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Sum of heterogeneous blind zones predict movements of simulated groups

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  • Romey, William L.
  • Vidal, Jose M.

Abstract

Simulation models regarding groups of fish and birds based on individual movement decision rules have become increasingly sophisticated. Recent studies have started to tie together how the rules of homogeneous independent-acting individuals lead to emergent group behaviors. However, there is less research on the role that heterogeneity within a group has on these emergent properties. Heterogeneity in real animal groups due to hunger, sex, body size, species, and age can influence speed, nearest neighbor distance, and viewing angle. In our study we examine how differences in viewing angle (or its complement: blind zone) within a group influence emergent properties such as group size, polarization, group shape, and segregation. Simulated groups were assembled with different mixes of blind zones (e.g. half the members with a blind zone of 60 degrees and half with a blind zone of 120 degrees). Significant differences in many of the measured emergent properties were found and were related to the level of heterogeneity as well as the absolute value of the blind zone. In homogeneous groups, increased values for the blind zone led to groups that were: smaller, more elongated, and denser. In heterogeneous groups the sum of blind zones predicted emergent group behaviors. Specifically, as the sum of the blind zones increased: group size and density decreased and the shape of the group became rounder. However, several mixes produced emergent properties that were very different than the predicted regressions. Our findings suggest that it will be important for researchers to look at how individual differences in blind zones within real groups such as fish schools and bird flocks influence emergent behaviors. Our findings also have applications to designing sensor systems for car navigation systems and robotic arrays.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:ecomod:v:258:y:2013:i:c:p:9-15
    DOI: 10.1016/j.ecolmodel.2013.02.020
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    References listed on IDEAS

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    1. William L. Romey & Emily Galbraith, 2008. "Optimal group positioning after a predator attack: the influence of speed, sex, and satiation within mobile whirligig swarms," Behavioral Ecology, International Society for Behavioral Ecology, vol. 19(2), pages 338-343.
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    3. Lesley J. Morrell & William L. Romey, 2008. "Optimal individual positions within animal groups," Behavioral Ecology, International Society for Behavioral Ecology, vol. 19(4), pages 909-919.
    4. Hedrick, J. K. & Mcmahnon, D. H. & Swaroop, D., 1993. "Vehicle Modeling And Control For Automated Highway Systems," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt81q709jn, Institute of Transportation Studies, UC Berkeley.
    5. 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.
    6. 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.
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    1. van Weerden, J. Fransje & Verbrugge, Rineke & Hemelrijk, Charlotte K., 2020. "Modelling non-attentional visual information transmission in groups under predation," Ecological Modelling, Elsevier, vol. 431(C).

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