Factors affecting intra- and inter-specific variations in the difference between alert distances and flight distances for birds in forested habitats
Bibliographic record
Abstract
Studies of escape from predators have usually focused on fleeing. We studied intra- and inter-specific variations in a previous level of decision-making during predatorprey encounters by determining the difference between the distance at which a predator is detected and the distance at which the prey flees from the predator (buffer distance). We measured buffer distances of four bird species (ground foragers) living in forested habitats (wooded recreational parks) to approaching humans. Buffer distances increased with group size and temperature, and this was probably related to dilution of the predation risk and a higher risk of heat stress, respectively. Buffer distances decreased with shrub and coniferous cover, probably because of increased visual obstruction, and increased with tree height, probably because of the increased security provided by taller trees. Grass cover increased buffer distances of wood pigeons (Columba palumbus) but decreased those of house sparrows (Passer domesticus) and magpies (Pica pica); this may be related to higher food availability, i.e., vegetation in grassy areas for wood pigeons and food left by humans in areas with bare ground for house sparrows and magpies. Buffer distances of blackbirds (Turdus merula) and house sparrows were greater in highly visited parks, which may be related to habituation. Finally, larger species showed greater buffer distances, landed farther away, used higher landing substrates (trees), and flew higher, probably because they need to ensure a certain margin of security from predators. Alternatively, the increased buffer distances of large species may be related to the increasing energy expenditure of flight. The buffer distance appears to be a good indicator of tolerance toward predators and (or) risk taken by prey after detecting predators.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".