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Record W2079510409 · doi:10.1890/es13-00158.1

Water mass characteristics and solar illumination influence leatherback turtle dive patterns at high latitudes

2014· article· en· W2079510409 on OpenAlexafffundabout
Kayla M. Hamelin, Dan Kelley, Christopher T. Taggart, Michael C. James

Bibliographic record

VenueEcosphere · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicTurtle Biology and Conservation
Canadian institutionsFisheries and Oceans CanadaMcGill UniversityDalhousie University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Wildlife FederationUniversities Space Research AssociationNational Geographic SocietySea Turtle ConservancyWorld Wildlife Fund
KeywordsTurtle (robot)LatitudeHigh latitudeEnvironmental scienceAtmospheric sciencesOceanographyEcologyBiologyGeographyGeologyGeodesy

Abstract

fetched live from OpenAlex

Eastern Canada hosts one of the largest seasonal aggregations of leatherback turtles ( Dermochelys coriacea ) in the Atlantic Ocean, and is considered critical foraging habitat. Explaining distributional variation of leatherbacks in this three‐dimensional habitat is relevant to the recovery strategy for this endangered species as human activities are a leading cause of mortality. We identify high‐resolution spatial and temporal patterns in leatherback movements, and associated environmental variables shaping leatherback habitat use in Atlantic Canadian foraging waters. Data loggers were deployed on three female leatherbacks off Halifax, Nova Scotia, and were recovered during subsequent nesting in South and Central America. Time (0.5 Hz), depth (±1 m), water temperature (±0.1°C), and location data were recorded and analyzed for the period when the turtles were resident in their Canadian foraging domain. We demonstrate that leatherback dives are primarily restricted to the main thermocline, suggesting a food‐related water mass association. We also identified low‐ and high‐frequency periodicities in turtle depth‐at‐time, reflecting a diel pattern triggered by nautical twilight and dive periods of 8–10 minutes. We further demonstrate that dive frequency is a function of seasonal change in daylight. Our findings illustrate that solar illumination influences leatherback diving in north temperate waters, consistent with turtles using visual cues for foraging.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.999

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)0.0040.002

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 head0.004
GPT teacher head0.170
Teacher spread0.167 · 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; both teacher heads agree on what is shown here.

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

Citations12
Published2014
Admission routes3
Has abstractyes

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