1
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Stin V, Godoy-Diana R, Bonnet X, Herrel A. Form and function of anguilliform swimming. Biol Rev Camb Philos Soc 2024; 99:2190-2210. [PMID: 39004428 DOI: 10.1111/brv.13116] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2024] [Revised: 06/18/2024] [Accepted: 06/19/2024] [Indexed: 07/16/2024]
Abstract
Anguilliform swimmers are long and narrow animals that propel themselves by undulating their bodies. Observations in nature and recent investigations suggest that anguilliform swimming is highly efficient. However, understanding the underlying reasons for the efficiency of this type of locomotion requires interdisciplinary studies spanning from biology to hydrodynamics. Regrettably, these different fields are rarely discussed together, which hinders our ability to understand the repeated evolution of this swimming mode in vertebrates. This review compiles the current knowledge of the anatomical features that drive anguilliform swimming, compares the resulting kinematics across a wide range of anguilliform swimmers, and describes the resulting hydrodynamic interactions using data from both in vivo experiments and computational studies.
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Affiliation(s)
- Vincent Stin
- UMR 7636, PMMH, CNRS, ESPCI Paris-PSL, Sorbonne Université, Université Paris Cité, 7 Quai Saint-Bernard, Paris, 75005, France
- Département Adaptation du Vivant, UMR 7179 MECADEV, MNHN/CNRS, 43 rue Buffon, Paris, 75005, France
| | - Ramiro Godoy-Diana
- UMR 7636, PMMH, CNRS, ESPCI Paris-PSL, Sorbonne Université, Université Paris Cité, 7 Quai Saint-Bernard, Paris, 75005, France
| | - Xavier Bonnet
- UMR 7372 Centre d'Etude Biologique de Chizé, CNRS, 405 Route de Prissé la Charrière, Villiers-en-Bois, 79360, France
| | - Anthony Herrel
- Département Adaptation du Vivant, UMR 7179 MECADEV, MNHN/CNRS, 43 rue Buffon, Paris, 75005, France
- Department of Biology, Evolutionary Morphology of Vertebrates, Ghent University, K.L. Ledeganckstraat 35, Ghent, 9000, Belgium
- Department of Biology, University of Antwerp, Universiteitsplein 1, Wilrijk, 2610, Belgium
- Naturhistorisches Museum Bern, Bernastrasse 15, Bern, 3005, Switzerland
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2
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Aragaki D, Nishimura T, Sato R, Ming A. Biomimetic Soft Underwater Robot Inspired by the Red Muscle and Tendon Structure of Fish. Biomimetics (Basel) 2023; 8:biomimetics8020133. [PMID: 37092385 PMCID: PMC10123703 DOI: 10.3390/biomimetics8020133] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Revised: 03/20/2023] [Accepted: 03/21/2023] [Indexed: 04/25/2023] Open
Abstract
Underwater robots are becoming increasingly important in various fields. Fish robots are attracting attention as an alternative to the screw-type robots currently in use. We developed a compact robot with a high swimming performance by mimicking the anatomical structure of fish. In this paper, we focus on the red muscles, tendons, and vertebrae used for steady swimming of fish. A robot was fabricated by replacing the red muscle structure with shape memory alloy wires and rigid body links. In our previous work, undulation motions with various phase differences and backward quadratically increasing inter-vertebral bending angles were confirmed in the air, while the swimming performance in insulating fluid was poor. To improve the swimming performance, an improved robot was designed that mimics the muscle contractions of mackerel using a pulley mechanism, with the robot named UEC Mackerel. In swimming experiments using the improved robot, a maximum swimming speed of 25.8 mm/s (0.11 BL/s) was recorded, which is comparable to that of other soft-swimming robots. In addition, the cost of transport (COT), representing the energy consumption required for robot movement, was calculated, and a minimum COT of 0.08 was recorded, which is comparable to that of an actual fish.
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Affiliation(s)
- Daisuke Aragaki
- Department of Mechanical Engineering and Intelligent Systems, The University of Electro-Communications, Tokyo 182-8585, Japan
| | - Toi Nishimura
- Department of Mechanical Engineering and Intelligent Systems, The University of Electro-Communications, Tokyo 182-8585, Japan
| | - Ryuki Sato
- Department of Mechanical Engineering and Intelligent Systems, The University of Electro-Communications, Tokyo 182-8585, Japan
| | - Aiguo Ming
- Department of Mechanical Engineering and Intelligent Systems, The University of Electro-Communications, Tokyo 182-8585, Japan
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3
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Matthews DG, Zhu R, Wang J, Dong H, Bart-Smith H, Lauder G. Role of the caudal peduncle in a fish-inspired robotic model: how changing stiffness and angle of attack affects swimming performance. BIOINSPIRATION & BIOMIMETICS 2022; 17:066017. [PMID: 36206750 DOI: 10.1088/1748-3190/ac9879] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Accepted: 10/06/2022] [Indexed: 06/16/2023]
Abstract
In fish, the tail is a key element of propulsive anatomy that contributes to thrust during swimming. Fish possess the ability to alter tail stiffness, surface area and conformation. Specifically, the region at the base of the tail, the caudal peduncle, is proposed to be a key location of fish stiffness modulation during locomotion. Most previous analyses have focused on the overall body or tail stiffness, and not on the effects of changing stiffness specifically at the base of the tail in fish and robotic models. We used both computational fluid dynamics analysis and experimental measurements of propulsive forces in physical models with different peduncle stiffnesses to analyze the effect of altering stiffness on the tail angle of attack and propulsive force and efficiency. By changing the motion program input to the tail, we were able to alter the phase relationship between the front and back tail sections between 0° and 330°. Computational simulations showed that power consumption was nearly minimized and thrust production was nearly maximized at the kinematic pattern whereφ= 270°, the approximate phase lag observed in the experimental foils and in free swimming tuna. We observed reduced thrust and efficiency at high angles of attack, suggesting that the tail driven during these motion programs experiences stalling and loss of lift. However, there is no single peduncle stiffness that consistently maximizes performance, particularly in physical models. This result highlights the fact that the optimal caudal peduncle stiffness is highly context dependent. Therefore, incorporating the ability to control peduncle stiffness in future robotic models of fish propulsion promises to increase the ability of robots to approach the performance of fish.
