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acta ethologica

, Volume 16, Issue 1, pp 21–30 | Cite as

Unraveling complexity in interspecies interaction through nonlinear dynamical models

  • Graciano Dieck Kattas
  • F. Javier Pérez-BarberíaEmail author
  • Michael Small
  • Xiao-Ke Xu
  • David M. Walker
Original Paper

Abstract

Unraveling complex interactions between animal species is of paramount importance to understand competition, facilitation, and community assembly processes. Using data from GPS positions of sheep (Ovis aries) and red deer (Cervus elaphus) grazing a moorland plot, we modeled the animal movement of each species as a function of the distance between individuals, with the aim to assess the role of animal interactions (i.e., attraction and repulsion) in their spatial movement. We used black box-based models. These models do not require making assumptions about the biological meaning of their parameters. They are data-driven and use embedding complex algorithms that create nonlinear functions that estimate the behavior of the system, in our case the movement of our animals, and its errors. We used an algorithm based on radial basis functions to build models of time series data, using minimum description length as the criteria for model optimization. Included in the model is a factor that captures the collective behavior of the animals based on the distance between individuals. The model emphasizes the spatial relationship between animals from the absolute navigational directions by attenuating the latter. Our simulations showed that animals of the same specie tend to group together, with sheep having a stronger grouping behavior than deer. The dynamics of the model are density dependent, that is, the number of animals within range affects the strength of the interactions and their grouping behavior. A strong swarm behavior was detected by the model, the longer the distance between species, the stronger the attraction between them; and the shorter the separation between species, the stronger their repulsion, which suggests inter- and intra-competition for food and space resources. Our modeling approach is useful to interpret animal movement interactions between animals of the same or different species, in order to unravel complex cooperative or competitive behaviors, or to make predictions of animal movement under different population scenarios.

Keywords

Animal behavior Computational modeling Social dynamics Ovis aries Cervus elaphus 

Notes

Acknowledgments

In memory of our colleague and friend Chano (Graciano Dieck Kattas) who might be watching this work from greener pastures. The field work was funded by the Scottish Government's Rural and Environment Science and Analytical Services Division (RESAS), and the Leonardo da Vinci programme (European Commission) provided grant-holders that assisted this study. We thank Russell Hooper for his support with the GPS collars and the personnel from Glensaugh Experimental Field Station for looking after the animals. GDK was supported by the Hong Kong PHD Fellowship Scheme (HKPFS) from the Research Grants Council (RGC) of Hong Kong. XKX is currently supported by the PolyU Postdoctoral Fellowships Scheme (G-YX4A) and the Research Grants Council of Hong Kong (BQ19H). XKX also acknowledges the Natural Science Foundation of China (61004104, 61104143). DMW acknowledges the Australian Research Council Discovery Projects 2012 (DP120104759) and the Melbourne Energy Institute for support.

Supplementary material

ESM 1

Video high.mp4 (MP4 44 kb)

ESM 2

Video low.mp4 (MP4 127 kb)

ESM 3

Video med.mp4 (MP4 47 kb)

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Copyright information

© Springer-Verlag and ISPA 2012

Authors and Affiliations

  • Graciano Dieck Kattas
    • 1
  • F. Javier Pérez-Barbería
    • 2
    Email author
  • Michael Small
    • 3
    • 1
  • Xiao-Ke Xu
    • 4
  • David M. Walker
    • 5
  1. 1.Department of Electronic and Information EngineeringThe Hong Kong Polytechnic UniversityHung HomHong Kong, China
  2. 2.The James Hutton InstituteAberdeenUK
  3. 3.School of Mathematics and StatisticsUniversity of Western AustraliaCrawleyAustralia
  4. 4.College of Information and Communication EngineeringDalian Nationalities UniversityDalianChina
  5. 5.Department of Mathematics and StatisticsUniversity of MelbourneMelbourneAustralia

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