Molecular Ecology · 2020 · 135 citations · 54 references
Life SciencesEcologyMarine SciencesFish BiologyMarine BiodiversityMarine EcologyFunctional DiversityMarine Fish BiologyMarine Species DiversitySpecies DiversityTaxonomic DiversityEnvironmental Dna DetectionFish CommunitiesFunctional Diversity AssessmentMarine Environmental DnaMarine Fish BiodiversityMarine Fish DiversityMarine Functional DiversityMarine Taxonomic Diversity
Robust assessments of taxonomic and functional diversity are essential components of research programmes aimed at understanding current biodiversity patterns and forecasting trajectories of ecological changes. Yet, evaluating marine biodiversity along its dimensions is challenging and dependent on the power and accuracy of the available data collection methods. Here we combine three traditional survey methodologies (underwater visual census strip transects [UVCt], baited underwater videos [BUV] and small-scale fishery catches [SSFc]), and one novel molecular technique (environmental DNA metabarcoding [eDNA]-12S rRNA and cytochrome oxidase subunit 1 [COI]) to investigate their efficiency and complementarity in assessing fish diversity. We analysed 1,716 multimethod replicates at a basin scale to measure the taxonomic and functional diversity of Mediterranean fish assemblages. Taxonomic identities were investigated at species, genus and family levels. Functional identities were assessed using combinations of morphological, behavioural and trophic traits. We show that: (a) SSFc provided the higher taxonomic diversity estimates followed by eDNA, and then UVCt and BUV; (b) eDNA was the only method able to gather the whole spectrum of considered functional traits, showing the most functionally diversified and least redundant fish assemblages; and (c) the effectiveness of eDNA in describing functional structure reflected its lack of selectivity towards any considered functional trait. Our findings suggest that the reach of eDNA analysis stretches beyond taxon detection efficiency and provides new insights into the potential of metabarcoding in ecological studies.
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