Long-distance movements of little brown bats (<i>Myotis lucifugus</i>)
Bibliographic record
Abstract
Quantifying distributions, home ranges, and individual movements for wildlife species is crucial for understanding their ecology and is important for conservation. This has become especially urgent for bat species affected by white-nose syndrome, a new disease of hibernating bats associated with the fungus Geomyces destructans. We studied within- and between-season movements of individual little brown bats (Myotis lucifugus) throughout a 337,540-km2 study area in Manitoba and northwestern Ontario, Canada. Our objectives were to quantify proportions of male and female bats that relocated from hibernacula and/or summer roosts between years, proportions of males and females captured at swarms that hibernated at those sites versus other hibernacula, and distances traveled by males and females during relocation events. We predicted that bats would exhibit male-biased dispersal, with males significantly more likely to relocate and more likely to travel long distances during relocation events. Between 1989 and 2010, we recaptured 1,459 of 10,432 banded individuals. Seasonal movements from hibernacula and/or swarms to summer colonies ranged widely from 10 to 647 km. Consistent with previous studies we found high fidelity to summer colonies and hibernacula across years. However, some individuals switched sites between years and the median relocation distance was 315 km, with over 20% of individual movements exceeding 500 km. Surprisingly, we found that females were significantly more likely to relocate than males. Our data could help explain apparent jumps in the distribution of G. destructans, but more data on transmission of the fungus in the wild are needed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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".