State-transitions facilitate robust quantum yields and cause an over-estimation of electron transport in Dunaliella tertiolecta cells held at the CO2 compensation point and re-supplied with DIC.

Photosynthetic energy consumption and non-photosynthetic energy quenching processes are inherently linked. Both processes must be controlled by the cell to allow cell maintenance and growth, but also to avoid photodamage. We used the chlorophyte algae Dunaliella tertiolecta to investigate how the interactive regulation of photosynthetic and non-photosynthetic pathways varies along dissolved inorganic carbon (DIC) and photon flux gradients. Specifically, cells were transferred to DIC-deplete media to reach a CO2 compensation before being re-supplied with DIC at various concentrations and different photon flux levels. Throughout these experiments we monitored and characterized the photophysiological responses using pulse amplitude modulated fluorescence, oxygen evolution, 77 K fluorescence emission spectra, and fast-repetition rate fluorometry. O2 uptake was not significantly stimulated at DIC depletion, which suggests that O2 production rates correspond to assimilatory photosynthesis. Fluorescence-based measures of relative electron transport rates (rETRs) over-estimated oxygen-based photosynthetic measures due to a strong state-transitional response that facilitated high effective quantum yields. Adoption of an alternative fluorescence-based rETR calculation that accounts for state-transitions resulted in improved linear oxygen versus rETR correlation. This study shows the extraordinary capacity of D. tertiolecta to maintain stable effective quantum yields by flexible regulation of state-transitions. Uncertainties about the control mechanisms of state-transitions are presented.

Predicting the electron requirement for carbon fixation in seas and oceans.

Marine phytoplankton account for about 50% of all global net primary productivity (NPP). Active fluorometry, mainly Fast Repetition Rate fluorometry (FRRf), has been advocated as means of providing high resolution estimates of NPP. However, not measuring CO2-fixation directly, FRRf instead provides photosynthetic quantum efficiency estimates from which electron transfer rates (ETR) and ultimately CO2-fixation rates can be derived. Consequently, conversions of ETRs to CO2-fixation requires knowledge of the electron requirement for carbon fixation (Φe,C, ETR/CO2 uptake rate) and its dependence on environmental gradients. Such knowledge is critical for large scale implementation of active fluorescence to better characterise CO2-uptake. Here we examine the variability of experimentally determined Φe,C values in relation to key environmental variables with the aim of developing new working algorithms for the calculation of Φe,C from environmental variables. Coincident FRRf and (14)C-uptake and environmental data from 14 studies covering 12 marine regions were analysed via a meta-analytical, non-parametric, multivariate approach. Combining all studies, Φe,C varied between 1.15 and 54.2 mol e(-) (mol C)(-1) with a mean of 10.9 ± 6.91 mol e(-) mol C)(-1). Although variability of Φe,C was related to environmental gradients at global scales, region-specific analyses provided far improved predictive capability. However, use of regional Φ e,C algorithms requires objective means of defining regions of interest, which remains challenging. Considering individual studies and specific small-scale regions, temperature, nutrient and light availability were correlated with Φ e,C albeit to varying degrees and depending on the study/region and the composition of the extant phytoplankton community. At the level of large biogeographic regions and distinct water masses, Φ e,C was related to nutrient availability, chlorophyll, as well as temperature and/or salinity in most regions, while light availability was also important in Baltic Sea and shelf waters. The novel Φ e,C algorithms provide a major step forward for widespread fluorometry-based NPP estimates and highlight the need for further studying the natural variability of Φe,C to verify and develop algorithms with improved accuracy.