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There are between 67 and 76 species of odontocetes (toothed whales) and presumably all have biosonar capabilites. There are three fundamental biosonar signal types that can be categorized by types of marine mammals that produce these signals. Whales and dolphins that can emit whistle signals (except for sperm whales) project short broadband clicks containing about 5 to 7 cycles with decaying exponential envelope and Q (center frequency over bandwidth) between 2 and 3. Porpoises do not whistle and produce polycyclic narrow band high frequency biosonar signals with approximately 20 or more cycles with a modified sinusoidal amplitude envelope and Q around 14. Biosonar waveforms of beaked whales (also non-whistling animals) typically have 10-15 cycles with a linear FM component and Q around 4. This presentation will discuss the characteristics of the three different biosonar signal types and suggest some motivation factors involved with the use of the different signals. The type of prey and their habitat will also be included in the discussion. It will be shown that in some cases, the signal type is motivated by anatomical constraints of the odontocete and in other cases, the backscatter characteristics of the prey may be the most important factor.

Humpback whale song research has focused on analyzing the full song structure rarely describing individual song units. Even less progress has been made in automatically distinguishing and classifying these individual units. Two different techniques were employed to study their call units, visual/aural and automated/statistical. Humpback whale songs were recorded in the Hawaiian Islands both remotely with an autonomous acoustic recorder and by a snorkeler with a portable digital tape recorder. Humpback whale song units collected by the autonomous acoustic recorders were aurally separated into 23 distinct units in a companion study. Song units collected by a snorkeler using the portable recorder off Maui were analyzed using a specialized Matlab script that defined 48 frequency and temporal parameters for each unit. From the 48 parameters, the units were separated into distinct categories using a multivariate categorical analysis. The distinct units were compared between the different techniques to gage if a...

Spinner dolphins (Stenella longirostris) in the near-shore waters of the Hawaiian islands forage on the mesopelagic boundary community (mbc) of organisms consisting of myctophids, mid-water shrimp and small squids. They forage at night and supposedly in a coordinated fashion and in groups between 16 and 24 animals that are divided into pairs. In the search phase of the foraging process, the dolphins are thought to be spaced in a V-shape formation with the tip of the “V” at the deepest depth, and swim parallel to shore hunting for patches of prey that they can encircle and herd into a tight three-dimensional patch. A profiler housing a broadband echo-ranger that projected dolphin-like biosonar signals was used to measure the target strength of the mbc based on a dolphin's integration window of 264 μs. The bottlenose dolphin, Tursiops truncatus, was used as a proxy to estimate the biosonar detection ranges of Stenella longirostris searching for mbc patches because only limited acoustic research has been per...

One of the strengths of the Acoustical Society of America (ASA) is the multi-disciplinary aspects of the society. Engineers, physicists, mathematicians, biologists, psychologists, physiologists, and speech researchers plus others are part of our society. The ASA can be broadly divided into two groups, those in the physical sciences and those in the life or natural sciences with signal processing bridging both groups. JASA reflects this diversity. Manuscripts by those in the physical sciences depend heavily on mathematical and physical modeling and various types of equations, while in the natural sciences spectrograms, various types of statistics and hypotheses testing are often used. Nevertheless, certain factors with regard to quality must be met by all authors. The articles should contribute new knowledge, be written in English and be grammatically correct. The approach or methodology must be sound. The results should be clearly presented whether in tables, graphs or in verbiage. Finally, the discussion...

The capability of an echolocating dolphin to discriminate differences in the wall thickness of cylinders (3.81 cm o.d. and 12.7 cm length) was determined by Au and Pawloski [J. Comp. Physiol. A 170, 41–47 (1992)]. The dolphin was required to discriminate a standard target from comparison targets of differing wall thicknesses. Performance varied from 96% to 56% correct depending on the wall thickness of the comparison targets. The 75% correct threshold was determined to be wall thickness differences of −0.23 mm for comparison targets with thinner walls and +0.27 mm for comparison targets with thicker walls than the standard. The dolphin performance was unchanged in the presence of artificial broadband masking noise until the echo‐energy‐to‐noise ratio fell below approximately 15 dB. A counterpropagation artificial neural network was used to examine broadband echo features from the same cylinders. Features of the echoes were determined by passing them through a filter bank of constant‐Q filters. Echo features of the standard and each comparison target were analyzed in pairs by a neural network having two output nodes. Twenty echoes per target were used in the training set and 30 additional echoes per target were used in the test set. For the noise free condition, the network performed at a comparable level to the dolphin for Q values between 4 and 5. In the presence of noise, Q values between 7 and 8 were needed before the network could perform at a comparable level to the dolphin for echo‐energy‐to‐noise ratios of 10 and 15 dB. Discrimination cues seem to originate from a shift in the spectra of the thinner comparison targets to lower frequencies and to higher frequencies for the thicker comparison targets.

Monitoring the changing state of marine habitats in remote areas is, in most cases, a challenging task due to limited and/or infrequent opportunities to make direct observations. Passive acoustic monitoring is sometimes the best means of establishing long-term biological trends in such areas. Since 2006, an effort has been underway to monitor the neashore ecosystems of the Northwestern Hawaiian Islands (NWHI) using a network of Ecological Acoustic Recorders. A wide range of acoustic signals are being monitored to infer biological trends and to gauge the relative stability of the ecosystem. Among the variables measured are the acoustic activity of snapping shrimp, the incidence of cetaceans and the extent of spectral and temporal partitioning of the acoustic space by different taxa, measured as the “acoustic entropy” of the habitat. Multiyear time series of the different measures provide baseline levels of biological activity at each location and also reveal periods of anomaly. Observed trends are then exa...

