DOI: 10.5061/dryad.00000008k
title: Data from: Holistic monitoring of aquatic and terrestrial vertebrates by camera trapping and aquatic environmental DNA

description: The anthropogenic impact on the world’s ecosystems is severe and the need
 for non-invasive, cost-effective tools for monitoring and understanding
 those impacts is therefore urgent. Here we combine two such methods in a
 comprehensive multi-year study; camera trapping (CT) and analysis of
 environmental DNA (eDNA), in river marginal zones of a temperate, wetland
 Nature Park in Denmark. CT was performed from 2015 to 2019 for a total of
 8,778 camera trap days and yielded 24,376 animal observations. The CT
 observations covered 87 taxa, of which 78 were identified to species
 level, and 73 were wild native species. For eDNA metabarcoding, a total of
 113 freshwater samples were collected from eight sites in all four seasons
 from 2017 to 2018. The eDNA results yielded a total detection of 80 taxa,
 of which 74 were identified to species level, and 65 were wild native
 species. While the number of taxa detected with the two methods was
 comparable, the species overlap was only 20%. In combination, CT and eDNA
 monitoring thus yielded a total of 115 wild species (20 fishes, four
 amphibians, one snake, 23 mammals and 67 birds), representing half of the
 species found via conventional surveys over the last ca. 20 years (83% of
 fishes, 68 % of mammals, 67 % of amphibians, 41 % of birds and 20 % of
 reptiles). Our study demonstrates that a holistic approach combining two
 non-invasive methods, CT and eDNA metabarcoding, has great potential as a
 cost-effective biomonitoring tool for vertebrates.
description: This README file was generated on 2023-Oct-12 by Steen Wilhelm Knudsen.
 GENERAL INFORMATION 1. Title of Dataset: Data from: Holistic monitoring of
 aquatic and terrestrial vertebrates by camera trapping and aquatic
 environmental DNA 2. Author Information Principal Investigator Contact
 Information Name: Anne Marie Rubæk Holm Institution: Natural History
 Museum of Denmark University of Copenhagen Address: Universitetsparken 15
 3. Date of data collection (single date, range, approximate date):
 2015-2019 4. Geographic location of data collection: Freshwater areas in
 Denmark 5. Information about funding sources that supported the collection
 of the data: 15. Juni Fonden, Award number: 2016-A-101; and Statens
 Naturhistorisk Museumi Danmark; and Miljøstyrelsen SHARING/ACCESS
 INFORMATION 1. Licenses/restrictions placed on the data: CC0 1.0 Universal
 (CC0 1.0) Public Domain 2. Links to publications that cite or use the
 data: Holm, A. M. R., Knudsen, S. W., Månsson, M., Pedersen, D. E.,
 Nordfoss, P. H., Johansson, D. K., Gramsbergen, M., Havmøller, R. W.,
 Sigsgaard, E. E., Thomsen, P. F., Olsen, M. T., Møller, P. R. (2023).
 Holistic monitoring of freshwater and terrestrial vertebrates by camera
 trapping and environmental DNA. Environmental DNA 00. DOI:
 https://doi.org/10.1002/edn3.481 3. Links to other publicly accessible
 locations of the data:
 https://github.com/monis4567/aamosen\_edna\_metabarcoding 4.
 Links/relationships to ancillary data sets: None 5. Was data derived from
 another source? No 6. Recommended citation for this dataset: Holm, A. M.
