Salberg, VM, Booth, AM, Jahren, S et al. (1 more author) (2022) Assessing Fuzzy Cognitive Mapping as a participatory and interdisciplinary approach to explore marine microfiber pollution. Marine Pollution Bulletin, 179. 113713. ISSN 0025-326X
Abstract
Fuzzy Cognitive Mapping (FCM) is a participatory modelling tool used to explore complex systems by facilitating interdisciplinary cooperation and integrating a variety of knowledge systems. Here FCM was used to explore marine microfiber pollution. Through individual interviews with representatives from the research, industry, water and environmental sectors, five stakeholder FCMs were developed and used to produce an aggregated community FCM in a stakeholder workshop. Stakeholder FCMs and the revised community FCM were used to compute how the modelled system reacted to changes under two scenarios developed during the stakeholder workshop; (i) Green Shift and (ii) increased textile consumption and production. Significant differences were observed in scenario results from the stakeholder-based models and the community-based model. For societal challenges characterized by unknowns around the problem and potential solutions, inclusion of a variety of knowledge systems through FCM and deliberation processes contribute to a more holistic picture of the system and its uncertainties.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2022 The Authors. This is an open access article under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0) (https://creativecommons.org/licenses/by/4.0/) |
Keywords: | Scenario development; Textiles; Complex systems; Interdisciplinary; Synthetic fibers; Natural fibers |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > School of Earth and Environment (Leeds) > Sustainability Research Institute (SRI) (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 16 May 2022 10:54 |
Last Modified: | 16 May 2022 10:54 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.marpolbul.2022.113713 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:186816 |