Restoration of Legacy Trees as Roosting Habitat for Myotis Bats in Eastern North American Forests
Bibliographic record
Abstract
Most eastern North American Myotis roost in forests during summer, with species forming maternity populations, or colonies, in cavities or crevices or beneath the bark of trees. In winter, these bats hibernate in caves and are experiencing overwinter mortalities due to infection from the fungus Pseudogymnoascus destructans, which causes white-nose syndrome (WNS). Population recovery of WNS-affected species is constrained by the ability of survivors to locate habitats suitable for rearing pups in summer. Forests in eastern North America have been severely altered by deforestation, land-use change, fragmentation and inadvertent introduction of exotic insect pests, resulting in shifts in tree distributions and loss of large-diameter canopy-dominant trees. This paper explores patterns in use of tree roosts by species of Myotis across Canada and the United States using meta-data from published sources. Myotis in western Canada, the Northwest, and Southwest selected the largest diameter roost trees and also supported the largest maximum exit counts. Myotis lucifugus, M. septentrionalis and M. sodalis, three species that inhabit eastern forests and which are currently experiencing region-wide mortalities because of WNS, selected roosts with the smallest average diameters. Recovery efforts for bark- and cavity-roosting Myotis in eastern North American forests could benefit from management that provides for large-diameter trees that offer more temporally-stable structures for roosting during the summer maternity season.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".