Monitoring changes in abundance of gadoids with varying availability to trawl and acoustic surveys

• Published in: ICES Journal of Marine Science
• Main Authors: Godø, Olav Rune, Wespestad, Vidar G.
• Format: Text
• Language: English
• Published: Oxford University Press 1993
• Subjects: Articles; Svalbard; North East Atlantic
• Online Access: http://icesjms.oxfordjournals.org/cgi/content/short/50/1/39; https://doi.org/10.1006/jmsc.1993.1005

The use of scientific survey data for assessing abundance of commercially important fish stocks has become a managerial necessity in many regions. Errors and bias in estimates from such surveys may thus have great economic impact. In the north-east Atlantic, abundance of cod has been estimated from bottom trawl surveys and acoustic surveys since 1981. In the Svalbard area, abundance indices derived from acoustic and bottom trawl surveys have differed considerably with discrepancies varying from year to year. At low stock abundance and particularly when the population is comprised of young fish, cod are distributed close to bottom and are thus optimally located for a bottom trawl survey, but are poorly recorded by the acoustic technique. In contrast, when abundant year-classes attain an age of 2–3 years and older, they are more pelagically distributed and clearly available for acoustic observation. Dependency on only one of the survey techniques could lead to severely biased stock estimates. A combination of estimates from the two methods is at present hindered by the lack of an absolute estimate of abundance, and by uncertainty in the actual volume sampled due to movement of fish during survey sampling. The vertical profile of the acoustic recordings and size composition and density of the population are factors which will affect fish availability to the two survey techniques differently. Such variation in availability seems to affect gadoid surveys in general. With a limited amount of additional effort changes in availability and selectivity can be monitored during the survey, and observed changes can be incorporated into analyses to compensate for potential bias due to variation in these parameters.