Journal Article

The fuzzy relationship between trawl and acoustic surveys in the North Sea

Steven Mackinson, Jeroen van der Kooij and Suzanna Neville

in ICES Journal of Marine Science

Published on behalf of ICES/CIEM

Volume 62, issue 8, pages 1556-1575
Published in print January 2005 | ISSN: 1054-3139
Published online January 2005 | e-ISSN: 1095-9289 | DOI: http://dx.doi.org/10.1016/j.icesjms.2005.06.007
The fuzzy relationship between trawl and acoustic surveys in the North Sea

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Adding information on the horizontal and vertical distribution of fish both on and between trawl stations is reason enough to perform acoustic surveys routinely in tandem with annual groundfish trawl surveys. Ideally, acoustic and trawl density indices could be combined to maximize information on fish distribution and provide more reliable estimates of stock size. The core of the problem boils down to the question: “how does what we see on an echosounder relate to what we catch in a net?” The fuzzy logic “model-free estimation” approach presented here sidesteps the need to understand specific mechanisms that determine the nature and variability of any relationship between acoustics and trawl catches. Fuzzy logic models that describe and predict the relationship linking acoustics and environmental variables (inputs) with trawl catches (output) are developed, and the sensitivities and robustness of the approach are discussed. In the models examined, the static environmental variables location and depth proved to be better predictors of trawl catches in the North Sea than the acoustic energy in the first 5 m off the bottom. We suggest that finding the “hidden” relationship between acoustics and trawls will require closer attention to partitioning the acoustics data by species/assemblages and understanding the key gear and behavioural differences responsible for producing the high between-gear variability.

Keywords: acoustic survey; fuzzy logic; groundfish; North Sea; trawl survey

Journal Article.  8277 words.  Illustrated.

Subjects: Environmental Science ; Marine and Estuarine Biology

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