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ICES Journal of Marine Science: Journal du Conseil Advance Access originally published online on May 2, 2009
ICES Journal of Marine Science: Journal du Conseil 2009 66(6):1111-1118; doi:10.1093/icesjms/fsp119
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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]

Acoustic species identification of schooling fish

Rolf J. Korneliussen1, Yngve Heggelund2, Inge K. Eliassen2 and Geir O. Johansen1

1 Institute of Marine Research, PO Box 1870 Nordnes, N-5817 Bergen, Norway
2 Christian Michelsen Research AS, PO Box 6031, N-5892 Bergen, Norway

Correspondence to R. J. Korneliussen: tel: +47 55 23 85 00 (6853); fax: +47 55 23 85 84; e-mail: rolf{at}imr.no.

Korneliussen, R. J., Heggelund, Y., Eliassen, I. K., and Johansen, G. O. 2009. Acoustic species identification of schooling fish. – ICES Journal of Marine Science, 66: 1111–1118.

The development of methods for the acoustic identification of fish is a long-term objective aimed at reducing uncertainty in acoustic-survey estimates. The relative frequency response r(f) measured simultaneously at several frequencies is one of the main acoustic features that characterize the targets, but the relationship between nearest neighbours, school morphology, and environmental and geographical data are also important characteristics in this context. The number of acoustic categories that can be separated with a high spatial resolution is limited by the stochastic nature of the measurements. Because the acoustic categorization of larger ensembles is more reliable than for single targets, spatial smoothing of the backscattering within the school boundaries before that process allows the separation of more categories than is possible with the raw, highly resolved data. Using the mean r(f) of an entire school gives even more reliable categorization, but determining whether or not the school is monospecific sets a new challenge. This problem is evaluated here. The methods are tested and verified. Identification of acoustic categories with similar acoustic properties is done for schooling fish, although the results have limited spatial resolution. The reliability of the categorization is further improved when knowledge of school morphology and geographical distribution of the species are taken into account.

Keywords: categorization, relative frequency response, school morphology

Received 8 August 2008; accepted 26 February 2009; advance access publication 2 May 2009.


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