Classification of the acoustic repertoires of animals into sound types is a useful tool for taxonomic studies, behavioral studies, and for documenting the occurrence of animals. Classification of acoustic repertoires enables the... more
Classification of the acoustic repertoires of animals into sound types is a useful tool for taxonomic studies, behavioral studies, and for documenting the occurrence of animals. Classification of acoustic repertoires enables the identification of species, age, gender, and individual identity, correlations between sound types and behavior, the identification of changes in vocal behavior over time or in response to anthropogenic noise, comparisons between the repertoires of populations living in different geographic regions and environments, and the development of software tools for automated signal processing. Techniques for classification have evolved over time as technical capabilities have expanded. Initially, researchers applied qualitative methods, such as listening and visually discerning sounds in spectrograms. Advances in computer technology and the development of software for the automatic detection and classification of sounds have allowed bioacousticians to quickly find so...
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Bottlenose dolphins possess vocal learning abilities that influence the development of individually distinctive signature whistles. While signature whistles have been studied in detail, little is known about other whistle types in... more
Bottlenose dolphins possess vocal learning abilities that influence the development of individually distinctive signature whistles. While signature whistles have been studied in detail, little is known about other whistle types in bottlenose dolphin communication or the size of their whistle repertoires. We made 24-hour acoustic recordings from a group of 13 bottlenose dolphins at Oceanogràfic (Valencia, Spain) for two months to determine the whistle repertoire size of this group and investigate whether learning leads to changes in existing whistle types over time. We extracted fundamental frequency contours from 50 randomly chosen whistles per day (n = 3,119 whistles) and categorised them using ARTwarp (96% vigilance level), resulting in 701 whistle types. The whistle type discovery curve did not plateau after two months, indicating that we did not capture the entire repertoire. Three analytical methods were used to estimate repertoire size (curve-fitting, a capture-recapture model...
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Three genetically distinct populations of false killer whales Pseudorca crassidens) reside in the Hawaiian Archipelago: two insular populations (one within the main Hawaiian Islands [MHI] and the other within the Northwestern Hawaiian... more
Three genetically distinct populations of false killer whales Pseudorca crassidens) reside in the Hawaiian Archipelago: two insular populations (one within the main Hawaiian Islands [MHI] and the other within the Northwestern Hawaiian Islands [NWHI]), and a wide-ranging pelagic population with a distribution overlapping the two insular populations. The mechanisms that created and maintain the separation among these populations are unknown. To investigate the distinctiveness of whistles produced by each population, we adapted the Real-time Odontocete Call Classification Algorithm (ROCCA) whistle classifier to classify false killer whale whistles to population based on 54 whistle measurements. 911 total whistles from the three populations were included in the analysis. Results show that the MHI population is vocally distinct, with up to 80% of individual whistles correctly classified. The NWHI and pelagic populations achieved between 48 and 52% correct classification for individual whistles. We evaluated the sensitivity of the classifier to the input whistle measurements to determine which variables are driving the classification results. Understanding how these three populations differ acoustically may improve the efficacy of the classifier and create new acoustic monitoring approaches for a difficult-to-study species.
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The field of bioacoustics is rapidly developing and characterized by diverse methodologies, approaches and aims. For instance, bioacoustics encompasses studies on the perception of pure tones in meticulously controlled laboratory... more
The field of bioacoustics is rapidly developing and characterized by diverse methodologies, approaches and aims. For instance, bioacoustics encompasses studies on the perception of pure tones in meticulously controlled laboratory settings, documentation of species’ presence and activities using recordings from the field, and analyses of circadian calling patterns in animal choruses. Newcomers to the field are confronted with a vast and fragmented literature, and a lack of accessible reference papers or textbooks. In this paper we contribute towards filling this gap. Instead of a classical list of “dos” and “don’ts”, we review some key papers which, we believe, embody best practices in several bioacoustic subfields. In the first three case studies, we discuss how bioacoustics can help identify the ‘who’, ‘where’ and ‘how many’ of animals within a given ecosystem. Specifically, we review cases in which bioacoustic methods have been applied with success to draw inferences regarding spe...
