A limit in the dynamic increase in the accuracy of group migration
A limit in the dynamic increase in the accuracy of group migration
复制标题
DOI：
10.1016/j.biosystems.2018.02.003
复制
发表时间：
2018-04-01
期刊：
影响因子：
1.6
通讯作者：
Binhi, Vladimir N.
中科院分区：
文献类型：
--
作者：
Binhi, Vladimir N.
许多迁徙动物经常旅行数千公里，准确地找到它们的季节性目的地。这种能力的本质仍然没有完全被理解。动物群聚及其社会协调运动被认为是消除导航误差的一种方式。一个群体的定向准确率可能显著更高，因为社会互动导致的各种偶然因素造成的误差是平均的。这个被称为“许多错误原理”的想法已经在行为实验和数值模拟中得到了证实。然而，关于这种效应与个体数量N之间的依赖关系，我们知之甚少。到目前为止，还没有考虑这种影响及其局限性的分析模型。本文提出了一种基于航向偏角及其方差的群航随机动态模型。发现了偏差方差的N相依性。方差首先随着N的增加而减小，但减小的速度随后减慢，从而表明不符合“多错原则”。这可以被解释为，由于将个人聚集成群体，移徙准确性的增长是有限的。这个极限取决于动物指南针的个体敏感度、羊群本能的力量和随机噪音的水平。(C)2018爱思唯尔B.V.保留所有权利。
Many migratory animals regularly travel thousands of kilometers, exactly finding their seasonal destinations. The nature of this ability is still not fully understood. The aggregation of animals in groups and their socially coordinated movement is considered a way to eliminate navigational errors. Orientation accuracy of a group may be significantly higher as the errors caused by a variety of casual factors are averaged due to social interactions. This idea, called the "many wrongs principle," has been confirmed both in behavioral experiments and numerical simulations. However, little is known about the dependence of this effect on the number N of individuals. Until now, there were no analytical models considering this effect and its limitations. In this article, a stochastic dynamic model of group navigation is presented in terms of the course deviation angle and its variance. The N-dependence of the variance of deviations is found. The variance first decreases with N, however the decrease then slows down thus showing disagreement with the "many wrongs principle." This can be interpreted as meaning that the growth in the accuracy of migration due to the aggregation of individuals into groups is limited. The limit depends on the individual sensitivity of the animal compass, the power of the herd instinct, and the level of random noise. (C) 2018 Elsevier B.V. All rights reserved.