Ecological acoustic recorders (EARs) were deployed in deep waters at five locations around the island of Kauai and one in waters off Ni'ihau in the main Hawaiian island chain. The EARs were moored to the bottom at depths between 400 and 800 m. The data acquisition sampling rate was 80 kHz and acoustic signals were recorded for 30 s every 5 min to conserve battery power and disk space. The acoustic data were analyzed using a suite of software including the M3R (marine mammal monitoring on navy ranges) algorithm, an energy-ratio-mapping algorithm developed at Oregon State University, Triton software developed at Scripps Institute of Oceanography, and custom Matlab programs. A variety of deep diving odontocetes, including pilot whales, Risso's dolphins, sperm whales, spinner and pan-tropical spotted dolphins, and beaked whales were detected at all sites. Foraging activity typically began to increase after dusk, peaked in the middle of the night, and began to decrease toward dawn. Between 75 and 87% of bioson...

Spinner dolphins in the near-shore waters of the Hawaiian islands forage on a mesopelagic boundary community of organisms consisting of myctophids, mid-water shrimps, and small squids. To better understand the foraging ecology of spinner dolphins, it is important to understand the relationship between volume scattering coefficient (Sv) obtained with an echosounder and the density of the organisms in the mesopelagic boundary community. A suite of Simrad Ek-60 scientific echosounders operating at 38, 72, 120, and 200 kHz directed vertically downward was used to collect volume backscatter data from a vessel anchored 1 km from shore. Sv tended to be highest at 38 kHz and lowest at 200 kHz, although at some depths Sv at 70 kHz was slight higher than at 38 kHz data. Immediately after collecting the echosounding data, a profiler with a broadband high-resolution echo ranger projecting a simulated dolphin biosonar signal horizontally was lowered into the same volume examined by the EK-60. The number of organism in the echoranger beam out to a specified range was estimated by counting the number of highlights in the echoes after performing an envelope detection. The relationship between Sv and number of organisms was found to be linearly related.

Humpback whales produce songs which consist of a sequence of short, continuous sounds known as units. This paper introduces an automated algorithm to extract the unit contours. An unsupervised classification is developed to provide a set of distinct units of the singing group. The analysis is performed on the vocalization spectrograms, which are normalized and interpolated into a squared time-frequency image. Unit contours are detected using two edge detection filters capturing sharp changes in the image intensities. The algorithm generates a group of rectangular image segments each containing a single contour unit, with the pixels outside the contour edge lines set to zero. The contours are compared with one another to identify distinct units. The comparison is quantified using parameters including the contour pixel intensity correlation, contour area, frequency range, and frequency of the peak pixel. A pairwise comparison provides a coarse division of classes, where each class is then represented by a candidate unit. The candidate units are compared with one another, and the ones with low similarity are advanced to the final set. The algorithm has been tested on humpback whale songs obtained during the winter season in Hawaiian waters in 2002 and 2003.

Parrotfishes (family Scaridae) are an important component of coral reef ecosystems, and this key functional group plays a major role in algae removal and bioerosion of reef substrate. They are also heavily fished in many locations, which may lead to ecosystem-wide impacts such as increased algal cover. In the State of Hawaii, parrotfish management is a priority for marine resource managers, with an ongoing need for accurate population monitoring that is currently addressed by diver-based visual surveys. However, parrotfishes are highly mobile and somewhat skittish around SCUBA divers, particularly in areas where fishing pressure is high. Because parrotfishes produce frequent audible scraping and crunching sounds associated with feeding, passive acoustic monitoring (PAM) can provide information on parrotfish occurrence without requiring the invasive presence of divers. Here, we present results from analyses of parrotfish foraging sounds in long-term acoustic recordings from 10 shallow reef locations throughout the Hawaiian Archipelago dating back to 2006. Parrotfish sounds are compared spatially across a fishing pressure gradient, from heavily fished areas in the main Hawaiian Islands to protected waters within the Papahānaumokuākea Marine National Monument (Northwestern Hawaiian Islands). Results from PAM are compared when possible with data from adjacent visual censuses conducted by divers.

The acoustic behavior of animals living at the edge or below the photic zone is poorly documented. Limited opportunities to make recordings and/or behavioral observations in deep water environments have resulted in a paucity of information about sound production by animals living at depth. Here we report on an effort begun in 2006 to acoustically monitor deep reef environments off Oahu, HI. Ecological acoustic recorders (EARs) were deployed along the perimeter of the island and along the slope of a nearby bank at depths ranging between 115 and 575 m. At several locations, one of the predominant sounds recorded was a chorus of pulsed signals centered at approximately 4 kHz timed closely with the period following sunset. The duration of the chorus varies between 1 and 10 h in length and is tied to the lunar cycle. The chorus is seasonal, beginning in late December and ending in early June. This period corresponds closely with the seasonal presence of humpback whales (Megaptera novaeangliae) in Hawaii. The source of the chorus is presently still unknown, but being investigated using a combination of passive and active acoustic methods.

