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Record W2771082521 · doi:10.3389/fmicb.2017.02498

Prokaryotic Community Composition in Arctic Kongsfjorden and Sub-Arctic Northern Bering Sea Sediments As Revealed by 454 Pyrosequencing

2017· article· en· W2771082521 on OpenAlexaboutno aff
Yin–Xin Zeng, Yong Yu, Huirong Li, Wei Luo

Bibliographic record

VenueFrontiers in Microbiology · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial Community Ecology and Physiology
Canadian institutionsnot available
FundersChinese Arctic and Antarctic AdministrationChinese Polar Environment Comprehensive Investigation and Assessment ProgrammesNational Natural Science Foundation of China
KeywordsArcticOceanographyThaumarchaeotaCanada BasinSea iceGammaproteobacteriaEcologyGeologyBiologyArchaeaPaleontology

Abstract

fetched live from OpenAlex

Fjords and continental shelves represent distinct marine ecosystems in the pan-arctic region. Kongsfjorden is a glacial fjord that is located on the west coast of Svalbard, and is influenced by both Atlantic and Arctic water masses. The Bering Sea consists of a huge continental shelf in the northeast and a deep ocean basin in the southwest, and is influenced by Pacific water. Microbial community compositions of Arctic sediment samples BJ4 from outer basin and BJ36 from inner basin of Kongsfjorden and sub-Arctic samples NEC5 from shallow shelf and DBS1 from deep basin region of the northern Bering Sea were investigated using 454 pyrosequencing of archaeal and bacterial 16S rRNA genes. Most archaeal sequences in the sediments were related to Thaumarchaeota, though Euryarchaeota were more abundant in the Arctic glacier-influencing inner basin sediment BJ36. Thaumarchaeota Group C3 was the dominant archaeal population in all samples. Proteobacteria and Bacteroidetes dominated the sediment bacterial communities. Acidobacteria and Actinobacteria were also dominant in the northern Bering Sea samples. Alphaproteobacteria and Epsilonproteobacteria were the two main classes in Kongsfjorden sediment bacterial communities while Deltaproteobacteria and Gammaproteobacteria were dominant in the northern Bering Sea sediments. Differences in the presence and abundance of other dominant archaeal and bacterial populations were observed among sediment samples. In contrast to archaeal community differences that the Arctic BJ36 archaeal community was distinct from the sub-Arctic sediments and the Arctic outer basin sediment BJ4, cluster analysis based on bacterial OTU (Operational Taxonomic Unit) distributions indicated that the Arctic and sub-Arctic bacterial communities segregated from one another. These results suggest that the sediment archaeal and bacterial community compositions can be driven by different environmental factors. Differences in the presence and abundance of particular archaeal species (e.g. Candidatus Nitrosopumilus and Methanococcoides) or bacterial species (e.g. Sulfurimonas, Sulfurovum and Desulfobulbaceae) involved in biogeochemical cycles were also observed among sediment samples. At the same time, despite the community variation, some phylotypes (e.g. Marinicella) were dominant in all sediments. This study indicates diverse microbial communities inhabiting pan-arctic marine sediments, and highlights potential roles for Archaea and Bacteria in global biogeochemical cycles in these environments.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.040
Threshold uncertainty score0.080

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.221
Teacher spread0.213 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations27
Published2017
Admission routes1
Has abstractyes

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