Modelling the food web in the Irish Sea in the context of a depleted commercial fish community Part 1: Ecopath Technical Report

Jacob W Bentley, Natalia Serpetti, Clive Fox, Dave Reid, Johanna Heymans

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Over the past century the commercial fish and shellfish stocks in the Irish Sea have changed dramatically, altering the way in which we utilise and manage different aspects of the ecosystem. As elsewhere in the North Atlantic, many of the Irish Sea stocks have historically been subject to high levels of fishing mortality leading to reduced spawning stock biomasses (SSB) and truncated age structures. Despite large reductions in fishing effort since 2003 there has been only slow recovery whist some fish stocks, such as whiting, do not appear to have improved. This project aims to use multi-species models to underpin the mechanisms behind the slow recovery of commercial fish stocks in the Irish Sea.
This project was designed under the remit of the first ICES Integrated Benchmark Assessment, WKIrish. WKIrish is a multi-year process focussing on improving single-species stock assessments (principally cod, haddock, whiting, plaice, herring), incorporating a mixed fisheries model, and developing the integration of ecosystem aspects and working towards an integrated assessment and advice. Two multi-species models (LeMans; Ecopath with Ecosim), developed simultaneously, will be used to inform the development of an integrated ecosystem assessment and advice.
This report describes the development of an Ecopath model of the Irish Sea, allowing the interested reader to understand the methodology and data used to construct the model. Importantly, the report is intended to provide transparency to the model construction process and highlight the limitations of the data and thus the caveats attached to model outputs.
Original languageEnglish
PublisherScottish Association for Marine Science
Number of pages147
Publication statusPublished - May 2018

Publication series

NameSAMS Internal Report
PublisherScottish Association for Marine Science


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