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All is fish that comes to the net: metabarcoding for rapid fisheries catch assessment
Author(s) -
Russo Tommaso,
Maiello Giulia,
Talarico Lorenzo,
Baillie Charles,
Colosimo Giuliano,
D'Andrea Lorenzo,
Di Maio Federico,
Fiorentino Fabio,
Franceschini Simone,
Garofalo Germana,
Scannella Danilo,
Cataudella Stefano,
Mariani Stefano
Publication year - 2021
Publication title -
ecological applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.864
H-Index - 213
eISSN - 1939-5582
pISSN - 1051-0761
DOI - 10.1002/eap.2273
Subject(s) - fishing , slush , fishery , demersal zone , marine life , biodiversity , fisheries science , resource (disambiguation) , fish <actinopterygii> , key (lock) , groundfish , demersal fish , environmental dna , sampling (signal processing) , fisheries management , ecology , environmental resource management , environmental science , geography , biology , computer science , filter (signal processing) , computer vision , computer network , meteorology
Monitoring marine resource exploitation is a key activity in fisheries science and biodiversity conservation. Since research surveys are time consuming and costly, fishery‐dependent data (i.e., derived directly from fishing vessels) are increasingly credited with a key role in expanding the reach of ocean monitoring. Fishing vessels may be seen as widely ranging data‐collecting platforms, which could act as a fleet of sentinels for monitoring marine life, in particular exploited stocks. Here, we investigate the possibility of assessing catch composition of single hauls carried out by trawlers by applying DNA metabarcoding to the dense water draining from fishing nets just after the end of hauling operations (hereafter “slush”). We assess the performance of this approach in portraying β‐diversity and examining the quantitative relationship between species abundances in the catch and DNA amount in the slush (read counts generated by amplicon sequencing). We demonstrate that the assemblages identified using DNA in the slush satisfactorily mirror those returned by visual inspection of net content (about 71% of species and 86% of families of fish) and detect a strong relationship between read counts and species abundances in the catch. We therefore argue that this approach could be upscaled to serve as a powerful source of information on the structure of demersal assemblages and the impact of fisheries.