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Eukaryotes in Arctic and Antarctic cyanobacterial mats

2012· article· en· W2077648534 on OpenAlexafffund
Anne D. Jungblut, Warwick F. Vincent, Connie Lovejoy

Bibliographic record

VenueFEMS Microbiology Ecology · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicPolar Research and Ecology
Canadian institutionsCenter for Northern StudiesUniversité Laval
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsArcticNet
KeywordsBiologyProtistUlvophyceaeMicrobial matEcologyCyanobacteriaArcticBiological dispersalExtreme environmentBotanyChlorophytaAlgaePopulationBacteriaGenePaleontology

Abstract

fetched live from OpenAlex

Cyanobacterial mats are commonly found in freshwater ecosystems throughout the polar regions. Most mats are multilayered three-dimensional structures with the filamentous cyanobacteria embedded in a gel-like matrix. Although early descriptions mentioned the presence of larger organisms including metazoans living in the mats, there have been few studies specifically focused on the microbial eukaryotes, which are often small cells with few morphological features suitable for identification by microscopy. Here, we applied 18S rRNA gene clone library analysis to identify eukaryotes in cyanobacterial mat communities from both the Antarctic and the extreme High Arctic. We identified 39 ribotypes at the level of 99% sequence similarity. These consisted of taxa within algal and other protist groups including Chlorophyceae, Prasinophyceae, Ulvophyceae, Trebouxiophyceae, Bacillariophyceae, Chrysophyceae, Ciliophora, and Cercozoa. Fungi were also recovered, as were 21 metazoan ribotypes. The eukaryotic taxa appeared habitat-specific with little overlap between lake, pond, and ice shelf communities. Some ribotypes were common to both Arctic and Antarctic mats, suggesting global dispersal of these taxa and similarity in the environmental filters acting on protist communities. Many of these eukaryotic taxa likely benefit from protected, nutrient-rich microhabitats within the cyanobacterial mat environment.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.248
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.002

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 head0.224
Teacher spread0.216 · 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; both teacher heads agree on what is shown here.

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

Citations61
Published2012
Admission routes2
Has abstractyes

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