Transcontinental latitudinal variation in song performance and complexity in house wrens (<i>Troglodytes aedon</i>)
Bibliographic record
Abstract
There is growing interest in latitudinal effects on animal behaviour and life history. One recent focus is on birdsong, which is hypothesized to be more elaborated or complex in the north temperate zone compared with the tropics. Current evidence is mixed and based on cross-species comparisons, or single species with restricted distributions. We circumvent these limitations using a transcontinental sample of 358 songs from house wrens (Troglodytes aedon) at 281 locations spanning more than 100° of latitude (52° N-55° S) across the Americas. We found a significant latitudinal gradient in several basic elements of song performance and complexity between north temperate and tropical populations. Furthermore, we document convergence in song patterns between populations at higher latitudes in the Northern and Southern Hemispheres. Effects were strongest for the number of elements in a song, and the rate of element production, both increasing towards the poles, with similar but weaker effects for other song dimensions (e.g. number of unique elements, trills and trill rate). We consider possible causes related to variable habitats and morphology, concluding that the shorter breeding seasons at higher latitudes in both hemispheres may favour greater song elaboration to mediate territory competition and mate choice.
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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 | 0.001 | 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".