Inadvertent social information in breeding site selection of natal dispersing birds
Bibliographic record
Abstract
Several species use the number of young produced as public information (PI) to assess breeding site quality. PI is inaccessible for synchronously breeding birds because nests are empty by the time the young can collect this information. We investigate if location cues are the next best source of inadvertent social information (ISI) used by young prospectors during breeding site choice. We experimentally deployed ISI as decoys and song playbacks of breeding males in suitable and sub-optimal habitats during pre- and post-breeding periods, and monitored territory establishment during the subsequent breeding season for a social, bobolink (Dolichonyx oryzivorus), and a more solitary species, Nelson's sharp-tailed sparrow (Ammodramus nelsoni). The sparrows did not respond to treatments, but bobolinks responded strongly to post-breeding location cues, irrespective of habitat quality. The following year, 17/20 sub-optimal plots to which bobolink males were recruited were defended for at least two weeks, indicating that song heard the previous year could exert a "carry-over attraction" effect on conspecifics the following year. Sixteen recruited males were natal dispersers, as expected when animals have little opportunity to directly sample their natal habitat quality. We suggest that differences in breeding synchronicity may induce an equivalent clinal distribution of ISI use.
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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 | 0.000 |
| 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".