Towards determining the spatio-temporal variability of upper-ocean
ecosystem stoichiometry from satellite remote sensing
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 the feeding behavior of
zooplankton and the decomposition of organic matter by bacteria and
viruses. 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 developed a new method that combines
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. Here, we
demonstrated this method specifically for the C:P ratio. The approach
was applied to phytoplankton growth rates and chlorophyll-to-carbon
ratios derived from MODIS-Aqua and to maps of temperature-dependent
nutrient limitation in order 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. A
reasonably good comparison of our results with available data, both
horizontal distributions and time series, indicates the viability of our
new method in accurately quantifying seasonally resolved global ocean
bulk C:P. We anticipate that the new hyperspectral capabilities of the
NASA’s PACE (Plankton, Aerosol, Cloud, ocean Ecosystem) mission will
facilitate the determination of phytoplankton stoichiometry for
different size classes and can further enhance the predictability of
marine ecosystem stoichiometry from space.