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ICES Journal of Marine Science: Journal du Conseil Advance Access originally published online on May 19, 2009
ICES Journal of Marine Science: Journal du Conseil 2009 66(6):1136-1142; doi:10.1093/icesjms/fsp109
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© 2009 International Council for the Exploration of the Sea. Published by Oxford Journals. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

This article appears in the following ICES Journal of Marine Science issue: The Ecosystem Approach with Fisheries Acoustics and Complementary Technologies [View the issue table of contents]

Classifying fish schools and estimating their species proportions in fishery-acoustic surveys

Ronan Fablet1,2, Riwal Lefort1,2, Imen Karoui1, Laurent Berger2, Jacques Massé3, Carla Scalabrin2 and Jean-Marc Boucher1

1 Institut TELECOM, TELECOM Bretagne, UMR CNRS 3192 Lab-STICC, Technopôle Brest Iroise CS 83818, 29238 Brest Cedex 3, France, and Université européenne de Bretagne, France
2 Ifremer/STH, BP 70 29280, Plouzané, France
3 Ifremer/EMH, Nantes, France

Correspondence to R. Fablet: tel: +33 229 001 287; fax: +33 229 001 012; e-mail: eronan.fablet{at}telecom-bretagne.eu.

Fablet, R., Lefort, R., Karoui, I., Berger, L., Massé, J., Scalabrin, C., and Boucher, J-M. 2009. Classifying fish schools and estimating their species proportions in fishery-acoustic surveys. – ICES Journal of Marine Science, 66: 1136–1142.

Automated or computer-assisted tools are needed for estimating the proportion of species and their biomass in echosounder surveys of marine ecosystems. Operational systems rely mainly on school morphologies or the frequency responses of scatterers to identify target species in echograms. This paper presents two complementary methods for classifying schools and estimating their species proportion in a multispecies, pelagic environment. One method relies on the training of probabilistic school classifiers; the other exploits echogram similarities to infer species proportions directly from the proportions known at trawled sites. The methods are demonstrated with empirical and simulated data. School classifications and species-proportion estimates are compared to demonstrate the effectiveness of the proposed methods.

Keywords: fisheries acoustics, multispecies environment, school classification

Received 8 August 2008; accepted 19 February 2009; advance access publication 19 May 2009.


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