Lights, bats, and buildings: investigating the factors influencing roosting sites and habitat use by bats in Grand Teton National Park
Bibliographic record
Abstract
Free-flying bats are highly affected by artificial night lighting, causing individuals to either 1) gather in unnaturally high densities around the light sources to exploit insects, or 2) travel increased distances to avoid light exposure. Similarly, nocturnal insects are disproportionately attracted to night lighting, trapping them until they die of exhaustion. The advent of new lighting technology which may decrease the impacts of night lighting on bats and insects by primarily producing light at wavelengths these animals are not sensitive to (i.e. in the red portion of the spectrum) is promising, however no studies have shown this at a large scale, and not in North America. Similarly, many studies on the effects of lights on bats, in general, have been on European species, and thus our overall understanding of how North American species are affected is low. Grand Teton National Park, Wyoming, provides an excellent natural system to study the effects of lights on bat behavior, as well as to test possible mitigation methods, as the park supports a large community of over a dozen species, as well as sizeable human infrastructure that generates night light. From June through September, 2019, we undertook a large-scale, blocked experiment examining bat activity and space use in Colter Bay Village under both traditional street-lighting, as well as new “bat friendly” street lighting. Using both passive echolocation records and radiotelemetry, we collected data that will allow us to examine the ability of red LED streetlights to mitigate artificial light’s negative impacts on bats and insects. Featured photo from figure 2 in report.
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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 | 0.000 |
| 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 | 0.001 |
| 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".