Geographic and temporal variation in the trophic ecology of a small-bodied shark: evidence of resilience to environmental change
Bibliographic record
Abstract
Shark dietary patterns can determine how they will respond to changes in prey availability and biodiversity. Geographic variation in diet can also indicate if species have unique structuring roles or feeding strategies in different environments. Unfortunately, little is known about the diet of most shark species and how diet varies over time and space. This study used stable isotope analysis to assess the diet of the Australian sharpnose shark (Rhizoprionodon taylori). Plasma and muscle δ13C and δ15N of R. taylori were compared with δ13C and δ15N baselines from multiple embayments to determine the isotopic niche, trophic position, and benthic and pelagic contributions to diet over time and space. Overall, R. taylori had a wide trophic position range and consumed prey from benthic and pelagic sources. However, there was geographic and temporal variation in trophic position and benthic and pelagic contributions. These findings indicate R. taylori is a dietary generalist, but different populations may have unique effects on distinct ecosystems. Geographic variation in diet also suggests R. taylori may be adaptive to changes in prey availability.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".