Why swarming insects have perplexing spatial statistics.

IF 2 4区生物学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY

Physical biology Pub Date : 2025-06-12 DOI:10.1088/1478-3975/addf08

Andy Reynolds

引用次数: 0

Abstract

Unlike flocks of birds and schools of fish that show net motion and synchronized motion, insect mating swarms are stationary and lack velocity ordering. Their collective nature when unperturbed is instead evident in their spatial statistics. In stark contrast with bird flocks, wherein the number density can fluctuate enormously from flock to flock, the number density of individuals in laboratory swarms of the midgeChironomus ripariusis approximately constant. Nonetheless, as swarms grow more populous, individuals cluster more and more. Here with the aid of stochastic trajectory models I show that these two seemingly contradictory behaviours can be attributed to the presence of multiplicative noise. The modelling also predicts that swarms are most stable when they are asymptotically large.

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为什么成群的昆虫有令人困惑的空间统计。

与鸟群和鱼群表现出净运动和同步运动不同，昆虫交配群是静止的，缺乏速度顺序。在不受干扰的情况下，它们的集体性质在它们的空间统计中表现得很明显。与鸟类种群的数量密度在不同种群间波动很大形成鲜明对比的是，河摇蚊实验室种群的个体数量密度几乎是恒定的。尽管如此，随着蜂群的数量越来越多，个体也越来越多地聚集在一起。在这里，借助随机轨迹模型，我证明了这两种看似矛盾的行为可以归因于乘法噪声的存在。该模型还预测，当群体渐近大时，它们是最稳定的。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Physical biology 生物-生物物理

CiteScore

4.20

自引率

0.00%

发文量

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.