Common dolphin whistle responses to experimental mid-frequency sonar.

Oceanic delphinids that occur in and around Navy operational areas are regularly exposed to intense military sonar broadcast within the frequency range of their hearing. However, empirically measuring the impact of sonar on the behavior of highly social, free-ranging dolphins is challenging. Additionally, baseline variability or the frequency of vocal state-switching among social oceanic dolphins during undisturbed conditions is lacking, making it difficult to attribute changes in vocal behavior to anthropogenic disturbance. Using a network of drifting acoustic buoys in controlled exposure experiments, we investigated the effects of mid-frequency (3-4 kHz) active sonar (MFAS) on whistle production in short-beaked (Delphinus delphis delphis) and long-beaked common dolphins (Delphinus delphis bairdii) in southern California. Given the complexity of acoustic behavior exhibited by these group-living animals, we conducted our response analysis over varying temporal windows (10 min- 5 s) to describe both longer-term and instantaneous changes in sound production. We found that common dolphins exhibited acute and pronounced changes in whistle rate in the 5 s following exposure to simulated Navy MFAS. This response was sustained throughout sequential MFAS exposures within experiments simulating operational conditions, suggesting that dolphins may not habituate to this disturbance. These results indicate that common dolphins exhibit brief yet clearly detectable acoustic responses to MFAS. They also highlight how variable temporal analysis windows-tuned to key aspects of baseline vocal behavior as well as experimental parameters related to MFAS exposure-enable the detection of behavioral responses. We suggest future work with oceanic delphinids explore baseline vocal rates a-priori and use information on the rate of change in vocal behavior to inform the analysis time window over which behavioral responses are measured.

Whistle repertoire and structure reflect ecotype distinction of pantropical spotted dolphins in the Eastern Tropical Pacific.

The pantropical spotted dolphin in the Eastern Tropical Pacific (ETP) is found in two genetically and phenotypically diverged ecotypes, coastal and offshore. These habitats have distinct acoustic characteristics, which can lead to the evolution of distinct acoustic communication. Whistles are sounds widely used by dolphins to mediate species and individual recognition and social interactions. Here, we study the whistle acoustic structure and repertoire diversity of offshore and coastal pantropical spotted dolphins. Our results show that there is significantly more within- and across-group variation in whistle fundamental frequency between ecotypes than between offshore groups and between coastal groups. A Random Forest classification analysis performed with an accuracy of 83.99% and identified duration, peak and minimum frequency as the most informative variables for distinguishing between ecotypes. Overall, coastal spotted dolphins produced significantly shorter whistles that were significantly lower in frequency (peak, minimum and maximum, and start and end) than offshore dolphins. Ecotypes produced whistle repertoires that were similar in diversity, but different in contour composition, with the coastal ecotype producing more upsweep whistles than offshore dolphins. The results of this study suggest that acoustic adaptations to coastal and offshore environments could be important contributors to intraspecific variation of dolphin whistle repertoires.

Effects of duty cycles on passive acoustic monitoring of southern resident killer whale (Orcinus orca) occurrence and behavior.

Long-term passive acoustic monitoring of cetaceans is frequently limited by the data storage capacity and battery life of the recording system. Duty cycles are a mechanism for subsampling during the recording process that facilitates long-term passive acoustic studies. While duty cycles are often used, there has been little investigation on the impact that this approach has on the ability to answer questions about a species' behavior and occurrence. In this study, the effects of duty cycling on the acoustic detection of southern resident killer whales (SRKW) (Orcinus orca) were investigated. Continuous acoustic data were subsampled to create 288 subsampled datasets with cycle lengths from 5 to 180 min and listening proportions from 1% to 67%. Duty cycles had little effect on the detection of the daily presence of SRKW, especially when using cycle lengths of less than an hour. However, cycle lengths of 15-30 min and listening proportions of at least 33% were required to accurately calculate durations of acoustic bouts and identify those bouts to ecotype. These results show that the optimal duty cycle depends on the scale of the research question and provide a framework for quantitative analysis of duty cycles for other marine species.

