Active sampling as an information seeking strategy in primate vocal interactions.

Active sensing is a behavioral strategy for exploring the environment. In this study, we show that contact vocal behaviors can be an active sensing mechanism that uses sampling to gain information about the social environment, in particular, the vocal behavior of others. With a focus on the real-time vocal interactions of marmoset monkeys, we contrast active sampling to a vocal accommodation framework in which vocalizations are adjusted simply to maximize responses. We conduct simulations of a vocal accommodation and an active sampling policy and compare them with actual vocal interaction data. Our findings support active sampling as the best model for real-time marmoset monkey vocal exchanges. In some cases, the active sampling model was even able to partially predict the distribution of vocal durations for individuals to approximate the optimal call duration. These results suggest a non-traditional function for primate vocal interactions in which they are used by animals to seek information about their social environments.

Cetacean passive acoustic network in the Belgian part of the North sea.

In 2016, a design for detecting harbor porpoises (Phocoena phocoena) in the Belgian part of the North Sea (BPNS) was developed in the framework of the LifeWatch project using Passive Acoustic Monitoring (PAM) loggers. In 2018, the network of deployments fully matured, and eight locations across the BPNS are presently housed with a C-POD (Chelonia Ltd., UK), a PAM logger moored on the seafloor using a multi-use platform. The PAM logger continuously listens for harbor porpoise click trains, but only stores the click parameters. This paper presents the generated data series of harbor porpoise click trains at a minute-resolution and the details on the individual click trains. The field recordings, methodology and processing are described, along with its data curation, integration and quality control. The data are annually published online in a standardized format, accompanied with the metadata description, and labelled with a digital object identifier for traceability. Data are published under a CC-BY license, allowing the use of data under the condition of providing reference to the original source.

Automated detection of Bornean white-bearded gibbon (Hylobates albibarbis) vocalizations using an open-source framework for deep learning.

Passive acoustic monitoring is a promising tool for monitoring at-risk populations of vocal species, yet, extracting relevant information from large acoustic datasets can be time-consuming, creating a bottleneck at the point of analysis. To address this, an open-source framework for deep learning in bioacoustics to automatically detect Bornean white-bearded gibbon (Hylobates albibarbis) "great call" vocalizations in a long-term acoustic dataset from a rainforest location in Borneo is adapted. The steps involved in developing this solution are described, including collecting audio recordings, developing training and testing datasets, training neural network models, and evaluating model performance. The best model performed at a satisfactory level (F score = 0.87), identifying 98% of the highest-quality calls from 90 h of manually annotated audio recordings and greatly reduced analysis times when compared to a human observer. No significant difference was found in the temporal distribution of great call detections between the manual annotations and the model's output. Future work should seek to apply this model to long-term acoustic datasets to understand spatiotemporal variations in H. albibarbis' calling activity. Overall, a roadmap is presented for applying deep learning to identify the vocalizations of species of interest, which can be adapted for monitoring other endangered vocalizing species.

Deep transfer learning-based bird species classification using mel spectrogram images.

The classification of bird species is of significant importance in the field of ornithology, as it plays an important role in assessing and monitoring environmental dynamics, including habitat modifications, migratory behaviors, levels of pollution, and disease occurrences. Traditional methods of bird classification, such as visual identification, were time-intensive and required a high level of expertise. However, audio-based bird species classification is a promising approach that can be used to automate bird species identification. This study aims to establish an audio-based bird species classification system for 264 Eastern African bird species employing modified deep transfer learning. In particular, the pre-trained EfficientNet technique was utilized for the investigation. The study adapts the fine-tune model to learn the pertinent patterns from mel spectrogram images specific to this bird species classification task. The fine-tuned EfficientNet model combined with a type of Recurrent Neural Networks (RNNs) namely Gated Recurrent Unit (GRU) and Long short-term memory (LSTM). RNNs are employed to capture the temporal dependencies in audio signals, thereby enhancing bird species classification accuracy. The dataset utilized in this work contains nearly 17,000 bird sound recordings across a diverse range of species. The experiment was conducted with several combinations of EfficientNet and RNNs, and EfficientNet-B7 with GRU surpasses other experimental models with an accuracy of 84.03% and a macro-average precision score of 0.8342.

Use of whistles for acoustic classification of delphinids (odontoceti: Delphinidae) in the Western South Atlantic Ocean.

