Stable isotope analysis reveals individual variations in feeding habits among wild Japanese macaques
Year: 2025
Type: article
Abstract: We employed stable isotope ratio analysis to quantitatively assess the feeding behaviors of individual macaques within a wild group of Japanese macaques ( Macaca fuscata ). The primary objective was to evaluate macaque's feeding habits at the individual scale and to clarify the relationship between feeding habits and social factors, including age, sex, and social rank. The study population consisted of the Main group of Japanese macaques on Koshima Island. We collected 78 body hair samples and 29 food resource samples for isotopic analysis. The variability in carbon, nitrogen, and sulfur isotope ratios among individuals in the Main group has ranges of 5.5‰, 6.5‰, and 6.8‰, respectively. Furthermore, the Bayesian mixture model revealed that there were individual differences in the utilization of forest‐derived (62.3%–90.5%), marine‐derived (6.1%–27.6%), and human‐derived (1.7%–23.4%) food resources, driven by the effect of sex, rank, and year. These findings particularly emphasize the utility of sulfur stable isotope ratios and demonstrate how the combined use of three stable isotope ratios enables effective analysis of the relationships between Japanese macaques and their food resources. Furthermore, our results provide a valuable opportunity for the advancement of future research that integrates stable isotope approaches with field investigations. This study not only highlights the applicability of sulfur isotope ratios as a tool for uncovering the use of marine resources by primates in other regions but also shows the potential of using isotopic techniques to distinguish human‐derived resources, such as wheat, and to develop strategies for managing crop‐raiding by macaques.
Source: Ecological Research
Language: English
Topic: Isotope Analysis in Ecology
Subfield: Ecology
Field: Environmental Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,000
Awards: G1148320047, G23366679, G649412278
OpenAlex ID: W4407167406
