Low complexity model to study scale dependence of phytoplankton dynamics in the tropical Pacific

TL;DR

This study demonstrates that a simple reaction-diffusion-advection model can effectively reproduce and analyze the scale-dependent dynamics of phytoplankton in the tropical Pacific, revealing the relative impacts of various drivers and stability under nutrient changes.

Contribution

The paper introduces a low-complexity RDA model that accurately captures phytoplankton distribution and scale relationships, enabling exploration of ecological questions beyond high-complexity models.

Findings

Advection significantly influences primary productivity rates.

Turbulent diffusion impacts phytoplankton variability and is scale-propagated.

Phytoplankton chlorophyll scales sub-linearly with nutrients and remains stable under nutrient decline.

Abstract

We demonstrate that a simple model based on reaction-diffusion-advection (RDA) equation forced by realistic surface velocities and nutrients is skilled in reproducing the distributions of the surface phytoplankton chlorophyll in the tropical Pacific. We use the low-complexity RDA model to investigate the scale-relationships in the impact of different drivers (turbulent diffusion, mean and eddy advection, primary productivity) on the phytoplankton chlorophyll concentrations. We find that in the 1/4{\deg} (~25km) model, advection has a substantial impact on the rate of primary productivity, whilst the turbulent diffusion term has a fairly negligible impact. Turbulent diffusion has an impact on the phytoplankton variability, with the impact being scale-propagated and amplified by the larger scale surface currents. We investigate the impact of a surface nutrient decline and some changes to mesoscale eddy kinetic energy (climate change projections) on the surface phytoplankton concentrations. The RDA model suggests that unless mesoscale eddies radically change, phytoplankton chlorophyll scales sub-linearly with the nutrients, and it is relatively stable with respect to the nutrient concentrations. Furthermore we explore how a white multiplicative Gaussian noise introduced into the RDA model on its resolution scale propagates across spatial scales through the non-linear model dynamics under different sets of phytoplankton drivers. The unifying message of this work is that the low complexity (e.g. RDA) models can be successfully used to realistically model some specific aspects of marine ecosystem dynamics and by using those models one can explore many questions that would be beyond computational affordability of the higher-complexity ecosystem models.