94 research outputs found
Detection, classification, and density estimation of marine mammals: final report
Detection, classification, and localization (DCL) research on marine mammal vocalizations has been in development for decades, and methods for marine mammal population density estimation using acoustic data have been in development since at least 2007. These efforts have been supported by MobySound, an archive of cetacean sounds used for studying call detection and localization that are annotated to facilitate research in DCL. This project was aimed to begin development of highâperforming automatic detection methods for the sounds of beaked whales and other odontocetes. Specifically, this report [1] details the newly collected odontocete recordings that have been added to the MobySound archive; [2] documents continuing development of methods for detection and classification, including improvements to the Energy Ratio Mapping Algorithm (ERMA) method for use on gliders and its extension to new species and populations; [3] reports on application of a newly developed method for population density estimation to field recordings; and [4] also reports on the successful production of datasets focused on odontocete whistles and clicks and baleen whale calls for the Fifth Workshop on Detection, Classification, Localization, and Density Estimation of Marine Mammals using Passive Acoustics.Chief of Naval Operations, Energy and Environmental
Readiness Division, Washington DC. The report was prepared by Oregon State University and
supported under NPS Grant N00244-10-1-0047.Approved for public release; distribution is unlimited
A comparison of methods for detecting right whale calls,â
ABSTRACT North Atlantic, North Pacific, and southern right whales all produce the up call, a frequency-modulated upsweep in the 50-200 Hz range. This call is one of the most common sounds, and frequently the most common sound, received from right whales, and as such is a useful indicator of the presence of right whales for acoustic surveys. A data set was prepared of 1857 calls and 6359 non-call sounds recorded from North Atlantic right whales (Eubalaena glacialis) near Georgia and Massachusetts. Two methods for the detection of the calls were compared: spectrogram correlation and a neural network. Spectrogram correlation parameters were chosen two ways, by manual choice using a sample of 20 calls, and by an optimization procedure that used all available calls. Neural network weights were trained via backpropagation on 9/10 of the test data set. Performance was measured separately for calls of different signal-to-noise ratio, as SNR heavily influences the performance of any detector. Results showed that the neural network performed best at this task, achieving an error rate of less than 6%, and is thus the preferred detection method here. Spectrogram correlation may be useful in situations in which a large set of training data is not available, as manual training on a small set of examples achieved an error rate (26%) that may be acceptable for many applications. SOMMAIRE Les baleines franches de l'Atlantique Nord, du Pacific Nord et Sud produisent toutes une vocalisation montante, soit un balayage ascendant modulĂ© en frĂ©quence dans la rĂ©gion de 50 Ă 200 Hz. Cette vocalisation est un des sons les plus communs produit par les baleines franches et, par le fait mĂȘme, est un indicateur trĂšs utile de la prĂ©sence des baleines lors de sondages acoustiques. Un ensemble de donnĂ©es a Ă©tĂ© prĂ©parĂ© avec 1857 vocalisations et 6359 sons non vocalisĂ©s enregistrĂ©s auprĂšs de baleines franches de l'Atlantique Nord (Eubalaena glacialis) prĂšs de la Georgie et du Massachusetts. Deux mĂ©thodes de dĂ©tection des vocalisations ont Ă©tĂ© comparĂ©es: la corrĂ©lation de spectrogramme et le rĂ©seau neuronal. Les paramĂštres de la corrĂ©lation de spectrogramme ont Ă©tĂ© choisis de deux façons: par choix manuel, en utilisant seulement 20 vocalisations, et par une optimisation de la procĂ©dure utilisant toutes les vocalisations. Les coefficients de pondĂ©ration du rĂ©seau neuronal ont Ă©tĂ© Ă©tabli par rĂ©tropropagation sur 9/10 des donnĂ©es de test. Les performances ont Ă©tĂ© mesurĂ©es sĂ©parĂ©ment pour des vocalisations ayant des rapports signal sur bruit diffĂ©rents, le rapport signal sur bruit ayant une grande influence sur tout dĂ©tecteur. Les rĂ©sultats dĂ©montrent que le rĂ©seau neuronal performe mieux dans ce genre de tĂąche, atteignant un taux d'erreur de moins de 6% et, par consĂ©quent, est dĂ©fini ici comme la meilleure mĂ©thode de dĂ©tection. La corrĂ©lation de spectrogramme peut ĂȘtre utile dans les situations oĂč un grand nombre de donnĂ©es de formation ne sont pas disponibles. Le choix manuel sur de petite tranche d'Ă©chantillons a atteint un taux d'erreur (26%) qui pourrait ĂȘtre acceptable dans plusieurs applications
Recommended from our members
The energy ratio mapping algorithm: A tool to improve the energy-based detection of odontocete echolocation clicks
The energy ratio mapping algorithm (ERMA) was developed to improve the performance of
energy-based detection of odontocete echolocation clicks, especially for application in environments
with limited computational power and energy such as acoustic gliders. ERMA systematically
evaluates many frequency bands for energy ratio-based detection of echolocation clicks produced
by a target species in the presence of the species mix in a given geographic area. To evaluate the
performance of ERMA, a Teager-Kaiser energy operator was applied to the series of energy ratios
as derived by ERMA. A noise-adaptive threshold was then applied to the Teager-Kaiser function to
