MRI Development: Imaging FlowCytobot on Autonomous Vehicles for Plankton Research and Harmful Algal Bloom Mitigation

MRI 开发:自主车辆上的 FlowCytobot 成像用于浮游生物研究和有害藻华缓解

基本信息

  • 批准号:
    1428703
  • 负责人:
  • 金额:
    $ 51.8万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2014
  • 资助国家:
    美国
  • 起止时间:
    2014-09-01 至 2018-08-31
  • 项目状态:
    已结题

项目摘要

Imaging FlowCytobot (IFCB) was developed to identify and monitor plankton in the size range 10 ~ 200 microns, which can be especially important in coastal blooms (including harmful algal blooms, HABs) and play critical roles in marine ecosystems. IFCB uses a combination of flow cytometric and video technology to automatically capture images of microscopic organisms. Existing IFCB instruments can be deployed unattended in the ocean for 6-9 month duration and have been used to produce fixed location plankton time series with unprecedented detail. Because these studies take place in a fluid ocean, they are always subject to questions about spatial variability in a patchy and dynamic system. This project will advance IFCB technology to develop an autonomous vehicle-ready version of the instrument (IFCB-AV) that can be deployed on diverse vehicles to enable high resolution plankton studies with both long duration and spatial coverage. Because of the current gap in technology for observing phytoplankton at appropriate spatial scales, access to shared-use IFCB-AVs (with vehicles) will advance knowledge in a wide range of aquatic research areas. Research topics that will directly benefit from IFCB-AV include effects of climate change on plankton community structure in US coastal waters and the Arctic, causes of variability in shelf break ecosystems that support critical fisheries, regulation of seasonal phytoplankton blooms, and early detection of harmful algal blooms in the Gulf of Mexico and the Gulf of Maine. The broader impacts of applications of IFCB-AV technology will span from basic research problems to science-based support for management and decision making in societally relevant problems. The existing IFCB time series technology has already proven effective for mitigation of HAB events, and IFCB-AV will enhance impact for these problems, as well as to other environmental management applications, such as knowledge-based Integrated Ecosystem Assessments in support of problems in fisheries. The proposed activities will improve training infrastructure and development of the research workforce. As shared use of the IFCB-AV system proceeds, diverse trainees will be involved in study design, field operation, and analysis of results from deployments. The project will also influence classroom instruction by enhancing content related to scales and impacts of spatial variability in marine ecosystems. IFCB-AV will be developed for use with multiple vehicles to suit different research goals. An iterative process for design, construction, and evaluation will be employed. Laboratory-based tests with a conventional IFCB oriented horizontally (as required for deployment on small vehicles) will guide design and operational modifications needed for long-duration deployments. An in-water (towed) deployment mode is preferred for compatibility with a wide range of vehicles and to simplify instrument temperature control and water sampling. If this approach proves problematic, the instrument will be redesigned to obtain vertical water flow through the critical analysis region but with modular layout of the remaining components. In this case the instrument will fit within a flat box compatible with a range of vehicle hulls.
开发了成像流体植物(IFCB),以识别和监测10〜200微米尺寸的浮游生物,这在沿海花朵(包括有害的藻华,HABS)中尤其重要,并在海洋生态系统中起关键作用。 IFCB使用流式细胞术和视频技术的组合来自动捕获微观生物的图像。现有的IFCB仪器可以在6-9个月的持续时间内无人看管的海洋部署,并用于生产固定位置浮游生物时间序列,并具有前所未有的细节。由于这些研究发生在流体海洋中,因此它们始终会受到有关斑点和动态系统中空间可变性的问题。该项目将推进IFCB技术,以开发可自动驾驶汽车的仪器(IFCB-AV),该版本可以在不同的车辆上部署,以使高分辨率浮游生物研究具有较长的持续时间和空间覆盖范围。由于目前在适当的空间尺度上观察浮游植物的技术差距,因此获得共享使用的IFCB-AV(带有车辆)的访问将在广泛的水上研究领域中提高知识。将直接从IFCB-AV中受益的研究主题包括气候变化对美国沿海水域浮游生物社区结构的影响以及支持关键渔业的Break Break生态系统的可变性的原因,调节季节性浮游植物的调节,以及早期的MECICOCO和MECICOS和MECIAN中有害藻类膨胀的季节性发现。 IFCB-AV技术应用的更广泛影响将从基础研究问题到基于科学的社会相关问题的管理和决策的支持。现有的IFCB时间序列技术已经证明可以有效缓解HAB事件,IFCB-AV将增强对这些问题的影响,以及对其他环境管理应用程序的影响,例如基于知识的综合生态系统评估,以支持渔业中的问题。拟议的活动将改善研究人员的培训基础设施和发展。随着IFCB-AV系统的共同使用,将参与研究设计,现场操作和部署结果分析。该项目还将通过增强与尺度和海洋生态系统空间变异性有关的内容来影响课堂教学。将开发IFCB-AV与多辆车一起使用,以适应不同的研究目标。将采用设计,构建和评估的迭代过程。基于实验室的基于实验室的测试水平的常规IFCB(根据小型车辆部署的要求)将指导长期部署所需的设计和操作修改。优选的水(拖曳)部署模式是与各种车辆的兼容,并简化仪器温度控制和水采样。如果这种方法证明有问题,则将重新设计该仪器,以获得穿过临界分析区域的垂直水流,但其余组件的模块化布局。在这种情况下,该仪器将适合与一系列车船体兼容的平箱。

