Quantifying seasonal fallback on invertebrates, pith, and bromeliad leaves by white‐faced capuchin monkeys (<scp><i>C</i></scp><i>ebus capucinus</i>) in a tropical dry forest
Bibliographic record
Abstract
OBJECTIVES: Fallback foods (FBFs) are hypothesized to shape the ecology, morphology, and behavior of primates, including hominins. Identifying FBFs is therefore critical for revealing past and present foraging adaptations. Recent research suggests invertebrates act as seasonal FBFs for many primate species and human populations. Yet, studies measuring the consumption of invertebrates relative to ecological variation are widely lacking. We address this gap by examining food abundance and entomophagy by primates in a seasonal forest. MATERIALS AND METHODS: We study foraging behavior of white-faced capuchins (Cebus capucinus)-a species renowned for its intelligence and propensity for extractive foraging-along with the abundance of invertebrates, dietary ripe fruits, pith, and bromeliads. Consumption events and processing time are recorded during focal animal samples. We determine abundance of vegetative foods through phenological and density records. Invertebrates are collected in malaise, pan, and terrestrial traps; caterpillar abundance is inferred from frass traps. RESULTS: Invertebrates are abundant throughout the year and capuchins consume invertebrates-including caterpillars-frequently when fruit is abundant. However, capuchins spend significantly more time processing protected invertebrates when fruit and caterpillars are low in abundance. DISCUSSION: Invertebrate foraging patterns are not uniform. Caterpillar consumption is consistent with a preferred strategy, whereas capuchins appear to fallback on invertebrates requiring high handling time. Capuchins are convergent with hominins in possessing large brains and high levels of sensorimotor intelligence, thus our research has broad implications for primate evolution, including factors shaping cognitive innovations, brain size, and the role of entomophagy in the human diet.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".