Phytoplankton growth and stoichiometry under multiple nutrient limitation

TLDR

Phytoplankton growth and stoichiometry depend on the availability of multiple nutrients. The study employs a flexible‑stoichiometry mathematical model to explain phytoplankton composition patterns observed in chemostat experiments and field nutrient drawdown dynamics. The model analytically distinguishes exponential growth and equilibrium phases, each amenable to mathematical analysis. The model predicts that at low growth rates phytoplankton stoichiometry matches nutrient supply stoichiometry, that stoichiometry varies nonlinearly with dilution rate between supply and species‑specific optimal ratios, and that equilibrium concentrations of two nutrients are low across a wide range of supply ratios—agreeing with experimental data except at extreme ratios that require a negative feedback from quota to uptake.

Abstract

Phytoplankton growth and stoichiometry depend on the availability of multiple nutrients. We use a mathematical model of phytoplankton with flexible stoichiometry to explain patterns of phytoplankton composition in chemostat experiments and nutrient drawdown dynamics that are found in the field. Exponential growth and equilibrium represent two distinct phases, each amenable to mathematical analysis. In a chemostat at a fixed dilution (growth) rate, phytoplankton stoichiometry matches the nutrient supply stoichiometry over a wide range at low growth rates and over a narrow range at high growth rates. In a chemostat with a fixed nutrient supply stoichiometry, phytoplankton stoichiometry varies with dilution rate nonlinearly, between the supply stoichiometry at low dilution rates and a species‐specific optimal ratio at high dilution rates. The flexible‐stoichiometry model we study predicts low equilibrium concentrations of two nutrients over a wide range of supply ratios, contrary to the predictions of a traditional fixed‐stoichiometry model. The model is in quantitative agreement with experimental data, except at extreme nutrient supply ratios, which require a negative feedback from quota to uptake to fit the data. Our analysis points to the importance of better understanding the regulation of uptake rates in determining phytoplankton stoichiometry and incorporating this knowledge into phytoplankton models.