Chemical profiles of Leach's storm-petrel (Oceanodroma leucorhoa) feathers collected on Bon Portage Island, Nova Scotia, Canada
Bibliographic record
Abstract
Avian chemical communication, once largely overlooked, is a growing field that has revealed the important role that olfaction plays in the social lives of some birds. Leach’s storm-petrels (Oceanodroma leucorhoa) have a remarkable sense of smell and a strong, musky scent. This long-lived, monogamous seabird relies on olfaction for nest relocation and foraging, but whether they use scent for communication is less well studied. They are nocturnally active at the breeding colony and yet successfully reunite with their mate despite poor night-vision, indicating an important role for non-visual communication. We investigated the chemical profiles of Leach’s storm-petrels to determine whether there is socially relevant information encoded in their plumage odor. To capture the compounds comprising their strong scent, we developed a method to study the compounds present in the air surrounding their feathers using headspace stir bar sorptive extraction coupled with gas-chromatography mass-spectrometry. We collected feathers from Leach’s storm-petrels breeding on Bon Portage Island in Nova Scotia, Canada in both 2015 and 2016. Our method detected 142 commonly occurring compounds. We found interannual differences in chemical profiles between the two sampling years. Males and females had similar chemical profiles, while individuals had distinct chemical signatures across the two years. These findings suggest that the scent of the Leach’s storm-petrel provides sociochemical information that could facilitate olfactory recognition of individuals and may inform mate choice decisions.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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".