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Record W2171643577 · doi:10.4319/lo.2012.57.4.1182

Iron‐light interactions differ in Southern Ocean phytoplankton

2012· article· en· W2171643577 on OpenAlexaff
Robert F. Strzepek, Keith A. Hunter, Russell Frew, Paul J. Harrison, Philip W. Boyd

Bibliographic record

VenueLimnology and Oceanography · 2012
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsUniversity of British Columbia
FundersMarsden FundMinisterio de Ciencia e Innovación
KeywordsPhytoplanktonPhotosynthesisHaptophyteThalassiosira weissflogiiTemperate climateOceanographyDiatomAcclimatizationPaleoceanographySeawaterDinoflagellateAlgaeEmiliania huxleyiBiologyIrradianceEnvironmental chemistryBotanyChemistryEcologyNutrientGeology

Abstract

fetched live from OpenAlex

In laboratory experiments we examined the interplay of light and iron availability on the intracellular iron concentrations, specific growth rates, and photosynthetic physiology of Southern (S.) Ocean diatoms ( Eucampia antarctica and Proboscia inermis ) and the haptophyte Phaeocystis antarctica . Intracellular iron concentrations and iron : carbon (Fe : C) molar ratios increased with decreasing irradiance in temperate coastal ( Thalassiosira weissflogii ) and oceanic ( Thalassiosira oceanica ) diatoms, in support of the well‐established antagonistic iron‐light relationship. In contrast, S. Ocean species required lower cellular iron concentrations and Fe : C ratios than temperate diatoms to grow at comparable rates, and their iron requirements decreased or remained relatively constant with decreasing light. These results suggest that the current paradigm that low light increases algal cellular iron requirements (supplied through “biodilution”) is not applicable to S. Ocean phytoplankton. Although iron use efficiencies decreased at sub‐saturating light in all species, these reductions were due primarily to lower growth rates, but not higher intracellular Fe : C ratios, in S. Ocean species. We propose that S. Ocean species have overcome the antagonistic iron‐light relationship by increasing the size, rather than the number, of photosynthetic units under low irradiances, resulting in an acclimation strategy that does not increase their cellular iron requirements.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.834

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 studies0.0000.000
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 head0.007
GPT teacher head0.190
Teacher spread0.183 · 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

Citations182
Published2012
Admission routes1
Has abstractyes

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