IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v14y2023i1d10.1038_s41467-023-40523-3.html
   My bibliography  Save this article

Fine-scale collective movements reveal present, past and future dynamics of a multilevel society in Przewalski’s horses

Author

Listed:
  • Katalin Ozogány

    (University of Debrecen
    University of Debrecen)

  • Viola Kerekes

    (Hortobágy National Park Directorate)

  • Attila Fülöp

    (University of Debrecen
    University of Debrecen
    Babeș-Bolyai University
    Babeș-Bolyai University)

  • Zoltán Barta

    (University of Debrecen
    University of Debrecen)

  • Máté Nagy

    (Hungarian Academy of Sciences
    Eötvös Loránd University
    Hungarian Academy of Sciences
    Max Planck Institute of Animal Behavior)

Abstract

Studying animal societies needs detailed observation of many individuals, but technological advances offer new opportunities in this field. Here, we present a state-of-the-art drone observation of a multilevel herd of Przewalski’s horses, consisting of harems (one-male, multifemale groups). We track, in high spatio-temporal resolution, the movements of 238 individually identified horses on drone videos, and combine movement analyses with demographic data from two decades of population monitoring. Analysis of collective movements reveals how the structure of the herd’s social network is related to kinship and familiarity of individuals. The network centrality of harems is related to their age and how long the harem stallions have kept harems previously. Harems of genetically related stallions are closer to each other in the network, and female exchange is more frequent between closer harems. High movement similarity of females from different harems predicts becoming harem mates in the future. Our results show that only a few minutes of fine-scale movement tracking combined with high throughput data driven analysis can reveal the structure of a society, reconstruct past group dynamics and predict future ones.

Suggested Citation

  • Katalin Ozogány & Viola Kerekes & Attila Fülöp & Zoltán Barta & Máté Nagy, 2023. "Fine-scale collective movements reveal present, past and future dynamics of a multilevel society in Przewalski’s horses," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-40523-3
    DOI: 10.1038/s41467-023-40523-3
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-023-40523-3
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/s41467-023-40523-3?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
    ---><---

    References listed on IDEAS

    as
    1. Máté Nagy & Zsuzsa Ákos & Dora Biro & Tamás Vicsek, 2010. "Hierarchical group dynamics in pigeon flocks," Nature, Nature, vol. 464(7290), pages 890-893, April.
    2. Xiao-Guang Qi & Paul A. Garber & Weihong Ji & Zhi-Pang Huang & Kang Huang & Peng Zhang & Song-Tao Guo & Xiao-Wei Wang & Gang He & Pei Zhang & Bao-Guo Li, 2014. "Satellite telemetry and social modeling offer new insights into the origin of primate multilevel societies," Nature Communications, Nature, vol. 5(1), pages 1-10, December.
    3. Marcelino, Rui & Sampaio, Jaime & Amichay, Guy & Gonçalves, Bruno & Couzin, Iain D. & Nagy, Máté, 2020. "Collective movement analysis reveals coordination tactics of team players in football matches," Chaos, Solitons & Fractals, Elsevier, vol. 138(C).
    Full references (including those not matched with items on IDEAS)

    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. Li Jiang & Luca Giuggioli & Andrea Perna & Ramón Escobedo & Valentin Lecheval & Clément Sire & Zhangang Han & Guy Theraulaz, 2017. "Identifying influential neighbors in animal flocking," PLOS Computational Biology, Public Library of Science, vol. 13(11), pages 1-32, November.
    2. Liang, Rizhou & Zhang, Jiqiang & Zheng, Guozhong & Chen, Li, 2021. "Social hierarchy promotes the cooperation prevalence," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 567(C).
    3. Carlo Bianca & Marco Menale, 2019. "A Convergence Theorem for the Nonequilibrium States in the Discrete Thermostatted Kinetic Theory," Mathematics, MDPI, vol. 7(8), pages 1-13, July.
    4. Gergely Tibély & David Sousa-Rodrigues & Péter Pollner & Gergely Palla, 2016. "Comparing the Hierarchy of Keywords in On-Line News Portals," PLOS ONE, Public Library of Science, vol. 11(11), pages 1-15, November.
    5. 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.
    6. 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.
    7. 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).
    8. Zhang, Jiu & Jin, Li-Fu & Zheng, Bo & Li, Yan & Jiang, Xiong-Fei, 2022. "Simplified calculations of time correlation functions in non-stationary complex financial systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 589(C).
    9. Ballı, Serkan & Özdemir, Engin, 2021. "A novel method for prediction of EuroLeague game results using hybrid feature extraction and machine learning techniques," Chaos, Solitons & Fractals, Elsevier, vol. 150(C).
    10. 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.
    11. 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).
    12. Pakpour, Fatemeh & Vicsek, Tamás, 2024. "Delay-induced phase transitions in active matter," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 634(C).
    13. Partha S Bhagavatula & Charles Claudianos & Michael R Ibbotson & Mandyam V Srinivasan, 2014. "Behavioral Lateralization and Optimal Route Choice in Flying Budgerigars," PLOS Computational Biology, Public Library of Science, vol. 10(3), pages 1-13, March.
    14. Néstor Sepúlveda & Laurence Petitjean & Olivier Cochet & Erwan Grasland-Mongrain & Pascal Silberzan & Vincent Hakim, 2013. "Collective Cell Motion in an Epithelial Sheet Can Be Quantitatively Described by a Stochastic Interacting Particle Model," PLOS Computational Biology, Public Library of Science, vol. 9(3), pages 1-12, March.
    15. Guang-Hui Xu & Meng Xu & Ming-Feng Ge & Teng-Fei Ding & Feng Qi & Meng Li, 2020. "Distributed Event-Based Control of Hierarchical Leader-Follower Networks with Time-Varying Layer-To-Layer Delays," Energies, MDPI, vol. 13(7), pages 1-14, April.
    16. Yandong Xiao & Xiaokang Lei & Zhicheng Zheng & Yalun Xiang & Yang-Yu Liu & Xingguang Peng, 2024. "Perception of motion salience shapes the emergence of collective motions," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
    17. Yilun Shang & Yamei Ye, 2017. "Leader-Follower Fixed-Time Group Consensus Control of Multiagent Systems under Directed Topology," Complexity, Hindawi, vol. 2017, pages 1-9, March.
    18. Nauta, Johannes & Simoens, Pieter & Khaluf, Yara, 2022. "Group size and resource fractality drive multimodal search strategies: A quantitative analysis on group foraging," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 590(C).
    19. Guy Amichay & Liang Li & Máté Nagy & Iain D. Couzin, 2024. "Revealing the mechanism and function underlying pairwise temporal coupling in collective motion," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    20. Zafeiris, Anna & Koman, Zsombor & Mones, Enys & Vicsek, Tamás, 2017. "Phenomenological theory of collective decision-making," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 479(C), pages 287-298.

    More about this item

    Statistics

    Access and download statistics

    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:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-40523-3. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    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.