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Record W4381832431 · doi:10.1525/elementa.2021.00080

Similarity in phytoplankton photophysiology among under-ice, marginal ice, and open water environments of Baffin Bay (Arctic Ocean)

2023· article· en· W4381832431 on OpenAlexafffund
Hannah L. Joy‐Warren, Kate M. Lewis, Mathieu Ardyna, Jean‐Éric Tremblay, Marcel Babin, Kevin R. Arrigo

Bibliographic record

VenueElementa Science of the Anthropocene · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsUniversité Laval
FundersOffice of Polar ProgramsCentre National d’Etudes SpatialesArcticNetAgence Nationale de la RechercheNational Science Foundation
KeywordsPhytoplanktonSea iceOceanographyEnvironmental scienceArcticBayArctic ice packUpwellingGeologyEcologyNutrientBiology

Abstract

fetched live from OpenAlex

As sea ice is declining rapidly in the Arctic, phytoplankton are being exposed to very different light regimes. Here we investigated how phytoplankton photoacclimate in three different irradiance regimes: under the ice, in the marginal ice zone, and in open water. We sampled from these three regimes in spring–summer 2016 during the Green Edge cruise in Baffin Bay. We also conducted experiments to investigate the impact of short-term surface light exposure on phytoplankton photophysiology, focusing on processes related to photoprotection and photodamage. These experiments were designed to simulate phytoplankton mixing to the surface or sea ice rapidly disappearing. Despite differences in hydrography, nutrient concentrations, light conditions, and phytoplankton biomass in each regime, the phytoplankton community was similar in terms of photophysiological state. Photoprotective pigments (including the xanthophyll cycle) were high in all three regimes sampled. As with the in situ measurements, ice conditions and light history had little impact on how phytoplankton responded to high light exposure, leading us to conclude that phytoplankton are largely prepared for a high light transition, even when originating from low light environments under sea ice.

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)0.001
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 score0.015
Threshold uncertainty score0.930

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.014
GPT teacher head0.246
Teacher spread0.233 · 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

Citations3
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueElementa Science of the AnthropoceneSame topicArctic and Antarctic ice dynamicsFrench-language works237,207