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Affiliation(s)
- David G Matthews
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 20138, United States of America
- Museum of Comparative Zoology, Harvard University, Cambridge, MA 20138, United States of America
| | - Ruijie Zhu
- Department of Mechanical & Aerospace Engineering, University of Virginia, Charlottesville, VA 22904, United States of America
| | - Junshi Wang
- Department of Mechanical & Aerospace Engineering, University of Virginia, Charlottesville, VA 22904, United States of America
| | - Haibo Dong
- Department of Mechanical & Aerospace Engineering, University of Virginia, Charlottesville, VA 22904, United States of America
| | - Hilary Bart-Smith
- Department of Mechanical & Aerospace Engineering, University of Virginia, Charlottesville, VA 22904, United States of America
| | - George Lauder
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 20138, United States of America
- Museum of Comparative Zoology, Harvard University, Cambridge, MA 20138, United States of America
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4
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Cooke SJ, Bergman JN, Twardek WM, Piczak ML, Casselberry GA, Lutek K, Dahlmo LS, Birnie-Gauvin K, Griffin LP, Brownscombe JW, Raby GD, Standen EM, Horodysky AZ, Johnsen S, Danylchuk AJ, Furey NB, Gallagher AJ, Lédée EJI, Midwood JD, Gutowsky LFG, Jacoby DMP, Matley JK, Lennox RJ. The movement ecology of fishes. JOURNAL OF FISH BIOLOGY 2022; 101:756-779. [PMID: 35788929 DOI: 10.1111/jfb.15153] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Accepted: 06/29/2022] [Indexed: 06/15/2023]
Abstract
Movement of fishes in the aquatic realm is fundamental to their ecology and survival. Movement can be driven by a variety of biological, physiological and environmental factors occurring across all spatial and temporal scales. The intrinsic capacity of movement to impact fish individually (e.g., foraging) with potential knock-on effects throughout the ecosystem (e.g., food web dynamics) has garnered considerable interest in the field of movement ecology. The advancement of technology in recent decades, in combination with ever-growing threats to freshwater and marine systems, has further spurred empirical research and theoretical considerations. Given the rapid expansion within the field of movement ecology and its significant role in informing management and conservation efforts, a contemporary and multidisciplinary review about the various components influencing movement is outstanding. Using an established conceptual framework for movement ecology as a guide (i.e., Nathan et al., 2008: 19052), we synthesized the environmental and individual factors that affect the movement of fishes. Specifically, internal (e.g., energy acquisition, endocrinology, and homeostasis) and external (biotic and abiotic) environmental elements are discussed, as well as the different processes that influence individual-level (or population) decisions, such as navigation cues, motion capacity, propagation characteristics and group behaviours. In addition to environmental drivers and individual movement factors, we also explored how associated strategies help survival by optimizing physiological and other biological states. Next, we identified how movement ecology is increasingly being incorporated into management and conservation by highlighting the inherent benefits that spatio-temporal fish behaviour imbues into policy, regulatory, and remediation planning. Finally, we considered the future of movement ecology by evaluating ongoing technological innovations and both the challenges and opportunities that these advancements create for scientists and managers. As aquatic ecosystems continue to face alarming climate (and other human-driven) issues that impact animal movements, the comprehensive and multidisciplinary assessment of movement ecology will be instrumental in developing plans to guide research and promote sustainability measures for aquatic resources.
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Affiliation(s)
- Steven J Cooke
- Fish Ecology and Conservation Physiology Laboratory, Department of Biology and the Institute of Environmental and Interdisciplinary Science, Carleton University, Ottawa, Ontario, Canada
| | - Jordanna N Bergman
- Fish Ecology and Conservation Physiology Laboratory, Department of Biology and the Institute of Environmental and Interdisciplinary Science, Carleton University, Ottawa, Ontario, Canada
| | - William M Twardek
- Fish Ecology and Conservation Physiology Laboratory, Department of Biology and the Institute of Environmental and Interdisciplinary Science, Carleton University, Ottawa, Ontario, Canada
| | - Morgan L Piczak
- Fish Ecology and Conservation Physiology Laboratory, Department of Biology and the Institute of Environmental and Interdisciplinary Science, Carleton University, Ottawa, Ontario, Canada
| | - Grace A Casselberry
- Department of Environmental Conservation, University of Massachusetts, Amherst, Massachusetts, USA
| | - Keegan Lutek
- Department of Biology, University of Ottawa, Ottawa, Ontario, Canada
| | - Lotte S Dahlmo
- Department of Biological Sciences, University of Bergen, Bergen, Norway
- Laboratory for Freshwater Ecology and Inland Fisheries, NORCE Norwegian Research Centre, Bergen, Norway
| | - Kim Birnie-Gauvin
- Section for Freshwater Fisheries and Ecology, National Institute of Aquatic Resources, Technical University of Denmark, Silkeborg, Denmark
| | - Lucas P Griffin
- Department of Environmental Conservation, University of Massachusetts, Amherst, Massachusetts, USA
| | - Jacob W Brownscombe
- Great Lakes Laboratory for Fisheries and Aquatic Sciences, Fisheries and Oceans Canada, Burlington, Ontario, Canada
| | - Graham D Raby
- Biology Department, Trent University, Peterborough, Ontario, Canada
| | - Emily M Standen
- Department of Biology, University of Ottawa, Ottawa, Ontario, Canada
| | - Andrij Z Horodysky
- Department of Marine and Environmental Science, Hampton University, Hampton, Virginia, USA
| | - Sönke Johnsen
- Biology Department, Duke University, Durham, North Caroline, USA
| | - Andy J Danylchuk
- Department of Environmental Conservation, University of Massachusetts, Amherst, Massachusetts, USA
| | - Nathan B Furey
- Department of Biological Sciences, University of New Hampshire, Durham, New Hampshire, USA
| | | | - Elodie J I Lédée
- College of Science and Engineering, James Cook University, Townsville, Queensland, Australia
| | - Jon D Midwood
- Great Lakes Laboratory for Fisheries and Aquatic Sciences, Fisheries and Oceans Canada, Burlington, Ontario, Canada
| | - Lee F G Gutowsky
- Environmental & Life Sciences Program, Trent University, Peterborough, Ontario, Canada
| | - David M P Jacoby
- Lancaster Environment Centre, Lancaster University, Lancaster, UK
| | - Jordan K Matley
- Program in Aquatic Resources, St Francis Xavier University, Antigonish, Nova Scotia, Canada
| | - Robert J Lennox
- Laboratory for Freshwater Ecology and Inland Fisheries, NORCE Norwegian Research Centre, Bergen, Norway
- Norwegian Institute for Nature Research, Trondheim, Norway
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5
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Wolf Z, Lauder GV. A fish-like soft-robotic model generates a diversity of swimming patterns. Integr Comp Biol 2022; 62:icac039. [PMID: 35588062 DOI: 10.1093/icb/icac039] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Fish display a versatile array of swimming patterns, and frequently demonstrate the ability to switch between these patterns altering kinematics as necessary. Many hard and soft robotic systems have sought to understand a variety of aspects pertaining to undulatory swimming, but most have been built to focus solely on a subset of those swimming patterns. We have expanded upon a previous soft robotic model, the pneufish, so that it can now simulate a variety of swimming patterns, much like a real fish. We explore the performance space available for this longer soft robotic model, which we call the quad-pneufish, with particular attention to the effects on lateral forces and z-torques produced during locomotion. We show that the quad-pneufish is capable of achieving a variety of midline patterns - including more realistic, fish-like patterns - and introducing a slight amount of co-activation between the left and right sides maintains forward thrust while decreasing lateral forces, indicating an increase in swimming efficiency. Robotic systems that are capable of producing an array of swimming movement patterns hold promise as experimental platforms for studying the diversity of fish locomotor patterns.
