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P C Dauk

Publications and source records attributed to P C Dauk.

2 recordsLinked to original sources

Catch estimation in the presence of declining catch rate due to gear saturation.

One strategy for estimating total catch is to employ two separate surveys that independently estimate total fishing effort and catch rate with the estimator for total catch formed by their product. Survey designs for estimating catch rate often involve interviewing the fishermen during their fishing episodes. Such roving designs result in incomplete episode data and characteristically have employed a model in which the catch rate is assumed to be constant over time. This article extends the problem to that of estimating total catch in the presence of a declining catch rate due, e.g., to gear saturation. Using a gill net fishery as an example, a mean-of-ratios type of estimator for the catch rate together with its variance estimator are developed. Their performance is examined using simulations, with special attention given to effects of restrictions on the roving survey window. Finally, data from a Fraser River gill net fishery are used to illustrate the use of the proposed estimator and to compare results with those from an estimator based on a constant catch rate.

Animals↗

Catch estimation with restricted randomization in the effort survey.

One common method for estimating total catch is to multiply an estimate for CPUE, the catch per unit effort, by an estimate of total effort obtained from an independent second survey. In general, estimating total effort requires that sample times are chosen at random over the full fishing period; however, in practice, this may not always be possible and the usual estimator may be severely biased. Such a restriction in randomization is likely when aircraft are used to make instantaneous counts of fishing activity. This article proposes alternate estimators for use with both access and roving designs in conjunction with effort surveys for which sample times are not random. Ratio type estimators based on activity counts are developed under various scenarios and their performance examined under simulation. In addition, optimizing strategies for use with multiple activity counts are explored. Finally, data from an in-river gill net fishery on the Fraser River is used to illustrate these results.

Animals↗