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Making spatial-temporal marine ecosystem modelling better-A perspective

Citation

Steenbeek, J and Buszowski, J and Chagaris, D and Christensen, V and Coll, M and Fulton, EA and Katsanevakis, S and Lewis, KA and Mazaris, AD and Macias, D and de Mutsert, K and Oldford, G and Pennino, MG and Piroddi, C and Romagnoni, G and Serpetti, N and Shin, Y-J and Spence, MA and Stelzenmueller, V, Making spatial-temporal marine ecosystem modelling better-A perspective, Environmental Modelling & Software, 145 pp. 1-11. ISSN 1364-8152 (2021) [Refereed Article]


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Copyright Statement

2021 The Author(s). Published by Elsevier Ltd. This is an open access article under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

DOI: doi:10.1016/j.envsoft.2021.105209

Abstract

Marine Ecosystem Models (MEMs) provide a deeper understanding of marine ecosystem dynamics. The United Nations Decade of Ocean Science for Sustainable Development has highlighted the need to deploy these complex mechanistic spatial-temporal models to engage policy makers and society into dialogues towards sustainably managed oceans. From our shared perspective, MEMs remain underutilized because they still lack formal validation, calibration, and uncertainty quantifications that undermines their credibility and uptake in policy arenas.

We explore why these shortcomings exist and how to enable the global modelling community to increase MEMs' usefulness. We identify a clear gap between proposed solutions to assess model skills, uncertainty, and confidence and their actual systematic deployment. We attribute this gap to an underlying factor that the ecosystem modelling literature largely ignores: technical issues. We conclude by proposing a conceptual solution that is cost-effective, scalable and simple, because complex spatial-temporal marine ecosystem modelling is already complicated enough.

Item Details

Item Type:Refereed Article
Keywords:opinion; spatial-temporal marine ecosystem modelling; capacity building; systematic skill assessments; systematic model calibration
Research Division:Biological Sciences
Research Group:Ecology
Research Field:Marine and estuarine ecology (incl. marine ichthyology)
Objective Division:Environmental Management
Objective Group:Marine systems and management
Objective Field:Marine systems and management not elsewhere classified
UTAS Author:Fulton, EA (Dr Elizabeth Fulton)
ID Code:152667
Year Published:2021
Web of Science® Times Cited:3
Deposited By:Research Division
Deposited On:2022-08-23
Last Modified:2022-09-20
Downloads:1 View Download Statistics

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