identify clicks in data sets. The method was tested for detecting clicks of Blainvilleâs beaked
whales while rejecting echolocation clicks of Rissoâs dolphins and pilot whales. Results showed
that the ERMA-based detector correctly identified 81.6% of the beaked whale clicks in an extended
evaluation data set. Average false-positive detection rate was 6.3% (3.4% for Rissoâs dolphins and
2.9% for pilot whales). VC 2011 Acoustical Society of America. [DOI: 10.1121/1.3531924
Detections of whale vocalizations by simultaneously deployed bottom-moored and deep-water mobile autonomous hydrophones
Funding for this work was provided by the Living Marine Resources Program (N39430-14-C-1435 and N39430-14-C-1434), the Office of Naval Research (N00014-15-1-2142, N00014-10-1-0534, and N00014-13-1-0682), and NOAAâs Southwest Fisheries Science Center. SF was supported by the National Science and Engineering Graduate Fellowship.Advances in mobile autonomous platforms for oceanographic sensing, including gliders and deep-water profiling floats, have provided new opportunities for passive acoustic monitoring (PAM) of cetaceans. However, there are few direct comparisons of these mobile autonomous systems to more traditional methods, such as stationary bottom moored recorders. Cross-platform comparisons are necessary to enable interpretation of results across historical and contemporary surveys that use different recorder types, and to identify potential biases introduced by the platform. Understanding tradeoffs across recording platforms informs best practices for future cetacean monitoring efforts. This study directly compares the PAM capabilities of a glider (Seaglider) and a deep-water profiling float (QUEphone) to a stationary seafloor system (High-frequency Acoustic Recording Package, or HARP) deployed simultaneously over a 2 week period in the Catalina Basin, California, United States. Two HARPs were deployed 4 km apart while a glider and deep-water float surveyed within 20 km of the HARPs. Acoustic recordings were analyzed for the presence of multiple cetacean species, including beaked whales, delphinids, and minke whales. Variation in acoustic occurrence at 1-min (beaked whales only), hourly, and daily scales were examined. The number of minutes, hours, and days with beaked whale echolocation clicks were variable across recorders, likely due to differences in the noise floor of each recording system, the spatial distribution of the recorders, and the short detection radius of such a high-frequency, directional signal type. Delphinid whistles and clicks were prevalent across all recorders, and at levels that may have masked beaked whale vocalizations. The number and timing of hours and days with minke whale boing sounds were nearly identical across recorder types, as was expected given the relatively long propagation distance of boings. This comparison provides evidence that gliders and deep-water floats record cetaceans at similar detection rates to traditional stationary recorders at a single point. The spatiotemporal scale over which these single hydrophone systems record sounds is highly dependent on acoustic features of the sound source. Additionally, these mobile platforms provide improved spatial coverage which may be critical for species that produce calls that propagate only over short distances such as beaked whales.Publisher PDFPeer reviewe
Recommended from our members
Repertoire and classification of non-song calls in Southeast Alaskan humpback whales (Megaptera novaeangliae)
On low-latitude breeding grounds, humpback whales produce complex and highly stereotyped
songs as well as a range of non-song sounds associated with breeding behaviors. While on their
Southeast Alaskan foraging grounds, humpback whales produce a range of previously unclassified
non-song vocalizations. This study investigates the vocal repertoire of Southeast Alaskan
humpback whales from a sample of 299 non-song vocalizations collected over a 3-month period on
foraging grounds in Frederick Sound, Southeast Alaska. Three classification systems were used,
including aural spectrogram analysis, statistical cluster analysis, and discriminant function analysis,
to describe and classify vocalizations. A hierarchical acoustic structure was identified; vocalizations
were classified into 16 individual call types nested within four vocal classes. The combined
classification method shows promise for identifying variability in call stereotypy between vocal
groupings and is recommended for future classification of broad vocal repertoires
Recommended from our members
Assessing the cross platform performance of marine mammal indicators between two collocated acoustic recorders
Equipment and deployment strategies for remote passive acoustic sensing of marine environments must balance
memory capacity, power requirements, sampling rate, duty-cycle, deployment duration, instrument size, and environmental
concerns. The impact of different parameters on the data and applicability of the data to the specific
questions being asked should be considered before deployment. Here we explore the effect of recording and detection
parameters on marine mammal acoustic data across two platforms. Daily classifications of marine mammal
vocalizations from two passive acoustic monitors with different subsampling parameters, an AURAL and a
Passive Aquatic Listener (PAL), collocated in the Bering Sea were compared. The AURAL subsampled on a preset
schedule, whereas the PAL sampled via an adaptive protocol. Detected signals of interest were manually classified
in each dataset independently. The daily classification rates of vocalizations were similar. Detections from
the higher duty-cycle but lower sample rate AURAL were limited to species and vocalizations with energy below
