Methods are developed for estimating the size/density of cetacean populations using data from a set of fixed passive acoustic sensors The methods convert the number of detected acoustic cues into animal density by accounting for (i) the probability of detecting cues, (ii) the rate at which animals produce cues, and (iii) the proportion of false positive detections Additional information is often required for estimation of these quantities, for example, from an acoustic tag applied to a sample of animals Methods are illustrated with a case study: estimation of Blainville’s beaked whale density over a 6day period in spring 2005, using an 82 hydrophone wide-baseline array located in the Tongue of the Ocean, Bahamas To estimate the required quantities, additional data are used from digital acoustic tags, attached to five whales over 21 deep dives, where cues recorded on some of the dives are associated with those received on the fixed hydrophones Estimated density was 253 or 225 animals/1000km2, depend

/pdf/estimating-cetacean-population-density-using-fixed-passive-2qhtevjdmh.pdf

Estimating cetacean population density using fixed passive acoustic sensors: an example with Blainville's beaked whales.

Fixed autonomous acoustic recording devices (autonomous recorders [ARs]) are defined as any electronic recording system that acquires and stores acoustic data internally (i.e., without a cable or radio link to transmit data to a receiving station), is deployed semi-permanently underwater (via a mooring, buoy, or attached to the sea floor), and must be retrieved to access the data. More than 30 ARs were reviewed. They varied greatly in capabilities and costs, from small, hand-deployable units for detecting dolphin and porpoise clicks in shallow water to larger units that can be deployed in deep water and can record at high-frequency bandwidths for over a year, but must be deployed from a large vessel. The capabilities and limitations of the systems reviewed herein are discussed in terms of their effectiveness in monitoring and studying marine mammals.

A Review and Inventory of Fixed Autonomous Recorders for Passive Acoustic Monitoring of Marine Mammals

The North Atlantic right whale Eubalaena glacialis is endangered, in part, due to vessel- strike mortality. We use vessel traffic and right whale survey data (~3 nautical miles (n miles), ~5.6 km resolution) for the Bay of Fundy and on the Scotian Shelf (northwest Atlantic) to determine the relative risk of lethal vessel encounters by using 2 estimates: (1) the event — the relative proba- bility of a vessel encountering a right whale, and (2) the consequence — the probability of a lethal injury arising from an encounter. For the Bay of Fundy region our estimates demonstrate that the rel- ative risk of lethal collision could be reduced by 62% by means of an amendment to the traffic sepa- ration scheme (TSS) that intersects a Right Whale Conservation Area. In the Roseway Basin region of the Scotian Shelf, the majority of vessels navigate outside of a Right Whale Conservation Area, although the highest relative risk is concentrated within the Conservation Area where fewer vessels navigate at greater speed. Here, our estimates demonstrate that a seasonal recommendatory area to be avoided (ATBA) could be designed to reduce the risk imposed by vessels upon right whales in the region. Our estimates contributed to the International Maritime Organisation (IMO) adoption of a TSS amendment in the Bay of Fundy and an ATBA on the Scotian Shelf. Thus, the goal of achieving the greatest reduction in the risk of lethal vessel-encounters with whales, balanced by some minimal disruption to vessel operations while maintaining safe navigation, can be achieved.

/pdf/reducing-the-risk-of-lethal-encounters-vessels-and-right-4ah09czys1.pdf

Reducing the risk of lethal encounters: vessels and right whales in the Bay of Fundy and on the Scotian Shelf

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.

http://lenthomas.org/papers/KuselJASA2011.pdf

Cetacean population density estimation from single fixed sensors using passive acoustics.

Covering about three quarters of the surface area of the earth, the ocean is a critical source of sustenance, medicine, and commerce. However, such vast expanse in both surface area and depth, presents myriad observing challenges for researchers, such as corrosion, attenuation of electromagnetic waves, and high pressure. Ocean observation technologies are progressing from the conventional single node, static and short-term modalities to multiple nodes, dynamic and long-term modalities, to increase the density of both temporal and spatial samplings. Although people’s knowledge of the oceans has been still quite limited, the contributions of many nations cooperating to develop the Global Ocean Observing System (GOOS) have remarkably promoted the development of ocean observing technologies. This paper reviews the typical observing technologies deployed from the sea surface to the seafloor, and discusses the future trend of the ocean observation systems with the docking technology and sustained ocean energy.

/pdf/ocean-observation-technologies-a-review-4r8klrig7c.pdf

Ocean Observation Technologies: A Review

A year-long acoustic survey for critically endangered North Atlantic right whales was conducted at two sites on the central and western Scotian Shelf Autonomous hydrophones recorded sound continuously from July 2004 to August 2005 Right whale contact calls (upcalls) were identified using automatic recognition software, and the resulting detections were checked manually Substantial numbers of hours with upcalls were observed at both sites, with approximately four times as many hours with calls at the western site as the central one Calls occurred mainly from August through October, with the earliest calls in late June and the latest at the end of December at both sites In addition to this seasonal trend, there was a significant diel pattern in calling at the central site but not at the more westerly site Results are analyzed in light of feeding ecology and broad-scale movements of right whales

Seasonal occurrence of north atlantic right whale (Eubalaena Glacialis) vocalizations at two sites on the scotian shelf

