Sound Production by Mulloway (Argyrosomus japonicus) and Variation Within Individual Calls

Parsons, Miles; McCauley, Robert D.

doi:10.1007/s40857-017-0112-9

Cited by 5 publications

(9 citation statements)

References 21 publications

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“…The SLT shows distinct components, and overall, the structure it shows bears the closest resemblance to the description by Parsons et al. ( 2013 ).…”

Section: Discussionsupporting

confidence: 75%

BASSA: New software tool reveals hidden details in visualisation of low‐frequency animal sounds

Jancovich,

Rogers

2024

Ecology and Evolution

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The study of animal sounds in biology and ecology relies heavily upon time–frequency (TF) visualisation, most commonly using the short‐time Fourier transform (STFT) spectrogram. This method, however, has inherent bias towards either temporal or spectral details that can lead to misinterpretation of complex animal sounds. An ideal TF visualisation should accurately convey the structure of the sound in terms of both frequency and time, however, the STFT often cannot meet this requirement. We evaluate the accuracy of four TF visualisation methods (superlet transform [SLT], continuous wavelet transform [CWT] and two STFTs) using a synthetic test signal. We then apply these methods to visualise sounds of the Chagos blue whale, Asian elephant, southern cassowary, eastern whipbird, mulloway fish and the American crocodile. We show that the SLT visualises the test signal with 18.48%–28.08% less error than the other methods. A comparison between our visualisations of animal sounds and their literature descriptions indicates that the STFT's bias may have caused misinterpretations in describing pygmy blue whale songs and elephant rumbles. We suggest that use of the SLT to visualise low‐frequency animal sounds may prevent such misinterpretations. Finally, we employ the SLT to develop ‘BASSA’, an open‐source, GUI software application that offers a no‐code, user‐friendly tool for analysing short‐duration recordings of low‐frequency animal sounds for the Windows platform. The SLT visualises low‐frequency animal sounds with improved accuracy, in a user‐friendly format, minimising the risk of misinterpretation while requiring less technical expertise than the STFT. Using this method could propel advances in acoustics‐driven studies of animal communication, vocal production methods, phonation and species identification.

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“…The SLT shows distinct components, and overall, the structure it shows bears the closest resemblance to the description by Parsons et al. ( 2013 ).…”

Section: Discussionsupporting

confidence: 75%

BASSA: New software tool reveals hidden details in visualisation of low‐frequency animal sounds

Jancovich,

Rogers

2024

Ecology and Evolution

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“…The temporal patterns, or rhythms, which can be compared to acoustic barcodes, contain information for discriminating sound types and eventually species. Thus, analyses of a signal's temporal pattern can be very effective for evaluating the behaviour and species composition of soniferous fish [ 214 ], though this can be non-trivial if the species have large vocal repertoires [ 165 , 152 ]. Key advances from marine mammal research, such as spectrogram correlation and parametrizing and grouping spectral peaks, may provide some important tools [ 173 , 215 ].…”

Section: Current Methods Supporting Acoustic Diversity Assessmentsmentioning

confidence: 99%

“…Open Sci. 7: 201287 across breeding seasons [150][151][152][153]. A chorus can mask the individual, often lower-level, transient sounds and thus will often reduce the detectability of many signals and the overall acoustic diversity.…”

Section: Mass Phenomenamentioning

confidence: 99%

Listening forward: approaching marine biodiversity assessments using acoustic methods

Mooney

Iorio

Lammers³

et al. 2020

R. Soc. open sci.

108

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Ecosystems and the communities they support are changing at alarmingly rapid rates. Tracking species diversity is vital to managing these stressed habitats. Yet, quantifying and monitoring biodiversity is often challenging, especially in ocean habitats. Given that many animals make sounds, these cues travel efficiently under water, and emerging technologies are increasingly cost-effective, passive acoustics (a long-standing ocean observation method) is now a potential means of quantifying and monitoring marine biodiversity. Properly applying acoustics for biodiversity assessments is vital. Our goal here is to provide a timely consideration of emerging methods using passive acoustics to measure marine biodiversity. We provide a summary of the brief history of using passive acoustics to assess marine biodiversity and community structure, a critical assessment of the challenges faced, and outline recommended practices and considerations for acoustic biodiversity measurements. We focused on temperate and tropical seas, where much of the acoustic biodiversity work has been conducted. Overall, we suggest a cautious approach to applying current acoustic indices to assess marine biodiversity. Key needs are preliminary data and sampling sufficiently to capture the patterns and variability of a habitat. Yet with new analytical tools including source separation and supervised machine learning, there is substantial promise in marine acoustic diversity assessment methods.

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“…Putland et al (2018) localised individual oyster toadfish in two dimensions (2D) using a 20 m long linear array fixed to a dock. Parsons et al (2009, 2010) and Locascio and Mann (2011) conducted finer scale three‐dimensional (3D) localisation and monitored individual fish in aggregations. Gervaise et al (2019), Ferguson and Cleary (2001) and Too et al (2019) also performed fine‐scale acoustic localisation on sounds produced by invertebrates.…”

Section: Introductionmentioning

confidence: 99%

Identification of fish sounds in the wild using a set of portable audio‐video arrays

et al. 2023

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Associating fish sounds to specific species and behaviours is important for making passive acoustics a viable tool for monitoring fish. While recording fish sounds in tanks can sometimes be performed, many fish do not produce sounds in captivity. Consequently, there is a need to identify fish sounds in situ and characterise these sounds under a wide variety of behaviours and habitats. We designed three portable audio‐video platforms capable of identifying species‐specific fish sounds in the wild: a large array, a mini array and a mobile array. The large and mini arrays are static autonomous platforms than can be deployed on the seafloor and record audio and video for one to two weeks. They use multichannel acoustic recorders and low‐cost video cameras mounted on PVC frames. The mobile array also uses a multichannel acoustic recorder, but mounted on a remotely operated vehicle with built‐in video, which allows remote control and real‐time positioning in response to observed fish presence. For all arrays, fish sounds were localised in three dimensions and matched to the fish positions in the video data. We deployed these three platforms at four locations off British Columbia, Canada. The large array provided the best localisation accuracy and, with its larger footprint, was well suited to habitats with a flat seafloor. The mini and mobile arrays had lower localisation accuracy but were easier to deploy, and well suited to rough/uneven seafloors. Using these arrays, we identified, for the first time, sounds from quillback rockfish Sebastes maliger, copper rockfish Sebastes caurinus and lingcod Ophiodon elongatus. In addition to measuring temporal and spectral characteristics of sounds for each species, we estimated mean source levels for lingcod and quillback rockfish sounds (115.4 and 113.5 dB re 1 μPa, respectively) and maximum detection ranges at two sites (between 10.5 and 33 m). All proposed array designs successfully identified fish sounds in the wild and were adapted to various budget, logistical and habitat constraints. We include here building instructions and processing scripts to help users replicate this methodology, identify more fish sounds around the world and make passive acoustics a more viable way to monitor fish.

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Sound Production by Mulloway (Argyrosomus japonicus) and Variation Within Individual Calls

Cited by 5 publications

References 21 publications

BASSA: New software tool reveals hidden details in visualisation of low‐frequency animal sounds

BASSA: New software tool reveals hidden details in visualisation of low‐frequency animal sounds

Listening forward: approaching marine biodiversity assessments using acoustic methods

Identification of fish sounds in the wild using a set of portable audio‐video arrays

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