Implementation of the Water Framework Directive: Lessons Learned and Future Perspectives for an Ecologically Meaningful Classification Based on Phytoplankton of the Status of Greek Lakes, Mediterranean Region

Use of Unmanned Surface Vehicles (USVs) in Water Chemistry Studies

Unmanned surface vehicles (USVs) equipped with integrated sensors are a tool valuable to several monitoring strategies, offering enhanced temporal and spatial coverage over specific timeframes, allowing for targeted examination of sites or events of interest. The elaboration of environmental monitoring programs has relied so far on periodic spot sampling at specific locations, followed by laboratory analysis, aiming at the evaluation of water quality at a catchment scale. For this purpose, automatic telemetric stations for specific parameters have been installed by the Institute of Marine Biological Resources and Inland Waters of Hellenic Centre for Marine Research (IMBRIW-HCMR) within several Greek rivers and lakes, providing continuous and temporal monitoring possibilities. In the present work, USVs were deployed by the Athens Water and Sewerage Company (EYDAP) as a cost-effective tool for the environmental monitoring of surface water bodies of interest, with emphasis on the spatial fluctuations of chlorophyll α, electrical conductivity, dissolved oxygen and pH, observed in Koumoundourou Lake and the rivers Acheloos, Asopos and Kifissos. The effectiveness of an innovative heavy metal (HM) system installed in the USV for the in situ measurements of copper and lead was also evaluated herewith. The results obtained demonstrate the advantages of USVs, setting the base for their application in real-time monitoring of chemical parameters including metals. Simultaneously, the requirements for accuracy and sensitivity improvement of HM sensors were noted, in order to permit full exploitation of USVs' capacities.

Assessing the relevance of DNA metabarcoding compared to morphological identification for lake phytoplankton monitoring

Phytoplankton is a key biological group used to assess the ecological status of lakes. The classical monitoring approach relies on microscopic identification and counting of phytoplankton species, which is time-consuming and requires high taxonomic expertise. High-throughput sequencing, combined with metabarcoding, has recently demonstrated its potential as an alternative approach for plankton surveys. Several studies have confirmed the relevance of the diatom metabarcoding approach to calculate biotic indices based on species ecology. However, phytoplankton communities have not yet benefited from such validation. Here, by comparing the results obtained with the two methods (molecular and microscopic counting), we evaluated the relevance of metabarcoding approach for phytoplankton monitoring by considering different metrics: alpha diversity, taxonomic composition, community structure and a phytoplankton biotic index used to assess the trophic level of lakes. For this purpose, 55 samples were collected in four large alpine lakes (Aiguebelette, Annecy, Bourget, Geneva) during the year 2021. For each sample, a metabarcoding analysis based on two genetic markers (16S and 23S rRNA) was performed, in addition to the microscopic count. Regarding the trophic level of lakes, significant differences were found between index values obtained with the two approaches. The main hypothesis to explain these differences comes from the incompleteness, particularly at the species level, of the barcode reference library for the two genetic markers. It is therefore necessary to complete reference libraries for using such species-based biotic indices with metabarcoding data. Besides this, species richness and diversity were higher in the molecular inventories than in the microscopic ones. Moreover, despite differences in taxonomic composition of the floristic lists obtained by the two approaches, their community structures were similar. These results support the possibility of using metabarcoding for phytoplankton monitoring but in a different way. We suggest exploring alternative approaches to index development, such as a taxonomy-free approach.

Air-dispersed aquatic microorganisms show establishment and growth preferences in different freshwater colonisation habitats

We attempted to mimic aeolian ecosystems to examine how filters posed by regional characteristics can influence the establishment and growth of airborne microcolonisers of a common air source. Using a natural single source of aerosols we applied a combined microscopy and high-throughput sequencing approach to examine the diversity, settling and growth potential of air-dispersed microbes in water containers representing newly formed aquatic colonisation habitats of different trophic states and salinity. Heterotrophic microeukaryotes were favoured as initial settlers when nutrients were low, while autotrophs rapidly proliferated in the high-nutrient containers, possibly due to favourable germinating conditions for their preferred mode of dispersal with resting spores. Following settling of colonisers, we investigated two contrasting hypotheses: if the different water colonisation habitats harboured the same microbial communities after establishment and growth periods, this would point towards a selection of best-fit cosmopolitan colonisers, regardless of habitat-specific characteristics. Alternatively, community dissimilarities after the growth period would suggest a selection of settlers due to bottom-up controls combined with priority effects. Both analyses suggested that the structure of the microbial communities in the different colonisation habitats were driven by nutrient content and salinity, showing clustering to similar bottom-up forces and dissimilarities in significantly different colonisation habitats.

