Abstract
Optimal foraging theory has only been sporadically applied to nonhuman primates. The classical prey model, modified for patch choice, predicts a sliding "profitability threshold" for dropping patch types from the diet, preference for profitable foods, dietary niche breadth reduction as encounter rates increase, and that exploitation of a patch type is unrelated to its own abundance. We present results from a 1-year study testing these predictions with Himalayan langurs (Semnopithecus entellus) at Langtang National Park, Nepal. Behavioral data included continuous recording of feeding bouts and between-patch travel times. Encounter rates were estimated for 55 food types, which were analyzed for crude protein, lipid, free simple sugar, and fibers. Patch types were entered into the prey model algorithm for eight seasonal time periods and differing age-sex classes and nutritional currencies. Although the model consistently underestimated diet breadth, the majority of nonpredicted patch types represented rare foods. Profitability was positively related to annual/seasonal dietary contribution by organic matter estimates, whereas time estimates provided weaker relationships. Patch types utilized did not decrease with increasing encounter rates involving profitable foods, although low-ranking foods available year-round were taken predominantly when high-ranking foods were scarce. High-ranking foods were taken in close relation to encounter rates, while low-ranking foods were not. The utilization of an energetic currency generally resulted in closest conformation to model predictions, and it performed best when assumptions were most closely approximated. These results suggest that even simple models from foraging theory can provide a useful framework for the study of primate feeding behavior.