IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v206y2007i1p153-165.html
   My bibliography  Save this article

Factors influencing the structure and maintenance of fish schools

Author

Listed:
  • Viscido, Steven V.
  • Parrish, Julia K.
  • Grünbaum, Daniel

Abstract

We explored the factors that contribute to fish school formation and maintenance using a series of computer simulation experiments. The factors we examined were mostly social, and included the functional form of attraction to – and repulsion from – neighbors, alignment with neighbors, regions of no social force (“neutral zones”), scaling of neighbor influence, random noise, and frictional drag. For each experiment, we compared the results from changing one factor with those of a “base case” that included a neutral zone 1 body length wide, linear attraction and repulsion forces, no alignment force, no scaling of neighbor influence, medium randomness, and no friction drag. We computed eight schooling metrics, two at the individual level (curvature and nearest-neighbor distance), four at the group level (group speed, polarity, group size, and expanse), and two at the population level (percent of stragglers and collision rate). For the parameter space we examined, all factors except random noise were important in determining the emergent properties of the group, as characterized by our schooling metrics. In some cases, schooling behavior was affected strongly by the presence or absence of a factor, but not to the value of the factor (e.g., drag) or its functional form (e.g., alignment force). In other cases, the results depended entirely on the functional form of the factor (e.g., attraction–repulsion; neighbor scaling). Our results indicate that a steep repulsion function is necessary to prevent collisions, and that this function must respond to local density. Second, a neutral zone must exist in which neither attraction nor repulsion operate. Third, to obtain polarity, there must be a modest alignment impulse, strong enough to induce polarity in the group, but weak enough to allow individual non-conformity. Fourth, the number and weighting of influential neighbors is crucially important in maintaining school structure. Fifth, the speed of motion is clearly important, leading to strong differences in school packing, individual path curvature, and polarization, between rapidly moving (with no drag present) and slow-moving (with high drag present) groups. Finally, individuality or non-conformity to group behavior, which most authors represent by randomness, likely plays a role in determining schooling behavior, although it was not a strong factor in our model. Each of these factors is important in determining the local interactions that give rise to emergent properties in fish schools.

