Density dependence of clutch size and offspring sex ratio in starling colonies
Bibliographic record
Abstract
Optimal life‐history theory predicts that individuals should adjust both the number and the sex of their offspring to maximize fitness in response to environmental and social factors such as breeding density. While reductions in optimal clutch size are well‐studied in birds, the evidence for sex ratio adjustments is still equivocal and, so far, we lack a thorough understanding of how these strategies interact to maximize fitness. Here, we investigate how breeding density simultaneously affects brood sex ratio and clutch size in a sexually dimorphic and polygynous bird. We tested the prediction that mothers breeding at a higher density lay smaller clutches and overproduce daughters, the sex with less variable fitness returns and that disperses further away from their natal territory. We distributed nest boxes at either a high (HD) or a low density (LD) and monitored clutch sizes and sex ratios during five years in a wild breeding colony of spotless starlings. While mothers breeding in HD nests produced more daughters than those breeding in LD nests, the density dependence of clutch size varied among years, with a tendency to lay smaller clutches in HD nests. Our results suggest that mothers consistently adjust offspring sex ratio in response to breeding density, whereas adjustments in clutch size varied in a more complex way. These results support the role of sex allocation strategies in response to density and show that further theoretical and empirical research is required to understand the interaction between clutch size and sex ratio adjustments in animals.
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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 | 0.001 |
| 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".