Dynamic variability of the phytoplankton electron requirement for carbon fixation in eastern Australian waters

TL;DR

This study investigates how the electron requirement for carbon fixation in phytoplankton varies in eastern Australian waters, revealing that physiological factors like NPQNSV better predict this variability than environmental conditions.

Contribution

It introduces a high-throughput coupling of ETRs and 14C-incubations to analyze phytoplankton productivity across diverse oceanographic conditions, highlighting physiological predictors over environmental factors.

Findings

NPQNSV explains 55% of e,C variability.

Environmental conditions account for less than 20% of e,C variance.

Warmer waters show higher e,C, but size-fraction biomass does not predict e,C.

Abstract

Fast Repetition Rate fluorometry (FRRf) generates high-resolution measures of phytoplankton primary productivity as electron transport rates (ETRs). How ETRs scale to corresponding inorganic carbon (C) uptake rates (the so-called electron requirement for carbon fixation, e,C), inherently describes the extent and effectiveness with which absorbed light energy drives C-fixation. However, it remains unclear whether and how e,C follows predictable patterns for oceanographic datasets spanning physically dynamic, and complex, environmental gradients. We utilise a unique high-throughput approach, coupling ETRs and 14C-incubations to produce a semi-continuous dataset of e,C (n = 80), predominantly from surface waters, along the Australian coast (Brisbane to the Tasman Sea), including the East Australian Current (EAC). Environmental conditions along this transect could be generally grouped into cooler, more nutrient-rich waters dominated by larger size-fractionated Chl-a (>10 um) versus warmer nutrient-poorer waters dominated by smaller size-fractionated Chl-a (< 2 um). Whilst e,C was higher for warmer water samples, environmental conditions alone explained less than 20% variance of e,C, and changes in predominant size-fraction(s) distributions of Chl-a (biomass) failed to explain variance of e,C. Instead, NPQNSV was a better predictor of e,C, explaining 55% of observed variability. NPQNSV is a physiological descriptor that accounts for changes in both long-term driven acclimation in non-radiative decay, and quasi-instantaneous PSII downregulation, and thus may prove a useful predictor of e,C across physically-dynamic regimes, provided the slope describing their relationship is predictable.