Modelling Freshwater Eutrophication with Limited Limnological Data Using Artificial Neural Networks

Artificial Neural Networks (ANNs) have wide applications in aquatic ecology and specifically in modelling water quality and biotic responses to environmental predictors. However, data scarcity is a common problem that raises the need to optimize modelling approaches to overcome data limitations. With this paper, we investigate the optimal k-fold cross validation in building an ANN using a small water-quality data set. The ANN was created to model the chlorophyll-a levels of a shallow eutrophic lake (Mikri Prespa) located in N. Greece. The typical water quality parameters serving as the ANN’s inputs are pH, dissolved oxygen, water temperature, phosphorus, nitrogen, electric conductivity, and Secchi disk depth. The available data set was small, containing only 89 data samples. For that reason, k-fold cross validation was used for training the ANN. To find the optimal k value for the k-fold cross validation, several values of k were tested (ranging from 3 to 30). Additionally, the leave-one-out (LOO) cross validation, which is an extreme case of the k-fold cross validation, was also applied. The ANN’s performance indices showed a clear trend to be improved as the k number was increased, while the best results were calculated for the LOO cross validation as expected. The computational times were calculated for each k value, where it was found the computational time is relatively low when applying the more expensive LOO cross validation; therefore, the LOO is recommended. Finally, a sensitivity analysis was examined using the ANN to investigate the interactions of the input parameters with the Chlorophyll-a, and hence examining the potential use of the ANN as a water management tool for nutrient control.

Advancing Knowledge on Cyanobacterial Blooms in Freshwaters

Cyanobacterial blooms have become a frequent phenomenon in freshwaters worldwide; they are a widely known indicator of eutrophication and water quality deterioration. Information and knowledge contributing towards the evaluation of the ecological status of freshwaters, particularly since many are used for recreation, drinking water, and aquaculture, is valuable. This Special Issue, entitled “Advancing Knowledge on Cyanobacterial Blooms in Freshwaters”, includes 11 research papers that will focus on the use of complementary approaches, from the most recently developed molecular-based methods to more classical approaches and experimental and mathematical modelling regarding the factors (abiotic and/or biotic) that control the diversity of not only the key bloom-forming cyanobacterial species, but also their interactions with other biota, either in freshwater systems or their adjacent habitats, and their role in preventing and/or promoting cyanobacterial growth and toxin production.

Effects of Harmful Blooms of Large-Sized and Colonial Cyanobacteria on Aquatic Food Webs

Cyanobacterial blooms are the most important and best studied type of harmful algal blooms in fresh waters and brackish coastal seas. We here review how and to which extent they resist grazing by zooplankton, how zooplankton responds to cyanobacterial blooms and how these effects are further transmitted to fish. Size, toxicity and poor nutritional value are widespread mechanisms of grazing defense by cyanobacteria. In some cases, defenses are inducible, in some they are obligate. However, to some extent zooplankton overcome grazing resistance, partly after evolutionary adaptation. Cyanotoxins are also harmful to fish and may cause fish kills. However, some fish species feed on Cyanobacteria, are able to reduce their abundance, and grow on a cyanobacterial diet. While reduced edibility for crustacean zooplankton tends to elongate the food chain from primary producers to fish, direct feeding by fish tends to shorten it. The few available comparative studies relating fish yield to nutrients or phytoplankton provide no indication that cyanobacteria should reduce the ratio fish production: primary production.

Patterns in Alpha and Beta Phytoplankton Diversity along a Conductivity Gradient in Coastal Mediterranean Lagoons

Understanding the diversity patterns of phytoplankton assemblages in coastal lagoons is clearly important for water management. In this study, we explored alpha and beta diversity patterns in phytoplankton communities across five Mediterranean lagoons hydrologically connected to Vistonikos Gulf. We examined the phytoplankton community composition and biomass on a monthly basis from November 2018 to October 2019. For this, water samples were collected from seven inshore, brackish and coastal waters, sampling sites covering a wide range of conductivity. We found significant spatial and temporal differences in phytoplankton alpha diversity and in phytoplankton biomass metrics explained by the high variation of conductivity. Evenness remained low throughout the study period, reflecting significant dominance of several phytoplankton blooms. Harmful algal blooms of Prorocentrum minimum, Alexandrium sp., Rhizosolenia setigera and Cylindrotheca closterium occurred. The system’s species pool was characterized by relatively high phytoplankton beta diversity (average ~0.7) resulting from high temporal species turnover (90%). Overall, alpha and beta diversity components were indicative of rather heterogeneous phytoplankton communities which were associated with the high differences in conductivity among the sampling sites.

Ecological Connectivity in Two Ancient Lakes: Impact Upon Planktonic Cyanobacteria and Water Quality

The ancient lakes Mikri Prespa and Megali Prespa are located in SE Europe at the transnational triangle and are globally recognized for their ecological significance. They host hundreds of flora and fauna species, and numerous types of habitat of conservational interest. They also provide a variety of ecosystem services. Over the last few decades, the two lakes have been interconnected through a surface water channel. In an attempt to explore whether such a management practice might alter the ecological properties of the two lakes, we investigated a series of community metrics for phytoplankton by emphasizing cyanobacteria. Our results demonstrate that the cyanobacterial metacommunity structure was affected by directional hydrological connectivity and high dispersal rates, and to a lesser extent, by cyanobacterial species sorting. Cyanobacterial alpha diversity was twofold in the shallow upstream Lake Mikri Prespa (Simpson index average value: 0.70) in comparison to downstream Lake Megali Prespa (Simpson index average value: 0.37). The cyanobacterial assemblage of the latter was only a strict subset of that in Mikri Prespa. Similarly, beta diversity components clearly showed a homogenization of cyanobacteria, supporting the hypothesis that water flow enhances fluvial translocation of potentially toxic and bloom-forming cyanobacteria. Degrading of the water quality in the Lake Megali Prespa in anticipation of improving that of the Lake Mikri Prespa is an issue of great concern for the Prespa lakes’ protection and conservation.