Elements of male song performance and complexity are associated with reduced risk of paternity loss in a South American passerine
Bibliographic record
Abstract
Many passerines have elaborated songs hypothesized to have evolved through sexual selection. Extra-pair mating can be a contributing factor in the evolution of complex songs by increasing the variance in male fitness. We investigated this by quantifying the relationship between male song performance and complexity and levels of paternity loss through extra-pair mating by their female mates in the grass wren ( Cistothorus platensis ), a socially monogamous passerine with elaborate songs. We conducted fieldwork in the Uspallata Valley, Mendoza, Argentina over two breeding seasons and recorded the songs of 30 focal males during the egg-laying stage of their social mate. We collected blood samples from adults and nestlings and used ddRAD sequencing SNP data to determine parentage. We assessed the extra-pair mating behaviour of females by measuring paternity loss of their social partner and examined whether variation in paternity loss was associated with structural characteristics of that male’s songs. We found relationships between paternity loss and song duration, syllable diversity and duty cycle. Our findings indicate that some specific traits of male song are associated with lower levels of paternity loss and therefore potentially higher fitness. Future studies should determine whether this relationship is a result of female preference (intersexual selection), effective male mate guarding or territory defence (intrasexual selection) or both.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 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".