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Methods for monitoring the socioeconomic effects of MPAs

Author : David Rodríguez-Rodríguez, Siân Rees, Lynda Rodwell, Marc Haenrick, Christine Dobroniak, Giles Bartlett, Gérald Mannaerts, Martin Attrill
Date : 04/03/2015

Recent legal and policy developments prompt us to assess social, economic and cultural effects of (MPAs) on local communities and marine and coastal stakeholders accurately and cost-effectively. In this report, we present a new marine protected area (MPA) socioeconomic assessment framework based on a mixed methods research design in 3 phases. In Phase 1, we conducted a literature review to identify a set of potentially relevant socioeconomic variables and stakeholder categories relevant in Europe. In Phase 2, we conducted an online survey among the main marine and coastal organisations in the UK and France to gather their perceptions of MPAs and their rating of potential socioeconomic variables for measuring MPAs' socioeconomic effects. In Phase 3 we used publicly available official statistics on those variables (or proxies) in a Multiple-Paired-Before-After-Control-Impact analysis to assess the socioeconomic effects of 6 case study MPAs in the PANACHE project area. A set of 14 socioeconomic variables for which data were available was identified. Of these, five variables were categorised as `priority 1' and nine variables as `priority 2' for stakeholders. Eight of them were community-scale variables, whereas 6 of them were sectorial variables related to fishing. Mixed Factorial ANOVA or descriptive statistics were used. No evidence of community-scale effects from our sample of stakeholders or MPAs was found, whereas effects were apparent on most fishing-related variables and also stated by some of the stakeholders surveyed. Our findings suggest that future socioeconomic assessments should focus on MPA effects on specific stakeholders rather than on the broader community. However, results should be handled with care due to the non-random selection of our sample of organisations and MPAs, the low sample sizes of some variables (e.g. fishing-related ones) and the likely masking effect of delayed management of some of the selected MPAs. Further studies should help to generalise our findings and the applicability of the framework

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