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Affiliation(s)
- Zane Wolf
- Department of Organismic and Evolutionary Biology, Harvard University, 26 Oxford Street, Cambridge, 02138, Massachusetts, USA
| | - George V Lauder
- Department of Organismic and Evolutionary Biology, Harvard University, 26 Oxford Street, Cambridge, 02138, Massachusetts, USA
- Museum of Comparative Zoology, Harvard University, 26 Oxford Street, Cambridge, 02138, Massachusetts, USA
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6
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Zhong Q, Zhu J, Fish FE, Kerr SJ, Downs AM, Bart-Smith H, Quinn DB. Tunable stiffness enables fast and efficient swimming in fish-like robots. Sci Robot 2021; 6:6/57/eabe4088. [PMID: 34380755 DOI: 10.1126/scirobotics.abe4088] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2020] [Accepted: 07/20/2021] [Indexed: 02/04/2023]
Abstract
Fish maintain high swimming efficiencies over a wide range of speeds. A key to this achievement is their flexibility, yet even flexible robotic fish trail real fish in terms of performance. Here, we explore how fish leverage tunable flexibility by using their muscles to modulate the stiffness of their tails to achieve efficient swimming. We derived a model that explains how and why tuning stiffness affects performance. We show that to maximize efficiency, muscle tension should scale with swimming speed squared, offering a simple tuning strategy for fish-like robots. Tuning stiffness can double swimming efficiency at tuna-like frequencies and speeds (0 to 6 hertz; 0 to 2 body lengths per second). Energy savings increase with frequency, suggesting that high-frequency fish-like robots have the most to gain from tuning stiffness.
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Affiliation(s)
- Q Zhong
- Department of Mechanical and Aerospace Engineering, University of Virginia, 122 Engineer's Way, Charlottesville, VA 22903, USA.
| | - J Zhu
- Department of Mechanical and Aerospace Engineering, University of Virginia, 122 Engineer's Way, Charlottesville, VA 22903, USA
| | - F E Fish
- Department of Biology, West Chester University, 730 S High St., West Chester, PA 19383, USA
| | - S J Kerr
- Department of Biology, West Chester University, 730 S High St., West Chester, PA 19383, USA
| | - A M Downs
- Department of Biology, West Chester University, 730 S High St., West Chester, PA 19383, USA
| | - H Bart-Smith
- Department of Mechanical and Aerospace Engineering, University of Virginia, 122 Engineer's Way, Charlottesville, VA 22903, USA
| | - D B Quinn
- Department of Mechanical and Aerospace Engineering, University of Virginia, 122 Engineer's Way, Charlottesville, VA 22903, USA. .,Department of Electrical and Computer Engineering, University of Virginia, 122 Engineer's Way, Charlottesville, VA 22903, USA
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7
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Printzi A, Fragkoulis S, Dimitriadi A, Keklikoglou K, Arvanitidis C, Witten PE, Koumoundouros G. Exercise-induced lordosis in zebrafish Danio rerio (Hamilton, 1822). JOURNAL OF FISH BIOLOGY 2021; 98:987-994. [PMID: 31858594 DOI: 10.1111/jfb.14240] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/27/2019] [Accepted: 12/15/2019] [Indexed: 06/10/2023]
Abstract
The anabolic effect of exercise on muscles and bones is well documented. In teleost fish, exercise has been shown to accelerate skeletogenesis, to increase bone volume, and to change the shape of vertebral bodies. Still, increased swimming has also been reported to induce malformations of the teleost vertebral column, particularly lordosis. This study examines whether zebrafish (Danio rerio) develops lordosis as a result of continuous physical exercise. Zebrafish were subjected, for 1 week, to an increased swimming exercise of 5.0, 6.5 or 8.0 total body lengths (TL) per second. Control and exercise group zebrafish were examined for the presence of vertebral abnormalities, by in vivo examination, whole mount staining for bone and cartilage and histology and micro-computed tomography (CT) scanning. Exercise zebrafish developed a significantly higher rate of lordosis in the haemal part of the vertebral column. At the end of the experiment, the frequency of lordosis in the control groups was 0.5 ± 1.3% and that in the exercise groups was 7.5 ± 10.6%, 47.5 ± 10.6% and 92.5 ± 6.0% of 5.0, 6.5 and 8.0 TL∙s-1 , respectively. Histological analysis and CT scanning revealed abnormal vertebrae with dorsal folding of the vertebral body end plates. Possible mechanisms that trigger lordotic spine malformations are discussed. This is the first study to report a quick, reliable and welfare-compatible method of inducing skeletal abnormalities in a vertebrate model during the post-embryonic period.
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Affiliation(s)
- Alice Printzi
- Biology Department, University of Crete, Heraklion, Crete, Greece
| | | | | | - Kleoniki Keklikoglou
- Institute for Marine Biology, Biotechnology and Aquaculture, Hellenic Centre for Marine Research, Heraklion, Crete, Greece
| | - Christos Arvanitidis
- Institute for Marine Biology, Biotechnology and Aquaculture, Hellenic Centre for Marine Research, Heraklion, Crete, Greece
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8
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Wolf Z, Jusufi A, Vogt DM, Lauder GV. Fish-like aquatic propulsion studied using a pneumatically-actuated soft-robotic model. BIOINSPIRATION & BIOMIMETICS 2020; 15:046008. [PMID: 32330908 DOI: 10.1088/1748-3190/ab8d0f] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Fish locomotion is characterized by waves of muscle electrical activity that proceed from head to tail, and result in an undulatory pattern of body bending that generates thrust during locomotion. Isolating the effects of parameters like body stiffness, co-activation between the right and left sides of the body, and frequency on thrust generation has proven to be difficult in live fishes. We use a pneumatically-actuated fish-like model to investigate how these parameters affect locomotor force generation. We measure thrust as well as side forces and torques generated during propulsion. Using a statistical linear model we examine the effects of input parameter combinations on thrust generation. We show that both stiffness and frequency substantially affect swimming kinematics, and that there are complex interactive effects of these two parameters on thrust. The stiffer the backbone the more impact that increasing frequency has on thrust production. For stiffer models, increasing frequency resulted in higher values for both thrust and lateral forces. Large side forces reduce swimming efficiency but this effect could be mitigated by decreasing undulatory wavelength and allowing appropriate phasing of left and right body movements to reduce amplitudes of side force.
