Collaborative Research: Development of a Swarm of Autonomous Subsea Vehicles to Infer Plankton Growth and Transport

合作研究：开发一批自主海底车辆来推断浮游生物的生长和运输

• 批准号: 2220258
• 负责人: Jules Jaffe
• 金额: $ 116.47万
• 依托单位: University of California-San Diego Scripps Inst of Oceanography
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-15 至 2025-07-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2220258&HistoricalAwards=false
• 关键词: Collaborative; Research; Development; Swarm; Autonomous

Marine plankton are likely the most important components of marine ecosystems: the phytoplankton produce oxygen as they create organic carbon through photosynthesis, while the zooplankton transfer this organic carbon to top predators such as fish, seabirds, marine mammals, and humans. Despite being relatively weak, plankton swimming behaviors can play an important role in determining their distribution and survival: swimming allows plankton to find food, reproduce, and avoid predators in a dynamic and patchy fluid environment. These behaviors also influence plankton dispersal and survival by modulating the ocean conditions that the plankton experience. Because it is presently impossible to track individual plankton for long periods in situ, current insights into the trade-offs and benefits associated with plankton behaviors have only been gained from experiments in controlled settings and from numerical models. Having drifting vehicles that simulate planktonic behaviors would enable unique and powerful insights into how plankton interact with the currents and properties of their environment. During this project, investigators will develop small, next-generation, subsurface, autonomous, buoyancy-controlled vehicles – plankton mimics – to study how relatively simple behaviors of plankton can alter their transport and environment. By sampling the ocean like planktonic organisms, this unique vehicle swarm will give plankton researchers unprecedented data to validate experimental and model predictions, and, hopefully, reveal previously unknown mechanisms driving planktonic population dynamics.To accomplish the above goals, a swarm of 20 quasi-Lagrangian underwater vehicles will be fabricated. The vehicles will mimic plankton behavior and will be tracked in 3D for 24–72 hours. These goals will be achieved based on several novel technological advances: 1) improved subsurface localization using the most recent developments in acoustic modem technology at reduced cost, 2) subsurface vehicle communication with surface buoys to relay vehicle information (e.g., data, location) to scientists on a nearby ship to facilitate additional ship-based sampling, and 3) a near-incompressible housing and drag skirts to improve the vehicles’ ability to follow fluid velocities and provide a ‘no behavior’ mode. The swarm will be optimized to investigate biological-physical interactions at spatial scales up to 10 km, focusing on internal waves and fronts. Ultimate performance tests will target high-frequency internal waves, acquiring vehicle trajectories with a spatial resolution of tens of centimeters vertically, sub-meters horizontally, and a temporal resolution of minutes. Additional sensors will provide along-track information on ocean temperature, salinity, irradiance, and chlorophyll-a. These data will provide unique time series of physical and environmental data along planktonic trajectories in the ocean. The vehicle swarm will generate multiple tracks showing the environmental properties in 3D along with the physical transport associated with different behaviors in the similar environments. Such tracks will lead to insights regarding the cues and consequences of behaviors in the plankter’s natural environment.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.

海洋浮游生物可能是海洋生态系统中最重要的组成部分：浮游植物通过光合作用产生有机碳，而浮游动物会将这种有机碳转移到鱼类，海鸟，海洋哺乳动物和人类等顶级捕食者。尽管浮游生物游泳行为相对较弱，但在确定其分布和生存方面可以发挥重要作用：游泳使浮游生物可以在动态且斑驳的液体环境中找到食物，繁殖并避免捕食者。这些行为还通过调节浮游生物经历的海洋条件来影响浮游生物的分散和生存。由于目前不可能长期跟踪单个浮游生物，因此当前对与浮游生物行为相关的权衡和收益的见解仅是从受控设置和数值模型中的实验中获得的。拥有模拟浮游性行为的起草车辆将使浮游生物如何与环境的电流和特性相互作用，从而使其具有独特而有力的见解。在此项目中，研究人员将开发小型的下一代，地下，自主，浮力控制的车辆 - 浮游生物模仿 - 以研究浮游生物的相对简单行为如何改变其运输和环境。通过像浮游生物这样的海洋采样，这种独特的车辆群将为浮游生物研究人员提供前所未有的数据，以验证实验和模型预测，并希望揭示以前未知的机制，驱动浮游生群人的人群动力学。为实现上述目标，将制造20个Quasi-lagrangangian下水管的群。这些车辆将模仿浮游生物的行为，并将在3D中进行24–72小时的跟踪。这些目标将根据几个新的技术进步来实现：1）使用降低的声学调制解调器技术的最新进展改进了地下定位，2）与地面浮标的地下车辆通信以中继车辆信息（例如，数据，位置）向科学家（例如，位置）近乎验证，以促进近乎船舶的采样，并在近乎造成的船舶上进行动力，并拖延了动力，并拖动了''''''and of Skirt''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''并提供“无行为”模式。该群将被优化，以研究高达10 km的空间尺度上的生物形态相互作用，重点是内波和前部。最终的性能测试将针对高频内波，采集车辆轨迹，并以空间分辨率垂直分辨，水平次级尺寸和临时分辨率分钟。其他传感器将提供有关海洋温度，盐度，辐照度和叶绿素-A的轨道信息。这些数据将在海洋中的浮游轨迹沿着物理和环境数据提供独特的时间序列。车辆群将生成多个轨道，显示3D中的环境特性以及与类似环境中不同行为相关的物理运输。此类曲目将导致有关木板自然环境中行为的提示和后果的见解。该奖项反映了NSF的法定任务，并使用基金会的知识分子优点和更广泛的审查标准，认为值得通过评估来获得支持。