Spatial and temporal variability in phytoplankton carbon, chlorophyll, and nitrogen in the North Pacific

Abstract

[1] Carbon, nitrogen, and chlorophyll are three commonly used variables to quantify phytoplankton productivity. However, owing to the complex effect of light, temperature, and nutrient, these three variables are usually decoupled from each other. By implementing a biogeochemical model that treats phytoplankton carbon, nitrogen, and chlorophyll separately in a Pacific basin-scale circulation model, we have investigated the physical and biogeochemical controls on phytoplankton C:Chl and C:N ratios at different scales. The model reproduces the general features of phytoplankton dynamics in the Pacific basin. Model results indicate a region dependent pattern of driving mechanisms for C:Chl ratio, where C:Chl is largely controlled by light condition in high latitude, by light and nutrient levels in midlatitude, and by nutrient and temperature in the equatorial Pacific, while C:N ratio seems to be region independent and is mostly determined by nutrient and temperature. Pacific basin-scale empirical orthogonal functions (EOF) decompositions suggest both C:Chl and C:N are regulated by the El Niño/Southern Oscillation (ENSO) events to the first-order variability. Owing to the variation of C:Chl, the decoupling between phytoplankton carbon and chlorophyll exists, especially at seasonal and long-term temporal scales. Climate change can affect phytoplankton pigment, biomass, and physiological state. As a consequence, using chlorophyll as a proxy for phytoplankton biomass to interpret decadal variation or long-term trend might be with bias.

Transport patterns of Pacific sardine Sardinops sagax eggs and larvae in the California Current System

“…The CoSiNE model consists of 13 state variables describing plankton (meso-zooplankton, micro-zooplankton, small phytoplankton and diatoms), nutrients (nitrate, silicate, ammonium, detritus nitrogen, detritus silicate, phosphate), and others (dissolved oxygen, total carbon dioxide and total alkalinity). Recently, the CoSiNE-13 has been improved to simulate phytoplanktonic photo-acclimation and the dynamic carbon to chlorophyll and carbon to nitrogen ratios with different growth conditions (Xiu and Chai, 2012).…”

A biogeochemical model of phytoplankton productivity in an urban estuary: The importance of ammonium and freshwater flow

“…In constructing this model, we drew upon our previous work in developing a biogeochemical ecosystem model -the CoSiNE (Carbon, Silicate, Nitrogen Ecosystem) model Dugdale et al, 2002) that has been incorporated into Pacific basin-wide and coastal ROMS models (e.g. Xiu and Chai, 2012), reproducing many important features of these ecosystems. The present model incorporates CoSiNE phytoplankton uptake kinetics (Michaelis-Menten formulation) and an exponential function ( ) for NH 4 inhibition of NO 3 uptake .…”

Does spatial variation in environmental conditions affect recruitment? A study using a 3-D model of Peruvian anchovy

“…1). The Carbon, Si(OH) 4 , Nitrogen Ecosystem (CoSiNE) model (Chai et al, 2002(Chai et al, , 2003 was imbedded in ROMS and simulated 3-dimensional lower trophic level dynamics (Chai et al, , 2009Xiu and Chai, 2012). The biogeochemical and lower trophic levels consisted nitrogen and silica cycling and the biomass dynamics of four plankton groups: small phytoplankton (or non-diatoms), large phytoplankton (diatoms), small (micro) zooplankton, and large (meso) zooplankton.…”