4.2 Article

Comparison of morphological and DNA metabarcoding analyses of diets in exploited marine fishes

期刊

MARINE ECOLOGY PROGRESS SERIES
卷 540, 期 -, 页码 167-181

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INTER-RESEARCH
DOI: 10.3354/meps11524

关键词

Foodweb; Ecosystem-based management; DNA sequencing; Fisheries management; Ecosystem modelling

资金

  1. ARC future fellowship [FT0991741]

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Ecosystem-based management (EBM) is a framework for managing marine re sources. EBM strategies can be evaluated with ecosystem models that represent functional components of ecosystems, including anthropogenic factors. Foodwebs are at the core of ecosystem models, but because dietary data can be difficult to obtain, they are often coarsely characterised. High-throughput DNA sequencing (HTS) of diets is a rapid way to parameterise foodwebs at enhanced taxonomic resolution, and potentially, to optimise the functioning of ecosystem models. We evaluated the relative merits of microscopic and HTS analyses of the diets of 8 fish species harvested in Australia's most intensive fishery, viz. the southeast trawl fishery. We compare the taxonomic resolution and phylogenetic breadth of diets yielded by these methods and include a comparison of 3 DNA barcoding markers (mtDNA COX1 Minibar, mtDNA 16S Chord-cephA, nDNA 18S Bilateria). Using paired individual gut samples (n = 151), we demonstrate that HTS typically identified similar taxon richness but at significantly higher taxonomic resolution than microscopy. However, DNA barcode selection significantly affected both the resolution and phylogenetic breadth of estimated diets. Both COX1 Minibar and 16S Chord-cephA barcodes provided higher taxonomic resolution than morphological analysis, but the resolution varied between taxonomic groups primarily due to availabilities of reference data. However, neither barcode recovered the full dietary spectrum revealed by the 18S Bilateria barcode. HTS also revealed the presence of dietary items not previously recorded for target species, and diverse parasite assemblages. We conclude that HTS has the potential to improve structure and function of ecosystem models and to facilitate best-practice EBM.

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