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Affiliation(s)
- Z Wolf
- Department of Organismic and Evolutionary Biology, Harvard University, 26 Oxford Street, Cambridge, MA 02138, United States of America
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9
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Zhu J, White C, Wainwright DK, Di Santo V, Lauder GV, Bart-Smith H. Tuna robotics: A high-frequency experimental platform exploring the performance space of swimming fishes. Sci Robot 2019; 4:4/34/eaax4615. [PMID: 33137777 DOI: 10.1126/scirobotics.aax4615] [Citation(s) in RCA: 70] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2019] [Accepted: 08/20/2019] [Indexed: 11/02/2022]
Abstract
Tuna and related scombrid fishes are high-performance swimmers that often operate at high frequencies, especially during behaviors such as escaping from predators or catching prey. This contrasts with most fish-like robotic systems that typically operate at low frequencies (< 2 hertz). To explore the high-frequency fish swimming performance space, we designed and tested a new platform based on yellowfin tuna (Thunnus albacares) and Atlantic mackerel (Scomber scombrus). Body kinematics, speed, and power were measured at increasing tail beat frequencies to quantify swimming performance and to study flow fields generated by the tail. Experimental analyses of freely swimming tuna and mackerel allow comparison with the tuna-like robotic system. The Tunabot (255 millimeters long) can achieve a maximum tail beat frequency of 15 hertz, which corresponds to a swimming speed of 4.0 body lengths per second. Comparison of midline kinematics between scombrid fish and the Tunabot shows good agreement over a wide range of frequencies, with the biggest discrepancy occurring at the caudal fin, primarily due to the rigid propulsor used in the robotic model. As frequency increases, cost of transport (COT) follows a fish-like U-shaped response with a minimum at ~1.6 body lengths per second. The Tunabot has a range of ~9.1 kilometers if it swims at 0.4 meter per second or ~4.2 kilometers at 1.0 meter per second, assuming a 10-watt-hour battery pack. These results highlight the capabilities of high-frequency biological swimming and lay the foundation to explore a fish-like performance space for bio-inspired underwater vehicles.
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Affiliation(s)
- J Zhu
- Bio-Inspired Engineering Research Laboratory (BIERL), Department of Mechanical and Aerospace Engineering, University of Virginia, 122 Engineer's Way, Charlottesville, VA 22903, USA
| | - C White
- Bio-Inspired Engineering Research Laboratory (BIERL), Department of Mechanical and Aerospace Engineering, University of Virginia, 122 Engineer's Way, Charlottesville, VA 22903, USA
| | - D K Wainwright
- Museum of Comparative Zoology, Harvard University, 26 Oxford Street, Cambridge, MA 02138, USA
| | - V Di Santo
- Museum of Comparative Zoology, Harvard University, 26 Oxford Street, Cambridge, MA 02138, USA
| | - G V Lauder
- Museum of Comparative Zoology, Harvard University, 26 Oxford Street, Cambridge, MA 02138, USA
| | - H Bart-Smith
- Bio-Inspired Engineering Research Laboratory (BIERL), Department of Mechanical and Aerospace Engineering, University of Virginia, 122 Engineer's Way, Charlottesville, VA 22903, USA.
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10
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Ming T, Jin B, Song J, Luo H, Du R, Ding Y. 3D computational models explain muscle activation patterns and energetic functions of internal structures in fish swimming. PLoS Comput Biol 2019; 15:e1006883. [PMID: 31487282 PMCID: PMC6748450 DOI: 10.1371/journal.pcbi.1006883] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2019] [Revised: 09/17/2019] [Accepted: 07/22/2019] [Indexed: 11/18/2022] Open
Abstract
How muscles are used is a key to understanding the internal driving of fish swimming. However, the underlying mechanisms of some features of the muscle activation patterns and their differential appearance in different species are still obscure. In this study, we explain the muscle activation patterns by using 3D computational fluid dynamics models coupled to the motion of fish with prescribed deformation and examining the torque and power required along the fish body with two primary swimming modes. We find that the torque required by the hydrodynamic forces and body inertia exhibits a wave pattern that travels faster than the curvature wave in both anguilliform and carangiform swimmers, which can explain the traveling wave speeds of the muscle activations. Notably, intermittent negative power (i.e., power delivered by the fluid to the body) on the posterior part, along with a timely transfer of torque and energy by tendons, explains the decrease in the duration of muscle activation towards the tail. The torque contribution from the body elasticity further clarifies the wave speed increase or the reverse of the wave direction of the muscle activation on the posterior part of a carangiform swimmer. For anguilliform swimmers, the absence of the aforementioned changes in the muscle activation on the posterior part is consistent with our torque prediction and the absence of long tendons from experimental observations. These results provide novel insights into the functions of muscles and tendons as an integral part of the internal driving system, especially from an energy perspective, and they highlight the differences in the internal driving systems between the two primary swimming modes. For undulatory swimming, fish form posteriorly traveling waves of body bending by activating their muscles sequentially along the body. However, experimental observations have shown that the muscle activation wave does not simply match the bending wave. Researchers have previously computed the torque required for muscles along the body based on classic hydrodynamic theories and explained the higher wave speed of the muscle activation compared to the curvature wave. However, the origins of other features of the muscle activation pattern and their variation among different species are still obscure after decades of research. In this study, we use 3D computational fluid dynamics models to compute the spatiotemporal distributions of both the torque and power required for eel-like and mackerel-like swimming. By examining both the torque and power patterns and considering the energy transfer, storage, and release by tendons and body viscoelasticity, we can explain not only the features and variations in the muscle activation patterns as observed from fish experiments but also how tendons and body elasticity save energy. We provide a mechanical picture in which the body shape, body movement, muscles, tendons, and body elasticity of a mackerel (or similar) orchestrate to make swimming efficient.
