Swarm formation as backward diffusion.

IF 2 4区 生物学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY
Andy M Reynolds, Nicholas T Ouellette
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引用次数: 0

Abstract

Considerable progress has been made in understanding insect swarms-forms of collective animal behaviour that unlike bird flocks, fish schools and animal herds do not possess global order. Nonetheless, little is known about swarm formation. Here we posit a mechanism for the formation of insect swarms that is consistent with recent empirical observations reported by (Patel and Ouellette 2022). It correctly predicts new features of swarm formation that have not been reported on previously. Our simple analytically tractable model shows how harmonic potential wells, a characteristic feature of swarming, and so swarm cohesion, arise from diffusion and local fission-fusion dynamics and how, in accord with observations, these wells deepen over time. The overall form of these potential wells is predicted to depend on the number and spatial distribution of all individuals, making them manifestly a collective phenomenon. Finally, swarms are predicted to 'cool' (that is, condense) as they form.

蜂群形成为逆向扩散。
昆虫群是一种集体动物行为形式,与鸟群、鱼群和动物群不同,它们不具有全球秩序。尽管如此,人们对蜂群的形成知之甚少。在这里,我们假设昆虫群形成的机制与(Patel和Ouellette 2022)最近报告的经验观察一致。它正确地预测了以前没有报道过的群体形成的新特征。我们的简单的易处理的分析模型显示了谐波势阱(群体的一个特征)是如何从扩散和局部裂变聚变动力学中产生的,以及这些势阱是如何随着时间的推移而加深的,这与观测结果一致。据预测,这些潜在井的整体形式取决于所有个体的数量和空间分布,使它们明显成为一种集体现象。最后,预计蜂群在形成时会“冷却”(即凝结)。
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
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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