Exploiting avian vision with aircraft lighting to reduce bird strikes
Bibliographic record
Abstract
Summary 1. Bird–aircraft collisions (bird strikes) represent a substantial safety concern and financial burden to civil aviation world‐wide. Despite an increase in the rate of damaging bird strikes, necessary steps to develop a mitigation method outside of the airport environment have not been empirically tested. 2. We assessed whether use of aircraft lighting might enhance detection of and reaction to the approach of an aircraft in flight by Canada geese Branta canadensis Linnaeus, a species responsible for a high rate of damaging bird strikes. We used a novel approach by estimating the visibility to the goose visual system of a standard radio‐controlled (RC) aircraft (standard aircraft) exhibiting either a 2‐Hz alternating pulse of two lights, or lights off; and another RC aircraft designed to mimic a raptor (predator model). We then exposed wing‐clipped Canada geese to the approach of each aircraft and quantified behavioural responses to respective treatments. 3. Estimates of chromatic and achromatic contrasts indicated that the standard aircraft with lights on was more salient to the visual system of the Canada goose than with lights off or the predator model. 4. At individual and group levels, quicker alert responses were observed to the standard aircraft with lights compared with the lights off and predator model. Goose groups showed similar responses to approaches by the standard aircraft and the predator model, suggesting use of antipredator behaviour to avoid the aircraft. 5. Synthesis and applications . Understanding animal sensory ecology and associated behaviours can aid the development of methods exploiting certain behaviours to reduce negative human–wildlife interactions. For example, reducing the frequency of bird strikes requires the integration of wildlife management efforts within and outside of the airport environment that target species resource use and response to disturbance, with mitigation techniques focused on the aircraft. Moreover, the design of aircraft lighting systems to enhance detection and avoidance by birds is contingent upon understanding avian visual ecology and behaviour. Based on spectral sensitivity in Canada geese, aircraft‐mounted lights that peak in the ultraviolet/violet range (380–400 nm) are likely to produce the maximal behavioural effect.
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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 | 0.001 |
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; both teacher heads agree on what is shown here.
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".