A decade of marine mammal acoustical presence and habitat preference in the Bering Sea

Seger, Kerri D.; Miksis‐Olds, Jennifer L.

doi:10.1007/s00300-020-02727-x

Cited by 12 publications

(8 citation statements)

References 63 publications

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“…We used all files that were of good enough quality to manually determine peak and notch patterns to ascribe to a species as well as files from the same day with similarly looking, but poor quality, pulsed signals. The poor quality files as stand-alone signals did not pass quality control guidelines put in place in previous work 2 , 24 , 33 , 34 , but they were recorded close in time to good quality files with more certain IDs. Therefore, they were assigned the same species as a good quality signal.…”

Section: Methodsmentioning

confidence: 78%

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Caller ID for Risso’s and Pacific White-sided dolphins

Al-Badrawi

Liang

Seger³

et al. 2022

Sci Rep

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Tracking species with expanding ranges is crucial to conservation efforts and some typically temperate marine species are spreading northward into the Arctic Ocean. Risso’s (Gg) and Pacific white-sided (Lo) dolphins have been documented spreading poleward. Further, they make very similar sounds, so it is difficult for both human analysts and classification algorithms to tell them apart. Using automatic detectors and classifiers on large acoustic datasets would improve the efficiency of monitoring these species. variational mode decomposition (VMD) provides both an easier visualization tool for human analysts and exhibited robustness to background noise while extracting features in pulsed signals with very similar spectral properties. The goal of this work was to develop a new visualization tool using VMD and a statistics-based classification algorithm to differentiate similar pulsed signals. The proposed VMD method achieved 81% accuracy, even when using audio files with low SNR that did not have concurrent visual survey data. While many dolphins whistle, pulsed signals are one of the more useful vocalizations to use in detection and classification because of their species-specific acoustic features. Automating the VMD method and expanding it to other dolphin species that have very similar pulsed signals would complement current detection and classification methods and lead to a more complete understanding of ecosystem dynamics under a changing climate.

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Section: Methodsmentioning

confidence: 78%

“…Data files from previous work 2 , 33 , 34 that were manually analyzed (visually validated) and found to contain Lo or Gg pulsed signals were used to test the Bayesian VMD Method . No animals were directly involved in this study as all acoustic data were collected passively.…”

Section: Methodsmentioning

confidence: 99%

Caller ID for Risso’s and Pacific White-sided dolphins

Al-Badrawi

Liang

Seger³

et al. 2022

Sci Rep

Self Cite

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“…Data files from previous work 2,41,42 that were manually analyzed (visually validated) and found to contain Lo or Gg pulsed signals were used to test the Bayesian VMD Method. No animals were directly involved in this study as all acoustic data were collected passively.…”

Section: Methods 1 Manual Analysismentioning

confidence: 99%

Caller ID for Risso's and Pacific White-Sided Dolphins

Al-Badrawi

Liang

Seger³

et al. 2021

Preprint

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Climate change affects the distributions of marine mammals1, and some temperate water species are spreading northward into the Arctic Ocean2, 3. Tracking expanding species is crucial to conservation efforts and using automatic detectors and classifiers to track the locations of their vocalizations could help. Risso’s (Gg) and Pacific white-sided (Lo) dolphins were documented spreading poleward2 and make very similar sounds, making it difficult for both human analysts and classification algorithms to tell them apart. Variational Mode Decomposition (VMD) has provided both an easier visualization tool4 for human analysts and offers promising capabilities in separating call types of similar spectral and temporal properties. Here we show a new visualization tool and feature extraction technique using VMD that achieves 81.3% accuracy, even when using audio files with faint signals and high background noise levels and without context clues. Because not all dolphins whistle5–7, being able to distinguish between just their pulsed signals is important for tracking them using as many files as possible from under-sampled areas of the ocean. Automating the VMD method and expanding it to other dolphin species that have very similar pulsive signals will lead to a faster understanding of ecosystem dynamics under a changing climate than can currently be achieved.

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“…Because co‐occurring species often vocalise at different frequencies, if one wishes to detect multiple or all taxa in a given location, it may be necessary to employ multiple types of passive acoustic instruments. These instruments will have different detection biases (Seger & Miksis‐Olds, 2020), although instruments can be designed to perform well across extremely wide frequency ranges (Wiggins & Hildebrand, 2007; Klinck et al ., 2020).…”

Section: Passive Acoustic Sampling and Analysis In An Ecological Contextmentioning

confidence: 99%

Ecological inferences about marine mammals from passive acoustic data

et al. 2023

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Monitoring on the basis of sound recordings, or passive acoustic monitoring, can complement or serve as an alternative to real‐time visual or aural monitoring of marine mammals and other animals by human observers. Passive acoustic data can support the estimation of common, individual‐level ecological metrics, such as presence, detection‐weighted occupancy, abundance and density, population viability and structure, and behaviour. Passive acoustic data also can support estimation of some community‐level metrics, such as species richness and composition. The feasibility of estimation and certainty of estimates is highly context dependent, and understanding the factors that affect the reliability of measurements is useful for those considering whether to use passive acoustic data. Here, we review basic concepts and methods of passive acoustic sampling in marine systems that often are applicable to marine mammal research and conservation. Our ultimate aim is to facilitate collaboration among ecologists, bioacousticians, and data analysts.Ecological applications of passive acoustics require one to make decisions about sampling design, which in turn requires consideration of sound propagation, sampling of signals, and data storage. One also must make decisions about signal detection and classification and evaluation of the performance of algorithms for these tasks. Investment in the research and development of systems that automate detection and classification, including machine learning, are increasing.Passive acoustic monitoring is more reliable for detection of species presence than for estimation of other species‐level metrics. Use of passive acoustic monitoring to distinguish among individual animals remains difficult. However, information about detection probability, vocalisation or cue rate, and relations between vocalisations and the number and behaviour of animals increases the feasibility of estimating abundance or density. Most sensor deployments are fixed in space or are sporadic, making temporal turnover in species composition more tractable to estimate than spatial turnover. Collaborations between acousticians and ecologists are most likely to be successful and rewarding when all partners critically examine and share a fundamental understanding of the target variables, sampling process, and analytical methods.

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A decade of marine mammal acoustical presence and habitat preference in the Bering Sea

Cited by 12 publications

References 63 publications

Caller ID for Risso’s and Pacific White-sided dolphins

Caller ID for Risso’s and Pacific White-sided dolphins

Caller ID for Risso's and Pacific White-Sided Dolphins

Ecological inferences about marine mammals from passive acoustic data

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