论文标题
嘈杂的果酱促进向日葵中的自组织避免避免阴影
Noisy circumnutations facilitate self-organized shade avoidance in sunflowers
论文作者
论文摘要
果树在植物中很普遍,通常与探索性运动有关,但是对其作用的定量理解仍然难以捉摸。在这项研究中,我们首次报道了嘈杂的果酱在促进拥挤的一群相互遮蔽植物中的最佳生长模式中的作用。我们重新审视了通过阴影反应相互作用介导的向日葵观察到的自组织问题。我们的分析表明,绕过的运动符合一个有界的随机行走,其特征是速度的分布非常广,涵盖了三个数量级。在动物系统中,这种运动速度的广泛分布经常通过增强行为过程来识别,这表明周围的营养不良可能是功能噪声的来源。为了检验我们的假设,我们开发了一种相互作用的生长磁盘的简约模型,该模型通过实验得出,成功捕获了个体和多个相互作用植物的特征动力学。采用我们的模拟框架,我们检查了繁殖力在系统中的作用,并发现速度分布的观察到的广度通过促进探索潜在构型的探索,从而赋予了优化的效果,从而导致优化的布置以最小的阴影。这些发现代表了植物运动中功能噪声的第一个报告,并建立了一个理论基础,用于研究植物如何通过采用诸如以任务为导向的过程,优化和主动感应的计算过程来导航其环境。
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 three 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 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 confers 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 establishes a theoretical foundation for investigating how plants navigate their environment by employing computational processes such as task-oriented processes, optimization, and active sensing.