Begging form and growth pattern of nestlings correlate with parental food-allocation patterns in the Horned Lark (<i>Eremophila</i><i> alpestris</i>)
Bibliographic record
Abstract
Life-history theory assumes that selection favors parents that can maximize their reproductive success via behavioral strategies. As brood size determines the reproductive value of each nestling, parents may adjust their food-allocation patterns according to brood size. We test this assumption in the Horned Lark (Eremophila alpestris (L., 1758)). Our findings revealed that nestling begging forms varied with brood size, by gaping in one-chick broods and postural activity in two- and three-chick broods. Accordingly, parental food-allocation patterns differed in different-sized broods. In one-chick broods, parents increased feeding rates with the gaping duration of nestling. In two-chick broods, parents did not change food-allocation patterns according to nestlings’ begging. In three-chick broods, however, they fed later-hatched nestlings more even when early-hatched nestlings begged more intensely. Horned Larks exhibited obvious sexual differences in parenting style and ability, which resulted in nestlings from two- and three-chick broods changing their begging intensity according to the sex of the provisioning adult. Furthermore, nestling growth pattern diverged with brood sizes, with body mass growing faster in one-chick broods than in two- and three-chick broods. Growth rate of beak gape and tarsus length did not differ significantly among brood sizes, but beak gape was larger and tarsus length was shorter in one-chick broods than in larger broods at fledging. Our results thus support the idea that parents may use food allocation to regulate sibling rivalry, which in turn cause nestlings to beg food in different forms and grow in different patterns so that their reproductive success can be enhanced.
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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 | 0.000 |
| 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".