Delivering Effective Marine Protected Areas – Backing the Blue Belt through Governance Structures

CASE award with the Marine Management Organisation

Delivering Effective Marine Protected Areas – Backing the Blue Belt through Governance Structures

CASE award with the Marine Management Organisation

Project Description

This project has been shortlisted for joint NERC-ESRC funding, with the SeNSS ESRC Doctoral Training Partnership

Supervisors

Dr Tom Cameron (University of Essex, Biological Sciences)

Dr Gina Yannitell Reinhardt (University of Essex, Department of Government)

Dr Michelle Taylor (University of Essex, Biological Sciences)

Dr Christopher Sweeting (Marine Management Organisation)

Background

Evaluations of MPAs highlight the lack of clear governance structures as contributing to low compliance and effective conservation outcomes (Buglass et al. 2018, Campbell et al. 2012). Many MPAs are supported through voluntary or commercial groups working with statutory regulators, but without formal institutional structures. Others are regulated by rigorous institutions. This studentship will assess MPA governance structures to determine how and whether they condition MPA conservation performance.

Research methodology

Decades of research have explored how best to manage and preserve collective resources, and solutions range from incentives to penalties, and from single providers to group coordination (e.g. Ostrom 2015). The student will undertake quantitative and qualitative analysis of academic literature, registered documents, online text and structured interviews to explore variations in MPA governance. The project will evaluate approaches to engage stakeholders, fund preservation, and effectively manage the maintenance or recovery of protected species and designated features.

Training

Along with outstanding NERC training as part of the ARIES and SeNSS DTP programs, this student will receive truly interdisciplinary training in marine social sciences, marine and environmental policy, policy analysis, discourse analysis, and computerised text mining (CTM) and machine learning. Training will include interview methods, and the student will be able to meet policy makers and practitioners in regional, national, and international fieldwork locations. The successful candidate may undertake an internship at a UK government or NGO organisation to gain experience of delivering the UK Blue Belt programme.

Person specification

We seek candidates with Bachelor’s degree and interest in or across relevant Social, Natural, and Computer Sciences, including: Marine or Conservation Biology, Public or Environmental Policy, International Development, Political Science, Economics, Data Sciences. If you have a passion for research in the natural world and effective conservation policy, this project could be for you!

References

  • Gawande, K, Reinhardt, GY., Silva, CL., Bearfield, D., (2013). Comparing Discrete Distributions: Survey Validation and Survey Experiments. Political Analysis. 21 (01), 70-85
  • Lown, AE, Hepburn, LJ, Heywood, JL, Cameron, TC (In Press) - Density and seasonally dependent associations of biodiversity with the European flat oyster (Ostrea edulis): evidence for marine planning. Journal of Applied Ecology
  • Caveen, AJ., Sweeting, C. et al., (2014). Diverging strategies to planning an ecologically coherent network of MPAs in the North Sea: the roles of advocacy, evidence and pragmatism in the face of uncertainty, Advances in Marine Biology 69: 325-370
  • Reinhardt, GY. (2017). Imagining Worse than Reality: Comparing Beliefs and Intentions between Disaster Evacuees and Survey Respondents. Journal of Risk Research, 20(2): 169-194. DOI:10.1080/13669877.2015.1017827
  • Ostrom, E. (1990). Governing the commons: The Evolution of Institutions for Collective Action. Cambridge University Press.

Open for applications

Please apply by sending a CV (including contact details of two academic referees) and a cover letter explaining your motivation and suitability for the PhD.

They should be sent to Emma Revill  ariesapp@essex.ac.uk  by 8th Jan 2019