Resting stages are common for the life cycle of some phytoplankton species, including blooming and potentially toxic species. The “seed bank” accumulated in the sediments can initiate blooms in the water column and could be an early warning signal of harmful algal blooms (HABs). In order to identify the phytoplankton cyst assemblages, thirteen surface sediment samples were collected from different sites in the Black Sea. The diversity of the resting stages was assessed using high-throughput sequencing metabarcoding (V7-9 hypervariable region of the 18S rDNA). One hundred and eighty microalgal species were identified with high level of similarity to the reference sequences. Dinoflagellates were dominated by Biecheleria, Gymnodinium and Karlodinium. Within diatoms, Skeletonema, Chaetoceros and Thalassiosira were the most abundant genera. Sixteen of the detected operational taxonomic units (OTUs) were assigned to harmful microalgae (12 dinoflagellates species, 1 diatom, 1 haptophyte and 2 raphidophytes). No pattern of microalgal sequences depth distribution was discriminated. The results show that DNA metabarcoding has a great potential for assessment of the phytoplankton diversity in environmental sediments.

Numerous potentially toxic plankton species commonly occur in the Black Sea, and phycotoxins have been reported. However, the taxonomy, phycotoxin profiles, and distribution of harmful microalgae in the basin are still understudied. An integrated microscopic (light microscopy) and molecular (18S rRNA gene metabarcoding and qPCR) approach complemented with toxin analysis was applied at 41 stations in the northwestern part of the Black Sea for better taxonomic coverage and toxin profiling in natural populations. The combined dataset included 20 potentially toxic species, some of which (Dinophysis acuminata, Dinophysis acuta, Gonyaulax spinifera, and Karlodinium veneficum) were detected in over 95% of the stations. In parallel, pectenotoxins (PTX-2 as a major toxin) were registered in all samples, and yessotoxins were present at most of the sampling points. PTX-1 and PTX-13, as well as some YTX variants, were recorded for the first time in the basin. A positive correlation was found between the cell abundance of Dinophysis acuta and pectenotoxins, and between Lingulodinium polyedra and Protoceratium reticulatum and yessotoxins. Toxic microalgae and toxin variant abundance and spatial distribution was associated with environmental parameters. Despite the low levels of the identified phycotoxins and their low oral toxicity, chronic toxic exposure could represent an ecosystem and human health hazard.

Harmful Algal Blooms (HABs) represent a significant global challenge to human health, economies, and ecosystems, including those of the Black Sea. Despite previous reports of potentially toxic microalgae and phycotoxins in the basin, the taxonomy and occurrence of toxigenic species and their associated toxins remain poorly resolved. During the PHYCOB cruise in September 2021, the diversity and distribution of toxigenic microalgae and phycotoxins were investigated across 23 stations in the western Black Sea, covering Bulgarian and Romanian waters. Numerous potentially toxic microalgal taxa were identified using complementary morphological (light microscopy and scanning electron microscopy) and molecular (DNA metabarcoding) methods. The genus Pseudo-nitzschia was the only representative of potentially toxic diatoms, but no domoic acid was found. Among toxic dinoflagellates, Dinophysis spp., Protoceratium reticulatum, Lingulaulax polyedra, and Gonyaulax spp. were frequently observed, along with the related pectenotoxins and yessotoxins. Species distribution modelling indicated that the western Black Sea provides favorable conditions for Dinophysis spp., L. polyedra, and P. reticulatum. Additionally, several Alexandrium species were identified, including the first record of A. fragae in the basin, along with the detection of the associated phycotoxins (GTX-2/3 and GDA). This study provides the first integrated assessment combining light and scanning electron microscopy, DNA metabarcoding, and chemical analyses of toxigenic microalgae in field samples from the western Black Sea, contributing to an improved understanding of their region-specific profiles.

