Marine water environmental DNA metabarcoding provides a comprehensive fish diversity assessment and reveals spatial patterns in a large oceanic area

• Published in: Ecology and Evolution
• Main Authors: Fraija‐Fernández, Natalia, Bouquieaux, Marie‐Catherine, Rey, Anaïs, Mendibil, Iñaki, Cotano, Unai, Irigoien, Xabier, Santos, María, Rodríguez‐Ezpeleta, Naiara
• Other Authors: Spanish Ministry of Science, Innovation and Universities, Department of Economic Development and Infrastructure of Basque Government
• Format: Article in Journal/Newspaper
• Language: English
• Published: Wiley 2020
• Subjects: Northeast Atlantic
• Online Access: http://dx.doi.org/10.1002/ece3.6482; https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fece3.6482; https://onlinelibrary.wiley.com/doi/pdf/10.1002/ece3.6482; https://onlinelibrary.wiley.com/doi/full-xml/10.1002/ece3.6482

Abstract Current methods for monitoring marine fish (including bony fishes and elasmobranchs) diversity mostly rely on trawling surveys, which are invasive, costly, and time‐consuming. Moreover, these methods are selective, targeting a subset of species at the time, and can be inaccessible to certain areas. Here, we used environmental DNA (eDNA), the DNA present in the water column as part of shed cells, tissues, or mucus, to provide comprehensive information about fish diversity in a large marine area. Further, eDNA results were compared to the fish diversity obtained in pelagic trawls. A total of 44 5 L‐water samples were collected onboard a wide‐scale oceanographic survey covering about 120,000 square kilometers in Northeast Atlantic Ocean. A short region of the 12S rRNA gene was amplified and sequenced through metabarcoding generating almost 3.5 million quality‐filtered reads. Trawl and eDNA samples resulted in the same most abundant species (European anchovy, European pilchard, Atlantic mackerel, and blue whiting), but eDNA metabarcoding resulted in more detected bony fish and elasmobranch species (116) than trawling (16). Although an overall correlation between fishes biomass and number of reads was observed, some species deviated from the common trend, which could be explained by inherent biases of each of the methods. Species distribution patterns inferred from eDNA metabarcoding data coincided with current ecological knowledge of the species, suggesting that eDNA has the potential to draw sound ecological conclusions that can contribute to fish surveillance programs. Our results support eDNA metabarcoding for broad‐scale marine fish diversity monitoring in the context of Directives such as the Common Fisheries Policy or the Marine Strategy Framework Directive.