An optimality model of photoadaptation in contrasting aquatic light regimes

David Talmy, Jerry Blackford, Nick J. Hardman-Mountford, Alex J. Dumbrell and Richard J. Geider

Limnol. Oceanogr., 58(5), 2013, 1802-1818 | DOI: 10.4319/lo.2013.58.5.1802

ABSTRACT: To investigate photoacclimation of phytoplankton adapted to different aquatic light regimes, a physiologically explicit phytoplankton optimality model was applied in two contrasting environments: constant irradiance vs. dynamic irradiance associated with oceanic mixed layers. Nitrogen was assumed to be partitioned between cellular components associated with light harvesting, carbon fixation, biosynthesis, and photoprotection. The model was used to predict how resources are (re)distributed to optimize growth in the different environments. Optimal intracellular nitrogen allocation in dynamic environments was associated with constitutive investment in Calvin cycle enzymes; in contrast, in the static environment Calvin cycle allocation was reduced at low light. Furthermore, reduced allocation to components associated with photoprotection in static environments led to heavily inhibited photosynthesis–irradiance response consistent with that of Prochlorococcus adapted to relatively stable oligotrophic gyres. In contrast, photosynthetic response in the diatom Skeletonema costatum was better explained by maintenance of photoprotection components across a range of integrated light doses. Limited range of chlorophyll : C in Thalassiosira pseudonana was consistent with optimization of resource allocation to light-harvesting components in dynamic environments, in contrast to the relatively wide range in allocation to light harvesting predicted by the model in static environments and chlorophyll cell−1 observed in high-light–adapted Prochlorococcus. The model was used to explain variability of the photosynthesis–irradiance response of samples from the Celtic and Irish Seas. Photoacclimation state is a consequence of optimization of resource allocation to the set of environmental parameters (e.g., surface irradiance, depth of mixing, and light attenuation) that influence light variability.

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