Massive Cell-by-Cell Phytoplankton Dataset Opens a Window on Europe’s Vanishing Lagoons

Hidden inside the murky waters of coastal lagoons lies one of the planet’s most consequential communities of organisms. Phytoplankton, the microscopic photosynthetic drifters that form the base of nearly every aquatic food web, are responsible for roughly forty percent of global primary production, and their fortunes rise and fall with the salinity, nutrients, and temperature of the water around them. Now, after nearly two decades of dormancy, a treasure trove of measurements from some of Europe’s most fragile and forgotten ecosystems has been rescued, standardized, and released to the world in unprecedented detail.

A team of researchers working within European research infrastructure projects has published a harmonized, individual-level dataset of phytoplankton traits collected from fourteen transitional water sites across the Mediterranean and Black Sea regions. Spanning Albania, Bulgaria, Greece, Italy, and Romania, the dataset contains 104,687 individual records covering 242 accepted taxa distributed across ten phyla, twenty-two classes, sixty-seven orders, one hundred families, and one hundred thirty-six genera. Crucially, the data were collected not just at the species level, as most trait databases are, but cell by cell, capturing the fine-grained variation within populations that ecologists increasingly recognize as essential for understanding how communities respond to environmental change.

Transitional waters, the dynamic ecosystems perched at the boundary between rivers and seas, are among the most variable and vulnerable habitats on Earth. Their salinity, nutrient loads, and hydrology fluctuate dramatically with freshwater inputs, tidal exchange, climatic variability, and human activity. The lagoons in this study, from Alimini and Torre Guaceto in southern Italy to Varna Bay in Bulgaria and Sinoe lagoon in Romania, are microtidal or non-tidal, nutrient-rich, depositional systems that experience intense anthropogenic pressure while simultaneously hosting remarkable biodiversity. Understanding how phytoplankton communities organize themselves across such steep environmental gradients is a central question in functional ecology, and it requires data of a kind that has been notoriously difficult to find.

The original sampling took place during two coordinated campaigns, in October 2004 and April 2005, conducted under the INTERREG IIIB CADSES TWReference Net Project coordinated by Prof. Alberto Basset and funded by the European Union’s Seventh Framework Programme. At each lagoon, between one and seven sampling stations were established according to a hierarchical design meant to capture both seasonal and spatial variability. Researchers collected water from a depth of half a meter using a Ruttner bottle, preserved samples in Lugol’s iodine solution, and stored them in darkness at four degrees Celsius until analysis. Physicochemical conditions, including temperature, salinity, pH, and dissolved oxygen, were measured in situ with a multiparametric probe, while nutrient samples were processed immediately upon arrival at the laboratory using standard methods.

The laboratory work is where the dataset acquires its unusual power. Following the classical Utermöhl method, subsamples were examined under an inverted Nikon T300E microscope at four hundred times magnification. For each sample, a minimum of four hundred cells were counted, measured, and identified to the lowest possible taxonomic level, ensuring statistically robust estimates of both community composition and cell dimensions. Each cell was assigned to one of twenty-four geometric shapes, from simple spheres and cubes to composite forms such as a cone paired with a half sphere, and its linear dimensions were recorded. These measurements fed into geometric equations that calculate biovolume, which was then converted into individual carbon content using the widely cited equations of Menden-Deuer and Lessard, and into biomass using a conversion factor of 1.03.

The resulting picture of phytoplankton life in these lagoons is strikingly region-dependent. By density, Chlorophyta, the green algae, dominated the dataset at 37.39 percent of total abundance, followed by Cyanobacteria at 23.58 percent and Cryptista at 15.12 percent. But biomass tells a very different story: Dinoflagellata contributed the largest share at 36.29 percent, followed by Heterokontophyta, the group containing diatoms, at 20.08 percent. This discrepancy reflects a fundamental ecological truth, that large-celled groups such as dinoflagellates and diatoms punch far above their numerical weight when it comes to carbon and energy flowing through the food web. Counting cells alone would badly misrepresent the functional structure of these communities.

