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Record W1758276717 · doi:10.1139/f2011-115

Stable isotope profiles of large marine predators: viable indicators of trophic position, diet, and movement in sharks?

2011· article· en· W1758276717 on OpenAlexaffvenue
Nigel E. Hussey, Sheldon F. Dudley, Ian McCarthy, Geremy Cliff, Aaron T. Fisk

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicIsotope Analysis in Ecology
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsTrophic levelPredationBiologyForagingApex predatorHabitatEcologyChondrichthyesMarine ecosystemIsotope analysisPredatorEcosystem

Abstract

fetched live from OpenAlex

Understanding the role of predators is challenging but critical for ecosystem management. For community dynamics, predator-specific size-based variation in diet, trophic position, and habitat use are rarely accounted for. Using two applied tools (stable isotopes and stomach content data), we examined inter- and intra-species ontogenetic variability in diet (stomach contents), trophic position (TP SIA for δ 15 N and TP SCA for stomach contents), and habitat use (δ 13 C) of two large sharks, the scalloped hammerhead ( Sphyrna lewini ) and the dusky ( Carcharhinus obscurus ). Stomach contents identified size-based and gender-specific shifts in diet indicating resource partitioning for and between species. Calculated TP for the two sharks varied by method, either TP SIA or TP SCA and with species, size, and gender, but were complicated by differing baselines and broad functional prey groups, respectively. TP increased with size for S. lewini, but was low in large C. obscurus compared with small sharks. Size-based δ 13 C profiles indicated habitat partitioning by sex in S. lewini and a movement to shelf edge foraging in large C. obscurus. These results demonstrate that predators exert proportional size-based effects on multiple components of the marine system that are further complicated by species- and gender-specific strategies.

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 score0.033
Threshold uncertainty score0.999

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)0.0020.000

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 head0.009
GPT teacher head0.199
Teacher spread0.189 · 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

Citations121
Published2011
Admission routes2
Has abstractyes

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