 R., Knudsen, S. W., Månsson, M., Pedersen, D. E., Nordfoss, P. H.,
 Johansson, D. K., Gramsbergen, M., Havmøller, R. W., Sigsgaard, E. E.,
 Thomsen, P. F., Olsen, M. T., Møller, P. R. (2023). Data from: Holistic
 monitoring of aquatic and terrestrial vertebrates by camera trapping and
 aquatic environmental DNA. Dryad Digital Repository. DATA & FILE
 OVERVIEW 1. File List: This data repository holds the raw MiSeq fasta
 files from the metabarcoding of eDNA in the study on "Holistic
 monitoring of aquatic and terrestrial vertebrates by camera trapping and
 aquatic environmental DNA". The repository data file is compressed
 and can be uncompressed following the instructions below. Uncompressing
 the repository data file returns 18 directories named: * MBIBA\_aa *
 MBIBB\_aa * MBIBC\_aa * MBIBD\_aa * MBIBE\_aa * MBIBF\_aa * MBIBG\_aa *
 MBIBH\_aa * MBIBI\_aa * MBIBJ\_aa * MBIBK\_aa * MBIBL\_aa * MBIBM\_aa *
 MBIBN\_aa * MBIBO\_aa * MBIBP\_aa * MBIBQ\_aa * MBIBR\_aa Where each
 directory holds two fastq files. The fastq files stems from Polymerase
 chain reaction (PCR) performed with two the primersets: Mamm01
 (mamm01\_F:5’-CCGCCCGTCACCCTCCT-3’, mamm01\_R:
 5’-GTAYRCTTACCWTGTTACGAC-3’) (Taberlet et al., 2018), and MiFish-U
 (MiFish-U\_F: 5’-GTCGGTAAAACTCGTGCCAGC-3’, MiFish-U\_R:
 5’-CATAGTGGGGTATCTAATCCCAGTTTG-3’) (Miya et al., 2015). Targeting two
 regions of approximately 59 bp and 170 bp (excluding primers),
 respectively, around 390-400 bp apart in the 12S mitochondrial gene. The
 setup of PCR for metabarcoding is presented in the supplied Excel file
 (dryad\_data\_rep\_suppl\_file01\_details\_on\_metabarcode\_seq\_libraries\_v01.xls). This Excel file holds lists of tags and sequencing libraries. The fastq files can be demultiplexed by using the tables supplied in the Excel file and following the protocol for demultiplexing described by Sigsgaard et al (2020). This protocol makes use of Cutadapt (Martin 2011) and VSEARCH (Rognes et al. 2016). Resulting sense and antisense reads within each fastq file can be separated using DADA2 (Callahan et al. 2016). Chimeras should be removed. Resulting sequences can then be compared with the NCBI database using BLASTn (Altschul et al. 1990). Hits can then be classified taxonomically using the R package 'taxize' (Chamberlain & Szocs 2013). ## Sharing/Access information Links to other publicly accessible locations of the data: * https://github.com/monis4567/aamosen\_edna\_metabarcoding ## Code/Software The file is compressed in a Unix format, and needs to be uncompressed The file can be renamed and uncompressed in a Unix terminal using the commands below Rename the downloaded compressed file ```{bash echo=FALSE, engine.opts='-l'} echo "mv eOoUOH6rip eOoUOH6rip.gz" ``` Then uncompress the file ```{bash echo=FALSE, engine.opts='-l'} echo "gzip -d eOoUOH6rip.gz" ``` Then rename the file using 'mv' ```{bash echo=FALSE, engine.opts='-l'} echo "mv eOoUOH6rip eOoUOH6rip.tar.gz" ``` Then uncompress the file ```{bash echo=FALSE, engine.opts='-l'} echo "tar xf eOoUOH6rip.tar.gz" ``` This uncompresses 18 directories with raw MiSeq data. Inside each directory are two fastq files. The supplied Excel file holds 5 tabs. Each tab has an appendix table (numbered 01 to 05) that provides information on sequencing libraries, metabarcoding PCR setup, list of tags, resulting sequencing library files, and collection site abbreviations, filtered volume of water, information on the genomic DNA extractions from mock species, that are non-occurring in Denmark. The metabarcoding eDNA analysis can be replicated by using these tables to produce list of tags and batch files to use for demultiplexing the sequencing data and relate the tags to the sampling sites. ## References: * Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. 1990. Basic local alignment search tool. Journal of Molecular Biology 215:403–410. * Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJA, Holmes SP. 2016. DADA2: high‐resolution sample inference from Illumina amplicon data. Nature Methods 13:581. * Chamberlain S, Szöcs E. 2013. Taxize ‐ taxonomic search and retrieval in R. F1000Research 2013:191.Martin M. 2011. Cutadapt removes adapter sequences from high‐throughput sequencing reads. EMBnet Journal 17:10–12. * Miya, M. et al., 2015. MiFish, a set of universal PCR primers for metabarcoding environmental DNA from fishes: detection of more than 230 subtropical marine species. Royal Society open science. 2, 150088. * Rognes T, Flouri T, Nichols B, Quince C, Mahé F. 2016. VSEARCH: a versatile open source tool for metagenomics. PeerJ 4:e2584. * Sigsgaard, E. E., Torquato, F., Frøslev, T. G., Moore, A. B. M., Sørensen, J. M., Range, P., Ben-Hamadou, R., Bach, S. S., Møller, P. R., & Thomsen, P. F. (2020). Using vertebrate environmental DNA from seawater in biomonitoring of marine habitats. Conservation biology: the journal of the Society for Conservation Biology, 34(3), 697–710. https://doi.org/10.1111/cobi.13437 * Taberlet, P., Bonin, A., Zinger, L., Coissac, E., 2018. Environmental DNA: For Biodiversity Research and Monitoring. Appendix 1, pp. 151-216. Oxford University Press. ## Funding This study was supported by the 15. Juni Fonden (Grant J.nr. 2016-A-101), and by the Danish Environmental Agency [Miljøstyrelsen] and by the Natural History Museum of Denmark.