Movement behavior of aquaria fish: A perspective
Abstract
The movement of fish in the aquarium typically indicates their health. Slow movements are signs of disease or stress, while rapid movements are used by fish to escape predators and show aggression. However, a very limited number of scientific publications have focused on the movement behavior of fish in aquariums. Therefore, this article was aimed at filling the knowledge gap regarding fish movement in aquaria by covering the following aspects of fish movement in aquaria: the definition and types of fish movement; the factors influencing fish movement; the methods and tools used to measure and analyze fish movement; the applications and implications of studying fish movement for ethology, ecology, and aquaculture. The article also highlights the gaps and challenges in current knowledge and suggests some directions for future research (e.g., the building of robotic systems and the development of software like Kinovea® for tracking fish movement that will be very important in the near future for ethological studies of fish). In conclusion, fish movement is a complex and dynamic phenomenon that reflects the interaction of fish with their environment, and more studies (based on robotics/AI) are needed to better understand the underlying mechanisms and consequences of fish movement in aquaria.
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Cooke SJ, Bergman JN, Twardek WM, et al. The movement ecology of fishes. Journal of Fish Biology. 2022; 101(4): 756-779. doi: 10.1111/jfb.15153
Chen X. Shoaling and Migration of Fish and Their Relationships with Environment. In: Theory and Method of Fisheries Forecasting. Springer Nature Singapore; 2022.
Singh B, Shahi N, Mallik SK. Aquatic Animal Welfare and Behavioural Health. In: Management of Fish Diseases. Springer Nature Singapore; 2025.
White PG. Environmental Management of Fish Cage Aquaculture. Journal of the Indian Society of Coastal Agricultural Research. 2021; 39(2): 229. doi: 10.54894/jiscar.39.2.2021.111852
Verhelst P, Brys R, Cooke SJ, et al. Enhancing our understanding of fish movement ecology through interdisciplinary and cross-boundary research. Reviews in Fish Biology and Fisheries. 2023; 33: 111-35.
Mushtaq ST. Aggression in aquatic environments and its relevance in aquaculture and conservation efforts. Discover Animals. 2024; 1(1). doi: 10.1007/s44338-024-00026-x
Onxayvieng K, Piria M, Fuka MM, et al. High stocking density alters growth performance, blood biochemical profiles, and hepatic antioxidative capacity in gibel carp (Carassius gibelio). Fish Physiology and Biochemistry. 2021; 47(2): 203-212. doi: 10.1007/s10695-020-00905-6
Mugwanya M, Dawood MAO, Kimera F, et al. A review on recirculating aquaculture system: influence of stocking density on fish and crustacean behavior, growth performance, and immunity. Annals of Animal Science. 2022; 22(3): 873-884. doi: 10.2478/aoas-2022-0014
Li L, Shen Y, Yang W, et al. Effect of different stocking densities on fish growth performance: A meta-analysis. Aquaculture. 2021; 544: 737152. doi: 10.1016/j.aquaculture.2021.737152
Cox RX, Kingsford RT, Suthers I, et al. Fish Injury from Movements across Hydraulic Structures: A Review. Water. 2023; 15(10): 1888. doi: 10.3390/w15101888
Akhtar N, Syakir Ishak MI, Bhawani SA, et al. Various Natural and Anthropogenic Factors Responsible for Water Quality Degradation: A Review. Water. 2021; 13(19): 2660. doi: 10.3390/w13192660
Khan A, Jafar K, Ahmad S, et al. Revision of some morphometric characteristics and building the standard haematological reference value in Rita rita from Pakistan. Journal of Entomology and Zoology Studies. 2020; 8(5).
Khan MS, Qureshi NA, Jabeen F. Assessment of toxicity in fresh water fish Labeo rohita treated with silver nanoparticles. Applied Nanoscience. 2017; 7(5): 167-179. doi: 10.1007/s13204-017-0559-x
Magnhagen C, Braithwaite VA, Forsgren E, et al. Fish Behaviour. Science Publishers Enfield, NH; 2008.
Hart PJ, Reynolds JD. Fish Biology. Blackwell Pub.; 2002.
Bell AM, Backström T, Huntingford FA, et al. Variable neuroendocrine responses to ecologically-relevant challenges in sticklebacks. Physiology & Behavior. 2007; 91(1): 15-25. doi: 10.1016/j.physbeh.2007.01.012
Tinbergen N. The study of instinct. Pygmalion Press, an imprint of Plunkett Lake Press; 2020.
Orth D. Pain, Sentience, and Animal Welfare. In: Fish, Fishing, and Conservation. Virginia Tech Publishing; 2023.
