Classification of broadband echoes from prey of a foraging Blainville’s beaked whale

Jones, Benjamin A.; Stanton, Timothy K.; Lavery, Andone C.; Johnson, Mark; Madsen, Peter T.; Tyack, Peter L.

doi:10.1121/1.2828210

Cited by 35 publications

(21 citation statements)

References 28 publications

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“…A few recent studies show that the phases of prey capture in odontocetes ͑e.g., Miller et al, 1995;Madsen et al, 2002;Johnson et al, 2004;Miller et al, 2004;Akamatsu et al, 2005;Madsen et al, 2005;Johnson et al, 2006Johnson et al, , 2008Jones et al, 2008;Verfuß et al, 2009͒ are very similar to those of prey capture in bats ͑e.g., Griffin et al, 1960;Kalko and Schnitzler, 1989;Surlykke et al, 1993;Schnitzler and Kalko, 1998;Miller and Surlykke, 2001;Schnitzler et al, 2003;Melcón et al, 2007͒. Vocalizing with long intervals is used to search for prey items while a group of signals with short intervals, the buzz, indicate prey capture attempts.…”

Section: Introductionmentioning

confidence: 77%

Echolocation signals of a beaked whale at Palmyra Atoll

Baumann‐Pickering

Wiggins

Roth

et al. 2010

The Journal of the Acoustical Society of America

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Acoustic recordings from Palmyra Atoll, northern Line Islands, central Pacific, showed upsweep frequency modulated pulses reminiscent of those produced by beaked whales. These signals had higher frequencies, broader bandwidths, longer pulse durations and shorter inter-pulse intervals than previously described pulses of Blainville's, Cuvier's and Gervais' beaked whales [Zimmer et al. (2005). J. Acoust. Soc. Am. 117, 3919-3927; Johnson et al. (2006). J. Exp. Biol. 209, 5038-5050; Gillespie et al. (2009). J. Acoust. Soc. Am. 125, 3428-3433]. They were distinctly different temporally and spectrally from the unknown beaked whale at Cross Seamount, HI [McDonald et al. (2009). J. Acoust. Soc. Am. 125, 624-627]. Genetics on beaked whale specimens found at Palmyra Atoll suggest the presence of a poorly known beaked whale species. Mesoplodon sp. might be the source of the FM pulses described in this paper. The Palmyra Atoll FM pulse peak frequency was at 44 kHz with a -10 dB bandwidth of 26 kHz. Mean pulse duration was 355 mus and inter-pulse interval was 225 ms, with a bimodal distribution. Buzz sequences were detected with inter-pulse intervals below 20 ms and unmodulated spectra, with about 20 dB lower amplitude than prior FM pulses. These clicks had a 39 kHz bandwidth (-10 dB), peak frequency at 37 kHz, click duration 155 mus, and inter-click interval between 4 and 10 ms.

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Section: Introductionmentioning

confidence: 77%

Echolocation signals of a beaked whale at Palmyra Atoll

Baumann‐Pickering

Wiggins

Roth

et al. 2010

The Journal of the Acoustical Society of America

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“…It is assumed that during each phase, a whale has certain distributions of depth and pitch. Depths are described by Gaussian distributions with mean and standard deviations estimated from published dive profiles (Johnson et al, 2004;Madsen et al, 2005;Tyack et al, 2006;Ward et al, 2008;Jones et al, 2008). Whale pitch is measured from þ90 to À90 , where negative angles correspond to downward orientation.…”

Section: A Animal Location and Orientationmentioning

confidence: 99%

Cetacean population density estimation from single fixed sensors using passive acoustics

Küsel

Mellinger

Thomas

et al. 2011

The Journal of the Acoustical Society of America

104

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Passive acoustic methods are increasingly being used to estimate animal population density. Most density estimation methods are based on estimates of the probability of detecting calls as functions of distance. Typically these are obtained using receivers capable of localizing calls or from studies of tagged animals. However, both approaches are expensive to implement. The approach described here uses a MonteCarlo model to estimate the probability of detecting calls from single sensors. The passive sonar equation is used to predict signal-to-noise ratios (SNRs) of received clicks, which are then combined with a detector characterization that predicts probability of detection as a function of SNR. Input distributions for source level, beam pattern, and whale depth are obtained from the literature. Acoustic propagation modeling is used to estimate transmission loss. Other inputs for density estimation are call rate, obtained from the literature, and false positive rate, obtained from manual analysis of a data sample. The method is applied to estimate density of Blainville's beaked whales over a 6-day period around a single hydrophone located in the Tongue of the Ocean, Bahamas. Results are consistent with those from previous analyses, which use additional tag data.

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“…Tagged beaked whales appear to ensonify many more organisms in the course of a foraging dive than they attempt to capture , perhaps indicating that a large proportion of the echoic targets do not represent worthwhile prey and that the whales may use acoustic cues in a selective foraging scheme ). While we know little about the prey targeted by beaked whales and whether these have distinctive echo signatures (Jones et al 2008), analysis of the general target density as a function of depth may provide information about the habitats preferred by these elusive whales ). The tortuous track segment associated with the buzz cluster supports the idea of a prey patch Studies of foraging using acoustic tags have considerable promise, especially for echolocating whales.…”

Section: Foragingmentioning

confidence: 99%

Studying the behaviour and sensory ecology of marine mammals using acoustic recording tags: a review

Johnson¹,

Soto²,

Madsen³

2009

Mar. Ecol. Prog. Ser.

199

215

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Many marine animals use sound passively or actively for communication, foraging, predator avoidance, navigation, and to sense their environment. The advent of acoustic recording tags has allowed biologists to get the on-animal perspective of the sonic environment and, in combination with movement sensors, to relate sounds to the activities of the tagged animal. These powerful tools have led to a wide range of insights into the behaviour of marine animals and have opened new opportunities for studying the ways they interact with their environment. Acoustic tags demand new analysis methods and careful experimental design to optimize the consistency between research objectives and the realistic performance of the tags. Technical details to consider are the suitability of the tag attachment to a given species, the accuracy of the tag sensors, and the recording and attachment duration of the tag. Here we consider the achievements, potential, and limitations of acoustic recording tags in studying the behaviour, habitat use and sensory ecology of marine mammals, the taxon to which this technology has been most often applied. We examine the application of acoustic tags to studies of vocal behaviour, foraging ecology, acoustic tracking, and the effects of noise to assess both the breadth of applications and the specific issues that arise in each.

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Classification of broadband echoes from prey of a foraging Blainville’s beaked whale

Cited by 35 publications

References 28 publications

Echolocation signals of a beaked whale at Palmyra Atoll

Echolocation signals of a beaked whale at Palmyra Atoll

Cetacean population density estimation from single fixed sensors using passive acoustics

Studying the behaviour and sensory ecology of marine mammals using acoustic recording tags: a review

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