The impact of cell-specific absorption properties on the correlation of electron transport rates measured by chlorophyll fluorescence and photosynthetic oxygen production in planktonic algae

Photosynthesis–irradiance (P–E)-curves describe the photosynthetic performance of autotrophic organisms. From these P–E-curves the photosynthetic parameters α-slope, Pmax, and Ek can be deduced which are often used to characterize and to compare different organisms or organisms in acclimation to different environmental conditions. Particularly, for in situ-measurements of P–E curves of phytoplankton the analysis of variable chlorophyll fluorescence proved its potential as a sensitive and rapid method. By using Chlorella vulgaris (Trebouxiophyceae), Nannochloropsis salina (Eustigmatophyceae), Skeletonema costatum and Cyclotella meneghiniana (Bacillariophyceae), the present study investigated the influence of cellular bio-optical properties on the correlation of the photosynthetic parameters derived from fluorescence-based P–E-curves with photosynthetic parameters obtained from the measurement of oxygen evolution. It is demonstrated that small planktonic algae show a wide range of cellular absorptivity which was subject to species-specifity, growth stage and environmental conditions, e.g. nutrient limitation. This variability in bio-optical properties resulted in a great deviation of relative electron transport rates (rETRs) from oxygen-based photosynthesis rates. Thus, the photosynthetic parameters α-slope and Pmax derived from rETRs strongly depend on the specific cellular absorptivity and cannot be used to compare the photosynthetic performance of cells with different optical properties. However, it was shown that Ek is independent of cellular absorptivity and could be used to compare samples with unknown optical properties.

► We have compared light saturation curves from fluorescence and oxygen measurements.
► We show that the relative electron transport rates do not match oxygen evolution rates.
► The absorptivity of the cells is the crucial factor for the observed mismatch. The results help to standardize PAM technology and to prevent misinterpretations.