Abstract

Catch-per-unit-effort (CPUE) is frequently used as a measure of relative abundance in fisheries stock assessment. Determining reliable estimates of species-specific CPUE is more challenging in multispecies, rather than single-species, fisheries because identification of appropriate effort data for each species is often difficult. Divers in the South Australian abalone fishery can harvest blacklip (Haliotis rubra) and greenlip (Haliotis laevigata) abalone simultaneously, but report only a single value for daily fishing effort. This is problematic because total allowable commercial catches are set for each species following species-specific stock assessments in which CPUE is a key index of relative abalone abundance. To provide an evidence-based approach to the identification of the most appropriate CPUE estimation method for ongoing assessment of the fishery, we assessed six diverse CPUE estimation methods for estimating annual, species-specific CPUEs using 30 y of data. The candidate CPUE estimation methods yielded relative CPUE time series with similar temporal trends throughout the 30-y period. These relative CPUE estimates each had low coefficients of variation and were highly correlated with one another, requiring consideration of other factors to determine a preferred method. Using a catch-weighted estimate of CPUE (CPUEwt) overcomes many of the problems associated with using the other five methods tested. Specifically, CPUEwt (1) weights each daily catch and effort objectively; (2) removes the need to “subset” the data subjectively, which ensures that data availability and representation are not reduced by arbitrary rules; and (3) is relatively simple to explain to stakeholders and can be applied consistently to greenlip and blacklip abalone at multiple spatial scales across the fishery. Although the requirement to estimate species-specific catch rates in mixed-species dive fisheries is rare, our analyses demonstrate that CPUEwt could provide a robust measure of species-specific CPUEs across other diverse multispecies fisheries.

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