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Record W2226889133 · doi:10.1007/s00300-015-1877-7

Size and stage composition of age class 0 Antarctic krill (Euphausia superba) in the ice–water interface layer during winter/early spring

2016· article· en· W2226889133 on OpenAlexaff
Fokje L. Schaafsma, Carmen David, E. A. Pakhomov, Brian P. V. Hunt, Benjamin Lange, Hauke Flores, J.A. van Franeker

Bibliographic record

VenuePolar Biology · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsUniversity of British Columbia
FundersNederlandse Organisatie voor Wetenschappelijk OnderzoekMinisterie van Economische Zaken
KeywordsEuphausiaKrillAntarctic krillBiologyPelagic zoneSea iceOceanographyPopulationCrustaceanWater columnEuphausiaceaArctic ice packFisheryEcologyGeology

Abstract

fetched live from OpenAlex

The condition and survival of Antarctic krill ( Euphausia superba ) strongly depends on sea ice conditions during winter. How krill utilize sea ice depends on several factors such as region and developmental stage. A comprehensive understanding of sea ice habitat use by krill, however, remains largely unknown. The aim of this study was to improve the understanding of the krill’s interaction with the sea ice habitat during winter/early spring by conducting large-scale sampling of the ice–water interface (0–2 m) and comparing the size and developmental stage composition of krill with the pelagic population (0–500 m). Results show that the population in the northern Weddell Sea consisted mainly of krill that were <1 year old (age class 0; AC0), and that it was comprised of multiple cohorts. Size per developmental stage differed spatially, indicating that the krill likely were advected from various origins. The size distribution of krill differed between the two depth strata sampled. Larval stages with a relatively small size (mean 7–8 mm) dominated the upper two metre layer of the water column, while larger larvae and AC0 juveniles (mean 14–15 mm) were proportionally more abundant in the 0- to 500-m stratum. Our results show that, as krill mature, their vertical distribution and utilization of the sea ice appear to change gradually. This could be the result of changes in physiology and/or behaviour, as, e.g., the krill’s energy demand and swimming capacity increase with size and age. The degree of sea ice association will have an effect on large-scale spatial distribution patterns of AC0 krill and on predictions of the consequences of sea ice decline on their survival over winter.

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 score0.105
Threshold uncertainty score0.562

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 studies0.0000.000
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 head0.010
GPT teacher head0.222
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 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

Citations21
Published2016
Admission routes1
Has abstractyes

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