Fecal carbon and nitrogen isotopic analysis as an indicator of diet in Kanyawara chimpanzees, Kibale National Park, Uganda
Bibliographic record
Abstract
Abstract Objectives The shorter‐term overview from feces provides scope to investigate dietary fluctuations. We assess the correlation of stable isotopic fecal values with recorded seasonal diet of 10 adult chimpanzees (P. t. schweinfurthii) of the Kanyawara community (Kibale National Park, Uganda) and whether fecal nitrogen levels (%N) indicate a change in crude protein intake. Materials and Methods We recorded food eaten by each ape and collected both concurrent fecal samples (N = 115) and plant foods eaten by this community (N = 64). We compared fecal δ13C and δ15N values (also %N) with: (a) plant values; (b) feeding data; and (c) food‐items found macroscopically in the fecal samples. Interspecies and intraspecies differences in plant and fecal isotope values (and %N) as well as seasonality in diet were determined using parametric and nonparametric tests. Results No difference in plant δ13C and δ15N values was found at intraspecies or interspecies level. Fecal isotope values reflected a diet of C3 plants from evergreen forest vegetation. Seasonal differences in δ13C and δ15N corresponded with aspects of feeding and fecal macroscopic data, but only at community level. A change in crude protein intake was not indicated from %N content. Discussion This study further validates the use of staple isotope analyses of primate feces to provide a dietary overview, revealing seasonal differences at community level; however, conclusive results may be limited for individuals when using short sampling periods. Further study of variables that influence fecal %N content is also suggested to interpret crude protein intake.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".