Lakes Of Greece Research Articles

A Certain Kind of Freedom

Άφρικα: A Certain Kind of Freedom is pivoting on artistic exploration and re-interpretation of a 'difficult' recent past. In part soundwalk, in part performance art, in part punk archaeology, in part getting lost in the dark; the work is a nocturnal rumination bringing together historical bewilderedness with first-person embodied experience of a place. The artist leads a night walk towards and inwards Agios Achillios island in Small Prespa Lake in Greece – near the borders of Albania, and North Macedonia – and back. En route, the walking audience is exposed to wildlife sounds and animal vocalisations, to orchestrated drama, and to historical records directly or indirectly concerning the broader geographical area and its significance during the Greek civil war.

Does littoral substrate affect macroinvertebrate assemblages in Mediterranean lakes?

The objective of this study was to investigate the effects of substrate type in macroinvertebrate assemblages in Mediterranean lakes. Samplings have taken place in the littoral zone of 21 lakes in Greece, between 2015 and 2018. We compared benthic macroinvertebrate assemblages among three substrate types of their littoral zones; sandy, covered with macrophytes and stony substrate. Benthic macroinvertebrate assemblages at sites with extended macrophyte cover differed only slightly in composition and abundance from the ones found in stony and sandy substrates. Coenagrionidae were indicative of sites covered with macrophytes and Oligochaeta and Erpobdellidae were representative of stony substrates. The type of substrate proved to be a statistically significant factor influencing the number of benthic macroinvertebrate taxa, the relative abundance of Oligochaeta and the relative abundance of Odonata. In the context of designing site-adapted management measures, priority could be given to the conservation and restoration of aquatic vegetation in lake littoral zones, which host rich macroinvertebrate assemblages with abundant taxa of Odonata.

Development of novel diatom metrics to assess ecological status of phytobenthos in Greek lakes

Mediterranean lakes present particular challenges when developing ecological assessment techniques, due partly to long histories of human activity in their catchments but also to strong interactions with climate, intensifying in recent decades due to global warming. A survey of diatoms in lakes in Greece revealed both a strong nutrient gradient and a salinity gradient. It is necessary to disentangle these when assessing ecological status in order that appropriate measures for restoring good ecological status are applied. Two approaches were used to develop a Water Framework Directive-compatible metric for assessing ecological status using diatoms. The strongest relationship was obtained using weighted averaging, but an alternative metric, generated by rescaling a well-established and widely used diatom metric performed only slightly less well. The limited number of lakes in Greece resulted in a small dataset, creating a risk of overfitting models and the rescaled metric has the advantage of drawing on a broader autecological knowledge base. Supplementary metrics to evaluate salinity are also proposed in order to ensure that lakes subject to this pressure are clearly differentiated from those where nutrient impacts predominate. Approaches to defining reference conditions and status class boundaries draw on established criteria developed for Water Framework Assessments in Europe to ensure that status assessments in Greece reflect similar levels of ambition to those established elsewhere in the European Union.

Deep Learning in Water Resources Management: Τhe Case Study of Kastoria Lake in Greece

The effects of climate change on water resources management have drawn worldwide attention. Water quality predictions that are both reliable and precise are critical for an effective water resources management. Although nonlinear biological and chemical processes occurring in a lake make prediction complex, advanced techniques are needed to develop reliable models and effective management systems. Artificial intelligence (AI) is one of the most recent methods for modeling complex structures. The applications of machine learning (ML), as a part of AI, in hydrology and water resources management have been increasing in recent years. In this paper, the ability of deep neural networks (DNNs) to predict the quality parameter of dissolved oxygen (DO), in Lake Kastoria, Greece, is tested. The available dataset from 11 November 2015, to 15 March 2018, on an hourly basis, from four telemetric stations located in the study area consists of (1) Chl-a (μg/L), (2) pH, (3) temperature—Tw (°C), (4) conductivity (μS/cm), (5) turbidity (NTU), (6) ammonia (NH4, mg/L), (7) nitrate nitrogen (N–NO3, mg/L), and (8) dissolved oxygen (DO) (mg/L). Feed-forward deep neural networks (FF-DNNs) of DO, with different structures, are tested for all stations. All the well-trained DNNs give satisfactory results. The optimal selected FF-DNNs of DO for each station with a high efficiency (NSE > 0.89 for optimal selected structures/station) constitute a good choice for modeling dissolved oxygen. Moreover, they provide information in real time and comprise a powerful decision support system (DSS) for preventing accidental and emergency conditions that may arise from both natural and anthropogenic hazards.

Assessing the Fisheries and Ecosystem Structure of the Largest Greek Lake (Lake Trichonis)

An Ecopath with Ecosim (EwE) modeling approach was used to explore the ecological structure of the largest lake in Greece (Lake Trichonis). Until the mid-1990s, the lake was receiving a high level of pollution and the fishing pressure was intense, while since the early 2000s, fisheries and other human pressures gradually declined. Nowadays, the lake’s fisheries mainly target Atherina boyeri due to the absence of market demand for the other fish species in the lake, resulting in a low overall fisheries pressure on the fish stocks. The model was built with data collected through: (a) field samplings, (b) in-depth targeted interviews of professional fishermen and (c) historical archive information. The model considered 22 functional groups, while fishing activities were represented by three classes according to the used gears. The outputs of the model revealed that the ecosystem is dominated by low trophic level species (also identified as keystone species), indicating the significance of bottom-up control in the regulation of food web processes. Ecological indicators depicted that the lake’s ecosystem is mature and resilient to external disturbances. The methodological approach used in this study was shown to be helpful for studies addressing ecosystem structure, in particular with limited data availability.

