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Título

Modeling Fish Egg Production and Spatial Distribution from Acoustic Data: A Step Forward into the Analysis of Recruitment

AutorOspina-Álvarez, Andrés CSIC ORCID ; Bernal, Miguel CSIC; Catalán, Ignacio Alberto CSIC ORCID ; Roos, David; Bigot, Jean-Louis; Palomera, Isabel CSIC ORCID
Fecha de publicaciónsep-2013
EditorPublic Library of Science
CitaciónPLoS ONE 8(9): e73687 (2013)
ResumenTo date, there are numerous transport simulation studies demonstrating the relevance of the hydrodynamics for the advection, dispersion and recruitment of early stages of marine organisms. However, the lack of data has conditioned the use of realistic locations for the model setup and configuration in transport studies. This work (I) demonstrates the key role played by the use of the realistic initial position of the eggs of small pelagic fishes in the analysis of late-larval recruitment in coastal nursery areas and (II) provides a general solution for deriving future egg positions and abundances from adult biomass obtained from acoustic surveys and available fecundity data. Using European anchovy in the NW Mediterranean as a case study, we first analyzed the impact of the initial location, timing, egg buoyancy and diel vertical migration of larvae on the potential late-larval recruitment to coastal areas. The results suggested that prior knowledge of the initial spawning grounds may substantially affect the estimates of potential recruitment. We then integrated biological and acoustics-derived data (the biomass and size structure, sex ratio, a weight-batch fecundity model, mean weight, number of fish and mean spawning) to build a predictive model for interannual egg production. This model was satisfactorily contrasted with field data for two years obtained with the Daily Egg Production Method (DEPM). We discuss our results in the context of the fluctuations of European anchovy egg abundance from 2003 through 2010 in the NW Mediterranean and in terms of the potential applicability of the acoustics-based spatial predictive egg production model
Descripción18 pages, 11 figures, 6 tables
Versión del editorhttps://doi.org/10.1371/journal.pone.0073687
URIhttp://hdl.handle.net/10261/84287
DOI10.1371/journal.pone.0073687
ISSN1932-6203
E-ISSN1932-6203
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