From guinea pigs to guides: advancing lessons learned from reviewing end-to-end marine ecosystem models
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2025
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Details
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Journal Title:Socio-Environmental Systems Modelling
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Description:Holistic approaches to managing living marine resources, which consider the suite of ecological and environmental interactions affecting a population, are becoming increasingly common. Often, these approaches utilize predictive models that include ecosystem dynamics. However, the application of marine ecosystem modeling tools is generally limited due to the lack of formal reviews of the model's utility and performance, despite these practices being commonplace for single-species stock assessment models. Herein, we provide an account of our experience undergoing a formal review of a Gulf of Mexico end-to-end marine ecosystem model. Guided by lessons learned from the “guinea pigs'' preceding us, described by Kaplan and Marshall (2016), we crafted and implemented a two-phase project timeline consisting of an informal review with regional experts and a formal review with independent experts. While the outcome of our review was that the model was not yet ready for use, a list of necessary model refinements provided by the reviewers offered a clear path for the model toward operational use. We reflect upon the practical challenges, successes, and setbacks encountered during our experience, offering insights into structuring a marine ecosystem model review for future applications. Additionally, building upon previous recommendations, we provide a list of baseline standards for reviewing marine ecosystem model performance. Addressing the inherent challenges in the review of marine ecosystem models is crucial for unlocking their potential contributions to ecosystem-based management, and our recommendations outlined herein offer guidance for future reviews.
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Source:Socio-Environmental Systems Modelling, 7, 18848
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DOI:
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ISSN:2663-3027
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Rights Information:CC BY-NC
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Compliance:Submitted
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Main Document Checksum:urn:sha-512:a156a0b432d194f785f432515a6ea29de74bb042f52ad0445aa5d402b352f556adc69d4c91e2a8cb953c42f4a951a7eeabc0db8ede5b516aa4ae4e71c406a225
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