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Record W4404884281 · doi:10.1038/s41598-024-81258-5

The timing of marine heatwaves during the moulting cycle affects performance of decapod larvae

2024· article· en· W4404884281 on OpenAlexaff
María José Bruning, David Véliz, Noemí Rojas‐Hernández, José Garcés‐Vargas, Ignacio Garrido, María José Cid, Kurt Paschke, Luis Miguel Pardo

Bibliographic record

VenueScientific Reports · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicCrustacean biology and ecology
Canadian institutionsUniversité Laval
FundersFondo de Financiamiento de Centros de Investigación en Áreas PrioritariasFondo Nacional de Desarrollo Científico y TecnológicoAgencia Nacional de Investigación y Desarrollo
KeywordsMoultingLarvaBiologyPopulationEcologyZoologyDemography

Abstract

fetched live from OpenAlex

Marine heatwaves (MHW) pose an increasing threat and have a critical impact on meroplanktonic organisms, because their larvae are highly sensitive to environmental stress and key for species' dispersion and population connectivity. This study assesses the effects of MHW on two key moulting cycle periods within first zoea of the valuable crab, Metacarcinus edwardsii. First, the changes in swimming behaviour during zoea I were recorded and associated to moult cycle substages. Then, larvae were exposed during the zoea I to (1) control temperature of 12 °C, (2) Early MHW, occurring in intermoult, (3) Late MHW, occurring in premoult and (4) 14 °C, representing MHW during whole development. Additionally, optimum temperature was estimated from thermal performance curves through swimming behaviour of one-day zoea I. The timing of the MHW within the moulting cycle significantly affects larval fitness. Early MHW led to improved survival rates (72%) and reduced developmental times (9.8 days) compared to those exposed to Later MHW (63% and 10.3 days, respectively). As optimum temperature was higher than 12 °C, MHW events maybe favouring larval performance. These results highlight the importance of interaction between the moult cycle and environmental variables as a factor of sublethal effects on population dynamics.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

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 head0.007
GPT teacher head0.219
Teacher spread0.212 · 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

Citations3
Published2024
Admission routes1
Has abstractyes

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