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Record W1525439457 · doi:10.1002/2014jc010583

High turnover rates indicated by changes in the fixed <scp>N</scp> forms and their stable isotopes in <scp>A</scp>ntarctic landfast sea ice

2015· article· en· W1525439457 on OpenAlexaff
François Fripiat, Daniel M. Sigman, Guillaume Massé, Jean‐Louis Tison

Bibliographic record

VenueJournal of Geophysical Research Oceans · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsUniversité Laval
FundersFonds Wetenschappelijk OnderzoekInstitut Polaire Français Paul Emile VictorFonds De La Recherche Scientifique - FNRSPrinceton UniversityNational Science Foundation
KeywordsNitrateSea iceSeawaterNitrogen assimilationNitrificationOceanographyPhytoplanktonNitrogen cycleAlgaeNitrogenChemistryIce shelfEnvironmental chemistryEnvironmental scienceGeologyCryosphereNutrientEcologyBiology

Abstract

fetched live from OpenAlex

Abstract We report concentration and nitrogen and oxygen isotopic measurements of nitrate, total dissolved nitrogen, and particulate nitrogen from Antarctic landfast sea ice, covering almost the complete seasonal cycle of sea ice growth and decay (from April to November). When sea ice forms in autumn, ice algae growth depletes nitrate and accumulates organic N within the ice. Subsequent low biological activity in winter imposes minor variations in the partitioning of fixed N. In early spring, the coupling between nitrate assimilation and brine convection at the sea ice bottom traps a large amount of fixed N within sea ice, up to 20 times higher than in the underlying seawater. At this time, remineralization and nitrification also accelerate, yielding nitrate concentrations up to 5 times higher than in seawater. Nitrate δ 15 N and δ 18 O are both elevated, indicating a near‐balance between nitrification and nitrate assimilation. These findings require high microbially mediated turnover rates for the large fixed N pools, including nitrate. When sea ice warms in the spring, ice algae grow through the full thickness of the ice. The warming stratifies the brine network, which limits the exchange with seawater, causing the once‐elevated nitrate pool to be nearly completely depleted. The nitrate isotope data point to light limitation at the base of landfast ice as a central characteristic of the environment, affecting its N cycling (e.g., allowing for nitrification) and impacting algal physiology (e.g., as reflected in the N and O isotope effects of nitrate assimilation).

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.087
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.029
GPT teacher head0.262
Teacher spread0.233 · 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.

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

Citations30
Published2015
Admission routes1
Has abstractyes

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