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Data · dataset · 2025

Revealing the diversity of bacteria in the active layer of permafrost at Spitsbergen island (Arctic) – Combining classical microbiology and metabarcoding for ecological and bioprospecting exploration

Listed in GBIF and University of Warsaw Research Data Repository — shown once because both records carry DOI 10.15468/ahrzgg

In this dataset, results of investigating the culturable biodiversity of microbial communities of Arctic soils – a pristine environment with still poorly explored biodiversity, are presented.

Description

The soil sampling covered diverse Arctic ecosystems, including soils under marine influence, zoogenic soil, and glacier moraine. Samples were taken in August 2017.

Physicochemical analyses showed a relatively high ratio of carbon to nitrogen (average 10:1) in the analyzed soils, which indicates a high influence of soil microorganisms on the shaping of the investigated ecosystems. Cultivation experiments using different rich and minimal growth media were conducted and metabarcoded using Ilumina sequencing of 16S rDNA to assess the overall microbial cultivability of Arctic soils. As revealed from the combining this results with soil metabarcoding (soil metabarcoding not included in this dataset), the culture-dependent approach allowed for the recovery of 6.37 % of bacterial genera when compared with the culture-independent approach.

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This indicates that majority of bacterial taxa may remain unexplored when performed sole classical cultivation approach. This dataset is related to the paper: Dziurzyński, M., Górecki, A., Pawłowska, J., Istel, Ł., Decewicz, P., Golec, P., Styczyński, M., Poszytek, K., Rokowska, A., Górniak, D., & Dziewit, Ł. (2023).

Revealing the diversity of bacteria and fungi in the active layer of permafrost at Spitsbergen Island (Arctic) – Combining classical microbiology and metabarcoding for ecological and bioprospecting exploration. Science of The Total Environment, 856(Part 2), 159072, containing also fungal data. [This dataset was processed using the GBIF Metabarcoding Data Toolkit.]

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From keywords
Life Sciences
Inferred from text
Microbial taxonomy 79% · Sequencing 75%
Provenance · 2 source records, 12 field assertions
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GBIF0ac6ba1c-d18f-4a49-9a8e-1a444f33d06810 d agoJSON v1
University of Warsaw Research Data Repositorydoi:10.15468/ahrzgg10 d agoJSON v1
FieldAssertionExtractorEvidence
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concepts[modality].local:modality:sequencingenrichment · gbifkeyword-concept-rules@1.0.0title+description (75%)
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