Primary Productivity Dynamics in the Summer Arctic Ocean Confirms Broad Regulation of the Electron Requirement for Carbon Fixation by Light-Phytoplankton Community Interaction
Predicting conversion of photosynthetic electron transport to inorganic carbon uptake rates (the so-called electron requirement for carbon fixation, KC) is central to the broad scale deployment of Fast Repetition Rate fluorometry (FRRf) for primary productivity studies. However, reconciling variability of KC over space and time to produce robust algorithms remains challenging given the large number of factors that influence KC. We have previously shown that light appears a proximal driver of Kc in several ocean regions and therefore examined whether and how light similarly regulated KC variability in the Arctic Ocean during a summer cruise 2016. Sampling transited ice-free and ice-covered waters, with temperature, salinity and Chl-a concentrations all higher for the ice-free than ice covered surface waters. Micro- and pico-phytoplankton generally dominated the ice-free and ice-covered waters respectively. Values of KC, determined from parallel measures of daily integrated electron transport rates and 14C-uptake, were overall lower for the ice-covered versus ice-free stations. As in our previous studies, KC was strongly linearly correlated to daily PAR (r=0.68, n=46, p<0.001) and this relationship could be further improved (r=0.84, n=46, p<0.001) by separating samples into ice-free (micro-phytoplankton dominated) versus ice-covered (Nano- and Pico-phytoplankton dominated water. We subsequently contrasted the PAR-KC relationship form the Arctic waters with the previous relationships from the Ariake Bay and East China Sea, and revealed that these various PAR-KC relationships can be systematically explained across regions by phytoplankton community size structure. Specifically, the value of the linear slope describing PAR-KC decreases as water bodies have an increasing fraction of larger phytoplankton. We propose that this synoptic trend reflects how phytoplankton community structure integrates past and immediate environmental histories and hence may be better broad-scale predictor of KC than specific environmental factors such as temperature and nutrients. We provide a novel algorithm that may enable broad-scale retrieval of CO2 uptake from FRRf with knowledge of light and phytoplankton community size information.