Integrated Fatty Acid and Stable Isotope Niches Reveal Trophic Connections Among Sympatric Large‐Bodied Sharks
Bibliographic record
Abstract
ABSTRACT This study used a novel approach combining stable isotope data and condensed multivariate fatty acid data to define comparative niche space and overlap of six sympatric sharks from the south‐west Indian Ocean: Galeocerdo cuvier, Sphyrna zygaena, Sphyrna lewini, Carcharias taurus, Carcharodon carcharias and Carcharhinus obscurus. G. cuvier had the smallest fatty acid niche space but exhibited the largest range in δ13C, suggestive of foraging across multiple environments (habitat generalist) but on nutritionally similar prey in a narrow trophic band (nutritional specialist). The remaining five species had comparatively higher δ15N, pelagic‐based fatty acids and larger fatty acid niche spaces, suggesting they are nutritional generalists with a preference for higher trophic level prey. Niche space was not associated with conservation status despite declining populations for half of the species studied. This suggests that resource availability is not a limiting factor for these species and that their mobile nature provides them access to diverse habitats and resources, while exposing them to a broad range of anthropogenic threats, muting the relationship between conservation status and resource use. The combined approach allowed for a comprehensive representation of niche space, distinguishing species based on trophic level, basal carbon sources and pelagic and coastal prey consumption. The presented integrated approach provides greater detail and resolution of elasmobranch trophic ecology that could not be achieved with either fatty acid or stable isotope analysis alone.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".