A major management objective for tunas in the eastern Pacific Ocean (EPO) is to keep stocks at levels capable of producing maximum sustainable yields (MSYs). Management objectives based on MSY or related reference points (e.g. fishing mortality that produces MSY (F_MSY); spawner-per-recruit proxies) are in use for many species and stocks worldwide. However, these objectives require that reference points and quantities to which they are compared be available. The various reference points require different amounts and types of information, ranging from biological information (e.g. natural mortality, growth, and stock-recruitment relationship) and fisheries characteristics (e.g. age-specific selectivity), to absolute estimates of biomass and exploitation rates. These absolute estimates generally require a formal stock assessment model. For many species, the information required to estimate these quantities is not available, and alternative approaches are needed.

Skipjack tuna is a notoriously difficult species to assess. Due to its high and variable productivity (i.e. annual recruitment is a large proportion of total biomass), it is difficult to detect the effect of fishing on the population with standard fisheries data and stock assessment methods. This is particularly true for the stock of the EPO, due to the lack of age-composition data, and especially tagging data, without which a conventional stock assessment of skipjack is not possible.

The continuous recruitment and rapid growth of skipjack mean that the temporal stratification needed to observe modes in length-frequency data make the current sample sizes inadequate.

Previous assessments have had difficulty in estimating the absolute levels of biomass and exploitation rates, due to the possibility of a dome-shaped selectivity curve, which would mean that there is a cryptic biomass of large skipjack that cannot be estimated.

The most recent assessment of skipjack in the EPO is considered preliminary because it is not known whether the catch per day fished for purse-seine fisheries is proportional to abundance.

Analysis of currently available tagging data is unlikely to improve the skipjack stock assessment and a fully length-structured model produced unrealistic estimates. In addition to the problems listed above, the levels of age-specific natural mortality are uncertain, if not unknown, and current yield-per-recruit (YPR) calculations indicate that the YPR would be maximized by catching the youngest skipjack in the model. Therefore, neither the biomass- nor fishing mortality-based reference points, nor the indicators to which they are compared, are available for skipjack in the EPO.

Further analysis of currently available tagging data is unlikely to improve the skipjack stock assessment and a fully length-structured model produced unrealistic estimates. In addition to the problems listed above, the levels of age-specific natural mortality are uncertain, if not unknown, and current yield-per-recruit (YPR) calculations indicate that the YPR would be maximized by catching the youngest skipjack in the model. Therefore, neither the biomass- nor fishing mortality-based reference points, nor the indicators to which they are compared, are available for skipjack in the EPO.

Since the stock assessments and reference points for skipjack in the EPO are so uncertain, developing alternative methods to assess and manage the species that are robust to these uncertainties would be beneficial. Full management strategy evaluation (MSE) for skipjack would be the most comprehensive method to develop and test alternative assessment methods and management strategies; however, developing MSE is time-consuming, and has not yet been conducted for skipjack. In addition, higher priority for MSE is given to yellowfin and bigeye tuna, as available data indicate that these species are more susceptible to overfishing than skipjack. Therefore, Maunder and Deriso (2007) investigated some simple indicators of stock status based on relative quantities. Rather than using reference points based on MSY, they compared current values of indicators to the distribution of indicators observed historically. They also developed a simple stock assessment model to generate indicators for biomass, recruitment, and exploitation rate. However, this year catch-per-set by set type replaces the catch-per-day-fished Stock Status Indicators (SSIs) used previously, which are considered unreliable due to possible biases in the method used to assign days fished to set types; also, the model-based indicators used for skipjack are no longer reported because they were based on the same CPDF data.

This analysis was originally presented in document SAC-10-09