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Recycling of Polyphosphate accumulated in picoplankton in coastal Lake Ontario

2020· article· en· W3084642730 on OpenAlexaffabout
Maria Dittrich, Jiying Li, Diane Plouchart, Arthur Zastepa

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicPhosphorus and nutrient management
Canadian institutionsEnvironment and Climate Change CanadaThe Scarborough Hospital
Fundersnot available
KeywordsPicoplanktonEutrophicationPolyphosphatePlanktonPhytoplanktonPhosphorusBiogeochemical cycleProductivityBacterioplanktonAlgaePrimary producersNutrientBayBiologyEnvironmental scienceEcologyOceanographyChemistryPhosphateBiochemistryGeology

Abstract

fetched live from OpenAlex

<p>Phytoplankton can accumulate polyphosphate (polyP) to alleviate the limitation of essential nutrient phosphorus (P). Yet polyP metabolisms in aquatic systems and their roles in P biogeochemical cycle remain elusive. Previously reported polyP enrichment in low-phosphorus oligotrophic marine waters contradicts the common view of polyP as a luxury P-storage molecule. Here, we show that in a P-rich eutrophic bay of Lake Ontario, planktonic polyP is controlled by multiple mechanisms and responds strongly to seasonal variations. Plankton accumulates polyP as P storage under high-P conditions via luxury uptake and uses it under acute P stress. Low phosphorus also triggers enrichment of polyP that can be preferentially recycled to attenuate P lost. We discover that picoplankton, despite their low production rates, are responsible for the dynamic polyP metabolisms. Picoplankton store and liberate polyP to support the high primary productivity of blooming algae. PolyP mechanisms enable and P exchange and efficient P recycling on the ecosystem and even larger scales.</p>

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 score0.589
Threshold uncertainty score0.997

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)0.0040.000

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 head0.019
GPT teacher head0.218
Teacher spread0.199 · 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

Citations0
Published2020
Admission routes2
Has abstractyes

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