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dc.contributor.authorKramer, Sasha J.  Concept link
dc.contributor.authorRoesler, Collin S.  Concept link
dc.contributor.authorSosik, Heidi M.  Concept link
dc.date.accessioned2018-11-01T15:50:27Z
dc.date.available2018-11-01T15:50:27Z
dc.date.issued2018-08-15
dc.identifier.citationRemote Sensing of Environment 217 (2018): 126-143en_US
dc.identifier.urihttps://hdl.handle.net/1912/10677
dc.description© The Author(s), 2018. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Remote Sensing of Environment 217 (2018): 126-143, doi:10.1016/j.rse.2018.08.010.en_US
dc.description.abstractDiatoms dominate global silica production and export production in the ocean; they form the base of productive food webs and fisheries. Thus, a remote sensing algorithm to identify diatoms has great potential to describe ecological and biogeochemical trends and fluctuations in the surface ocean. Despite the importance of detecting diatoms from remote sensing and the demand for reliable methods of diatom identification, there has not been a systematic evaluation of algorithms that are being applied to this end. The efficacy of these models remains difficult to constrain in part due to limited datasets for validation. In this study, we test a bio-optical algorithm developed by Sathyendranath et al. (2004) to identify diatom dominance from the relationship between ratios of remote sensing reflectance and chlorophyll concentration. We evaluate and refine the original model with data collected at the Martha's Vineyard Coastal Observatory (MVCO), a near-shore location on the New England shelf. We then validated the refined model with data collected in Harpswell Sound, Maine, a site with greater optical complexity than MVCO. At both sites, despite relatively large changes in diatom fraction (0.8–82% of chlorophyll concentration), the magnitude of variability in optical properties due to the dominance or non-dominance of diatoms is less than the variability induced by other absorbing and scattering constituents of the water. While the original model performance was improved through successive re-parameterizations and re-formulations of the absorption and backscattering coefficients, we show that even a model originally parameterized for the Northwest Atlantic and re-parameterized for sites such as MVCO and Harpswell Sound performs poorly in discriminating diatom-dominance from optical properties.en_US
dc.description.sponsorshipThis work was supported by: a Woods Hole Oceanographic Institution Summer Student Fellowship (NSF REU award #1156952) and a Bowdoin College Grua/O'Connell Research Award to SJK; grants to HMS from NASA (Ocean Biology and Biogeochemistry program and Biodiversity and Ecological Forecasting program), NSF (Ocean Sciences), the Gordon and Betty Moore Foundation, the Simons Foundation, and NOAA through the Cooperative Institute for the North Atlantic Region (CINAR) under Cooperative Agreement NA14OAR4320158; and grants to CSR from NASA (Ocean Biology and Biogeochemistry program).en_US
dc.language.isoen_USen_US
dc.publisherElsevieren_US
dc.relation.urihttps://doi.org/10.1016/j.rse.2018.08.010
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectPhytoplanktonen_US
dc.subjectCommunity structureen_US
dc.subjectOcean coloren_US
dc.subjectDiatomsen_US
dc.titleBio-optical discrimination of diatoms from other phytoplankton in the surface ocean: Evaluation and refinement of a model for the Northwest Atlanticen_US
dc.typeArticleen_US
dc.identifier.doi10.1016/j.rse.2018.08.010


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