Phytoplankton Blooms: New Initiative Using Marine Optics as a Basis for Monitoring Programs

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Book Chapter

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marine optical proprieties, monitoring coastal system, Phytoplankton blooms


Ocean color and optical remote sensing techniques has become a useful tool to study coastal problems such as harmful algal blooms and water pollution. Considering that phytoplankton blooms affect the ocean color, we proposed here an innovative technique using optical data to determine if there is a bloom or not, characterize the bloom stage, and the phytoplankton composition. Data were collected during two sampling campaigns: one from August 27th to 30th, 2011 in Dzilam de Bravo (State of Yucatan) and Holbox Island (State of Quintana Roo), México; and the second campaign was conducted from September 22nd to 24th, 2011 in the Bank of Campeche, Campeche, México. Optical data were analyzed for a total of 30 stations. For each station, discrete samples were collected for phytoplankton identification and enumeration and determination of chlorophyll-a concentration and absorption coefficients (particulate material, phytoplankton, detritus, and colored dissolved organic matter). Most of the samples were collected near the surface; however a few samples were collected at mid and bottom depths. During campaign 1, Secchi disk measurements were taken to measure the light attenuation. Principal component analysis (PCA) with a numerical solution was used to explore the associations among samples (stations) using the absorption coefficients, chlorophyll-a and total phytoplankton abundance. To comprehensively summarize all the information produced by each of the variables, a multi-dimensional index was derived based on the first standardized empirical orthogonal function. We refer to the index as the inherent optical properties (IOP) index. A positive IOP index indicated bloom conditions were present, while a negative index indicated non-bloom conditions. Once the samples were classified by bloom condition, we attempted to determine the phytoplankton group that constituted the bloom. The spectral shape of the phytoplankton absorption coefficient spectra aphy(λ)was calculated and a spectral shape index was derived using the phytoplankton absorption coefficient in the green and the blue part of the spectrum. Finally, a blue/red ratio was calculated to determine the dominant phytoplankton population. The IOP index was successful in classifying the station as having bloom or non-bloom conditions. The spectral shape analysis gave promising results regarding the group composition. Additional analyses, with different phytoplakton groups and taxa, are required to further test this ratio. A final classification scheme using the IOP index and the blue/red ratio is proposed to determine the bloom condition (operational, non-operational bloom and non-bloom) and dominate size of the phytoplankton responsible for the bloom. This innovative technique can provide insightful information about the bloom that cannot be obtained using traditional methods. The results here showed clearly the importance of optical data when monitoring phytoplankton blooms.

Citation / Publisher Attribution

Phytoplankton Blooms: New Initiative using Marine Optics as a Basis for Monitoring Programs, in M. T. Sebastiá, Coastal Ecosystems: Experiences and Recommendations for Environmental Monitoring Programs, Nova Science Publishers, p. 57-88

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