The unicellular NUM v.0.91: A trait-based plankton model evaluated in two contrasting biogeographic provinces

Abstract. Trait-based models founded on biophysical principles are becoming popular in planktonic ecological modeling, and justifiably so. They allow for slim, efficient models with a significant reduction in parameters, well suited for modeling the past and future climate changes. In their simplest form, trait-based models describe the ecosystem in one set of parameters defined by first principles, rooted in physics, geometry, and evolution. The result is an emerging ecosystem defined by physical and chemical limitations at the cell level. At present, however, a significant part of these parameters is not fully constrained, which potentially introduces a considerable uncertainty to the model results. Here, we investigate how these parameters influence the ecosystem structure of one of the simplest trait-based models, the Nutrient-Unicellular-Multicellular (NUM) model. We describe the unicellular module of the NUM model and through an extensive parameter sensitivity analysis, we demonstrate that the model – with a large span in parameters – can capture the general features of the pico-, nano-, and micro planktonic ecosystem at the southern California Current. We show that it is possible to narrow the range of parameters to get a stable, acceptable, solution. Finally, we show that the model responds correctly to a change in oceanographic setting.

Our analysis demonstrates that the unicellular module of the NUM model is accessible for the general non-expert without intimate knowledge of the parameter settings, and that the first-principal approach is well suited for modeling poorly resolved region and ecosystem evolution during current and deep time climate change.