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: Substantial advancements have been made in the identification of odontocete species based on the properties of their whistles and clicks. However, the suitability of species classifiers trained using data from the sea surface to analyze... more
: Substantial advancements have been made in the identification of odontocete species based on the properties of their whistles and clicks. However, the suitability of species classifiers trained using data from the sea surface to analyze recordings obtained at depth is currently unknown. As a result, it remains unclear how depth, distance of animals from the recorder and sound propagation influence classification results. If classifiers perform differently on data recorded at depth than at the surface, it may be necessary to re-train them to ensure accurate results. Similarly, if the behavior of animals or signal propagation affects the identification of species using echolocation clicks, this must be understood and integrated into analysis methods. In this project, we examine how species-specific signaling cues are affected by recording depth by using both surface-deployed and bottom-moored vertical arrays of hydrophones and autonomous recorders to obtain recordings at different d...
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Visually validated towed hydrophone array recordings made in the presence of four killer whale communities (northern and southern residents, offshores, and west coast transients) were collected during the Pacific Orca Distribution Surveys... more
Visually validated towed hydrophone array recordings made in the presence of four killer whale communities (northern and southern residents, offshores, and west coast transients) were collected during the Pacific Orca Distribution Surveys (PODS) conducted by the Northwest Fisheries Science Center in the winters of 2006-2009, 2012, 2013, and 2015. Killer whale communities are known to exhibit differences in their prey preferences, genetic structure, and acoustic call repertoire, but little is known about differences in echolocation clicks. Over 20,000 echolocation clicks were measured from 49 independent killer whale acoustic encounters that were recorded during these cruises to compare signal parameters between communities. Echolocation click parameters were measured automatically using tools available in PAMGuard software. Results of pairwise comparisons indicated that duration, center frequency, peak frequency, sweep rate, number of zero crossings, and inter-click interval were si...
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... more
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,...
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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.... more
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.
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SHANNON RANKIN, Marine Mammal & Turtle Division, Southwest Fisheries Science Center, National Marine Fisheries Service, National Oceanographic and Atmospheric Administration, 8901 La Jolla Shores Drive, La Jolla, California 92037,... more
SHANNON RANKIN, Marine Mammal & Turtle Division, Southwest Fisheries Science Center, National Marine Fisheries Service, National Oceanographic and Atmospheric Administration, 8901 La Jolla Shores Drive, La Jolla, California 92037, U.S.A.; JULIE N. OSWALD, Bio-waves, Inc., 364 2nd Street, Suite #3, Encinitas, California 92024, U.S.A.; ANNE E. SIMONIS, Scripps Institution of Oceanography, University of California San Diego, 9500 Gilman Drive, La Jolla, California 92093, U.S.A.; JAY BARLOW, Marine Mammal & Turtle Division, Southwest Fisheries Science Center, National Marine Fisheries Service, National Oceanographic and Atmospheric Administration, 8901 La Jolla Shores Drive, La Jolla, California 92037, U.S.A.
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Papale, E., Azzolin, M., Cascao, I., Gannier, A., Lammers, M. O., Martin, V. M., Oswald, J., Perez-Gil, M., Prieto, R., Silva, M. A., & Giacoma, C. (2014). Macro- and micro-geographic variation of short-beaked common dolphin's whistles in the Mediterranean Sea and Atlantic Ocean. Ethology Ecology...more
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ABSTRACT Acoustic signals are expressions of phenotypic diversity and their variation could provide important information on differentiation patterns within species. Due to a number of selective pressures acting on signals, the... more
ABSTRACT Acoustic signals are expressions of phenotypic diversity and their variation could provide important information on differentiation patterns within species. Due to a number of selective pressures acting on signals, the contribution of genetic drift is often complex to outline. This study aims at evaluating if an examination of the acoustic structure of communication signals can allow the identification of evolutionary units in species capable of vocal learning. We quantified and compared parameters of whistles emitted by three dolphin species (Stenella coeruleoalba, Delphinus delphis, and Tursiops truncatus) to examine the hypothesis that acoustic signals permit the recognition of differentiation between populations from the Atlantic Ocean and the Mediterranean Sea. In the three species, recordings were correctly assigned to their basin of origin with a percentage higher than 82% by DFA. Frequency parameters were the most stable within each species. Where gene flow has been shown, i.e., within Atlantic Ocean, significant differences were found principally in modulation parameters. We hypothesize that these parameters are influenced by social and behavioral factors and that similar ecological conditions led to convergent acoustic features. Results of this study suggest that is it possible to recognize evolutionary units based on acoustic data.
