Application of CRISPR-Dx and metabarcoding to catchment-level eDNA for terrestrial mammal detection

Beschreibung

General description

Data associated with the publication "CRISPR-Dx and metabarcoding perform similarly for monitoring mammals with eDNA on the catchment level in high-alpine ecosystems". The data set contains the cleaned metabarcoding reads per site/catchment, the CRISPR-Dx detection per species and site, the site coordinates and a species checklist obtained from the Swiss National Park with the species known to occur at the sampling time point in the respective catchments.

Authors Flurin Leugger, Martina Lüthi, Michel Schmidlin, Sarah Marie-Antoine Turnheer, Zacharias Kontarakis and Loïc Pellissier

Contact flurinleugger@gmail.com loic.pellissier@usys.ethz.ch

Project description We collected eDNA samples in the Swiss National Park in September 2022 using VigiDNA filters. We extracted the samples in the clean lab at ETH using a modified extraction protocol of Pont et al. (2018). We used the Mamm01 primer (Tabarlet et al. 2018) for metabarcoding and for CRISPR analysis. We applied CRISPR-Dx for eight species occurring in the Swiss National Park. Additionally, we compared the eDNA detections to species inventories per catchment obtained from the Swiss National Park. See publication for more details.

Folders catchments Shape file containing the catchments sampled in the Swiss National Park. metadata Folder containing files with overview of site names and extract number. Second file with metadata per site (e..g., sampling date). Column called "EVS" (Environmental sample) is the key between the two files. data Folder containing a folder for eDNA and species_inventory (traditional monitoring), respectively. eDNA folder CRISPR_classifications.csv: CRISPR-Dx classifications per extract (and PCR pool). metabarcoding_seqs_all_cleaned.csv: all DNA sequences from metabarcoding after removing all sequences found in the negative controls. species_inventory Species per catchment reported by the Swiss National Park, based on traditional monitoring including. visual surveys and other opportunistic records. 2: known presence in 2022, 1: maybe present in 2022, 0: not recorded in 2022