Impacts of seasonal stock mixing on the assessment of Atlantic cod in the Gulf of Maine

Atlantic cod (Gadus morhua) in the Northwest Atlantic off New England and southern Atlantic Canada exhibit a complex population structure. This region has three independently assessed stocks [Georges Bank, Gulf of Maine (GOM), and the 4X stock], all of which are known to mix with each other. Assessm...

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Bibliographic Details
Published in:ICES Journal of Marine Science
Main Authors: Cao, Jie, Truesdell, Samuel B., Chen, Yong
Format: Article in Journal/Newspaper
Language:English
Published: Oxford University Press (OUP) 2014
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Online Access:http://dx.doi.org/10.1093/icesjms/fsu066
http://academic.oup.com/icesjms/article-pdf/71/6/1443/29147215/fsu066.pdf
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Summary:Atlantic cod (Gadus morhua) in the Northwest Atlantic off New England and southern Atlantic Canada exhibit a complex population structure. This region has three independently assessed stocks [Georges Bank, Gulf of Maine (GOM), and the 4X stock], all of which are known to mix with each other. Assessments of these stocks, however, assume no interpopulation mixing. Using simulations, we evaluated impacts of ignoring mixing resulting from seasonal migrations on the GOM assessment. The dynamics of the three stocks were simulated according to different scenarios of interstock mixing, and a statistical catch-at-age stock assessment model was fitted to the simulated GOM data with and without mixing. The results suggest that, while mixing causes measurable bias in the assessment, under the conditions tested, this model still performed well. Of the bias that does exist, spawning-stock biomass estimates are relatively sensitive to mixing compared with estimates of recruitment and exploitation rate. The relative timing of seasonal migration of the three stocks plays a critical role in determining the magnitude of bias. The scale and trends among years in the bias were driven by how representative the catch and survey data were for the GOM stock; this representation changed with the mixing rates.