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

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:
$54.0万
依托单位:
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
项目状态:
已结题
起止时间:
2021-09-01 至 2024-08-31

项目摘要

项目成果

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中文摘要
翻译
几个世纪以来,群居动物的机动和导航能力一直令人类着迷。在经济上和生态上最重要的鱼类是成群游动的鱼类,它们成群游动,在汹涌的洋流中迁徙数百英里。一个鱼群如何感知并穿越自己湍急的尾流和不可预测的洋流,对于它们在日常生死关头的成功至关重要,在这种情况下,个体必须迅速、团结地从大型、快速攻击的捕食者的口中逃脱。因为邻近的领域,如自主群体机器人是基于生物鱼群的集体行为并受到启发,所以迫切需要了解复杂的尾流如何促进或破坏鱼群中有组织的、有凝聚力的运动。对这一现象的洞察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。由于缺乏对野生行为动物进行实验的理论框架,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。为了应对这一挑战,该项目将利用计算流体动力学建模和活鱼实验来研究圆柱体阵列下游的涡旋街相互作用。该项目的总体目标是定义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,一个成熟的社交媒体存在(超过1万YouTube订阅者),以及一本正在撰写的科普书籍(普林斯顿大学出版社)。PI将结合计算流体动力学(CFD)建模、机器学习运动跟踪算法、有机生物力学和实验感觉神经科学,研究复杂的流体动力学环境如何影响鱼群的集体行为,目标如下:目标1:确定产生漩涡尾迹的圆柱体的排列,以最大限度地吸引鱼,以及次优控制配置。假设存在一种使涡旋街相干性最大化的最优排列,它由两个方向上各有恒定间距的结构化阵列组成。目标2:揭示鱼群的分布模式,无论是单独的还是集体的,在实验的圆柱尾迹后面。这里的假设是鱼的行为取决于圆柱体分布和相关的湍流。目标3:研究鱼类如何保持一致的鱼群编队的感觉生物学。PI假设,面对复杂的水流,鱼群优先考虑视觉而不是水流感应。该奖项反映了美国国家科学基金会的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
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.
期刊论文(4)
专著(0)
科研奖励(0)
会议论文
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.]
通讯作者: Liao, James C.
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
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
Collaborative Research: Flexibility and Robustness of attack and evasion: reverse-engineering the mechanisms of behavioral control
  • 批准号:
    1856237
  • 项目类别:
    Standard Grant
  • 资助金额:
    $34.58万
  • 财政年份:
    2019
  • 负责人:
    James Liao
  • 依托单位:
Single Neuron Resolution of Flow Sensing in the Zebrafish Lateral line during development
  • 批准号:
    1257150
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $51.61万
  • 财政年份:
    2013
  • 负责人:
    James Liao
  • 依托单位:
Metabolomics: Development of novel metabolic analysis system for 1-butanol production
  • 批准号:
    1139318
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $149.69万
  • 财政年份:
    2011
  • 负责人:
    James Liao
  • 依托单位:
Collaborative Research: Metabolically Engineered Organisms for Conversion of Cellulose to Isobutanol
国内基金
海外基金
基于Flow-through流场的双离子嵌入型电容去离子及其动力学调控研究
  • 批准号:
    52009057
  • 项目类别:
    青年科学基金项目
  • 资助金额:
    24.0万元
  • 批准年份:
    2020
  • 负责人:
    刘勇
  • 依托单位: