Improvement to the stock assessment of witch flounder in NAFO 3N+3O division

Chen, Jiaying (2022) Improvement to the stock assessment of witch flounder in NAFO 3N+3O division. Masters thesis, Memorial University of Newfoundland.

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Abstract

Traditional stock assessment models rely on statistical fitting to abundance indices, fishery catch and age-length-maturation data. Aging information is essential as it determines the growth function, maturity schedule and mortality. For many hard-to-age stocks, it is challenging in fisheries stock assessment to estimate cohort dynamics and fishing mortality at length from length-based data with existing approaches, e.g. age-based catch-at-length model (ACL). An age and length structured statistical catch-at-length model (ALSCL) has been developed for groundfish species that are hard to age. At the same time, abundance indices from scientific surveys as the core input for stock assessment can be standardized by various different ways. Therefore, it is essential to compare the efficiency of those approaches to find the best method to standardize the indices. In this study, I focus on improving the stock assessment of an important commercial stock of witch flounder in NAFO 3N+3O division. I first use a traditional design-based way and a spatiotemporal model to standardize length composition data from government surveys. Specifically, I compare the uncertainty between design-based and model-based indices for each length bins. I then apply ALSCL and ACL models to the length composition data standardized using the design-based and model-based estimators in the previous step to estimate the age-based population dynamics for NAFO Div. 3NO witch flounder.

Item Type: Thesis (Masters)
URI: http://research.library.mun.ca/id/eprint/15654
Item ID: 15654
Additional Information: Includes bibliographical references.
Keywords: witch flounder, stock assessment, population dynamics, data standardization
Department(s): Marine Institute > School of Fisheries
Date: June 2022
Date Type: Submission
Digital Object Identifier (DOI): https://doi.org/10.48336/3KJ5-HS72
Library of Congress Subject Heading: Glyptocephalus cynoglossus; Fish stock assessment; Fish populations; Northwest Atlantic Fisheries Organization

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