Hibernacula microclimate and declines in overwintering bats during an outbreak of white‐nose syndrome near the northern range limit of infection in North America
Bibliographic record
Abstract
Abstract We document white‐nose syndrome (WNS), a lethal disease of bats caused by the fungusPseudogymnoascus destructans(Pd), and hibernacula microclimate in New Brunswick, Canada. Our study area represents a more northern region than is common for hibernacula microclimate investigations, providing insight as to how WNS may impact bats at higher latitudes. To determine the impact of the March 2011 arrival ofPdin New Brunswick and the role of hibernacula microclimate on overwintering bat mortality, we surveyed bat numbers at hibernacula twice a year from 2009 to 2015. We also collected data from iButton temperature loggers deployed at all sites and data from HOBO temperature and humidity loggers at three sites. Bat species found in New Brunswick hibernacula includeMyotis lucifugus(Little Brown Bat) andM. septentrionalis(Northern Long‐eared Bat), with small numbers ofPerimyotis subflavus(Tricolored Bat). All known hibernacula in the province werePd‐positive with WNS‐positive bats by winter 2013. A 99% decrease in the overwintering bat population in New Brunswick was observed between 2011 and 2015. We did not observeP. subflavusduring surveys 2013–2015 and the species appears to be extirpated from these sites. Bats did not appear to choose hibernacula based on winter temperatures, but dark zone (zone where no light penetrates) winter temperatures did not differ among our study sites. Winter dark zone temperatures were warmer and less variable than entrance or above ground temperatures. We observed visiblePdgrowth on hibernating bats in New Brunswick during early winter surveys (November), even though hibernacula temperatures were colder than optimum for in vitroPdgrowth. This suggests that cold hibernacula temperatures encountered near the apparent northern range limit forPddo not sufficiently slow fungal growth to prevent the onset of WNS and associated bat mortality over the winter.
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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 | 0.001 |
| 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) | 0.001 | 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".