Detecting seasonal shifts in the taxonomic structure of marine phytoplankton in the Southern Ocean based on their bio-optical properties

1. Assess the distribution of phytoplankton groups using in situ measurements pigment markers, marine bio-optics and microscopic cell counts. 

2. Identify the key environmental variables that govern shifts in phytoplankton community structure in space and time. 

3. Determine the light absorption signatures that may be used to detect the presence of phytoplankton functional types using ocean-colour radiometry. 

4. Produce a resolved time series of community structure and marine primary production during key transition periods in a highly undersampled region of the Southern Ocean using optical and satellite datasets

Marine diatoms are key players in the ocean carbon cycle, responsible for ~ 20% of global marine productivity. In the High-Nitrate Low-Chlorophyll (HNLC) regions of the Southern Ocean (SO), phytoplankton communities are dominated by a diverse assemblage of small eukaryotic cells under low light (winter) and low nutrient (summer) conditions (Bouman et al. 2012).  Yet in the spring period, the increase in availability of light and nutrients, in particular dissolved silica (Si) and Fe, allows large cells (diatoms) to bloom, potentially increasing the efficiency of the SO’s biological pump (Coale et al. 2004).  In this grossly undersampled region of the global ocean, to study the succession in phytoplankton taxonomic composition in response to changes in growth conditions, and its interannual variability, requires sustained large-scale observations which only earth-orbiting satellites can provide. 

The student will use data collected as part of the NERC Carbon Uptake and Seasonal Traits in Antarctic Remineralisation Depth (CUSTARD) project in the Southeast Pacific, where Antarctic Intermediate Waters and SubAntarctic Mode Waters form, along with historical data from other regions of the SO.  The relationships between surface chlorophyll concentrations and the light absorption characteristics of phytoplankton will be compared with global trends.  Implications of these findings for the retrieval of chlorophyll biomass using conventional remote sensing reflectance algorithms will be explored. The assembled bio-optical dataset will be used to develop a satellite algorithm specific for HNLC seas to improve the retrieval of surface chlorophyll, primary production and phytoplankton functional types from space.