Assessing a data-limited horse mackerel stock using the Gadget modelling framework

Over the past years, fisheries stock assessment in Angola has been done using cohort analysis in a yield-per recruit, and Schaefer surplus production model. Lack of biological data such as sex, size and age-based differences in these models limits a holistic view of the dynamics of the fish stock po...

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Bibliographic Details
Main Author: Victor Wendulika Agostinho 1991-
Other Authors: Háskóli Íslands
Format: Thesis
Language:English
Published: 2021
Subjects:
Online Access:http://hdl.handle.net/1946/37554
Description
Summary:Over the past years, fisheries stock assessment in Angola has been done using cohort analysis in a yield-per recruit, and Schaefer surplus production model. Lack of biological data such as sex, size and age-based differences in these models limits a holistic view of the dynamics of the fish stock population. Therefore, the Gadget modelling framework was used to build a stock assessment model to analyse the horse mackerel stock along the Angolan coast. A time-series survey data collected onboard of R/V DR. FRIDTJOF NANSEN and commercial catch data consisting of sex, maturity, gear, and length distribution was used to assess the stock. As the model is size and age-structured it is able to integrate various disparate data sets and thus is able to provide insights into the population dynamics. The main objective of the project was to investigate the feasibility of assessing the horse mackerel stock using the age-length Gadget modelling framework in order to: 1. Provide an estimate of the absolute biomass and thus improve advice on exploitation; 2. Define short- and long-term projections from the model; 3. Set biological and management reference points. The model showed a bad fit due to inconsistent data. This highlights the need for further data exploration. However, it seems to capture some of the trends in the larger length groups. Overall, the Gadget modelling framework proved to be a feasible tool to assess the stock dynamics of horse mackerel data. GRÓ Fisheries Training Program