Rose JD. The Neurobehavioral Nature of Fishes and the Question of Awareness and Pain. Reviews in Fisheries Science. 2002; 10(1): 1-38. doi: 10.1080/20026491051668
Rose J. Anthropomorphism and ‘mental welfare’ of fishes. Diseases of Aquatic Organisms. 2007; 75: 139-154. doi: 10.3354/dao075139
Chandroo KP, Duncan IJH, Moccia RD. Can fish suffer?: perspectives on sentience, pain, fear and stress. Applied Animal Behaviour Science. 2004; 86(3-4): 225-250. doi: 10.1016/j.applanim.2004.02.004
Braithwaite V. Do Fish Feel Pain? Oxford: Oxford University Press; 2010.
Braithwaite V, Huntingford F. Fish and welfare: do fish have the capacity for pain perception and suffering? Animal Welfare. 2004; 13(S1): S87-S92. doi: 10.1017/s096272860001441x
Rodríguez F, Broglio C, Durán E, et al. Neural Mechanisms of Learning in Teleost Fish. Fish Cognition and Behavior; 2006.
Brown C, Laland K, Krause J. Fish Cognition and Behaviour. Fish Cognition and Behavior; 2011.
Salena MG, Turko AJ, Singh A, et al. Understanding fish cognition: a review and appraisal of current practices. Animal Cognition. 2021; 24(3): 395-406. doi: 10.1007/s10071-021-01488-2
Ogawa S, Pfaff DW, Parhar IS. Fish as a model in social neuroscience: conservation and diversity in the social brain network. Biological Reviews. 2021; 96(3): 999-1020. doi: 10.1111/brv.12689
Calvo R, Schluessel V. Neural substrates involved in the cognitive information processing in teleost fish. Animal Cognition. 2021; 24(5): 923-946. doi: 10.1007/s10071-021-01514-3
Mazzitelli-Fuentes LS, Román FR, Castillo Elías JR, et al. Spatial Learning Promotes Adult Neurogenesis in Specific Regions of the Zebrafish Pallium. Frontiers in Cell and Developmental Biology. 2022; 10. doi: 10.3389/fcell.2022.840964
Claiborne JB, Evans DH. The physiology of fishes. CRC, Taylor & Francis; 2006.
Hara TJ. Olfaction in fish. Progress in neurobiology. 1975; 5(4): 271-335. doi: 10.1016/0301-0082(75)90014-3
Magurran AE, Khachonpisitsak S, Ahmad AB. Biological diversity of fish communities: pattern and process§. Journal of Fish Biology. 2011; 79(6): 1393-1412. doi: 10.1111/j.1095-8649.2011.03091.x
Hildebrand JG. Analysis of chemical signals by nervous systems. Proceedings of the National Academy of Sciences. 1995; 92(1): 67-74. doi: 10.1073/pnas.92.1.67
Evans D. The Physiology of Fishes. CRC Press; 1998.
Jobling M. Environmental links-Sensory systems. In: Environmental biology of fishes. Chapman & Hall London; 1995.
Willmer P, Stone G, Johnston I. Environmental physiology of animals. John Wiley & Sons; 2009.
Huntingford F, Hunter W, Braithwaite V. Movement and Orientation. Oxford: Blackwell Publishing Ltd.; 2012.
Raubenheimer D, Simpson S, Sánchez-Vázquez J, et al. Nutrition and Diet Choice. In: Hart PJ, Reynolds JD (editors). Fish Biology. Vol Fish Biology. Oxford: Blackwell Publishing Ltd.; 2002.
Jobling M, Alanärä A, Kadri S, et al. Feeding Biology and Foraging. Oxford: Blackwell Publishing Ltd.; 2012.
Jobling M, Alanärä A, Noble C, et al. Appetite and Feed Intake. Oxford: Blackwell Publishing Ltd.; 2012.
Huntingford F, Coyle S, Hunter W. Avoiding Predators. Oxford: Blackwell Publishing Ltd.; 2012.
Damsgård B, Huntingford F. Fighting and Aggression. Oxford: Blackwell Publishing Ltd.; 2002.
Fleming IA, Huntingford F. Reproductive Behaviour. Oxford: Blackwell Publishing Ltd.; 2002.
An D, Huang J, Wei Y. A survey of fish behaviour quantification indexes and methods in aquaculture. Reviews in Aquaculture. 2021; 13(4): 2169-2189. doi: 10.1111/raq.12564
Pavlov D, Kasumyan A. Patterns and mechanisms of schooling behavior in fish: a review. Journal of Ichthyology. 2000; 40: S163.
Ruzzante DE. Domestication effects on aggressive and schooling behavior in fish. Aquaculture. 1994; 120: 1-24. doi: 10.1016/0044-8486(94)90217-8
Matley JK, Klinard NV, Larocque SM, et al. Making the most of aquatic animal tracking: a review of complementary methods to bolster acoustic telemetry. Reviews in Fish Biology and Fisheries; 2022.
