AUTHOR=Tanioka Tatsuro , Fichot Cédric G. , Matsumoto Katsumi TITLE=Toward Determining the Spatio-Temporal Variability of Upper-Ocean Ecosystem Stoichiometry From Satellite Remote Sensing JOURNAL=Frontiers in Marine Science VOLUME=7 YEAR=2020 URL=https://www.frontiersin.org/journals/marine-science/articles/10.3389/fmars.2020.604893 DOI=10.3389/fmars.2020.604893 ISSN=2296-7745 ABSTRACT=

The elemental stoichiometry of particulate organic carbon (C), nitrogen (N), and phosphorus (P) connects the C fluxes of biological production to the availability of the limiting nutrients in the ocean. It also influences the marine food-web by modulating zooplankton’s feeding behavior and organic matter decomposition by bacteria. Despite its importance, there is a general paucity of information on how the global C:N:P ratio evolves seasonally and interannually, and large parts of the global ocean remain devoid of observational data. Here, we present a new method combining satellite ocean-color data with a cellular-trait-based model to characterize the spatio-temporal variability of the phytoplankton stoichiometry in the surface mixed layer of the ocean. This new method is demonstrated specifically for the C:P ratio. The approach was applied to phytoplankton growth rates and chlorophyll-to-carbon ratios derived from MODIS-Aqua and maps of temperature-dependent nutrient limitation to generate global and seasonal maps of upper-ocean phytoplankton C:P. Taking it a step further, we determined the C:P of the bulk particulate organic matter, using MODIS-Aqua estimates of particulate organic carbon and phytoplankton biomass. Our results are within 95% confidence interval of available data for both horizontal distributions and time series, indicating our new method’s viability in accurately quantifying seasonally resolved global ocean bulk C:P. We anticipate the new hyperspectral capabilities of the NASA PACE (Plankton, Aerosol, Cloud, ocean Ecosystem) mission will facilitate the determination of phytoplankton stoichiometry for different size classes and further enhance the predictability of marine-ecosystem stoichiometry from space.