Seasonal activity patterns of Arsi geladas (Theropithecus gelada arsi) inhabiting an anthropogenic landscape at Goro-Jena, Ethiopia
Bibliographic record
Abstract
Characterizing activity budgets in response to seasonality and anthropogenic pressures provides insights into primate behavioral ecology. The Arsi geladas (T. gelada arsi) are a distinct and little-known subspecies of geladas living south of the Rift Valley in eastern Arsi, Ethiopia, where elevation and rainfall levels are low, temperatures are high, and habitat loss and degradation threaten the geladas. To better understand how Arsi geladas cope with the challenges of their highly disturbed and climatically challenging environment, we conducted 16 months of observational scan sampling on a focal band of approx. 35 individuals (consisting of two one-male units) at Goro-Jena to examine diurnal and seasonal variation in their activity budgets. Overall, Arsi geladas spent most of their time feeding (57.3 ± 5.0%), followed by socializing (18.7% ± 3.8), moving (12.5 ± 5.0), and resting (10.2 ± 3.1). Feeding peaked in the late morning and late afternoon and social behavior peaked in the early morning near sleeping sites. Resting also peaked in the early morning as well as around mid-day, when ambient temperatures were warmest, the latter peak potentially reflecting the thermoregulatory challenges of the hot climate in Arsi. Arsi geladas exhibited only minor seasonal shifts in their activity patterns with increases in feeding time corresponding with periods of lower resource availability and quality. Percentage of time devoted to feeding by geladas at Goro-Jena was comparable to that of some populations at high elevations which themselves must cope with cold climates. This finding suggests that Arsi geladas at Goro-Jena occupy a marginal environment that imposes substantial energetic stress on them. As such, priority conservation actions must include protecting and expanding natural gelada habitat at Goro-Jena - as well as elsewhere in Arsi - to ensure the persistence of this increasingly rare and threatened gelada subspecies.
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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".