Parameterization of Photoinhibition For Phytoplankton

TL;DR

This paper introduces a new model for phytoplankton photosynthesis that accurately captures photoinhibition and the plateau in photosynthetic rates, improving predictions of primary production in aquatic ecosystems.

Contribution

The authors develop a novel parameterization of photoinhibition that enhances existing models by incorporating a saturating function, requiring only one additional parameter.

Findings

Best model improves adjusted R2 by up to 37%

Reduces RMSE by up to 70% compared to existing models

Photoinhibition parameter indicates onset and rate of decline

Abstract

Mathematical models of photosynthesis-irradiance relationships in phytoplankton are used to compute integrated water-column photosynthetic rates and predict primary production. Models typically ignore an important phenomenon observed in most experiments: photosynthetic rate remains constant over a range of irradiances before declining due to photoinhibition. Here we develop an approach that captures both photoinhibition and this plateau. We test six new models of photoinhibition and ten more photoinhibition models from the literature against a database of 1808 photosynthesis-irradiance curves exhibiting photoinhibition. The best model improves adjusted R2 by 6-37% and reduces RMSE by 15-70% compared to existing models. In the best model, photoinhibition is phenomenologically described by multiplication by a saturating function of the reciprocal of irradiance, simplifies to the widely-used Jassby & Platt photosynthesis-irradiance curve in the absence of photoinhibition, and only requires one new parameter. This photoinhibition parameter identifies the onset of photoinhibition and is the rate of decrease in photosynthetic rate at that irradiance. Simulations show that while parameter values vary up to 40% across existing models, particularly with and without photoinhibition, our representation of photoinhibition does not affect the interpretation or numerical values of parameters compared to the corresponding model without photoinhibition.