4 kHz precluding detection of echolocation signals. Temporal coverage from the PAL audio files was limited by
the adaptive sub-sampling protocol. A method for classifying ribbon (Histriophoca fasciata) and bearded seal
(Erignathus barbatus) vocalizations from the sparse spectral time histories of the PAL was developed. Although
application of the acoustic entropy as a rapid assessment of biodiversity was not reflective of the number of species
detected, acoustic entropy was robust to changes in sample rate and window length.Keywords: Acoustic diversity, Marine mammal classification, Spectral detection, Acoustic entropy, Ocean acousticsKeywords: Acoustic diversity, Marine mammal classification, Spectral detection, Acoustic entropy, Ocean acousticsKeywords: Acoustic diversity, Marine mammal classification, Spectral detection, Acoustic entropy, Ocean acoustic
Recommended from our members
Source levels of foraging humpback whale calls
Humpback whales produce a wide range of low-to mid-frequency vocalizations throughout their migratory range. Non-song "calls" dominate this species' vocal repertoire while on high-latitude foraging grounds. The source levels of 426 humpback whale calls in four vocal classes were estimated using a four-element planar array deployed in Glacier Bay National Park and Preserve, Southeast Alaska. There was no significant difference in source levels between humpback whale vocal classes. The mean call source level was 137 dB(RMS) re 1 mu Pa @ 1m in the bandwidth of the call (range 113-157 dBRMS re 1 mu Pa @ 1m), where bandwidth is defined as the frequency range from the lowest to the highest frequency component of the call. These values represent a robust estimate of humpback whale source levels on foraging grounds and should append earlier estimates. (C) 2018 Acoustical Society of Americ
Extracellular Vesicles from Pseudomonas aeruginosa Suppress MHC-Related Molecules in Human Lung Macrophages
Pseudomonas aeruginosa, a Gram-negative bacterium, is one of the most common pathogens colonizing the lungs of cystic fibrosis patients. P. aeruginosa secrete extracellular vesicles (EVs) that contain LPS and other virulence factors that modulate the host\u27s innate immune response, leading to an increased local proinflammatory response and reduced pathogen clearance, resulting in chronic infection and ultimately poor patient outcomes. Lung macrophages are the first line of defense in the airway innate immune response to pathogens. Proper host response to bacterial infection requires communication between APC and T cells, ultimately leading to pathogen clearance. In this study, we investigate whether EVs secreted from P. aeruginosa alter MHC Ag expression in lung macrophages, thereby potentially contributing to decreased pathogen clearance. Primary lung macrophages from human subjects were collected via bronchoalveolar lavage and exposed to EVs isolated from P. aeruginosa in vitro. Gene expression was measured with the NanoString nCounter gene expression assay. DNA methylation was measured with the EPIC array platform to assess changes in methylation. P. aeruginosa EVs suppress the expression of 11 different MHC-associated molecules in lung macrophages. Additionally, we show reduced DNA methylation in a regulatory region of gene complement factor B (CFB) as the possible driving mechanism of widespread MHC gene suppression. Our results demonstrate MHC molecule downregulation by P. aeruginosa-derived EVs in lung macrophages, which is consistent with an immune evasion strategy employed by a prokaryote in a host-pathogen interaction, potentially leading to decreased pulmonary bacterial clearance
Recommended from our members
Seasonal presence of cetaceans and ambient noise levels in polar waters of the North Atlantic
In 2009 two calibrated acoustic recorders were deployed in polar waters of the North Atlantic to study the seasonal occurrence of blue, fin, and sperm whales and to assess current ambient noise levels. Sounds from these cetaceans were recorded at both locations in most months of the year. During the summer months, seismic airguns associated with oil and gas exploration were audible for weeks at a time and dominated low frequency noise levels. Noise levels might further increase in the future as the receding sea ice enables extended human use of the area.Keywords: underwater sound, acoustic measurement, acoustic nois
Recommended from our members
Sounds from airguns and fin whales recorded in the mid-Atlantic Ocean, 1999-2009
Between 1999 and 2009, autonomous hydrophones were deployed to monitor seismic activity from 16° N to 50° N along the Mid-Atlantic Ridge. These data were examined for airgun sounds produced during offshore surveys for oil and gas deposits, as well as the 20âHz pulse sounds from fin whales, which may be masked by airgun noise. An automatic detection algorithm was used to identify airgun sound patterns, and fin whale calling levels were summarized via long-term spectral analysis. Both airgun and fin whale sounds were recorded at all sites. Fin whale calling rates were higher at sites north of 32° N, increased during the late summer and fall months at all sites, and peaked during the winter months, a time when airgun noise was often prevalent. Seismic survey vessels were acoustically located off the coasts of three major areas: Newfoundland, northeast Brazil, and Senegal and Mauritania in West Africa. In some cases, airgun sounds were recorded almost 4000âkm from the survey vessel in areas that are likely occupied by fin whales, and at some locations airgun sounds were recorded more than 80% days/month for more than 12 consecutive months
- âŠ