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ABSTRACT Passive acoustic systems used to study and monitor marine mammals generate enormous datasets which are costly and time-consuming to analyze. As part of a Joint Industry Programme sponsored effort, we reviewed automated and... more
ABSTRACT Passive acoustic systems used to study and monitor marine mammals generate enormous datasets which are costly and time-consuming to analyze. As part of a Joint Industry Programme sponsored effort, we reviewed automated and semi-automated methods and software packages available to detect, extract, and classify marine mammal sounds; identified gaps in capabilities and knowledge; and suggested ways forward. Because of the variability in marine mammal sounds, no single method is effective for all species. While spectrogram correlation works well for stereotyped calls, more general methods like band-limited threshold detection are more effective for variable sounds. Feature extraction is a rapidly evolving field, but a reliable, automated method has yet to be successfully implemented into existing software. A major gap in our capabilities is the ability to reliably detect and classify the highly variable signals produced by some species. The development of effective, efficient, and standardized methods applicable to many species will require large, validated datasets. The acquisition, maintenance, and availability of such datasets will entail concerted, collaborative efforts. Development of common datasets and organization of workshops that focus on furthering detection, extraction, and classification methods are two ways to address these important issues in the automated analysis of marine mammal sounds.
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ABSTRACT Autonomous underwater recorders (ARs) are fixed passive acoustic electronic systems that acquire and store acoustic data internally (i.e., without a cable or radio link to a receiving station). They are deployed semi-permanently... more
ABSTRACT Autonomous underwater recorders (ARs) are fixed passive acoustic electronic systems that acquire and store acoustic data internally (i.e., without a cable or radio link to a receiving station). They are deployed semi-permanently underwater (via a mooring, buoy, or resting on the sea-floor) and must be retrieved after the deployment period to access the data. ARs are capable of monitoring and recording underwater sounds over a wide range of spatial and temporal scales. As part of a Joint Oil & Gas Industry Program on Sound and Marine Life (JIP) sponsored effort, we reviewed over 30 ARs that are available for recording marine mammal sounds. They varied greatly in price and capabilities, from small hand-deployable units for detecting dolphin and porpoise clicks in shallow water to large units that can be deployed in deep water and record wide frequency bands for long durations. Considerations to weigh when selecting which device to use include price, longevity and depth of deployment, area to be monitored, and, most importantly, the bandwidth and the characteristics of sounds to be monitored (i.e., marine mammal call types and noise sources).
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The acoustic ecology and behavior of minke whales (Balaenoptera acutorostrata) near tropical and subtropical North Pacific Islands. [The Journal of the Acoustical Society of America 128, 2414 (2010)]. Thomas Norris, Tina M ...
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ABSTRACT 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... more
ABSTRACT 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 automated methods could be used in future humpback whale studies. After this comparison was made, a principal component analysis (PCA) determined which of the aforementioned 48 parameters were important in statistically distinguishing between the distinct units furthering our understanding of frequency and temporal importance in categorizing song structure.
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ABSTRACT Passive acoustic monitoring using seafloor-mounted recorders allows cetacean occurrence to be examined over time and space. Four ecological acoustic recorders (EARs) were moored around the Hawaiian island of Niihau in summer/fall... more
ABSTRACT Passive acoustic monitoring using seafloor-mounted recorders allows cetacean occurrence to be examined over time and space. Four ecological acoustic recorders (EARs) were moored around the Hawaiian island of Niihau in summer/fall (July-November) 2011, and winter/spring (January-May) 2012. Delphinid whistle "detections" (a proxy for schools) were identified and characterized. Whistles were identified to species using a random forest classifier trained with whistles recorded from seven species (Globicephala macrorhynchus, Pseudorca crassidens, Stenella attenuata, S. coeruleoalba, S. longirostris, Steno bredanensis, and Tursiops truncatus) in the tropical Pacific Ocean. The highest number of detections per day occurred during summer/fall at all sites. All species except for G. macrorhynchus were detected at every site during both deployments. No single species dominated the detections at any site, with the exception of Stenella longirostris at the Pueo Point site during summer/fall (53% of detections). Pseudorca crassidens, a species of particular management/conservation interest due to small population sizes, were detected most frequently (18% of detections) at the Niihau NW site during summer/fall and least frequently (7% of detections) at the Pueo Point site during summer/fall. Understanding trends in species composition provides insight into how species use different habitats and aids in management efforts.
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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... more
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.