Suggested Citation

  • Viscido, Steven V. & Parrish, Julia K. & Grünbaum, Daniel, 2007. "Factors influencing the structure and maintenance of fish schools," Ecological Modelling, Elsevier, vol. 206(1), pages 153-165.
  • Handle: RePEc:eee:ecomod:v:206:y:2007:i:1:p:153-165
    DOI: 10.1016/j.ecolmodel.2007.03.042
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380007001755
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ecolmodel.2007.03.042?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Iain D. Couzin & Jens Krause & Nigel R. Franks & Simon A. Levin, 2005. "Effective leadership and decision-making in animal groups on the move," Nature, Nature, vol. 433(7025), pages 513-516, February.
    2. Charlotte K. Hemelrijk & Hanspeter Kunz, 2005. "Density distribution and size sorting in fish schools: an individual-based model," Behavioral Ecology, International Society for Behavioral Ecology, vol. 16(1), pages 178-187, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Romey, William L. & Vidal, Jose M., 2013. "Sum of heterogeneous blind zones predict movements of simulated groups," Ecological Modelling, Elsevier, vol. 258(C), pages 9-15.
    2. Reuter, Hauke & Kruse, Maren & Rovellini, Alberto & Breckling, Broder, 2016. "Evolutionary trends in fish schools in heterogeneous environments," Ecological Modelling, Elsevier, vol. 326(C), pages 23-35.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Vabø, Rune & Skaret, Georg, 2008. "Emerging school structures and collective dynamics in spawning herring: A simulation study," Ecological Modelling, Elsevier, vol. 214(2), pages 125-140.
    2. Simon Levin & Anastasios Xepapadeas, 2021. "On the Coevolution of Economic and Ecological Systems," Annual Review of Resource Economics, Annual Reviews, vol. 13(1), pages 355-377, October.
    3. Becco, Ch. & Vandewalle, N. & Delcourt, J. & Poncin, P., 2006. "Experimental evidences of a structural and dynamical transition in fish school," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 367(C), pages 487-493.
    4. Long-Hai Wang & Alexander Ulrich Ernst & Duo An & Ashim Kumar Datta & Boris Epel & Mrignayani Kotecha & Minglin Ma, 2021. "A bioinspired scaffold for rapid oxygenation of cell encapsulation systems," Nature Communications, Nature, vol. 12(1), pages 1-16, December.
    5. Richard P Mann, 2011. "Bayesian Inference for Identifying Interaction Rules in Moving Animal Groups," PLOS ONE, Public Library of Science, vol. 6(8), pages 1-10, August.
    6. Ma, Jian & Song, Wei-guo & Zhang, Jun & Lo, Siu-ming & Liao, Guang-xuan, 2010. "k-Nearest-Neighbor interaction induced self-organized pedestrian counter flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(10), pages 2101-2117.
    7. Andrew Hoegh & Frank T. Manen & Mark Haroldson, 2021. "Agent-Based Models for Collective Animal Movement: Proximity-Induced State Switching," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 26(4), pages 560-579, December.
    8. Tamás Nepusz & Tamás Vicsek, 2013. "Hierarchical Self-Organization of Non-Cooperating Individuals," PLOS ONE, Public Library of Science, vol. 8(12), pages 1-9, December.
    9. Amos Korman & Efrat Greenwald & Ofer Feinerman, 2014. "Confidence Sharing: An Economic Strategy for Efficient Information Flows in Animal Groups," PLOS Computational Biology, Public Library of Science, vol. 10(10), pages 1-10, October.
    10. Roy Harpaz & Minh Nguyet Nguyen & Armin Bahl & Florian Engert, 2021. "Precise visuomotor transformations underlying collective behavior in larval zebrafish," Nature Communications, Nature, vol. 12(1), pages 1-14, December.
    11. Li, Qing & Zhang, Lingwei & Jia, Yongnan & Lu, Tianzhao & Chen, Xiaojie, 2022. "Modeling, analysis, and optimization of three-dimensional restricted visual field metric-free swarms," Chaos, Solitons & Fractals, Elsevier, vol. 157(C).
    12. Mathew Titus & George Hagstrom & James R Watson, 2021. "Unsupervised manifold learning of collective behavior," PLOS Computational Biology, Public Library of Science, vol. 17(2), pages 1-20, February.
    13. Sophie Lardy & Daniel Fortin & Olivier Pays, 2016. "Increased Exploration Capacity Promotes Group Fission in Gregarious Foraging Herbivores," PLOS ONE, Public Library of Science, vol. 11(12), pages 1-14, December.
    14. Fan, Kangqi & Pedrycz, Witold, 2016. "Opinion evolution influenced by informed agents," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 431-441.
    15. De Rosis, Alessandro, 2014. "Hydrodynamic effects on a predator approaching a group of preys," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 414(C), pages 329-339.
    16. Shao, Zhi-Gang & Yang, Yan-Yan, 2015. "Effective strategies of collective evacuation from an enclosed space," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 427(C), pages 34-39.
    17. Panpan Yang & Maode Yan & Jiacheng Song & Ye Tang, 2019. "Self-Organized Fission-Fusion Control Algorithm for Flocking Systems Based on Intermittent Selective Interaction," Complexity, Hindawi, vol. 2019, pages 1-12, February.
    18. Huepe, Cristián & Aldana, Maximino, 2008. "New tools for characterizing swarming systems: A comparison of minimal models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(12), pages 2809-2822.
    19. Federico Pratissoli & Andreagiovanni Reina & Yuri Kaszubowski Lopes & Carlo Pinciroli & Genki Miyauchi & Lorenzo Sabattini & Roderich Groß, 2023. "Coherent movement of error-prone individuals through mechanical coupling," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    20. Milad Haghani & Majid Sarvi & Zahra Shahhoseini & Maik Boltes, 2016. "How Simple Hypothetical-Choice Experiments Can Be Utilized to Learn Humans’ Navigational Escape Decisions in Emergencies," PLOS ONE, Public Library of Science, vol. 11(11), pages 1-24, November.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecomod:v:206:y:2007:i:1:p:153-165. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/ecological-modelling .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.