Social information trumps vegetation structure in breeding-site selection by a migrant songbird
Bibliographic record
Abstract
To maximize fitness, organisms must assess and select suitable habitat. Early research studying birds suggested that organisms consider primarily vegetation structural cues in their habitat choices. We show that experimental exposure to singing in the post-breeding period provides a social cue that is used for habitat selection the following year by a migrant songbird, the black-throated blue warbler (Dendroica caerulescens). Our experimental social cues coerced individuals to adopt territories in areas of very poor habitat quality where individuals typically do not occur. This indicates that social information can override typical associations with vegetation structure. We demonstrate that a strong settlement response was elicited because post-breeding song at a site is highly correlated with reproductive success. These results constitute a previously undocumented, but highly parsimonious mechanism for the inadvertent transfer of reproductive (public) information from successful breeders to dispersers. We hypothesize that post-breeding song is a pervasive and reliable cue for species that communicate vocally, inhabit temporally autocorrelated environments, produce young asynchronously and/or abandon territories after reproductive failure.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".