The current capacity of environmental DNA (eDNA) to provide accurate insights into the biodiversity of megadiverse regions (e.g., the Neotropics) requires further evaluation to ensure its reliability for long-term monitoring. In this study, we first evaluated the taxonomic resolution capabilities of a short fragment from the 12S rRNA gene widely used in fish eDNA metabarcoding studies, and then compared eDNA metabarcoding data from water samples with traditional sampling using nets. For the taxonomic discriminatory power analysis, we used a specifically curated reference dataset consisting of 373 sequences from 264 neotropical fish species (including 47 newly generated sequences) to perform a genetic distance-based analysis of the amplicons targeted by the MiFish primer set. We obtained an optimum delimitation threshold value of 0.5% due to lowest cumulative errors. The barcoding gap analysis revealed only a 50.38% success rate in species recovery (133/264), highlighting a poor taxonomic resolution from the targeted amplicon. To evaluate the empirical performance of this amplicon for biomonitoring, we assessed fish biodiversity using eDNA metabarcoding from water samples collected from the Amazon (Adolpho Ducke Forest Reserve and two additional locations outside the Reserve). From a total of 84 identified Molecular Operational Taxonomic Units (MOTUs), only four could be assigned to species level using a fixed threshold. Measures of α-diversity analyses within the Reserve showed similar patterns in each site between the number of MOTUs (eDNA dataset) and species (netting data) found. However, β-diversity revealed contrasting patterns between the methods. We therefore suggest that a new approach is needed, underpinned by sound taxonomic knowledge, and a more thorough evaluation of better molecular identification procedures such as multi-marker metabarcoding approaches and tailor-made (i.e., order-specific) taxonomic delimitation thresholds.

中文翻译：

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瓶颈中的eDNA：大型多样的淡水系统中鱼类元条形码研究的障碍

当前环境DNA（eDNA）能够提供对大范围生物多样性（例如新热带）的生物多样性的准确见解的能力，需要进一步评估以确保其长期监测的可靠性。在这项研究中，我们首先评估了广泛用于鱼类eDNA元条形码研究中的12S rRNA基因的短片段的分类学分辨能力，然后将水样中的eDNA元条形码数据与使用网络的传统采样进行了比较。对于分类学鉴别力分析，我们使用了特定的参考数据集，该数据集由来自264个新热带鱼类的373个序列（包括47个新生成的序列）组成，对MiFish引物组靶向的扩增子进行基于遗传距离的分析。我们获得的最佳划界阈值为0。由于最低的累积误差，所以为5％。条形码缺口分析显示，物种恢复成功率只有50.38％（133/264），突出显示了目标扩增子的分类学分辨率差。为了评估该扩增子用于生物监测的经验性能，我们使用eDNA元条形码从亚马逊（Adolpho Ducke森林保护区和保护区外的两个其他地点）收集的水样中使用了eDNA元条形码，评估了鱼类的生物多样性。在总共84个已确定的分子操作分类单位（MOTU）中，使用固定阈值只能将4个分配给物种级别。在保护区内进行的α多样性分析表明，每个站点的MOTU数量（eDNA数据集）和物种（网状数据）之间的模式相似。但是，β多样性揭示了两种方法之间的对比模式。