Ecology of reproduction in Sanje mangabeys (<i>Cercocebus sanjei</i>): Dietary strategies and energetic condition during a high fruit period
Bibliographic record
Abstract
The ability to increase energy storage when food is abundant for later use during late gestation and early lactation is often considered the primary benefit of the capital breeding strategy (clustering conceptions during high food periods, HFP) that promotes reproductive success among females living in unpredictable environments. Capital breeding, however, may also enable preconceptive females to increase hormone production for ovulation, which has been linked to energetic condition in capital breeders, and/or allow females entering the subsequent HFP to increase their energetic condition in order to continue nursing unweaned infants. Here, we investigate whether capital breeding provides these additional benefits in 16 female Sanje mangabeys (Cercocebus sanjei) and determine the dietary strategies used to increase energetic condition (measured by urinary C-peptide: UCP) during the HFP. Fecal estradiol (fE2 ) and UCP were negatively correlated with number of cycles before conception (r = -0.591, r = -0.646, P < 0.01) and were highest in conceptive cycles. Both peri-conceptive (preconception and early gestation) and non-peri-conceptive (lactation) females increased energetic condition over the HFP (r = 0.612, r = 0.583, P < 0.001) by increasing dietary fat (r = 0.619, r = 0.703, P < 0.001) and, for non-peri-conceptive females, protein (r = 0.437, P < 0.001). Feeding intake rate (FIR) and time spent foraging and feeding did not change over the HFP; however, non-peri-conceptive females exhibited a faster FIR compared to peri-conceptive females (t = -2.324, P < 0.05), consuming almost twice as much food per unit time. The results of this study confirm that Sanje mangabeys benefit in multiple phases of the reproductive cycle by using capital breeding, which may explain how this strategy promotes female reproductive success.
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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) | 0.000 | 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) | 0.000 | 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".