Differential Response to Interspecific and Intraspecific Signals Amongst Chickadees
Bibliographic record
Abstract
Abstract Black‐capped chickadees (Poecile atricapillus) and mountain chickadees (P. gambeli) have a similar vocal repertoire and share many other life history traits; yet, black‐capped chickadees are socially dominant to mountain chickadees where populations overlap. Previous research suggested that in contact zones, both species respond weakly to heterospecific songs during the breeding season, and have suggested minimal interspecific competition. However, both black‐capped and mountain chickadees discriminate between conspecific and heterospecific chick‐a‐dee calls, suggesting attention is paid to interspecific signals. We compared the responses of both black‐capped and mountain chickadees to conspecific and heterospecific chick‐a‐dee calls during the winter, when both species compete for the same food resources. We conducted an aviary playback experiment exposing both species to playback composed of heterospecific and conspecific chick‐a‐dee calls, which had been recorded in the context of finding food sources. Responses from the tested birds were measured by recording vocalizations and behaviour. Black‐capped chickadees responded significantly more to conspecific than to heterospecific stimuli, whereas the subordinate mountain chickadees responded to both mountain and black‐capped chickadee calls. Based upon the reactions to playbacks, our results suggest these two closely related species may differ in their perception of the relative threat associated with intra‐ versus interspecific competitors.
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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 | 0.000 | 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) | 0.002 | 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".