Articles | Volume 12, issue 2
Ocean Sci., 12, 561–575, 2016
Ocean Sci., 12, 561–575, 2016

Research article 18 Apr 2016

Research article | 18 Apr 2016

Carbon-based phytoplankton size classes retrieved via ocean color estimates of the particle size distribution

Tihomir S. Kostadinov1, Svetlana Milutinović2, Irina Marinov2, and Anna Cabré2 Tihomir S. Kostadinov et al.
  • 1Department of Geography and the Environment, 28 Westhampton Way, University of Richmond, Richmond, VA 23173, USA
  • 2Department of Earth & Environmental Science, Hayden Hall, University of Pennsylvania, 240 South 33rd St., Philadelphia, PA 19104, USA

Abstract. Owing to their important roles in biogeochemical cycles, phytoplankton functional types (PFTs) have been the aim of an increasing number of ocean color algorithms. Yet, none of the existing methods are based on phytoplankton carbon (C) biomass, which is a fundamental biogeochemical and ecological variable and the “unit of accounting” in Earth system models. We present a novel bio-optical algorithm to retrieve size-partitioned phytoplankton carbon from ocean color satellite data. The algorithm is based on existing methods to estimate particle volume from a power-law particle size distribution (PSD). Volume is converted to carbon concentrations using a compilation of allometric relationships. We quantify absolute and fractional biomass in three PFTs based on size – picophytoplankton (0.5–2 µm in diameter), nanophytoplankton (2–20 µm) and microphytoplankton (20–50 µm). The mean spatial distributions of total phytoplankton C biomass and individual PFTs, derived from global SeaWiFS monthly ocean color data, are consistent with current understanding of oceanic ecosystems, i.e., oligotrophic regions are characterized by low biomass and dominance of picoplankton, whereas eutrophic regions have high biomass to which nanoplankton and microplankton contribute relatively larger fractions. Global climatological, spatially integrated phytoplankton carbon biomass standing stock estimates using our PSD-based approach yield  ∼  0.25 Gt of C, consistent with analogous estimates from two other ocean color algorithms and several state-of-the-art Earth system models. Satisfactory in situ closure observed between PSD and POC measurements lends support to the theoretical basis of the PSD-based algorithm. Uncertainty budget analyses indicate that absolute carbon concentration uncertainties are driven by the PSD parameter No which determines particle number concentration to first order, while uncertainties in PFTs' fractional contributions to total C biomass are mostly due to the allometric coefficients. The C algorithm presented here, which is not empirically constrained a priori, partitions biomass in size classes and introduces improvement over the assumptions of the other approaches. However, the range of phytoplankton C biomass spatial variability globally is larger than estimated by any other models considered here, which suggests an empirical correction to the No parameter is needed, based on PSD validation statistics. These corrected absolute carbon biomass concentrations validate well against in situ POC observations.

Short summary
Recent advances in ocean color remote sensing have allowed the quantification of the particle size distribution (and thus volume) of suspended particles in surface waters, using their backscattering signature. Here, we leverage these developments and use volume-to-carbon allometric relationships to quantify phytoplankton carbon globally using SeaWiFS ocean color data. Phytoplankton carbon concentrations are partitioned among three size classes: picoplankton, nanoplankton and microplankton.