Integrative bioacoustics discrimination of eight delphinid species in the western South Atlantic Ocean

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.

The Dog Soundscape: Recurrence, Emotional Impact, Acoustics, and Implications for Dog Observations and Dog-Human Interactions

While numerous dog behavioral studies use environmental sounds, the dog soundscape remains undescribed. We proposed a list of 79 sounds classified into six categories: Dog, Dog accessories, Human, city and vehicles, Garden, countryside and weather, and Household. In a survey, 620 dog owners scored the frequency of their dog's exposure to, and thus, the recurrence of, each of the 79 sounds, from never to daily. The survey results also extended to about 25 sounds the number of acknowledged sounds that are likely to elicit stress or fear, that is, negative emotional sensitivity, in dogs. Sound recurrence and emotional sensitivity were not correlated, showing no beneficial effect of frequent exposure to, and no deleterious effect of scarcity of, sound events. We suggest that for the sake of dog welfare, researchers, veterinarians, trainers, and owners may limit dogs' exposure to the sensitive sounds identified in the study during their dog observations and dog-human interactions. A corpus of 84 sounds was collected. The sounds were spectrally analyzed by determining their F0 and 10 dB bandwidth parameters. At the lowest sound frequencies, where canine hearing is poorest, negative emotional sensitivity was generally low. At the middle and high sound center frequencies/F0s, sensitivity greatly varied from lowest to highest, which is incompatible with both the general assumption and dog auditory detection thresholds. How emotional sensitivity relates to F0 (pitch) and hearing sensitivity remains undetermined. Finally, we suggest that future behavioral audiometric studies of dogs may maximize the spectral spread of each sound while minimizing the spectral overlap between sounds so as to reduce both the testing duration and the risk of inadvertently targeting or, conversely, missing frequency-dependent hearing impairments.

Acoustic identification and classification of four dolphin species in the Brazilian marine area affected by the largest tailings dam failure disaster

Passive acoustic monitoring (PAM) is an increasingly used technique to access the occurrence, distribution, and abundance of cetaceans that may be visually unavailable most of the time. The largest tailings dam failure disaster occurred on 5 November 2015, when the Fundão dam collapsed, releasing over 50 million cubic meters of tailings into the Doce River basin; 14 days later, the tailings plume reached the Atlantic Ocean. PAM was implemented in the concerned area and cetacean species were acoustically identified. Whistles and clicks of visual and acoustic matches were used to predict and classify exclusive acoustic records through random forest models. The identified species were Guiana, rough-toothed, and bottlenose dolphins. Additionally, the franciscana, the most threatened cetacean in the western South Atlantic Ocean, was also acoustically identified. The whistle classifier had 86.9% accuracy with final frequency, duration, and maximum frequency ranked as the most important parameters. The clicks classifier had 86.7% accuracy with peak frequency and 3 dB bandwidth as the most important parameters for classifying species. Considering the potential effect of the increase in turbidity on sound transmission, such as attenuation, the presented classifier should be continuously improved with novel data collected from long-term acoustic monitoring.

Acoustic differentiation and classification of wild belugas and narwhals using echolocation clicks

Belugas (Delphinapterus leucas) and narwhals (Monodon monoceros) are highly social Arctic toothed whales with large vocal repertoires and similar acoustic profiles. Passive Acoustic Monitoring (PAM) that uses multiple hydrophones over large spatiotemporal scales has been a primary method to study their populations, particularly in response to rapid climate change and increasing underwater noise. This study marks the first acoustic comparison between wild belugas and narwhals from the same location and reveals that they can be acoustically differentiated and classified solely by echolocation clicks. Acoustic recordings were made in the pack ice of Baffin Bay, West Greenland, during 2013. Multivariate analyses and Random Forests classification models were applied to eighty-one single-species acoustic events comprised of numerous echolocation clicks. Results demonstrate a significant difference between species' acoustic parameters where beluga echolocation was distinguished by higher frequency content, evidenced by higher peak frequencies, center frequencies, and frequency minimums and maximums. Spectral peaks, troughs, and center frequencies for beluga clicks were generally > 60 kHz and narwhal clicks < 60 kHz with overlap between 40-60 kHz. Classification model predictive performance was strong with an overall correct classification rate of 97.5% for the best model. The most important predictors for species assignment were defined by peaks and notches in frequency spectra. Our results provide strong support for the use of echolocation in PAM efforts to differentiate belugas and narwhals acoustically.

The biosonar of the boto: evidence of differences among species of river dolphins (Inia spp.) from the Amazon

Echolocation clicks can reflect the anatomy of the vocalizing animal, enabling the distinction of species. River dolphins from the family Iniidae are formally represented by one species and two subspecies (Inia geoffrensis geoffrensis and I. g. humboldtiana). Additionally, two other species have been proposed (I. boliviensis and I. araguaiaensis) regarding its level of restricted distribution and morph-genetics differences. For the Committee on Taxonomy of the Society for Marine Mammalogy, the specific status of the proposed species relies on further knowledge on morphology, ecology, and genetics. Given that species-specific status is required for conservation efforts, we described and compared the echolocation clicks of Inia spp., searching for specific differences on their vocalizations. The sounds were captured with a Cetacean Research ™ C54XRS (+3/−20 dB, −185 dB re: 1V/μPa) in Guaviare River (Orinoco basin), Madeira River (Madeira basin), Xingu River (Amazon Basin), and Araguaia River (Tocantins-Araguaia basin). We found significant differences in all analyzed parameters (peak frequency, 3 dB bandwidth, 10 dB bandwidth and inter-click interval) for all species and subspecies. Differences in acoustical parameters of clicks are mainly related to the animal’s internal morphology, thus this study may potentially support with information for the species-level classification mostly of I. araguaiaensis (the Araguaian boto). Classifying the Araguaian boto separately from I. geoffrensis has important implications for the species in terms of conservation status, since it is restricted to a highly impacted river system.

Whistles of Atlantic spotted dolphin from a coastal area in the southwestern Atlantic Ocean

Atlantic spotted dolphins were recorded on the coastal area of Rio de Janeiro with equipment of 192 kHz sampling rate. The animals produced an average of 33 whistles/min. The repertoire was balanced among four contour categories, with the occurrence of a stereotyped whistle. Frequency parameters were measured between 1.3 and 29 kHz, which represents an increase in the frequency range previously reported for this species in the southwestern Atlantic Ocean. With the use of a higher sampling rate, the acoustic parameters of S. frontalis whistles have changed significantly and became more similar to those reported for North Atlantic populations.

Acoustic recordings of rough-toothed dolphin (Steno bredanensis) offshore Eastern Sicily (Mediterranean Sea)

Rough-toothed dolphin's abundance and distribution is largely unknown worldwide and evaluation of its conservation status in the Mediterranean Sea is necessary. A rough-toothed dolphin was sighted offshore Eastern Sicily (Mediterranean Sea) in July 2017 and acoustic data were acquired in the same area of Watkins, Tyack, Moore, and Notarbartolo di Sciara [(1987). Mar. Mamm. Sci. 3, 78-82]. An automatic detection algorithm was developed to identify the echolocation clicks recorded within both datasets and a recurrent inter-click interval value was identified during the new encounter. Distinctive whistle classes were also identified with similar contour shapes within both datasets.