Target-based catch-per-unit-effort standardization in multispecies fisheries

Abstract

Standardized catch per unit effort (CPUE) is a fundamental component of fishery stock assessment. In multispecies fisheries, catchability can differ depending on which species is being targeted, and so the yearly trend extracted from the standardized CPUE is likely to be biased. We have, therefore, developed a method for predicting the unobserved variable related to targeted species from among multispecies composition data using a mixture regression model for the transformed residuals. In contrast with traditional methods, the proposed method predicts the target variable in CPUE standardization without removing a subset of the data. Keeping the entire data set avoids information loss, and so CPUE standardization with the predicted target variable should yield an unbiased estimate of the yearly trend. Simple simulation tests demonstrate that our method outperforms traditional methods. We illustrate the use of our method by applying it to CPUE data on arabesque greenling (Pleurogrammus azonus) caught in multispecies trawl fisheries in Hokkaido, Japan.