An extensive study of the population structure of North Pacific humpback whales (SPLASH) has revealed that many of the whales feeding in the Aleutian Islands and the Bering Sea are not observed in known wintering and breeding areas in the Pacific. Recent findings suggest that the Northwestern Hawaiian Islands (NWHIs) represent a previously undocumented wintering area that may be distinct from the Main Hawaiian Islands’ (MHIs’) wintering ground. To examine this issue further, data from Ecological Acoustic Recorders (EARs) deployed at five locations in the NWHIs and MHIs were analyzed to compare the structure of songs produced by whales in both areas. Previous research suggests that songs from different breeding groups differ from one another, providing a method to evaluate whether whales in the NWHIs are part of the same breeding group as those in the MHIs. Recordings from each site were randomly selected, and song units were classified and counted to compare between sites. Preliminary results indicate that there are differences between the NWHIs and MHIs. These findings suggest that further work using photo ID should be undertaken to confirm whether whales in the NWHIs are indeed those feeding in the Aleutians and the Bering Sea.

Acoustic identification of delphinid species is hampered by high variability in whistle characteristics. It is possible that not every whistle contains species‐specific information and that there are “species‐specific” whistle types. Random forest analysis was used to examine whistles of 8 species recorded in the eastern tropical Pacific Ocean (Delphinus species, Globicephala macrorhynchus, Pseudorca crassidens, Stenella attenuata, S. coeruleoalba, S. longirostris, Steno bredanensis, Tursiops truncatus). Fifty‐one variables were measured from 2176 whistles. The number of trees within a random forest that “voted” for the predicted species was used as a measure of the strength of classification. A whistle was considered strongly classified if the predicted species received at least 40% of the votes, even if the prediction was incorrect. The percent of whistles that were strongly classified ranged from 33% (S. longirostris) to 73% (G. macrorhynchus). Overall, 62% of strong whistles were correctly classified, ranging from 22% (S. longirostris) to 87% (P. crassidens). Overall correct classification for weakly classified whistles was 33% and ranged from 17% (Delphinus spp. and G. macrorhynchus) to 55% (S. bredanensis). Results suggest that while there may be “species‐specific” whistle types, the distinctiveness of these whistles and the frequency with which they are produced varies among species.

Real‐time odontocete call classification algorithm (ROCCA) is a tool for real‐time acoustic species identification of delphinid whistles. Introduced in 2006 as MATLAB‐based software, ROCCA is currently being incorporated into PAMGUARD, a freely‐available, open source software package. ROCCA provides automated extraction of whistle contours from a spectrogram. It measures 54 whistle contour features including frequencies, slopes, duration, and variables related to the positions of inflection points and steps. ROCCA currently classifies whistles of seven species and one genus: Globicephala macrorhynchus, Pseudorca crassidens, Steno bredanensis, Stenella attenuata, S. coeruleoalba, S. longirostris, Tursiops truncatus, and Delphinus species. The classifier is a Random Forest trained on 2231 whistles collected over six cruises and 7 years in the eastern tropical Pacific Ocean. The original ROCCA classifier used a combination of discriminant function analysis and CART algorithms on 13 whistle contour features for an overall correct classification score of 35%, which was significantly greater than random (12%). The current Random Forest scheme, trained on 54 whistle contour features, yields an overall correct classification score of 62%. Feedback from at‐sea beta testing has been incorporated into the latest version of ROCCA. Additional species, automated detection, and alternate classification schemes are being explored to extend ROCCA into different geographic areas with greater accuracy.

In the past years, the development of a variety of passive acoustics recorders has provided a unique way of acquiring information about marine mammal species in remote regions of the ocean. During the NATO Undersea Research Centre Sirena 10 cruise an ecological acoustic recorder (EAR) was deployed to monitor the presence of marine mammal. The EAR was deployed on May 13, 2010 at a depth of 944 m in the vicinity of Josephine seamount (37 deg; 02.087’N, 013¢a 51.733W, south west Portugal) and programed for a recording time of 40 s every 2 min. For the detection and classification of echolocation clicks we integrated the visual analysis of spectrograms with the analysis performed by an automatic detector/classification system called M3R, developed by the Naval Undersea Warfare Center Division. M3R has been successfully operated for the analysis of recording from different US Navy ranges. Cetaceans detected include beaked whales, sperm whales, pilot whales, risso’s dolphins, and dolphins. Hourly and daily distributions of signals were calculated. Beaked whales have been regularly detected everyday and the echolocation activity has been found to be higher at night. This suggests that Josephine seamount represents a good habitat for these deep diving cetaceans. [NATO Undersea Res. Ctr. funded and operated the sea trial Sirena 10.]

The seasonal occurrence and distribution of cetaceans around island archipelagos is often poorly understood. This is generally due to the variability in sea surface conditions associated with islands, which make visual surveys prohibitive along exposed areas and/or during seasonal periods of rough seas. Historically, this has been the case for many cetacean species found in Hawaiian waters. Recently, however, concerns about the impacts of anthropogenic activities have created a need to better understand the long‐term, spatial and temporal distributions of cetaceans in the archipelago. To meet this need, an effort was begun in February 2009 to study cetacean occurrence around the island of Oahu using a network of passive acoustic recorders. Five ecological acoustic recorders (EARs) were deployed in waters 115–575 m deep along the perimeter of the island and refurbished approximately every 4 months. Data from these deployments are providing an unprecedented perspective on the occurrence of both odontocete and mysticete cetaceans around the island. The southeastern corner of Oahu, in particular, has emerged as a hotspot of odontocetes; diversity and abundance. This and two other sites being monitored have historically received little or no visual survey attention, but are clearly important habitats for a variety of species.