Delcourt J, Denoël M, Ylieff M, et al. Video multitracking of fish behaviour: a synthesis and future perspectives. Fish and Fisheries. 2012; 14(2): 186-204. doi: 10.1111/j.1467-2979.2012.00462.x
Jolles JW, Boogert NJ, Sridhar VH, et al. Consistent Individual Differences Drive Collective Behavior and Group Functioning of Schooling Fish. Current Biology. 2017; 27(18): 2862-2868.e7. doi: 10.1016/j.cub.2017.08.004
Veras GC, Murgas LDS, Rosa PV, et al. Effect of photoperiod on locomotor activity, growth, feed efficiency and gonadal development of Nile tilapia. Revista Brasileira de Zootecnia. 2013; 42(12): 844-849. doi: 10.1590/s1516-35982013001200002
Biswas AK, Seoka M, Inoue Y, et al. Photoperiod influences the growth, food intake, feed efficiency and digestibility of red sea bream (Pagrus major). Aquaculture. 2005; 250(3-4): 666-673. doi: 10.1016/j.aquaculture.2005.04.047
Ginés R, Afonso JM, Argüello A, et al. Growth in adult gilthead sea bream (Sparus aurata L) as a result of interference in sexual maturation by different photoperiod regimes. Aquaculture Research. 2002; 34(1): 73-83. doi: 10.1046/j.1365-2109.2003.00801.x
Waheed A, Naz H, Wajid M, et al. Impact of background colorations on growth, movement behavior, and some body physiological factors of Nile tilapia, Oreochromis niloticus. Fish Physiology and Biochemistry. 2023; 49(2): 275-287. doi: 10.1007/s10695-023-01180-x
Waheed A, Naz H, Wajid M, et al. Impact of isolation on growth performance, behavior, and stress responses in Nile tilapia, Oreochromis niloticus. Latin American Journal of Aquatic Research. 2023; 51(4): 483-490. doi: 10.3856/vol51-issue4-fulltext-3019
Bonnet F, Cazenille L, Séguret A, et al. Design of a modular robotic system that mimics small fish locomotion and body movements for ethological studies. International Journal of Advanced Robotic Systems. 2017; 14(3): 172988141770662. doi: 10.1177/1729881417706628
da Silva Souza JG, Libeck LT, do Carmo Rodrigues Virote B, et al. A method to analyze the relationship between locomotor activity and feeding behaviour in larvae of Betta splendens. Aquaculture International. 2020; 28(3): 1141-1152. doi: 10.1007/s10499-020-00516-1
Zhang Y, Ko H, Calicchia MA, et al. Collective movement of schooling fish reduces the costs of locomotion in turbulent conditions. Hedenström A, ed. PLOS Biology. 2024; 22(6): e3002501. doi: 10.1371/journal.pbio.3002501
Abangan AS, Kopp D, Faillettaz R. Artificial intelligence for fish behavior recognition may unlock fishing gear selectivity. Frontiers in Marine Science. 2023; 10. doi: 10.3389/fmars.2023.1010761
Yang L, Liu Y, Yu H, et al. Computer Vision Models in Intelligent Aquaculture with Emphasis on Fish Detection and Behavior Analysis: A Review. Archives of Computational Methods in Engineering. 2020; 28(4): 2785-2816. doi: 10.1007/s11831-020-09486-2
Fan YL, Hsu FR, Wang Y, et al. Unlocking the Potential of Zebrafish Research with Artificial Intelligence: Advancements in Tracking, Processing, and Visualization. Medical & Biological Engineering & Computing. 2023; 61(11): 2797-2814. doi: 10.1007/s11517-023-02903-1
Ullah F, Saqib S, Xiong YC. Integrating artificial intelligence in biodiversity conservation: bridging classical and modern approaches. Biodiversity and Conservation. 2024; 34(1): 45-65. doi: 10.1007/s10531-024-02977-9
Baines R, Patiballa SK, Booth J, et al. Multi-environment robotic transitions through adaptive morphogenesis. Nature. 2022; 610(7931): 283-289. doi: 10.1038/s41586-022-05188-w
Polverino G, Soman VR, Karakaya M, et al. Ecology of fear in highly invasive fish revealed by robots. iScience. 2022; 25(1): 103529. doi: 10.1016/j.isci.2021.103529
Li T, Zhang C, Zhang G, et al. A numerical simulation research on fish adaption behavior based on deep reinforcement learning and fluid–structure coupling: The refuge–predation behaviors of intelligent fish under varying environmental pressure. Physics of Fluids. 2024; 36(12). doi: 10.1063/5.0244010
García S, Strüber D, Brugali D, et al. Software variability in service robotics. Empirical Software Engineering. 2022; 28(2). doi: 10.1007/s10664-022-10231-5
DOI: https://doi.org/10.18686/fsa2290
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