Albacore tuna (Thunnus alalunga) has a distinctly complex life history in which juveniles and adults separate geographically but at times inhabit the same spaces sequentially. The species also migrates long distances and presumably experiences varied regimes of physical stress over a lifetime. There are, therefore, many opportunities for population structure to arise based on stochastic differences or environmental factors that promote local adaptation. However, with the extent of mobility consistently demonstrated by tagged individuals, there is also a strong argument for panmixia within an ocean basin. It is important to confirm such assumptions from a population genetics standpoint for this species in particular because albacore is one of the principal market tuna species that sustains massive global fisheries and yet is also a slow‐growing temperate tuna. Consequently, we used 1,837 neutral SNP loci and 89 loci under potential selection to analyze population genetic structure among five sample groups collected from the western and central South Pacific. We found no evidence to challenge panmixia at neutral loci, but strong indications of structuring at adaptive loci. One population sample, from French Polynesia in 2004, was particularly differentiated. Unfortunately, the current study cannot infer whether the divergence is geographic or temporal, or possibly caused by sample distribution. We encourage future studies to include potentially adaptive loci and to continue fine‐scale observations within an ocean basin, and not to assume genome‐wide panmixia.

Recent studies argue for the presence of genetic population structure in yellowfin tuna (Thunnus albacares) in all oceans. However, the persistence of family groups has never been considered a viable mechanism of structure, nor has it been measured. We analyzed genetic similarity among 280 yellowfin tunas from seven population samples collected in the Western and Central Pacific Ocean (WCPO) using single nucleotide polymorphisms, and found population structure that was significantly explained by the presence of 96 individuals involved in 332 half or full sib dyads. We found significantly higher mean and median relatedness between individuals from the same sample groups, compared to individuals from different groups; and high relatedness between individuals caught at the same fish-aggregating device (FAD) than between those caught in the wider exclusive economic zone (EEZ). Alternatively, the EEZ of the Federated States of Micronesia may harbor exceptionally large numbers of close kin. We conclude that yellowfin directly school with related individuals through their first year, and at least demonstrate tightly overlapping regional fidelity as adults. These results may explain, to some extent, the patterns of population genetic structure recently observed in yellowfin tuna.

Skipjack tuna (Katsuwonus pelamis) has historically been considered panmictic at the ocean basin scale because of the species’ life history and substantial absolute population size. However, recent advances in population genomics have enabled scientists to demonstrate population structure in other species that were likewise traditionally assumed to be panmictic. Accordingly, we used DArTseq, a proprietary platform of reduced-representation genome sequencing developed by Diversity Arrays Technology (DArTech) to genotype 222 skipjack tuna from 9 sample groups collected across 6 exclusive economic zones (EEZs) and over 6 years in the tropical Western and Central Pacific Ocean. This is one of the most fine-scale population genetics assessments of skipjack tuna to date. We found several statistically significant pairwise FST comparisons using purportedly neutral loci, but very little indication of structure based on observed and expected heterozygosity, effective population size, a Mantel test, AMOVA, numerous genetic clustering and population assignment tests, and exploration of correlation with oceanographic features. Significant pairwise FST values were often shallow and resulted in uncertainty about their biological significance. Furthermore, a test of the hypothesis that the geographic and temporal distribution of the potentially adaptive genetic diversity may depict cryptic fine scale structure using two different outlier detection methods, could not reject panmixia based on estimates of fixation indices and two clustering software. Our results support the presence of a single population of skipjack tuna in the tropical Western and Central Pacific Ocean, but highly recommend the expansion of the study area, in latitude, longitude, and seasonality, before drawing any global conclusions.

Decades of study have attempted to describe the population genetic structure of tuna species, including a significant number of studies focused on yellowfin (Thunnus albacares). Very often, analyses do not agree on how many stocks exist per species, and where their boundaries lie. This is possibly because studies vary so much across numerous variables, such as the geographic range covered in a study, the number and type of genetic markers used, and the number of sites sampled. This meta-analysis of 22 yellowfin studies attempts to standardize and isolate the key variables to assessing the strength of correlation with the resulting number of populations a study observes. Overall trends across the studies suggest that genetic markers with a high probability of being under selective constraints, or are located in coding regions, are more or less likely to sense population structure depending on geographic range coverage. Alternatively, when assessing neutral or non-coding genomic regions, studies also benefit from (i) more polymorphic and numerous loci, and (ii) increasing the number of sampling locations analyzed, both of which increase the statistical power of an analysis. Finally, trends were clearest when groups of accurately identified coding and non-coding, or neutral and non-neutral, studies were further subdivided by whether they used mitochondrial or nuclear DNA, confirming that analyses of the two genomes should not be compared directly. Our meta-analysis provides concrete support for long held assumptions about the relationships between population genetics study parameters and outcomes, and provides guidance for future studies on how to maximize the likelihood of identifying population structure where it exists.

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