data on input costs, vessel characteristics and performance from the Seafish-owned Annual Fleet Survey, and the technical expertise of the UEA team, the PhD candidate will be able to apply the most recent Stochastic Frontier methods and estimate production frontiers for a range of fisheries around the United Kingdom (see Mainardi, 2022; Walden et al., 2022; Kerstens et al., 2023, for recent examples). This is the first attempt of its kind in the UK, constitutes the first work package of this project (WP1), and represents the necessary stepping stone for the rest of the analysis. Besides its academic and scientific merits, this part of the research has the potential to directly feed into policy discussions, for example, by providing clear guidance to policy makers to target specific fisheries or fleet segments with selective interventions aimed at improving their overall performance or to support specific goals. The student's placement within CEFAS offers a unique opportunity for the students to realize this type of impact.
Having developed the methodology discussed above, the second part of the project will demonstrate some of the possible applications of this analytical tool and further contribute to the policy debate both locally and nationally.
While these applications might change depending on the policy landscape, the first suggested application focuses on the impact of offshore wind farms on the profitability and productivity of fishing vessels in areas where large wind farms already operate, e.g. Hornsea OWF or Walney OWF (work package 2, WP2); the second case study aims to use environmental forecasts provided by CEFAS to identify the fisheries/fishery segments most at risk from the environmental changes brought about by global heating, gauge their degree of resilience to the expected changes over the next 30 years, and identify the potential for targeted policy support (work package 3, WP3).
People |
ORCID iD |
Corrado Di Maria (Primary Supervisor) | |
Zhiqing Zhang (Student) |
Studentship Projects
Project Reference | Relationship | Related To | Start | End | Student Name |
---|---|---|---|---|---|
ES/Y001834/1 | 30/09/2023 | 29/09/2032 | |||
2930133 | Studentship | ES/Y001834/1 | 30/09/2024 | 30/03/2028 | Zhiqing Zhang |