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Record W2481282270 · doi:10.1139/cjfas-2016-0105

Feeding patterns of two sympatric shark predators in coastal ecosystems of an oceanic island

2016· article· en· W2481282270 on OpenAlexvenueno aff
Clément Trystram, Karyne M. Rogers, Marc Soria, Sébastien Jaquemet

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicIchthyology and Marine Biology
Canadian institutionsnot available
FundersWestern Indian Ocean Marine Science AssociationStyrelsen för Internationellt Utvecklingssamarbete
KeywordsCarcharhinusApex predatorPredationTigerTrophic levelBiologyEcologyFisheryPopulationHabitatSympatric speciationMesopredator release hypothesis

Abstract

fetched live from OpenAlex

Stomach contents and stable carbon and nitrogen isotope analyses (δ 13 C and δ 15 N) were used to investigate the trophic ecology of two apex predators, tiger sharks (Galeocerdo cuvier) and bull sharks (Carcharhinus leucas), from Reunion Island to describe their dietary habits at both the population and individual levels. In this oceanic island, the tiger and bull sharks were more piscivorous and teutophagous than noted in previous research from other localities. The δ 13 C values suggested that bull sharks depended on more neritic organic matter sources than tiger sharks, confirming a coastal habitat preference for bull sharks. Moreover, the total length of the bull shark influenced δ 13 C values, with smaller individuals being more coastal than larger individuals. All indicators suggest that there is a higher degree of similarity between individual tiger sharks compared with the more heterogeneous bull shark population, which is composed of individuals who specialize on different prey. These results suggest that the two species have different functions in these coastal habitats, and thus, they must be considered independently in terms of conservation and management.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.324
Threshold uncertainty score0.985

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.210
Teacher spread0.199 · 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

Citations41
Published2016
Admission routes1
Has abstractyes

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