Working Group on Commercial Catches



WGCATCHWGCATCHTrueKarolina Molla GaziDSTSG11/29/2013 10:48:00 AMkarolina.mollagazi@wur.nl722Working Group on Commercial Catches

WGCATCH documents national fishery sampling schemes, establishes best practice and guidelines on sampling and estimation procedures, and provides advice on other uses of fishery data.

​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​​WGCATCH aims to bring together the best expertise in fishery data, sampling design and analysis available in ICES community.

Many ICES expert groups use data on fishery catches to describe fishing activities and evaluate the impacts of fisheries on stocks and ecosystems. Data are often the primary basis for reconstructing historical populations and estimating fishing mortality. Although often treated as exact, data are of variable quality. Reported landings may be inaccurate, and there is bias and uncertainty associated with sampling of catches. These translate into inaccuracies in advice. Confidence in the fishery data underpinning assessments and advice on sustainable fishing is vital, as it is to understand their limitations. 

Making sure that the data are collected using statistically-sound sampling designs is a key first step, and ICES has provided extensive guidelines on this through a wide range of groups dealing with the statistical and practical aspects of sampling catches. The work of all these groups forms the foundation for ICES Working Group on Commercial Catches (WGCATCH). 

The group documents national fishery sampling schemes, establish best practice and guidelines on sampling and estimation procedures, and provide advice on other uses of fishery data. The group also evaluates how new data collection regulations or management measures will alter how data need to be collected and provide guidelines about biases and disruptions this may induce in time series. WGCATCH also continues to develop and promote the use of a range of indicators of fishery data quality for different users. These include indicators to allow stock assessment and other ICES scientists to decide if data are of sufficient quality to be used, or how different data sets can be weighted in an assessment model according to their relative quality.​

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