The Black Sea is an extraordinarily complex water body for ocean color remote sensing, as it belong to Case 2 waters, which are characterized by relatively high absorption by Colored Dissolved Organic Matter (CDOM) while the concentration of non-pigmented particulate matter does not co-vary in a predictable manner with chlorophyll a . The optical complexity of the Black Sea is the reason why the standard bio-optical algorithms developed for Case 1 waters, are the source of large uncertainties (of the order of hundreds of percent) of chlorophyll a concentration in the coastal and shelf regions. In the framework of ESA contract “BIO-OPTICS FOR OCEAN COLOR REMOTE SENSING OF THE BLACK SEA - Black Sea Color” we developed empirical ocean color algorithm for chlorophyll a retrieval from Sentinel 3A/OLCI primary ocean color products using the in situ reference bio-optical datasets collected in the Black Sea in the period 2012-2019. Results obtained from the assessment of operational S3A/OLCI chlorophyll products, highlighted and confirmed that the specific regional algorithm is essential for the Black Sea. The coefficients of the regional algorithm were derived from the regression of log-transformed pigment concentrations and remote sensing reflectance ratio at 490nm and 560 nm with determination coefficient R2 =0.88 and number of samples N=186. The algorithm predicts chlorophyll a values using a cubic polynomial formulation. The result of assessment of the regional chlorophyll a product against independent in situ measurements from the data utilized for algorithm development, showed relatively high accuracy (31.7%), fewer underestimations (MPD=-9.2%) and a good agreement (R2=0.66) between datasets indicating that the regional algorithm is more effective in reproducing the  pigment concentration in the Black Sea waters in comparison to the standard Sentinel 3A/OLCI algorithms. Our analysis revealed the importance of providing regional algorithms strictly required to suit the peculiar bio-optical properties featuring this basin. However, this requires collection of accurate in situ measurements in the different parts of the Black Sea. The validity of the reported empirical algorithm obviously depends on the size of the dataset used for its development. The Black Sea waters vary at a basin level due to the sub-regional features, environmental factors and seasonal variability, consequently the presented regional algorithm might have a limited generalization capability. Clearly, more in situ data with improved spatial and temporal coverage are critically needed for further calibration and validation of the ocean color products in the Black Sea.

Phytoplankton monitoring is essential for assessing marine ecosystem health, as phytoplankton are sensitive indicators of ecosystem disturbances. Imaging flow cytometry (IFC) has emerged as a powerful tool for high-throughput phytoplankton analysis, providing taxon-specific insights into community composition and dynamics. The integration of imaging technology with machine learning has enabled the automated classification of plankton images. Geographical variation in phytoplankton community composition necessitates the development of region-specific annotated datasets for accurate automated recognition. This paper presents an initial version of the regional Black Sea phytoplankton image dataset, comprising 8,077 taxonomically annotated images (JPEG format;Fig. 1), together with their associated morphological, optical scattering, fluorescence, and pulse-shape attributes (e.g., length, size, structure, shape, pigments). The dataset was built using Easyclus© software (https://www.easyclus.com/) from samples collected between June 2022 and June 2023 in Varna Bay, Black Sea, and analyzed using a CytoSense flow cytometer (CytoBuoy b.v., Woerden, The Netherlands). It encompasses 162 categories representing 160 taxa, including 49 identified to genus level and 111 to species level. Taxonomic names at the genus and species levels were verified against the World Register of Marine Species (WoRMS Editorial Board 2024). The number of images per category varies considerably, ranging from 1 to 1127, reflecting the naturally imbalanced representation of taxa in the collected samples and resulting image library (Fig. 2). The dataset was subsequently tested as a reference library for the automated classification of phytoplankton in 72 Black Sea samples using Easyclus© software, and the results were compared with those obtained using conventional light microscopy (LM). Automated classification of the test samples identified between 61 and 122 categories per sample. The proportion of particles successfully assigned to one of the predefined categories varied considerably among samples, from 7.3% to 92.6% of total particle counts, although the average classification rate was high (78.1%). The overall taxonomic coverage achieved by IFC was lower than that obtained by LM: 304 taxa were identified by LM, compared with 152 taxa by IFC. The taxonomic overlap between methods within individual samples ranged from 18% to 39%, with a mean of 29.3%. The observed discrepancy may be attributed to several factors, including the natural heterogeneity of field samples (Cermeño et al. 2013, Rodríguez-Ramos et al. 2013), identification difficulties associated with sample fixation (Mukherjee et al. 2014), sedimentation effects within the sample tubing (Peperzak et al. 2018), and gaps in the reference image dataset. In addition, the strong imbalance in the number of images across categories may affect classification performance by biasing results toward better-represented categories (Johnson and Khoshgoftaar 2019). Despite these limitations, CytoSense demonstrated greater sample-level taxon detection and substantially higher time efficiency, with an analysis time of approximately 20 min per sample compared with 8–10 h per sample for LM. Although further development of the Black Sea Phytoplankton Image Dataset is needed to increase both taxonomic coverage and the number of representative images per category, the results demonstrate the strong potential of this regional annotated image library for imaging flow cytometry-based phytoplankton monitoring in the Black Sea.

