Relatedness within and among northern long-eared bat (<i>Myotis septentrionalis</i>) colonies at a local scale
Bibliographic record
Abstract
We assessed parentage within and among maternity colonies of northern long-eared bats (Myotis septentrionalis (Trouessart, 1897)) in north-central Kentucky, USA, from 2011 to 2013 to examine colony social structure, formation, and membership dynamics. We intensively sampled colonies in close and remote (>10 km) proximity before and after targeted day-roost removal. Colonies were not necessarily composed of closely related individuals, although natal philopatry was common. Adjacent colonies often contained maternally related individuals, indicating that some pups did disperse, albeit not far from their natal home range. Whereas some young had been sired by males also collected on site, most had not, as would be expected since the species mates in fall near hibernacula across a wider landscape. The number of parentages that we inferred among colonies, however, suggests that outside the maternity season, social groups may be relatively flexible and open. Analysis of microsatellite DNA data showed a low FST (0.011) and best fit to a model of one multilocus genotypic cluster across the study area. We observed high turnover in colony membership between years in all colonies, regardless of roost-removal treatment. Our results suggest that female northern long-eared bats exhibit fidelity to a general geographic area and complex, dynamic social–genetic 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".