Hearing in Marine Fish and Its Application in Fisheries

Yan, Hong; Anraku, Kazuhiko; Babaran, Ricardo P.

doi:10.1002/9780813810966.ch3

Cited by 32 publications

(7 citation statements)

References 52 publications

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“…Boat noise alone is neither attractive nor repellent (equal trapping). There are a number of acoustic fishing techniques (see Yan et al ) that have been developed around the world, testifying to the inability of fish to adaptively respond to human‐made sounds. Although anthropogenic sounds could easily add information on dangerous locations or provide navigational cues to fishes (see below), in most cases it is likely that anthropogenic sounds are only detrimental to fish behavior.…”

Section: Discussionmentioning

confidence: 99%

“…Human actions sometimes create ecologically relevant perceptual objects that fish interact with, generally in a predator–prey context (often ending badly for the fish). In such cases, human activities form sources in the traditional sense, perhaps as cues for escape or as deliberate attempts to manipulate behavior for fishing (Yan et al ) or guide migration (Simpson et al ). The more dramatic human contribution to the noise levels in the aquatic soundscape is both more widespread and more devastating.…”

Section: Discussionmentioning

confidence: 99%

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Signals and noise in the octavolateralis systems: What is the impact of human activities on fish sensory function?

Braun

2015

Integrative Zoology

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The octavolateralis systems of fishes include the vestibular, auditory, lateral line and electrosensory systems. They are united by common developmental and neuro-computational features, including hair cell sensors and computations based on cross-neuron analyses of differential hair cell stimulation patterns. These systems also all use both spectral and temporal filters to separate signals from each other and from noise, and the distributed senses (lateral line and electroreception) add spatial filters as well. Like all sensory systems, these sensors must provide the animal with guidance for adaptive behavior within a sensory scene composed of multiple stimuli and varying levels of ambient noise, including that created by human activities. In the extreme, anthropogenic activities impact the octavolateralis systems by destroying or degrading the habitats that provide ecological resources and sensory inputs. At slightly lesser levels of effect, anthropogenic pollutants can be damaging to fish tissues, with sensory organs often the most vulnerable. The exposed sensory cells of the lateral line and electrosensory systems are especially sensitive to aquatic pollution. At still lesser levels of impact, anthropogenic activities can act as both acute and chronic stressors, activating hormonal changes that may affect behavioral and sensory function. Finally, human activities are now a nearly ubiquitous presence in aquatic habitats, often with no obvious effects on the animals exposed to them. Ship noise, indigenous and industrial fishing techniques, and all the ancillary noises of human civilization form a major part of the soundscape of fishes. How fish use these new sources of information about their habitat is a new and burgeoning field of study.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Signals and noise in the octavolateralis systems: What is the impact of human activities on fish sensory function?

Braun

2015

Integrative Zoology

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“…Both the fish inner ear and the lateral line are likely to play an integrative role in perceiving ʻacoustic' stimuli (Young Yan et al, 2010;Higgs and Radford, 2013), with the contributions of each being difficult to differentiate (Braun and Coombs, 2000;Webb et al, 2008;Mirjany et al, 2011). In order to avoid potential confounding effects related to the lateral line system and to specifically investigate the effect of otolith-related hearing, mechanoreceptors from the lateral lines were chemically inhibited.…”

Section: Chemical Ablation Of the Lateral Linementioning

confidence: 99%

Functional effect of vaterite – the presence of an alternative crystalline structure in otoliths alters escape kinematics of the brown trout

