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Record W2995841677 · doi:10.1038/s41598-019-56042-5

Picoplankton accumulate and recycle polyphosphate to support high primary productivity in coastal Lake Ontario

2019· article· en· W2995841677 on OpenAlexafffundabout
Jiying Li, Diane Plouchart, Arthur Zastepa, Maria Dittrich

Bibliographic record

VenueScientific Reports · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Ecosystems and Phytoplankton Dynamics
Canadian institutionsThe Scarborough HospitalEnvironment and Climate Change CanadaUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of WaterlooCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada
KeywordsPicoplanktonPrimary productivityPolyphosphateProductivityPrimary (astronomy)Environmental scienceFisheryOceanographyEcologyNutrientBiologyGeologyPhytoplanktonPhosphateBiochemistry

Abstract

fetched live from OpenAlex

Phytoplankton can accumulate polyphosphate (polyP) to alleviate 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 accumulate polyP as P storage under high-P conditions via luxury uptake and use 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 efficient P recycling on ecosystem and even larger scales.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.414
Threshold uncertainty score0.832

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.205
Teacher spread0.198 · 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 source (direct Gemma or distilled Codex), 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

Citations35
Published2019
Admission routes3
Has abstractyes

Explore more

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