A man-made sonar system can be subdivided into three major subsystems, the receiving, transmitting, and signal processing/decision subsystems. The capabilities of a sonar are dependent on the integrated, interdependent functioning of the three major subsystems. Each subsystem contributes in a specific, but different, manner to the functioning of the total unit. There is no priority of importance assigned to any subsystem; only the capability of the total sonar system can be evaluated. The dolphin sonar system can also be subdivided into the same three major components, and here as well the understanding of each subsystem is equally important in understanding the total unit. In this chapter the receiving system will be studied and its characteristics discussed.

The sonar task for dolphins perceiving their environment involves detection, localization, discrimination, and recognition of objects of interest. Target information such as range, azimuth, direction of movement, speed, and size should also be of interest. The ability of dolphins to accurately perceive their environment and to perform difficult recognition and discrimination tasks depends to a large extent on the characteristics of their sonar signals and how these signals are emitted. The signals must have sufficient energy to detect small targets at large ranges. They must also have sufficient information-carrying capacity so that fine features and characteristics of objects and targets can be determined by analyzing their sonar echoes. At a minimum, a dolphin sonar system should be able to detect and recognize prey, obstacles, and predators. The sonar task is usually performed in a noisy or highly reverberant environment associated with shallow waters, or during searches near the bottom or in the presence of many obstacles.

One of the outstanding characteristics of the dolphin sonar system which distinguishes it from any man-made sonar is the ability to make fine distinctions in the features or properties of targets. This ability has amazed and sparked the interest of many involved in the development and use of active sonar systems. The abilities to perform fine target discrimination, recognition, and classification are often considered synonymous; however, there are subtle differences between these functions. Target discrimination means the ability to discern from their echoes that two targets are different. Target recognition means the ability to recognize features of the echoes from specific targets compared with echoes from any other targets; it involves a discrimination capability, an ability to recall from memory the echo features of specific targets, and the ability to compare present sonar echoes with those stored in memory. Target classification means the ability to separate targets into different classes according to some arbitrary criteria such as metal versus nonmetal, organic versus inorganic, edible versus inedible, smooth surface versus rough surface, etc. Most of the experiments discussed in this chapter involve target discrimination; a few involve target recognition.

The dolphin must have a fairly general and flexible sonar system in order to maximize its survival. Since acoustic energy propagates in water more efficiently than almost any other form of energy, a good passive and active sonar system is ideal for the aquatic environment. In order to have good passive and active sonar capabilities, the receiving system of the dolphin should have certain important characteristics. The receiver should be very sensitive over a wide frequency range to detect minute echoes and externally generated sounds. It should also be sensitive in both quiet and noisy environments and should be able to detect short and long duration sounds. A good spectral analysis capability, including frequency discrimination, is important in identifying and recognizing predators, prey, and other objects in the environment. Other important characteristics of a good sonar receiver include the capability to (a) spatially resolve and localize sounds, (b) reject externally generated interferences, and (c) recognize temporal and spectral patterns of sounds. In this chapter, these characteristics of the dolphin’s receiving system will be examined.

As sonar signals propagate out of the dolphin’s head, a definite acoustic field is formed that is governed by the size of the animal’s head, the peak frequency of the signals, the area of the sound production mechanism, and the amount of focusing within the melon and at the melon-water interface. The acoustic near field will form in the vicinity of the dolphin’s head as it would near the transmitting surface of any energy radiator. The concept of a near field is often difficult to grasp since many explanations are embroiled in mathematics that seem to confuse rather than clarify the issue. In this section, a simple model will be used to discuss the notion of the near and far acoustic field of a radiator and to provide insights into the physics involved with the propagation of acoustic energy from a dolphin’s head.

Another animal that possesses a sophisticated and highly developed sonar is the bat. A considerable amount of research is being performed on the auditory system of bats, much more than on dolphins. A conservative estimate would indicate that there are approximately three to four times more scientists involved with bat sonar and auditory research than with dolphins. There are many reasons for this imbalance; most are related to the high cost associated with a dolphin research facility. The expense of constructing a facility having large tanks filled with high-quality salt water, or installing a facility that includes animal holding pens and laboratories in an isolated but readily accessible lagoon, can be quite high. In comparison, a cage to house a colony of bats can be easily and inexpensively constructed and located in most laboratories even though bats require good control of room temperature and humidity.

We will now begin to examine another major subsystem of the dolphin sonar, the signal transmission system. In this chapter we will first discuss the general characteristics of sonar signals used by odontocetes, both in open waters and in enclosed tanks, in order to gain an appreciation of the wide variety of signals that are used. The topic of biosonar (biological sonar) signals will be briefly covered in this chapter, mainly as a prelude to the subject of sound production mechanisms. Characteristics of dolphin sonar signals will be more thoroughly discussed in Chapter 7. Although we are generally concerned with sonar signals used by dolphins, we need to pay some attention to other types of acoustic signals they produce. Bottlenose and other dolphins emit a wide variety of sounds not used for active sonar searches. Sound emissions can be classified into two broad categories of narrow-band frequency-modulated (FM) continuous tonal sounds referred to as whistles and broadband sonar clicks (Evans 1967). Whistles appear to be used for intraspecific communications (Herman and Tavolga 1980). These sounds are generally low frequency emissions between 5 and 30 kHz and may last for several seconds. They are often referred to as squeaks, squawks, and squeals, as well as whistles.

