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Record W2022827642 · doi:10.1093/plankt/fbq144

Long-term seasonal and interannual variations of krill spawning in the lower St Lawrence estuary, Canada, 1979-2009

2010· article· en· W2022827642 on OpenAlexaffabout
Stéphane Plourde, Gesche Winkler, Pierre Benoît Joly, Jean‐François St‐Pierre

Bibliographic record

VenueJournal of Plankton Research · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsUniversité du Québec à RimouskiFisheries and Oceans Canada
Fundersnot available
KeywordsKrillEstuaryBiomass (ecology)Abundance (ecology)EuphausiaPhytoplanktonEnvironmental scienceOceanographyAntarctic krillBiologySeasonalityChlorophyll aFisheryEcologyNutrient

Abstract

fetched live from OpenAlex

This study describes the long-term seasonal and interannual variations in krill spawning using abundance of krill eggs collected during an on-going long-term monitoring program at an anchor station in the lower St Lawrence Estuary from 1992 to 2009 and data collected in the same region in 1979 to 1980. The long-term seasonal semi-monthly climatology in egg abundance revealed that krill generally reproduced during two periods, i.e. in late spring (mid-May to late June) and in late summer (August to mid-September), when phytoplankton biomass in the upper 50 m was greater than 75 mg chlorophyll a m−2. The identification of krill eggs to the species level in 2007 revealed that Meganyctiphanes norvegica egg abundance was related to the biomass of phytoplankton averaged over the month prior to sampling, corresponding to the duration of one spawning cycle (two intermolt periods) known for this species. Overall krill egg abundance varied significantly between years, showing high abundance every 3–5 years with no long-term interannual trend. The annual mean egg abundance normalized for the duration of krill spawning showed the same interannual long-term pattern. Both egg abundance indices were independent of the annual phytoplankton biomass, indicating that interannual variations in krill spawning biomass would be the most likely candidate to explain interannual variability in egg abundance. We propose that such normalized annual egg abundance based on high-resolution seasonal sampling could be a useful index of interannual variations in krill spawning biomass which is otherwise difficult to sample.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.423
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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 science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.022
GPT teacher head0.304
Teacher spread0.282 · 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

Citations19
Published2010
Admission routes2
Has abstractyes

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