Carbon-to-chlorophyll ratio and growth rate of phytoplankton in the sea

Abstract

Observations from offshore regions (NW Atlantic and Arabian Sea) and from a semienclosed bay (Tokyo Bay) were used to study the relationships between chlorophyll and particulate carbon in the sea. A simple conceptual model was then developed to infer in situ phytoplankton carbon as a function of chlorophyll a. This allowed indirect estimates of the carbon-to-chlorophyll ratio of phytoplankton in the sea. Using data from high-performance liquid chromatography, field samples dominated by diatoms, dinoflagellates, green algae, prymnesiophytes and cyanobacteria were identified, and their carbon-to-chlorophyll ratios were established. The computations yielded conservative estimates for the ratio (15 to 176 weight:weight). The results were applied to satellite data to map the carbon-to-chlorophyll ratios in the NW Atlantic. Since methods were already in place to estimate photosynthesis-irradiance parameters for the region by remote sensing (Platt et al. 2008), we showed that it was possible, using remote sensing, to compute carbon-based phytoplankton growth rates by making use of the existing information on photosynthesis-irradiance parameters and carbonto-chlorophyll ratios. The method makes it possible to compute primary production by using either carbon-based growth models or photosynthesis-irradiance models in ways that are fully comparable with each other.

Effects of elevated CO<sub>2</sub> and temperature on phytoplankton community biomass, species composition and photosynthesis during an experimentally induced autumn bloom in the western English Channel

“…Photosynthetic carbon fixation in Phaeocystis spp. is presently near saturation with respect to current levels of pCO 2 (Rost et al, 2003). Dominance of this spp.…”

“…We speculate that the decline in biomass under nutrient replete conditions in the combination treatment was probably due to slower species-specific growth rates when diatoms and dinoflagellates became more prominent in this treatment. Carbon : Chl a ratios in diatoms and dinoflagellates have previously been demonstrated to be lower than nano-and picophytoplankton (Sathyendranath et al, 2009). This contrasts the results reported in comparable studies as Chl a is generally highly correlated with biomass (e.g.…”

Retrieval of phytoplankton size from bio-optical measurements: theory and applications

“…Based on major pigments identified by HPLC, phytoplankton samples dominated by certain taxonomic groups can be distinguished [31]. Using this method samples dominated by diatoms, prymnesiophytes, Prochlorococcus, other cyanobacteria and green algae were identified.…”

Intercomparison of Ocean Color Algorithms for Picophytoplankton Carbon in the Ocean

“…However, with a median value of 91 mg C mg Chla −1 , the in situ C phy -to-satellite-B-ratio falls within or close to observed values in oligotrophic areas. For instance, Sathyendranath et al (2009) Statistics provided have uncertainty estimates (95% confidence interval), from 1,000 bootstrap realizations (See section 2.4). Bold numbers are the best results for each statistic: highest value for rs and rp, lowest for Ψ , δ, ∆, I and MAPD, and closest to one for S. ratio greater than 100 mg C mg Chla −1 for prymnesiophytes, cyanobacteria and Prochlorococcus sp.…”

“…These include methods based on particle back-scattering coefficient (b bp ) at a single wavelength (Behrenfeld et al, 2005;Martínez-Vicente et al, 2013); empirical relationships based on chlorophyll concentration (Sathyendranath et al, 2009;Marañón et al, 2014); and methods based on allometric considerations combined with either the spectral slope of the particle back-scattering spectrum (Kostadinov et al, 2009(Kostadinov et al, , 2016 or with the phytoplankton absorption characteristics (Roy et al, 2017). Of these, the method proposed by Martínez-Vicente et al (2013) dealt with a fraction of the phytoplankton community (diameter < 20 µm), whereas those of Behrenfeld et al (2005), Sathyendranath et al (2009), and Marañón et al (2014) dealt with the whole phytoplankton community. The methods based on allometric structure (Kostadinov et al, 2009(Kostadinov et al, , 2016Roy et al, 2017), on the other hand, have the advantage of being able to target the whole of the phytoplankton community, and partition phytoplankton carbon among any user-defined size-intervals.…”