Integrating environmental impacts on stocks in Management Strategy Evaluation models

Joint ICES-SEAwise Course – Ecological Effects on Fisheries

Integrating environmental impacts on stock productivity in Management Strategy Evaluation models

Date: 25-27 November 2024

Location: Online

Registration deadline: 11 November

 

 

Recognised as a key aspect of Ecosystem Based Fisheries Management (EBFM), environmental factors can have a profound impact on the productivity of fish stocks. As part of our Ecological Effects on Fisheries work theme, SEAwise has worked to improve our understanding of these effects and our ability to predict their potential long-term impacts, in an effort to enhance fisheries management advice.

Most commonly conducted as single-species analyses, Management Strategy Evaluations (MSEs) can also address mixed-fisheries objectives using multi-stock and multi-fleet operating models. SEAwise has worked to further develop such models so they can be used to define and evaluate management strategies that address broad ecosystem-based fisheries management (EBFM) objectives, including identifying Harvest Control Rules (HCRs) that are robust to productivity changes. 

As part of this, a key deliverable of the project has been the development of robust and consistent environment-productivity relationships for commercial fish stocks across selected case studies, which can be integrated in MSE models. 

Drawing on this, this course will consist of practical sessions based on the advancement of work in this regard across SEAwise’s case studies in the: Baltic Sea, North Sea, Western Waters, and central Mediterranean Sea. 

The course will cover the following topics: 

(1) Environmental data preparation;

(2) Covariate selection;

(3) Model fitting: statistical vs. mechanistic;

(4) Model evaluation & validation;

(5) Projection and;

(6) Communication of assumptions. 

 

Models: The MSE models used include FLBEIA and BEMTOOL.

Level: General knowledge about stock assessment and MSE models, as well as experience with FLR and R would be helpful.

For more information and to register click here.

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