Foraging interactions between wading birds and strand-feeding bottlenose dolphins (<i>Tursiops truncatus</i>) in a coastal salt marsh
Bibliographic record
Abstract
Strand-feeding is a unique foraging technique used by Atlantic bottlenose dolphins ( Tursiops truncatus (Montagu, 1821)) in salt marshes of the southeastern USA wherein a group of dolphins rushes a creek bank, temporarily stranding themselves to capture fish that have been pushed ashore by their bow wave. Wading birds are attracted to these events to forage on stranded fish. We hypothesized that birds foraging in association with dolphins experience greater foraging efficiency than birds foraging away from dolphins and that some birds are able to meet their entire daily metabolic needs by foraging at strand-feeding events. The species composition, abundance, and foraging success of birds at 569 strand-feeding events were compared with the same parameters from marsh surveys of birds not associated with dolphins. Only Great Egrets ( Ardea alba L., 1758) were proportionately more common at strand-feeding events than in the marsh overall (p < 0.001). During peak strand-feeding hours, energy intake per hour was higher for Great Egrets foraging with strand-feeding dolphins than for birds foraging away from dolphins (p = 0.04). Bioenergetic models indicated that prey intake by Great Egrets at strand-feeding events was sufficient to meet their existence and likely their active metabolic requirements.
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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 | 0.000 | 0.000 |
| 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".