English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Owing to their important roles in biogeochemical cycles, phytoplanktonfunctional types (PFTs) have been the aim of an increasing number of oceancolor algorithms. Yet, none of the existing methods are based onphytoplankton carbon (C) biomass, which is a fundamental biogeochemical andecological variable and the “unit of accounting” in Earth system models. Wepresent a novel bio-optical algorithm to retrieve size-partitionedphytoplankton carbon from ocean color satellite data. The algorithm is basedon existing methods to estimate particle volume from a power-law particlesize distribution (PSD). Volume is converted to carbon concentrations usinga compilation of allometric relationships. We quantify absolute andfractional biomass in three PFTs based on size – picophytoplankton (0.5–2 µm in diameter), nanophytoplankton (2–20 µm) andmicrophytoplankton (20–50 µm). The mean spatial distributions of totalphytoplankton C biomass and individual PFTs, derived from globalSeaWiFSmonthly ocean color data, are consistent with current understanding ofoceanic ecosystems, i.e., oligotrophic regions are characterized by lowbiomass and dominance of picoplankton, whereas eutrophic regions have highbiomass to which nanoplankton and microplankton contribute relatively largerfractions. Global climatological, spatially integrated phytoplankton carbonbiomass standing stock estimates using our PSD-based approach yield ∼  0.25 Gt of C, consistent with analogous estimates from twoother ocean color algorithms and several state-of-the-art Earth systemmodels. Satisfactory in situ closure observed between PSD and POC measurementslends support to the theoretical basis of the PSD-based algorithm.Uncertainty budget analyses indicate that absolute carbon concentrationuncertainties are driven by the PSD parameter No which determinesparticle number concentration to first order, while uncertainties in PFTs'fractional contributions to total C biomass are mostly due to the allometriccoefficients. The C algorithm presented here, which is not empirically constraineda priori, partitions biomass in size classes and introduces improvement over theassumptions of the other approaches. However, the range of phytoplankton Cbiomass spatial variability globally is larger than estimated by any othermodels considered here, which suggests an empirical correction to theNo parameter is needed, based on PSD validation statistics. Thesecorrected absolute carbon biomass concentrations validate well againstin situ POC observations

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