Local and range-wide distribution of song types suggest Ovenbirds (Seiurus aurocapilla) have song neighborhoods but not macro-dialects
Bibliographic record
Abstract
The song systems of oscine passerines (songbirds) are complex and diverse. Because songs are used for both mate attraction and territory defense and are therefore important signals for survival and reproduction, comprehensive knowledge of within and among species song structure and distribution is informative for understanding the evolution of song repertoires and vocal behaviour. In this study, we explored variation in the song structure of the Ovenbird ( Seiurus aurocapilla ), a widespread warbler (Family Parulidae) found in North American forests. We analyzed recordings from the 2021 breeding season to assess song type variation at a local ( n = 158 birds; Sault Ste. Marie, ON) and breeding range scale ( n = 512 birds; eBird). We characterized the local song types and tested whether Ovenbirds share song types with their neighbors more often than expected by chance. We then characterized song types of Ovenbirds across the breeding range to determine whether any geographic pattern of song clustering exists (i.e., macro-dialects). We found 10 distinct song types and some evidence for song type clustering at the local study site (i.e., song neighborhoods). We found 7 of those 10 song types throughout the breeding range and identified an additional 24 types that were not recorded in our local population. We found no evidence for song dialects across the Ovenbird breeding range. This study contributes to our understanding of Ovenbird song while simultaneously adding to our understanding of geographic structuring of warbler repertoires. Our work contributes to delineating a more comprehensive understanding of factors affecting dialect development for this diverse group of songbirds.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 teacher head, 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".