Microbial communities are major players in the biogeochemical processes and ecosystem functioning of river networks. Despite their importance in the ecosystem, biomonitoring tools relying on prokaryotes are still lacking. Only a few studies have employed both metabarcoding and quantitative techniques such as catalysed reported deposition fluorescence in situ hybridization (CARD‐FISH) to analyse prokaryotic communities of epilithic biofilms in river ecosystems. We intended to investigate the efficacy of both techniques in detecting changes in microbial community structure associated with environmental drivers. We report a significant correlation between the prokaryotic community composition and pH in rivers from two different geographical areas in Norway. Both CARD‐FISH and metabarcoding data were following the pattern of the environmental variables, but the main feature distinguishing the community composition was the regional difference itself. Beta‐dispersion analyses on both CARD‐FISH abundance and metabarcoding data revealed higher accuracy of metabarcoding to differentiate regions and river systems. The CARD‐FISH results showed high variability, even for samples within the same river, probably due to some unmeasured microscale ecological variability which we could not resolve. We also present a statistical method, which uses variation coefficient and overall prevalence of taxonomic groups, to detect possible biological indicators among prokaryotes using metabarcoding data. The development of new prokaryotic bioindicators would benefit from both techniques used in this study, but metabarcoding seems to be faster and more reliable than CARD‐FISH for large scale bio‐assessment.

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多种压力条件下河流附石生物膜微生物群落结构表征的两种不同方法：开发分子指标

微生物群落是河流网络生物地球化学过程和生态系统功能的主要参与者。尽管它们在生态系统中很重要，但仍然缺乏依赖原核生物的生物监测工具。只有少数研究同时采用了元条形码和定量技术，例如催化报告的原位沉积荧光杂交（CARD-FISH）分析河流生态系统附石生物膜的原核生物群落。我们打算研究这两种技术在检测与环境驱动因素相关的微生物群落结构变化方面的功效。我们报告了来自挪威两个不同地理区域的河流中原核生物群落组成与 pH 值之间的显着相关性。CARD-FISH 和元条形码数据都遵循环境变量的模式，但区分群落组成的主要特征是区域差异本身。对 CARD-FISH 丰度和元条形码数据的 Beta 分散分析显示，元条形码在区分区域和河流系统方面具有更高的准确性。CARD-FISH 结果显示出很高的变异性，即使对于同一条河流中的样本，可能是由于我们无法解决的一些未测量的微尺度生态变异。我们还提出了一种统计方法，该方法使用变异系数和分类群的总体流行率，使用元条形码数据检测原核生物中可能的生物学指标。新原核生物指标的开发将受益于本研究中使用的两种技术，但对于大规模生物评估，元条形码似乎比 CARD-FISH 更快、更可靠。