Decision support for marine spatial planning affecting fisheries: a case study of a small scale fishery

Abstract

Increasing competition for space in the marine environment has resulted in a need for decision makers to better understand and consider fisheries in spatial planning decisions; this is to ensure the maintenance of fishing livelihoods as well as to meet conservation and sustainability goals. To accomplish this, the following key steps should be considered; (1)established where fishers actually fish, (2) understand the value of areas for fishers, (3)understand the spatial distribution of vulnerable species and habitats, and (4) assess spatiotemporal overlap to inform on the trade-offs and consequences associated with various planning scenarios. However, to support these key steps requires decision support tools and analyses. Using the scallop fishery in the Bay of Fundy, Canada, as a case study, this project presents a demonstrated example of how this support can be provided. A methodology by which vessel monitoring system data can be processed to derive fishing activity metrics and combined with logbook data is established, fisher habitat preferences are quantified, a framework approach to value space is developed, a novel spatially explicit species distribution model is developed and used to identify area of conservation priority for a sensitive benthic species of concern (the horse mussel, Modiolus modiolus), and spatio-temporal overlap assessments between the scallop fishery, horse mussel habitat, and a proposed conservation closure for horse mussel are evaluated. Scenarios and trade-offs are quantified to demonstrate how analysts can support effective evidence-based decision making regarding fishing and marine spatial planning as it relates to spatial conservation planning. The general approaches and lessons learnt from this thesis can be applied more broadly across other small scale fisheries facing competition for space from other sectors worldwide.

Date of Award	Jun 2025
Original language	English
Supervisor	Chris McGonigle (Supervisor) & Rory Quinn (Supervisor)