PAE Coding System and Ethogram of Wild Yunnan Snub-Nosed Monkeys with Behavioral Comparisons Based on Infrared Camera...

The standardized construction of ethograms and the quantitative comparison of behavioral differences are fundamental to animal behavioral ecology research. This study focused on the Yunnan snub-nosed monkey (Rhinopithecus bieti) inhabiting the Weixi area of the Baimaxueshan National Nature Reserve and the Mangkang area of the Mangkang Yunnan Snub-nosed Monkey National Nature Reserve. From 2017 to 2021, a total of 120 infrared cameras were deployed, yielding 21,813 image and video files containing R. bieti. Based on the PAE (Posture-Act-Environment) coding system, an ethogram and corresponding coding framework were constructed. In total, 16 postures, 84 acts, and 22 environmental factors were identified; 135 behaviors were defined and classified into 18 functional categories. On this basis, behavioral composition differences were quantitatively compared across seasons and geographic regions. The results showed that season significantly affected behavioral composition (F = 5.029, R² = 0.255, p < 0.01). Four behavioral categories exhibited significant seasonal fluctuations: Locomotive behavior (χ² = 12.97, p < 0.01), Ingestive behavior (χ² = 12.04, p < 0.01), Resting behavior (χ² = 26.18, p < 0.001), and Miscellaneous behavior (χ² = 29.92, p < 0.001). Locomotive behavior peaked in summer, whereas Ingestive behavior was at its lowest and Resting behavior at its highest in autumn. Geographic region also significantly influenced behavioral composition (F = 2.808, R² = 0.149, p < 0.01). These differences were mainly reflected in significantly lower Locomotive behavior (U = 13, p < 0.01) and higher Ingestive behavior (U = 13, p < 0.05) in the higher-elevation Mangkang group compared with the lower-elevation Weixi group. By integrating infrared camera with the PAE coding system, this study not only constructs an ethogram for R. bieti but also compares behavioral differences across seasonal and geographic dimensions. The findings demonstrate the comprehensive applicability of this technical pathway for macroscopic behavior recognition, frequency statistics, and difference analysis in wild primates, and provide fundamental data for further understanding the ecological driving mechanisms of behavioral plasticity and for differentiated conservation management of R. bieti.