Articles | Volume 15, issue 14
https://doi.org/10.5194/bg-15-4515-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-15-4515-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
25 Jul 2018
Research article |
| 25 Jul 2018
| 25 Jul 2018
A multi-method autonomous assessment of primary productivity and export efficiency in the springtime North Atlantic
National Oceanography Centre, Southampton SO14 3ZH, UK
Kristinn Guðmundsson
Marine Research Institute, P.O. Box 1390, 121 Reykjavík, Iceland
Ivona Cetinić
GESTAR/Universities Space Research Association, 7178 Columbia Gateway
Drive, Columbia, MD 21046, USA
Ocean Ecology Laboratory, NASA Goddard Space Flight Center Code 616,
Greenbelt, MD 20771, USA
Eric D'Asaro
Applied Physics Laboratory and School of Oceanography, University of
Washington, Seattle, WA 98105, USA
Eric Rehm
Département de Biologie et Québec-Océan, Université
Laval, Québec QC G1V 0A6, Canada
Craig Lee
Applied Physics Laboratory and School of Oceanography, University of
Washington, Seattle, WA 98105, USA
Mary Jane Perry
Darling Marine Center, School of Marine Sciences, University of Maine,
Walpole, ME 04573, USA
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Total article views: 2,650 (including HTML, PDF, and XML)
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Latest update: 17 May 2025
Short summary
We rigorously tested emerging methods for measuring the rate of photosynthesis in the ocean using autonomous robotic platforms. We found similar accuracy to traditional, labor-intensive, ship-based measurements across a variety of ocean conditions. Photosynthesis is the basis of nearly all life, both on land and in the ocean. Our results suggest that by scaling up existing technologies, we can greatly improve global monitoring of one of life's key processes.
We rigorously tested emerging methods for measuring the rate of photosynthesis in the ocean...
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