IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v414y2014icp329-339.html
   My bibliography  Save this article

Hydrodynamic effects on a predator approaching a group of preys

Author

Listed:
  • De Rosis, Alessandro

Abstract

A numerical approach to predict the hydrodynamics involving a predator approaching a group of 100 preys is presented. A collective behavioural model is adopted to predict the two-dimensional space–time evolution of the predator–preys system that is supposed to be immersed in a fluid. The preys manifest mutual repulsion, attraction and orientation, while the predator is idealized as an individual to be strongly repulsed. During the motion, the predator experiences a resistance induced by the encompassing fluid. Such effect is accounted for by computing the hydrodynamic force and by modifying the predator’s velocity given by the behavioural equations. A numerical campaign is carried out by varying the predator’s drag coefficient. Moreover, analyses characterized by progressively wider predator’s perception areas are performed, thus highlighting the role of the hydrodynamics over the behavioural interactions. In order to estimate the predator’s performance, an ad-hoc parameter is proposed. Moreover, findings in terms of trajectories and angular momentum of the group of preys are discussed. Present findings show that the sole collective behavioural equations are insufficient to predict the performance of a predator that is immersed in a fluid, since its motion is drastically affected by the resistance of the surrounding fluid.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:phsmap:v:414:y:2014:i:c:p:329-339
    DOI: 10.1016/j.physa.2014.07.062
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437114006463
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/j.physa.2014.07.062?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.
    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. Wang, Xiaohong & Jia, Jianwen, 2015. "Dynamic of a delayed predator–prey model with birth pulse and impulsive harvesting in a polluted environment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 422(C), pages 1-15.
    2. Zhang, Xinhong & Li, Wenxue & Liu, Meng & Wang, Ke, 2015. "Dynamics of a stochastic Holling II one-predator two-prey system with jumps," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 421(C), pages 571-582.

    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. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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).
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. Li, Chenyang & Yang, Yonghui & Jiang, Guanjie & Chen, Xue-Bo, 2024. "Flocking for leader ability effect and formation obstacle avoidance of multi-agents based on different potential functions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 636(C).
    17. Kong, Decheng & Xue, Kai & Wang, Ping, 2024. "Collective queuing motion of self-propelled particles with leadership and experience," Applied Mathematics and Computation, Elsevier, vol. 476(C).
    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:phsmap:v:414:y:2014:i:c:p:329-339. 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/physica-a-statistical-mechpplications/ .

    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.