Sleeping Site and Tree Selection by Bale Monkeys (Chlorocebus djamdjamensis) at Kokosa Forest Fragment in Southern Ethiopia
Bibliographic record
Abstract
Abstract Although selecting advantageous sleeping sites is crucial for nonhuman primates, the extent to which different factors contribute to their selection remains largely unknown for many species. We investigated hypotheses relating to predator avoidance, food access, and thermoregulation to explain the sleeping behavior of Bale monkeys ( Chlorocebus djamdjamensis ) occupying a degraded fragmented forest, Kokosa, in the southern Ethiopian Highlands. We found that the study group reused 11 out of 20 sleeping sites used during the 42 study days over a 6-month period. Sleeping sites were usually close to the last feeding trees of the day (mean distance =15.2 m) and/or the first feeding trees of the next morning (mean distance = 13.5 m). This may reflect an attempt to maximize feeding efficiency and reduce travel costs. Compared to the mean trees in the study area, sleeping trees were significantly shorter. Bale monkeys selected sleeping places in trees with high foliage density above and below them, lending support to the hypothesis that they select sleeping places that can conceal them from predators and at the same time offer shelter from cold weather. The monkeys also frequently huddled at night. Our results suggest that predator avoidance, access to food resources, and thermoregulation all likely influence the selection of sleeping sites by Bale monkeys.
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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 | 0.000 | 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) | 0.001 | 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 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".