High resolution ancient sedimentary DNA shows that alpine plant diversity is associated with human land use and climate change
Garcés-Pastor, Sandra et al. (2022), High resolution ancient sedimentary DNA shows that alpine plant diversity is associated with human land use and climate change, Dryad, Dataset, https://doi.org/10.5061/dryad.7wm37pvx5
The European Alps are highly rich in species, but their future may be threatened by ongoing changes in human land use and climate. Here, we reconstructed vegetation, temperature, human impact and livestock over the past ~12,000 years from Lake Sulsseewli, based on sedimentary ancient plant and mammal DNA, pollen, spores, chironomids, and microcharcoal. We assembled a highly-complete local DNA reference library (PhyloAlps, 3,923 plant taxa), and used this to obtain an exceptionally rich sedaDNA record of 366 plant taxa. Vegetation mainly responded to climate during the early Holocene, while human activity had an additional influence on vegetation from 6 ka onwards. Land-use shifted from episodic grazing during the Neolithic and Bronze Age to agropastoralism in the Middle Ages. Associated human deforestation allowed the coexistence of plant species typically found at different elevational belts, leading to levels of plant richness that characterise the current high diversity of this region. Our findings indicate a positive association between low-intensity agropastoral activities and precipitation with the maintenance of the unique subalpine and alpine plant diversity of the European Alps.
DNA was extracted from 80 sediment samples and 8 extraction/sampling negative controls using a modified DNeasy PowerSoil kit (Qiagen, Germany) protocol in the ancient DNA laboratory at TMU. DNA extracts and negative extraction/sampling controls, along with 8 PCR controls, were amplified using uniquely dual-tagged universal primer sets that amplify either the trnL P6 loop region of the chloroplast genome (gh primers) or a section of the mammalian mitochondrial 16S locus (MamP007 primers). Eight PCR replicates were carried out for each sample or control for trnL, whereas four replicates were performed for 16S.
The OBITools software package was used for the bioinformatics pipeline. Paired-end reads were aligned using SeqPrep (https://github.com/jstjohn/SeqPrep/releases, v1.2). Merged reads were demultiplexed according to the 8 bp unique primer tags and identical sequences were collapsed. Singleton sequences and those shorter than 10 bp were removed and putative artifactual sequences were identified and removed from the dataset. The trnL data were identified with 4 different reference libraries: PhyloAlps; ArctBorBryo; PhyloNorway; and the global reference library based on the EMBL rl143 database. The 16S data was only identified using the global reference library based on the EMBL rl143 database.
The data files are "Tab-Separated Values" (TSV) files and can be opened with any text editor, imported into spreadsheet software, analysed with stastical programs such as R, parsed with command line tools or scripting languages.
Norges Forskningsråd, Award: 250963/F20