Yates Christian A, Erban Radek, Escudero Carlos, Couzin Iain D, Buhl Camille, Kevrekidis Ioannis G, Maini Philip K, Sumpter David J T
Centre for Mathematical Biology, University of Oxford, 24-29 St. Giles', Oxford OX1 3LB, United Kingdom.
Proc Natl Acad Sci U S A. 2009 Apr 7;106(14):5464-9. doi: 10.1073/pnas.0811195106. Epub 2009 Mar 31.
Among the most striking aspects of the movement of many animal groups are their sudden coherent changes in direction. Recent observations of locusts and starlings have shown that this directional switching is an intrinsic property of their motion. Similar direction switches are seen in self-propelled particle and other models of group motion. Comprehending the factors that determine such switches is key to understanding the movement of these groups. Here, we adopt a coarse-grained approach to the study of directional switching in a self-propelled particle model assuming an underlying one-dimensional Fokker-Planck equation for the mean velocity of the particles. We continue with this assumption in analyzing experimental data on locusts and use a similar systematic Fokker-Planck equation coefficient estimation approach to extract the relevant information for the assumed Fokker-Planck equation underlying that experimental data. In the experiment itself the motion of groups of 5 to 100 locust nymphs was investigated in a homogeneous laboratory environment, helping us to establish the intrinsic dynamics of locust marching bands. We determine the mean time between direction switches as a function of group density for the experimental data and the self-propelled particle model. This systematic approach allows us to identify key differences between the experimental data and the model, revealing that individual locusts appear to increase the randomness of their movements in response to a loss of alignment by the group. We give a quantitative description of how locusts use noise to maintain swarm alignment. We discuss further how properties of individual animal behavior, inferred by using the Fokker-Planck equation coefficient estimation approach, can be implemented in the self-propelled particle model to replicate qualitatively the group level dynamics seen in the experimental data.
许多动物群体运动最显著的方面之一是它们方向上突然的一致变化。最近对蝗虫和椋鸟的观察表明,这种方向转换是它们运动的固有属性。在自驱动粒子和其他群体运动模型中也能看到类似的方向转换。理解决定这种转换的因素是理解这些群体运动的关键。在这里,我们采用一种粗粒度方法来研究自驱动粒子模型中的方向转换,假设粒子平均速度存在一个潜在的一维福克 - 普朗克方程。在分析蝗虫的实验数据时,我们继续采用这一假设,并使用类似的系统福克 - 普朗克方程系数估计方法来提取该实验数据背后假设的福克 - 普朗克方程的相关信息。在实验中,研究了5到100只蝗虫若虫群体在均匀实验室环境中的运动,这有助于我们确定蝗虫行军带的内在动力学。我们确定了实验数据和自驱动粒子模型中方向转换之间的平均时间作为群体密度的函数。这种系统方法使我们能够识别实验数据与模型之间的关键差异,揭示出个体蝗虫似乎会因群体排列的丧失而增加其运动的随机性。我们对蝗虫如何利用噪声来维持群体排列给出了定量描述。我们进一步讨论了如何通过福克 - 普朗克方程系数估计方法推断出的个体动物行为特性,在自驱动粒子模型中得以实现,从而定性地复制实验数据中所见的群体水平动力学。