In this chapter, we will begin to examine the active sonar capabilities of dolphins by considering their target detection capabilities. However, it will be helpful to first take a short excursion and consider the reflection of acoustic energy by underwater targets and the application of the sonar equation to dolphin target detection. The subject of acoustic scattering by targets under water is an extremely complicated one, with physical processes often described by extremely complex mathematical functions and operations. This topic has been the subject of much research since the end of World War II. A good review of some of the modem research on acoustic scattering has been written by Neubauer (1986). Even after much intensive research, only problems involving simple geometrical shapes such as spheres, cylinders, spheroids, and plates are well understood and have lent themselves to some form of analytical solution. In the next section we will examine the acoustic backscatter from spheres and cylinders in order to gain an appreciation of the complex nature of echoes from targets.

Many different types of target discrimination experiments have been performed with echolocating dolphins in order to understand and model their echolocation capabilities. However, not many experiments have been performed that measured differential performance as a function of the magnitude of a single target variable, thus making it very difficult to extract limits of various auditory discrimination capabilities. Nevertheless, sufficient information exists that could provide some insight on important echo cues utilized by dolphins and what the signal processing may be. Furthermore, other types of experiments emulating some dolphin experiments have also been conducted. Stretched versions of echoes from target used in dolphin experiments have been used in human listening experiments to determine salient cues present in the echoes. Neural network experiments have also been conducted using echoes from the same target used in the dolphin experiments. The most pertinent of these experiments involving dolphins, humans, and neural networks will be discussed in order to gain insight into important target cues and the manner in which these cues might be processed by echolocating dolphins. The discussion will be conducted in light of the results of a recent experiment in which the auditory filter shape of a dolphin for different frequencies was determined.

We used the experimental setup designed to simulate ultrasound transmission and binaural reception by dolphins at the Marine Mammals Research Program. Three composite piezoelectric transducers, located in the same plane, were placed at the corners of a triangle such that a distance of 14 cm separates the two receivers. This approximates the presumed spacing between the dolphin sound entrances. The two receiving channels approximate those of dolphins (e.g., similar spectral responses, different receiving patterns between the two receptors). Transmitted signals were similar to dolphin clicks and echoes were recorded simultaneously at the two receivers and digitized at 1 MHz using two data acquisition boards housed in a portable computer. We sought to identify different targets in these preliminary experiments: a 3‐in. stainless steel spherical shell filled with water and two copper cylindrical shells with outer diameters equal to 1.63 and 1 in., respectively. The last two samples have the same thickness (1/16 in.) and are filled either with water or with air. The scattered signals are processed via a simple Fourier transform and analyzed using the resonance scattering theory. A preliminary study of the results is presented.

The use of remote autonomous passive acoustic recorders (PARs) to determine the distribution of dolphins at given locations has become very popular. Some investigators are using echolocation clicks to gather information on the presence of dolphins and to identify species. However, in all of these cases, the PAR probably recorded mainly off‐axis clicks, even some from behind the animals. Yet we have a very poor understanding of the beam pattern and the click waveform and spectrum from different azimuths around the animal’s body. The beam pattern completely around an echolocating dolphin was measured at 16 different but equally spaced angles in the horizontal plane using an 8‐hydrophone array in sequence. Eight channels of data were digitized simultaneously at a sampling rate of 500 kHz. The resulting beam patterns in both planes showed a continuous drop off in sound pressure with azimuth around the animal and reached levels below −50 dB relative to the signal recorded on the beam axis. The signals began to...

The North Pacific right whale (Eubalaena japonica) is one of the most endangered baleen whales in the world, with current abundance estimates of fewer than 40 individuals. As such, it has been the focus of intensive population monitoring studies. Long‐term passive acoustic monitoring is a useful tool for assessing distribution, habitat use, and population status of marine mammals. For Bering Sea right whales, past analyses of distribution were based on their stereotyped upsweep call. Results from sonobuoy recordings made during the 2008 and 2009 southeastern Bering Sea right whale cruises, however, found gunshot calls to be much more common. To assess whether inclusion of gunshot call detections will change our understanding of the spatial and temporal distribution of North Pacific right whales, we examined four years (2006–2009) of long‐term recordings made by the National Marine Mammal Laboratory and the Pacific Marine Environmental Laboratory at six different locations on the Bering Sea shelf. A compar...

In the past decade, the use of autonomous remote passive acoustic recorders to detect the presence of cetaceans has grown enormously throughout the world. Since these devices digitize acoustic signals at sampling rates in the tens of kHz, a single device can quickly accumulate many Gbytes of data in a short time. Therefore, automatic detection and recognition algorithms must be developed to handle the large amount of data. There is no general signal method processing method that can be applied to all species of cetacean. The algorithm by the name of ROCCA (real‐time odontocete call classification algorithm) developed by Dr. Julie Oswald is probably the most general one that has been applied to the whistles of dolphins. The program, extensible bio acoustics tool (XBAT) developed by Harold Figueroa, is probably the most general tool for use with baleen whales. However, investigators also tend to develop their own algorithms to suit their requirements. The problems and difficulties in developing automatic de...

