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The vocal structure of gibbons has long been believed to be under strong genetic control and consistent with phylogeny. Gibbon vocalizations show hierarchical structures and song coordination behaviors, which may have different functions and convey distinct information compared to basic notes. However, previous studies have not compared vocalizations at multiple levels across species. We compared the vocal structures of three Nomascus species in the wild in South China, namely the western black gibbon (Nomascus concolor), Cao vit gibbon (N. nasutus), and Hainan gibbon (N. hainanus) at the levels of note (six features of four types of notes), male sequence (eight features), and song coordination (four features of the overlap pattern between male and female songs). We selected 15 recordings for each species: N. concolor (six groups, 2006 to 2021), N. nasutus (seven groups, 2008 to 2021), and N. hainanus (six groups, 2020 to 2021). We used permuted random forest analysis to test for species differences in vocal structure and the contribution of acoustic features to species differences at each level. We used acoustic features to construct a hierarchical clustering tree, and compared it with phylogenetic relationships. We found significant differences at all levels except the boom note. Acoustic similarity did not match genetic similarity in boom and pre-modulated notes, suggesting that genetic differences are not the only factor leading to species differences in vocal structures. We also found different contributions of acoustic features to differentiation in vocal structure at different levels. Our study suggests that we need to compare gibbon vocalizations at different levels to understand their differentiation and evolution. [ABSTRACT FROM AUTHOR]

Monitoring threatened species at the individual level is fundamental and crucial in ecology and conservation, especially for critically endangered species. Hainan gibbon (Nomasucs hainanus) is the world's rarest primate species with <40 individuals, urgently needs a labor-efficient and continuous individual-level monitoring system to inform science-based conservation actions. Male dispersal, replacement, and formation of new groups with females are crucial for the population dynamics of gibbons. Their loud and elaborate morning songs provide the potential to automate the monitoring of their dynamics. Based on acoustic recordings from focal recording and 13 autonomous recording units within gibbons' home ranges, we developed an automated system, which successively (a) detected song bouts (duration ≈ 10 min, with ≈ 50 phrases) with temporal parameters using an energy detector with a hidden Markov model (F1 score >75 %), (b) detected and classified phrases (duration ≈ 5 s) within song bouts using a random forest model (F1 score ≈ 80–90 %), and (c) classified known individuals by a linear support vector machine (accuracy >93 %), and recognized unknown individuals by Gaussian mixture models (accuracy >90 %). The system successfully monitored a male immigration and kept tracking a dispersing male for nearly a year since it left the natal group to establish its own group with two females. Our system is effective even in the face of an ever-changing population and can be applied to passive acoustic data. It will contribute to the realization of long-term, large-scale, and continuous monitoring of individual dynamics for vocal animals. • We identified and tracked the dispersal of male Hainan gibbons with an automated system. • The system needs little training data and is robust against data variations. • The system helps to monitor individual dynamics from passive acoustics continuously. [ABSTRACT FROM AUTHOR]