Summer cave use by tricolored bats declined in response to white-nose syndrome despite persistence in winter hibernacula in the southeastern United States
Bibliographic record
Abstract
Abstract Several bat species have experienced rapid population declines in the northern United States and Canada in response to the white-nose syndrome (WNS) epizootic. The pathogen has since spread across the United States, including the Southeast, where relatively warm temperatures may change host–pathogen interactions. In the cave-rich Tennessee–Alabama–Georgia (TAG) region, we examined the impacts of WNS and forest cover on the Tricolored Bat (Perimyotis subflavus) metapopulation using a long-term data set of 832 cave surveys conducted in summer and winter from 2004 to 2022. Most bat colonies were small (<30 individuals), and bats were more likely to be present and abundant in caves surrounded by high percent forest cover, reiterating the importance of forest management for bat conservation. When comparing the years before and after the pathogen arrived in 2010 to 2012, bat presence and abundance during winter hibernation did not change. This stability contrasts with significant declines in other studies, suggesting that Tricolored Bat populations respond differently to WNS in small colonies in the TAG region. Fewer tricolored bats used caves in the summer than during hibernation, but across all years, we observed 1,021 tricolored bats in 121 caves during summer surveys. Unlike stable winter trends, bat presence and abundance declined in the post-WNS period in summer, when cave use is optional. This first broad geographical analysis of summer cave use highlights a potentially important change in bat behavior. Disease surveillance and conservation efforts that target caves with relatively small Tricolored Bat colonies in winter and/or summer may be important for regional population persistence of this threatened species.
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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".