Modeling carbon to nitrogen and carbon to chlorophyll a ratios in the ocean at low latitudes: Evaluation of the role of physiological plasticity

Abstract

Simulation modeling provides a means for testing the limits of our quantitative understanding of the factors that control phytoplankton biomass, growth rate, and primary productivity in the sea. We simulated the annual cycles of chlorophyll a (Chl a) concentration, primary productivity, nitrogen export, phytoplankton carbon to nitrogen (C : N) and carbon to Chl a ratios (C : Chl a) using a physiological model of phytoplankton carbon, nitrogen, and Chl a dynamics. The model was embedded within a one-dimensional physical model of vertical exchanges that included simple mortality and recycling terms. A sensitivity analysis allowed evaluation of the relative effects of changes in phytoplankton physiology, physical forcing, mortality, and nutrient cycling on Chl a distributions and phytoplankton C : N. Critical to the success of the model was the treatment of mortality, which included seasonal (temperature) and depth-related components, and the treatment of recycling efficiency, which was considered to be a function of the inorganic nitrogen concentration. The subtropical simulation compared favorably with data obtained at the Bermuda Atlantic Time-series Study (BATS) station. Our results illustrate the utility of physiological data in validation of biogeochemical models. In particular, model predictions of phytoplankton C : Chl a, which ranged from 30 to 170 g C (g Chl a)Ϫ1 , compared well with direct estimates based on 14 C labeling of Chl a. However, predictions of phytoplankton C : N, which ranged from ϳ5-9 g C (g N) Ϫ1 , could not be verified because of lack of data. This range of C : N suggests a slight limitation of phytoplankton growth rates by nutrients in surface waters.At the heart of pelagic biogeochemical models are the phytoplankton because they are responsible for carbon dioxide fixation. In addition, the extensive and growing database of chlorophyll a (Chl a) measurements provides the major reality check on the performance of pelagic biogeochemical models. Despite the explicit treatment of phytoplankton growth in these models, growth rates generated by the models typically do not agree with observations. Observed phytoplankton growth rates () in the mixed layer of subtropical gyres typically equal 0.6-0.7 d Ϫ1 (Lessard and Murrell 1998;Claustre et al. 1999;Stelfox-Widdicombe et al. 2000), whereas models typically return values of 0.1-0.2 d Ϫ1 (Fasham et al. 1990;Doney et al. 1996). Observations indicate that the phytoplankton relative growth rate (/ m ) is not severely nutrient-limited in subtropical and tropical

The role of temperature, cellular quota and nutrient concentrations for photosynthesis, growth and light–dark acclimation in phytoplankton

“…The observational data for natural phytoplankton assemblages, needed to validate our approach, were scattered over a vast range of journals. We note the important studies by Goldman et al (1979); Sakshaug et al (1989);Flynn et al (1994);Flynn et al (1997); Frenette et al (1998); Lefevre et al (2003); Klausmeier et al (2004) and by Schulz et al (2004).…”

Phytoplankton carbon and chlorophyll distributions in the equatorial Pacific and Atlantic: A basin-scale comparative study

“…The SeaWiFS chlorophyll dataset has been used widely, e.g., for the estimations of the global oceanic primary productivity (Behrenfeld and Falkowski, 1997;Behrenfeld et al, 2005;Carr et al, 2006;Westberry et al, 2008), and the validation of biogeochemical and ecosystem models (Doney et al, 2009;Faure et al, 2006;Lefevre et al, 2003;Wang et al, 2009a). However, these approaches rely on the knowledge of converting chlorophyll concentration to phytoplankton carbon biomass.…”

Untitled

“…The C:Chl ratio in live algal biomass, which has been investigated mostly in phytoplankton, is known to vary with taxonomic composition, light availability, and other factors (Reynolds 1984). C:Chl mass ratios of phytoplankton in culture and in pelagic environments commonly range between 25 and 100 (Ahlgren 1983;Geider 1987;Riemann et al 1989) but can be 150 or more in natural algal assemblages (Gieskes and Kraay 1989;Lefevre et al 2003). Higher C:Chl in biofilms can reflect slower growth rates and consequent secretion of mucilaginous materials (de Jonge 1980).…”