Biodiversity monitoring via environmental DNA, particularly metabarcoding, is evolving into a powerful assessment tool for riverine systems. However, for metabarcoding to be fully integrated into standardized monitoring programmes, some current challenges concerning sampling design, laboratory workflow, and data analysis need to be overcome. Here, we review some of these major challenges and potential solutions. We further illustrate three potential pitfalls, namely the choice of suitable metabarcoding primers, the necessity of complete reference databases, and varying assay sensitivities, by a reappraisal of our‐own recently carried out metabarcoding study in the Volga headwaters. TaqMan qPCRs had detected catfish (Silurus glanis) and European eel (Anguilla anguilla), whereas metabarcoding had not, in the same samples. Furthermore, after extending the genetic reference database by 12 additional species and re‐analysing the metabarcoding data, we additionally detected the Siberian spiny loach (Cobitis sibirica) and Ukrainian brook lamprey (Eudontomyzon mariae) and reassigned the operational taxonomic units previously assigned to Misgurnus fossilis to Cobitis sibirica. In silico analysis of metabarcoding primer efficiencies revealed considerable variability among primer pairs and among target species, which could lead to strong primer bias and potential false‐negatives in metabarcoding studies if not properly compensated for. These results highlight some of the pitfalls of eDNA‐metabarcoding as a means of monitoring fish biodiversity in large rivers, which need to be considered in order to fully unleash the full potential of these approaches for freshwater biodiversity monitoring.

中文翻译：

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参考数据库，引物选择和对环境元条形码的测定敏感性：从伏尔加河源水中eDNA鱼评估的重新评估中学到的经验教训

通过环境DNA（尤其是元条形码）进行的生物多样性监测正在演变为针对河流系统的强大评估工具。但是，要将元条形码完全集成到标准化的监视程序中，需要克服一些当前有关采样设计，实验室工作流程和数据分析的挑战。在这里，我们回顾了其中一些主要挑战和潜在解决方案。通过对我们最近在伏尔加河源头进行的元条形码研究的重新评估，我们进一步说明了三个潜在的陷阱，即选择合适的元条形码编码引物，完整参考数据库的必要性和不同的测定灵敏度。TaqMan qPCR检测到cat鱼（Silurus glanis）和欧洲鳗鱼（Anguilla anguilla）），而在相同的样本中没有元条形码。此外，在将遗传参考数据库扩展了12个其他物种并重新分析了元条形码数据之后，我们还检测了西伯利亚刺lo（Cobitis sibirica）和乌克兰布鲁克南芥（Eudontomyzon mariae），并重新分配了先前分配给Misgurnus化石的操作分类单位到Cobitis山杏。在对条码引物效率进行的计算机分析中，发现引物对之间和目标物种之间存在相当大的差异，如果没有适当补偿，可能会导致在条码研究中产生强烈的引物偏倚和潜在的假阴性。这些结果凸显了eDNA元条形码编码作为监测大型河流鱼类生物多样性的一种方法的缺陷，必须充分考虑这些方法，以充分释放这些方法在淡水生物多样性监测中的全部潜力。