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Affiliation(s)
- Tingyu Ming
- Beijing Computational Science Research Center, Haidian District, Beijing, China
| | - Bowen Jin
- Beijing Computational Science Research Center, Haidian District, Beijing, China
| | - Jialei Song
- Beijing Computational Science Research Center, Haidian District, Beijing, China
- Department of Mechanical and Automation Engineering, Chinese University of Hong Kong, Hong Kong SAR, China
| | - Haoxiang Luo
- Department of Mechanical Engineering, Vanderbilt University, Nashville, Tennessee, United States of America
| | - Ruxu Du
- Department of Mechanical and Automation Engineering, Chinese University of Hong Kong, Hong Kong SAR, China
| | - Yang Ding
- Beijing Computational Science Research Center, Haidian District, Beijing, China
- * E-mail:
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11
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Gough WT, Segre PS, Bierlich KC, Cade DE, Potvin J, Fish FE, Dale J, di Clemente J, Friedlaender AS, Johnston DW, Kahane-Rapport SR, Kennedy J, Long JH, Oudejans M, Penry G, Savoca MS, Simon M, Videsen SKA, Visser F, Wiley DN, Goldbogen JA. Scaling of swimming performance in baleen whales. J Exp Biol 2019; 222:jeb.204172. [DOI: 10.1242/jeb.204172] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2019] [Accepted: 09/24/2019] [Indexed: 12/11/2022]
Abstract
The scale-dependence of locomotor factors have long been studied in comparative biomechanics, but remain poorly understood for animals at the upper extremes of body size. Rorqual baleen whales include the largest animals, but we lack basic kinematic data about their movements and behavior below the ocean surface. Here we combined morphometrics from aerial drone photogrammetry, whale-borne inertial sensing tag data, and hydrodynamic modeling to study the locomotion of five rorqual species. We quantified changes in tail oscillatory frequency and cruising speed for individual whales spanning a threefold variation in body length, corresponding to an order of magnitude variation in estimated body mass. Our results showed that oscillatory frequency decreases with body length (∝ length−0.53) while cruising speed remains roughly invariant (∝ length0.08) at 2 m s−1. We compared these measured results for oscillatory frequency against simplified models of an oscillating cantilever beam (∝ length−1) and an optimized oscillating Strouhal vortex generator (∝ length−1). The difference between our length-scaling exponent and the simplified models suggests that animals are often swimming non-optimally in order to feed or perform other routine behaviors. Cruising speed aligned more closely with an estimate of the optimal speed required to minimize the energetic cost of swimming (∝ length0.07). Our results are among the first to elucidate the relationships between both oscillatory frequency and cruising speed and body size for free-swimming animals at the largest scale.
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Affiliation(s)
- William T. Gough
- Hopkins Marine Station, Stanford University, Pacific Grove, CA 93950, USA
| | - Paolo S. Segre
- Hopkins Marine Station, Stanford University, Pacific Grove, CA 93950, USA
| | - K. C. Bierlich
- Nicholas School of the Environment, Duke University, Beaufort, NC 28516, USA
| | - David E. Cade
- Hopkins Marine Station, Stanford University, Pacific Grove, CA 93950, USA
| | - Jean Potvin
- Department of Physics, Saint Louis University, St. Louis, MO 633103, USA
| | - Frank E. Fish
- Department of Biology, West Chester University, West Chester, PA 19383, USA
| | - Julian Dale
- Nicholas School of the Environment, Duke University, Beaufort, NC 28516, USA
| | | | - Ari S. Friedlaender
- Institute of Marine Sciences, University of California Santa Cruz, Santa Cruz, CA 95064, USA
| | - David W. Johnston
- Nicholas School of the Environment, Duke University, Beaufort, NC 28516, USA
| | | | - John Kennedy
- Department of Physics, Saint Louis University, St. Louis, MO 633103, USA
| | - John H. Long
- Departments of Biology and Cognitive Science, Vassar College, Poughkeepsie, NY 12604, USA
| | | | - Gwenith Penry
- Department of Zoology, Institute for Coastal and Marine Research, Nelson Mandela University, Port Elizabeth, South Africa
| | - Matthew S. Savoca
- Hopkins Marine Station, Stanford University, Pacific Grove, CA 93950, USA
| | - Malene Simon
- Greenland Climate Research Centre, Greenland Institute of Natural Resources, Kivioq 2, 3900 Nuuk, Greenland
| | - Simone K. A. Videsen
- Zoophysiology, Department of Bioscience, Faculty of Science and Technology, Aarhus University, Aarhus 8000, Denmark
| | - Fleur Visser
- Kelp Marine Research, Hoorn, the Netherlands
- Institute for Biodiversity and Ecosystem Dynamics – Freshwater and Marine Ecology, University of Amsterdam, the Netherlands
- Royal Netherlands Institute for Sea Research, Texel, the Netherlands
| | - David N. Wiley
- US National Oceanic and Atmospheric Administration, Office of National Marine Sanctuaries, Stellwagen Bank National Marine Sanctuary, Scituate, MA 02066, USA
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12
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Skjelvareid MH, Stormo SK, Þórarinsdóttir KA, Heia K. Weakening Pin Bone Attachment in Fish Fillets Using High-Intensity Focused Ultrasound. Foods 2017; 6:foods6090082. [PMID: 28926968 PMCID: PMC5615294 DOI: 10.3390/foods6090082] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2017] [Accepted: 09/08/2017] [Indexed: 01/09/2023] Open
Abstract
High Intensity Focused Ultrasound (HIFU) can be used for the localized heating of biological tissue through the conversion of sound waves into heat. Although originally developed for human medicine, HIFU may also be used to weaken the attachment of pin bones in fish fillets to enable easier removal of such bones. This was shown in the present study, where a series of experiments were performed on HIFU phantoms and fillets of cod and salmon. In thin objects such as fish fillets, the heat is mainly dissipated at the surfaces. However, bones inside the fillet absorb ultrasound energy more efficiently than the surrounding tissue, resulting in a “self-focusing” heating of the bones. Salmon skin was found to effectively block the ultrasound, resulting in a significantly lower heating effect in fillets with skin. Cod skin partly blocked the ultrasound, but only to a small degree, enabling HIFU treatment through the skin. The treatment of fillets to reduce the pin bone attachment yielded an average reduction in the required pulling force by 50% in cod fillets with skin, with little muscle denaturation, and 72% in skinned fillets, with significant muscle denaturation. Salmon fillets were treated from the muscle side of the fillet to circumvent the need for penetration through skin. The treatment resulted in a 30% reduction in the peak pulling force and 10% reduction in the total pulling work, with a slight denaturation of the fillet surface.
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Affiliation(s)
| | | | | | - Karsten Heia
- Department of Seafood Industry, Nofima AS, P.O. Box 6122, 9291 Tromsø, Norway.
