Onboard sampling for measuring discards in commercial fishing based on multilevel modelling of measurements for the Irish Sea from NW England and N Wales

Duncan Tamsett, Gareth Janacek, Mike Emberton, William Lart, Grant Course

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A method for onboard sampling of discards developed for the North Sea was found to be unsatisfactory in the Irish Sea. An alternative method for the Irish Sea provided data between August 1993 and September 1994 on discarding rates at the haul and within-haul levels, as well as the trip level (the lowest level for which data are available from the method used in the North Sea). The data are subjected to multilevel analysis of variance to measure components of variance associated with fishing and environmental parameters.

Discarding rates at the haul level are affected by distance from the coast and duration of haul. Within-haul estimates of discarding rates are analysed for evidence that estimates from samples of catches for hauls are over-dispersed (relative to the dispersion associated with binomially distributed discarding rates). This has a bearing on the optimal size that samples of catches for hauls should be. No evidence for over-dispersion is found for the Irish Sea for which the data set with within-haul data is small. However, analysis of a data set from the English Channel for which there is a greater volume of data at the within-haul level, has indicated significant and sizeable over-dispersion.

An approach is outlined for calculating the optimal size that samples of catches for hauls should be for estimating discarding rates as a function of year class, and taking account of over-dispersion. Optimal sample sizes are surprisingly small. This might render practicable the acquisition of samples of hauls by fishermen in the absence of an onboard technician for analysis by technicians post-trip.
Original languageEnglish
Pages (from-to)117-126
Number of pages9
JournalFisheries Research
Issue number1-2
Publication statusPublished - Aug 1999



  • Fish discards
  • Stratification
  • Components of variance
  • Multilevel models

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