Offspring provisioning is affected by begging and hatch order but not relatedness in a communally breeding bird
Bibliographic record
Abstract
In cooperative breeders, individuals provide alloparental care to nonfilial young. Caregivers differ in their degree of relatedness to young, so kin selection theory predicts that individuals should increase their fitness by preferentially caring for their offspring or close relatives. Caregivers may also attend to cues like size, begging latency and begging intensity, providing more care to young in better condition or greater need. We investigated offspring provisioning in communal breeding smooth-billed anis, Crotophaga ani , a bird species where multiple nonkin co-breeders form a single group and females contribute eggs to a communal clutch reared by all group members. Hypothesizing that these birds exhibit kin recognition and adjust provisioning effort in relation to their genetic contribution to communal nests, we predicted that smooth-billed anis would preferentially feed their offspring and/or increase feeding effort as their genetic contribution to communal broods increased. Hypothesizing that nestling signals and cues affect provisioning, we predicted that adults would be more likely to feed nestlings that begged earlier, begged harder and hatched first (i.e. larger nestlings). Using video from 13 breeding groups, we found no evidence that smooth-billed anis preferentially feed their offspring or increase feeding effort when they have more offspring in communal broods. Individuals were more likely to feed their offspring in communal broods containing a higher proportion of their offspring, suggesting that more productive individuals indirectly benefit their offspring via chance. Caregivers were more likely to feed nestlings that begged earlier and harder and that hatched first. We conclude that smooth-billed anis do not preferentially feed their offspring but do attend to signals and cues of nestling condition and need. Future work should evaluate the effects of nestling competitive ability and behaviour on provisioning.
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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 | 0.000 | 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) | 0.000 | 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".