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Record W4390703911 · doi:10.1093/ismeco/ycad004

A multiyear time series (2004–2012) of bacterial and archaeal community dynamics in a changing Arctic Ocean

2024· article· en· W4390703911 on OpenAlexafffundabout
Susanne A. Kraemer, Arthi Ramachandran, Vera E. Onana, William K. W. Li, David A. Walsh

Bibliographic record

VenueISME Communications · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsBedford Institute of OceanographyConcordia UniversityFisheries and Oceans CanadaEnvironment and Climate Change Canada
FundersFisheries and Oceans CanadaDivision of Ocean SciencesNatural Sciences and Engineering Research Council of CanadaConcordia University
KeywordsArcticClimate changeOceanographyEnvironmental scienceThaumarchaeotaArctic vegetationEcosystemSea iceEcologyBiologyGeologyArchaeaTundra

Abstract

fetched live from OpenAlex

Abstract Climate change is profoundly impacting the Arctic, leading to a loss of multiyear sea ice and a warmer, fresher upper Arctic Ocean. The response of microbial communities to these climate-mediated changes is largely unknown. Here, we document the interannual variation in bacterial and archaeal communities across a 9-year time series of the Canada Basin that includes two historic sea ice minima (2007 and 2012). We report an overall loss of bacterial and archaeal community richness and significant shifts in community composition. The magnitude and period of most rapid change differed between the stratified water layers. The most pronounced changes in the upper water layers (surface mixed layer and upper Arctic water) occurred earlier in the time series, while changes in the lower layer (Pacific-origin water) occurred later. Shifts in taxonomic composition across time were subtle, but a decrease in Bacteroidota taxa and increase in Thaumarchaeota and Euryarchaeota taxa were the clearest signatures of change. This time series provides a rare glimpse into the potential influence of climate change on Arctic microbial communities; extension to the present day should contribute to deeper insights into the trajectory of Arctic marine ecosystems in response to warming and freshening.

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)0.001
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 score0.519
Threshold uncertainty score0.967

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.246
Teacher spread0.230 · 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

Citations4
Published2024
Admission routes3
Has abstractyes

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