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利用代谢条码技术评估后生动物生态模式。

The use of metabarcoding for meiofauna ecological patterns assessment.

机构信息

Centro de Estudos do Mar, Universidade Federal do Paraná, Av. Beira-Mar, s/n, Pontal do Sul, PO Box 61, Pontal do Paraná, PR, Zip Code 83255-976, Brazil.

Centro de Estudos do Mar, Universidade Federal do Paraná, Av. Beira-Mar, s/n, Pontal do Sul, PO Box 61, Pontal do Paraná, PR, Zip Code 83255-976, Brazil.

出版信息

Mar Environ Res. 2018 Sep;140:160-168. doi: 10.1016/j.marenvres.2018.06.013. Epub 2018 Jun 14.

DOI:10.1016/j.marenvres.2018.06.013
PMID:29933903
Abstract

Marine meiofauna comprises up to 22 phyla. Its morphological identification requires time and taxonomists' expertise, and molecular tools can make this task faster. We aim to disentangle meiofaunal diversity patterns at Araçá Bay by applying a model selection approach and estimating the effectiveness of metabarcoding (18S rDNA) and morphological methods for estimating the response of meiofauna diversity in small-scale interactions with environmental variables. A rarefaction curve indicated that ten samples were sufficient for estimating the total number of meiofauna OTUs in a tidal flat. In both approaches, richness was predicted by mean sand percentage, sediment sorting, and bacteria concentration. Nematode genera composition differed significantly between approaches, the result of taxonomic mismatch in the genetic database. The similarity between the model selected for diversity descriptors, the richness of nematode genera and meiofauna composition emphasized the utility of predictive models for metabarcoding estimates to detect small-scale interactions of these organisms.

摘要

海洋中型动物群包含多达 22 个门。其形态鉴定需要时间和分类学家的专业知识,而分子工具可以使这项任务更快完成。我们旨在通过应用模型选择方法来厘清阿拉萨伊湾的中型动物群多样性模式,并估计 metabarcoding(18S rDNA)和形态方法在估计小型潮间带环境变量与中型动物群多样性相互作用中的有效性。稀有曲线表明,十个样本足以估计潮坪中中型动物群 OTUs 的总数。在这两种方法中,丰度均由平均沙含量、沉积物分选和细菌浓度来预测。线虫属的组成在两种方法之间存在显著差异,这是由于遗传数据库中的分类不匹配。所选多样性描述符模型、线虫属丰度和中型动物群组成之间的相似性强调了预测模型对 metabarcoding 估计的实用性,以检测这些生物的小型相互作用。

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