This study focuses on the acoustic classification of delphinid species at the southern continental slope of Brazil. Recordings were collected between 2013 and 2015 using towed arrays and were processed using a classifier to identify the species in the recordings. Using Raven Pro 1.6 software (Cornell Laboratory of Ornithology, Ithaca, NY), we analyzed whistles for species identification. The random forest algorithm in R facilitates classification analysis based on acoustic parameters, including low, high, delta, center, beginning, and ending frequencies, and duration. Evaluation metrics, such as correct and incorrect classification percentages, global accuracy, balanced accuracy, and p-values, were employed. Receiver operating characteristic curves and area-under-the-curve (AUC) values demonstrated well-fitting models (AUC ≥ 0.7) for species definition. Duration and delta frequency emerged as crucial parameters for classification, as indicated by the decrease in mean accuracy. Multivariate dispersion plots visualized the proximity between acoustic and visual match data and exclusively acoustic encounter (EAE) data. The EAE results classified as Delphinus delphis (n = 6), Stenella frontalis (n = 3), and Stenella longirostris (n = 2) provide valuable insights into the presence of these species between approximately 23° and 34° S in Brazil. This study demonstrates the effectiveness of acousting classification in discriminating delphinids through whistle parameters.

Widespread cultural change in declining populations of Amazon parrots.

Species worldwide are experiencing anthropogenic environmental change, and the long-term impacts on animal cultural traditions such as vocal dialects are often unknown. Our prior studies of the yellow-naped amazon (Amazona auropalliata) revealed stable vocal dialects over an 11-year period (1994-2005), with modest shifts in geographic boundaries and acoustic structure of contact calls. Here, we examined whether yellow-naped amazons maintained stable dialects over the subsequent 11-year time span from 2005 to 2016, culminating in 22 years of study. Over this same period, this species suffered a dramatic decrease in population size that prompted two successive uplists in IUCN status, from vulnerable to critically endangered. In this most recent 11-year time span, we found evidence of geographic shifts in call types, manifesting in more bilingual sites and introgression across the formerly distinct North-South acoustic boundary. We also found greater evidence of acoustic drift, in the form of new emerging call types and greater acoustic variation overall. These results suggest cultural traditions such as dialects may change in response to demographic and environmental conditions, with broad implications for threatened species.

Increased alertness and moderate ingroup cohesion in bonobos' response to outgroup cues.

In a number of species, including humans, perceived outgroup threat can promote ingroup cohesion. However, the distribution and selection history of this association across species with varied intergroup relations remains unclear. Using a sample of 8 captive groups (N = 43 individuals), we here tested whether bonobos, like chimpanzees, show more affiliative ingroup behaviour following perception of outgroup cues (unfamiliar male long-distance vocalisations). We used comparable methods to our previous study of captive chimpanzees, and found that, although weaker, there was an association for more frequent social grooming in response to the outgroup condition than the control condition, alongside more alert posture and increased self-directed behaviour. This provides preliminary evidence for an ancestral origin to the proximate association between outgroup cues and ingroup cohesion, at least prior to the Pan-Homo split, and suggests the presence of intergroup competition in our last common ancestor.

Language evolution in primates.

Human speech evolution is not just about having a speech-ready brain and vocal apparatus.

Development of sound production in Danionella cerebrum.

Acoustic signalling, integral to intraspecific communication and reproductive behaviour, undergoes notable changes during an animal's ontogenetic development. The onset and progression of this maturation in fish remains poorly understood. Here, we investigated the ontogeny of acoustic communication in the miniature teleost Danionella cerebrum, one of the smallest known vertebrates and an emerging model organism. Its adult males produce audible clicks that appear in sequences with a repetition rate of ∼60 or ∼120 Hz, caused by consecutive unilateral or alternating bilateral compressions of the swim bladder. To investigate the maturation of this ability, we performed long-term sound recordings and morphological studies of the sound production apparatus in D. cerebrum throughout its ontogenetic development. We found that fish start producing clicks during the second month of their lives and continually increase their abundance and structured repetition over the course of the following 1 to 2 months. The sound production machinery, including specialised bone and cartilage structures, starts to form in males after approximately 4 weeks and prior to reaching sexual maturity. Although clicks increase in amplitude as animals mature, click repetition rates of 60 and 120 Hz are stable throughout development. This suggests fully mature pattern generation in juvenile males, yet a continued development of the drumming apparatus capable of creating louder sounds.

Vocal tract dynamics shape the formant structure of conditioned vocalizations in a harbor seal.

Formants, or resonance frequencies of the upper vocal tract, are an essential part of acoustic communication. Articulatory gestures-such as jaw, tongue, lip, and soft palate movements-shape formant structure in human vocalizations, but little is known about how nonhuman mammals use those gestures to modify formant frequencies. Here, we report a case study with an adult male harbor seal trained to produce an arbitrary vocalization composed of multiple repetitions of the sound wa. We analyzed jaw movements frame-by-frame and matched them to the tracked formant modulation in the corresponding vocalizations. We found that the jaw opening angle was strongly correlated with the first (F1) and, to a lesser degree, with the second formant (F2). F2 variation was better explained by the jaw angle opening when the seal was lying on his back rather than on the belly, which might derive from soft tissue displacement due to gravity. These results show that harbor seals share some common articulatory traits with humans, where the F1 depends more on the jaw position than F2. We propose further in vivo investigations of seals to further test the role of the tongue on formant modulation in mammalian sound production.

