The growing concern for the ongoing biodiversity loss drives researchers towards practical and large-scale automated systems to monitor wild animal populations. Primates, with most species threatened by extinction, face substantial risks. We focused on the vocal activity of the indri (Indri indri) recorded in Maromizaha Forest (Madagascar) from 2019 to 2021 via passive acoustics, a method increasingly used for monitoring activities in different environments. We first used indris’ songs, loud distinctive vocal sequences, to detect the species’ presence. We processed the raw data (66,443 10-min recordings) and extracted acoustic features based on the third-octave band system. We then analysed the features extracted from three datasets, divided according to sampling year, site, and recorder type, with a convolutional neural network that was able to generalise to recording sites and previously unsampled periods via data augmentation and transfer learning. For the three datasets, our network detected the song presence with high accuracy (>90%) and recall (>80%) values. Once provided the model with the time and day of recording, the high-performance values ensured that the classification process could accurately depict both daily and annual habits of indris‘ singing pattern, critical information to optimise field data collection. Overall, using this easy-to-implement species-specific detection workflow as a preprocessing method allows researchers to reduce the time dedicated to manual classification.

Duets are one of the most fascinating displays in animal vocal communication, where two animals fine-tune the timing of their emissions to create a coordinated signal. Duetting behavior is widespread in the animal kingdom and is present in insects, birds, and mammals. Duets are essential to regulate activities within and between social units. Few studies assessed the functions of these vocal emissions experimentally, and for many species, there is still no consensus on what duets are used for. Here, we reviewed the literature on the function of duets in non-human primates, investigating a possible link between the social organization of the species and the function of its duetting behavior. In primates and birds, social conditions characterized by higher promiscuity might relate to the emergence of duetting behavior. We considered both quantitative and qualitative studies, which led us to hypothesize that the shift in the social organization from pair living to a mixed social organization might have led to the emergence of mate defense and mate guarding as critical functions of duetting behavior. Territory/resource ownership and defense functions are more critical in obligate pair-living species. Finally, we encourage future experimental research on this topic to allow the formulation of empirically testable predictions.

Animal vocalizations contain a varying degree of nonlinear phenomena (NLP) caused by irregular or chaotic vocal organ dynamics. Several hypotheses have been proposed to explain NLP presence, from unintentional by-products of poor vocal technique to having a functional communicative role. We aimed to disentangle the role of sex, age and physiological constraints in the occurrence of NLP in the songs of the lemur Indri indri , which are complex harmonic vocal displays organized in phrases. Age and sex affected the presence and type of NLP in songs. In particular, the proportion of the phenomena considered decreased with age, except for subharmonics. Subharmonics potentially mediate the perception of lower pitch, making signallers appear larger. Subharmonics and frequency jumps occurred in lower-pitched notes than regular units, while chaos and sidebands occurred in higher-pitched units. This suggests that different types of NLP can be associated with different vocal constraints. Finally, indris might present short-term vocal fatigue, with units occurring in the last position of a phrase having the highest probability of containing NLP. The presence of NLP in indris might result from proximate causes, such as physiological constraints, and ultimate causes, such as evolutionary pressures, which shaped the communicative role of NLP. This article is part of the theme issue ‘Nonlinear phenomena in vertebrate vocalizations: mechanisms and communicative functions’.

The study of how animals adapt their behaviors depending on weather variables has gained particular significance in the context of climate change. This exploration offers insights into endangered species' potential threats and provides information on the direction to take in conservation activities. In this context, noninvasive, cost‐effective, and potentially long‐term monitoring systems, such as Passive Acoustic Monitoring (PAM), become particularly appropriate. Our study investigates the relationship between weather variables and the vocal behavior of Indri indri, the sole singing lemur species, within Madagascar's Maromizaha New Protected Area. Using PAM, we explore the factors shaping the vocalization patterns of this primate species in response to some environmental factors in their natural habitat. Analysis of an extensive audio data set collected across different years revealed the differential influence of temperature and precipitation on Indri indri vocal activity. We found that rainfall negatively influenced the emission of the vocalizations while warmer temperatures correlated with a greater emission of songs. The various environmental factors we considered also affected the timing of vocal emissions, showing the same pattern. Furthermore, our study confirms, once again, the strength of PAM as a valuable tool for studying vocal animal communication quickly, giving us information about long‐term behavioral patterns that would be difficult to get in other ways. This research gives us further valuable information about how indris use vocalizations in their environment and how they adjust to environmental changes.

Nonlinear phenomena (NLP) in animal vocalizations arise from irregularities in the oscillation of the vocal folds. Various non-mutually exclusive hypotheses have been put forward to explain the occurrence of NLP, from adaptive to physiological ones. Non-human primates often display NLP in their vocalizations, yet the communicative role of these features, if any, is still unclear. We here investigate the occurrence of NLP in the song of a singing primate, the indri (Indri indri), testing for the effect of sex, age, season, and duration of the vocal display on their emission. Our results show that NLP occurrence in indri depends on phonation, i.e., the cumulative duration of all the units emitted by an individual, and that NLP have higher probability to be emitted in the later stages of the song, probably due to the fatigue indris may experience while singing. Furthermore, NLP happen earlier in the vocal display of adult females than in that of the adult males, and this is probably due to the fact that fatigue occurs earlier in the former because of a greater contribution within the song. Our findings suggest, therefore, that indris may be subjected to physiological constraints during the singing process which may impair the production of harmonic sounds. However, indris may still benefit from emitting NLP by strengthening the loudness of their signals for better advertising their presence to the neighboring conspecific groups.