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Record W3185135218 · doi:10.1093/plankt/fbab047

Krill diel vertical migration in Southern Patagonia

2021· article· en· W3185135218 on OpenAlexaff
Ariadna C. Nocera, Eloísa Giménez, Mariano J. Diez, María Valeria Retana, Gesche Winkler

Bibliographic record

VenueJournal of Plankton Research · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsUniversité du Québec à Rimouski
FundersConsejo Nacional de Investigaciones Científicas y Técnicas
KeywordsKrillDiel vertical migrationEcho soundingOceanographyEuphausiaEuphausiaceaBiomass (ecology)Environmental sciencePlanktonBiologyGeology

Abstract

fetched live from OpenAlex

Abstract Diel vertical migration (DVM) of krill was studied throughout 36 h at a fixed station (46.05°S, 66.19°W; 98-m depth) located in the center of the San Jorge Gulf, Southern Patagonia area, during February 2014. Using an echosounder system, combined with an autonomous Video Plankton Recorder (Auto-VPR) and Jacknet samplings, we describe the migration pattern, the associated biomass and the macrozooplankton species involved. The net sampling and the Auto-VPR images allowed us to identify the krill species detected in the echosounder signals, which corresponded to Euphausia lucens, Euphausia vallentini and Nematoscelis megalops. The krill community followed a “normal pattern” of DVM, ascending at dusk (~18:30 h) and descending at dawn (~06:30 h), forming a dense layer near the bottom during the day. Krill vertical migration speed was estimated from the echogram data at ~ 1 cm s−1 (1 body length per s for 1-cm-long animal), and the integrated mean biomass was 57.8 g m−2. This study provides a description of temporal and spatial patterns of krill vertical distribution, which should be taken into account when studying the complexity of the SJG ecosystem dynamics and carbon flux.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.531
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0110.000

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 head0.046
GPT teacher head0.330
Teacher spread0.284 · 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

Citations14
Published2021
Admission routes1
Has abstractyes

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