Three distant-water tuna longline countries, Japan, Korea and Taiwan, have started a collaborative
study since December 2019 for producing the joint abundance indices using integrated fishery data of
these fleets to contribute to the upcoming stock assessments of yellowfin tuna in the Indian Ocean.
The intention is to produce reliable indices by increasing the spatial and temporal coverage of fishery
data. In this paper, results using data up to 2020 fisheries were provided to update the WPTT on the
progress of this activity. As an underlying analysis, a clustering approach was utilized to account for
the inter-annual changes of the target in each fishery in each region. For this purpose, a hierarchical
clustering method with “fastcluster” was used, and the outputs of the finalized cluster were then used
to assign the cluster label on fishery target to each catch-effort data. For standardizing the
catch-per-unit-effort data, the conventional linear models and delta-lognormal linear models were
employed for data of monthly and 1° grid resolution in each region. In addition to the implicit target
species through the clustering, geographical and temporal covariates were used in the regression
structures. The models were diagnosed by the standard residual plots and influence analysis.