Arrays of up to six broadband suction cup hydrophones were placed on the forehead of two bottlenose dolphins to determine the location where the beam axis emerges and to examine how signals in the acoustic near-field relate to signals in the far-field. Four different array geometries were used; a linear one with hydrophones arranged along the midline of the forehead, and two around the front of the melon at 1.4 and 4.2 cm above the rostrum insertion, and one across the melon in certain locations not measured by other configurations. The beam axis was found to be close to the midline of the melon, approximately 5.4 cm above the rostrum insert for both animals. The signal path coincided with the low-density, low-velocity core of the melon; however, the data suggest that the signals are focused mainly by the air sacs. Slight asymmetry in the signals were found with higher amplitudes on the right side of the forehead. Although the signal waveform measured on the melon appeared distorted, when they are mathematically summed in the far-field, taking into account the relative time of arrival of the signals, the resultant waveform matched that measured by the hydrophone located at 1 m.

The target detection range of two echolocating Atlantic Bottlenose dolphins as a function of target depth in Kaneohe Bay, Hawaii, was determined by Murchison [A. E. Murchison, Ph.D. dissertation, Univ. of Calif., Santa Cruz (1980)]. The threshold range decreased monotonically as the depth of the 6.35‐cm‐diam solid‐steel sphere increased and approached the bottom. For the target lying on the bottom, the 50% correct detection threshold detection range was approximately 70 m. The scattering strength of the bottom in Kaneohe Bay at approximately the same location of the Murchison’s experiment was recently measured using a simulated dolphin echolocation signal and a transducer tilted at the appropriate grazing angle. The bottom scattering strength along with the target strength of the 6.35‐cm sphere and the dolphin threshold range were incorporated into the generalized form of the sonar equation for a reverberation‐limited situation and a detection threshold of 4.0 dB was calculated. This detection threshold compared well with the 2.3 dB obtained in an experiment in which the dolphin was required to detect a target in the presence of a clutter screen.

This study demonstrated the ability of a false killer whale (Pseudorca crassidens) to discriminate between two targets and investigated the parameters of the whale's emitted signals for changes related to test conditions. Target detection performance comparable to the bottlenose dolphin's (Tursiops truncatus) has previously been reported for echolocating false killer whales. No other echolocation capabilities have been reported. A false killer whale, naive to conditioned echolocation tasks, was initially trained to detect a cylinder in a "go/no-go" procedure over ranges of 3 to 8 m. The transition from a detection task to a discrimination task was readily achieved by introducing a spherical comparison target. Finally, the cylinder was successfully compared to spheres of two different sizes and target strengths. Multivariate analyses were used to evaluate the parameters of emitted signals. Duncan's multiple range tests showed significant decreases (df = 185, p less than 0.05) in both source level and bandwidth in the transition from detection to discrimination. Analysis of variance revealed a significant decrease in the number of clicks over test conditions [F(5.26) = 5.23, p less than 0.0001]. These data suggest that the whale relied on cues relevant to target shape as well as target strength, that changes in source level and bandwidth were task-related, that the decrease in clicks was associated with learning experience, and that Pseudorca's ability to discriminate shapes using echolocation may be comparable to that of Tursiops truncatus.

One of the outstanding characteristics of the dolphin sonar system which distinguishes it from any man-made sonar is the ability to make fine distinctions in the features or properties of targets. Sonar experiments have shown that dolphins can discriminate between objects differing in size, structure, shape and material composition. This discrimination capability has amazed and sparked the interest of many involved in the development and use of active sonar systems.

The Atlantic bottlenose dolphin has a sonar detection range of 72 m for a 2.54‐cm solid sphere and 113 m for a 7.63‐cm water‐filled sphere in a noise‐limited environment. However, there are many natural environments in which the ambient noise is low and will not mask a dolphin auditory system. The dolphin’s detection range for the same 2.54‐ or 7.62‐cm sphere in a nonmasking environment should be considerably longer than 72 and 113 m, respectively. In order to perform a sonar experiment in an environment where the ambient noise is low, a pool must be extremely large, or an outdoor facility with low ambient noise conditions would need to be available. Another way of approaching this problem is to perform a passive listening experiment in which the signal presented to a dolphin simulates an echo from a specific target. We performed a listening experiment using both pure tones and simulated broadband echo from a 7.62‐cm water‐filled sphere. The detection threshold for narrow‐band tonal signals (audiogram) is compared with the detection threshold for a broadband echo signal in order to determine the relationship between an audiogram and sonar detection. The results obtained with the broadband echo also represent the sonar detection range of a dolphin in a nonmasking environment. [Work suported by ONR.]

Monitoring the changing state of marine habitats is a challenging task that is exacerbated when the habitats in question are in remote locations. Passive acoustic monitoring is sometimes the best, if not the only, means of gauging levels of biological and anthropogenic activities in such areas. Since 2006, the Pacific Islands Fisheries Science Center, in partnership with the University of Hawaii, has been building a network of long‐term acoustic monitoring stations across the Pacific Islands Region using Ecological Acoustic Recorders (EARs). The network is currently composed of 29 long‐term monitoring stations and spans the Hawaiian Archipelago, American Samoa, the Line Islands, Johnston Atoll, Wake Atoll, Guam, and the Commonwealth of the Northern Mariana Islands. EARs are diver‐deployed and refurbished by local partners and/or during annual or biennial research cruises to deployment locations. A wide range of natural and anthropogenic acoustic signals are monitored, including sounds produced by invertebrates, fish, cetaceans, vessels, and surface weather events. The long‐term trends in biological acoustic activity obtained through this network will be used to gauge the relative stability of the ecosystems associated with each location. Detections of vessels are common at many locations and provide a quantitative means of establishing levels of anthropogenic activity.

