Retrieval of phytoplankton size from bio-optical measurements: theory and applications

Abstract

The absorption coefficient of a substance distributed as discrete particles in suspension is less than that of the same material dissolved uniformly in a medium-a phenomenon commonly referred to as the flattening effect. The decrease in the absorption coefficient owing to flattening effect depends on the concentration of the absorbing pigment inside the particle, the specific absorption coefficient of the pigment within the particle, and on the diameter of the particle, if the particles are assumed to be spherical. For phytoplankton cells in the ocean, with diameters ranging from less than 1 mm to more than 100 mm, the flattening effect is variable, and sometimes pronounced, as has been well documented in the literature. Here, we demonstrate how the in vivo absorption coefficient of phytoplankton cells per unit concentration of its major pigment, chlorophyll a, can be used to determine the average cell size of the phytoplankton population. Sensitivity analyses are carried out to evaluate the errors in the estimated diameter owing to potential errors in the model assumptions. Cell sizes computed for field samples using the model are compared qualitatively with indirect estimates of size classes derived from high performance liquid chromatography data. Also, the results are compared quantitatively against measurements of cell size in laboratory cultures. The method developed is easy-to-apply as an operational tool for in situ observations, and has the potential for application to remote sensing of ocean colour data.

Effect of phytoplankton size classes on bio-optical properties of phytoplankton in the Western Iberian coast: Application of models

“…Differences were more pronounced for the other locations. Absorption in this wavelength range has been used to estimate size class (Roy et al, 2011). At these wavelengths, the absorption is dominated by chlorophyll-a and the influence of other pigments is low.…”

A Consumer's Guide to Satellite Remote Sensing of Multiple Phytoplankton Groups in the Global Ocean

“…The chemotaxonomic approach provides a means to quantify phytoplankton taxonomic composition utilizing a set of biomarker pigments (e.g., Jeffrey et al, 1997;Roy et al, 2011). Claustre (1994) and Vidussi et al (2001) further proposed to utilize groupings of biomarker pigments to estimate phytoplankton size structure.…”

“…They estimate PSC utilizing empirical relationships with phytoplankton absorption-spectra ratios and the particulate backscatter slope. Roy et al (2011) developed a semi-analytical algorithm based on phytoplankton absorption at a red wavelength (676 nm) to compute the equivalent spherical diameter of phytoplankton. Roy et al (2013) further extended the algorithm to heterogeneous phytoplankton populations, where they utilized phytoplankton absorption at 676 nm to compute the PSD corresponding to the phytoplankton cells alone, and derived the power-law exponent/slope of the phytoplankton size spectrum.…”

Inter-comparison of phytoplankton functional type phenology metrics derived from ocean color algorithms and Earth System Models

“…Another class of algorithms relies on various spectral features. The PHYSAT algorithm exploits second-order anomalies of reflectance spectra Alvain et al, 2008), whereas several other algorithms are based on either absorption (Bracher et al, 2009;Ciotti and Bricaud, 2006;Mouw and Yoder, 2010;Roy et al, 2011;Roy et al, 2013), or backscattering (Kostadinov et al, 2009;Kostadinov et al, 2010;Kostadinov et al, 2016), or a hybrid of absorption and backscattering (Fujiwara et al, 2011). Brewin et al (2011) conducted the first systematic inter-comparison of PFT algorithms designed to identify "dominant" PFTs in the oceans.…”