Trait-based numerical model for mixotrophic phytoplankton and application in Singapore water

TL;DR

This paper introduces a trait-based numerical model for mixotrophic phytoplankton that simplifies parameterization and accurately simulates growth, nutrient dynamics, and interactions, with practical applications in Singapore water.

Contribution

It presents a novel trait-based modeling approach for mixotrophic phytoplankton that improves parameter efficiency and matches experimental data.

Findings

Model accurately reproduces phytoplankton growth and nutrient uptake.

Trait-based approach reduces model complexity.

Successful application in simulating algal blooms in Singapore water.

Abstract

A numerical model for mixotrophic phytoplankton is described in this paper. In contrast with traditional approach where nutrient uptake rates are constrained by a predefined growth rate, this model uses empirical traits to compute nutrient uptake rates, and then the growth is controlled by the nutrient uptake. Simple but meaningful traits for heterotrophy are derived by analogising heterotrophic mode with phototrophic mode. The trait-based approach could reduce the model parameterization significantly. Model performance evaluation against laboratory experiments of various phytoplankton species has shown remarkable successfulness. Using a single set of model parameterization, the model is able to capture well the growth rate, nutrient consumption, accumulation of none-limiting nutrients, increase of cell size of nutrient-starved cells, surge uptake and rapid population growth of starved cells when nutrient is added as well as the mixotrophic interaction of different pairs of predator-prey. The model for mixotrophic phytoplankton is couped with a hydrodynamic model to simulate algal blooms in Singapore water. The model has shown a great potential for practical applications