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ICES Journal of Marine Science: Journal du Conseil Advance Access originally published online on October 25, 2006
ICES Journal of Marine Science: Journal du Conseil 2007 64(1):160-168; doi:10.1093/icesjms/fsl007
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© 2006 International Council for the Exploration of the Sea. Published by Oxford Journals. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Sensitivity analysis and parameter selection for detecting aggregations in acoustic data

Julian M. Burgos1 and John K. Horne1,2

1 University of Washington, School of Fishery and Aquatic Sciences, Box 35520, Seattle, WA 98355, USA
2 National Oceanic and Atmospheric Administration, National Marine Fisheries Service, Alaska Fisheries Science Center, 7600 Sand Point Way NE, Seattle, WA 98115, USA

Correspondence to J. M. Burgos: tel: +1 206 2216864; fax: +1 206 6857471; e-mail: jmburgos{at}u.washington.edu

Burgos, J. M., and Horne, J. K. 2007. Sensitivity analysis and parameter selection for detecting aggregations in acoustic data. ICES Journal of Marine Science, 64: 160–168.

A global sensitivity analysis was conducted on the algorithm implemented in the Echoview ® software to detect and describe aggregations in acoustic backscatter. Multiple aggregation detections were performed using walleye pollock (Theragra chalcogramma) data from the eastern Bering Sea. Walleye pollock form distinct aggregations and dense and diffuse layers. In each aggregation detection, input parameters defining minimum size, density, and distance to other aggregations were selected at random using a Latin hypercube sampling design. Sensitivity was quantified by testing for correlation among input parameters and a series of aggregation descriptors. In all, 336 correlation tests were performed, corresponding to a combination of seven detection input parameters, eight aggregation descriptors, and six transects. Among these, 181 tests were significant, indicating sensitivity between input parameters and aggregation descriptors. The aggregation-detection algorithm is sensitive to changes in threshold and minimum size, but less sensitive to changes in the connectivity criterion among aggregations.

Keywords: aggregations, echo-trace classification, sensitivity analysis, walleye pollock


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J. M. Burgos and J. K. Horne
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ICES J. Mar. Sci., October 1, 2008; 65(7): 1235 - 1247.
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