Summary Report on the Bird Friendly Building Program: Effect of Light Reduction on Collision of Migratory Birds.
Bibliographic record
Abstract
Most migratory songbirds are nocturnal migrants, which makes them vulnerable to collision with lighted structures they encounter along their flight path during migration. The Fatal Light Awareness Program (FLAP) was formed by a group of concerned citizens to rescue and relocate disoriented birds trapped in the city centre, and to record the number and species of birds killed due to collision. Following the initiation of the Bird Friendly Building (BFB) Program by FLAP and World Wildlife Fund Canada in 1997, light emissions at 16 buildings in the downtown core of Toronto were also monitored during migration seasons. This report summarizes data on birds and light emissions collected from 1997 to spring 2001. This data provides evidence that: • the number of fatal bird collisions increases with increasing light emissions • the number of birds entrapped by particular buildings rises with increasing light emissions • the BFB has been successful in reducing light emissions • weather is the most important factor influencing collision risk • nights of heavy cloud cover and/or nights with precipitation are the conditions most likely to result in high numbers of collisions. A survey of building managers involved in the BFB program revealed that tenant education programs about bird collisions had increased awareness of the problem. Managers found that most tenants were willing to participate in the BFB, which they saw as a “green” initiative that had a positive environmental impact. Many buildings had installed or reprogrammed automated light systems that reduced the number of night-time hours that lights were left on. Several buildings that had limited success in reducing light levels between 1997 and fall 2001 have recently installed automated timer systems that should dramatically improve their light emission reductions in the future. In general, the BFB represents a win-win situation for property managers because reducing the period of time that lights are on not only reduces bird mortality but also results in substantial cost savings due to reduced energy consumption. An estimated $3.2 million could be saved if all of the 16 monitored buildings employed the nighttime light emission reductions already in place at several of the BFB sites. Such a reduction in power consumption would result in an estimated reduction of 38,400 tons of CO2-emissions from fossil-fuel burning energy sources. The BFB therefore contributes locally to a reduction in bird mortality, and globally to a reduction in carbon dioxide emissions, thus reducing the production of greenhouse gases that lead to global climate change.
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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 | 0.001 | 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 | 0.000 | 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 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".