DOI: 10.5061/dryad.bvq83bkkq
title: Data from: DNA metabarcoding as a tool to study plankton responses to warming and salinity change in mesocosms

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.
description: 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.
description: # Data from: DNA metabarcoding as a tool to study plankton responses to
 warming and salinity change in mesocosms
 [https://doi.org/10.5061/dryad.bvq83bkkq](https://doi.org/10.5061/dryad.bvq83bkkq) ## Description of the data and file structure This dataset contains species abundance data from a mesocosm experiment conducted at Tvärminne Zoological Station, Finland (59.84° N, 23.25° E), between September and October 2022. The experiment investigated the effects of warming and salinity changes on plankton communities using microscopy-based counts, DNA metabarcoding (18S rRNA and COI markers), and associated environmental metadata. ### Files and variables #### File: new_metadata.tsv **Description:** This file contains metadata associated with the mesocosm experiment to use with metabarcoding tables, including sample identifiers, environmental conditions, and treatment groups. ##### Variables * sample_metab: Unique identifier for each sample. * Treatment: Identifier for the experimental mesocosm. * Date: Timepoint of sample collection (Start, Mid, End). * Temperature: Temperature treatment (Low, High). * Salinity: Salinity treatment in PSU (Practical Salinity Units). #### File: all_plakton_micro_wide.csv **Description:** This file contains plankton abundance data obtained from microscopy, with individual species abundances recorded for each sample in wide format with species names. ##### Variables * date: Timepoint of sample collection (Start, Mid, End). * sample: Unique identifier for each sample. * salinity: Salinity treatment in PSU (Practical Salinity Units). * temperature: Temperature treatment (Low, High). * mesocosm_id: Identifier for the experimental mesocosm. * Other columns are individual species names #### File: Aquacosm2022_DataTZS.csv **Description:** This file contains extra environmental data from the mesocosm experiment, including temperature, salinity and chlorophyll measurements. ##### Variables * Mesocosm: Identifier for the experimental mesocosm. * Temperature_treatment: Temperature treatment (Low, High). * Salinity_treatment: Salinity treatment in PSU (Practical Salinity Units). * DOY: Day of the year. * Date: Date of sample collection (YYYY-MM-DD). * Temperature: Actual water temperature (°C). * Salinity: Actual salinity (PSU). * O2_mgL: Dissolved oxygen concentration (mg/L). * Fluorescence: Fluorescence in RFU (Relative Fluorescence Units). #### File: mesocosm-18s_dada2_v1.0.filtered.table.lulu.with.taxo.tsv **Description:** This file contains DNA metabarcoding data from the 18S rRNA gene marker, including taxonomic assignments and sequence abundance across samples. ##### Variables * amplicon:  Unique identifier for each ASV (Amplicon Sequence Variant). * upper_similarity_vsearch: Upper similarity threshold from VSEARCH taxonomic assignment. * lower_similarity_vsearch: Lower similarity threshold from VSEARCH taxonomic assignment. * references_vsearch: Accession numbers of reference sequences used for taxonomic assignment in VSEARCH.  * taxonomy_vsearch: Taxonomic classification based on VSEARCH. * taxonomy_idtaxa: Taxonomic classification based on IDTAXA. * confidence_idtaxa:  Confidence score for IDTAXA classification. * sequence: DNA sequence of the ASV. * total: Total sequence reads per ASV. * spread: Distribution of sequence reads across samples. * Blank-22-9, Blank-6-10, Blank-8-9, etc: Control sample identifiers. * m1-22-9, m2-6-10, etc:  Mesocosm sample identifiers. * pcr-0ctrl1, pcr-0ctrl3: PCR negative control sample identifiers. #### File: mesocosm-coi_dada2_v1.0.filtered.table.d4.lulu.with.taxo.tsv **Description:** This file contains DNA metabarcoding data from the COI gene marker, including taxonomic assignments and sequence abundance across samples. ##### Variables * amplicon:  Unique identifier for each ASV (Amplicon Sequence Variant). * upper_similarity_vsearch: Upper similarity threshold from VSEARCH taxonomic assignment. * lower_similarity_vsearch: Lower similarity threshold from VSEARCH taxonomic assignment. * references_vsearch: Accession numbers of reference sequences used for taxonomic assignment in VSEARCH.  * taxonomy_vsearch: Taxonomic classification based on VSEARCH. * taxonomy_idtaxa: Taxonomic classification based on IDTAXA. * confidence_idtaxa: Confidence score for IDTAXA classification. * sequence: DNA sequence of the ASV. * total: Total sequence reads per ASV. * spread: Distribution of sequence reads across samples. * Blank-22-9, Blank-6-10, Blank-8-9, etc: Control sample identifiers. * m1-22-9, m2-6-10, etc:  Mesocosm sample identifiers. * pcr-0ctrl1, pcr-0ctrl3: PCR negative control sample identifiers. #### File: long_table_with_taxonomy.csv **Description:** This file contains long-format species abundance data with taxonomic classifications. ##### Variables * date: Timepoint of sample collection (Start, Mid, End). * sample: Unique identifier for each sample. * salinity: Salinity treatment in PSU (Practical Salinity Units). * temperature: Temperature treatment (Low, High). * mesocosm_id: Identifier for the experimental mesocosm. * species: Species/taxa names. * units.per.l: Individuals/cells per litre. * taxonomy:  Full taxonomic classification of the species. **NA:** In this dataset, NA represents values that were *not available* (e.g., unassigned taxonomy or unmeasured variables). ## Code/software Details about metabarcoding workflows for generating ASV and OTU tables are available at [https://gitlab.com/tvarminne-metabarcoding/mesocosm-18s-bioinfo](https://gitlab.com/tvarminne-metabarcoding/mesocosm-18s-bioinfo) and [https://gitlab.com/tvarminne-metabarcoding/mesocosm-coi-bioinfo](https://gitlab.com/tvarminne-metabarcoding/mesocosm-coi-bioinfo). Zip files of these is also available here under 'mesocosm-18s-bioinfo-main-2.zip' and 'mesocosm-coi-bioinfo-main.zip'. **Code for analysis:** This dataset includes R scripts used for analysing mesocosm experiment data, including statistical modelling, visualisation and diversity analyses. The analyses were performed using R (version 4.4.2). **R packages required:** * tidyverse: Data manipulation * vegan: NMDS, PERMANOVA and diversity analysis * ggplot2: Visualisation of bar plots and graphs * phyloseq: Analysis of metabarcoding data * nlme: Linear models and mixed-effects models * dplyr: Data manipulation * ggpubr: Multiple plotting * patchwork: Combines multiple ggplot figures into a single layout * gridExtra: Arranges multiple grid-based plots * cowplot: Multi-panel figures * MicrobiomeStat: Statistical analysis for microbiome and community data (LinDA analysis) * purrr: Handling lists and iteration * RColorBrewer: Predefined color palettes for data visualisation * data.table: Data manipulation and aggregation * grid: Arranging plots **Description of R scripts:** 1. **Diversity_models_plots_micro_metaB.R**: Runs diversity models and creates plots comparing microscopy and metabarcoding diversity data. Uses data: 'long_table_with_taxonomy.csv', 'mesocosm-coi_dada2_v1.0.filtered.table.d4.lulu.with.taxo.tsv', 'mesocosm-18s_dada2_v1.0.filtered.table.lulu.with.taxo.tsv', and 'new_metadata.tsv'. 2. **Fluorescence_graph.R**: Generates fluorescence graph visualisations. Uses data: 'Aquacosm2022_DataTZS.csv' 3. **LinDA script final.R**: Performs differential abundance analysis (LinDA) on ASV/OTU data. Uses data: 'mesocosm-coi_dada2_v1.0.filtered.table.d4.lulu.with.taxo.tsv', 'mesocosm-18s_dada2_v1.0.filtered.table.lulu.with.taxo.tsv,' and 'new_metadata.tsv'. 4. **linear_models_micro.R**: Runs statistical models on microscopy-based abundance data. Uses data: 'long_table_with_taxonomy.csv'.  5. **NMDS PERMANOVA.R**: Conducts Non-Metric Multidimensional Scaling (NMDS) and PERMANOVA analyses. Uses data: 'all_plakton_micro_wide.csv', 'mesocosm-coi_dada2_v1.0.filtered.table.d4.lulu.with.taxo.tsv', 'mesocosm-18s_dada2_v1.0.filtered.table.lulu.with.taxo.tsv', and 'new_metadata.tsv'. 6. **zooplankton_ciliate_protist relative abundance barplot ASV and micro.R**: Generates ASV/OTU and species relative abundance bar plots for zooplankton, ciliates, and protists. Uses data: 'long_table_with_taxonomy.csv', 'mesocosm-coi_dada2_v1.0.filtered.table.d4.lulu.with.taxo.tsv', 'mesocosm-18s_dada2_v1.0.filtered.table.lulu.with.taxo.tsv,' and 'new_metadata.tsv'. 7. **zooplankton_ciliate_protist richness barplot ASV and micro.R**: Generates ASV/OTU and unique species richness bar plots for zooplankton, ciliates, and protists. Uses data: 'long_table_with_taxonomy.csv', 'mesocosm-coi_dada2_v1.0.filtered.table.d4.lulu.with.taxo.tsv', 'mesocosm-18s_dada2_v1.0.filtered.table.lulu.with.taxo.tsv,' and 'new_metadata.tsv'.