Oceanic temperature fluctuations are one of the leading factors affecting marine fish populations. Indian Ocean Dipole (IOD), characterized as the sea surface temperature (SST) anomaly change, is an ocean–atmosphere interactive process causing interannual climate variability in the Indian Ocean. Influences of the IOD on the tuna catch rates are supported by previous research. Yet, there remains limited information about the impacts on the abundance of tuna stocks. In this study, we used the standardized Catch Per Unit Effort (CPUE) index to present the stock abundance and compared the effects of the IOD on the bigeye tuna (Thunnus obesus) and yellowfin tuna (Thunnus albacares) among different management areas of the Indian Ocean Tuna Commission (IOTC). Results show significant correlations between IOD events on both species’ abundance in the tropical western Indian Ocean. However, in the tropical eastern Indian Ocean and the southern Indian Ocean, neither bigeye nor yellowfin tuna abundances were significantly correlated by the IOD. For the whole Indian Ocean, IOD was significantly correlated uniquely with the yellowfin tuna abundance. Our results emphasized the importance of evaluating the climate variability effects over fisheries abundance species by species and per fishing areas analyses.

Most sophisticated stock assessment models often need a large amount of data to assess fish stocks, yet this data is often lacking for most fisheries worldwide, resulting in the increasing demand for data-limited stock assessment methods. To estimate fish stock status, one class of these data-limited methods uses simply catch time series data and, in other instances, life history information or fishery characteristics. These catch-only methods (COMs) built differently are known to make assumptions about changes in fishing effort and may perform differently under various fishing scenarios. As a case study, this paper used European anchovy (Engraulis encrasicolus) caught in the northwest African waters, though very economically and ecologically important, but still unassessed. Our study investigated the performance of five COMs under different fishing scenarios using as a reference the life-history information of the European anchovy captured in this region of the Atlantic. Hence, the present study developed a simulation approach to evaluate the performance of the five COMs in inferring the stock biomass status (B/B_MSY) with consideration of different fishing scenarios under prior information true to anchovy. All five COMs mostly underestimated B/B_MSY throughout the simulation period, especially under constant fishing mortality, and in the last five years of the simulation during all fishing scenarios. Overall, these COMs were generally poor classifiers of stock status, however, the state-space COM (SSCOM) generally performed better than the other COMs as it showed possibilities of recovering an overfished stock. When these methods were explored using actual anchovy catch data collected in the northwest African waters, SSCOM yielded results that were deferred from the other COMs. This study being the first to assess this species’ stock in this area using a suite of COMs, presents more insights into the species stock status, and what needs to be considered before scientifically putting in place management measures of the stock in the area.