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Catch-per-unit-effort: which estimator is best?

M Petrere¹, H C Giacomini, P De Marco

¹Departamento de Ecologia, Universidade Estadual Paulista Júlio de Mesquita Filho, Rio Claro, SP, Brazil. mpetrere@rc.unesp.br

Brazilian Journal of Biology = Revista Brasleira De Biologia

|August 26, 2010

Summary

This summary is machine-generated.

This study evaluates catch-per-unit-effort (CPUE) indices using simulations. The Jackknife approach is recommended for accurate fishery stock assessments, especially when catch is proportional to effort.

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Area of Science:

Fisheries science
Quantitative ecology
Statistical modeling

Background:

Accurate estimation of fish stock abundance is crucial for sustainable fisheries management.
Catch-per-unit-effort (CPUE) is a widely used index for assessing relative abundance.
The reliability of CPUE indices depends on underlying assumptions about catch data and effort proportionality.

Purpose of the Study:

To assess the accuracy and precision of three different catch-per-unit-effort (CPUE) indices.
To evaluate the performance of CPUE indices under various data-generating scenarios.
To provide recommendations for robust CPUE index selection in fisheries research.

Main Methods:

Simulations were conducted using catch data generated from six probability distributions (normal, Poisson, lognormal, gamma, delta, negative binomial).
Three distinct variance structures (constant, proportional to effort, proportional to squared effort) were simulated.
The accuracy and precision of CPUE indices were analyzed under varying magnitudes and tail weights of the simulated data.

Main Results:

The study identified significant variations in the accuracy and precision of different CPUE indices based on the simulated data characteristics.
The Jackknife approach demonstrated superior performance under conditions of catch proportionality to effort.
Deviations from the proportionality assumption impacted index performance, with the Jackknife showing resilience to minor deviations.

Conclusions:

The Jackknife approach is recommended for estimating CPUE indices, particularly when catch is proportional to effort or exhibits minor deviations from this assumption.
This method offers a robust ratio estimator suitable for situations with limited knowledge of underlying variable behavior, common in fisheries.
The findings support the use of the Jackknife method for improving the reliability of stock assessments in diverse fishery contexts.