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Proceedings 2024/042

Proceedings of the Regional Peer Review on the Multi Species Stock Assessment Framework for Great Slave Lake; March 14–15, 2023

Chairperson: Joclyn Paulic

Editor: Kayla Gagliardi

Summary

A Canadian Science Advisory Secretariat (CSAS) Regional Peer Review Process on a Multi Species Stock Assessment Framework for Great Slave Lake (GSL) was held March 14–15, 2023 as a hybrid in-person/virtual meeting. The fisheries of GSL are dominated by three species, Lake Whitefish (Coregonus clupeaformis), Lake Trout (Salvelinus namaycush) and Inconnu (Stenodus leucichthys). Expansion of the fisheries is expected in the near future and the development of an Integrated Fisheries Management Plan (IFMP) is critical for the long-term management of lake fisheries. Due to these initiatives and other existing pressures on the fishery, DFO Science has been asked to provide robust advice on the stock status for GSL fisheries to support the establishment of sustainable harvest levels and limit reference points for each of the three dominant species.

Due to challenges in the acquisition of data for GSL (e.g., funding, sufficient personnel, logistics) and data management, the quantitative approach to conducting a stock assessment is uncertain. Additionally, rapid development of alternative quantitative modeling techniques over the last ten years, especially in the area of data-limited assessment, could provide new opportunities. As a first step to the stock assessments, Science will explore the availability of monitoring data, and examine the feasibility of well-fit quantitative modeling approaches for each stock. The recommendations from this meeting will form the basis for the selection of candidate models that are well supported by the available information for each stock and ultimately generate a set of reference points for each of the three fish species.

The objectives of this peer-review meeting were to: 1) compile Lake Whitefish, Lake Trout and Inconnu harvest, abundance indicators, and biological/demographic parameters from GSL; 2) peer review compiled data and make decisions on datasets which are potentially able to support data requirements for full or data-limited quantitative assessments based on data quality; 3) explore the potential to apply various quantitative assessment models ranging from indicator-based assessments to full data rich stock assessment options; and, 4) select the appropriate models that will be used for the full stock assessment of each species and list assumptions and caveats with the use of the models.

This Proceedings report summarizes the relevant discussions and presents key conclusions reached during the meeting. The models chosen for each species were: Pella-Tomlinson to structure Bayesian-based Surplus Production Models (SPMs) by JABBA for Lake Whitefish, CMSY++ , Bayesian state-space implementation of the Schaefer surplus production model (BSM), Stock Synthesis (SS) for Inconnu, and CMSY++ , Bayesian state-space implementation of the Schaefer surplus production model (BSM) for Lake Trout.

Additional publications from this process will be posted on the DFO Canadian Science Advisory Secretariat website as they become available.

Accessibility Notice

This document is available in PDF format. If the document is not accessible to you, please contact the Secretariat to obtain another appropriate format, such as regular print, large print, Braille or audio version.

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