Tromsø Museum, University of Tromsø -The Arctic University of Norway, Tromsø, Norway.
Department of Arctic and Marine Biology, University of Tromsø -The Arctic University of Norway, Tromsø, Norway.
PLoS One. 2018 Apr 17;13(4):e0195403. doi: 10.1371/journal.pone.0195403. eCollection 2018.
Metabarcoding of lake sediments have been shown to reveal current and past biodiversity, but little is known about the degree to which taxa growing in the vegetation are represented in environmental DNA (eDNA) records. We analysed composition of lake and catchment vegetation and vascular plant eDNA at 11 lakes in northern Norway. Out of 489 records of taxa growing within 2 m from the lake shore, 17-49% (mean 31%) of the identifiable taxa recorded were detected with eDNA. Of the 217 eDNA records of 47 plant taxa in the 11 lakes, 73% and 12% matched taxa recorded in vegetation surveys within 2 m and up to about 50 m away from the lakeshore, respectively, whereas 16% were not recorded in the vegetation surveys of the same lake. The latter include taxa likely overlooked in the vegetation surveys or growing outside the survey area. The percentages detected were 61, 47, 25, and 15 for dominant, common, scattered, and rare taxa, respectively. Similar numbers for aquatic plants were 88, 88, 33 and 62%, respectively. Detection rate and taxonomic resolution varied among plant families and functional groups with good detection of e.g. Ericaceae, Roseaceae, deciduous trees, ferns, club mosses and aquatics. The representation of terrestrial taxa in eDNA depends on both their distance from the sampling site and their abundance and is sufficient for recording vegetation types. For aquatic vegetation, eDNA may be comparable with, or even superior to, in-lake vegetation surveys and may therefore be used as an tool for biomonitoring. For reconstruction of terrestrial vegetation, technical improvements and more intensive sampling is needed to detect a higher proportion of rare taxa although DNA of some taxa may never reach the lake sediments due to taphonomical constrains. Nevertheless, eDNA performs similar to conventional methods of pollen and macrofossil analyses and may therefore be an important tool for reconstruction of past vegetation.
对湖泊沉积物的代谢组学研究表明，它可以揭示当前和过去的生物多样性，但对于在植被中生长的分类群在环境 DNA（eDNA）记录中的代表性程度知之甚少。我们分析了挪威北部 11 个湖泊的湖泊和集水区植被以及维管植物 eDNA 的组成。在离湖岸 2 米范围内生长的 489 个分类群记录中，17-49%（平均 31%）可识别的分类群通过 eDNA 检测到。在 11 个湖泊中，217 个 eDNA 记录的 47 种植物中，分别有 73%和 12%与离湖岸 2 米和 50 米范围内的植被调查中记录的分类群匹配，而 16%的分类群在同一湖泊的植被调查中未被记录。后者包括在植被调查中可能被忽略或生长在调查区域之外的分类群。检测到的百分比分别为优势、常见、分散和稀有分类群的 61%、47%、25%和 15%。水生植物的相应百分比分别为 88%、88%、33%和 62%。植物科和功能组的检测率和分类分辨率各不相同，例如对 Ericaceae、Roseaceae、落叶树、蕨类植物、石松类和水生植物的检测效果较好。陆地分类群在 eDNA 中的代表性取决于它们与采样点的距离以及它们的丰度，足以记录植被类型。对于水生植被，eDNA 可能与湖泊内植被调查相当，甚至更优越，因此可以用作生物监测工具。对于陆地植被的重建，需要改进技术并进行更密集的采样，以检测到更高比例的稀有分类群，尽管由于埋藏学限制，某些分类群的 DNA 可能永远不会到达湖泊沉积物。然而，eDNA 的表现与花粉和大型化石分析的常规方法相似，因此可能是重建过去植被的重要工具。
