Diet and Activity Budget in Colobus angolensis ruwenzorii at Nabugabo, Uganda: Are They Energy Maximizers?
Bibliographic record
Abstract
INTRODUCTION: Colobine monkeys are specialized folivores that use foregut fermentation to digest leaves. The slow process of fermentation forces them to spend a lot of time resting and to minimize their energy expenditure to subsist on a lower-quality diet. METHODS: We recorded the diet and activity budget of Colobus angolensis ruwenzorii, which form a three-tiered multi-level society, at Lake Nabugabo, Uganda, over 12 months using scan sampling on adults and subadults, to determine whether they utilize the energy minimization strategy typical of colobines. RESULTS: We found that the annual diet was primarily comprised of high-quality food resources (young leaves 65% and fruit 31%), and fruits were the only plant part the monkeysselected when available. Both the fruits and young leaves of some species were preferred food items in some months, and mature leaf consumption correlated negatively with preferred food availability. Mature leaves appear to be a fallback food for this population but are rarely relied upon (3%). The C. a. ruwenzoriiat Nabugabo spent less time resting (40%) and more time moving (25%) than is typical for other species of black-and-white colobus. DISCUSSION/CONCLUSION: The high-quality diet of this population appears to allow them to utilize an energy maximization strategy. Their reliance on food items that tend to be clumped in space and time likely explains the frequent fission-fusion behaviour that we observe between core units. Our findings demonstrate that the foraging strategies of colobines may be more flexible than was previously thought and illustrate how food availability and distribution can impact primate social organization.
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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 | 0.001 | 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".