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.湖泊沉积物的元条形码（Metabarcoding）技术已被证实可揭示当前与过往的生物多样性，但针对植被中生长的类群在环境DNA（eDNA）记录中的表征程度，目前仍缺乏足够研究。我们对挪威北部11个湖泊的湖泊及流域植被组成，以及维管植物的eDNA开展了分析。在距湖岸2米范围内生长的489条类群记录中，有17%~49%（平均31%）的可识别类群通过eDNA被成功检出。在这11个湖泊的47个植物类群对应的217条eDNA记录中，分别有73%和12%的记录与距湖岸2米以内、以及距湖岸最远约50米区域内的植被调查类群相匹配；另有16%的记录未在对应湖泊的植被调查中被检索到，此类类群要么是在植被调查中被遗漏，要么是生长于调查区域之外。不同丰度类群的检出率存在差异：优势类群为61%、常见类群为47%、零散类群为25%、稀有类群为15%；水生植物的对应检出比例则分别为88%、88%、33%和62%。检出率与分类学分辨率因植物科和功能群而异，其中杜鹃花科（Ericaceae）、蔷薇科（Roseaceae）、落叶乔木、蕨类、石松类植物以及水生类群均实现了良好的检出效果。陆地类群在eDNA中的表征情况同时受其距采样点的距离与自身丰度的影响，且该技术足以实现植被类型的记录。针对水生植被，eDNA技术可与湖内植被调查方法相媲美，甚至更具优势，因此可作为生物监测的有效工具。在陆地植被重建领域，尽管部分类群的DNA可能因埋藏学约束（taphonomical constraints）无法抵达湖泊沉积物，但仍需通过技术改进与更密集的采样方案，才能检出更高比例的稀有类群。即便如此，eDNA技术的表现与传统的花粉及大化石分析方法相当，因此可成为重建过往植被的重要研究工具。