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The importance of individual variation in the dynamics of animal collective movements

  • Maria del Mar Delgado
  • , Maria Miranda
  • , Silvia J. Alvarez
  • , Eliezer Gurarie
  • , William F. Fagan
  • , Vincenzo Penteriani
  • , Agustina di Virgilio
  • , Juan Manuel Morales
  • University of Oviedo
  • University of Maryland, College Park
  • Wildlife Conservation Society Colombia
  • Instituto Pirenaico de Ecología
  • Instituto de Investigaciones en Biodiversidad y Medioambiente (Consejo Nacional de Investigaciones Cientificas y Tecnicas – Universidad Nacional del Comahue)

Research output: Contribution to journalReview articlepeer-review

88 Scopus citations

Abstract

Animal collective movements are a key example of a system that links two clearly defined levels of organization: the individual and the group. Most models investigating collective movements have generated coherent collective behaviours without the inclusion of individual variability. However, new individual-based models, together with emerging empirical information, emphasize that within-group heterogeneity may strongly influence collective movement behaviour. Here we (i) review the empirical evidence for individual variation in animal collective movements, (ii) explore how theoretical investigations have represented individual heterogeneity when modelling collective movements and (iii) present a model to show how within-group heterogeneity influences the collective properties of a group. Our review underscores the need to consider variability at the level of the individual to improve our understanding of how individual decision rules lead to emergent movement patterns, and also to yield better quantitative predictions of collective behaviour.

Original languageEnglish
Article number20170008
JournalPhilosophical Transactions of the Royal Society B: Biological Sciences
Volume373
Issue number1746
DOIs
StatePublished - May 19 2018

Keywords

  • Aggregation
  • Behavioural rules
  • Collective motion
  • Context-dependent factors
  • Lagrangian models

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