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      Remotely sensing harmful algal blooms in the Red Sea

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          Abstract

          Harmful Algal Blooms (HABs) are of global concern, as their presence is often associated with socio-economic and environmental issues including impacts on public health, aquaculture and fisheries. Therefore, monitoring the occurrence and succession of HABs is fundamental for managing coastal regions around the world. Yet, due to the lack of adequate in situ measurements, the detection of HABs in coastal marine ecosystems remains challenging. Sensors on-board satellite platforms have sampled the Earth synoptically for decades, offering an alternative, cost-effective approach to routinely detect and monitor phytoplankton. The Red Sea, a large marine ecosystem characterised by extensive coral reefs, high levels of biodiversity and endemism, and a growing aquaculture industry, is one such region where knowledge of HABs is limited. Here, using high-resolution satellite remote sensing observations (1km, MODIS-Aqua) and a second-order derivative approach, in conjunction with available in situ datasets, we investigate for the first time the capability of a remote sensing model to detect and monitor HABs in the Red Sea. The model is able to successfully detect and generate maps of HABs associated with different phytoplankton functional types, matching concurrent in situ data remarkably well. We also acknowledge the limitations of using a remote-sensing based approach and show that regardless of a HAB’s spatial coverage, the model is only capable of detecting the presence of a HAB when the Chl-a concentrations exceed a minimum value of ~ 1 mg m -3. Despite the difficulties in detecting HABs at lower concentrations, and identifying species toxicity levels (only possible through in situ measurements), the proposed method has the potential to map the reported spatial distribution of several HAB species over the last two decades. Such information is essential for the regional economy (i.e., aquaculture, fisheries & tourism), and will support the management and sustainability of the Red Sea’s coastal economic zone.

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          Smoothing and differentiation of data by simplified least square procedure.

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            Remote sensing of phytoplankton groups in case 1 waters from global SeaWiFS imagery

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              Red tide detection and tracing using MODIS fluorescence data: A regional example in SW Florida coastal waters

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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: SoftwareRole: ValidationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: SupervisionRole: Writing – review & editing
                Role: Writing – review & editing
                Role: Data curation
                Role: ConceptualizationRole: SupervisionRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                16 April 2019
                2019
                : 14
                : 4
                : e0215463
                Affiliations
                [1 ] Physical Science and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Kingdom of Saudi Arabia
                [2 ] Remote Sensing Group, Plymouth Marine Laboratory (PML), Plymouth, Devon, United Kingdom
                [3 ] Department of Biology, National and Kapodistrian University of Athens (NKUA), Athens, Greece
                [4 ] Department of Marine Biology, Hodeidah University, Al Hodeidah, Yemen
                University of Siena, ITALY
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0002-9642-4419
                http://orcid.org/0000-0002-3751-4393
                Article
                PONE-D-18-29842
                10.1371/journal.pone.0215463
                6467414
                30990831
                fafdd2a5-ed83-4d50-bc06-2d55a5f1ec59
                © 2019 Gokul et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 15 October 2018
                : 2 April 2019
                Page count
                Figures: 11, Tables: 4, Pages: 21
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100004052, King Abdullah University of Science and Technology;
                Award ID: REP/1/3268-01-01
                Award Recipient :
                This research was funded by the King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR) (REP/1/3268-01-01 to IH). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Earth sciences
                Marine and aquatic sciences
                Bodies of water
                Red Sea
                Ecology and Environmental Sciences
                Aquatic Environments
                Marine Environments
                Sea Water
                Earth Sciences
                Marine and Aquatic Sciences
                Aquatic Environments
                Marine Environments
                Sea Water
                Biology and Life Sciences
                Organisms
                Eukaryota
                Plants
                Algae
                Phytoplankton
                Biology and Life Sciences
                Organisms
                Eukaryota
                Animals
                Invertebrates
                Plankton
                Phytoplankton
                Biology and Life Sciences
                Organisms
                Eukaryota
                Plants
                Algae
                Engineering and Technology
                Remote Sensing
                Biology and Life Sciences
                Organisms
                Eukaryota
                Protists
                Dinoflagellates
                Earth Sciences
                Marine and Aquatic Sciences
                Bodies of Water
                Oceans
                Research and Analysis Methods
                Spectrum Analysis Techniques
                Infrared Spectroscopy
                near-Infrared Spectroscopy
                Custom metadata
                All relevant data are within the manuscript and its Supporting Information files.

                Uncategorized
                Uncategorized

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