Among-population divergence in personality is linked to altitude in plateau pikas (Ochotona curzoniae)
Bibliographic record
Abstract
Animals inhabiting high altitudes consistently show slow life-histories. The pace-of-life syndrome (POLS) hypothesis posits behavioural, physiological and/or morphological traits that mediate the trade-off between current and future reproduction or survival, which have coevolved along a slow-fast life history continuum. Previous studies have shown that the life histories of plateau pikas varied across altitude, high-altitude individuals showed slow pace of life which were characterized by few litters per year with small litter sizes. Thus, we hypothesized that pikas populations at higher altitudes would also express personalities characteristic associated with slow life history, such as high sociability, low activity or aggressiveness. We tested this hypothesis by comparing the activity and docility of three plateau pika ( Ochotona curzoniae ) populations distributed along an altitudinal gradient of the Tibetan Plateau. We predicted that high-altitude pika would be more docile and less active. The behaviour of 556 pikas, from which 120 individuals were measured at least twice, was quantified. We observed that plateau pikas at high altitudes were less active and more docile than pika at lower altitudes. Activity and docility were significantly and negatively correlated in populations from high altitudes but not in populations from low altitudes. Our results support the POLS hypothesis, highlight the existence of personality variation among populations distributed along an altitudinal gradient and emphasise the importance of environmental selection on personality divergence.
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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 | 0.000 |
| 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".