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Classification of fish schools based on evaluation of acoustic descriptor characteristics

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Abstract

Acoustic surveys were conducted from 2002 to 2006 in the East China Sea off the Japanese coast in order to develop a quantitative classification typology of a pelagic fish community and other co-occurring fishes based on acoustic descriptors. Acoustic data were postprocessed to detect and extract fish aggregations from echograms. Based on the expert visual examination of the echograms, detected schools were divided into three broad fish groups according to their schooling characteristics and ethological properties. Each fish school was described by a set of associated descriptors in order to objectively allocate each echo trace to its fish group. Two methods of supervised classification were employed, the discriminant function analysis (DFA) and the artificial neural network technique (ANN). We evaluated and compared the performance of both methods, which showed encouraging and about equally highly correct classification rates (ANN 87.6%; DFA 85.1%). In both techniques, positional and then morphological parameters were most important in discriminating among fish schools. Fish catch composition from midwater trawling validated the fish group classification through one representative example of each grouping. Both methods provided the essential information required for assessing fish stocks. Similar techniques of fish classification might be applicable to marine ecosystems with high pelagic fish diversity.

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Acknowledgments

We are grateful to Dr. Hiroshige Tanaka (Fisheries Research Agency) for data collection, and Dr. Tadanori Fujino and Dr. Kazushi Miyashita (University of Hokkaido) for data analysis initiation. Thanks are due to Dr. Vidar Wespestad (University of Alaska Fairbanks), Dr. Hideaki Tanoue and Dr. Teruhisa Komatsu (University of Tokyo) for providing advice at various stages of the work. We thank Dr. Takaomi Kaneko for his thorough editorial assistance.

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Authors and Affiliations

  1. Graduate School of Agriculture and Life Science, University of Tokyo, Bunkyo, Tokyo, 113-8657, Japan

    Aymen Charef & Ichiro Aoki

  2. Seikai National Fisheries Research Institute, Fisheries Research Agency, Nagasaki, 851-2213, Japan

    Seiji Ohshimo

  3. Ocean Research Institute, University of Tokyo, Nakano, Tokyo, 164-8639, Japan

    Natheer Al Absi

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  1. Aymen Charef
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  2. Seiji Ohshimo
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  3. Ichiro Aoki
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  4. Natheer Al Absi
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Correspondence to Aymen Charef.

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Charef, A., Ohshimo, S., Aoki, I. et al. Classification of fish schools based on evaluation of acoustic descriptor characteristics. Fish Sci 76, 1–11 (2010). https://doi.org/10.1007/s12562-009-0186-x

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  • DOI: https://doi.org/10.1007/s12562-009-0186-x

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