Published September 1, 2025 | Version v1
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Data from: DNA metabarcoding as a tool to study plankton responses to warming and salinity change in mesocosms

  • 1. University of Helsinki
  • 2. Station Biologique de Roscoff
  • 3. AZTI
  • 4. GEOMAR Helmholtz Centre for Ocean Research Kiel

Description

Climate change is transforming marine ecosystems, with rising temperatures and changing salinity patterns expected to reshape plankton communities in the Baltic Sea. As key components of marine food webs and biogeochemical cycles, plankton are highly sensitive to environmental change. Here, we examined the effects of warming and salinity change on plankton communities using a mesocosm experiment at the Tvärminne Zoological Station, Finland. We employed both traditional microscopy-based identification and DNA metabarcoding (18S rRNA and COI markers) to assess shifts in phytoplankton, ciliates, and mesozooplankton. Our findings indicate that salinity primarily affected higher trophic levels, while warming influenced lower ones. Warmer conditions increased community evenness and favoured mixotrophic and heterotrophic taxa, whereas salinity effects were most pronounced in rotifers and copepods, reflecting species-specific tolerances. Interactive effects varied, with salinity sometimes buffering warming impacts and other times intensifying them, highlighting complex stressor interactions. Microscopy allowed for a more precise quantification of plankton abundance, whereas metabarcoding captured a broader taxonomic diversity. Our results suggest that freshening and warming in the Baltic Sea may lead to a shift towards smaller, mixotrophic and bloom-forming plankton species, with potential consequences for ecosystem functioning. This study highlights metabarcoding's value in mesocosm research while emphasising the need to refine molecular techniques for ecological interpretations.

Notes

Funding provided by: Maj and Tor Nessling Foundation
ROR ID: https://ror.org/047egay20
Award Number:

Funding provided by: Nottbeck Foundation
Crossref Funder Registry ID:
Award Number:

Methods

Samples were collected from mesocosms at a depth of 1 m. Temperature, salinity, fluorescence, and dissolved oxygen were measured every two days using a calibrated digital water meter (MU 6100 H, VWR). Water samples (4 L) were taken every two days, stored in a 10 L plastic container, and transported to the laboratory for further analysis.

Microscopy-based plankton identification: Phytoplankton, ciliates, and zooplankton samples were preserved with Lugol's iodine (1%) and counted using Utermöhl chambers under an inverted microscope (Olympus CKx41). Phytoplankton and ciliates were identified to genus level, while zooplankton were identified to genus or species where possible. Enumeration methods followed standard protocols, with abundance reported as cells or individuals per liter. 

Metabarcoding: DNA samples for metabarcoding were collected every two weeks following modified protocols from Minamoto et al. (2019). A 1000 mL water sample was filtered onto 47 mm diameter, 0.7µm pore size GF/F filters (Whatman, USA) using a vacuum pump. Filters were stored at -80°C and transported on dry ice to the Molecular Ecology and Systematics Laboratory, Finland, for sequencing. DNA was extracted using the DNeasy® Blood and Tissue kit (Qiagen) with modifications, including Buffer ATL and a 6-hour incubation. Extracted DNA was quantified via a NanoDrop 1000 spectrophotometer, and integrity was assessed by electrophoresis. The cytochrome c oxidase subunit I (COI) gene was amplified with primers mlCOIintF and HCO2198, while the 18S rRNA V9 region was amplified with primers 1391F and EukBr. PCR products were dual-indexed, pooled, and sequenced on an Illumina MiSeq platform (MiSeq V3 600-cycle flow cell) with paired-end reads (326 bp Read 1 and 278 bp Read 2). Raw sequencing reads were processed using Cutadapt v3.1 for primer removal and quality-controlled with DADA2 in R. Forward and reverse reads were merged, and chimeric sequences were removed. COI ASVs were clustered into OTUs using Swarm (local similarity threshold d = 4) and refined with LULU. Taxonomic classification used PR2 5.0.0 with IDTAXA (40% confidence threshold) for 18S ASVs and MIDORI2 (GB254) with VSEARCH (≥80% similarity) for COI OTUs. Raw sequencing data is publicly available in the European Nucleotide Archive (ENA: PRJEB79753). Details about workflows are available at https://gitlab.com/tvarminne-metabarcoding/mesocosm-18s-bioinfo and https://gitlab.com/tvarminne-metabarcoding/mesocosm-coi-bioinfo.

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Additional details

Related works

Is source of
10.5061/dryad.bvq83bkkq (DOI)