项目成果

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Heidi Sosik其他文献

Heidi Sosik的其他文献

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{{ truncateString('Heidi Sosik', 18)}}的其他基金

LTER: Scales of Variability in Ecosystem Dynamics and Production on the Changing Northeast U.S. Shelf (NES II)
LTER:变化中的美国东北部陆架生态系统动态和生产的变异规模 (NES II)
  • 批准号:
    2322676
  • 财政年份:
    2023
  • 资助金额:
    $ 51.8万
  • 项目类别:
    Continuing Grant
RAPID: Collaborative Research: Autumn transition in plankton ecology during an ocean heatwave on the Northeast U.S. Shelf
RAPID:合作研究:美国东北部陆架海洋热浪期间浮游生物生态的秋季转变
  • 批准号:
    2102434
  • 财政年份:
    2020
  • 资助金额:
    $ 51.8万
  • 项目类别:
    Standard Grant
Collaborative Research: Automated observations of phytoplankton communities from open water moorings
合作研究:从开放水域系泊处自动观测浮游植物群落
  • 批准号:
    1810927
  • 财政年份:
    2018
  • 资助金额:
    $ 51.8万
  • 项目类别:
    Standard Grant
Next generation submersible flow cytometry for plankton studies: Extended dynamic range and orthogonal imaging
用于浮游生物研究的下一代潜水式流式细胞术:扩展的动态范围和正交成像
  • 批准号:
    1736510
  • 财政年份:
    2017
  • 资助金额:
    $ 51.8万
  • 项目类别:
    Continuing Grant
LTER: Linking Pelagic Community Structure with Ecosystem Dynamics and Production Regimes on the Changing Northeast US Shelf
LTER:将远洋群落结构与不断变化的美国东北部大陆架的生态系统动态和生产制度联系起来
  • 批准号:
    1655686
  • 财政年份:
    2017
  • 资助金额:
    $ 51.8万
  • 项目类别:
    Continuing Grant
CyberSEES: Type 2: Collaborative Research: A Computational and Analytic Laboratory for Modeling and Predicting Marine Biodiversity and Indicators of Sustainable Ecosystems
Cyber​​SEES:类型 2:协作研究:用于建模和预测海洋生物多样性和可持续生态系统指标的计算和分析实验室
  • 批准号:
    1539256
  • 财政年份:
    2015
  • 资助金额:
    $ 51.8万
  • 项目类别:
    Standard Grant

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