Modeling phytoplankton growth rates and chlorophyll to carbon ratios in California coastal and pelagic ecosystems

TLDR

High‑resolution models are required to capture the temporal and spatial variability of physical, biological, and biogeochemical processes, yet many ecosystem models disagree with observations due to data or formulation inadequacies, and Lagrangian field measurements from the CCE program provide strong constraints for improving such models. The study aims to parameterize and optimize a two‑phytoplankton functional type model of growth rate and chlorophyll‑to‑carbon ratio using Lagrangian field data from the CCE program. The model was parameterized on a coastal subset of the data and then extended and tested with the full dataset, leveraging size‑resolved measurements of growth, grazing, production, and export rates collected during process cruises that tracked water parcels. The optimized model accurately reproduces observed growth rates and Chl:C ratios, predicts biomasses and growth rates from temperature, nutrients, and bulk chlorophyll, and captures subsurface growth maxima and the spatial separation of carbon and chlorophyll maxima in California coastal and pelagic ecosystems.

Abstract

To understand and quantify plankton community dynamics in the ocean, high‐resolution models are needed to capture the temporal and spatial variations of physical, biological, and biogeochemical processes. However, ecosystem models often fail to agree with observations. This failure can be due to inadequacies in the data and/or inadequacies in the model formulation and parameterization. Here we parameterize and optimize a two‐phytoplankton functional type model of phytoplankton growth rate and chlorophyll/carbon (Chl:C) ratio using data from the Lagrangian field measurements conducted during process cruises of the Long‐Term Ecosystem Research–California Current Ecosystem (CCE) program. We parameterize the model based on a small coastal subset of the data and then extend and test it with the full data set, including data from offshore regions. The CCE process studies were focused on quantifying the size‐resolved planktonic growth, grazing, production, and export rates while following water parcels. The resulting data therefore provided strong constraints for the model we employed. The modeled growth rates and Chl:C ratios were in good agreement with observations. Our results indicate that the model can accurately predict Chl:C ratios, biomasses, and growth rates of dominant functional types using relatively easily measured environmental variables (temperature, nutrients, and bulk chlorophyll). The model also accurately reproduces the subsurface maxima of growth rates, the spatial separation of carbon and chlorophyll maxima, and many other observations in the California Current coastal and pelagic ecosystems.