/pdf/ambient-sound-at-challenger-deep-mariana-trench-3wxfl9gmws.pdf

Ambient Sound at Challenger Deep, Mariana Trench

Automated methods for marine mammal passive acoustic research reach back at least 33 years, when Clark (1980) developed a direction-finding device to locate southern right whales. Automated methods soon became essential to the field, as rapid advances in technology and methodology led to huge volumes of passive-acoustic data, too large for convenient or timely manual analysis. By the early 2000s, automated passive acoustic research and monitoring had become widespread, used worldwide by academic, industrial, governmental, and independent researchers and agencies. Development of automated analytical tools for detection, classification and localization (DCL) of marine mammals from acoustic data was blossoming into an independent field of research. By 2003, the DCL research community had grown large enough to warrant the organization of the first International Workshop on Detection, Classification, and Localization of Marine Mammals using Passive Acoustics. The first workshop, organized by Francine Desharnais in Halifax, NS, Canada, focused on right whales (Eubalaena spp.). This workshop established the precedent of publishing a dataset before the meeting, a dataset to be used by workshop participants competing in the development of the best detection method. The result was the presentation of many novel techniques for detection and localization of right whale calls, and a broad education for all participants about the wide variety of research methods that might work best for this task. It also resulted in the publication of a special issue of Canadian Acoustics devoted to peer-reviewed papers from the workshop (Desharnais and Hay, 2004). The second workshop, organized by Olivier Adam and held in Monaco in 2005, focused on sperm whales (Physeter macrocephalus). Many of the practices of the first workshop were repeated, thus establishing several traditions for these workshops: Holding the workshop every other year (in oddnumbered years); alternating workshop locations between North America and Europe; publishing a workshop dataset some months before the workshop and holding a competition to see which methods had the best performance with this dataset; and publishing many of the results presented at the workshop in a special issue of a journal. The special issue related to the 2005 workshop appeared in Applied Acoustics (Adam et al., 2006). The third workshop, held in Boston in 2007 and organized by Dave Moretti, repeated and furthered the above traditions. Its focal species was Blainville’s beaked whale (Mesoplodon densirostris), and the corresponding special journal issue was in Canadian Acoustics (Moretti et al., 2008). The fourth workshop was organized by Gianni Pavan and held in Pavia, Italy in September 2009. It focused on Cuvier’s beaked whale (Ziphius cavirostris), with the special journal issue appearing in Applied Acoustics (Pavan et al., 2010). The fifth workshop was held at Mt. Hood, OR, in 2011, and was organized by the authors of this paper at Oregon State University. The focus was the detection and classification of odontocete sounds, including both whistles and clicks. This workshop was the first to focus on multiple components of odontocete vocalizations. It was at this workshop that the idea of a special issue of JASA devoted to methods for marine mammal passive acoustics was introduced and subsequently accepted. Since the first workshop 10 years ago, the field has changed in many ways. Machine learning methods, many derived from research in speech recognition or machine vision, have become widespread and prominent in detection and classification. Localization methods have incorporated acoustic propagation codes to obtain higher levels of localization accuracy. Methods for population density estimation (DE) have become important in the field, to the extent that the workshop is no longer “the DCL workshop” but rather has become “the DCLDE workshop.” Methods have changed from research topics into practical systems for everyday use. Implementations of detection and classification methods have been developed for networked systems capable of handling hundreds of hydrophones in real time. Many of these advances are related in the papers in this special issue, and we hope you find them interesting and informative. We, the guest editors, would like to thank the JASA editorial staff, particularly Allan Pierce, Editor-in-Chief for assistance in assembling and editing this special issue. We would like to thank the Office of Naval Research for supporting this special issue, and for longstanding support of the DCLDE workshops. We would also like to thank all of the authors who have contributed such high-quality articles that make this issue a truly special one.

Introduction to the special issue on methods for marine mammal passive acoustics.

An array of seven autonomous hydrophones, deployed within 12 N 8S and 95 110W, continuously recorded the frequency band 1–110 Hz from November 1999 to November 2001. Four low frequency sound types were observed, similar to Brydes whale vocalizations previously reported [E. Oleson et al., Mar. Mammal. Sci. 19, 407–419 (2003)]. Two averaged 2.5‐s duration and were commonly high amplitude sounds that exceeded the sampling frequency. Both had a distinct tone averaging 18.6 and 25.4 Hz, respectively, several frequency‐modulated higher tones that resembled harmonics but were not, and often an initial short broad band pulse which overlapped the tonal components. Two were lower amplitude sounds that typically began with a single constant‐frequency upper tone, averaging 36.6 Hz, 1.1‐s duration, and 28.7 Hz, 1.1‐s duration, respectively. Sometimes, an overlapping lower tone followed 0.7 s later, lasting 1.6 s and averaging 21.4 and 15.3 Hz, respectively. Occasionally the upper and lower tones alternated two or more times, with decreasing amplitude on each repetition. Differences in seasonal occurrence and geographic distribution amongst the four types were found. These results support the use of passive acoustics as a technique for examining existing and proposed stock definitions.

Brydes whale (balaenoptera edeni) sounds collected from autonomous hydrophones in the eastern tropical Pacific, 1999–2001

Automatic detection of animal vocalizations is now used widely for handling long‐duration recording. Automatic detection methods inevitably make some errors—both false positive (wrong detection) and false negative (missed call) errors. Here a system is described for checking these errors. The MATLAB system “Osprey” allows viewing spectrograms, manipulating their parameters, and making various measurements of the displayed sounds. Another program, “checkDetections”, takes a log file that was output by an automatic detection software and systematically displays the detected sound in Osprey, allows a user to indicate whether the detection is correct, and then skips to the next detection in the log. This allows for rapid checking of detected sounds and calculation of the false‐positive (wrong‐detection) error rate. A second system, “checkMissedCalls”, displays random segments of sound in which no calls were found and allows the user to check whether there really were calls. This allows the user to estimate th...

Software for viewing and checking automatic detections.

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