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Record W2997923920 · doi:10.1111/fog.12463

Long‐term trends and drivers of larval phenology and abundance of dominant brachyuran crabs in the Gulf of St. Lawrence (Canada)

2019· article· en· W2997923920 on OpenAlexafffundabout
Kim Émond, Bernard Sainte‐Marie, Joël Bêty

Bibliographic record

VenueFisheries Oceanography · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicCrustacean biology and ecology
Canadian institutionsCenter for Northern StudiesUniversité du Québec à RimouskiFisheries and Oceans Canada
FundersFisheries and Oceans CanadaFonds Québécois de la Recherche sur la Nature et les Technologies
KeywordsPhenologyAbundance (ecology)BiologyClimate changePlanktonEcologyPopulationHatchingLarvaGlobal warmingEffects of global warming on oceans

Abstract

fetched live from OpenAlex

Abstract Climate change has led to major shifts in the timing of biological events, with many studies demonstrating earlier phenology in response to warming. However, few of these studies have investigated the effects of climate change on the phenology of larvae in marine species. Phenological shifts can result in mismatches between consumers and prey and hence affect growth and survival of individuals, and ultimately population demography. We investigated the temporal changes in phenology and abundance of the larvae of dominant brachyuran crabs in the southern Gulf of St. Lawrence (eastern Canada) based on plankton collections spanning 1982–2012. The Gulf of St. Lawrence has warmed since the early 1990s, and our analyses revealed that larvae of snow crab ( Chionoecetes opilio ) and toad crabs ( Hyas spp.) exhibited a significant trend towards earlier phenology over the 30‐year study period. This shift in phenology appeared to be a consequence of the effect of climate warming on both the timing of hatching and larval development rate. Larval abundance responded differently by crab taxon to climate warming, likely due to differences in thermal tolerance. The warming trend was unfavourable to snow crab, which is the most cold‐adapted and stenothermic of the taxa examined in this study. The abundance of snow crab larvae was lower when sea ice retreat occurred earlier than day 110 of the year and sea surface temperature was higher than 8.5°C. On the other hand, larval abundance of rock crab ( Cancer irroratus ), which prefers higher temperatures, was positively related to surface temperature.

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)0.000
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 score0.128
Threshold uncertainty score0.885

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.006
GPT teacher head0.190
Teacher spread0.184 · 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

Citations9
Published2019
Admission routes3
Has abstractyes

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