Using Optical Sensors on Gliders to Estimate Phytoplankton Carbon Concentrations and Chlorophyll-to-Carbon Ratios in the Southern Ocean

• Published in: Frontiers in Marine Science
• Main Authors: Sandy J. Thomalla, A. Gilbert Ogunkoya, Marcello Vichi, Sebastiaan Swart
• Format: Article in Journal/Newspaper
• Language: English
• Published: Frontiers Media S.A. 2017
• Subjects: phytoplankton carbon; chlorophyll to carbon ratios; particulate backscattering; gliders; Southern Ocean; Science; Q; General. Including nature conservation; geographical distribution; QH1-199.5; Antarctic; Antarc*
• Online Access: https://doi.org/10.3389/fmars.2017.00034; https://doaj.org/article/a0583275a8ba4443b93c1db6370110f1

One approach to deriving phytoplankton carbon biomass estimates (Cphyto) at appropriate scales is through optical products. This study uses a high-resolution glider data set in the Sub-Antarctic Zone (SAZ) of the Southern Ocean to compare four different methods of deriving Cphyto from particulate backscattering and fluorescence-derived chlorophyll (chl-a). A comparison of the methods showed that at low (<0.5 mg m−3) chlorophyll concentrations (e.g., early spring and at depth), all four methods produced similar estimates of Cphyto, whereas when chlorophyll concentrations were elevated one method derived higher concentrations of Cphyto than the others. The use of methods derived from particulate backscattering rather than fluorescence can account for cellular adjustments in chl-a:Cphyto that are not driven by biomass alone. A comparison of the glider chl-a:Cphyto ratios from the different optical methods with ratios from laboratory cultures and cruise data found that some optical methods of deriving Cphyto performed better in the SAZ than others and that regionally derived methods may be unsuitable for application to the Southern Ocean. A comparison of the glider chl-a:Cphyto ratios with output from a complex biogeochemical model shows that although a ratio of 0.02 mg chl-a mg C−1 is an acceptable mean for SAZ phytoplankton (in spring-summer), the model misrepresents the seasonal cycle (with decreasing ratios from spring to summer and low sub-seasonal variability). As such, it is recommended that models expand their allowance for variable chl-a:Cphyto ratios that not only account for phytoplankton acclimation to low light conditions in spring but also to higher optimal chl-a:Cphyto ratios with increasing growth rates in summer.