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Author (up) Parrish, J. K.; Viscido, S. V.
Title Traffic rules of fish schools: A review of agent-based approaches. Type Book Chapter
Year 2005 Publication Self-organisation and the evolution of social behaviour. Abbreviated Journal
Volume Issue Pages 50-80
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Publisher Cambridge University Press Place of Publication Cambridge Editor C. K. Hemelrijk
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Notes Approved no
Call Number Equine Behaviour @ team @ Serial 5419
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Author (up) Parrish, J.K.; Viscido, S.V.; Grunbaum, D.
Title Self-Organized Fish Schools: An Examination of Emergent Properties Type Journal Article
Year 2002 Publication Biol Bull Abbreviated Journal Biol Bull
Volume 202 Issue 3 Pages 296-305
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Abstract Heterogeneous, “aggregated” patterns in the spatial distributions of individuals are almost universal across living organisms, from bacteria to higher vertebrates. Whereas specific features of aggregations are often visually striking to human eyes, a heuristic analysis based on human vision is usually not sufficient to answer fundamental questions about how and why organisms aggregate. What are the individual-level behavioral traits that give rise to these features? When qualitatively similar spatial patterns arise from purely physical mechanisms, are these patterns in organisms biologically significant, or are they simply epiphenomena that are likely characteristics of any set of interacting autonomous individuals? If specific features of spatial aggregations do confer advantages or disadvantages in the fitness of group members, how has evolution operated to shape individual behavior in balancing costs and benefits at the individual and group levels? Mathematical models of social behaviors such as schooling in fishes provide a promising avenue to address some of these questions. However, the literature on schooling models has lacked a common framework to objectively and quantitatively characterize relationships between individual-level behaviors and group-level patterns. In this paper, we briefly survey similarities and differences in behavioral algorithms and aggregation statistics among existing schooling models. We present preliminary results of our efforts to develop a modeling framework that synthesizes much of this previous work, and to identify relationships between behavioral parameters and group-level statistics. N1 -
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Call Number Equine Behaviour @ team @ Serial 5254
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Author (up) Reluga, T.C.; Viscido, S.
Title Simulated evolution of selfish herd behavior Type Journal Article
Year 2005 Publication Journal of Theoretical Biology Abbreviated Journal J. Theor. Biol.
Volume 234 Issue 2 Pages 213-225
Keywords Selfish herd; Behavior; Evolution; Predation risk
Abstract Single species aggregations are a commonly observed phenomenon. One potential explanation for these aggregations is provided by the selfish herd hypothesis, which states that aggregations result from individual efforts to reduce personnel predation risk at the expense of group-mates. Not all movement rules based on the selfish herd hypothesis are consistent with observed animal behavior. Previous work has shown that herd-like aggregations are not generated by movement rules limited to local interactions between nearest neighbors. Instead, rules generating realistic herds appear to require delocalized interactions. To date, it has been an open question whether or not the necessary delocalization can emerge from local interactions under natural selection. To address this question, we study an individual-based model with a single quantitative genetic trait that controls the influence of neighbors as a function of distance. The results indicate that predation-based selection can increase the influence of distant neighbors relative to near neighbors. Our results lend support for the idea that selfish herd behavior can arise from localized movement rules under natural selection.
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Call Number refbase @ user @ Serial 553
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Author (up) Viscido, S.V.; Miller, M.; Wethey, D.S.
Title The dilemma of the selfish herd: the search for a realistic movement rule Type Journal Article
Year 2002 Publication Journal of theoretical biology Abbreviated Journal J. Theor. Biol.
Volume 217 Issue 2 Pages 183-194
Keywords Animals; *Behavior, Animal; *Mass Behavior; Models, Biological; *Motor Activity; Predatory Behavior
Abstract The selfish herd hypothesis predicts that aggregations form because individuals move toward one another to minimize their own predation risk. The “dilemma of the selfish herd” is that movement rules that are easy for individuals to follow, fail to produce true aggregations, while rules that produce aggregations require individual behavior so complex that one may doubt most animals can follow them. If natural selection at the individual level is responsible for herding behavior, a solution to the dilemma must exist. Using computer simulations, we examined four different movement rules. Relative predation risk was different for all four movement rules (p<0.05). We defined three criteria for measuring the quality of a movement rule. A good movement rule should (a) be statistically likely to benefit an individual that follows it, (b) be something we can imagine most animals are capable of following, and (c) result in a centrally compact flock. The local crowded horizon rule, which allowed individuals to take the positions of many flock-mates into account, but decreased the influence of flock-mates with distance, best satisfied these criteria. The local crowded horizon rule was very sensitive to the animal's perceptive ability. Therefore, the animal's ability to detect its neighbors is an important factor in the dynamics of group formation.
Address Department of Biological Sciences, University of South Carolina, Columbia, SC, 29208, USA. viscido@u.washington.edu
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Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0022-5193 ISBN Medium
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Notes PMID:12202112 Approved no
Call Number refbase @ user @ Serial 554
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Author (up) Viscido, S.V.; Miller, M.; Wethey, D.S.
Title The response of a selfish herd to an attack from outside the group perimeter Type Journal Article
Year 2001 Publication Journal of theoretical biology Abbreviated Journal J. Theor. Biol.
Volume 208 Issue 3 Pages 315-328
Keywords Animals; *Behavior, Animal; *Computer Simulation; Models, Biological; *Movement; Predatory Behavior
Abstract According to the selfish herd hypothesis, animals can decrease predation risk by moving toward one another if the predator can appear anywhere and will attack the nearest target. Previous studies have shown that aggregations can form using simple movement rules designed to decrease each animal's Domain of Danger. However, if the predator attacks from outside the group's perimeter, these simple movement rules might not lead to aggregation. To test whether simple selfish movement rules would decrease predation risk for those situations when the predator attacks from outside the flock perimeter, we constructed a computer model that allowed flocks of 75 simulated fiddler crabs to react to one another, and to a predator attacking from 7 m away. We attacked simulated crab flocks with predators of different sizes and attack speeds, and computed relative predation risk after 120 time steps. Final trajectories showed flight toward the center of the flock, but curving away from the predator. Path curvature depended on the predator's size and approach speed. The average crab experienced a greater decrease in predation risk when the predator was small or slow moving. Regardless of the predator's size and speed, however, predation risk always decreased as long as crabs took their flock-mates into account. We conclude that, even when flight away from an external predator occurs, the selfish avoidance of danger can lead to aggregation.
Address Department of Biological Sciences, University of South Carolina, Columbia, SC 29208, U.S.A. viscido@u.washington.edu
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Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0022-5193 ISBN Medium
Area Expedition Conference
Notes PMID:11207093 Approved no
Call Number refbase @ user @ Serial 555
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