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Record W1706369616 · doi:10.1139/f2011-070

A new method to reconstruct fish diet and movement patterns from δ<sup>13</sup>C values in otolith amino acids

2011· article· en· W1706369616 on OpenAlexvenueno aff
Kelton W. McMahon, Marilyn L. Fogel, Beverly J. Johnson, L. Houghton, Simon R. Thorrold

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicIsotope Analysis in Ecology
Canadian institutionsnot available
FundersKing Abdullah University of Science and TechnologyWoods Hole Oceanographic InstitutionNational Science Foundation
KeywordsOtolithAragoniteIsotopes of carbonIsotope analysisHabitatPopulationδ13CReefCoral reefδ15NFisheryBiologyCoral reef fishFish <Actinopterygii>IsotopeStable isotope ratioOceanographyEcologyTotal organic carbonGeologyCalcitePaleontology

Abstract

fetched live from OpenAlex

Fish ecologists have used geochemical values in otoliths to examine habitat use, migration, and population connectivity for decades. However, it remains difficult to determine an unambiguous dietary δ 13 C signature from bulk analysis of otolith. Studies to date have focused on the aragonite component of otoliths with less attention paid to the organic fraction. We describe the application of compound-specific stable isotope analysis (SIA) to analyze amino acid (AA) δ 13 C values from small amounts (&lt;1 mg) of otolith powder. We examined δ 13 C values of otolith and muscle AAs from a reef-associated snapper (Lutjanus ehrenbergii (Peters, 1869)) collected along a carbon isotope gradient (isoscape) from seagrass beds to coral reefs. Carbon isotope values in otolith and muscle samples were highly correlated within and among coastal habitats. Moreover, δ 13 C values of otolith AAs provided a purely dietary record that avoided dilution from dissolved inorganic carbon. Otolith AAs served as a robust tracer of δ 13 C values at the base of the food web, making compound-specific SIA a powerful tool for dietary reconstructions and tracking the movement of fishes across isoscapes.

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)0.001
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 score0.163
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0030.000

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 head0.235
Teacher spread0.213 · 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

Citations74
Published2011
Admission routes1
Has abstractyes

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