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

Abstract

Abstract. Diversity plays critical roles in ecosystem functioning, but it remains challenging to model phytoplankton diversity in order to better understand those roles and reproduce 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 macroscopic 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 representations of physiological acclimation, i.e., flexible chlorophyll-to-carbon and nitrogen-to-carbon ratios. We have implemented CITRATE at two contrasting stations in the North Pacific where several years of observational data are available. The model is driven by physical forcing including vertical eddy diffusivity imported from three-dimensional general 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 prototype upon which more sophisticated continuous trait-based models can be developed.

Effect of phytoplankton size diversity on primary productivity in the North Pacific: trait distributions under environmental variability

“…In the 3D model ocean, even in the unrealistic cases without TD or KTW to sustain diversity, advection and diffusion still maintain levels of size diversity greater than 0.05 (ln μm 3 ) 2 in many areas (Figs and ). Vertically, deepening mixed layers during fall can entrain communities living at depth where nutrients are plentiful but light is limiting, into surface waters where nutrient can be limiting (Chen & Smith ). Horizontally, high diversity can also emerge along ocean fronts where mixing is active (Barton et al .…”

“…). The model details have been reported in Chen & Smith () with the only difference that only one zooplankton compartment is included in the present study. Here we briefly describe the main features that are most relevant for the present study.…”

“…Further model details relevant to size diversity, the TD coefficient u and the KTW coefficient a g , are given in the Supporting Online Materials and Chen & Smith (). To analyse the effect of the diversity enhancing coefficients on total NPP, we also decomposed the differences of integrated NPP among model runs using the chain rule:where is the NPP integrated over all model grids ( dV stands for the volume of each grid) from 0 to 260 m over an annual cycle.…”

“…We quantify size diversity in terms of the variance of log-transformed cell volume, following previous studies (Wirtz 2014;Acevedo-Trejos et al 2015;Smith et al 2016). The model details have been reported in Chen & Smith (2018) with the only difference that only one zooplankton compartment is included in the present study. Here we briefly describe the main features that are most relevant for the present study.…”

“…where Q min and Q max are the minimal and maximal nitrogento-carbon ratios respectively. Further model details relevant to size diversity, the TD coefficient u and the KTW coefficient a g , are given in the Supporting Online Materials and Chen & Smith (2018). To analyse the effect of the diversity enhancing coefficients on total NPP, we also decomposed the differences of integrated NPP among model runs using the chain rule:…”