Determination of the cross-section absorption coeffcient of individual phytoplankton cells by analytical flow cytometry

An empirical relationship between the cellular cross-section absorption coefficient (a) and the Chl a fluorescence of individual plankton cells was established. Chl a fluorescence of single cells was measured in a flow cytometer with 488-nm argon-ion laser excitation. Absorption by dilute suspensions of cells was measured spectrophotometrically and normalized to cell number for computation of (r(488) (m2 cell-l). At the high excitation irradiances characteristic of lasers, a constant proportion of photons absorbed by photosynthetic pigments was re-emitted as Chl a fluorescence; a strong correlation was observed between absorption at 488 nm and Chl a fluorescence (r2 = 0.93; P << 0.00 1). The regression predicted the total phytoplankton absorption coefficient [a,,,,(488) (m-l)] at 488 nm for mixtures of five monospecific cultures with <9% error. For field samples, discrepancies between the flow cytometric method and the filter pad spectrophotometric method for estimating a,,,,(488) were greater. Relatively large, rare phytoplankton cells accounted for a disproportionate percentage of total a,,,,(488). The coherence between absorption at 488 nm and at other wavelengths was high and provides a basis for extrapolating from (r(488) to single-cell absorption coefficients at all visible wavelengths. The single-cell spectral absorption coefficients can be used to compute total in situ photon absorption for modeling light-limited photosynthetic rates of individual phytoplankton cells in the ocean. In the open ocean, phytoplankton and their derivative products dominate the optical characteristics of seawater. The ability to determine absorption and scattering by phytoplankton is key to understanding the optical properties of case 1 waters. Direct measurement of phytoplankton absorption coefficients in ocean waters has been difficult because absorption by detrital pigments and other particles is substantial and variable. Within the last few years, considerable progress has been made in measuring and modeling the contribution of phytoplankton to total light absorption in the ocean (Kishino et al. 1985; Bidigare et al. 1987; Cleveland 1988; Morrow et al. 1989; Roesler et al. 1989). Because these “bulk” phyAcknowledgments We thank C. S. Roesler and R. F. Davis for critically reading the manuscript, M. C. Talbot for technical assistance in the laboratory, and D. A. Kiefer for access to his particulate absorption data from the May 1987 Biowatt cruise. ONR contract NO001 4-87-K-01 60 and NSF grant OCE 86-003 10 provided research support; instrumentation support was provided from these sources and additionally from University of Washington matching funds. School of Oceanography Contribution 18 13; Biowatt Project Contribution 33. toplankton absorption coefficients are composites of the absorption coefficients of individual phytoplankton cells, changes or differences in absorption coefficients within or among water masses largely reflect differences in phytoplankton biomass, species composition, and/or optical properties of individual phytoplankton cells. Modern ecological theory recognizes that, in order to understand differences among communities, it is essential to statistically address the underlying variability at the level of the individual (Huston et al. 1988). Analagously, the ability to study optical properties of individual particles in seawater is essential for a mechanistic understanding of the causes of variability observed in bulk or composite optical measurements (cf. variability in attenuation profiles of Morel 1988). Except for the single-cell microspectrophotometric work of Iturriaga and Siegel (1988), relatively little attention has been focused on the variability ofabsorption coefficients of individual phytoplankton cells in the ocean. With microspectrophotometry, absorption spectra for the entire visible spectrum can be determined for an individual cell; however, present technology realistically constrains such analyses to a small