We present a model of the growth rate and elemental stoichiometry of phytoplankton as a function of resource allocation between and within broad macromolecular pools under a variety of resource supply conditions. The model is based on four, empirically-supported, cornerstone assumptions: that there is a saturating relationship between light and photosynthesis, a linear relationship between RNA/protein and growth rate, a linear relationship between biosynthetic proteins and growth rate, and a constant macromolecular composition of the light-harvesting machinery. We combine these assumptions with statements of conservation of carbon, nitrogen, phosphorus, and energy. The model can be solved algebraically for steady state conditions and constrained with data on elemental stoichiometry from published laboratory chemostat studies. It interprets the relationships between macromolecular and elemental stoichiometry and also provides quantitative predictions of the maximum growth rate at given light intensity and nutrient supply rates. The model is compatible with data sets from several laboratory studies characterizing both prokaryotic and eukaryotic phytoplankton from marine and freshwater environments. It is conceptually simple, yet mechanistic and quantitative. Here, the model is constrained only by elemental stoichiometry, but makes predictions about allocation to measurable macromolecular pools, which could be tested in the laboratory.

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 21 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.

Abstract. Phytoplankton cell size influences particle sinking rate, food web interactions and biogeographical distributions. We present a model in which the uptake, storage and assimilation of nitrogen and carbon are explicitly resolved in different-sized phytoplankton cells. In the model, metabolism and cellular C : N ratio are influenced by the accumulation of carbon polymers such as carbohydrate and lipid, which is greatest when cells are nutrient starved, or exposed to high light. Allometric relations and empirical data sets are used to constrain the range of possible C : N, and indicate that larger cells can accumulate significantly more carbon storage compounds than smaller cells. When forced with extended periods of darkness combined with brief exposure to saturating irradiance, the model predicts organisms large enough to accumulate significant carbon reserves may on average synthesize protein and other functional apparatus up to five times faster than smaller organisms. The advantage of storage in terms of average daily protein synthesis rate is greatest when modeled organisms were previously nutrient starved, and carbon storage reservoirs saturated. Small organisms may therefore be at a disadvantage in terms of average daily growth rate in environments that involve prolonged periods of darkness and intermittent nutrient limitation. We suggest this mechanism is a significant constraint on phytoplankton C : N variability and cell size distribution in different oceanic regimes.