Disinhibition enables vocal repertoire expansion after a critical period.

The efficiency of motor skill acquisition is age-dependent, making it increasingly challenging to learn complex manoeuvres later in life. Zebra finches, for instance, acquire a complex vocal motor programme during a developmental critical period after which the learned song is essentially impervious to modification. Although inhibitory interneurons are implicated in critical period closure, it is unclear whether manipulating them can reopen heightened motor plasticity windows. Using pharmacology and a cell-type specific optogenetic approach, we manipulated inhibitory neuron activity in a premotor area of adult zebra finches beyond their critical period. When exposed to auditory stimulation in the form of novel songs, manipulated birds added new vocal syllables to their stable song sequence. By lifting inhibition in a premotor area during sensory experience, we reintroduced vocal plasticity, promoting an expansion of the syllable repertoire without compromising pre-existing song production. Our findings provide insights into motor skill learning capacities, offer potential for motor recovery after injury, and suggest avenues for treating neurodevelopmental disorders involving inhibitory dysfunctions.

Towards automated animal density estimation with acoustic spatial capture-recapture.

Passive acoustic monitoring can be an effective way of monitoring wildlife populations that are acoustically active but difficult to survey visually, but identifying target species calls in recordings is non-trivial. Machine learning (ML) techniques can do detection quickly but may miss calls and produce false positives, i.e., misidentify calls from other sources as being from the target species. While abundance estimation methods can address the former issue effectively, methods to deal with false positives are under-investigated. We propose an acoustic spatial capture-recapture (ASCR) method that deals with false positives by treating species identity as a latent variable. Individual-level outputs from ML techniques are treated as random variables whose distributions depend on the latent identity. This gives rise to a mixture model likelihood that we maximize to estimate call density. We compare our method to existing methods by applying it to an ASCR survey of frogs and simulated acoustic surveys of gibbons based on real gibbon acoustic data. Estimates from our method are closer to ASCR applied to the dataset without false positives than those from a widely used false positive "correction factor" method. Simulations show our method to have bias close to zero and accurate coverage probabilities and to perform substantially better than ASCR without accounting for false positives.

Vocal labeling of others by nonhuman primates.

Humans, dolphins, and elephants are the only known species that vocally label their conspecifics. It remains unclear whether nonhuman primates share this ability. We recorded spontaneous "phee-call" dialogues between pairs of marmoset monkeys. We discovered that marmosets use these calls to vocally label their conspecifics. Moreover, they respond more consistently and correctly to calls that are specifically directed at them. Analysis of calls from multiple monkeys revealed that family members use similar calls and acoustic features to label others and perform vocal learning. These findings shed light on the complexities of social vocalizations among nonhuman primates and suggest that marmoset vocalizations may provide a model for understanding aspects of human language, thereby offering new insights into the evolution of social communication.

Buzzfindr: Automating the detection of feeding buzzes in bat echolocation recordings.

Quantification of bat communities and habitat heavily rely on non-invasive acoustic bat surveys the scope of which has greatly amplified with advances in remote monitoring technologies. Despite the unprecedented amount of acoustic data being collected, analysis of these data is often limited to simple species classification which provides little information on habitat function. Feeding buzzes, the rapid sequences of echolocation pulses emitted by bats during the terminal phase of prey capture, have historically been used to evaluate foraging habitat quality. Automated identification of feeding buzzes in recordings could benefit conservation by helping identify critical foraging habitat. I tested if detection of feeding buzzes in recordings could be automated with bat recordings from Ontario, Canada. Data were obtained using three different recording devices. The signal detection method involved sequentially scanning narrow frequency bands with the "Bioacoustics" R package signal detection algorithm, and extracting temporal and signal strength parameters from detections. Buzzes were best characterized by the standard deviation of the time between consecutive pulses, the average pulse duration, and the average pulse signal-to-noise ratio. Classification accuracy was highest with artificial neural networks and random forest algorithms. I compared each model's receiver operating characteristic curves and random forest provided better control over the false-positive rate so it was retained as the final model. When tested on a new dataset, buzzfindr's overall accuracy was 93.4% (95% CI: 91.5%- 94.9%). Overall accuracy was not affected by recording device type or species frequency group. Automated detection of feeding buzzes will facilitate their integration in the analytical workflow of acoustic bat studies to improve inferences on habitat use and quality.

Cross-population variation in usage of a call combination: evidence of signal usage flexibility in wild bonobos.