Species information in whistle frequency modulation patterns of common dolphins.

The most flexible communication systems are those of open-ended vocal learners that can acquire new signals throughout their lifetimes. While acoustic signals carry information in general voice features that affect all of an individual's vocalizations, vocal learners can also introduce novel call types to their repertoires. Delphinids are known for using such learned call types in individual recognition, but their role in other contexts is less clear. We investigated the whistles of two closely related, sympatric common dolphin species, Delphinus delphis and Delphinus bairdii, to evaluate species differences in whistle contours. Acoustic recordings of single-species groups were obtained from the Southern California Bight. We used an unsupervised neural network to categorize whistles and compared the resulting whistle types between species. Of the whistle types recorded in more than one encounter, 169 were shared between species and 60 were species-specific (32 D. delphis types, 28 D. bairdii types). Delphinus delphis used 15 whistle types with an oscillatory frequency contour while only one such type was found in D. bairdii. Given the role of vocal learning in delphinid vocalizations, we argue that these differences in whistle production are probably culturally driven and could help facilitate species recognition between Delphinus species. This article is part of the theme issue 'Vocal learning in animals and humans'.

Dolphin whistles can be useful tools in identifying units of conservation.

BACKGROUND: Prioritizing groupings of organisms or 'units' below the species level is a critical issue for conservation purposes. Several techniques encompassing different time-frames, from genetics to ecological markers, have been considered to evaluate existing biological diversity at a sufficient temporal resolution to define conservation units. Given that acoustic signals are expressions of phenotypic diversity, their analysis may provide crucial information on current differentiation patterns within species. Here, we tested whether differences previously delineated within dolphin species based on i) geographic isolation, ii) genetics regardless isolation, and iii) habitat, regardless isolation and genetics, can be detected through acoustic monitoring. Recordings collected from 104 acoustic encounters of Stenella coeruleoalba, Delphinus delphis and Tursiops truncatus in the Azores, Canary Islands, the Alboran Sea and the Western Mediterranean basin between 1996 and 2012 were analyzed. The acoustic structure of communication signals was evaluated by analyzing parameters of whistles in relation to the known genetic and habitat-driven population structure. RESULTS: Recordings from the Atlantic and Mediterranean were accurately assigned to their respective basins of origin through Discriminant Function Analysis, with a minimum 83.8% and a maximum 93.8% classification rate. A parallel pattern between divergence in acoustic features and in the genetic and ecological traits within the basins was highlighted through Random Forest analysis. Although it is not yet possible to establish a causal link between each driver and acoustic differences between basins, we showed that signal variation reflects fine-scale diversity and may be used as a proxy for recognizing discrete units. CONCLUSION: We recommend that acoustic analysis be included in assessments of delphinid population structure, together with genetics and ecological tracer analysis. This cost-efficient non-invasive method can be applied to uncover distinctiveness and local adaptation in other wide-ranging marine species.

Whistle characteristics and daytime dive behavior in pantropical spotted dolphins (Stenella attenuata) in Hawai'i measured using digital acoustic recording tags (DTAGs).

This study characterizes daytime acoustic and dive behavior of pantropical spotted dolphins (Stenella attenuata) in Hawai'i using 14.58 h of data collected from five deployments of digital acoustic recording tags (DTAG3) in 2013. For each tagged animal, the number of whistles, foraging buzzes, dive profiles, and dive statistics were calculated. Start, end, minimum, and maximum frequencies, number of inflection points and duration were measured from 746 whistles. Whistles ranged in frequency from 9.7 ± 2.8 to 19.8 ± 4.2 kHz, had a mean duration of 0.7 ± 0.5 s and a mean of 1.2 ± 1.2 inflection points. Thirteen foraging buzzes were recorded across all tags. Mean dive depth and duration were 16 ± 9 m and 1.9 ± 1.0 min, respectively. Tagged animals spent the majority of time in the upper 10 m (76.9% ± 16.1%) of the water column. Both whistle frequency characteristics and dive statistics measured here were similar to previously reported values for spotted dolphins in Hawai'i. Shallow, short dive profiles combined with few foraging buzzes provide evidence that little spotted dolphin feeding behavior occurs during daytime hours. This work represents one of the first successful DTAG3 studies of small pelagic delphinids, providing rare insights into baseline bioacoustics and dive behavior.

