Amplied Birdstrike Risk Related to Population Increases of Large Birds in North America
Bibliographic record
Abstract
Bird-aircraft collisions (bird strikes) are an increasing safety and economic concern to the civil aviation industry worldwide, costing well over $1 billion each year.To reduce risks associated with strikes, the U.S. Federal Aviation Administration has developed airworthiness standards for airframes, windshields, and engines using a single 4-lb (1.82-kg) bird mass as the maximum that must be tested for most components.We determined that 36 of the approximately 650 bird species that nest in North America have average body masses greater than 4 lbs.Of the 31 species for which population trend data were available, 24 (77%) showed population increases over the past 20-40 years, only 2 showed declines and 5 were stable.Of most importance, 13 of the 14 species with body masses over 8 lbs (3.64 kg) showed population increases.At least 294 strikes with >4-lb birds caused substantial damage to civil aircraft in the USA, 1990-2002; 30% of these strikes involved multiple birds.Over 6,022 strikes occurred at heights >1,000 feet above ground level of which at least 1,986 (33%) involved >4-lb birds.We conclude that airworthiness standards, as well as proposals to allow high-speed (>250 knots [288 miles/hour]) operations below 10,000 feet, should be reevaluated to address the threat posed by increased populations of large flocking birds.Also, increased research and development is needed in the deployment of bird-detecting radar to warn pilots of flocks of migrating birds and in techniques to make aircraft more visible to birds.Finally, wildlife biologists should increase efforts to reduce or disperse populations of these large birds in airport environments.For certain overabundant large species such as non-migratory Canada geese (Branta Canadensis), management programs may be needed to reduce populations regionally.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 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".