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Environmental DNA effectively captures functional diversity of coastal fish communities

生物 环境DNA 互补性(分子生物学) 分类单元 渔业 沿海鱼类 生态学 细胞色素c氧化酶亚单位Ⅰ 分类等级 生物多样性 栖息地 线粒体DNA 遗传学 生物化学 基因 珊瑚鱼
作者
Giorgio Aglieri,Charles Baillie,Stefano Mariani,Carlo Cattano,Antonio Calò,Gabriele Turco,Davide Spatafora,Antonio Franco,Manfredi Di Lorenzo,Paolo Guidetti,Marco Milazzo
出处
期刊:Molecular Ecology [Wiley]
卷期号:30 (13): 3127-3139 被引量:74
标识
DOI:10.1111/mec.15661
摘要

Abstract 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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