Dispersal in male ursine colobus monkeys (Colobus vellerosus): influence of age, rank and contact with other groups on dispersal decisions
Bibliographic record
Abstract
Dispersal is male-biased in ursine colobus monkeys (Colobus vellerosus), although female dispersal also occurs (Teichroeb et al., 2009). Here we describe the process of male dispersal and its connection with between-group encounters (BGEs, N = 444) and male incursions (when males left their group and approached within 50 m of another group; N = 128) at the Boabeng-Fiema Monkey Sanctuary in central Ghana. Through BGEs and incursions, particularly those with non-aggressive interactions between individuals in different groups (BGEs, N = 17; incursions, N = 4), males could probably assess other groups for dispersal opportunities. There was a trend for males to perform incursions more frequently before emigrating voluntarily than involuntarily. Incursions were often performed towards the group that the male eventually transferred to. Incursions by alpha males were temporally shorter and more aggressive than those by non-alpha males. We suggest that non-alpha males used incursions to assess other groups for breeding or dispersal opportunities, whereas alpha males performed incursions mainly to convey information about their quality to neighbouring males and females. Male emigrations/disappearances (natal N = 20, secondary N = 43, unknown N = 9) and immigrations (N = 62) were recorded for seven groups during ten years (2000- 2010). Alpha males always emigrated involuntarily. Parallel emigration and immigration occurred. Males often immigrated into groups with a more favourable adult male/adult female ratio and improved their rank, both of which likely increased their mating opportunities. The most fitting ultimate explanation for both natal and secondary male dispersal in this population was the intrasexual competition for mates hypothesis, as males of all ages appeared to emigrate to improve their reproductive opportunities. © 2011 Koninklijke Brill NV, Leiden.
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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 | 0.000 | 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".