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ICES Journal of Marine Science: Journal du Conseil Advance Access originally published online on February 12, 2009
ICES Journal of Marine Science: Journal du Conseil 2009 66(6):1197-1204; doi:10.1093/icesjms/fsp008
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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]

A Bayesian approach to estimating target strength

Sascha M. M. Fässler1, Andrew S. Brierley1 and Paul G. Fernandes2

1 Gatty Marine Laboratory, University of St Andrews, St Andrews, Fife KY16 8LB, Scotland, UK
2 FRS Marine Laboratory, PO Box 101, 375 Victoria Road, Torry, Aberdeen AB11 9DB, Scotland, UK

Correspondence to S. M. M. Fässler: tel: +44 1224 295538; fax: +44 1224 295511; e-mail: s.faessler{at}marlab.ac.uk

Fässler, S. M. M., Brierley, A. S., and Fernandes, P. G. 2009. A Bayesian approach to estimating target strength. – ICES Journal of Marine Science, 66: 1197–1204.

Currently, conventional models of target strength (TS) vs. fish length, based on empirical measurements, are used to estimate fish density from integrated acoustic data. These models estimate a mean TS, averaged over variables that modulate fish TS (tilt angle, physiology, and morphology); they do not include information about the uncertainty of the mean TS, which could be propagated through to estimates of fish abundance. We use Bayesian methods, together with theoretical TS models and in situ TS data, to determine the uncertainty in TS estimates of Atlantic herring (Clupea harengus). Priors for model parameters (surface swimbladder volume, tilt angle, and s.d. of the mean TS) were used to estimate posterior parameter distributions and subsequently build a probabilistic TS model. The sensitivity of herring abundance estimates to variation in the Bayesian TS model was also evaluated. The abundance of North Sea herring from the area covered by the Scottish acoustic survey component was estimated using both the conventional TS–length formula (5.34x109 fish) and the Bayesian TS model (mean = 3.17x109 fish): this difference was probably because of the particular scattering model employed and the data used in the Bayesian model. The study demonstrates the relative importance of potential bias and precision of TS estimation and how the latter can be so much less important than the former.

Keywords: acoustic target strength, Bayesian statistics, herring, survey uncertainty

Received 9 August 2008; accepted 7 November 2008; advance access publication 12 February 2009.


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