Invertebrate eDNA Gotland Summer 2021

Registros de Dados

Os dados deste recurso de evento de amostragem foram publicados como um Darwin Core Archive (DwC-A), que é o formato padronizado para compartilhamento de dados de biodiversidade como um conjunto de uma ou mais tabelas de dados. A tabela de dados do núcleo contém 9 registros.

Também existem 3 tabelas de dados de extensão. Um registro de extensão fornece informações adicionais sobre um registro do núcleo. O número de registros em cada tabela de dados de extensão é ilustrado abaixo.

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.

Versões

A tabela abaixo mostra apenas versões de recursos que são publicamente acessíveis.

Como citar

Pesquisadores deveriam citar esta obra da seguinte maneira:

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

Direitos

Pesquisadores devem respeitar a seguinte declaração de direitos:

O editor e o detentor dos direitos deste trabalho é OBIS Secretariat. This work is licensed under a Creative Commons Attribution Non Commercial (CC-BY-NC 4.0) License.

GBIF Registration

Este recurso foi registrado no GBIF e atribuído ao seguinte GBIF UUID: afdf89d6-4aa9-41e1-bc3d-cee33befa66c.  OBIS Secretariat publica este recurso, e está registrado no GBIF como um publicador de dados aprovado por Ocean Biodiversity Information System.

Palavras-chave

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

Contatos

Cobertura Geográfica

Coastal waters of Gotland in the central Baltic Sea

Cobertura Temporal

Dados Sobre o Projeto

Nenhuma descrição disponível

O pessoal envolvido no projeto:

Métodos de Amostragem

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.

Descrição dos passos do método:

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

Metadados Adicionais