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"Fishes Behavior."
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Sink or swim
Ms. Frizzle takes the class on a trip to a Pacific Island, where the Magic School Bus provides them with individual submarines, and they learn about fish schools and the behavior of undersea animals--and try to avoid being eaten by a shark.
Book
The effect of hypoxia on fish schooling
Low-oxygen areas are expanding in the oceans as a result of climate change. Work carried out during the past two decades suggests that, in addition to impairing basic physiological functions, hypoxia can also affect fish behaviour. Given that many fish species are known to school, and that schooling is advantageous for their survival, the effect of hypoxia on schooling behaviour may have important ecological consequences. Here, we review the effects of hypoxia on school structure and dynamics, together with the mechanisms that cause an increase in school volume and that ultimately lead to school disruption. Furthermore, the effect of hypoxia generates a number of trade-offs in terms of schooling positions and school structure. Field observations have found that large schools of fish can exacerbate hypoxic conditions, with potential consequences for school structure and size. Therefore, previous models that predict the maximum size attainable by fish schools in relation to oxygen levels are also reviewed. Finally, we suggest that studies on the effect of hypoxia on schooling need to be integrated with those on temperature and ocean acidifications within a framework aimed at increasing our ability to predict the effect of multiple stressors of climate change on fish behaviour.
This article is part of the themed issue ‘Physiological determinants of social behaviour in animals’.
Journal Article
Water quality monitoring in recirculating aquaculture systems
Good water quality in recirculating aquaculture systems (RAS) is crucial for ensuring the successful growth and survival of reared species. So far, there are no regulations for which parameters should be measured in RAS, and each farmer decides which parameters to follow. Traditionally, water quality parameters have been measured at certain intervals with handheld sensors and laboratory analyses, which can be labour intensive. Currently, a variety of sensors and monitoring equipment is available, even for the real‐time monitoring of water quality parameters. Internet of Things‐based systems and artificial intelligence can be applied for the monitoring purposes which allows real‐time measurements and warnings of critical situations. However, many of the modern systems need competent users and require regular maintenance and calibration. Changes in water quality also induces changes in fish behaviour, such as swimming activity, depth, acceleration and water quality can be assessed also based on these changes. In this review, water quality parameters, variety of sensors and monitoring technologies have been summarised to provide an overview of the current monitoring systems for water quality. Additionally, analytical methods for more advanced analyses have also been briefly summarised. Although there are several advanced options available for monitoring the basic water quality parameters, real‐time measurements of more advanced parameters still required require further development.
Journal Article
Little royal : a fish tale
A very self-important fish in a very small pond follows a frog to the biggest pond of all, where a whale teaches him important lessons.
Book
Artificial intelligence for fish behavior recognition may unlock fishing gear selectivity
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.
Journal Article
What a fish knows : the inner lives of our underwater cousins
\"Do fishes think? Do they really have three-second memories? And can they recognize the humans who peer back at them from above the surface of the water? In [this book], the myth-busting ethologist Jonathan Balcombe addresses these questions and more, taking us under the sea, through streams and estuaries, and to the other side of the aquarium glass to reveal the surprising capabilities of fishes\"--Dust jacket flap.
Book
Flow hydrodynamics drive effective fish attraction behaviour into slotted fishway entrances
Effective fishways rely on attracting fish, utilising the natural rheotactic behaviour of fish to orient into an attraction flow near the entrance. Despite the critical importance of attraction, understanding of the hydrodynamics of vertical slot entrances in relation to fish behaviour remains poor. Herein, hydrodynamic measurements of flows at slotted fishway entrances were experimented with two different designs, two velocities, three water depths, and two fish species, silver perch (
Bidyanus bidyanus
) and Australian bass (
Percalates novemaculeata
). Fish behaviours were tracked in relation to hydrodynamic measures of three-dimensional velocity and turbulent kinetic energy (TKE). There were distinct differences in the attraction flow between entrance designs, irrespective of velocity and water depth. A plain slotted entrance produced a more symmetric flow in the centre of the flume, causing fish to approach the entrance by skirting the core of the attraction jet flow and areas of high turbulence. In contrast, streamlined slotted entrance design resulted in an asymmetric attraction flow which guided fish along the wingwall towards the slotted entrance, improving attraction for both species. There were clear patterns in swimming trajectories for silver perch, swimming along the sidewalls of the observation zone towards the entrance, but Australian bass were less predictable, using random routes on their way to the slotted entrance. Both species preferred areas of low turbulence (TKE < 0.02 m
2
/ s
2
). This work has important implications for design of vertical slotted entrance systems.
Journal Article
The shocking secret of the electric eel... and more!
Tag along with scientists as they uncover intriguing adaptations that help animals survive in their environments. Discover the electric eels hunting tactics and an unexpected defense strategy, why some fish sleep in mucous cocoons, how jumping spiders hear from across a room, what the shape of a European eels head reveals about its diet, and why midshipman fish sing only at night.
Book
Behaviour of Temperate Reef Fish Species Around Oyster Aquaculture Farms and Natural Rock Reefs
Cultivation of eastern oysters using aquaculture gear increases habitat for temperate reef fish. Cunner ( Tautogolabrus adspersus ), scup ( Stenotomus chrysops ) and tautog ( Tautoga onitis ) inhabit a variety of complex natural and manmade habitats, including oyster aquaculture cage farms. Underwater video was recorded on two cage farms and a rock reef during May–September 2018 to quantify fish behavioural interactions and to assess ecological services provided by aquaculture gear, relative to natural structured seafloor. To collect video, action cameras were mounted on four study cages at a high‐density farm of 40–100 commercial cages (dense farm), on four single cages interspersed on low relief seafloor (sparse farm) and adjacent to four boulders on a rock reef (rock reef), within an embayment off Milford, Connecticut in Long Island Sound (NW Atlantic). Video was recorded hourly in 8‐min segments from 7 AM to 7 PM. Behaviours associated with habitat provisioning (e.g., courtship/reproduction, escape from predators, foraging, sheltering, schooling/grouping, territoriality) were observed for all three fish species on cages and boulders. Foraging and sheltering activity in cunner was significantly higher on cages than boulders while territorial behaviour occurred more frequently on boulders. Instances of escape from predators, foraging and sheltering behaviours in scup and tautog were significantly higher on cages than on boulders. Courtship/reproduction, grouping and territoriality were also higher on cages than boulders in tautog. Our results suggest that oyster cages confer ecological services that fulfil the basic biological and functional requirements of reef‐oriented fish, and provide habitat attributes afforded by natural rock reefs.
Journal Article