Invertebrate eDNA Gotland Summer 2021

Data Records

The data in this sampling event resource has been published as a Darwin Core Archive (DwC-A), which is a standardized format for sharing biodiversity data as a set of one or more data tables. The core data table contains 9 records.

3 extension data tables also exist. An extension record supplies extra information about a core record. The number of records in each extension data table is illustrated below.

This IPT archives the data and thus serves as the data repository. The data and resource metadata are available for download in the downloads section. The versions table lists other versions of the resource that have been made publicly available and allows tracking changes made to the resource over time.

Versions

The table below shows only published versions of the resource that are publicly accessible.

How to cite

Researchers should cite this work as follows:

Nordlund L M, Lüskow F, Lawrence E (2026). Invertebrate eDNA Gotland Summer 2021. Version 2.1. OBIS Secretariat. Samplingevent dataset. https://doi.org/10.25607/bgjoog

Rights

Researchers should respect the following rights statement:

The publisher and rights holder of this work is OBIS Secretariat. This work is licensed under a Creative Commons Attribution Non Commercial (CC-BY-NC 4.0) License.

GBIF Registration

This resource has been registered with GBIF, and assigned the following GBIF UUID: afdf89d6-4aa9-41e1-bc3d-cee33befa66c.  OBIS Secretariat publishes this resource, and is itself registered in GBIF as a data publisher endorsed by Ocean Biodiversity Information System.

Keywords

Samplingevent; Benthic invertebrates: http://vocab.nerc.ac.uk/collection/EXV/current/EXV068/ Zooplankton: http://vocab.nerc.ac.uk/collection/EXV/current/EXV057/

Contacts

Geographic Coverage

Coastal waters of Gotland in the central Baltic Sea

Temporal Coverage

Project Data

No Description available

The personnel involved in the project:

Sampling Methods

Environmental DNA (eDNA) water samples were collected using a stratified random sampling approach to ensure coverage across distinct areas of the coastal bays. At each of the three sites, three separate 5-litre water samples were collected from a depth of < 0.5 m below the surface, either from a boat or by snorkelling. Samples were immediately stored on ice in cooler boxes for transport. In the laboratory, 500 ml from each 5-litre collection was filtered through a Nalgene® analytical filter funnel with a 0.45 µm pore size. The resulting filters were preserved in 200-proof ethanol and stored at -20°C until further processing. At the time of collection, in situ measurements for temperature, salinity, and dissolved oxygen were recorded using a handheld Elma 795 Multi Chemistry instrument.

Method step description:

1. The analytical workflow followed a standardised marine eDNA metabarcoding pipeline: - DNA extraction & purification: DNA was extracted from the filters using a commercial kit with a modified protocol to maximise yields and purified to remove PCR inhibitors - PCR amplification: the V4–V5 region of the 18S rRNA gene was targeted to capture a broad range of invertebrates. Standard analysis included three PCR replicates per sample - Library preparation & sequencing: PCR amplicons were purified, quantified using a Qubit broad-range kit, and pooled into a final library at equal concentrations; sequencing was performed on an Illumina MiSeq V3 kit (10.5 pM) with a 20% PhiX spike-in - Bioinformatics & taxonomic assignment: Sequences were processed through a custom pipeline for quality filtering and Operational Taxonomic Unit (OTU) clustering. Taxonomic assignments were made by comparing consensus sequences against the NCBI nt and SILVA 18S (v138.1) databases, using the GBIF taxonomic backbone for consistency; minimum similarity thresholds were set at 98% for species, 95% for genus, and 92% for higher taxonomic levels - Data filtering & analysis: The final dataset was filtered to remove low-abundance OTUs (< 0.025% or < 10 reads) and common contaminants; for multivariate analysis, OTU data were transformed into presence–absence data to account for biological and methodological biases in read proportions

Additional Metadata