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Record W4406900818 · doi:10.1101/2025.01.27.634736

Warming, but not acidification, increases metabolism and reduces growth of redfish ( <i>Sebastes fasciatus</i> ) in the Gulf of St. Lawrence

2025· preprint· en· W4406900818 on OpenAlexaff
Joëlle Guitard, Denis Chabot, Caroline Senay, Dominique Robert, David Deslauriers

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2025
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicOcean Acidification Effects and Responses
Canadian institutionsFisheries and Oceans CanadaUniversité du Québec à Rimouski
Fundersnot available
KeywordsSebastesHypoxia (environmental)FisheryBiologyRockfishOcean acidificationEffects of global warming on oceansGlobal warmingEcologyFish <Actinopterygii>Climate changeOxygenChemistry

Abstract

fetched live from OpenAlex

Abstract Understanding the effects of global change, including temperature, pH, and oxygen availability, on commercially important species is crucial for anticipating consequences for these resources and their ecosystems. In the Gulf of St. Lawrence (GSL), redfish (Sebastes spp.) have been under moratorium from 1995 to 2024, with a massive recruitment observed in 2011–2013. However, little is known about their metabolic and thermal physiology, making predictions of their response to changing GSL conditions challenging. To address this, we quantified the effects of four acclimatation temperatures (2.5, 5.0, 7.5, and 10.0 ℃) and two pH levels (7.35 and 7.75) on standard and maximum metabolic rates (SMR and MMR), aerobic scope (AS), hypoxia tolerance (O 2 crit), food consumption, and growth in redfish. SMR, MMR, and AS increased with temperature, but growth decreased at the highest temperature, likely due to increased metabolic demand, with food consumption similar across 5.0 to 10.0 °C treatments. O 2 crit was lower for fish acclimated to 2.5 and 5.0 ℃, making redfish less hypoxia-tolerant at higher temperatures. Except from SMR, no significant effect of pH was observed. These results suggest that future changes in the GSL will challenge redfish, with potential long-term effects on their growth due to increased energy requirements.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.302
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.013
GPT teacher head0.210
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 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

Citations2
Published2025
Admission routes1
Has abstractyes

Explore more

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