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A comprehensive dataset on spatiotemporal variation of microbial plankton communities in the Baltic Sea
KTH Royal Institute of Technology, Department of Gene Technology, Science for Life Laboratory, Stockholm, Sweden; University of Copenhagen, Department of Plant and Environmental Sciences, Frederiksberg C, Denmark.
Umeå University, Faculty of Science and Technology, Department of Ecology and Environmental Sciences. Umeå University, Faculty of Science and Technology, Umeå Marine Sciences Centre (UMF). (EcoChange; UMFpub)ORCID iD: 0000-0001-7819-9038
Umeå University, Faculty of Science and Technology, Department of Ecology and Environmental Sciences. Umeå University, Faculty of Science and Technology, Umeå Marine Sciences Centre (UMF).ORCID iD: 0000-0002-1298-3839
Swedish Meteorological and Hydrological Institute, Community Planning Services - Oceanography, Västra Frölunda, Sweden.
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2024 (English)In: Scientific Data, E-ISSN 2052-4463, Vol. 11, no 1, article id 18Article in journal (Refereed) Published
Abstract [en]

The Baltic Sea is one of the largest brackish water environments on earth and is characterised by pronounced physicochemical gradients and seasonal dynamics. Although the Baltic Sea has a long history of microscopy-based plankton monitoring, DNA-based metabarcoding has so far mainly been limited to individual transect cruises or time-series of single stations. Here we report a dataset covering spatiotemporal variation in prokaryotic and eukaryotic microbial communities and physicochemical parameters. Within 13-months between January 2019 and February 2020, 341 water samples were collected at 22 stations during monthly cruises along the salinity gradient. Both salinity and seasonality are strongly reflected in the data. Since the dataset was generated with both metabarcoding and microscopy-based methods, it provides unique opportunities for both technical and ecological analyses, and is a valuable biodiversity reference for future studies, in the prospect of climate change.

Place, publisher, year, edition, pages
Springer Nature, 2024. Vol. 11, no 1, article id 18
National Category
Oceanography, Hydrology and Water Resources Ecology
Identifiers
URN: urn:nbn:se:umu:diva-219321DOI: 10.1038/s41597-023-02825-5PubMedID: 38168085Scopus ID: 2-s2.0-85181259194OAI: oai:DiVA.org:umu-219321DiVA, id: diva2:1827286
Note

The raw sequencing data generated in this study are available at the European Nucleotide Archive (ENA) under the study accession number https://identifiers.org/ena.embl:PRJEB55296 (2023).

Processed sequencing data (ASV sequences with taxonomic annotations and counts in samples) are available at our figshare repository (https://doi.org/10.17044/scilifelab.20751373), along with the contextual, physicochemical, and microscopy data, and sequences of synthetic spike-ins. 

Available from: 2024-01-12 Created: 2024-01-12 Last updated: 2024-01-15Bibliographically approved

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Andersson, AgnetaBrugel, Sonia

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