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13
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Marras S, Noda T, Steffensen JF, Svendsen MBS, Krause J, Wilson ADM, Kurvers RHJM, Herbert-Read J, Boswell KM, Domenici P. Not So Fast: Swimming Behavior of Sailfish during Predator-Prey Interactions using High-Speed Video and Accelerometry. Integr Comp Biol 2015; 55:719-27. [PMID: 25898843 DOI: 10.1093/icb/icv017] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Billfishes are considered among the fastest swimmers in the oceans. Despite early estimates of extremely high speeds, more recent work showed that these predators (e.g., blue marlin) spend most of their time swimming slowly, rarely exceeding 2 m s(-1). Predator-prey interactions provide a context within which one may expect maximal speeds both by predators and prey. Beyond speed, however, an important component determining the outcome of predator-prey encounters is unsteady swimming (i.e., turning and accelerating). Although large predators are faster than their small prey, the latter show higher performance in unsteady swimming. To contrast the evading behaviors of their highly maneuverable prey, sailfish and other large aquatic predators possess morphological adaptations, such as elongated bills, which can be moved more rapidly than the whole body itself, facilitating capture of the prey. Therefore, it is an open question whether such supposedly very fast swimmers do use high-speed bursts when feeding on evasive prey, in addition to using their bill for slashing prey. Here, we measured the swimming behavior of sailfish by using high-frequency accelerometry and high-speed video observations during predator-prey interactions. These measurements allowed analyses of tail beat frequencies to estimate swimming speeds. Our results suggest that sailfish burst at speeds of about 7 m s(-1) and do not exceed swimming speeds of 10 m s(-1) during predator-prey interactions. These speeds are much lower than previous estimates. In addition, the oscillations of the bill during swimming with, and without, extension of the dorsal fin (i.e., the sail) were measured. We suggest that extension of the dorsal fin may allow sailfish to improve the control of the bill and minimize its yaw, hence preventing disturbance of the prey. Therefore, sailfish, like other large predators, may rely mainly on accuracy of movement and the use of the extensions of their bodies, rather than resorting to top speeds when hunting evasive prey.
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Affiliation(s)
- Stefano Marras
- *IAMC-CNR, Istituto per l'Ambiente Marino Costiero, Consiglio Nazionale delle Ricerche, Località Sa Mardini, Torregrande, 09170 Oristano, Italy; Department of Social Informatics, Graduate School of Informatics, Kyoto University, Yoshidahonmachi, Kyoto 606-8501, Japan; Marine Biological Section, University of Copenhagen Strandpromenaden 5, DK-3000 Helsingør, Denmark; Leibniz Institute of Freshwater Ecology and Inland Fisheries, Mueggelseedamm 310, 12587 Berlin, Germany; Faculty of Life Sciences, Humboldt-Universität zu Berlin, Invalidenstrasse 42, 10115 Berlin, Germany; Fish Ecology and Conservation Physiology Laboratory, Department of Biology, Carleton University, 1125 Colonel By Drive, Ottawa, Ontario, Canada K1S 5B6; **Department of Mathematics, Uppsala University, Uppsala, 75106, Sweden; Department of Biological Sciences, Marine Sciences Program, Florida International University, North Miami, FL 33181, USA
| | - Takuji Noda
- *IAMC-CNR, Istituto per l'Ambiente Marino Costiero, Consiglio Nazionale delle Ricerche, Località Sa Mardini, Torregrande, 09170 Oristano, Italy; Department of Social Informatics, Graduate School of Informatics, Kyoto University, Yoshidahonmachi, Kyoto 606-8501, Japan; Marine Biological Section, University of Copenhagen Strandpromenaden 5, DK-3000 Helsingør, Denmark; Leibniz Institute of Freshwater Ecology and Inland Fisheries, Mueggelseedamm 310, 12587 Berlin, Germany; Faculty of Life Sciences, Humboldt-Universität zu Berlin, Invalidenstrasse 42, 10115 Berlin, Germany; Fish Ecology and Conservation Physiology Laboratory, Department of Biology, Carleton University, 1125 Colonel By Drive, Ottawa, Ontario, Canada K1S 5B6; **Department of Mathematics, Uppsala University, Uppsala, 75106, Sweden; Department of Biological Sciences, Marine Sciences Program, Florida International University, North Miami, FL 33181, USA *IAMC-CNR, Istituto per l'Ambiente Marino Costiero, Consiglio Nazionale delle Ricerche, Località Sa Mardini, Torregrande, 09170 Oristano, Italy; Department of Social Informatics, Graduate School of Informatics, Kyoto University, Yoshidahonmachi, Kyoto 606-8501, Japan; Marine Biological Section, University of Copenhagen Strandpromenaden 5, DK-3000 Helsingør, Denmark; Leibniz Institute of Freshwater Ecology and Inland Fisheries, Mueggelseedamm 310, 12587 Berlin, Germany; Faculty of Life Sciences, Humboldt-Universität zu Berlin, Invalidenstrasse 42, 10115 Berlin, Germany; Fish Ecology and Conservation Physiology Laboratory, Department of Biology, Carleton University, 1125 Colonel By Drive, Ottawa, Ontario, Canada K1S 5B6; **Department of Mathematics, Uppsala University, Uppsala, 75106, Sweden; Department of Biological Sciences, Marine Sciences Program, Florida International University, North Miami, FL 33181, USA
| | - John F Steffensen
- *IAMC-CNR, Istituto per l'Ambiente Marino Costiero, Consiglio Nazionale delle Ricerche, Località Sa Mardini, Torregrande, 09170 Oristano, Italy; Department of Social Informatics, Graduate School of Informatics, Kyoto University, Yoshidahonmachi, Kyoto 606-8501, Japan; Marine Biological Section, University of Copenhagen Strandpromenaden 5, DK-3000 Helsingør, Denmark; Leibniz Institute of Freshwater Ecology and Inland Fisheries, Mueggelseedamm 310, 12587 Berlin, Germany; Faculty of Life Sciences, Humboldt-Universität zu Berlin, Invalidenstrasse 42, 10115 Berlin, Germany; Fish Ecology and Conservation Physiology Laboratory, Department of Biology, Carleton University, 1125 Colonel By Drive, Ottawa, Ontario, Canada K1S 5B6; **Department of Mathematics, Uppsala University, Uppsala, 75106, Sweden; Department of Biological Sciences, Marine Sciences Program, Florida International University, North Miami, FL 33181, USA
| | - Morten B S Svendsen
- *IAMC-CNR, Istituto per l'Ambiente Marino Costiero, Consiglio Nazionale delle Ricerche, Località Sa Mardini, Torregrande, 09170 Oristano, Italy; Department of Social Informatics, Graduate School of Informatics, Kyoto University, Yoshidahonmachi, Kyoto 606-8501, Japan; Marine Biological Section, University of Copenhagen Strandpromenaden 5, DK-3000 Helsingør, Denmark; Leibniz Institute of Freshwater Ecology and Inland Fisheries, Mueggelseedamm 310, 12587 Berlin, Germany; Faculty of Life Sciences, Humboldt-Universität zu Berlin, Invalidenstrasse 42, 10115 Berlin, Germany; Fish Ecology and Conservation Physiology Laboratory, Department of Biology, Carleton University, 1125 Colonel By Drive, Ottawa, Ontario, Canada K1S 5B6; **Department of Mathematics, Uppsala University, Uppsala, 75106, Sweden; Department of Biological Sciences, Marine Sciences Program, Florida International University, North Miami, FL 33181, USA
