The commercially important Atlantic bluefin tuna (Thunnus thynnus), a large migratory fish, has experienced notable recovery aided by accurate resource assessment and effective fisheries management efforts. Traditionally, this species has been perceived as consisting of eastern and western populations, spawning respectively in the Mediterranean Sea and the Gulf of Mexico, with mixing occurring throughout the Atlantic. However, recent studies have emerged challenging this assumption by revealing weak genetic differentiation and identifying a previously unknown spawning ground in the Slope Sea used by Atlantic bluefin tuna of uncertain origin. To further understand the current and past population structure and connectivity of Atlantic bluefin tuna, we have assembled a unique dataset including thousands of genome-wide Single Nucleotide Polymorphisms (SNPs) from five hundred larvae, young of the year and spawning adult samples covering the three spawning grounds and including individuals of other Thunnus species. Our analyses support two weakly differentiated but demographically connected ancestral populations that interbreed in the Slope Sea. Moreover, we also identified signatures of introgression from albacore into the Atlantic bluefin tuna genome, exhibiting varied frequencies across spawning areas, indicating strong gene flow from the Mediterranean Sea towards the Slope Sea. We hypothesize that the observed genetic differentiation may be attributed to increased gene flow caused by a recent intensification of westward migration by the eastern population, which could have implications for the genetic diversity and conservation of western populations. Future conservation efforts should consider these findings to address potential genetic homogenization in the species.

Mesozooplankton is a key component of the ocean, regulating global processes such as the carbon pump, and ensuring energy transfer from lower to higher trophic levels. Yet, despite the importance of understanding mesozooplankton diversity, distribution and connectivity at global scale to predict the impact of climate change in marine ecosystems, there is still fragmented knowledge. To fill this gap, we applied DNA metabarcoding to mesozooplankton samples collected during the Malaspina-2010 circumnavigation expedition across temperate and tropical oceans from the surface to bathypelagic depths. By conducting a hidden diversity analysis, we highlight the still scarce knowledge on global mesozooplankton diversity and identify the Indian Ocean and the deep sea as the most understudied areas. By analysing mesozooplankton community spatial distribution, we confirm global biogeographical patterns across the temperate to tropical oceans both in the vertical and horizontal gradients. Additionally, we reveal a consistent increase in mesozooplankton beta-diversity with depth, indicating reduced connectivity at deeper layers, and identify a water mass type-mediated structuring of bathypelagic communities, instead of an oceanic basin-mediated as observed at upper layers. This suggests limited dispersal at deep ocean layers, most likely due to weaker currents and lower mixing of water mass types. Overall, our work supports the neutral theory of biodiversity and thus the importance of oceanic currents and barriers in dispersal in shaping global plankton communities, and provides key knowledge for predicting the impact of climate change in the deep-sea.

In a recent paper, “Environmental DNA: What’s behind the term? Clarifying the terminology and recommendations for its future use in biomonitoring”, Pawlowski et al. argue that the term eDNA should be used to refer to the pool of DNA isolated from environmental samples, as opposed to only extra-organismal DNA from macro-organisms. We agree with this view. However, we are concerned that their proposed two-level terminology specifying sampling environment and targeted taxa is overly simplistic and might hinder rather than improve clear communication about environmental DNA and its use in biomonitoring. Not only is this terminology based on categories that are often difficult to assign and uninformative, but it ignores what is in our opinion the most important distinction within eDNA: the type of DNA (organismal or extra-organismal) from which ecological interpretations are derived.