Simultaneous measurements of three-dimensional trajectories and wingbeat frequencies of birds in the field
Bibliographic record
Abstract
Tracking the movements of birds in three dimensions is integral to a wide range of problems in animal ecology, behaviour and cognition. Multi-camera stereo-imaging has been used to track the three-dimensional (3D) motion of birds in dense flocks, but precise localization of birds remains a challenge due to imaging resolution in the depth direction and optical occlusion. This paper introduces a portable stereo-imaging system with improved accuracy and a simple stereo-matching algorithm that can resolve optical occlusion. This system allows us to decouple body and wing motion, and thus measure not only velocities and accelerations but also wingbeat frequencies along the 3D trajectories of birds. We demonstrate these new methods by analysing six flocking events consisting of 50 to 360 jackdaws ( Corvus monedula ) and rooks ( Corvus frugilegus ) as well as 32 jackdaws and 6 rooks flying in isolated pairs or alone. Our method allows us to (i) measure flight speed and wingbeat frequency in different flying modes; (ii) characterize the U-shaped flight performance curve of birds in the wild, showing that wingbeat frequency reaches its minimum at moderate flight speeds; (iii) examine group effects on individual flight performance, showing that birds have a higher wingbeat frequency when flying in a group than when flying alone and when flying in dense regions than when flying in sparse regions; and (iv) provide a potential avenue for automated discrimination of bird species. We argue that the experimental method developed in this paper opens new opportunities for understanding flight kinematics and collective behaviour in natural environments.
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 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 | 0.000 | 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 | 0.000 | 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) | 0.000 | 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".