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

(2019) Data from: Plant DNA metabarcoding of lake sediments: how does it represent the contemporary vegetation. DRYAD doi:10.5061/dryad.g72v731 [Dataset]

Abstract

NGSfilter file.The ngsfilter file containing the sample - PCR tag information necessary for demultiplexing the sequence data in OBITools.140704_SND104_B_L001_GZO-13.ngsfilterPost OBITools analysis scriptThe R script contains the various commands that were used for filtering the metabarcoding data and matching it to the vegetation.FilterDNAandCompareToVegetation.RVegetation dataThe results of the vegetation surveys of the 11 lakes. Abundance assignment in the >2m survey is follows: Dominant taxa are recorded as 4, common taxa as 3, scattered taxa as 2 and rare taxa as 1.Vegetation.csvMetabarcoding resultsThe OBITools output, expanded with the lake name, core number, depth information and and a shorter taxa code used for linking the results to the vegetation data.IdentifiedDNA.tsvSample code informationFile that links the sample codes used in the study to the lake name, core and depth information.SampleToSampleInfo.tsvForward reads (part 1)Compressed FASTQ file containing the first half of the forward reads.140704_SND104_B_L001_GZO-13_R1-1.fastq.gzForward reads (part 2)Compressed FASTQ file containing the second half of the forward reads.140704_SND104_B_L001_GZO-13_R1-2.fastq.gzReverse reads (part 1)Compressed FASTQ file containing the first half of the reverse reads.140704_SND104_B_L001_GZO-13_R2-1.fastq.gzReverse reads (part 2)Compressed FASTQ file containing the second half of the reverse reads.140704_SND104_B_L001_GZO-13_R2-2.fastq.gz,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.

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Contributors

Contributor: Mary E. Edwards

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