Behavioral flexibility of vervet monkeys in response to climatic and social variability
Bibliographic record
Abstract
Responses to environmental variability sheds light on how individuals are able to survive in a particular habitat and provides an indication of the scope and limits of its niche. To understand whether climate has a direct impact on activity, and determine whether vervet monkeys have the behavioral flexibility to respond to environmental change, we examined whether the amount of time spent resting and feeding in the nonmating and mating seasons were predicted by the thermal and energetic constraints of ambient temperature. Our results show that high temperatures during the nonmating season were associated with an increase in time spent resting, at the expense of feeding. Cold temperatures during the nonmating season were associated with an increase in time spent feeding, at the expense of resting. In contrast, both feeding and resting time during the mating season were independent of temperature, suggesting that animals were not adjusting their activity in relation to temperature during this period. Our data indicate that climate has a direct effect on animal activity, and that animals may be thermally and energetically compromised in the mating season. Our study animals appear to have the behavioral flexibility to tolerate current environmental variability. However, future climate change scenarios predict that the time an animal has available for behaviors critical for survival will be constrained by temperature. Further investigations, aimed at determining the degree of behavioral and physiological flexibility displayed by primates, are needed if we are to fully understand the consequences of environmental change on their distribution and survival.
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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 | 0.001 | 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".