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Record W2786155428 · doi:10.1111/gcb.14075

Increased intrusion of warming Atlantic water leads to rapid expansion of temperate phytoplankton in the Arctic

2018· article· en· W2786155428 on OpenAlexafffund
Griet Neukermans, Laurent Oziel, Marcel Babin

Bibliographic record

VenueGlobal Change Biology · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsUniversité LavalMakivik Corporation
FundersNatural Sciences and Engineering Research Council of CanadaHorizon 2020 Framework Programme
KeywordsTemperate climatePhytoplanktonEnvironmental scienceArcticOceanographyIntrusionClimate changeGlobal warmingEcologyClimatologyGeologyBiologyNutrient

Abstract

fetched live from OpenAlex

The Arctic Ocean and its surrounding shelf seas are warming much faster than the global average, which potentially opens up new distribution areas for temperate-origin marine phytoplankton. Using over three decades of continuous satellite observations, we show that increased inflow and temperature of Atlantic waters in the Barents Sea resulted in a striking poleward shift in the distribution of blooms of Emiliania huxleyi, a marine calcifying phytoplankton species. This species' blooms are typically associated with temperate waters and have expanded north to 76°N, five degrees further north of its first bloom occurrence in 1989. E. huxleyi's blooms keep pace with the changing climate of the Barents Sea, namely ocean warming and shifts in the position of the Polar Front, resulting in an exceptionally rapid range shift compared to what is generally detected in the marine realm. We propose that as the Eurasian Basin of the Arctic Ocean further atlantifies and ocean temperatures continue to rise, E. huxleyi and other temperate-origin phytoplankton could well become resident bloom formers in the Arctic Ocean.

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 score0.015
Threshold uncertainty score0.030

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 studies0.0000.000
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 head0.024
GPT teacher head0.247
Teacher spread0.223 · 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

Citations231
Published2018
Admission routes2
Has abstractyes

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