The primacy of dissolved organic matter to aquatic light variability

Abstract. Absorption and scattering by optically active constituents (OACs) modify the sunlit aquatic light environment, facilitating the derivation of biogeochemical data products at scales spanning in situ to satellite observations. Excluding solar illumination and atmospheric effects, variability in an optical parameter arises from changing OAC concentrations, wherein observed patterns in the spectral evolution of data products are associated with the connectivity and spatiotemporal dynamics of OACs. In open-ocean water masses far from terrestrial and riverine inputs, the content and mixture of OACs principally relates to the dynamics of the microbial loop—a trophic pathway describing the cycling of microbial primary producers (i.e., phytoplankton), remineralizers (e.g., bacteria and archaea), plus dissolved organic and inorganic materials (as applicable). Historical models of open-ocean optical data products, such as the normalized water-leaving radiance, [L_W (λ)]_N, primarily invoke chlorophyll a (C_a)—a commonly used proxy for phytoplankton biomass—as the ubiquitous independent variable governing aquatic light variability. Formulation of [L_W (λ)]_N as a function of C_a content assumes an idealized microbial loop wherein phytoplankton variability modifies other OACs, including the colored (or chromophoric depending on the literature) portion of the dissolved organic matter (DOM) pool, hereafter CDOM. The prescription in which C_a maximally captures oceanic light variability (hereafter primacy) is tested herein using eigen analyses on three independent bio-optical datasets to assess the shapes and associations of the principal and secondary eigenfunctions of aquatic [L_W (λ)]_N observations. The analyses reveal [L_W (λ)]_N variations to be more strongly associated with changes in CDOM than C_a—even for oligotrophic and oceanic datasets—indicating that CDOM dynamics are more variable and exhibit greater independence from C_a than formerly ascribed. Blue and green band-ratio algorithms routinely used for remote sensing of C_a are found to be maximally sensitive to CDOM—rather than C_a—variability based on partial correlation coefficients relating eigenfunction scalar amplitude functions to field or derived observations, plus validation tests of OC algorithm performance. Spectral subset eigen analyses indicate expansive spectral range observing improves the independence in retrieving CDOM absorption and C_a. The combined findings indicate expanded spectral observations supported by recent domestic and international satellite missions constitute a new and unique opportunity to optically characterize surface ocean phytoplankton stocks without relying on explicit or implied empiricisms requiring CDOM and other OACs to vary consistently with C_a. Shapes and associations of the eigen functions suggest a greater diversity of trophic pathways drive OAC dynamics—e.g., in addition to phytoplankton contributing CDOM via cellular lysis, excretion, and grazing—and are consistent with advancing knowledge of the microbial loop in the decades after bio-optical formulations based on C_a were proposed.