Phytoplankton play a key role in the geochemical cycles of the Earth, are responsible for 50% of global carbon fixation, and through this, provide almost all of the energy for the entire marine trophic system. Understanding the dynamics of phytoplankton, and the species composition in relation to environmental factors is therefore of great importance. In this thesis a range of techniques to identify phytoplankton groups that use accessory pigment data obtained from high performance liquid chromatography are compared. While fixed indicator pigment:chl-a ratio approaches provide a quick and simple way of estimating phytoplankton distributions either on the basis of size-class or taxonomic group, the more sophisticated iterative approach of CHEMTAX divides the biomass into more categories and allows more flexibility to adapt to changes in indicator pigment:chl-a ratios caused by environmental variability. Combined with flow cytometric cell counts, depth-dependent trends in the intracellular concentration and composition of phytoplankton pigments can be identified. These data show an exponential decrease in the ratio of carbon-to-chlorophyll with depth, in response to decreasing light intensity. The relative as well as absolute concentrations of phytoplankton pigments are also seen to change with depth, particularly under stratified conditions, with the ratio of zeaxanthin to chlorophyll-a decreasing with increasing depth, and the ratio of chlorophyll-b to chlorophyll-a increasing. Cluster analysis is used to identify the main phytoplankton populations in the North West Atlantic, with communities of large, fucoxanthin-containing phytoplankton dominating in spring when mixing is strong, before being replaced by smaller cells upon the onset of stratification. The links between trends in phytoplankton photophysiology and abiotic conditions are also explored, with temperature being found to be the most important forcing factor. Size-class specific relationships between phytoplankton photosynthetic rates and temperature are identified, with the potential for use in remotely-sensed models of primary production.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:635212 |
| Date | January 2013 |
| Creators | Robinson, Alex |
| Contributors | Bouman, Heather; Sathyendranath, Shubha; Tilstone, Gavin |
| Publisher | University of Oxford |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://ora.ox.ac.uk/objects/uuid:49a0f202-6f3f-4f2e-ace5-572faf583222 |
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