What factors limit bat abundance and diversity in temperate, North American urban environments?
Bibliographic record
Abstract
Urbanization in North America has replaced many pre-existing natural environments with artificial, human-populous environments of low biodiversity. Although some bat species have persisted in urban environments, the overall abundance and diversity of bats within them is low. We examined five factors that may contribute to the low diversity of bats in temperate, North American urban environments: anthropogenic noise, road infrastructure and traffic, ecological light pollution, plant roost availability and diversity and the distribution and diversity of prey. We present a review of available literature to evaluate how each factor may constrain bat abundance and diversity in urban environments. We found that anthropogenic noise and plant roost availability and diversity were more likely to influence only some species of bats, whereas road infrastructure and traffic, ecological light pollution and the distribution and diversity of prey were likely to influence most species of bats. Generally, the effects of these factors on bats are common among urban environments, but individual species' responses to these characteristics might differ slightly among urban environments. Additional research about the effects of these factors on urban bat ecology, abundance and diversity, combined with the protection and connection of existing natural habitat, and education about bats, would inform efforts to increase the suitability of urban environments for bats.
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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 | 0.001 |
| 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".