The arbitrary relationship between signifier and signified is one of the features responsible for language's extreme lability, adaptability, and expressiveness. Understanding this arbitrariness and its emergence is essential in any account of the evolution of language. To shed light on the phylogeny of the phenomenon, comparative data examining the relationship between signal form and function in the communication systems of non-humans is central. Here we report the results of a study on the production and usage the whistle-high hoot call combination (W + HH) from two distant populations of wild bonobos (Pan paniscus): Lui Kotale, DRC, and Kokolopori, DRC. We find that the context in which bonobos produce the W + HHs varies systematically between populations. Our results suggest that variation in W + HH production may represent an example of signal-adjustment optionality, a key component of arbitrariness.

Lasting benefits of embryonic eavesdropping on parent-parent communication.

Developing embryos have traditionally been viewed as passive agents in the evolution of family conflicts, with maternal substances within the uterus or eggs as main factors modulating later expression of offspring solicitation behaviors. Yet, parent-offspring conflict theory predicts that offspring might also rely on alternative cues to adjust demand in response to prenatal cues of parental capacity for resource provisioning. Here, we show how embryonic experience with vocalizations carried out by parents during nest-relief displays at incubation adaptively shapes avian offspring development, providing lasting benefits to offspring. Genetic siblings prenatally exposed to different levels of parent-parent communication showed differences in epigenetic patterns, adrenocortical responsiveness, development, and food solicitation behavior. The correspondence between prenatal acoustic experience and parental context positively influenced the nutritional status and growth rate of offspring reared by communicative parents. Offspring can thus retain strong control over their own development by gathering prenatal acoustic information about parental generosity.

Agomelatine Is Unable to Attenuate Kainic Acid-Induced Deficits in Early Life Communicative Behavior.

Early life seizures are associated with a variety of behavioral comorbidities. Among the most prevalent of these are deficits in communication. Auditory communicative behaviors in mice, known as ultrasonic vocalizations (USVs), can be used to assess potential treatments. Agomelatine is a melatonin agonist that effectively reduces behavioral comorbidities of seizures in adults; however, its ability to attenuate seizure-induced communicative deficits in neonates is unknown. To address this, we administered C57 mice either saline or kainic acid (KA) on postnatal day (PD) 10. The mice then received either agomelatine or saline 1-h post-status epilepticus. On PD 11, we assessed the quantity of USVs produced, the duration, peak frequency, fundamental frequency, and amplitude of the vocalizations, as well as the call type utilization. We found that KA increased vocal production and reduced USV variability relative to controls. KA also increased USV duration and amplitude and significantly altered the types of calls produced. Agomelatine did not attenuate any of the deficits. Our study is the first to assess agomelatine's efficacy to correct USVs and thus provides an important point of context to the literature, indicating that despite its high therapeutic efficacy to attenuate other behavioral comorbidities of seizures, agomelatine's ability to correct neonatal communicative deficits is limited.

Electroencephalography Measurements in Awake Marmosets Listening to Conspecific Vocalizations.

Vocal communication plays a crucial role in the social interactions of primates, particularly in survival and social organization. Humans have developed a unique and advanced vocal communication strategy in the form of language. To study the evolution of human language, it is necessary to investigate the neural mechanisms underlying vocal processing in humans, as well as to understand how brain mechanisms have evolved by comparing them with those in nonhuman primates. Herein, we developed a method to noninvasively measure the electroencephalography (EEG) of awake nonhuman primates. This recording method allows for long-term studies without harming the animals, and, importantly, allows us to directly compare nonhuman primate EEG data with human data, providing insights into the evolution of human language. In the current study, we used the scalp EEG recording method to investigate brain activity in response to species-specific vocalizations in marmosets. This study provides novel insights by using scalp EEG to capture widespread neural representations in marmosets during vocal perception, filling gaps in existing knowledge.

Size differences among canaries, goldfinches and allies may explain correlated evolution of song and colour.

Sexual signals such as colour ornamentation and birdsong evolve independently of each other in some clades, and in others they evolve positively or negatively correlated. We rarely know why correlated evolution does or does not occur. Here, we show positively correlated evolution between plumage colour and song motor performance among canaries, goldfinches and allies, associated with species differences in body size. When controlling for body size, the pattern of correlated evolution between song performance and colour disappeared. Syllable diversity was not as strongly associated with size, and did not evolve in a correlated manner with colour. We argue that correlated evolution between song and colour was mediated by large size limiting song motor performance, likely due to constraints on the speed of moving heavier bills, and by larger species having less saturated plumage colour, possibly due to life-history traits of larger birds (e.g. longevity, stable pairs) contributing to weaker sexual selection. Results are consistent with the hypothesis that correlated evolution between sexual signals is influenced by how, in a clade, selective pressures and constraints affecting each type of signal happen to be co-distributed across species. Such contingency helps explain the diversity in clade-specific patterns of correlated evolution between sexual signals.