There has been a proliferation of different types of remote underwater autonomous acoustic recorders in recent years. Many were designed for a specific purpose to measure sounds from specific organisms. Others were designed for general application to encompass a wide variety of sounds. Many have fancy acronyms such as ARP, BPROBE, DTAG, EAR, EARS, HARP, MARU, PALs, RUDAR, and TPOD, to name a few. All have essentially the same subsystems consisting of a hydrophone and amplifier assembly, an analog‐to‐digital converter, data storage, and a microcontroller to handle the data acquisition and storage operations and to control the overall functioning of the unit. The differences are in the bandwidth of the system, amount of storage available, amount of power required, and duration of deployment possible. Some can be purchased commercially, some can only be leased, while others can only be used in a collaborative research project. The prices also vary considerably. Some have been used for many years while others...

Fish are an important component of coral reef ecosystems and can be valuable indicators of ecological change on reef environments. Many species of fish produce sounds and are therefore well suited for passive acoustic monitoring. Since 2006, NOAA has been using Ecological Acoustic Recorders (EARs) to monitor coral reef habitats in the main and Northwestern Hawaiian Islands in an effort to develop multi‐year time series of biological activity at these locations. Sixteen EARs are presently deployed on reef habitats ranging in depth from 2 to 23 meters. Preliminary results reveal that each site is characterized by a unique composition of acoustically active fish. Many sounds are also common at multiple sites. Different species show considerable variability in their diet and seasonal patterns of activity. The results indicate that long‐term acoustic monitoring of fish at these sites is likely to yield useful information about changing patterns of fish presence, behavior, and relative abundance. These metrics can be used to gauge the relative stability of ecosystems and be related to physical, oceanographic, and anthropogenic variables affecting them.

An acoustic monitoring system in the nearshore waters of the south shore of Oahu is a part of the Kilo Nalu nearshore coral reef observatory (http://www.soest.hawaii.edu/OE/kilonalu/). The underwater housing containing the hydrophone, amplifier‐filter, A/D converter, and an ethernet converter is located 690 m from shore at a depth of 22 m. Acoustic signals are digitized at a rate of 24 kHz, and sent to shore on a fiber optic link to a laptop computer and are stored on a disk drive. Snapping shrimp sounds are the most prevalent biological signals and are always present. Other sounds from biological organisms include humpback whales (during their winter season in Hawaii), fish, and dolphins. However, the soundscape during daylight hours is dominated by small boat sounds as a variety of vessels are regularly detected and the signal levels from these boats are considerable higher than the biological sounds. Only humpback whale songs have the chance of being detected in the presence of boat sounds, whereas oth...

In the present work, groups of spinner dolphins (Stenella longirostris) off four of the main Hawai’ian islands (Hawai’i, Lana’i, Maui, and O’ahu) have been studied. The whistle repertoire of dolphin groups from each island will be compared to search for geographic variations. In addition, behavioral, ecological, and acoustical variables have been quantified in order to correlate the dolphin whistle repertoire with specific behavioral and ecological factors. Geographic variations in the whistle repertoire of coastal bottlenose dolphins (Tursiops truncatus) from the Gulf of Mexico have been found. The differences were not attributable to different behavioral states, but were related to group structure (group size and contacts established between groups) and coastal habitat. These findings on the whistle repertoire of coastal bottlenose dolphins support the hypothesis that delphinid whistles serve to coordinate group behavior. Preliminary results on group structure of spinner dolphin groups off Hawai’i sugge...

Spinner dolphins are the most commonly sighted cetacean in coastal Hawaiian waters and are an important higher‐level trophic component of the near‐shore ecosystem. Establishing their long‐term patterns of occurrence is important both for their conservation and for a better understanding of the relationships between dolphins, their prey, and other members of the ecosystem. Here we report on an effort to use ecological acoustic recorders (EARs) to monitor the presence of spinner dolphins along the leeward coast of the island of Oahu, Hawaii. The EAR is a bottom‐moored recorder with a bandwidth of 30 kHz, which allows the detection of both dolphin whistles and echolocation clicks. Eight EARs were deployed along the coast at depths ranging from 15 to 50 m. Five units were deployed in an array, providing information about the EAR’s detection range. The other three units were placed at sites along the coast commonly frequented by spinner dolphins. The results reveal distinct patterns of preference in habitat use, both for daytime resting behavior and night‐time foraging. The recordings also provide a measure of vessel traffic at locations important to spinner dolphins. Combined, these data demonstrate the value of passive acoustic methods for monitoring cetacean populations and their habitat over extended periods.

The resident ecotype of killer whales (Orcinus orca) in the waters of British Columbia and Washington State has a strong preference for Chinook salmon even in months when Chinook are 5%–10% of the salmon population. The foraging behavior of killer whales suggests that they rely on echolocation to detect and recognize their prey. In order to determine possible cues in echoes from salmon, a series of backscatter measurements was made at the Applied Physics Laboratory, University of Washington Facility on Lake Union, on three different salmon species using simulated killer whale echolocation signals. The fish were tied to a monofilament net and rotated while echoes were collected, digitized, and stored on a laptop computer. Three transducer depths were used; same depth, 22o, and 45o above the horizontal plane of the fish. Echoes were collected from five Chinook, three Coho, and one Sockeye salmon. Radiograph images of all the specimens were also obtained to examine the swim bladder shape and orientation. Res...