Patterns of Occurrence and Marine Mammal Acoustic Behavior in Relation to Navy Sonar Activity Off Jacksonville, Florida.

Passive acoustic data collected from marine autonomous recording units deployed off Jacksonville, FL (from 13 September to 8 October 2009 and 3 December 2009 to 8 January 2010), were analyzed for detection of cetaceans and Navy sonar. Cetaceans detected included Balaenoptera acutorostrata, Eubalaena glacialis, B. borealis, Physeter macrocephalus, blackfish, and delphinids. E. glacialis were detected at shallow and, somewhat unexpectedly, deep sites. P. macrocephalus were characterized by a strong diel pattern. B. acutorostrata showed the strongest relationship between sonar activity and vocal behavior. These results provide a preliminary assessment of cetacean occurrence off Jacksonville and new insights on vocal responses to sonar.

Combining whistle acoustic parameters to discriminate Mediterranean odontocetes during passive acoustic monitoring.

Acoustic observation can complement visual observation to more effectively monitor occurrence and distribution of marine mammals. For effective acoustic censuses, calibration methods must be determined by joint visual and acoustic studies. Research is still needed in the field of acoustic species identification, particularly for smaller odontocetes. From 1994 to 2012, whistles of four odontocete species were recorded in different areas of the Mediterranean Sea to determine how reliably these vocalizations can be classified to species. Recordings were attributed to species by simultaneous visual observation. The results of this study highlight that the frequency parameters, which are linked to physical features of animals, show lower variability than modulation parameters, which are likely to be more dependent on complex eco-ethological contexts. For all the studied species, minimum and maximum frequencies were linearly correlated with body size. DFA and Classification Tree Analysis (CART) show that these parameters were the most important for classifying species; however, both statistical methods highlighted the need for combining them with the number of contour minima and contour maxima for correct classification. Generally, DFA and CART results reflected both phylogenetic distance (especially for common and striped dolphins) and the size of the species.

Passive acoustic monitoring of Cook Inlet beluga whales (Delphinapterus leucas).

The endangered beluga whale (Delphinapterus leucas) population in Cook Inlet, AK faces threats from a variety of anthropogenic factors, including coastal development, oil and gas exploration, vessel traffic, and military activities. To address existing gaps in understanding about the occurrence of belugas in Cook Inlet, a project was developed to use passive acoustic monitoring to document the year-round distribution of belugas, as well as killer whales (Orcinus orca), which prey on belugas. Beginning in June 2009, ten moorings were deployed throughout the Inlet and refurbished every two to eight months. Despite challenging conditions consisting of strong tidal currents carrying debris and seasonal ice cover, 83% of mooring deployments were successfully recovered. Noise from water flow, vessel traffic, and/or industrial activities was present at several sites, potentially masking some signals. However, belugas were successfully detected at multiple locations. Detections were relatively common in the upper inlet and less common or absent at middle and lower inlet locations. Killer whale signals were also recorded. Some seasonal variability in the occurrence of both belugas and killer whales was evident.

A non-spectrogram-correlation method of automatically detecting minke whale boings.

