Dual foraging and pair-coordination during chick provisioning by Manx shearwaters: empirical evidence supported by a simple model
Bibliographic record
Abstract
The optimal allocation of time and energy between one's own survival and offspring survival is critical for iteroparous animals, but creates a conflict between what maximises the parent's fitness and what maximises fitness of the offspring. For central-place foragers, provisioning strategies may reflect this allocation, while the distance between central-places and foraging areas may influence the decision. Nevertheless, few studies have explored the link between life history and foraging in the context of resource allocation. Studying foraging behaviour alongside food load rates to chicks provides a useful system for understanding the foraging decisions made during parent-offspring conflict. Using simultaneously deployed GPS and time-depth recorders, we examined the provisioning strategies in free-living Manx shearwaters Puffinus puffinus, which were caring for young. Our results showed a bimodal pattern, where birds alternate short and long trips. Short trips were associated with higher feeding frequency and larger meals than long trips, suggesting that long trips were performed for self-feeding. Furthermore, most foraging was carried out within 100 km of sea fronts. A simple model based on patch quality and travel time shows that for Manx shearwaters combining chick feeding and self-maintenance, bimodal foraging trip durations optimise feeding rates.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".