Offspring sex ratio is affected by pre-breeding rainfall and hatching order in a cooperative breeding bird
Bibliographic record
Abstract
Selection may favour sex ratio adjustment when the fitness benefits of producing male or female offspring vary. In birds, sex ratio bias at hatching has been particularly well-studied in cooperative breeding species, primarily in helper-at-the-nest systems wherein young remain with their parents and help raise subsequent broods. In these systems, breeding females are expected to skew offspring sex ratio in favour of the helping sex if sufficient resources exist. In communal laying systems multiple group members breed and raise the young and offspring dispersal varies, making it difficult to predict whether and how breeders should skew offspring sex ratio. We tested for sex ratio bias in smooth-billed anis (Crotophaga ani), a communal laying cuckoo with low within-group relatedness, high offspring dispersal, and high annual turnover in group membership. One male performs nocturnal incubation and sires more offspring, suggesting these males may have higher reproductive variance and thus that it may be beneficial for his mate to produce more male offspring. We hypothesized that pre-breeding rainfall influences food availability and thus offspring sex ratio, predicting that breeding females skew production towards the more beneficial sex (i.e., males) in high food years, consistent with the Trivers-Willard hypothesis. Females may also adjust sex ratio across the hatching order, so we predicted a male-bias in first hatched chicks in larger broods that should experience greater competition. Contrary to our first prediction, more male chicks hatched when pre-breeding rainfall was lower. In partial support of our second prediction, marginally more first hatched chicks were male in larger broods. Based on these results, we propose the nestling competition hypothesis and predict that when nestling competition is high (i.e., in poor years and in large joint broods), mothers should produce more of the more competitive sex.
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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".