Continuing increase in the abundance of the Big Brown Bat (Eptesicus fuscus) in Maritime Canada in the presence of White-nose Syndrome
Bibliographic record
Abstract
Based on public reporting (mainly incidents of bats in homes and bats submitted for rabies testing and health monitoring), the number of reports of the Big Brown Bat (Eptesicus fuscus) in New Brunswick (Canada) has increased significantly over the past three decades. Prior to 1990 this species was rarely encountered in the province. From 2000 to 2013 the number of Big Brown Bat reports remained low but regular, including during the emergence of the white-nose syndrome (WNS) epidemic and subsequent endemicity of the disease in New Brunswick. From 2014-2020 numbers of Big Brown Bats reported have risen markedly. The Big Brown Bat is now the bat species most frequently encountered by the public in New Brunswick, although the species remains rare in Nova Scotia and is as yet unrecorded on Prince Edward Island. Establishment and initial increase of the Big Brown Bat in New Brunswick pre-dates the introduction of WNS to North America. Recent increases may be a continuation of a trend related to climate warming that was underway prior to WNSinduced declines in bat species in eastern Canada. However, we cannot discount a role for disease-mediated competitive release in the current surge in reports of the Big Brown Bat in New Brunswick. We also document aspects of the natural history of the Big Brown Bat in the Maritimes, including maternity roosts, autumn swarming behaviour, and first reported over-wintering by multiple Big Brown Bats in underground hibernacula in the region. While the probability of being bitten by a rabid bat in Canada is exceedingly low, the increasing abundance of the Big Brown Bat in New Brunswick and its association with human dwellings throughout the year may warrant increased public education and surveillance for rabies. However, given the continuing persecution of bats, any such educational campaign must be coupled with a strong message emphasizing the importance of bat conservation.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".