蝗虫行进的有效流体力学描述。

IF 2 4区 生物学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY Physical biology Pub Date : 2024-02-14 DOI:10.1088/1478-3975/ad2219
Dan Gorbonos, Felix B Oberhauser, Luke L Costello, Yannick Günzel, Einat Couzin-Fuchs, Benjamin Koger, Iain D Couzin
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引用次数: 0

摘要

复杂系统的一个基本问题是如何将单个成分之间的相互作用("微观描述")与系统的整体特性("宏观描述")联系起来。此外,这种宏观描述是否存在,以及这种描述是否能捕捉到大尺度特性,目前尚不清楚。在此,我们以沙漠蝗虫的集体运动为例,探讨对复杂生物系统进行宏观描述的有效性。世界上最具破坏性的昆虫灾害之一始于不会飞的幼蝗虫组成的 "行军队伍"。这些蝗虫在半干旱的栖息地中寻找食物,表现出惊人的协调运动能力。我们研究了宏观物理模型能在多大程度上描述蝗虫在带内的流动。为此,我们拍摄了肯尼亚蝗灾爆发时蝗虫在行进队伍中的情况,并自动跟踪了所有通过摄像机画面的蝗虫个体。我们首先分析了近邻的空间拓扑结构,发现蝗虫个体呈等向分布。尽管表面上看是随机的,但在径向分布函数的高密度区域观察到了局部有序性,类似于有序流体。此外,重建蝗虫个体的运动轨迹显示出高度一致的运动,这与托纳-图方程的一维版本相一致,托纳-图方程是流体纳维-斯托克斯方程的广义版本,用于描述活性颗粒的等效宏观流体特性。利用这个将压力梯度与加速度相关联的有效 Toner-Tu 方程,我们发现蝗虫的有效 "压力 "在极化程度最高的区段(一维近似最适合该区段)随着密度的线性增加而增加。因此,我们的研究证明了对鼠疫蝗群流动动力学的有效流体力学描述。
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An effective hydrodynamic description of marching locusts.

A fundamental question in complex systems is how to relate interactions between individual components ('microscopic description') to the global properties of the system ('macroscopic description'). Furthermore, it is unclear whether such a macroscopic description exists and if such a description can capture large-scale properties. Here, we address the validity of a macroscopic description of a complex biological system using the collective motion of desert locusts as a canonical example. One of the world's most devastating insect plagues begins when flightless juvenile locusts form 'marching bands'. These bands display remarkable coordinated motion, moving through semiarid habitats in search of food. We investigated how well macroscopic physical models can describe the flow of locusts within a band. For this, we filmed locusts within marching bands during an outbreak in Kenya and automatically tracked all individuals passing through the camera frame. We first analyzed the spatial topology of nearest neighbors and found individuals to be isotropically distributed. Despite this apparent randomness, a local order was observed in regions of high density in the radial distribution function, akin to an ordered fluid. Furthermore, reconstructing individual locust trajectories revealed a highly aligned movement, consistent with the one-dimensional version of the Toner-Tu equations, a generalization of the Navier-Stokes equations for fluids, used to describe the equivalent macroscopic fluid properties of active particles. Using this effective Toner-Tu equation, which relates the gradient of the pressure to the acceleration, we show that the effective 'pressure' of locusts increases as a linear function of density in segments with the highest polarization (for which the one-dimensional approximation is most appropriate). Our study thus demonstrates an effective hydrodynamic description of flow dynamics in plague locust swarms.

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来源期刊
Physical biology
Physical biology 生物-生物物理
CiteScore
4.20
自引率
0.00%
发文量
50
审稿时长
3 months
期刊介绍: Physical Biology publishes articles in the broad interdisciplinary field bridging biology with the physical sciences and engineering. This journal focuses on research in which quantitative approaches – experimental, theoretical and modeling – lead to new insights into biological systems at all scales of space and time, and all levels of organizational complexity. Physical Biology accepts contributions from a wide range of biological sub-fields, including topics such as: molecular biophysics, including single molecule studies, protein-protein and protein-DNA interactions subcellular structures, organelle dynamics, membranes, protein assemblies, chromosome structure intracellular processes, e.g. cytoskeleton dynamics, cellular transport, cell division systems biology, e.g. signaling, gene regulation and metabolic networks cells and their microenvironment, e.g. cell mechanics and motility, chemotaxis, extracellular matrix, biofilms cell-material interactions, e.g. biointerfaces, electrical stimulation and sensing, endocytosis cell-cell interactions, cell aggregates, organoids, tissues and organs developmental dynamics, including pattern formation and morphogenesis physical and evolutionary aspects of disease, e.g. cancer progression, amyloid formation neuronal systems, including information processing by networks, memory and learning population dynamics, ecology, and evolution collective action and emergence of collective phenomena.
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