Event Title
Streaming Media
Presentation Abstract
Seasonal and spatial variability in phytoplankton community composition in the Salish Sea was investigated between the spring and summer of 2018 and 2019. Surface water for the measurements for HPLC pigments and coloured dissolved organic matter (CDOM), total suspended matter (TSM) concentration were collected from (~2 m depth) using a water pumping system installed on the ferry Queen of Alberni. At the same time, an above-water radiometer was installed on the bow of the ferry to measure the water-leaving radiance. The surface bio-geochemical variables such as TChla, CDOM, and TSM concentration has demonstrated a remarkable spatial and seasonal variability. In addition, reflectance spectra acquired using the above-water radiometer have shown a typical case-2 water reflectance governed by phytoplankton pigments, high absorption from CDOM, and the backscattering from suspended sediments. HPLC derived phytoplankton pigment data from 2018 has shown the signals of seasonal spring bloom and large raphidophytes bloom mainly comprises Heterosigma akashiwo during summer 2018. Similarly, CHEMTAX derived phytoplankton community composition shows that diatom constitutes highly to the overall phytoplankton biomass, especially during the spring, and cryptophytes and prasinophytes are the common flagellates that dominate during summer. We have developed an Empirical Orthogonal Function-based model to retrieve different phytoplankton groups in the Salish Sea from the satellite image. The EOF-based phytoplankton group model developed showed a moderate retrieval for diatom, dictyochophytes, raphidophytes (R2=0.51, MDPD=56%; R2=0.36, MDPD=41%; R2=0.49, MDPD=58%), respectively. As a final step, we have applied the model to individual satellite images and derived the spatial distribution of different phytoplankton groups.
Session Title
Innovations and Emerging Science 1
Conference Track
SSE1: Science for the Future
Conference Name
Salish Sea Ecosystem Conference (2022 : Online)
Document Type
Event
SSEC Identifier
SSE-traditionals-121
Start Date
27-4-2022 9:45 AM
End Date
27-4-2022 11:15 AM
Rights
Copying of this document in whole or in part is allowable only for scholarly purposes. It is understood, however, that any copying or publication of this document for commercial purposes, or for financial gain, shall not be allowed without the author's written permission.
Type
Text
Language
English
Deriving Phytoplankton Community Composition in the Salish Sea using CHEMTAX and OLCI Sentinel 3 data
Seasonal and spatial variability in phytoplankton community composition in the Salish Sea was investigated between the spring and summer of 2018 and 2019. Surface water for the measurements for HPLC pigments and coloured dissolved organic matter (CDOM), total suspended matter (TSM) concentration were collected from (~2 m depth) using a water pumping system installed on the ferry Queen of Alberni. At the same time, an above-water radiometer was installed on the bow of the ferry to measure the water-leaving radiance. The surface bio-geochemical variables such as TChla, CDOM, and TSM concentration has demonstrated a remarkable spatial and seasonal variability. In addition, reflectance spectra acquired using the above-water radiometer have shown a typical case-2 water reflectance governed by phytoplankton pigments, high absorption from CDOM, and the backscattering from suspended sediments. HPLC derived phytoplankton pigment data from 2018 has shown the signals of seasonal spring bloom and large raphidophytes bloom mainly comprises Heterosigma akashiwo during summer 2018. Similarly, CHEMTAX derived phytoplankton community composition shows that diatom constitutes highly to the overall phytoplankton biomass, especially during the spring, and cryptophytes and prasinophytes are the common flagellates that dominate during summer. We have developed an Empirical Orthogonal Function-based model to retrieve different phytoplankton groups in the Salish Sea from the satellite image. The EOF-based phytoplankton group model developed showed a moderate retrieval for diatom, dictyochophytes, raphidophytes (R2=0.51, MDPD=56%; R2=0.36, MDPD=41%; R2=0.49, MDPD=58%), respectively. As a final step, we have applied the model to individual satellite images and derived the spatial distribution of different phytoplankton groups.
