Temperature effects on optimality-based phytoplankton growth model

Phytoplankton are a key driver of global marine biogeochemical cycles, but the response to ocean warming remains difficult to predict, partly because the temperature-dependence of physiological processes is not well understood. This study extends an optimality-based phytoplankton growth model to include metabolic responses to temperature. Using microcosm data, we identify two key parameters showing roughly consistent temperature responses: maximum uptake rate (V0) and chlorophyll synthesis cost (ζC). We assess the accuracy of temperature-dependent species-specific (SS) and non-species-specific (nSS) model configurations in reproducing microcosm experimental data, relative to a non-temperature-dependent, species-specific control model (noTemp). Our results demonstrate that explicitly accounting for temperature-dependence can significantly improve predictions of phytoplankton biomass production, nitrogen uptake, and stoichiometry. The SS configuration consistently outperforms other setups in predicting particulate organic carbon, chlorophyll-a, and nutrients (DIN, DIP), while the nSS configuration still performs substantially better than the (species-specific) noTemp configuration. These findings underscore the importance of accounting for temperature-dependence in ecological models for future projections of phytoplankton responses to environmental change.