Spatial variation in the echolocation calls of the little brown bat (<i>Myotis</i> <i>lucifugus</i>)
Bibliographic record
Abstract
We studied spatial variation in echolocation call structure of the little brown bat (Myotis lucifugus (LeConte, 1831)) by analysing calls recorded from free-flying individuals at 1 site in Haida Gwaii, British Columbia, 1 site in Chautaqua, New York, and 20 sites along the Hudson River, New York. We controlled for factors that are often thought to lead to interspecific variation in echolocation calls (habitat, ontogeny, presence of conspecifics, recording techniques, ambient conditions), which allowed us to focus on the effect of spatial scale on call structure. As predicted, we found that at small scales (up to 1 km), there was significant geographic variation, likely owing to roost-specific signatures and group foraging activities. At intermediate scales (2–500 km), we found no differences in call structure, suggesting that populations within this area are part of a single hibernating and breeding population. Finally, echolocation call structure differed at the continental scale (>1000 km) likely because of little genetic exchange among sampled populations. Our results highlight the importance of considering the magnitude of spatial scale when examining variation in echolocation call structure.
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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 | 0.001 | 0.001 |
| 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".