Bat distribution and activity in Montréal Island green spaces: Responses to multi-scale habitat effects in a densely urbanized area
Bibliographic record
Abstract
(Uploaded by Plazi for the Bat Literature Project) In Quebec, Canada, 5 out of the 8 species of bats are considered potentially threatened or vulnerable. Measuring the impact on bat species of environmental changes brought about by urban development is crucial for bat species conservation. At which spatial scale does a gradient of increasing urbanization have the most significant effect on the distribution and activity of bats? To address this question, 3 sampling points in each of 24 green spaces (of different sizes, degree of "naturalness", and presence or not of water) across Montréal Island were sampled over 3 separate nights in June and July 2006. Echolocation calls of bats were recorded with Anabat detectors. Bat activity was determined by species or group of species for each green space. Various habitat factors associated with the urban gradient were acquired using GIS along a range of spatial scales, from local to landscape scales (areas of 0.1 km to 2 km radius around sampling points). Results show that patterns of distribution and bat activity differ according to species. Bats of the Myotis genus and Perimyotis subflavus were found mostly in areas with a high percentage of forest cover and near running water. Eptesicus fuscus and Lasiurus cinereus appeared to be less selective, as they were distributed much more uniformly across the study area. The more local spatial scales (from 0.1 km to 0.5 km radius) seem to have had a predominant influence on habitat requirements of bats, particularly for forest-dwelling 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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".