1. Research outline for CPUE data used in WCPO stock assessments
Simon Hoyle
SPC

2. Introduction
Longline CPUE data drive abundance trends for bigeye, yellowfin, and albacore assessments
There are conflicts between CPUE and size data trends
We have all been aware for some time of the need to improve methods for analyzing CPUE data
Highlighted by the recent YFT reviews
Progress has been made – ‘more work is needed’

3. Background Long history of analyzing CPUE data to estimate abundance
Various approaches have been used, including habitat- based standardization (HBS), statistical HBS, and standardization that includes oceanographic effects
The current approach focuses on standardizing out spatial and HBF effects, to extract a year-quarter effect as the index of abundance
Developments are under way towards using operational data instead of aggregated data

4. Recommendations from past work
Numerous recommendations in many areas, summarized in the research outline document
Regional weighting
Modeling approaches
Spatial effects and data weighting
Targeting, fishing behavior and catchability
Covariates and data resolution
Data
Model selection

5. Proposed work areas 1 Weighting given to different strata
Weights given to individual records affect abundance trends
Aggregated analyses give each stratum the same weight, while operational data analyses give each set the same weight
This is a statistical problem that can have a surprisingly large effect on the indices
Related to issue of error distributions
better approaches are available than the current delta lognormal

6. Proposed work areas 2
Hidden assumptions about abundance trends in areas not fished early or late
Classic problem – what is the abundance in areas not being fished
Approaches are available – spatial backfilling to infer abundance
Related to issues of spatial stratification, consistency of abundance trends among areas, and range expansion / contraction

7. Proposed work areas 3 Fishing practices changing through time
Fishing fleets change their behaviour through time
Clear evidence for changes in interactions among vessels, changes in technology, changes in incentives from fish prices and marketing strategies
Need for analyses using fine-scale location data, to better understand the changes in fishing strategies and their effects on CPUE indices
Fishing fleets are not homogeneous, but CPUE analyses should work with homogeneous data
Need for clustering approaches to separate subfleets

8. Proposed work areas 4 Regional weighting factors
Very influential for the assessments, but assumptions not particularly robust
Need for alternative perspectives and alternative datasets
Should also try assessment approaches that do not use regional weighting

9. Conclusions
The research outline is intended as advice from the science provider to the SC. To be considered for inclusion in the overall research plan
This is a work in progress – early stages of development
Seeking advice about priorities, and how this document might be improved.