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Effects of population size/age structure, condition and temporal dynamics of spawning on reproductive output in Atlantic cod (Gadus morhua)

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ECOLOGICAL MODELLING
卷 191, 期 3-4, 页码 383-415

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ELSEVIER
DOI: 10.1016/j.ecolmodel.2005.05.015

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Gadus morhua; cod; egg quality; fish condition; individual-based modelling; population structure; stock reproductive potential

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In this study, we model daily reproductive output over an entire spawning season for a range of simulated age/size-structured populations of Atlantic cod (Gadus morhua), which are created under contrasting stock-recruitment and fishing pressure scenarios. An individual-based modelling approach is used to link empirical relationships with flexible reproductive parameters to quantify and qualify the effects that individual female condition and egg quality can have on stock reproductive potential (SRP) and the temporal distribution of reproductive output. The results of this study indicate that, even with a set of steady state populations that have equal spawning stock biomass (SSB), the differences in population structure brought about by a difference of fishing mortality (F) from 0 to 1.0 will substantially reduce the SRP. Compared to a non-fished population the decline in SRP will range from 48 to 74%, depending upon respective assumptions of egg size on viability. The truncation of population age/size structure due to fishing mortality will also lead to a 4 weeks shorter spawning season and a 2 weeks shift in the date of peak spawning. The effect of low condition of individuals can lead to almost total reproductive failure for the population and the effect of increased condition is dependent upon the population structure in question. Results as such support the view that predictions of recruitment can no longer be based solely as a function of SSB. More careful analysis of the population structure as well as annual dynamics of condition factors and exploration of functional relationships between female characteristics and egg quality are needed to assess and accurately predict survival and the probability of recruitment levels. (c) 2005 Elsevier B.V. All rights reserved.

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