The present study was designed to assess the effectiveness of the eDNA metabarcoding approach to determine the phytoplankton composition in the marine environment with a special focus on mucilage episodes in the Sea of Marmara. For this purpose, the samples were collected from 5 different sites located in the Sea of Marmara and the northern Aegean Sea during the mucilage episode in June 2021. The phytoplankton diversity was analyzed morphologically and by 18S rRNA gene amplicon sequencing, and the dataset of both methods was compared, accordingly. The results showed significant differences between methods in terms of composition and the abundance of the phytoplankton groups. While Miozoa was the most abundant group by metabarcoding, light microscopy (LM) indicated a dominance of Bacillariophyta. Katablepharidophyta was found at lower abundances by the metabarcoding (representing < 1% of the community); the members of this phylum were not observed by a microscope. At the lower taxonomic levels, Chaetoceros was the only genus detected in all samples by both methods. Additionally, while mucilage-forming Gonyaulax fragilis, Cylindrotheca closterium, and Thalassiosira rotula were detected to species-level by LM, metabarcoding was able to determine these organisms at the genus level. On the other hand, the genus Arcocellulus was found in all metabarcoding datasets and not detected by microscopy. The results indicated that metabarcoding can detect a greater number of genera and reveal taxa that were overlooked by light microscopy but to develop a complete picture of phytoplankton diversity in the sample, microscopical observations still are in need.

Marine mucilage outbreaks occurred in the Sea of Marmara in 2021 which severely affected the marine ecosystem. The thick mucilage blankets with different colors became a public concern due to the toxicity potential related to pathogens that accumulate in prolonged presence of mucilage. The mucilage-covered areas in the Sea of Marmara detected by remote sensing data acquired in 2021 were previously reported. However, the areal extents and spectral characteristics of the different colored mucilage types remain unknown. This study presents the spectral characteristics of different types of mucilage in the İzmit Bay in the Sea of Marmara by using medium- (Sentinel-2) and high-spatial resolution (Worldview-3) satellite images. Also, the sea surface temperatures (SST) were studied in relation with the mucilage formation from January 2015 to August 2021 by using NOAA data. Two multispectral satellite sensors Sentinel-2 and Worldview-3 were studied for their potential for mucilage mapping and characterization in the sub-region İzmit Bay. Support vector machine (SVM) classifier was used to detect three different types of mucilage with distinguishable spectral differences in infrared region ranging from 725 to 950 nm. Three different types of mucilage were characterized based on color and texture including (a) the white mucilage aggregates with dispersed patterns which are likely freshly formed, (b) the yellow mucilage accumulations in the coasts that are wind/current transported, and (c) the brown mucilage accumulations that are probably the most-aged. Our results showed that brown mucilage and white mucilage showed similar reflectance values between 425 and 545 nm region, while yellow mucilage showed higher and more distinctive spectral reflectance than white and brown mucilages. The NOAA data showed that average surface water temperature has been increased over the years from 2015 (16.1 °C) to 2021 (17.6 °C). This increase trend in SSTs points out a likely relation with the mucilage formation and hence may suggest a potential of repeating mucilage events in the near future. This study provides a practical methodology for monitoring, classification, and efficient site selection for mucilage cleaning areas in the Sea of Marmara.