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Record W2074072916 · doi:10.1111/1574-6941.12154

Spatio-temporal changes in the structure of archaeal communities in two deep freshwater lakes

2013· article· en· W2074072916 on OpenAlexaff
Lyria Berdjeb, Thomas V. Pollet, Cécile Chardon, Stéphan Jacquet

Bibliographic record

VenueFEMS Microbiology Ecology · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial Community Ecology and Physiology
Canadian institutionsUniversité du Québec à Rimouski
FundersInstitut National de la Recherche AgronomiqueAgence Nationale de la Recherche
KeywordsBiologyEcologyArchaeaCommunity structureTrophic levelAbiotic componentPhylumHypolimnionBiotic componentNutrientEutrophicationBacteria

Abstract

fetched live from OpenAlex

In this study, we evaluated the driving forces exerted by a large set of environmental and biological parameters on the spatial and temporal dynamics of archaeal community structure in two neighbouring peri-alpine lakes that differ in terms of trophic status. We analysed monthly data from a 2-year sampling period at two depths corresponding to the epi- and hypolimnetic layers. The archaeal communities seemed to be mainly composed of ammonia-oxidizing archaea belonging to the thaumarchaeotal phylum. The spatio-temporal dynamics of these communities were very similar in the two lakes and were characterized by (1) disparities in archaeal community structure in both time and space and (2) no seasonal reproducibility between years. The archaeal communities were regulated by a complex combination of abiotic factors, including temperature, nutrients, chlorophyll a and dissolved oxygen, and biotic factors such as heterotrophic nanoflagellates and ciliates. However, in most cases, these factors explained < 52% of the variance in archaeal community structure, while we showed in a previous study that these factors explained 70-90% of the temporal variance for bacteria. This suggests that Bacteria and Archaea may be influenced by different factors and could occupy different ecological niches despite similar spatio-temporal dynamics.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.933
Threshold uncertainty score0.989

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 studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0220.000

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 head0.011
GPT teacher head0.226
Teacher spread0.215 · 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 teacher head, not a consensus.

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

Citations32
Published2013
Admission routes1
Has abstractyes

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