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An abundance index for skipjack and juvenile yellowfin tuna from 1970 to 2018 has been developed from Maldives pole and line catch and effort data. The index was derived from multiple datasets with differing level of detail over the period. Solutions for missing data were a random effects component used to account for missing mechanization information on the fleet 1974-1979 (Medley et al. 2017a) and the reconstruction of vessel length information using a vessel survival regression (described in Medley et al. 2017c). Fishing power effects related to vessel length are explained using a segmented regression that accounts for different classes of vessel. Both skipjack and yellowfin are combined into a single multivariate model, with skipjack and yellowfin catch rates standardized through a compound poisson-gamma (Tweedie) regression model. Additional fishing power effects which have not been recorded in the data have been estimated using subjective priors based on an expert meeting, and these effects could be included. The model was fitted obtaining a MCMC approximation to the Bayes posterior for the abundance indices using Stan software. Remaining issues include poor estimation of catch rates for the smallest vessels which has only been partially resolved and unaccounted for differences among landing atolls, as the reasons for these differences are not understood. Also, declines in data reporting, which coincided with the introduction of the logbooks, are a cause for concern, although reporting rates are improving. The analysis is fully reproducible and have been made available for peer review.
