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© 2021 American Association for the Advancement of Science. All rights reserved.The deep chlorophyll maximum (DCM) layer is an ecologically important feature of the open ocean. The DCM cannot be observed using aerial or satellite remote sensing; thus, in situ observations are essential. Further, understanding the responses of microbes to the environmental processes driving their metabolism and interactions requires observing in a reference frame that moves with a plankton population drifting in ocean currents, i.e., Lagrangian. Here, we report the development and application of a system of coordinated robots for studying planktonic biological communities drifting within the ocean. The presented Lagrangian system uses three coordinated autonomous robotic platforms. The focal platform consists of an autonomous underwater vehicle (AUV) fitted with a robotic water sampler. This platform localizes and drifts within a DCM community, periodically acquiring samples while continuously monitoring the local environment. The second platform is an AUV equipped with environmental sensing and acoustic tracking capabilities. This platform characterizes environmental conditions by tracking the focal platform and vertically profiling in its vicinity. The third platform is an autonomous surface vehicle equipped with satellite communications and subsea acoustic tracking capabilities. While also acoustically tracking the focal platform, this vehicle serves as a communication relay that connects the subsea robot to human operators, thereby providing situational awareness and enabling intervention if needed. Deployed in the North Pacific Ocean within the core of a cyclonic eddy, this coordinated system autonomously captured fundamental characteristics of the in situ DCM microbial community in a manner not possible previously.
Author(s): Zhang Y, Ryan JP, Hobson BW, Kieft B, Romano A, Barone B, Preston CM, Roman B, Raanan B-Y, Pargett D, Dugenne M, White AE, Freitas FH, Poulos S, Wilson ST, DeLong EF, Karl DM, Birch JM, Bellingham JG, Scholin CA
Publication type: Article
Publication status: Published
Journal: Science Robotics
Year: 2021
Volume: 6
Issue: 50
Print publication date: 20/01/2021
Online publication date: 13/01/2021
Acceptance date: 14/12/2020
ISSN (electronic): 2470-9476
Publisher: American Association for the Advancement of Science
URL: https://doi.org/10.1126/SCIROBOTICS.ABB9138
DOI: 10.1126/SCIROBOTICS.ABB9138
PubMed id: 34043577
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