Nocturnal activity in wild chimpanzees (<i>Pan troglodytes</i>): Evidence for flexible sleeping patterns and insights into human evolution
Bibliographic record
Abstract
OBJECTIVES: We investigated occurrences and patterns of terrestrial nocturnal activity in wild chimpanzees (Pan troglodytes) and modelled the influence of various ecological predictors on nocturnal activity. METHODS: Data were extracted from terrestrial camera-trap footage and ecological surveys from 22 chimpanzee study sites participating in the Pan African Programme: The Cultured Chimpanzee. We described videos demonstrating nocturnal activity, and we tested the effects of the percentage of forest, abundance of predators (lions, leopards and hyenas), abundance of large mammals (buffalos and elephants), average daily temperature, rainfall, human activity, and percent illumination on the probability of nocturnal activity. RESULTS: We found terrestrial nocturnal activity to occur at 18 of the 22 study sites, at an overall average proportion of 1.80% of total chimpanzee activity, and to occur during all hours of the night, but more frequently during twilight hours. We found a higher probability of nocturnal activity with lower levels of human activity, higher average daily temperature, and at sites with a larger percentage of forest. We found no effect of the abundance of predators and large mammals, rainfall, or moon illumination. DISCUSSION: Chimpanzee terrestrial nocturnal activity appears widespread yet infrequent, which suggests a consolidated sleeping pattern. Nocturnal activity may be driven by the stress of high daily temperatures and may be enabled at low levels of human activity. Human activity may exert a relatively greater influence on chimpanzee nocturnal behavior than predator presence. We suggest that chimpanzee nocturnal activity is flexible, enabling them to respond to changing environmental factors.
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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 | 0.001 | 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 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".