Introduction The Institute of Oceanology – Bulgarian Academy of Sciences (IO-BAS) manages the Black Sea macrosite, comprising the Kaliakra, Galata, and Koketrice marine sites, which have been part of the Bulgarian national Long-Term Ecological Research (LTER) network since 2007. Since 2022, a new equipment - WiMo Plus multiparameter platform - has been installed in Varna Bay near Cape Galata, providing in situ data on temperature, conductivity, salinity, pH, dissolved oxygen, chlorophyll-a and other physicochemical indicators. In addition, samples are taken monthly by the Testing Laboratory "Marine Chemistry" for analysis of the main physicochemical parameters, dissolved oxygen and nutrients, as well as chlorophyll-a. The analyses are carried out in the accredited chemical laboratory and the specialized biological laboratory using validated methods for marine waters. The present study aims to investigate the interannual variability of physicochemical quality elements and assess the ecological status of the Galata site, with particular emphasis on trophic status and temporal variations in nutrient ratios. Material and methods The study is based on data from Varna Bay - Galata site, including continuous in situ measurements obtained using the WiMo Plus multiparametric platform and monthly field sampling conducted between January 2022 – December 2025. In situ data were processed statistically (TIBCO Software Inc. (2018) 2023). Water samples were measured by a WTW multimeter on site for temperature (T), conductivity (Cond), salinity (S ‰) and pH. Dissolved oxygen (DO) was fixed for subsequent analysis in the Testing Laboratory “Marine Chemistry” by the Winkler method. The samples were analysed in the Testing Laboratory for the content of ammonium nitrogen (N-NH4), nitrate nitrogen (N-NO3), nitrite nitrogen (N-NO2), total nitrogen (TN), phosphate phosphorus (P-PO4), total phosphorus (TP) and silicon (Si) spectrophotometrically with a CECIL 1021 spectrophotometer by internally validated methods based on Grasshoff et al. (2009)). Chlorophyll-a was prepared in the specialized biological laboratory following the steps: filtration, extraction, photometry at different wavelengths, and calculation of concentrations according to the equations of Jeffrey and Humphrey (1975) using a specialized computer program (Edler 1979). Results and Discussions The laboratory analysis results were evaluated on both a seasonal and annual basis. The coldest winter occurred in 2022, with an average sea surface temperature of 6.1 °C, while the warmest was in 2023, averaging 8.7 °C. Naturally, summer was the warming season overall, peaking in 2024 with the maximum seasonal average of 25.9 °C. Throughout the study period (2022-2025), oxygen conditions remained dynamic and frequently unstable. Dissolved oxygen reached maximum levels during the winters of 2024 (14.9 mg/L) and 2025 (16 mg/L). As expected, DO concentrations decreased toward the summer months, reaching a minimum of 4.4 mg/L in summer 2023. Oxygen saturation (OS%) recorded its minimum in January 2022 (69.1%) and peak levels in March 2023 (159.9%) and March 2025 (152%). Absolute maximum for chlorophyll-a (76.19 mg/m³), five- day biochemical oxygen demand BOD 5 (10.3 mg/L), and dissolved oxygen (15.96 mg/L) coincided with this saturation peak, clearly indicating phytoplankton blooms. Nutrient concentrations varied widely across the study period. Phosphate phosphorus and total phosphorus shared a common pattern, reaching minimum values in autumn 2022 and maximum values in summer 2025. Dissolved silicate peaked in July 2025 before dropping to its minimum in September, whereas inorganic nitrogen species exhibited no distinct seasonal trend. The annual ecological status assessment was conducted using reference values for OS%, DO, BOD 5, N-NH4, N-NO2, N-NO3 and P-PO4 across the seasons and categories specified in Regulation No. H‑4/14.09.2012 (rev. 2023) on the characterization of surface waters. An adapted approach for applying the classification system to assess physicochemical quality elements in the "coastal marine waters" category, developed by IO-BAS, was utilized. The ecological status of the site based on physicochemical quality elements for the studied period 2022–2025 is Moderate. This assessment is confirmed by the chlorophyll-a data, for which categories outside of "good" and "high" account for 55–76% of all measurements. The trophic status assessment was performed using the Trophic Index - TRIX (Vollenweider et al. 1998), whose values range between 2.38 and 8.92 (mean 5 ± 1.23). The results indicate moderate to high anthropogenic nutrient loading, accompanied by oxygen supersaturation and phytoplankton blooms. Over the period under review (2022–2025), an increasing trend in the trophic index is observed, confirming the site's vulnerability to local anthropogenic sources and climate fluctuations, and defining the area as a coastal zone hotspot. The analysis of the in-situ platform data and the trend in laboratory test results correlate, underscoring the appropriateness of selecting the Galata site for monitoring. Beyond contributing to long-term ecological research, the monitoring results emphasize the need for enhanced control of coastal runoff and anthropogenic pressure in the area.