Underwater Soundscape Monitoring and Fish Bioacoustics: A Review

Lindseth, Adelaide V.; Lobel, Phillip S.

doi:10.3390/fishes3030036

Cited by 99 publications

(80 citation statements)

References 92 publications

(221 reference statements)

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“…They can loosely be divided into 2 categories: direct observation and remote observation. For example, vessel monitoring systems and bioacoustics are used extensively to monitor fish and fisheries (Gerritsen & Lordan, Hogan et al , ; Lindseth & Lobel, ). Increasingly data from earth observation is finding its place in global monitoring systems and although fish are below the surface, there are surrogates of fishing activity and production that have more recently been used to estimate fishing pressure and fish abundance, such as the presence of boats and traps (Al‐Abdulrazzak & Pauly, ) and indicators of primary production (Deines et al, ), respectively.…”

Section: Monitoring Tools: Strengths Weaknesses and Trade‐offsmentioning

confidence: 99%

Section: Monitoring Tools: Strengths Weaknesses and Trade-offsmentioning

confidence: 99%

See 1 more Smart Citation

Monitoring of tropical freshwater fish resources for sustainable use

Elliott

Phen

et al. 2019

Journal of Fish Biology

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Tropical freshwater ecosystems are some of the world's most biodiverse and productive systems where determining what sustainable exploitation of inland fisheries looks like is particularly challenging. One of the greatest obstacles to sustainable management is collecting and using quality data on fish production and yield. The biodiversity and hydro‐ecology of these systems often under open‐access governance, add to the complexity of managing them. This paper describes an integrated citizen‐science, earth observation, environmental DNA and independent survey approach to collecting fish and fisheries data, using the Cambodian Mekong as a case study.

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Section: Monitoring Tools: Strengths Weaknesses and Trade‐offsmentioning

confidence: 99%

Section: Monitoring Tools: Strengths Weaknesses and Trade-offsmentioning

confidence: 99%

Monitoring of tropical freshwater fish resources for sustainable use

Elliott

Phen

et al. 2019

Journal of Fish Biology

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“…where A 1 (t) and A 2 (t) are the probability mass functions of the amplitude envelope of the two acoustic files under comparison, and S 1 (f ) and S 2 (f ) are the probability mass functions of the mean spectrum. The acoustic complexity index (ACI) was proposed in 2008 by Farina and Morri [77] and represents one of the most utilized ecoacoustic metrics since the first edition in 2011 [78]. The ACI measures the amount of (syntactic) information of a matrix of sound amplitude obtained after the application of a fast Fourier transform (FFT) on an acoustic file.…”

Section: Complexity Indicesmentioning

confidence: 99%

Ecoacoustics: A Quantitative Approach to Investigate the Ecological Role of Environmental Sounds

Farina

2018

Mathematics

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Ecoacoustics is a recent ecological discipline focusing on the ecological role of sounds. Sounds from the geophysical, biological, and anthropic environment represent important cues used by animals to navigate, communicate, and transform unknown environments in well-known habitats. Sounds are utilized to evaluate relevant ecological parameters adopted as proxies for biodiversity, environmental health, and human wellbeing assessment due to the availability of autonomous audio recorders and of quantitative metrics. Ecoacoustics is an important ecological tool to establish an innovative biosemiotic narrative to ensure a strategic connection between nature and humanity, to help in-situ field and remote-sensing surveys, and to develop long-term monitoring programs. Acoustic entropy, acoustic richness, acoustic dissimilarity index, acoustic complexity indices (ACItf and ACIft and their evenness), normalized difference soundscape index, ecoacoustic event detection and identification routine, and their fractal structure are some of the most popular indices successfully applied in ecoacoustics. Ecoacoustics offers great opportunities to investigate ecological complexity across a full range of operational scales (from individual species to landscapes), but requires an implementation of its foundations and of quantitative metrics to ameliorate its competency on physical, biological, and anthropic sonic contexts.

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“…In aquatic studies, remote underwater video has allowed more efficient, extensive and less biased sampling than diver-based surveys (Mallet and Pelletier 2014; King et al 2018). Similarly, with the aid of automatic identification algorithms, acoustic detectors are becoming a more accessible and popular tool for studying and monitoring a variety of taxa such as whales and dolphins (Zimmer 2011), birds (Johnson and Tyack 2003;Celis-Murillo et al 2009;Blumstein et al 2011;Klinck et al 2012), echolocating bats (Marques et al 2013;Walters et al 2013;Bader et al 2015), and even fishes that produce species-specific sounds (Luczkovich et al 2008;Lindseth and Lobel 2018;Gibb et al 2019). In every case, the technologies, software and analysis methods are constantly evolving (Burton et al 2015).…”

Section: Introductionmentioning

confidence: 99%

Estimating animal density in three dimensions using capture‐frequency data from remote detectors

Soto

Castañeda

Mandrak

et al. 2020

Remote Sens Ecol Conserv

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Remote detectors are being used increasingly often to study aquatic and aerial species, which move significantly differently from terrestrial species. Camera-trapping studies have used frameworks based on animal movement patterns to show that a species' detection frequency, along with movement speed and detector specifications, can be used to estimate absolute population density. This approach, however, has not yet been adapted to cases where movement is threedimensional. Here we adapt one such framework to three-dimensional movement, to characterize the relationship between population density, animal speed, characteristics of a remote sensor's detection zone and detection frequency. The derivation involves defining the detection zone mathematically and calculating the mean area of the profile it presents to approaching individuals. We developed two variants of the model-one assuming random movement of all individuals, and one allowing for different probabilities for each approach direction (e.g. that animals more often swim/fly horizontally than vertically). We used computer simulations to evaluate model performance for a wide range of animal and detector densities. Simulations show that in ideal conditions the method approximates true density well, and that estimates become increasingly accurate using more detectors, or sampling for longer. Moreover the method is robust to violations of assumptions, accuracy is decreased only in extreme cases where all detectors are facing the same way. We provide equations for estimating population density from detection frequency and outline how to estimate the necessary parameters. We discuss how environmental variables and species-specific characteristics affect parameter estimates and how to account for these differences in density estimations. Our method can be applied to common remote detection methods (cameras and acoustic detectors), which are currently being used to study a diversity of species and environments. Therefore, our work may significantly expand the number and diversity of species for which density can be estimated.

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Underwater Soundscape Monitoring and Fish Bioacoustics: A Review

Cited by 99 publications

References 92 publications

Monitoring of tropical freshwater fish resources for sustainable use

Monitoring of tropical freshwater fish resources for sustainable use

Ecoacoustics: A Quantitative Approach to Investigate the Ecological Role of Environmental Sounds

Estimating animal density in three dimensions using capture‐frequency data from remote detectors

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