CITRATE 1.0: Phytoplankton continuous trait-distribution model with one-dimensional physical transport applied to the North Pacific

Bingzhang Chen, Sherwood Lan Smith

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

Diversity plays critical roles in ecosystem func- tioning, but it remains challenging to model phytoplankton diversity in order to better understand those roles and repro- duce consistently observed diversity patterns in the ocean. In contrast to the typical approach of resolving distinct species or functional groups, we present a ContInuous TRAiT-basEd phytoplankton model (CITRATE) that focuses on macro- scopic system properties such as total biomass, mean trait values, and trait variance. This phytoplankton component is embedded within a nitrogen–phytoplankton-zooplankton– detritus–iron model that itself is coupled with a simplified one-dimensional ocean model. Size is used as the master trait for phytoplankton. CITRATE also incorporates “trait diffusion” for sustaining diversity and simple representa- tions of physiological acclimation, i.e., flexible chlorophyll- to-carbon and nitrogen-to-carbon ratios. We have imple- mented CITRATE at two contrasting stations in the North Pacific where several years of observational data are avail- able. The model is driven by physical forcing including ver- tical eddy diffusivity imported from three-dimensional gen- eral ocean circulation models (GCMs). One common set of model parameters for the two stations is optimized using the Delayed-Rejection Adaptive Metropolis–Hasting Monte Carlo (DRAM) algorithm. The model faithfully reproduces most of the observed patterns and gives robust predictions on phytoplankton mean size and size diversity. CITRATE is suitable for applications in GCMs and constitutes a proto- type upon which more sophisticated continuous trait-based models can be developed.
LanguageEnglish
Pages467-495
Number of pages29
JournalGeoscientific Model Development
Volume11
DOIs
Publication statusPublished - 1 Feb 2018

Fingerprint

Phytoplankton
phytoplankton
Ocean
Model
distribution
Nitrogen
Carbon
Metropolis-Hastings Algorithm
Zooplankton
nitrogen
Monte Carlo Algorithm
Chlorophyll
carbon
ocean
Biomass
Diffusivity
Rejection
Ecosystem
acclimation
Iron

Keywords

  • Phytoplankton
  • North Pacific
  • ocean circulation models

Cite this

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title = "CITRATE 1.0: Phytoplankton continuous trait-distribution model with one-dimensional physical transport applied to the North Pacific",
abstract = "Diversity plays critical roles in ecosystem func- tioning, but it remains challenging to model phytoplankton diversity in order to better understand those roles and repro- duce consistently observed diversity patterns in the ocean. In contrast to the typical approach of resolving distinct species or functional groups, we present a ContInuous TRAiT-basEd phytoplankton model (CITRATE) that focuses on macro- scopic system properties such as total biomass, mean trait values, and trait variance. This phytoplankton component is embedded within a nitrogen–phytoplankton-zooplankton– detritus–iron model that itself is coupled with a simplified one-dimensional ocean model. Size is used as the master trait for phytoplankton. CITRATE also incorporates “trait diffusion” for sustaining diversity and simple representa- tions of physiological acclimation, i.e., flexible chlorophyll- to-carbon and nitrogen-to-carbon ratios. We have imple- mented CITRATE at two contrasting stations in the North Pacific where several years of observational data are avail- able. The model is driven by physical forcing including ver- tical eddy diffusivity imported from three-dimensional gen- eral ocean circulation models (GCMs). One common set of model parameters for the two stations is optimized using the Delayed-Rejection Adaptive Metropolis–Hasting Monte Carlo (DRAM) algorithm. The model faithfully reproduces most of the observed patterns and gives robust predictions on phytoplankton mean size and size diversity. CITRATE is suitable for applications in GCMs and constitutes a proto- type upon which more sophisticated continuous trait-based models can be developed.",
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