This letter introduces an algorithm for automatic detection of minke whale boing sounds. This method searches for frequency features of boings without calculating the continuous spectrogram of the data, thereby reducing computational time. The detector has been tested on 8 h of acoustic data recorded at the Station ALOHA Cabled Observatory in March 2007. This dataset was previously analyzed using the cross-correlation detector of XBAT and was verified by a human listener, as reported in Oswald et al. [(2011). J. Acoust. Soc. Am. 129, 3353-3360]. A comparison of results indicates that the detector introduced here generates fewer false alarms, and it recognizes low-SNR calls that are missed by XBAT.

Minke whale (Balaenoptera acutorostrata) boings detected at the Station ALOHA Cabled Observatory.

Minke whales (Balaenoptera acutorostrata) in the tropical North Pacific are elusive and difficult to detect visually. The recent association of a unique sound called the "boing" to North Pacific minke whales has made it possible to use passive acoustics to investigate the occurrence of this species in Hawaiian waters. One year of recordings (17 February 2007-18 February 2008) made at the Station ALOHA Cabled Observatory were examined to investigate the characteristics of boings and temporal patterns in their occurrence at this site, located 100 km north of Oahu. Characteristics of boings exhibited low variability. Pulse repetition rate and duration measurements matched those for "central" or "Hawaii" boing types. Boings were detected from October until May, with a peak in March. Although no boings were detected from June to September, the absence of boings does not necessarily indicate the absence of minke whales. Significant diel variation in boing rate was not observed. The absence of a diel pattern in boing production suggests that day- or night-time acoustic surveys are equally acceptable methods for studying minke whale occurrence. Future research should include efforts to determine what other sounds are produced by minke whales in this area, and which age/sex classes produce boings.

A tool for real-time acoustic species identification of delphinid whistles.

The ability to identify delphinid vocalizations to species in real-time would be an asset during shipboard surveys. An automated system, Real-time Odontocete Call Classification Algorithm (ROCCA), is being developed to allow real-time acoustic species identification in the field. This Matlab-based tool automatically extracts ten variables (beginning, end, minimum and maximum frequencies, duration, slope of the beginning and end sweep, number of inflection points, number of steps, and presence/absence of harmonics) from whistles selected from a real-time scrolling spectrograph (ISHMAEL). It uses classification and regression tree analysis (CART) and discriminant function analysis (DFA) to identify whistles to species. Schools are classified based on running tallies of individual whistle classifications. Overall, 46% of schools were correctly classified for seven species and one genus (Tursiops truncatus, Stenella attenuata, S. longirostris, S. coeruleoalba, Steno bredanensis, Delphinus species, Pseudorca crassidens, and Globicephala macrorhynchus), with correct classification as high as 80% for some species. If classification success can be increased, this tool will provide a method for identifying schools that are difficult to approach and observe, will allow species distribution data to be collected when visual efforts are compromised, and will reduce the time necessary for post-cruise data analysis.

The effect of recording and analysis bandwidth on acoustic identification of delphinid species.

Because many cetacean species produce characteristic calls that propagate well under water, acoustic techniques can be used to detect and identify them. The ability to identify cetaceans to species using acoustic methods varies and may be affected by recording and analysis bandwidth. To examine the effect of bandwidth on species identification, whistles were recorded from four delphinid species (Delphinus delphis, Stenella attenuata, S. coeruleoalba, and S. longirostris) in the eastern tropical Pacific ocean. Four spectrograms, each with a different upper frequency limit (20, 24, 30, and 40 kHz), were created for each whistle (n = 484). Eight variables (beginning, ending, minimum, and maximum frequency; duration; number of inflection points; number of steps; and presence/absence of harmonics) were measured from the fundamental frequency of each whistle. The whistle repertoires of all four species contained fundamental frequencies extending above 20 kHz. Overall correct classification using discriminant function analysis ranged from 30% for the 20-kHz upper frequency limit data to 37% for the 40-kHz upper frequency limit data. For the four species included in this study, an upper bandwidth limit of at least 24 kHz is required for an accurate representation of fundamental whistle contours.