Integration of tagging and population dynamics models in fisheries stock assessment

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Integration of tagging and population dynamics models in fisheries stock assessment

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Title: Integration of tagging and population dynamics models in fisheries stock assessment
Author: Maunder, Mark Nicholas
Abstract: An integrated tagging and population dynamics model is developed, tested, and applied to the SNA1 snapper (Pagrus auratus) stock off the east coast of the North Island of New Zealand. An Integrated Model (IM) is a model that combines two analyses that are usually carried out separately into one analysis, by incorporating the raw data directly into the fitting procedure of the population dynamics model. When tagging data is integrated with a catch-at-age model, it is called an Integrated Tagging and Catch-at-Age ANalysis (ITCAAN). The integrated approach has a number of advantages over traditional methods: it includes all information from the data, standardizes dynamics and parameters for all analyses, automatically incorporates correlation between parameters, allows detailed investigation of the model fit, and allows the incorporation of any dynamics. The main disadvantage of the integrated modeling approach is the complexity of the models needed to implement it. This complexity can lead to confounding between parameters, problems with model misspecification, and high computational demands. Movement between sub-stocks is a main dynamic that is included in the models used in this dissertation. Incorporation of movement in the analysis is very important, if management of individual sub-stocks is required. The results of the Integrated Model applied to the SNA1 snapper stock are more pessimistic than results from the current assessment. The initial fishing mortality rate in 1970 is a critical parameter of the model, and model misspecification caused problems in estimating this parameter. The integrated modeling approach can be applied to a number of other applications in fisheries and other fields.
Description: Thesis (Ph. D.)--University of Washington, 1998
URI: http://hdl.handle.net/1773/5284

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