The effects of light characteristics on avian mortality at lighthouses
Bibliographic record
Abstract
The generation of artificial light by human activity can have far‐reaching detrimental impacts upon a wide variety of organisms. A great deal of attention has been paid to well‐lit buildings, television towers, and communication towers as sources of mortality for nocturnally migrating songbirds. However, despite being among the first human structures known to generate migratory bird kills, little is known about the current impact of lighthouses on birds, or the impact of light design. We examined the impact of a lighthouse on nocturnal avian migrants at Long Point, Lake Erie, Ontario, Canada. From 1960–1989, mean annual kills were 200 birds in spring, and 393 in autumn, with kills of up to 2000 birds in a single night. In 1989, the Long Point lighthouse was automated, with a simultaneous change in beam characteristics – the new beam is narrower and less powerful. This change brought about a drastic reduction in avian mortality at the lighthouse to a mean of only 18.5 birds per year in spring, and 9.6 in autumn from 1990–2002. Our results highlight the effectiveness of simple changes in light signatures in reducing avian light attraction and mortality during migration.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".