| | - Jens Krause
- *IAMC-CNR, Istituto per l'Ambiente Marino Costiero, Consiglio Nazionale delle Ricerche, Località Sa Mardini, Torregrande, 09170 Oristano, Italy; Department of Social Informatics, Graduate School of Informatics, Kyoto University, Yoshidahonmachi, Kyoto 606-8501, Japan; Marine Biological Section, University of Copenhagen Strandpromenaden 5, DK-3000 Helsingør, Denmark; Leibniz Institute of Freshwater Ecology and Inland Fisheries, Mueggelseedamm 310, 12587 Berlin, Germany; Faculty of Life Sciences, Humboldt-Universität zu Berlin, Invalidenstrasse 42, 10115 Berlin, Germany; Fish Ecology and Conservation Physiology Laboratory, Department of Biology, Carleton University, 1125 Colonel By Drive, Ottawa, Ontario, Canada K1S 5B6; **Department of Mathematics, Uppsala University, Uppsala, 75106, Sweden; Department of Biological Sciences, Marine Sciences Program, Florida International University, North Miami, FL 33181, USA *IAMC-CNR, Istituto per l'Ambiente Marino Costiero, Consiglio Nazionale delle Ricerche, Località Sa Mardini, Torregrande, 09170 Oristano, Italy; Department of Social Informatics, Graduate School of Informatics, Kyoto University, Yoshidahonmachi, Kyoto 606-8501, Japan; Marine Biological Section, University of Copenhagen Strandpromenaden 5, DK-3000 Helsingør, Denmark; Leibniz Institute of Freshwater Ecology and Inland Fisheries, Mueggelseedamm 310, 12587 Berlin, Germany; Faculty of Life Sciences, Humboldt-Universität zu Berlin, Invalidenstrasse 42, 10115 Berlin, Germany; Fish Ecology and Conservation Physiology Laboratory, Department of Biology, Carleton University, 1125 Colonel By Drive, Ottawa, Ontario, Canada K1S 5B6; **Department of Mathematics, Uppsala University, Uppsala, 75106, Sweden; Department of Biological Sciences, Marine Sciences Program, Florida International University, North Miami, FL 33181, USA
| | - Alexander D M Wilson
- *IAMC-CNR, Istituto per l'Ambiente Marino Costiero, Consiglio Nazionale delle Ricerche, Località Sa Mardini, Torregrande, 09170 Oristano, Italy; Department of Social Informatics, Graduate School of Informatics, Kyoto University, Yoshidahonmachi, Kyoto 606-8501, Japan; Marine Biological Section, University of Copenhagen Strandpromenaden 5, DK-3000 Helsingør, Denmark; Leibniz Institute of Freshwater Ecology and Inland Fisheries, Mueggelseedamm 310, 12587 Berlin, Germany; Faculty of Life Sciences, Humboldt-Universität zu Berlin, Invalidenstrasse 42, 10115 Berlin, Germany; Fish Ecology and Conservation Physiology Laboratory, Department of Biology, Carleton University, 1125 Colonel By Drive, Ottawa, Ontario, Canada K1S 5B6; **Department of Mathematics, Uppsala University, Uppsala, 75106, Sweden; Department of Biological Sciences, Marine Sciences Program, Florida International University, North Miami, FL 33181, USA *IAMC-CNR, Istituto per l'Ambiente Marino Costiero, Consiglio Nazionale delle Ricerche, Località Sa Mardini, Torregrande, 09170 Oristano, Italy; Department of Social Informatics, Graduate School of Informatics, Kyoto University, Yoshidahonmachi, Kyoto 606-8501, Japan; Marine Biological Section, University of Copenhagen Strandpromenaden 5, DK-3000 Helsingør, Denmark; Leibniz Institute of Freshwater Ecology and Inland Fisheries, Mueggelseedamm 310, 12587 Berlin, Germany; Faculty of Life Sciences, Humboldt-Universität zu Berlin, Invalidenstrasse 42, 10115 Berlin, Germany; Fish Ecology and Conservation Physiology Laboratory, Department of Biology, Carleton University, 1125 Colonel By Drive, Ottawa, Ontario, Canada K1S 5B6; **Department of Mathematics, Uppsala University, Uppsala, 75106, Sweden; Department of Biological Sciences, Marine Sciences Program, Florida International University, North Miami, FL 33181, USA
| | - Ralf H J M Kurvers
- *IAMC-CNR, Istituto per l'Ambiente Marino Costiero, Consiglio Nazionale delle Ricerche, Località Sa Mardini, Torregrande, 09170 Oristano, Italy; Department of Social Informatics, Graduate School of Informatics, Kyoto University, Yoshidahonmachi, Kyoto 606-8501, Japan; Marine Biological Section, University of Copenhagen Strandpromenaden 5, DK-3000 Helsingør, Denmark; Leibniz Institute of Freshwater Ecology and Inland Fisheries, Mueggelseedamm 310, 12587 Berlin, Germany; Faculty of Life Sciences, Humboldt-Universität zu Berlin, Invalidenstrasse 42, 10115 Berlin, Germany; Fish Ecology and Conservation Physiology Laboratory, Department of Biology, Carleton University, 1125 Colonel By Drive, Ottawa, Ontario, Canada K1S 5B6; **Department of Mathematics, Uppsala University, Uppsala, 75106, Sweden; Department of Biological Sciences, Marine Sciences Program, Florida International University, North Miami, FL 33181, USA
| | - James Herbert-Read
- *IAMC-CNR, Istituto per l'Ambiente Marino Costiero, Consiglio Nazionale delle Ricerche, Località Sa Mardini, Torregrande, 09170 Oristano, Italy; Department of Social Informatics, Graduate School of Informatics, Kyoto University, Yoshidahonmachi, Kyoto 606-8501, Japan; Marine Biological Section, University of Copenhagen Strandpromenaden 5, DK-3000 Helsingør, Denmark; Leibniz Institute of Freshwater Ecology and Inland Fisheries, Mueggelseedamm 310, 12587 Berlin, Germany; Faculty of Life Sciences, Humboldt-Universität zu Berlin, Invalidenstrasse 42, 10115 Berlin, Germany; Fish Ecology and Conservation Physiology Laboratory, Department of Biology, Carleton University, 1125 Colonel By Drive, Ottawa, Ontario, Canada K1S 5B6; **Department of Mathematics, Uppsala University, Uppsala, 75106, Sweden; Department of Biological Sciences, Marine Sciences Program, Florida International University, North Miami, FL 33181, USA
| | - Kevin M Boswell
- *IAMC-CNR, Istituto per l'Ambiente Marino Costiero, Consiglio Nazionale delle Ricerche, Località Sa Mardini, Torregrande, 09170 Oristano, Italy; Department of Social Informatics, Graduate School of Informatics, Kyoto University, Yoshidahonmachi, Kyoto 606-8501, Japan; Marine Biological Section, University of Copenhagen Strandpromenaden 5, DK-3000 Helsingør, Denmark; Leibniz Institute of Freshwater Ecology and Inland Fisheries, Mueggelseedamm 310, 12587 Berlin, Germany; Faculty of Life Sciences, Humboldt-Universität zu Berlin, Invalidenstrasse 42, 10115 Berlin, Germany; Fish Ecology and Conservation Physiology Laboratory, Department of Biology, Carleton University, 1125 Colonel By Drive, Ottawa, Ontario, Canada K1S 5B6; **Department of Mathematics, Uppsala University, Uppsala, 75106, Sweden; Department of Biological Sciences, Marine Sciences Program, Florida International University, North Miami, FL 33181, USA
| | - Paolo Domenici
