Data from: Dispersal influences genetic and acoustic spatial structure for both males and females in a tropical songbird
Bibliographic record
Abstract
1. Animals exhibit diverse dispersal strategies, including sex-biased dispersal, a phenomenon common in vertebrates. Dispersal influences the genetic structure of populations as well as geographic variation in phenotypic traits. Patterns of spatial genetic structure and geographic variation may vary between the sexes whenever males and females exhibit different dispersal behaviours. 2. Here, we examine dispersal, spatial genetic structure, and spatial acoustic structure in Rufous-and-white Wrens, a year-round resident tropical bird. Both sexes sing in this species, allowing us to compare acoustic variation between males and females, and examine the relationship between dispersal and song sharing for both sexes. 3. Using a long-term dataset collected over an 11-year period, we used banding data and molecular genetic analyses to quantify natal and breeding dispersal distance in Rufous-and-white Wrens. We quantified song-sharing and examined whether sharing varied with dispersal distance, for both males and females. 4. Observational data and molecular genetic analyses indicate that dispersal is female-biased. Females dispersed farther from natal territories than males, and more often between breeding territories than males. Furthermore, females showed no significant spatial genetic structure, consistent with expectations, whereas males showed significant spatial genetic structure. Overall, natal dispersal appears to have more influence than breeding dispersal on spatial genetic structure and spatial acoustic structure, given that the majority of breeding dispersal events resulted in individuals moving only short distances. 5. Song sharing between pairs of same-sex animals decreases with the distance between their territories for both males and females, although males exhibited significantly greater song-sharing than females. 6. Lastly, we measured the relationship between natal dispersal distance and song sharing. We found that sons shared fewer songs with their fathers the farther they dispersed from their natal territories, but that song sharing between daughters and mothers was not significantly correlated with natal dispersal distance. 7. Our results reveal cultural differences between the sexes, suggesting a relationship between culture and sex-biased dispersal
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.005 | 0.001 |
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".