Conflict analysis and reallocation opportunities in the framework of marine spatial planning: A novel, spatially explicit Bayesian belief network approach for artisanal fishing and aquaculture

Abstract

The competition for marine space is a recognized challenge, and the implementation of new activities, such as those emerging from Blue Growth initiatives, may amplify this competition. The marine spatial planning (MSP) framework requires decision makers to analyse spatially explicit environmental and socio-economic data to determine where user conflicts are or might emerge and consider several potential management scenarios. In the present research, a spatially explicit Bayesian belief network (BBN) was applied for this purpose. The BBN was developed to analyse the potential reallocation of artisanal fishing effort to alternative sites due to the introduction of a new, non-take area: an offshore aquaculture site along the Basque continental shelf. The constructed model combined discrete, operational fisheries data, continuous environmental data, and expert judgment to produce fishing activity suitability maps for three different métiers (longlines, nets and traps). The BBN was run with various effort reallocation scenarios for each metier, and the best alternative fishing locations were identified based on environmental suitability, past revenue, and past fishing presence. The closure had a lesser effect on net and longline activity, displacing 10% and 7% of local fishing effort respectively. Comparatively, 50% of all local effort by traps took place within the closed grounds, and few alternative sites were identified. Nets were found to have the greatest number of alternative fishing grounds surrounding the aquaculture site. The present research demonstrates how BBNs can support spatially explicit scenario building and user-user conflict analysis for sustainable and successful ecosystem-based marine spatial planning.