- *IAMC-CNR, Istituto per l'Ambiente Marino Costiero, Consiglio Nazionale delle Ricerche, Località Sa Mardini, Torregrande, 09170 Oristano, Italy; Department of Social Informatics, Graduate School of Informatics, Kyoto University, Yoshidahonmachi, Kyoto 606-8501, Japan; Marine Biological Section, University of Copenhagen Strandpromenaden 5, DK-3000 Helsingør, Denmark; Leibniz Institute of Freshwater Ecology and Inland Fisheries, Mueggelseedamm 310, 12587 Berlin, Germany; Faculty of Life Sciences, Humboldt-Universität zu Berlin, Invalidenstrasse 42, 10115 Berlin, Germany; Fish Ecology and Conservation Physiology Laboratory, Department of Biology, Carleton University, 1125 Colonel By Drive, Ottawa, Ontario, Canada K1S 5B6; **Department of Mathematics, Uppsala University, Uppsala, 75106, Sweden; Department of Biological Sciences, Marine Sciences Program, Florida International University, North Miami, FL 33181, USA
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15
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Abstract
Research on fish locomotion has expanded greatly in recent years as new approaches have been brought to bear on a classical field of study. Detailed analyses of patterns of body and fin motion and the effects of these movements on water flow patterns have helped scientists understand the causes and effects of hydrodynamic patterns produced by swimming fish. Recent developments include the study of the center-of-mass motion of swimming fish and the use of volumetric imaging systems that allow three-dimensional instantaneous snapshots of wake flow patterns. The large numbers of swimming fish in the oceans and the vorticity present in fin and body wakes support the hypothesis that fish contribute significantly to the mixing of ocean waters. New developments in fish robotics have enhanced understanding of the physical principles underlying aquatic propulsion and allowed intriguing biological features, such as the structure of shark skin, to be studied in detail.
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Affiliation(s)
- George V Lauder
- Museum of Comparative Zoology, Harvard University, Cambridge, Massachusetts 02138;
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16
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Built for speed: strain in the cartilaginous vertebral columns of sharks. ZOOLOGY 2014; 117:19-27. [DOI: 10.1016/j.zool.2013.10.007] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2013] [Revised: 10/22/2013] [Accepted: 10/25/2013] [Indexed: 11/22/2022]
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17
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Exceptional fossil preservation demonstrates a new mode of axial skeleton elongation in early ray-finned fishes. Nat Commun 2013; 4:2570. [DOI: 10.1038/ncomms3570] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2013] [Accepted: 09/05/2013] [Indexed: 11/09/2022] Open
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18
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Schwarz C, Parmentier E, Wiehr S, Gemballa S. The locomotory system of pearlfish Carapus acus: What morphological features are characteristic for highly flexible fishes? J Morphol 2011; 273:519-29. [DOI: 10.1002/jmor.11038] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2011] [Revised: 08/31/2011] [Accepted: 09/27/2011] [Indexed: 11/09/2022]
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19
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Danos N, Fisch N, Gemballa S. The musculotendinous system of an anguilliform swimmer: Muscles, myosepta, dermis, and their interconnections inAnguilla rostrata. J Morphol 2007; 269:29-44. [PMID: 17886889 DOI: 10.1002/jmor.10570] [Citation(s) in RCA: 14] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
Eel locomotion is considered typical of the anguilliform swimming mode of elongate fishes and has received substantial attention from various perspectives such as swimming kinematics, hydrodynamics, muscle physiology, and computational modeling. In contrast to the extensive knowledge of swimming mechanics, there is limited knowledge of the internal body morphology, including the body components that contribute to this function. In this study, we conduct a morphological analysis of the collagenous connective tissue system, i.e., the myosepta and skin, and of the red muscle fibers that sustain steady swimming, focusing on the interconnections between these systems, such as the muscle-tendon and myosepta-skin connections. Our aim is twofold: (1) to identify the morphological features that distinguish this anguilliform swimmer from subcarangiform and carangiform swimmers, and (2) to reveal possible pathways of muscular force transmission by the connective tissue in eels. To detect gradual morphological changes along the trunk we investigated anterior (0.4L), midbody (0.6L), and posterior body positions (0.75L) using microdissections, histology, and three-dimensional reconstructions. We find that eel myosepta have a mediolaterally oriented tendon in each the epaxial and hypaxial regions (epineural or epipleural tendon) and two longitudinally oriented tendons (myorhabdoid and lateral). The latter two are relatively short (4.5-5% of body length) and remain uniform along a rostrocaudal gradient. The skin and its connections were additionally analyzed using scanning electron microscopy (SEM). The stratum compactum of the dermis consists of approximately 30 layers of highly ordered collagen fibers of alternating caudodorsal and caudoventral direction, with fiber angles of 60.51 +/- 7.05 degrees (n = 30) and 57.58 +/- 6.92 degrees (n = 30), respectively. Myosepta insert into the collagenous dermis via fiber bundles that pass through the loose connective tissue of the stratum spongiosum of the dermis and either weave into the layers of the stratum compactum (weaving fiber bundles) or traverse the stratum compactum (transverse fiber bundles). These fiber bundles are evenly distributed along the insertion line of the myoseptum. Red muscles insert into lateral and myorhabdoid myoseptal tendons but not into the horizontal septum or dermis. Thus, red muscle forces might be distributed along these tendons but will only be delivered indirectly into the dermis and horizontal septum. The myosepta-dermis connections, however, appear to be too slack for efficient force transmission and collagenous connections between the myosepta and the horizontal septum are at obtuse angles, a morphology that appears inadequate for efficient force transmission. Though the main modes of undulatory locomotion (anguilliform, subcarangiform, and carangiform) have recently been shown to be very similar with respect to their midline kinematics, we are able to distinguish two morphological classes with respect to the shape and tendon architecture of myosepta. Eels are similar to subcarangiform swimmers (e.g., trout) but are substantially different from carangiform swimmers (e.g., mackerel). This information, in addition to data from kinematic and hydrodynamic studies of swimming, shows that features other than midline kinematics (e.g., wake patterns, muscle activation patterns, and morphology) might be better for describing the different swimming modes of fishes.
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Affiliation(s)
- Nicole Danos
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, Massachusetts 02138, USA.
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