Ecological Exposure History Shapes Giraffe Vigilance Responses to Anthropogenic Noise: A Multisite Playback Experiment
Bibliographic record
Abstract
multiple giraffe species face varying degrees of conservation condern under IUCN criteria due to rapid habitat modification and increasing human disturbance, yet the behavioral consequences of anthropogenic noise exposure have not been experimentally tested. Because vigilance is a key anti-predator response in large herbivores and is highly sensitive to disturbance, we used it as a focal metric to assess giraffe reactions to noise. We conducted multisite playback experiments across three reserves in the Free State Province, South Africa, that differed in human-exposure levels. Free-roaming giraffes were presented with three anthropogenic sound stimuli (drone, vehicle, people talking) and a natural control stimulus (ring-necked dove). Vigilance responses were video-recorded, quantified, and analyzed using mixed-effects models. Giraffes at the low-exposure site showed markedly stronger vigilance responses to anthropogenic than to the natural control, whereas responses at high-exposure sites were weaker and less differentiated across stimuli. These site-specific patterns indicate that ecological exposure history modulates giraffe responsiveness to noise. Across the full dataset, anthropogenic sounds consistently elicited stronger vigilance responses than the control stimulus, demonstrating that noise alone, independent of visual cues, can alter natural behavior in free-roaming giraffes. Collectively, these findings highlight the importance of incorporating acoustic disturbance into environmental impact assessments and protected-area management. More broadly, the results contribute to understanding how wildlife perceive and respond to human-generated noise and emphasize the need to integrate soundscape considerations into conservation planning as anthropogenic noise continues to expand across savanna ecosystems.
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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 | 0.001 |
| 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 | 0.001 |
| 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".