Reproductive Consequences of Aggression in a Territorial Songbird
Bibliographic record
Abstract
Abstract Territorial aggression can influence males’ ability to obtain high‐quality resources and access to mates; however, in many species, the reproductive consequences of variation in aggression are unknown. In this study, we investigated how individual variation in aggressive behavior relates to reproductive success in socially monogamous, genetically polygynous song sparrows (Melospiza melodia). Prior research in this species shows that male song sparrows differ in their willingness to engage in agonistic interactions with territorial intruders and that individual variation in aggression appears to have functional significance. Aggressive males have been shown to obtain territories where females produce larger clutch sizes, suggesting that individuals who display high levels of territorial aggression are defending high‐quality territories or females. Further, aggressive males are considered a greater threat to territory‐holding males than less aggressive males. In this study, we ask whether individual differences in aggression are linked to differences in extra‐pair reproductive success, annual reproductive success, and offspring quality. We did not uncover a relationship between aggression and annual reproductive success or patterns of extra‐pair paternity. However, we found that the nestlings of aggressive males grew at a faster rate than the nestlings of less aggressive males. Future studies should attempt to identify mechanisms to explain the relationship between offspring growth rate and male aggression and investigate whether faster offspring growth rates translate to greater survival and recruitment of offspring.
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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) | 0.000 | 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 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".