Gibson, TI, Carvalho, G, Ellison, A, Gargiulo, E, Hatton-Ellis, T, Lawson-Handley, L, Mariani, S, Collins, RA, Sellers, G, Antonio Distaso, M, Zampieri, C and Creer, S (2023) Environmental DNA metabarcoding for fish diversity assessment in a macrotidal estuary: A comparison with established fish survey methods. Estuarine, Coastal and Shelf Science, 294. ISSN 0272-7714

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Abstract

Fishes are a dominant component of the macrofauna in estuaries and are important for assessing the health of these threatened ecosystems. Several studies have applied environmental DNA (eDNA) metabarcoding to assess the biodiversity of fishes in estuaries. However, none have combined measurement of physicochemical variables with a spatially extensive sampling design across the full salinity gradient. This study aimed to compare spatial fish assemblage composition detected via eDNA metabarcoding of surface water samples with conventional fishing gear surveys in a macrotidal estuary (river Dee, North Wales, UK). In addition, eDNA assemblage composition across seasons was investigated. In autumn 2018, triplicate eDNA samples were taken at 13 stations in a spatially systematic design alongside seine, fyke and beam trawl sampling. In summer 2019, eDNA samples from eight of the 13 original stations were collected again in the upper and lower estuary. DNA was extracted from samples and subjected to metabarcoding analysis using an established assay targeting teleost fishes. The key findings were that in autumn, eDNA detected 17 of the 26 (71%) species caught by fishing gears, which included the most abundant species. Overall, eDNA detected a greater species richness, per 30 samples, than seine or fyke nets (but not beam trawling). Additionally, there was a clear correlation between salinity and assemblage composition, which was consistent across seasons. Overall, the study indicates that eDNA metabarcoding could enhance existing fish sampling methods, by generating a more comprehensive picture of estuarine fish biodiversity and providing additional information for ecological inference and management actions.

Item Type:	Article
Uncontrolled Keywords:	Marine Biology & Hydrobiology
Subjects:	G Geography. Anthropology. Recreation > GE Environmental Sciences Q Science > QL Zoology
Divisions:	Biological & Environmental Sciences (from Sep 19)
Publisher:	Elsevier
SWORD Depositor:	A Symplectic
Date Deposited:	17 Sep 2024 14:10
Last Modified:	17 Sep 2024 14:15
DOI or ID number:	10.1016/j.ecss.2023.108522
URI:	https://researchonline.ljmu.ac.uk/id/eprint/24164

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