Vignon

2020

Journal of Experimental Biology

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The fast-start escape response is the main locomotor behaviour observed in fish to evade predatory attacks and thereby increase their probability of survival. Thus far, this high-speed sensory motor control has been extensively studied in relation to extrinsic factors. In contrast, there has been surprisingly little consideration of intrinsic individual factors that can mediate sensorial perception, such as interindividual variability in mechanosensory systems. The inner ear of teleost fishes is composed of otoliths that play an important role in hearing and balance functions. While sagittal otoliths are normally composed of aragonite in many fish species, the inclusion of vaterite (an abnormal crystalline structure) has been reported in a number of individuals from different environments. There is currently strong theoretical and empirical evidence that vaterite deposition has a negative impact on auditory sensitivity in fishes. While the functional/ behavioural implications of this defect on otolith-related hearing function has been hypothesised, it has remained largely untested experimentally. Here, using juvenile (0+ years) Salmo trutta originating from the wild in experimental conditions, we report for the first time that the deposition of calcium carbonate in its crystalline vateritic polymorph has significant pervasive effects on the escape kinematics of fish. The presence of an alternative crystalline structure in otoliths is likely to alter fish behaviour in ways that decrease survival. We also report that altered behaviour in individuals with vateritic otoliths is partially compensated for by the presence of a functional lateral line. Such functional compensation suggests more slight consequences, if any, in the wild.

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“…Innovations in gear selectivity continue to bring in new types of selection and bycatch reduction devices added to gear designs (e.g., for review of selective and bycatch reductions devices, see Vogel, 2016;Matt et al, 2021; for grid, see Brinkhof et al, 2020, for mesh size: Kim et al, 2008;Aydin and Tosunòlu, 2010;Cuende et al, 2020b;Cuende et al, 2022, for panels: Bullough et al, 2007Ferro et al, 2007). By observing the influence of these modifications, finer selectivity patterns have been unraveled, highlighting how the visual, hearing and tactile cues that species are sensitive to are key in the capture process of fishes (Arimoto et al, 2010;Yan et al, 2010). As studies in fish vision show differences in behavior across species in relation to their spectral sensitivity (Goldsmith and Fernandez, 1968;Carleton et al, 2020), gears continue to be developed with visual components, such as light and color, that aim to make them more or less detectable (Ellis and Stadler, 2005;Sarriáet al, 2009;Underwood et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Artificial intelligence for fish behavior recognition may unlock fishing gear selectivity

2023

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Through the advancement of observation systems, our vision has far extended its reach into the world of fishes, and how they interact with fishing gears—breaking through physical boundaries and visually adapting to challenging conditions in marine environments. As marine sciences step into the era of artificial intelligence (AI), deep learning models now provide tools for researchers to process a large amount of imagery data (i.e., image sequence, video) on fish behavior in a more time-efficient and cost-effective manner. The latest AI models to detect fish and categorize species are now reaching human-like accuracy. Nevertheless, robust tools to track fish movements in situ are under development and primarily focused on tropical species. Data to accurately interpret fish interactions with fishing gears is still lacking, especially for temperate fishes. At the same time, this is an essential step for selectivity studies to advance and integrate AI methods in assessing the effectiveness of modified gears. We here conduct a bibliometric analysis to review the recent advances and applications of AI in automated tools for fish tracking, classification, and behavior recognition, highlighting how they may ultimately help improve gear selectivity. We further show how transforming external stimuli that influence fish behavior, such as sensory cues and gears as background, into interpretable features that models learn to distinguish remains challenging. By presenting the recent advances in AI on fish behavior applied to fishing gear improvements (e.g., Long Short-Term Memory (LSTM), Generative Adversarial Network (GAN), coupled networks), we discuss the advances, potential and limits of AI to help meet the demands of fishing policies and sustainable goals, as scientists and developers continue to collaborate in building the database needed to train deep learning models.

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Hearing in Marine Fish and Its Application in Fisheries

Abstract: In "Behavior of Marine Fishes: Capture Processes and Conservation Challenges" (ed.) P. He. Wiley-Blackwell, Ames, Iowa. pp. 45~64. (2010).

Cited by 32 publications

References 52 publications

Signals and noise in the octavolateralis systems: What is the impact of human activities on fish sensory function?

Signals and noise in the octavolateralis systems: What is the impact of human activities on fish sensory function?

Functional effect of vaterite – the presence of an alternative crystalline structure in otoliths alters escape kinematics of the brown trout

Artificial intelligence for fish behavior recognition may unlock fishing gear selectivity

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