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Noisy Circumnutations Facilitate Self-Organized Shade Avoidance in Sunflowers
Physical Review X ( IF 11.6 ) Pub Date : 2024-08-15 , DOI: 10.1103/physrevx.14.031027 Chantal Nguyen 1 , Imri Dromi 2, 3 , Ahron Kempinski 2, 3 , Gabriella E. C. Gall 2, 3, 4, 5 , Orit Peleg 1, 1, 1, 1, 1, 6 , Yasmine Meroz 2, 3
Physical Review X ( IF 11.6 ) Pub Date : 2024-08-15 , DOI: 10.1103/physrevx.14.031027 Chantal Nguyen 1 , Imri Dromi 2, 3 , Ahron Kempinski 2, 3 , Gabriella E. C. Gall 2, 3, 4, 5 , Orit Peleg 1, 1, 1, 1, 1, 6 , Yasmine Meroz 2, 3
Affiliation
Circumnutations are widespread in plants and typically associated with exploratory movements; however, a quantitative understanding of their role remains elusive. In this study we report, for the first time, the role of noisy circumnutations in facilitating an optimal growth pattern within a crowded group of mutually shading plants. We revisit the problem of self-organization observed for sunflowers, mediated by shade response interactions. Our analysis reveals that circumnutation movements conform to a bounded random walk characterized by a remarkably broad distribution of velocities, covering 3 orders of magnitude. In motile animal systems such wide distributions of movement velocities are frequently identified with enhancement of behavioral processes, suggesting that circumnutations may serve as a source of functional noise. To test our hypothesis, we developed a Langevin-type parsimonious model of interacting growing disks, informed by experiments, successfully capturing the characteristic dynamics of individual and multiple interacting plants. Employing our simulation framework we examine the role of circumnutations in the system, and find that the observed breadth of the velocity distribution represents a sharp transition in the force-noise ratio, conferring advantageous effects by facilitating exploration of potential configurations, leading to an optimized arrangement with minimal shading. These findings represent the first report of functional noise in plant movements and establish a theoretical foundation for investigating how plants navigate their environment by employing computational processes such as task-oriented processes, optimization, and active sensing. Since plants move by growing, space and time are coupled, and dynamics of self-organization lead to emergent 3D patterns. As such, this system provides conceptual insight for other interacting growth-driven systems such as fungal hyphae, neurons and self-growing robots, as well as active matter systems where agents interact with past trajectories of their counterparts, such as stigmergy in social insects. This foundational insight has implications in statistical physics, ecological dynamics, agriculture, and even swarm robotics. Published by the American Physical Society 2024
中文翻译:
嘈杂的环绕有助于向日葵自组织地避荫
环状运动在植物中广泛存在,通常与探索性运动有关;然而,对它们的作用的定量理解仍然难以捉摸。在这项研究中,我们首次报告了嘈杂的环旋在促进拥挤的相互遮荫植物群中的最佳生长模式中的作用。我们重新审视了在向日葵中观察到的由阴影反应交互介导的自组织问题。我们的分析表明,环行运动符合有界随机游走,其特征是速度分布非常广泛,涵盖 3 个数量级。在运动动物系统中,如此广泛的运动速度分布经常被确定为行为过程的增强,这表明回旋可能是功能噪声的来源。为了验证我们的假设,我们开发了一个 Langevin 型相互作用的生长盘模型,以实验为依据,成功地捕捉了单个和多个相互作用植物的特征动态。利用我们的仿真框架,我们检查了环动在系统中的作用,发现观察到的速度分布宽度代表了力噪声比的急剧过渡,通过促进对潜在配置的探索而产生有利效果,从而获得具有最小阴影的优化排列。这些发现代表了植物运动中功能噪声的首次报告,并为研究植物如何通过采用面向任务的过程、优化和主动传感等计算过程来导航其环境奠定了理论基础。 由于植物通过生长移动,空间和时间是耦合的,自组织的动态导致了 3D 模式的出现。因此,该系统为其他相互作用的生长驱动系统(如真菌菌丝、神经元和自我生长的机器人)以及代理与同类的过去轨迹(如群居昆虫中的耻辱)相互作用的活性物质系统提供了概念性见解。这一基础见解对统计物理学、生态动力学、农业甚至群体机器人学都有影响。美国物理学会 2024 年出版
更新日期:2024-08-15
中文翻译:
嘈杂的环绕有助于向日葵自组织地避荫
环状运动在植物中广泛存在,通常与探索性运动有关;然而,对它们的作用的定量理解仍然难以捉摸。在这项研究中,我们首次报告了嘈杂的环旋在促进拥挤的相互遮荫植物群中的最佳生长模式中的作用。我们重新审视了在向日葵中观察到的由阴影反应交互介导的自组织问题。我们的分析表明,环行运动符合有界随机游走,其特征是速度分布非常广泛,涵盖 3 个数量级。在运动动物系统中,如此广泛的运动速度分布经常被确定为行为过程的增强,这表明回旋可能是功能噪声的来源。为了验证我们的假设,我们开发了一个 Langevin 型相互作用的生长盘模型,以实验为依据,成功地捕捉了单个和多个相互作用植物的特征动态。利用我们的仿真框架,我们检查了环动在系统中的作用,发现观察到的速度分布宽度代表了力噪声比的急剧过渡,通过促进对潜在配置的探索而产生有利效果,从而获得具有最小阴影的优化排列。这些发现代表了植物运动中功能噪声的首次报告,并为研究植物如何通过采用面向任务的过程、优化和主动传感等计算过程来导航其环境奠定了理论基础。 由于植物通过生长移动,空间和时间是耦合的,自组织的动态导致了 3D 模式的出现。因此,该系统为其他相互作用的生长驱动系统(如真菌菌丝、神经元和自我生长的机器人)以及代理与同类的过去轨迹(如群居昆虫中的耻辱)相互作用的活性物质系统提供了概念性见解。这一基础见解对统计物理学、生态动力学、农业甚至群体机器人学都有影响。美国物理学会 2024 年出版