Foraging Trade‐offs between Prey Size, Delivery Rate and Prey Type: How Does Niche Breadth and Early Learning of the Foraging Niche Affect Food Delivery?
Bibliographic record
Abstract
Abstract Optimal foraging theory suggests that avian parents should prefer the most energetically efficient (largest) prey items when delivering food to offspring at a central place. However, during periods of high demand, selectivity of prey may decline, leading to the delivery of smaller and/or less nutritious items. We compared foraging trade‐offs between great tits ( Parus major ) which had a wider feeding niche than blue tits ( Cyanistes caeruleus ). We also compared the foraging efficiency of cross‐fostered young, which had learned the spatial foraging niche and prey size of the foreign species, to that of control conspecifics. Mean delivery rates did not differ between control and cross‐fostered parents of either species but as delivery rates increased, prey size declined for both species and both treatment groups. However, across the range of increasing delivery rates, parents were able to increase the total biomass of prey delivered. Cross‐fostering did not alter the proportion of different prey taxa in the diet, but cross‐fostered birds shifted the size of the prey taken to that of their foster species. Consistent with their broader feeding niche, great tits, but not blue tits, incorporated more unpalatable items (flies) as delivery rates increased. Although great tits foraged less efficiently in the blue tit niche, paradoxically, blue tits seem to deliver more prey biomass when foraging in the great tit niche.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".