Data from: Plant DNA metabarcoding of lake sediments: how does it represent the contemporary vegetation

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.湖泊沉积物宏条形码（metabarcoding）技术已被证实可揭示当前与过去的生物多样性，但学界对陆地植被分类群在环境DNA（environmental DNA，简称eDNA）记录中的表征程度仍知之甚少。本研究对挪威北部11个湖泊的湖滨与集水区植被组成，以及维管植物的eDNA进行了分析。在距湖岸2米范围内生长的489条分类群记录中，有17%~49%（平均31%）的可识别分类群通过eDNA被检出。在11个湖泊的47个植物分类群对应的217条eDNA记录中，分别有73%和12%的记录与距湖岸2米范围内、以及距湖岸约50米范围内的植被调查分类群相匹配；另有16%的记录未在对应湖泊的植被调查中被发现。此类未被检出的分类群可能是植被调查中被遗漏的类群，或是生长于调查区域之外的类群。优势种、常见种、偶见种和稀有种的检出率分别为61%、47%、25%和15%；水生植物的对应检出率则分别为88%、88%、33%和62%。不同植物科与功能群的检出率和分类分辨率存在差异，其中杜鹃花科(Ericaceae)、蔷薇科(Rosaceae)、落叶乔木、蕨类、石松类植物以及水生植物均具有较好的检出效果。陆地分类群在eDNA中的表征情况取决于其距采样点的距离与自身丰度，且该表征足以反映植被类型。对于水生植被而言，eDNA的检测效果可与湖内植被调查相媲美，甚至更优，因此可作为生物监测的工具。若要重建陆地植被，需通过技术改进与更密集的采样来提升稀有类群的检出比例；不过由于埋藏学(taphonomy)限制，部分类群的DNA可能永远无法抵达湖泊沉积物中。尽管如此，eDNA的检测效果与传统的花粉及大化石分析方法相当，因此可作为重建古植被的重要工具。