Population size, catchment area, and sex-influenced differences in autumn and spring swarming of the brown long-eared bat (Plecotus auritus)
Bibliographic record
Abstract
Swarming by bats is defined as intense autumnal flight activity in and near underground hibernation sites and is considered to be associated with mating, but this behaviour may also serve to allow bats to assess potential hibernacula. To test if swarms consist of resident bat populations from the surrounding area or transitional bat populations migrating between summer and winter areas, I measured activity patterns and the distribution of day roosts of swarming brown long-eared bats ( Plecotus auritus (L., 1758)) at two abandoned mines in southwestern Poland. Swarming occurred from mid-August to mid-October, and also in March and April. The maximum population of swarming bats was estimated to be about 500 individuals. The sex ratio was male-biased and was more skewed in spring than in autumn. Bats frequently travelled to the swarming site from day roosts as far away as 31.5 km. They usually stayed for several hours before returning to a day roost without visiting other hibernacula. Males roosted closer to the swarming site and visited it more frequently than females, consistent with increased mating attempts. My results suggest that swarming sites are hot spots for populations resident in the surrounding area. They likely play an important role in gene flow and facilitate mating among bats from spatially isolated populations.
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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 | 0.000 |
| 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".