The goal of the work was to maximize the accuracy of standardized catch per unit effort as an index of relative abundance. Linear regression models were fitted to daily logbook data from a multispecies penaeid trawl fishery in which within-vessel changes in effi- ciency are common. Two model-fitting strategies were compared. The predictive strategy focused on maximizing the explained var- iance, and the estimation strategy on finding realistic coefficients for important components of changing catchability. Realistic values could not always be obtained, because the regression factors were not orthogonal, and data on the presence of technology were some- times unreliable or systematically incomplete. It was not possible to separate fishing power from abundance by analysing logbook data alone; it was necessary to incorporate external information within the standardization model. Therefore, the resultant estimation models incorporated external information and expert knowledge by offsets. There was no single best estimation model. Instead, a series of models provided an envelope of possible changes in relative fishing power and prawn abundance since 1970. Compared with the prediction models, the estimation models revealed different trends in relative fishing power and relative abundance.
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