Testing management scenarios for the North Sea ecosystem using qualitative and quantitative models. (30th December 2022)

• Record Type: Journal Article
• Authors: Olsen, Erik; Tomczak, Maciej T; Lynam, Christopher P; Belgrano, Andrea; Kenny, Andrew
• Editors: Hunsicker, Mary
• Is Part Of: ICES journal of marine science. Volume 80:Number 1(2023)
• Page Start: 218
• Page End: 234
• Publication Date: 2022-12-30
• Subjects: ecosystem model -- Fuzzy Cognitive Mapping -- North Sea -- qualitative modelling -- stakeholders; Ocean -- Periodicals; Fisheries -- Periodicals; Fishes -- Periodicals; Marine biology -- Bibliography -- Periodicals; 551.4605
• DOI: 10.1093/icesjms/fsac231
• Languages: English
• ISSNs: 1054-3139

Abstract

Abstract: The complexities of ecosystem-based management require stepwise approaches, ideally involving stakeholders, to scope key processes, pressures, and impact in relation to sustainability and management objectives. Use of qualitative methods like Fuzzy Cognitive Mapping (FCM) with a lower skill and data threshold than traditional quantitative models afford opportunity for even untrained stakeholders to evaluate the present and future status of the marine ecosystems under varying impacts. Here, we present the results applying FCM models for subregions of the North Sea. Models for the southern North Sea, Skagerrak, Kattegat, and the Norwegian Trench were developed with varying level of stakeholder involvement. Future scenarios of increased and decreased fishing, and increased seal biomass in the Kattegat, were compared with similar scenarios run on two quantitative ecosystem model. Correspondence in response by the models to the same scenarios was lowest in the southern North Sea, which had the simplest FCM model, and highest in Norwegian Trench. The results show the potential of combining FCM and quantitative modelling approaches in integrated ecosystem assessments (IEAs) and in future ecosystem-based management advice, but to facilitate such comparisons and allow them to complement and enhance our IEAs, it is important that their components are aligned and comparable.