Goitered Gazelle Gazella subgutturosa Responded to Human Disturbance by Increasing Vigilance Rather than Changing the Group Size
Bibliographic record
Abstract
Nonlethal human disturbances have been confirmed to have a negative effect on wildlife in a variety of ways, including on behaviors. In many studies, the impact of human disturbances on gregarious species of wildlife is assessed through changes in their social organization and vigilance. In our study in the Kalamaili Nature Reserve, China, we wanted to estimate the impacts of differing levels of human disturbances on two different group types (mixed-sex and all-male) of goitered gazelle, Gazella subgutturosa, living in three functional zones (experimental, buffer, and core zones), which represent high, medium, and low human disturbance levels, respectively. In addition, we studied the time spent vigilant as a function of group size with different levels of human disturbances in the three zones. In general, mixed-sex gazelle groups were of similar sizes in the three different zones, while all-male groups slightly differed in their sizes between the experimental and buffer zones. This may indicate that human disturbances have varying effects on the different group types, with smaller-sized, single-sex groups being more significantly affected by human disturbances than larger-sized, mixed-sex groups. Goitered gazelle showed higher vigilance levels in the experimental zone than in the two other zones. A trend of decreasing vigilance varying linearly with group size was also found in the three zones, and the rate of decrease was higher in the experimental zone. Increased habitat fragmentation and human activities brought goitered gazelle and humans closer together in the core zone. Therefore, stopping mining activities and returning the reserve to a continuous habitat with fewer environmental disturbances is the best way to establish and protect a stable population of this endangered species of gazelle.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".