Numerical analysis of cumulative impact of phytoplankton photoresponses to light variation on carbon assimilation

Abstract

Light variation in temporal and spatial domains is a key constraint on the photosynthetic performance of phytoplankton. The most obvious responses are the modification of cell pigment content either to improve photocapture or to mitigate photo-damage. Very few studies have analyzed whether light variation significantly alters carbon assimilation, especially in a fluctuating light environment as in the mixed layer of the ocean. We addressed the question using a modeling approach, which allows the reproduction of most of the possible scenarios, obtained with great difficulty from laboratory or field experiments. The complete model is based on the dynamic coupling of a photoacclimation and photodamage-repair responses. In this combined model the virtual phytoplankton is exposed to different light regimes (steady, square wave, sinusoidal light-dark cycles and fluctuating regimes). The results reconcile controversial results on different photoacclimation states achieved during fluctuating light regimes. The model produces a depression of carbon assimilation in any light fluctuating scenario, as compared to steady light regimes, due to the temporal delay between light fluctuations and photoresponses. These results suggest the possibility of selective pressure during evolution, more effective on photoprotective mechanisms than on optimization of light harvesting.

Vortex waves and vertical motion in a mesoscale cyclonic eddy

“…On the other hand, plankton physiology and ecology are characterized by time‐based rates, so that not only photosynthesis, but also other processes (such as grazing, remineralization, photoinhibition, etc.) can modulate primary production at specific time scales, ranging between a few hours and several weeks [e.g., Franks , ; Sarmiento and Gruber , ; Esposito et al ., ]. In all cases, the biological response is related to the history of the environmental conditions surrounding the organisms, so that characteristic rates should effectively be evaluated in a Lagrangian framework.…”

“…Even if particle trajectories cannot be considered reliable in the upper mixed layer, due to the coarse resolution and to the limitations of the approximation adopted, they provide insight on the vertical exchange driven by internal dynamics at the base of the euphotic layer. Corresponding timescales are in the range between a few days and a couple of weeks, comparable to the characteristic scales of several biogeochemical processes influencing photosynthesis and phytoplankton dynamics [e.g., Franks , ; Sarmiento and Gruber , ; Esposito et al ., , Perruche et al ., ].…”

The diatom molecular toolkit to handle nitrogen uptake

“…At the beginning, he focused on the dependence of growth rate on the internal quota of the nutrient, i.e., Uptakerate ∝ Growth-rate = Growth-rate max (1 − Quota max / Quota). Merging the two, the dependence of growth from uptake rate would be a function of external and internal concentrations with the maximum assimilation rate (V max in the Michaelis-Menten formulation, Uptake max in the formulation above) modulated by the internal N quota (e.g., Esposito et al, 2009;Geider et al, 1998), e.g., Uptake ∝ (1 − Q/Q max ) / (1 − Q / Q max + shape function) * [Nut] / (K Nut + [Nut]), where Q is explicitly the N/C ratio in the cell and the shape function that allows to modulate the uptake in dependence of the internal quota in a more realistic way. It is worth mentioning that we are assuming here a simplified view where the external concentration is the concentration in the vicinity of the transporter, thus without considering the processes in the cell boundary layer (see (Aksnes and Egge, 1991) and (Fiksen et al, 2013) for a more integrated approach).…”

“…Several studies have been carried out to understand which are the checkpoints in the cell metabolism that allow for modulation of the uptake (Flynn, 1991). However they are either empirical (Esposito et al, 2009;Geider et al, 1998) or based on the internal processing of assimilated N (e.g. (Flynn, 1991)) without focusing on the fact that the regulation must occur on the intake process, i.e., at the transporter level.…”

Marine diatoms change their gene expression profile when exposed to microscale turbulence under nutrient replete conditions

“…Considering that the cell concentrations in all cylinders were comparable, there was no effect of light attenuation. We also considered that cells in turbulence experienced a fluctuating light regime with respect to those in still 45 but since the illumination was from the side and the cylinder radius was 0.12 m 28 , the maximum light variation between the wall and the centre of the cylinder was less than 5%, and overall fluctuation in the 3D space of the cylinder accounted for no more than 13%, even at the maximum cell concentration recorded.…”