Testing mechanisms of coexistence among two species of frugivorous primates
Bibliographic record
Abstract
1. We examined mechanisms of coexistence between two congeneric species of frugivorous primates, the blue monkey (Cercopithecus mitis) and the red-tailed monkey (C. ascanius). 2. We used giving-up densities (the amount of food which animals leave in a patch) in fruit trees to measure foraging efficiency and to evaluate possible mechanisms of coexistence. Animals with higher giving-up densities are less likely to persist in the company of those with lower giving-up densities because the former are not able to exploit food patches used previously by the latter. We climbed trees to estimate giving-up densities by counting the fruit which primates left behind. 3. We tested five possible mechanisms of coexistence. Three mechanisms proposed that each frugivorous species has a lower giving-up density than the other in at least one of the following: (1) different tree species, (2) within-tree foraging zones or (3) seasons. The fourth mechanism predicted that the socially dominant species exploits resources first and that the subordinate species has lower giving-up densities. The final mechanism predicted that one species would find resources more quickly than the other, which would in turn have a lower giving-up density. 4. Four of the five mechanisms received no support from our data. Only a trade-off between interspecific dominance and giving-up densities was supported. 5. We discuss the generality of our results and possible interactions with other factors.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".