Landscape‐Scale Effects of Season and Predation Risk on the Terrestrial Behavior of Chacma Baboons (<i>Papio ursinus</i>)
Bibliographic record
Abstract
OBJECTIVES: "Terrestrial" primates are not common nor well defined across the order. In those species that do use the ground, terrestriality is rarely documented outside daylight hours. Predation risk is thought to have shaped conserved behaviors like primates' selection of arboreal sleep sites, but it is less clear-particularly at the landscape scale-how predation risk interacts with other ecological and seasonal variables to drive terrestriality. This camera trapping study investigates patterns in terrestrial behavior both spatially and temporally across neighboring populations of chacma baboons. MATERIALS AND METHODS: We use camera trap data from two terrestrial grids, one established within and one outside the boundaries of Gorongosa National Park, Mozambique. We model how baboon terrestrial activity varies with woody cover, proximity to water, season, anthropogenic variables, as well as predation risk. We also model how terrestrial activity varies across the diel cycle and use overlap analyses to explore differences in the baboon populations' activity patterns. RESULTS: We find no significant predictors of geospatial variation in the terrestrial activity of baboons across each grid but do find evidence of higher terrestrial activity in the late dry season. We also find significantly different diel patterns of baboon activity detected across each grid. DISCUSSION: Baboons likely use the ground more in the dry season for accessing water and resources when arboreal foods are less abundant. Diel variation between the two populations suggests that baboons might utilize the ground more during "riskier" crepuscular and nocturnal hours where leopards are not present.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.003 |
| 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".