Software for real-time localization of baleen whale calls using directional sonobuoys: A case study on Antarctic blue whales

Miller, Brian; Calderan, Susannah; Gillespie, Douglas; Weatherup, Graham; Leaper, Russell; Collins, Kym; Double, Michael C.

doi:10.1121/1.4943627

Cited by 14 publications

(7 citation statements)

References 22 publications

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“…Call recognition and pre‐processing was done using pamguard (version 1.11.00 BETA; Miller et al . ; http://www.pamguard.org), which also allowed us to check recognitions. Arthroleptella lightfooti calls consist of three pulses that make up a single note and are identified as a single frog call using a click detector in pamguard (see Stevenson et al .…”

Section: Methodsmentioning

confidence: 99%

Counting chirps: acoustic monitoring of cryptic frogs

Measey

Stevenson

Scott

et al. 2016

Journal of Applied Ecology

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Summary1. Global amphibian declines have resulted in a vital need for monitoring programmes that follow population trends. Monitoring using advertisement calls is ideal as choruses are undisturbed during data collection. However, methods currently employed by managers frequently rely on trained observers and/or do not provide density data on which to base trends. 2. This study explores the utility of monitoring using acoustic spatially explicit capturerecapture (aSCR) with time of arrival (ToA) and signal strength (SS) as a quantitative monitoring technique to measure call density of a threatened but visually cryptic anuran, the Cape peninsula moss frog Arthroleptella lightfooti. 3. The relationships between temporal and climatic variables (date, rainfall, temperature) and A. lightfooti call density at three study sites on the Cape peninsula, South Africa, were examined. Acoustic data, collected from an array of six microphones over 4 months during the winter breeding season, provided a time series of call density estimates. 4. Model selection indicated that call density was primarily associated with seasonality fitted as a quadratic function. Call density peaked mid-breeding season. At the main study site, the lowest recorded mean call density (0Á160 calls m À2 min À1 ) occurred in May and reached its peak mid-July (1Á259 calls m À2 min À1 ). The sites differed in call density, but also the effective sampling area. 5. Synthesis and applications. The monitoring technique, acoustic spatially explicit capturerecapture (aSCR), quantitatively estimates call density of calling animals without disturbing them or their environment. In addition, time of arrival (ToA) and signal strength (SS) data significantly add to the accuracy of call localization, which in turn increases precision of call density estimates without the need for specialist field staff. This technique appears ideally suited to aid the monitoring of visually cryptic, acoustically active species.

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Section: Methodsmentioning

confidence: 99%

Counting chirps: acoustic monitoring of cryptic frogs

Measey

Stevenson

Scott

et al. 2016

Journal of Applied Ecology

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“…Through IWC-SORP, the Acoustic Trends Project working group has built upon the pioneering work done in the first decade of the twenty-first century, and has fostered an increasing number of passive acoustic studies focusing on the calls of Antarctic blue whales and to a lesser extent fin whales across broad time and spatial scales, as well as acoustic data processing and analysis methodology. The data from these studies have been collected both from ships during Antarctic voyages and from long-term moored recording devices 4, [14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30][31] . The project working group presently (as of March 2020) has access to more than 300,000 h of passive acoustic data that have been collected throughout the Southern Ocean over the past 20 years.…”

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confidence: 99%

An open access dataset for developing automated detectors of Antarctic baleen whale sounds and performance evaluation of two commonly used detectors

Miller

Stafford²,

Opzeeland³

et al. 2021

Sci Rep

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Since 2001, hundreds of thousands of hours of underwater acoustic recordings have been made throughout the Southern Ocean south of 60° S. Detailed analysis of the occurrence of marine mammal sounds in these circumpolar recordings could provide novel insights into their ecology, but manual inspection of the entirety of all recordings would be prohibitively time consuming and expensive. Automated signal processing methods have now developed to the point that they can be applied to these data in a cost-effective manner. However training and evaluating the efficacy of these automated signal processing methods still requires a representative annotated library of sounds to identify the true presence and absence of different sound types. This work presents such a library of annotated recordings for the purpose of training and evaluating automated detectors of Antarctic blue and fin whale calls. Creation of the library has focused on the annotation of a representative sample of recordings to ensure that automated algorithms can be developed and tested across a broad range of instruments, locations, environmental conditions, and years. To demonstrate the utility of the library, we characterise the performance of two automated detection algorithms that have been commonly used to detect stereotyped calls of blue and fin whales. The availability of this library will facilitate development of improved detectors for the acoustic presence of Southern Ocean blue and fin whales. It can also be expanded upon to facilitate standardization of subsequent analysis of spatiotemporal trends in call-density of these circumpolar species.

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“…Erbs et al, 2017; Keating et al, 2015) and vocalisations of baleen whales (e.g. Miller et al, 2016). Gillespie et al (2013) reported a recall of 88% (the percentage of manual detections which were detected automatically).…”

Section: Discussionmentioning

confidence: 99%

Streamlining analysis methods for large acoustic surveys using automatic detectors with operator validation

Webber

Gillespie

Lewis³

et al. 2022

Methods Ecol Evol

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Passive acoustic surveys are becoming increasingly popular as a means of surveying for cetaceans and other marine species. These surveys yield large amounts of data, the analysis of which is time consuming and can account for a substantial proportion of the survey budget. Semi‐automatic processes enable the bulk of processing to be conducted automatically while allowing analyst time to be reserved for validating and correcting detections and classifications. Existing modules within the Passive Acoustic Monitoring software PAMGuard were used to process a large (25.4 Terabyte) dataset collected during towed acoustic ship transits. The recently developed ‘Multi‐Hypothesis Tracking Click Train Detector’ and the ‘Whistle and Moan Detector’ modules were used to identify occasions within the dataset at which vocalising toothed whales (odontocetes) were likely to be acoustically present. These putative detections were then reviewed by an analyst, with false positives being corrected. Target motion analysis provided a perpendicular distance to odontocete click events enabling the estimation of detection functions for both sperm whales and delphinids. Detected whistles were assigned to the lowest taxonomical level possible using the PAMGuard ‘Whistle Classifier’ module. After an initial tuning process, this semi‐automatic method required 91 hr of an analyst's time to manually review both automatic click train and whistle detections from 1,696 hr of survey data. Use of the ‘Multi‐Hypothesis Tracking Click Train Detector’ reduced the amount of data for the analyst to search by 74.5%, while the ‘Whistle and Moan Detector’ reduced data to search by 85.9%. In total, 443 odontocete groups were detected, of which 55 were from sperm whale groups, six were from beaked whales, two were from porpoise and the remaining 380 were identified to the level of delphinid group. An effective survey strip half width of 3,277 and 699 m was estimated for sperm whales and delphinids respectively. The semi‐automatic workflow proved successful, reducing the amount of analyst time required to process the data, significantly reducing overall project costs. The workflow presented here makes use of existing modules within PAMGuard, a freely available and open‐source software, readily accessible to acoustic analysts.

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Software for real-time localization of baleen whale calls using directional sonobuoys: A case study on Antarctic blue whales

Cited by 14 publications

References 22 publications

Counting chirps: acoustic monitoring of cryptic frogs

Counting chirps: acoustic monitoring of cryptic frogs

An open access dataset for developing automated detectors of Antarctic baleen whale sounds and performance evaluation of two commonly used detectors

Streamlining analysis methods for large acoustic surveys using automatic detectors with operator validation

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