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Record W4389398694 · doi:10.1038/s43247-023-01140-6

Hypoxia-tolerant zooplankton may reduce biological carbon pump efficiency in the Humboldt current system off Peru

2023· article· en· W4389398694 on OpenAlexaff
Anja Engel, Carolina Cisternas‐Novoa, Helena Hauss, Rainer Kiko, Frédéric A.C. Le Moigne

Bibliographic record

VenueCommunications Earth & Environment · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsMemorial University of Newfoundland
FundersBundesministerium für Bildung und ForschungAgence Nationale de la RechercheHelmholtz AssociationDeutsche Forschungsgemeinschaft
KeywordsZooplanktonMesopelagic zoneUpwellingOceanographyEnvironmental scienceCarbon sequestrationOxygen minimum zoneHypoxia (environmental)Carbon fibersCarbon dioxideCarbon dioxide in Earth's atmosphereEcosystemWater columnBiological pumpGelatinous zooplanktonTotal organic carbonAtmospheric carbon cycleEcologyCarbon cycleOxygenPelagic zoneBiologyChemistryGeologyMaterials science

Abstract

fetched live from OpenAlex

Abstract In the ocean, downward flux of particles produced in sunlit surface waters is the major component of the biological carbon pump, which sequesters atmospheric carbon dioxide and fuels deep-sea ecosystems. The efficiency of downward carbon transfer is expected to be particularly high in tropical upwelling systems where hypoxia occurring beneath the productive surface waters is thought to hamper particle consumption. However, observations of both particle feeders and carbon export in low-oxygen waters are scarce. Here, we provide evidence that hypoxia-tolerant zooplankton feed on sinking particles in the extensive Oxygen Minimum Zone (OMZ) off Peru. Using several arrays of drifting sediment traps and in situ imaging, we show geochemical and morphological transformations of sinking particles and substantial control of carbon export by zooplankton. Our findings challenge the assumption of a consistently efficient biological carbon pump in OMZs and further demonstrate the need to consider mesopelagic organisms when studying oceanic carbon sequestration.

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 score0.023
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.046
GPT teacher head0.240
Teacher spread0.194 · 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

Citations4
Published2023
Admission routes1
Has abstractyes

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