Vocal signatures affected by population identity and environmental sound levels

Passive acoustic monitoring has improved our understanding of vocalizing organisms in remote habitats and during all weather conditions. Many vocally active species are highly mobile, and their populations overlap. However, distinct vocalizations allow the tracking and discrimination of individuals or populations. Using signature whistles, the individually distinct calls of bottlenose dolphins, we calculated a minimum abundance of individuals, characterized and compared signature whistles from five locations, and determined reoccurrences of individuals throughout the Mid-Atlantic Bight and Chesapeake Bay, USA. We identified 1,888 signature whistles in which the duration, number of extrema, start, end, and minimum frequencies of signature whistles varied significantly by site. All characteristics of signature whistles were deemed important for determining from which site the whistle originated and due to the distinct signature whistle characteristics and lack of spatial mixing of the dolphins detected at the Offshore site, we suspect that these dolphins are of a different population than those at the Coastal and Bay sites. Signature whistles were also found to be shorter when sound levels were higher. Using only the passively recorded vocalizations of this marine top predator, we obtained information about its population and how it is affected by ambient sound levels, which will increase as offshore wind energy is developed. In this rapidly developing area, these calls offer critical management insights for this protected species.

First acoustic evidence of signature whistle production by spinner dolphins (Stenella longirostris)

A dolphin's signature whistle (SW) is a distinctive acoustic signal, issued in a bout pattern of unique frequency modulation contours; it allows individuals belonging to a given group to recognize each other and, consequently, to maintain contact and cohesion. The current study is the first scientific evidence that spinner dolphins (Stenella longirostris) produce SWs. Acoustic data were recorded at a shallow rest bay called "Biboca", in Fernando de Noronha Archipelago, Brazil. In total, 1902 whistles were analyzed; 40% (753/1,902) of them were classified as stereotyped whistles (STW). Based on the SIGID method, 63% (472/753) of all STWs were identified as SWs; subsequently, they were categorized into one of 18 SW types. SWs accounted for 25% (472/1,902) of the acoustic repertoire. External observers have shown near perfect agreement to classify whistles into the adopted SW categorization. Most acoustic and temporal variables measured for SWs showed mean values similar to those recorded in other studies with spinner dolphins, whose authors did not differentiate SWs from non-SWs. Principal component analysis has explained 78% of total SW variance, and it emphasized the relevance of shape/contour and frequency variables to SW variance. This scientific discovery helps improving bioacoustics knowledge about the investigated species. Future studies to be conducted in Fernando de Noronha Archipelago should focus on continuous investigations about SW development and use by S. longirostris, expanding individuals' identifications (Photo ID and SW Noronha Catalog), assessing long-term whistle stability and emission rates, and making mother-offspring comparisons with sex-based differences.

Variation in foraging activity influences area-restricted search behaviour by bottlenose dolphins

Area-restricted search (ARS) behaviour is commonly used to characterize spatio-temporal variation in foraging activity of predators, but evidence of the drivers underlying this behaviour in marine systems is sparse. Advances in underwater sound recording techniques and automated processing of acoustic data now provide opportunities to investigate these questions where species use different vocalizations when encountering prey. Here, we used passive acoustics to investigate drivers of ARS behaviour in a population of dolphins and determined if residency in key foraging areas increased following encounters with prey. Analyses were based on two independent proxies of foraging: echolocation buzzes (widely used as foraging proxies) and bray calls (vocalizations linked to salmon predation attempts). Echolocation buzzes were extracted from echolocation data loggers and bray calls from broadband recordings by a convolutional neural network. We found a strong positive relationship between the duration of encounters and the frequency of both foraging proxies, supporting the theory that bottlenose dolphins engage in ARS behaviour in response to higher prey encounter rates. This study provides empirical evidence for one driver of ARS behaviour and demonstrates the potential for applying passive acoustic monitoring in combination with deep learning-based techniques to investigate the behaviour of vocal animals.

A simple tool for linking photo-identification with multimedia data to track mammal behaviour

Identifying individual animals is critical to describe demographic and behavioural patterns, and to investigate the ecological and evolutionary underpinnings of these patterns. The traditional non-invasive method of individual identification in mammals—comparison of photographed natural marks—has been improved by coupling other sampling methods, such as recording overhead video, audio and other multimedia data. However, aligning, linking and syncing these multimedia data streams are persistent challenges. Here, we provide computational tools to streamline the integration of multiple techniques to identify individual free-ranging mammals when tracking their behaviour in the wild. We developed an open-source R package for organizing multimedia data and for simplifying their processing a posteriori—“MAMMals: Managing Animal MultiMedia: Align, Link, Sync”. The package contains functions to (i) align and link the individual data from photographs to videos, audio recordings and other text data sources (e.g. GPS locations) from which metadata can be accessed; and (ii) synchronize and extract the useful multimedia (e.g. videos with audios) containing photo-identified individuals. To illustrate how these tools can facilitate linking photo-identification and video behavioural sampling in situ, we simultaneously collected photos and videos of bottlenose dolphins using off-the-shelf cameras and drones, then merged these data to track the foraging behaviour of individuals and groups. We hope our simple tools encourage future work that extend and generalize the links between multiple sampling platforms of free-ranging mammals, thereby improving the raw material needed for generating new insights in mammalian population and behavioural ecology.

First characterization of vocalizations and passive acoustic monitoring of the vulnerable African manatee (Trichechus senegalensis)

Even among the understudied sirenians, African manatees (Trichechus senegalensis) are a poorly understood, elusive, and vulnerable species that is difficult to detect. We used passive acoustic monitoring in the first effort to acoustically detect African manatees and provide the first characterization of their vocalizations. Within two 3-day periods at Lake Ossa, Cameroon, at least 3367 individual African manatee vocalizations were detected such that most vocalizations were detected in the middle of the night and at dusk. Call characteristics such as fundamental frequency, duration, harmonics, subharmonics, and emphasized band were characterized for 289 high-quality tonal vocalizations with a minimum signal-to-noise ratio of 4.5 dB. African manatee vocalizations have a fundamental frequency of 4.65 ± 0.700 kHz (mean ± SD), duration of 0.181 ± 0.069 s, 97% contained harmonics, 21% contained subharmonics, and 27% had an emphasized band other than the fundamental frequency. Altogether, the structure of African manatee vocalizations is similar to other manatee species. We suggest utilizing passive acoustic monitoring to fill in the gaps in understanding the distribution and biology of African manatees.