Phytoplankton community structure determined through remote sensing and in situ optical measurements

dc.contributor.advisorBernard, Stewarten_ZA
dc.contributor.advisorHenson, Stephanieen_ZA
dc.contributor.advisorShillington, Franken_ZA
dc.contributor.advisorLucas, Mikeen_ZA
dc.contributor.authorEvers-King, Hayley Louiseen_ZA
dc.date.accessioned2015-06-15T06:59:45Z
dc.date.available2015-06-15T06:59:45Z
dc.date.issued2014en_ZA
dc.descriptionIncludes bibliographical references.en_ZA
dc.description.abstractLinking variability in optical signals with phytoplankton community characteristics is important to extend the use of the vast resource that is the satellite ocean colour archive. Detection of species, functional types or size classes has been addressed through a spectrum of empirical to analytical approaches. A key step in developing these techniques is quantifying the sensitivity in reflectance, which can be attributed to phytoplankton characteristics (e.g cell size) under different optical regimes. Ultimately, highly spatially and temporally resolved information on phytoplankton characteristics can help the global scientific community to answer important questions relating to primary ecosystem variability. In the southern Benguela, Harmful Algal Blooms threaten public health and the economic viability of fishery and aquaculture industries in the region. Concurrently, the dominance of phytoplankton biomass amongst optically significant constituents in the southern Benguela makes the region ideal for assessing the extent to which phytoplankton characteristics beyond biomass can influence the ocean colour signal. A forward and inverse approach is presented. Phytoplankton absorption and back scattering are generated from a phytoplankton particle population model coupled to two radiative transfer approaches: a reflectance approximation and the radiative transfer model, EcoLight-S. Non-linear optimisation inversion schemes are then implemented. A simulated dataset is created to investigate how much variability in reflectance can be associated with changes in phytoplankton cell size in different bio-optical water types. This dataset is inverted to investigate the errors inherent in the inversion process as a result of ambiguity. Comparison of the two radiative transfer techniques allows for consideration of the suitability of approximations for bidirection-ality and subsurface propagation. The inversion algorithm is then applied to hyperspectral in situ radiometric data to provide validation and further assessment of errors from all sources. Results indicate that size related sensitivity in reflectance is highly dependent on phytoplank-ton biomass, as determined by the relative phytoplankton contribution to the Inherent Optical Property budget. The algorithm is finally applied to ten years of MERIS data covering the southern Benguela. A time series of biomass and cell size is presented and metrics developed to demonstrate the utility of this approach for identifying previously unobserved interannual variability in Harmful Algal Blooms.en_ZA
dc.identifier.apacitationEvers-King, H. L. (2014). <i>Phytoplankton community structure determined through remote sensing and in situ optical measurements</i>. (Thesis). University of Cape Town ,Faculty of Science ,Department of Oceanography. Retrieved from http://hdl.handle.net/11427/13076en_ZA
dc.identifier.chicagocitationEvers-King, Hayley Louise. <i>"Phytoplankton community structure determined through remote sensing and in situ optical measurements."</i> Thesis., University of Cape Town ,Faculty of Science ,Department of Oceanography, 2014. http://hdl.handle.net/11427/13076en_ZA
dc.identifier.citationEvers-King, H. 2014. Phytoplankton community structure determined through remote sensing and in situ optical measurements. University of Cape Town.en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Evers-King, Hayley Louise AB - Linking variability in optical signals with phytoplankton community characteristics is important to extend the use of the vast resource that is the satellite ocean colour archive. Detection of species, functional types or size classes has been addressed through a spectrum of empirical to analytical approaches. A key step in developing these techniques is quantifying the sensitivity in reflectance, which can be attributed to phytoplankton characteristics (e.g cell size) under different optical regimes. Ultimately, highly spatially and temporally resolved information on phytoplankton characteristics can help the global scientific community to answer important questions relating to primary ecosystem variability. In the southern Benguela, Harmful Algal Blooms threaten public health and the economic viability of fishery and aquaculture industries in the region. Concurrently, the dominance of phytoplankton biomass amongst optically significant constituents in the southern Benguela makes the region ideal for assessing the extent to which phytoplankton characteristics beyond biomass can influence the ocean colour signal. A forward and inverse approach is presented. Phytoplankton absorption and back scattering are generated from a phytoplankton particle population model coupled to two radiative transfer approaches: a reflectance approximation and the radiative transfer model, EcoLight-S. Non-linear optimisation inversion schemes are then implemented. A simulated dataset is created to investigate how much variability in reflectance can be associated with changes in phytoplankton cell size in different bio-optical water types. This dataset is inverted to investigate the errors inherent in the inversion process as a result of ambiguity. Comparison of the two radiative transfer techniques allows for consideration of the suitability of approximations for bidirection-ality and subsurface propagation. The inversion algorithm is then applied to hyperspectral in situ radiometric data to provide validation and further assessment of errors from all sources. Results indicate that size related sensitivity in reflectance is highly dependent on phytoplank-ton biomass, as determined by the relative phytoplankton contribution to the Inherent Optical Property budget. The algorithm is finally applied to ten years of MERIS data covering the southern Benguela. A time series of biomass and cell size is presented and metrics developed to demonstrate the utility of this approach for identifying previously unobserved interannual variability in Harmful Algal Blooms. DA - 2014 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 2014 T1 - Phytoplankton community structure determined through remote sensing and in situ optical measurements TI - Phytoplankton community structure determined through remote sensing and in situ optical measurements UR - http://hdl.handle.net/11427/13076 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/13076
dc.identifier.vancouvercitationEvers-King HL. Phytoplankton community structure determined through remote sensing and in situ optical measurements. [Thesis]. University of Cape Town ,Faculty of Science ,Department of Oceanography, 2014 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/13076en_ZA
dc.language.isoengen_ZA
dc.publisher.departmentDepartment of Oceanographyen_ZA
dc.publisher.facultyFaculty of Scienceen_ZA
dc.publisher.institutionUniversity of Cape Town
dc.subject.otherPhysical Oceanographyen_ZA
dc.titlePhytoplankton community structure determined through remote sensing and in situ optical measurementsen_ZA
dc.typeDoctoral Thesis
dc.type.qualificationlevelDoctoral
dc.type.qualificationnamePhDen_ZA
uct.type.filetypeText
uct.type.filetypeImage
uct.type.publicationResearchen_ZA
uct.type.resourceThesisen_ZA
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