Schooling through Vortex Streets; A Biological and Computational Approach to Understanding Collective Behavior in Wild Fish

通过涡街 (Vortex Street) 上学；

• 批准号: 2102891
• 负责人: James Liao
• 金额: $ 54万
• 依托单位: University of Florida
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2102891&HistoricalAwards=false
• 关键词: Schooling; through; Vortex; Streets; Biological

The ability of swarming animals to maneuver and navigate has fascinated humans for centuries. The most economically and ecologically important fishes are schooling fishes that swim together in the millions and migrate hundreds of miles through turbulent ocean currents. How a school senses and moves through its own turbulent wake and unpredictable ocean currents is vital to its success in daily life-or-death scenarios, where individuals must quickly and cohesively maneuver out of the jaws of large, fast-attacking predators. Because adjacent fields such as autonomous swarm robotics are based on and inspired by the collective behavior of biological fish schools, there is a critical need to understand how complex wakes can facilitate or disrupt organized, cohesive motion in schooling fishes. Insight into this phenomenon holds the key to unlocking unknown mechanisms that could advance the fields of collective behavior, neuroscience, evolution, movement ecology, robotics and fluid dynamics. The hydrodynamic mechanisms underlying schooling remain largely speculative due to the lack of a theoretical framework with which to experiment with wild, behaving animals. To meet this challenge, this project will examine the vortex street interactions downstream of arrays of cylinders by leveraging both computational fluid dynamics modeling and live fish experiments. The overall objective of the project is to define the fundamental mechanisms with which interacting vortex streets influence the patterns of formation in schooling fishes. The research project will broaden participation of underrepresented groups in STEM fields by providing an authentic research experience for undergraduate students and the public. This includes the long-running NSF REU program and K-9 outreach program at the Whitney Lab for Marine Bioscience, an established social media presence (over 10k YouTube subscribers), and a popular science book currently being written (Princeton University Press).The PI will combine computational fluid dynamic (CFD) modeling, machine-learning motion-tracking algorithms, organismal biomechanics, and experimental sensory neuroscience to examine how complex hydrodynamic environments impact the collective behavior of schooling fishes with the following aims. Aim 1: Determine the arrangement of cylinders that generates vortex wakes that maximize attraction to fish, as well as sub-optimal control configurations. The hypothesis is that an optimal arrangement maximizing the coherency of the vortex street exists and it consists of a structured array with a constant spacing for each of the two directions. Aim 2: Reveal distribution patterns of schooling fishes, both individually and collectively, behind experimental cylinder wakes. Here the hypothesis is that fish behavior depends on the cylinder distribution and relevant turbulent flow. Aim 3: Investigate the sensory biology of how fish remain in coherent schooling formations. The PI hypothesizes that faced with complex flows, schooling fish prioritize vision over flow sensing.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

几个世纪以来，群居动物的机动和导航能力一直吸引着人类。在经济和生态上最重要的鱼类是成群游动的鱼类，它们数百万只一起游动，通过汹涌的洋流迁移数百英里。鱼群如何感知并穿越自己的湍流和不可预测的洋流，对于它在日常生死场景中的成功至关重要，在这种场景中，个体必须快速而团结地从大型快速攻击的捕食者的口中逃脱。由于相邻的领域，如自主集群机器人是基于生物鱼群的集体行为和启发，有一个关键需要了解复杂的唤醒如何促进或破坏有组织的，有凝聚力的运动在学校的鱼。对这种现象的深入了解是解开未知机制的关键，这些机制可以推动集体行为，神经科学，进化，运动生态学，机器人和流体动力学等领域的发展。学校教育背后的流体动力学机制在很大程度上仍然是推测性的，因为缺乏一个理论框架来对野生动物进行实验。为了应对这一挑战，本项目将利用计算流体动力学模型和活鱼实验来研究圆柱阵列下游的涡街相互作用。该项目的总体目标是确定相互作用的涡旋街道影响鱼群形成模式的基本机制。该研究项目将通过为本科生和公众提供真实的研究体验，扩大代表性不足的群体在STEM领域的参与。这包括长期运行的NSF REU计划和惠特尼海洋生物科学实验室的K-9外展计划，这是一个成熟的社交媒体存在（超过1万YouTube订阅者），以及一本正在编写的科普书籍（普林斯顿大学出版社）。PI将结合联合收割机计算流体动力学（CFD）建模，机器学习运动跟踪算法，生物生物力学，和实验感觉神经科学来研究复杂的水动力环境如何影响集群鱼类的集体行为，其目的如下。目标1：确定产生最大吸引力的涡流尾流的气缸布置以及次优控制配置。假设存在最大化涡街相干性的最佳布置，并且其由两个方向中的每一个具有恒定间距的结构化阵列组成。目的2：揭示集群鱼类的分布模式，单独和集体，后面的实验缸尾流。这里的假设是，鱼的行为取决于圆柱体的分布和相关的湍流。目的3：调查鱼如何保持连贯的集群形成的感觉生物学。PI假设，面对复杂的水流，鱼群优先考虑视觉而不是水流传感。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估来支持。

项目成果

Fish swimming efficiency

鱼的游泳效率

• DOI: 10.1016/j.cub.2022.04.073
• 发表时间: 2022
• 期刊: Current Biology
• 影响因子: 9.2
• 作者: Liao, James C.

Convergence of undulatory swimming kinematics across a diversity of fishes

• DOI: 10.1073/pnas.2113206118
• 发表时间: 2021-12-07
• 期刊: PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
• 影响因子: 11.1
• 作者: Di Santo, Valentina;Goerig, Elsa;Lauder, George, V
• 通讯作者: Lauder, George, V

Fish-inspired segment models for undulatory steady swimming

• DOI: 10.1088/1748-3190/ac6bd6
• 发表时间: 2022-07-01
• 期刊: BIOINSPIRATION & BIOMIMETICS
• 影响因子: 3.4
• 作者: Akanyeti, Otar;Di Santo, Valentina;Lauder, George, V
• 通讯作者: Lauder, George, V