Humpback whales are amongst the best studied of the baleen whales. The species is also known for its flexibility and variety of behavior on both feeding and breeding grounds. DTAGs were attached to 19 whales on the Hawaiian breeding grounds and to 24 whales on the northwestern Atlantic feeding grounds between the years of 2004 and 2008 to describe the variety of acoustic behavior in each location. Sounds were analyzed using ADOBE AUDITION, XBAT, and custom programs in MATLAB 7, and acoustic records from the tags showed differences in sound production between the two populations engaged in different activities. Recordings from the feeding grounds showed higher social sound production rates and also contained the sounds with the highest signal‐to‐noise ratios (10–20 dB for 1 μPa higher than on the breeding grounds). Differences in ambient noise may contribute to this: song chorusing is present in Hawaii, but commercial shipping traffic is higher in the northwest Atlantic feeding areas. Some similar sounds w...

Minke whales are elusive and difficult to study using visual methods. The source of the “boing” sound was recently linked to North Pacific minke whales, allowing passive acoustics to be used to study this species. The seasonal occurrence of minke whales was examined using data collected at the Station ALOHA Cabled Observatory, an ocean bottom hydrophone 100 km north of Oahu. Preliminary analysis of data collected between February and June 2007 indicates that boings occur during all of these months, peaking in early April. No diurnal variation was evident. Towed hydrophone‐array surveys were conducted in the offshore waters of the islands of Oahu, Kauai and Ni’ihau (February 2005) and off Guam and the Northern Mariana Islands (January–April 2007). Although rarely observed visually, the prevalence of boings detected in these areas indicates that minke whales are common. Distribution patterns from both studies suggest that minke whales prefer deep but not the deepest waters. Boings recorded from Guam and the Northern Mariana Islands appear to be more similar to the “central” boing (which includes the Hawaiian Islands) than the “eastern” boing [which includes those recorded east of 138°W, Rankin and Barlow (2005)]. This has important implications for North Pacific minke whale stock structure.

Underwater measurements of the Hawaii Super Ferry were made with a vertical array of four hydrophones. The depths of the hydrophones were 3, 6.5, 10, and 20 m. The Alakai is a 107 m catamaran passenger and automobile ferry that has a waterjet propulsion system with no exposed propellers. The Alakai made three close proximity passes at speeds of 37, 24, and 12 kn on tracks that allowed for acoustic measurements of sounds radiating from the bow, broadside, and stern aspects. The track of the Alakai was recorded on global positioning system. The measurements were conducted while the ferry proceeded on normal scheduled trips, allowing for three measurements a day. All the sound pressure levels were referenced to 91 m (100 yards), the minimum legal approach distance of boats to humpback whales. Sound intensity increased with speed and was the highest at 37 kn in the broadside aspect (160 dB) and was 14 dB lower for both the bow and stern aspects. The sounds had a broadband noise quality with spectra that had a low frequency peak below 100 Hz and decreased continuously with frequency. The effects of the sounds will be discussed from a humpback whale perspective.

Hawaiian waters support a wide variety of cetacean species, however, little is known about their occurrence in offshore waters. A cabled ocean bottom observatory located at Station ALOHA (Station ALOHA Cabled Observatory ‐ ACO) provides a unique opportunity to study the occurrence of cetaceans in real‐time and over long time scales at a deep ocean research site located 100 km north of Oahu. A retired electro‐optical telecommunications cable provides power and broadband Ethernet communications capability to the ACO, allowing real‐time continuous acoustic monitoring. The ACO has been operational since February 2007 and includes a hydrophone with a bandwidth of 0.01Hz to 40kHz. Automated methods for detection and identification of cetacean calls have been developed and data are processed in nearly real‐time. Several cetacean species have been detected, including: dolphins and humpback, minke, fin, and sperm whales. The relationship between the occurrence of different species and changes in the environment has been explored using near‐monthly shipboard oceanographic observations collected at Station ALOHA. In addition, seasonal trends in the occurrence of minke whales, a species that has been especially difficult to study using visual methods due to their cryptic behavior, have been examined.

Dolphins have a very keen sonar system that is able to make fine discriminations between complex targets such as proud and buried mines. To understand the cues that dolphins use for fine target discrimination, human listening experiments have been conducted with echoes from real targets using a simulated broadband dolphin echo‐ranger. Echoes are stretched in time to translate the echoes into the human auditory range. The human performance is usually as accurate as the dolphin, with the additional benefit of being able to get feedback on cues used. Various types of discrimination and detection experiments have been conducted paralleling dolphin sonar experiments. Discrimination of material composition of cylinders and spheres, detection of target in clutter and cylinder wall thickness difference discrimination experiment have been performed. The human listeners performed as well or better than the dolphins at the task of discriminating between a standard target and comparison targets. Click pitch, echo duration, time‐separation pitch and timbre are some of the cues used by human listeners to discriminate targets. Dolphins may use some of the same echo features as humans. Human listening studies can quickly identify salient combinations of echo features that permit object discrimination and also help refine dolphin experiments.