Patterns and drivers of the diving behavior of large pelagic predators

Nuno, Amy; Guiet, Jérôme; Baranek, Brooke; Bianchi, Daniele

doi:10.1101/2022.12.27.521953

Cited by 2 publications

(2 citation statements)

References 82 publications

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“…For this purpose, we simulated the behavior of fish during feeding within our model. It is well-documented that certain species, such as tuna, exhibit phototaxis, actively avoiding light by diving deeper, a behavior that has significant implications for their feeding patterns [30]. Typically, in a fish pen, when feed is introduced, fish converge around the area where the food is distributed, begin feeding, and subsequently resume random swimming within the pen.…”

Section: (Analysis-3) Behavioral Changes During Feeding and Entropymentioning

confidence: 99%

Quantitative Assessment and Analysis of Fish Behavior in Closed Systems Using Information Entropy

Kadota,

Torisawa,

Takagi

2024

Fishes

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This study introduces a method for quantitatively assessing the complexity and predictability of fish behavior in closed systems through the application of information entropy, offering a novel lens through which to understand how fish adapt to environmental changes. Utilizing simulations rooted in a random walk model for fish movement, we delve into entropy fluctuations under varying environmental conditions, including responses to feeding and external stimuli. Our findings underscore the utility of information entropy in capturing the intricacies of fish behavior, particularly highlighting the synchrony in collective actions and adaptations to environmental shifts. This research not only broadens our comprehension of fish behavior but also paves the way for its application in fields like aquaculture and resource management. Through our analysis, we discovered that smaller grid sizes in simulations capture detailed local fluctuations, while larger grids elucidate general trends, pinpointing a 2.5 grid as optimal for our study. Moreover, changes in swimming speeds and behavioral adaptations during feeding were quantitatively analyzed, with results illustrating significant behavior modifications. Additionally, employing a Gaussian mixture model helped to clarify the nuanced changes in fish behavior in response to altered light conditions, demonstrating the layered complexity of fish responses to environmental stimuli. This investigation confirms the efficacy of information entropy as a robust metric for evaluating fish shoal behavior, offering a fresh methodology for ecological and environmental studies, with promising implications for sustainable management practices.

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Section: (Analysis-3) Behavioral Changes During Feeding and Entropymentioning

confidence: 99%

Quantitative Assessment and Analysis of Fish Behavior in Closed Systems Using Information Entropy

Kadota,

Torisawa,

Takagi

2024

Fishes

View full text Add to dashboard Cite

show abstract

“…As Figure 6 reveals, the information entropy variations following time step 50 are not adequately explained by the entropy graph in isolation. To delineate the entropy fluctuation patterns with greater precision, we employed a Gaussian Mixture Model (GMM)-a method proven effective in previous studies for analyzing complex data distributions [28,29]. By clustering the time series entropy data into three distinct groups using GMM, we could identify nuanced behavior patterns within the data.…”

Section: (Analysis-4): Behavioral Changes and Entropy In Response To ...mentioning

confidence: 99%

Quantitative Assessment and Analysis of Fish Behavior in Closed Systems Using Information Entropy

Kadota,

Torisawa,

Takagi

2024

Preprint

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This study introduces a method for quantitatively assessing the complexity and predictability of fish behavior in closed systems through the application of information entropy, offering a novel lens to understand how fish adapt to environmental changes. Utilizing simulations rooted in a random walk model for fish movement, we delve into entropy fluctuations under varying environmental conditions, including responses to feeding and external stimuli. Our findings underscore the utility of information entropy in capturing the intricacies of fish behavior, particularly highlighting the synchrony in collective actions and adaptations to environmental shifts. This research not only broadens our comprehension of fish behavior but also paves the way for its application in fields like aquaculture and resource management. Through our analysis, we discovered that smaller grid sizes in simulations capture detailed local fluctuations, while larger grids elucidate general trends, pinpointing a 2.5m grid as optimal for our study. Moreover, changes in swimming speeds and behavioral adaptations during feeding were quantitatively analyzed, with results illustrating significant behavior modifications. Additionally, employing a Gaussian Mixture Model helped to clarify the nuanced changes in fish behavior in response to altered light conditions, demonstrating the layered complexity of fish responses to environmental stimuli. This investigation confirms the efficacy of information entropy as a robust metric for evaluating fish shoal behavior, offering a fresh methodology for ecological and environmental studies, with promising implications for sustainable management practices.

show abstract

Patterns and drivers of the diving behavior of large pelagic predators

Cited by 2 publications

References 82 publications

Quantitative Assessment and Analysis of Fish Behavior in Closed Systems Using Information Entropy

Quantitative Assessment and Analysis of Fish Behavior in Closed Systems Using Information Entropy

Quantitative Assessment and Analysis of Fish Behavior in Closed Systems Using Information Entropy

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