Chickadees sing different songs in sympatry versus allopatry
Bibliographic record
Abstract
Character displacement theory predicts that closely-related co-occurring species should diverge in relevant traits to reduce costly interspecific interactions such as competition or hybridization. While many studies document character shifts in sympatry, few provide corresponding evidence that these shifts are driven by the costs of co-occurrence. Black-capped (Poecile atricapillus) and mountain chickadees (Poecile gambeli) are closely-related, ecologically similar, and broadly distributed songbirds with both allopatric and sympatric populations. In sympatry, both species appear to suffer costs of their co-occurrence: (a) both species are in worse body condition compared to allopatry and (b) hybridization sometimes yields sterile offspring. Here, we explored character displacement in the songs of black-capped and mountain chickadees by characterizing variation in male songs from sympatric and allopatric populations. We found that mountain chickadees sing differently in sympatry versus allopatry. Specifically, they produced more notes per song, were more likely to include an extra introductory note, and produced a smaller glissando in their first notes compared to all other populations. Combined with previous research on social dominance and maladaptive hybridization between black-capped and mountain chickadees, we posit that differences in sympatric mountain chickadee song are population-wide shifts to reduce aggression from dominant black-capped chickadees and/or prevent maladaptive hybridization.
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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".