Spatial Occupancy Patterns of the Endangered Northern Long‐Eared Bat in New England
Bibliographic record
Abstract
ABSTRACT Aim White‐nose syndrome has caused severe declines in eastern North American cave bats, leading to the federal listing of the northern long‐eared bat ( Myotis septentrionalis ) as endangered in the United States and Canada. This has heightened the importance of long‐term monitoring to inform species status assessments. We employed a combination of long‐term repeated and single‐season acoustic survey data to assess the regional presence, spatial distribution, occupancy, and detection probability of northern long‐eared bats. Location New England, United States. Methods We analysed acoustic data from 2357 detector sites, aggregated by year, using Bayesian single‐species occupancy models. We investigated the influence of habitat characteristics, climatic variables, and year (2015–2022) on occupancy and the effects of weather conditions and survey month (May to August) on detection probability. Spatial random effects were included to address residual spatial autocorrelation, with a 1‐km resolution chosen based on significant positive autocorrelation observed in a non‐spatial model. Results Occupancy was highest on steep, forested hillsides with minimal anthropogenic development, higher in warmer regions, particularly along coastlines and on offshore islands, and declined across survey years. Including a 1‐km spatial random effect reduced residual autocorrelation and suggests northern long‐eared bats utilise resources at small to medium landscape scales. Detection probability was highest earlier in the maternity season, but declined when monthly precipitation or temperature exceeded average conditions. Conclusions Conservation efforts that focus on steep, forested hillsides in warmer regions with low anthropogenic development could be beneficial. Our analysis supports the use of spatial random effects at a 1‐km 2 scale, highlighting the importance of survey designs that capture ecological variation at species‐specific resolutions. Additionally, early‐season acoustic surveys conducted during favourable weather conditions may improve monitoring effectiveness. Acoustic sampling and spatial occupancy modelling offer powerful tools for monitoring remnant populations of northern long‐eared bats and guiding conservation practices.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 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) | 0.000 | 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 teacher head, 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".