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Acoustic signals are ubiquitous across mammalian taxa. They serve a myriad of functions related to the formation and maintenance of social bonds and can provide conspecifics information about caller condition, motivation and identity. Disentangling the relative importance of evolutionary mechanisms that shape vocal variation is difficult, and little is known about heritability of mammalian vocalizations. Duetting--coordinated vocalizations within male and female pairs--arose independently at least four times across the Primate Order. Primate duets contain individual- or pair-level signatures, but the mechanisms that shape this variation remain unclear. Here, we test for evidence of heritability in two call types (pulses and chirps) from the duets of captive coppery titi monkeys (Plecturocebus cupreus). We extracted four features--note rate, duration, minimum and maximum fundamental frequency--from spectrograms of pulses and chirps, and estimated heritability of the features. We also tested whether features varied with sex or body weight. We found evidence for moderate heritability in one of the features examined (chirp note rate), whereas inter-individual variance was the most important source of variance for the rest of the features. We did not find evidence for sex differences in any of the features, but we did find that body weight and fundamental frequency of chirp elements covaried. Kin recognition has been invoked as a possible explanation for heritability or kin signatures in mammalian vocalizations. Although the function of primate duets remains a topic of debate, the presence of moderate heritability in titi monkey chirp elements indicates duets may serve a kin recognition function.

As social animals, many primates use acoustic communication to maintain relationships. Vocal individuality has been documented in a diverse range of primate species and call types, many of which have presumably different functions. Auditory recognition of one's neighbors may confer a selective advantage if identifying conspecifics decreases the need to participate in costly territorial behaviors. Alternatively, vocal individuality may be nonadaptive and the result of a unique combination of genetics and environment. Pair-bonded primates, in particular, often participate in coordinated vocal duets that can be heard over long distances by neighboring conspecifics. In contrast to adult calls, infant vocalizations are short-range and used for intragroup communication. Here, we provide two separate but complementary analyses of vocal individuality in distinct call types of coppery titi monkeys (Plecturocebus cupreus) to test whether individuality occurs in call types from animals of different age classes with presumably different functions. We analyzed 600 trill vocalizations from 30 infants and 169 pulse-chirp duet vocalizations from 30 adult titi monkeys. We predicted that duet contributions would exhibit a higher degree of individuality than infant trills, given their assumed function for long-distance, intergroup communication. We estimated 7 features from infant trills and 16 features from spectrograms of adult pulse-chirps, then used discriminant function analysis with leave-one-out cross-validation to classify individuals. We correctly classified infants with 48% accuracy and adults with 83% accuracy. To further investigate variance in call features, we used a multivariate variance components model to estimate variance partitioning in features across two levels: within- and between-individuals. Between-individual variance was the most important source of variance for all features in adults, and three of four features in infants. We show that pulse-chirps of adult titi monkey duets are individually distinct, and infant trills are less individually distinct, which may be due to the different functions of the vocalizations.

The figures included in this ESM are representative unsupervised phrase classifications of male solos as determined using affinity propagation clustering. Each page has four 30-sec excerpts from male solos with boxes drawn around unique phrases, and the number above the box indicates phrase type. In cases where there are two pages with the same male identifier, this is the result of the solo spanning two separate 40min recording windows.

Protocols for recording and acoustic analysis for each study.

The recent improvements in recording technology, data storage and battery life have led to an increased interest in the use of passive acoustic monitoring for a variety of research questions. One of the main obstacles in implementing wide scale acoustic monitoring programs in terrestrial environments is the lack of user-friendly, open source programs for processing large sound archives. Here we describe the new, open-source R package GIBBONFINDR which has functions for detection, classification and visualization of acoustic signals using a variety of readily available machine learning algorithms in the R programming environment. We provide a case study showing how GIBBONFINDR functions can be used in a workflow to detect and classify Bornean gibbon (Hylobates muelleri) calls in long-term acoustic data sets recorded in Danum Valley Conservation Area, Sabah, Malaysia. Machine learning is currently one of the most rapidly growing fields-- with applications across many disciplines-- and our goal is to make commonly used signal processing techniques and machine learning algorithms readily available for ecologists who are interested in incorporating bioacoustics techniques into their research., Comment: R package