DNA metabarcoding captures different macroinvertebrate biodiversity than morphological identification approaches across a continental scale
DNA metabarcoding captures different macroinvertebrate biodiversity than morphological identification approaches across a continental scale
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DOI：
10.1002/edn3.453
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发表时间：
2023-07
影响因子：
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通讯作者：
Sean C. Emmons;Z. Compson;Megan C. Malish;Michelle H. Busch;V. Saenz;Kierstyn T. Higgins;Daniel C. Allen
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文献类型：
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作者：
Sean C. Emmons;Z. Compson;Megan C. Malish;Michelle H. Busch;V. Saenz;Kierstyn T. Higgins;Daniel C. Allen
基于DNA的水生生物监测方法有望提供快速，标准化和有效的生物多样性评估，以补充并在某些情况下取代目前基于形态学的方法，这些方法通常效率较低，并且可能产生不一致的结果。尽管有这种潜力，但最终用户对基于DNA的方法的广泛采用仍然有限，并且缺乏关于这两种方法在大空间尺度上检测水生生物多样性的差异的研究。在这里，我们提出了一个DNA元编码和形态识别的比较，利用国家生态观测网络（氖）的国家规模，开源，生态数据集。在北美的24个可涉水的溪流中，有179个配对的样本比较，我们发现DNA元编码检测到的独特类群是形态学鉴定的两倍。这两种方法在检测相同的类群时一致性较差，在目、科和属水平上分别检测到59%、35%和23%的共享类群。重要的是，这两种方法检测到不同比例的指示类群，如%EPT和%摇蚊科。DNA metabarcoding检测到的摇蚊和毛翅目类群比形态鉴定少得多，但更多的蜉蝣目和鳞翅目类群，结果可能是由于引物的选择。总体而言，我们的研究结果表明，DNA元编码和形态鉴定检测不同的底栖大型无脊椎动物群落。尽管存在这些差异，我们发现，相同的环境变量与无脊椎动物群落结构，这表明这两种方法可以准确地检测跨环境梯度的生物多样性模式。进一步完善的DNA元条形码协议，引物和参考文库，以及更标准化，大规模的比较研究，可能会提高我们的DNA元条形码和形态学方法之间的分类学协议和数据联系的理解。
DNA‐based aquatic biomonitoring methods show promise to provide rapid, standardized, and efficient biodiversity assessment to supplement and in some cases replace current morphology‐based approaches that are often less efficient and can produce inconsistent results. Despite this potential, broad‐scale adoption of DNA‐based approaches by end‐users remains limited, and studies on how these two approaches differ in detecting aquatic biodiversity across large spatial scales are lacking. Here, we present a comparison of DNA metabarcoding and morphological identification, leveraging national‐scale, open‐source, ecological datasets from the National Ecological Observatory Network (NEON). Across 24 wadeable streams in North America with 179 paired sample comparisons, we found that DNA metabarcoding detected twice as many unique taxa than morphological identification overall. The two approaches showed poor congruence in detecting the same taxa, averaging 59%, 35%, and 23% of shared taxa detected at the order, family, and genus levels, respectively. Importantly, the two approaches detected different proportions of indicator taxa like %EPT and %Chironomidae. DNA metabarcoding detected far fewer Chironomid and Trichopteran taxa than morphological identification, but more Ephemeropteran and Plecopteran taxa, a result likely due to primer choice. Overall, our results showed that DNA metabarcoding and morphological identification detected different benthic macroinvertebrate communities. Despite these differences, we found that the same environmental variables were correlated with invertebrate community structure, suggesting that both approaches can accurately detect biodiversity patterns across environmental gradients. Further refinement of DNA metabarcoding protocols, primers, and reference libraries–as well as more standardized, large‐scale comparative studies–may improve our understanding of the taxonomic agreement and data linkages between DNA metabarcoding and morphological approaches.