Economic and socio-cultural implications of offshore wind on fishing communities

Research projects

  • Research area

    Environmental impact marine biology and aquaculture

  • Institution

    University of Hull

  • Research project

    Economic and socio-cultural implications of offshore wind on fishing communities

  • Lead supervisor

    Dr Charlotte Hopkins (Lecturer in Marine Science, University of Hull)

  • PhD Student

    Woolganathan Naidoo

  • Supervisory Team

    Dr Magnus Johnson (Senior Lecturer in Environmental Marine Science, University of Hull)
    Dr Andrew Gill (Principal Scientist, CEFAS)

Project Description:

Logo for CEFAS  Logo for Holderness Fishing Industry Group

Offshore wind (OSW) energy facilities have been operating in Europe for 20 years with large scale developments now also being progressed in North America. Existing knowledge of the impact of wind energy on fisheries is mainly focused on ecological and environmental impacts. There is limited understanding of how the development of OSW is affected by consideration and interactions with fisheries. As OSW energy expands, there is also a clear knowledge gap surrounding economic and socio-cultural impacts on fishing behaviour, fishing communities and coastal economies. In the North Sea, particularly, space is becoming limited and there is a need for greater understanding of the cumulative impacts of OSW developments on different fisheries at a local and seascape scales. Assessments of the wider socio-economic impacts of planning are crucial for sustainable co-location of OSW energy and fisheries.

Part of the costs to OSW developers relate to the licensing requirements and potential mitigation and/or compensation to fisheries. Different fisheries are at different stages of interaction with OSW developments and some fisheries have received financial compensation for loss of earnings and opportunities as a result of OSW. However, the impact of the requirement for compensation on the planning, construction and operational processes and decommissioning of OSW is poorly understood. A further knowledge gap is the impact of compensation by OSW developers on fisheries, as compensation can have both positive and negative effects. For example, previous research has shown that fishers have recognised benefits gained by one group of fishers might represent a cost to another group by simply displacing the problem elsewhere. It is becoming clear that displacement of fishing activity is also leading to fishers displaced onto already fished areas and there is some evidence to suggest that compensation is leading to fishers investing in more gear and larger vessels.

The aim of this PhD research project is to better understand the economic and socio-cultural interactions between the Offshore Wind industry and fisheries.


  1. Identify the social and economic impacts of OSW on different fisheries
  2. Understand the perceptions of OSW developers of OSW and fisheries interactions
  3. Identify why and how compensation varies across different fisheries
  4. Identify the potential positive and negative impacts of compensation from OSW developments to fisheries


The project will adopt a mixed-methodology approach combining both qualitative and quantitative data.

Social science methodologies will be adopted for this project. The specific methodologies will be designed to provide fishermen and OSW industry representatives with adequate opportunities to contribute their knowledge, views and information on fishing activities in relation to OSW.

The specific social methodologies could include: focus groups, semi-structured interviews, and questionnaires. A Delphi process could also be employed to structure a group communication so that the process is effective in allowing a group of individuals, as a whole, to deal with this complex issue.

The extent of spatial co-location of fisheries and OSW, current fishing activity and forecasting fishing behaviour will be mapped out using spatial data analysis methodologies using tools such as GIS and Advanced R spatial data analysis.

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