Report of the Benchmark Workshop on Deep-sea Stocks (WKDEEP)

The Benchmark Workshop on Deep-sea Stocks 2014 meet in Copenhagen, Denmark at ICES HQ during 3–7 February 2014. The main goal of the benchmark workshop meeting was to evaluate the appropriateness of stock assessment data and methods for the following ICES stocks: Blue ling in Division Vb, and Subare...

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Bibliographic Details
Main Author: ICES (11907872)
Format: Report
Language:unknown
Published: 2015
Subjects:
Online Access:https://doi.org/10.17895/ices.pub.19283132.v1
Description
Summary:The Benchmark Workshop on Deep-sea Stocks 2014 meet in Copenhagen, Denmark at ICES HQ during 3–7 February 2014. The main goal of the benchmark workshop meeting was to evaluate the appropriateness of stock assessment data and methods for the following ICES stocks: Blue ling in Division Vb, and Subareas VI, VII; Ling in Division Va; Black scabbardfish (Aphanopus carbo) in Subareas VI, VII and Divisions Vb and XIIb; Black scabbardfish (Aphanopus carbo) in Subareas VIII and IX; Black scabbardfish (Aphanopus carbo) in other areas (Subareas I, II, IV, X, XIV and Divisions IIIa, Va). The benchmark focused on compiling and evaluating data sources for stock assessment of mentioned stocks, evaluate the assessment models suitable to provide information on the stocks status and to update the relevant stock annexes to provide a comprehen-sive description of the agreed procedure for generating the assessment. For black scabbard fish it was decided to produce a join assessment for all three stocks as they were considered to be part of a unique single stock that migrates through the Northeast Atlantic and a HCR was agreed. For Ling in Va, new ageing of Icelandic survey data was incorporated into a new Gadget model to derive estimates of FMSY proxies. For blue ling in Division Vb, and Subareas VI, VII, a multiyear catch curve model (MYCC) was used to estimate the total annual mortality, a stock reduction analysis (SRA) was used to predict the biomass dynamics of the stock and a yield-per-recruit model is used to estimate reference points.