Geographic contrasts were equally revealing. Mediterranean lagoons hosted communities with richness values typically between twenty-three and forty-nine taxa, whereas Black Sea lagoons were richer, ranging from forty-six to seventy-nine taxa, with the highest diversity observed in Varna. Mediterranean communities were more evenly distributed, with alternating dominance of Cryptista, Cyanobacteria, and Chlorophyta in density terms, while Black Sea systems, particularly Sinoe and Varna, showed stronger dominance by cyanobacteria and dinoflagellates, especially when biomass was considered. Shannon diversity values based on density ranged from 0.56 to 2.56 across lagoons, indicating substantial differences in community evenness from one system to the next.

Even cell shape itself carries an ecological signal. Across the whole dataset, cube-shaped cells accounted for 19.3 percent of total density and cylindrical cells 19.2 percent, together making up nearly forty percent of all individuals counted. Shape composition differed sharply between the two seas: the cone-plus-half-sphere morphology dominated Mediterranean sites at 43.8 percent of cell density, while cylindrical forms, associated with genera such as Cyclotella, Anabaena, and Planktolyngbya, and cube-shaped cells, represented mainly by Merismopedia and Crucigenia, predominated in the Black Sea. Grouped by geometric complexity, simple shapes accounted for roughly seventy-two percent of total density overall, but the balance shifted between regions, with simple shapes reaching 78.0 percent of mean relative density in Black Sea sites compared with a more even 50.8 percent split in the Mediterranean.

What elevates this dataset beyond a simple archive is the extraordinary effort devoted to making the data genuinely interoperable and reusable, compliant with the FAIR principles of findability, accessibility, interoperability, and reusability. The phytoplankton records are accompanied by a complementary abiotic dataset containing in situ measurements of salinity, conductivity, temperature, pH, dissolved oxygen, oxygen saturation, and total dissolved solids, along with nutrient concentrations including nitrite, nitrate, ammonium, dissolved inorganic nitrogen, phosphate, and silicate. Physiographic and hydrological characteristics of each lagoon, such as water depth, tidal range, inlet morphology, sinuosity index, surface area, and hydrological connectivity, are included alongside qualitative descriptors of anthropogenic pressure and protection status, including Ramsar designation, Natura 2000 site membership, and local protection plans.

The curation pipeline drew on an impressive array of controlled vocabularies and standards. Data were organized using the Data Template Builder tool of the Phytoplankton Virtual Research Environment, incorporating concepts from Darwin Core standards, the Traits Thesaurus, MarineRegions, EnvThes, and NERC vocabularies to generate semantically consistent data tables. Taxonomic validation was performed against the AlgaeBase repository, with both the original identification and the accepted name preserved in the dataset through dedicated Darwin Core properties, ensuring traceability. Morphological shape assignments were verified using the Atlas of Shapes web service, and trait computation was automated through a dedicated Python-based e-service. The dataset has already served as a reference case for harmonization and trait-based integration within the Phyto VRE and has underpinned previously published studies on morpho-functional analysis, guild classification, and hypothesis testing across multiple levels of biological organization.

Archived in comma-separated value format with metadata in the Ecological Metadata Language 2.2.0 standard, the two datasets are openly accessible through the LifeWatch Italy Data Portal and Metadata Catalogue under a Creative Commons Attribution 4.0 licence. For researchers studying functional diversity, trait-environment relationships, or the ecology of coastal ecosystems under mounting human pressure, the resource represents something rare: a standardized, cell-level record spanning five countries, two seas, and a full spectrum of environmental gradients. As transitional waters face intensifying eutrophication, hydrological alteration, and climate-driven change, having a decade-spanning, taxonomically validated, individually measured baseline from these vulnerable lagoons may prove invaluable, not only for charting what has been lost, but for predicting what these ecosystems, and the microscopic engines at their heart, will become.

Subject of Research: Individual-level phytoplankton trait data from Mediterranean and Black Sea transitional waters

Article Title: A harmonized individual-level phytoplankton trait dataset from Mediterranean and Black Sea transitional waters

Article References: Titocci, J., Laraib, M., Semeraro, T., & Basset, A. (2026). A harmonized individual-level phytoplankton trait dataset from Mediterranean and Black Sea transitional waters. Biodiversity Data Journal, 14, Article e196603. https://doi.org/10.3897/bdj.14.e196603

Image Credits: AI Generated

DOI: 10.3897/BDJ.14.e196603

Keywords: phytoplankton, trait-based ecology, transitional waters, coastal lagoons, Mediterranean Sea, Black Sea, FAIR data, biovolume, functional diversity, biodiversity data, cyanobacteria, dinoflagellates