In the present study we have investigated the population genetic structure of albacore (Thunnus alalunga, Bonnaterre 1788) and assessed the loss of genetic diversity, likely due to overfishing, of albacore population in the North Atlantic Ocean. For this purpose, 1,331 individuals from 26 worldwide locations were analyzed by genotyping 75 novel nuclear SNPs. Our results indicated the existence of four genetically homogeneous populations delimited within the Mediterranean Sea, the Atlantic Ocean, the Indian Ocean and the Pacific Ocean. Current definition of stocks allows the sustainable management of albacore since no stock includes more than one genetic entity. In addition, short- and long-term effective population sizes were estimated for the North Atlantic Ocean albacore population, and results showed no historical decline for this population. Therefore, the genetic diversity and, consequently, the adaptive potential of this population have not been significantly affected by overfishing.

One of the most common problems in fisheries is the definition of management units. Albacore Thunnus alalunga is an important species for commercial fisheries. Its population structure is still partially unknown; however, on the basis of fisheries data, tagging experiments, and morpho-ecological studies, 6 management units are currently accepted for this species. The main objective of this study was to define genetic entities within T. alalunga and to discuss the appropriateness of current management units. For this purpose, 13 microsatellite loci were applied to 551 albacore samples collected worldwide, and the population genetic structure was assessed. The most relevant differences between management and genetic units were that (1) Atlantic and Indian Ocean samples are genetically indistinguishable, and (2) possible differentiation exists within the Pacific Ocean and also within the Mediterranean Sea. Thus, this study provides genetic information to clarify albacore population delimitation, which is a key factor to reach the demanded sustainable management of this resource.

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Background With numerous endemic subspecies representing four of its five evolutionary lineages, Europe holds a large fraction of Apis mellifera genetic diversity. This diversity and the natural distribution range have been altered by anthropogenic factors. The conservation of this natural heritage relies on the availability of accurate tools for subspecies diagnosis. Based on pool-sequence data from 2145 worker bees representing 22 populations sampled across Europe, we employed two highly discriminative approaches (PCA and FST) to select the most informative SNPs for ancestry inference. Results Using a supervised machine learning (ML) approach and a set of 3896 genotyped individuals, we could show that the 4094 selected single nucleotide polymorphisms (SNPs) provide an accurate prediction of ancestry inference in European honey bees. The best ML model was Linear Support Vector Classifier (Linear SVC) which correctly assigned most individuals to one of the 14 subspecies or different genetic origins with a mean accuracy of 96.2% ± 0.8 SD. A total of 3.8% of test individuals were misclassified, most probably due to limited differentiation between the subspecies caused by close geographical proximity, or human interference of genetic integrity of reference subspecies, or a combination thereof. Conclusions The diagnostic tool presented here will contribute to a sustainable conservation and support breeding activities in order to preserve the genetic heritage of European honey bees.

Anchovies represent the largest world’s marine fish catches and the current threats on their populations impose a sustainable exploitment based on sound scientific information. In the European anchovy (Engraulis encrasicolus), the existence of several populations has been proposed but a global view is missing. Using a multidisciplinary approach, here we assessed the divergence among different ecotypes and its possible causes. SNPs have revealed two functionally distinct ecotypes overlapping in the Central Mediterranean, with one ecotype confined near the river estuaries. The same SNPs outliers also segregated two distinct populations in the near Atlantic, despite their large spatial distance. In addition, while most studies suggested that adaptation to low salinity is key to divergence, here we show that the offshore ecotype has higher environmental tolerance and an opportunistic feeding behaviour, as assessed by the study of environmental conditions, anchovy diet and trophic levels, and passive egg dispersal. These results provide insights into the anchovy evolutionary history, stressing the importance of behaviour in shaping ecotypes.