Schuback, Nina, Tortell, P., Berman-Frank, I., Campbell, Douglas A., Hickman, Anna, Ciotti, Aurea M., Courtecuisse, Emilie, Erickson, Zachary K., Fujiki, Tetsuichi, Halsey, Kimberly, Hughes, David, Huot, Yannick, Gorbunov, Maxim Y., Kolber, Z., Moore, Christopher, Oxborough, Kevin, Prášil, Ondřej, Robinson, Charlotte Mary, Ryan-Keogh, T., Silsbe, Greg, Simis, Stefan G. H., Suggett, David J., Thomalla, Sandy J. and Varkey, Deepa Ruth (2021) Single-turnover variable chlorophyll fluorescence as a tool for assessing phytoplankton photosynthesis and primary productivity: Opportunities, caveats and recommendations. Frontiers in Marine Science, 8, [690607]. (doi:10.3389/fmars.2021.690607).
Abstract
Phytoplankton photosynthetic physiology can be investigated through single-turnover variable chlorophyll fluorescence (ST-ChlF) approaches, which carry unique potential to autonomously collect data at high spatial and temporal resolution. Over the past decades, significant progress has been made in the development and application of ST-ChlF methods in aquatic ecosystems, and in the interpretation of the resulting observations. At the same time, however, an increasing number of sensor types, sampling protocols, and data processing algorithms have created confusion and uncertainty among potential users, with a growing divergence of practice among different research groups. In this review, we assist the existing and upcoming user community by providing an overview of current approaches and consensus recommendations for the use of ST-ChlF measurements to examine in-situ phytoplankton productivity and photo-physiology. We argue that a consistency of practice and adherence to basic operational and quality control standards is critical to ensuring data inter-comparability. Large datasets of inter-comparable and globally coherent ST-ChlF observations hold the potential to reveal large-scale patterns and trends in phytoplankton photo-physiology, photosynthetic rates and bottom-up controls on primary productivity. As such, they hold great potential to provide invaluable physiological observations on the scales relevant for the development and validation of ecosystem models and remote sensing algorithms.
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