Variation in quantitative properties of song among European populations of reed bunting (<i>Emberiza schoeniclus</i>) with respect to bill morphology
Bibliographic record
Abstract
We analysed the geographical variation in quantitative song properties among reed bunting (Emberiza schoeniclus ssp.) populations belonging to two subspecies groups with different bill morphologies: large and curved bill (namely E. s. intermedia and E. s. witherbyi, in southern Europe) and thin and conical bill (E. s. schoeniclus, in northern Europe). We collected song recordings from 11 European populations of the two subspecies groups and measured song properties of 116 males. We found significant differences among populations despite a high degree of individual variation. Populations with similar morphology were more homogeneous in song characters, despite geographical distances between them. The two subspecies groups differed mainly in the number of different syllable types used in a song, with the songs of the southern group having higher syllabic complexity. Cluster analysis and matrix correlation tests showed an association between song variation and morphological variation. The populations morphologically belonging to E. s. schoeniclus along the contact zone of the breeding distributions had song characters similar to southern populations and possibly represent a "hybrid" zone, which is not evidenced by morphological or recent genetic analyses. This may be due to song being learned socially, populations mixing in winter and, along the contact zone, populations of different subspecies groups often breeding a few kilometres apart. The generally high degree of variation in song among populations can be a consequence of the relative isolation of the breeding populations, which are restricted to uncommon and fragmented habitats, along with the rapid cultural evolution of song in this species.
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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 | 0.001 |
| 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) | 0.001 | 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".