Project number: 2012-201
Project Status:
Completed
Budget expenditure: $302,753.80
Principal Investigator: Geoff Tuck
Organisation: CSIRO Oceans and Atmosphere Hobart
Project start/end date: 31 Oct 2012 - 11 Jan 2015
Contact:
FRDC

Need

Catch rates are important as the only index of relative abundance in most Australian fisheries. Numerous projects have attempted to improve catch rate standardization in multi-species fisheries but there remains no agreed robust method. Another study of alternative applications of GLMs or GAMs, etc, is unlikely to resolve the issue because the multi-species nature of many of Australia’s fisheries has always overwhelmed attempts at determining targeting behaviour solely from logbook data. There is therefore a need to analyse the problem of targeting and standardization using techniques akin to Management Strategy Evaluation such that standardization strategies can be compared in an environment where the underlying trends in a multi-species fishery being standardized are known.

This is becoming more critical as recent large scale management initiatives (HSP) are beginning to influence how fishers operate and this is changing the character of catch rates. Some species are being actively avoided, which gives a false impression of stock decline; the bias would always be downwards. This obfuscation of catch rates will eventually threaten our ability to assess the stocks appropriately in the absence of a time series of Fishery Independent Surveys. There is a need to understand the extent of this problem and what can be done to mitigate against incorrect assessments of stock status.

There is a need to use available survey information in addition to the use of logbooks to provide a strong test of methods. Additionally, there is a need to simulate catch rate data realistically so that different methods can be subject to stringent testing. This would have wide national and international value.

Objectives

1. Review the most appropriate catch rate standardisation strategies when targeting is well defined in multi-species fisheries.
2. Compare alternative catch rate standardization strategies in those fisheries where both fishery independent and fishery dependent data are available.
3. After modifying Atlantis SE, simulate shot-by-shot commercial catch rate data and use this in simulation tests for the most robust standardization strategies in mixed fisheries when targeting is unknown and management interventions influence catch rates.
4. Use simulated catch rate data to conduct MSE testing of the influence of potential biased data and standardization strategies on the outcome of stock assessments that rely on catch rate trends and targets.
5. Use simulated catch rate data to test the potential influence of effort creep (technical improvements in fishing power) on stock assessments.
6. Based on the results of objectives 1 to 5 write a reference manual on the application of the most robust CPUE standardization strategies for Australian fisheries.

Final report

ISBN: 978-1-4863-0834-7
Authors: Malcolm Haddon Rik Buckworth Natalie Dowling George Leigh David C. Smith
Final Report • 2020-01-01 • 5.07 MB
2012-201-DLD.pdf

Summary

In Australia many stock assessments are dependent upon catch-per-unit-effort (CPUE) to act as an index of relative abundance of fished stocks through time. But CPUE trends can be affected by many factors other than just stock size changes. Around Australia, and internationally, numerous and disparate approaches are used to conduct standardiza-tions of CPUE using statistical methods to account for the effects of these other factors (e.g. the effect of which vessel is fishing, and where and when it is fishing). The objec-tive in all cases is to discover trends in the CPUE that better reflect how the stock’s rela-tive abundance is changing through time rather than reflecting changes in the fisher’s behaviour. In attempts to improve how such analyses are conducted and reported in Australia, stock assessment scientists from CSIRO and Queensland DPI explored an ar-ray of different aspects of CPUE standardizations. The overall aim was to generate a se-ries of recommendations to act as a guide or a set of suggestions when it becomes nec-essary to use CPUE data in a stock assessment.

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