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Humpback whales, Megaptera novaeangliae, are one of the most recognizable and investigated marine mammals. However, little progress has been made in automatically distinguishing and classifying individual units of their song. A Matlab... more
Humpback whales, Megaptera novaeangliae, are one of the most recognizable and investigated marine mammals. However, little progress has been made in automatically distinguishing and classifying individual units of their song. A Matlab script has been developed to characterize the different song units and to apply the appropriate statistics to separate and categorize each unit. The Matlab program measures 48 parameters from each song unit. The songs were recorded by a swimmer snorkeling above vocalizing humpbacks in the waters off Maui, HI. A 16 bit, digital tape recorder with the automatic gain control disabled and a sample rate of 44.1 kHz was used to record songs from different whales. The swimmer determined the range of the whale using a portable handheld fathometer. Singing whales typically suspended themselves in the water column at depths varying from 15 to 30 m, which was contingent on the bottom depth. Song units were separated into distinct categories using a principle component analysis (PCA) ba...
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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... more
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 f...
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1. J Acoust Soc Am. 2011 Oct;130(4):2321. The acoustic ecology of minke whales in the tropical north pacific. Norris T, Martin SW, Yack TM, Thomas L, Oswald J. Bio-Waves, Inc., 517 Cornish, Encinitas, CA 92024. The minke ...
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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.... more
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,...
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ABSTRACT Passive acoustic data were collected from nine Marine Autonomous Recording Units (MARUs) deployed 60-150 km in an area that coincides with the U.S. Navy's planned Undersea Warfare Training Range (USWTR) off Jacksonville... more
ABSTRACT Passive acoustic data were collected from nine Marine Autonomous Recording Units (MARUs) deployed 60-150 km in an area that coincides with the U.S. Navy's planned Undersea Warfare Training Range (USWTR) off Jacksonville FL. MARUs were deployed for 26 days during fall 2009, and 37 days in winter 2009-2010. Data were manually reviewed for marine mammal vocalization events, man-made noise, and mid-frequency active sonar events, which were logged using Triton software. Seasonal and diel patterns were characterized qualitatively. Patterns and probabilities of vocalization events by species, or species groups, were related to sonar events. Vocalizations were detected for minke whales, North Atlantic right whales, sei whales, humpback whales, sperm whales, the blackfish group, and delphinids. Minke whale pulse-trains occurred almost continuously during the winter deployment but were absent in fall. Right whale events occurred mostly during winter at shallow-water sites, but unexpectedly were also detected at deep-water sites. Sperm whale events occurred exclusively near the continental shelf break and exhibited a strong diel pattern. Minke whale events had a strong negative relationship with sonar events. These results provide an initial assessment of marine mammal occurrence within the Navy's planned USWTR, and provide new information on vocalization events in relation to sonar.
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ABSTRACT 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... more
ABSTRACT 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 degrees W, Rankin and Barlow (2005)]. This has important implications for North Pacific minke whale stock structure.
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Acoustic species identification studies generally focus on postprocessing of field recordings using multivariate statistics such as classification tree analysis (CART). When CART was used to classify whistles of nine delphinid species... more
Acoustic species identification studies generally focus on postprocessing of field recordings using multivariate statistics such as classification tree analysis (CART). When CART was used to classify whistles of nine delphinid species recorded in the eastern tropical Pacific ocean (n=908), 51% were correctly classified to species (versus 11% expected by chance). These results led to the development of a new automated
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Dolphins were detected using a towed hydrophone array during cetacean abundance surveys in the eastern tropical Pacific (ETP) and in U.S. west coast waters up to 300 nmi offshore (USWC). Cross‐correlation algorithms were used to estimate... more
Dolphins were detected using a towed hydrophone array during cetacean abundance surveys in the eastern tropical Pacific (ETP) and in U.S. west coast waters up to 300 nmi offshore (USWC). Cross‐correlation algorithms were used to estimate bearing angles to vocalizing dolphins. The convergence of bearing angles as the ship traveled indicated the probable location of dolphins. The study areas were stratified based on sound speed profiles, sea surface temperature, and depth of the thermocline to examine the effect of oceanographic conditions on acoustic detection distances (the greatest distance at which bearing angles can be determined) for delphinid whistles. Significant differences in mean detection distances were found between offshore ETP (2.9 nmi) and USWC waters (1.5 nmi, p<0.001), and between USWC waters and waters off Peru and Baja pooled (2.9 nmi, p=0.005). Ray trace models confirm these empirical differences in acoustic propagation. Results suggest that the effectiveness of acoustic methods during ...