Mass mortality of unknown etiology in alpine newts (Ichtyosaura alperstris veluchiensis) in an alpine lake in Greece

A mass mortality in alpine newts (Ichthyosaura alpestris veluchiensis) was observed in May/June 2013, in Drakolimni lake on Smolikas Mountain, Northwest Greece. 1300 alpine newts were found dead in two events. In 1998 a similar incident was recorded in the nearby lake of Timfi Mt. Newts of every stage and sex were affected, presenting incoordination and inability to float evenly. Ten animals were submitted for complete pathological examination. Field environmental measurements (water temperature, oxygen saturation, pH, conductance, nitric/phosphate concentration) and samples (water, snow, benthos) were collected for ecotoxicological and quality analysis. Necropsy, microbiology (parasitology, bacteriology, mycology), histopathology, molecular investigations (Ranavirus spp, Batrachochytridium dendrobatidis, Batrachochytridium salamandrivorans), quality and ecotoxicological examinations did not indicate a causative source for the mortality. To the author´s knowledge this is the biggest mortality of unknown etiology reported in free-living alpine newts in Europe.

Production, Validation and Morphometric Analysis of a Digital Terrain Model for Lake Trichonis Using Geospatial Technologies and Hydroacoustics

Covering an area of approximately 97 km2 and with a maximum depth of 58 m, Lake Trichonis is the largest and one of the deepest natural lakes in Greece. As such, it constitutes an important ecosystem and freshwater reserve at the regional scale, whose qualitative and quantitative properties ought to be monitored. Depth is a crucial parameter, as it is involved in both qualitative and quantitative monitoring aspects. Thus, the availability of a bathymetric model and a reliable DTM (Digital Terrain Model) of such an inland water body is imperative for almost any systematic observation scenario or ad hoc measurement endeavor. In this context, the purpose of this study is to produce a DTM from the only official cartographic source of relevant information available (dating back approximately 70 years) and evaluate its performance against new, independent, high-accuracy hydroacoustic recordings. The validation procedure involves the use of echosoundings coupled with GPS, and is followed by the production of a bathymetric model for the assessment of the discrepancies between the DTM and the measurements, along with the relevant morphometric analysis. Both the production and validation of the DTM are conducted in a GIS environment. The results indicate substantial discrepancies between the old DTM and contemporary acoustic data. A significant overall deviation of 3.39 ± 5.26 m in absolute bottom elevation differences and 0.00 ± 7.26 m in relative difference residuals (0.00 ± 2.11 m after 2nd polynomial model corrector surface fit) of the 2019 bathymetric dataset with respect to the ~1950 lake DTM and overall morphometry appear to be associated with a combination of tectonics, subsidence and karstic phenomena in the area. These observations could prove useful for the tectonics, geodynamics and seismicity with respect to the broader Corinth Rift region, as well as for environmental management and technical interventions in and around the lake. This dictates the necessity for new, extensive bathymetric measurements in order to produce an updated DTM of Lake Trichonis, reflecting current conditions and tailored to contemporary accuracy standards and state-of-the-art research in various disciplines in and around the lake.

Application of Non-Destructive Techniques on a Varve Sediment Record from Vouliagmeni Coastal Lake, Eastern Gulf of Corinth, Greece

During the last few decades, X-ray attenuation systems have been established as standard techniques in geosciences and as excellent scientific tools for the analysis of sedimentary facies and structures. In the present study, we use two non-destructive and high-resolution systems (computed tomography, X-ray fluorescence) to address all sedimentological facies and structural characteristics on a 6 m long, partly laminated sediment record, from Vouliagmeni lake, located at the eastern part of the Corinth Gulf, Greece. Vouliagmeni lake is the deepest coastal lake in Greece, and its location is of great importance since it is located in one of the most tectonically active regions in the world. The chronological framework of the retrieved sediment sequence spans the last 12,000 years, with alternations of laminated and non-laminated sections. The annual accumulation of the laminated sequences was determined through the radionuclide concentration of 14 samples. Scanning tomography was performed with a medical CT scanner and a μCT scanner, aiming to compare the potentials and variations of both methods. Lamination boundaries, event layers (turbidites) and sediment deformations were distinguished through processing the extracted 3D rendered volumes, after applying ranges depending on Hounsfield (HU) values. Microscopic analysis revealed three main layer types in the varve sequences that were examined, attributing to summer/spring, autumn and winter deposits. Statistical analysis of the elemental composition, magnetic susceptibility (MS) measurements and HU values revealed three clusters/facies, reflecting climatic and in-lake hydrological changes. Cluster A emulates sedimentation during arid conditions, while Cluster B reflects humid conditions with increased precipitation and erosion. Cluster C represents sequences with homogenous Ca-rich sediment. Our proposed workflow highlights the possible correlation between the non-destructive variables that were measured, but also the variations and applications of each method and software used during this study.

A 2600-year high-resolution climate record from Lake Trichonida (SW Greece)

Abstract. This paper aims at reconstructing the palaeoclimatic changes during the last 2600 years in southern Greece based on a proxy record from Lake Trichonida. For the first time, we provide a reliable age-depth model and continuous geochemical data for the largest and deepest lake in Greece. We use X-ray fluorescence (XRF) geochemical data supported by discrete mineral analysis based on X-ray diffraction (XRD), grain size distribution, and organic matter content to investigate changes in the lake sedimentary system and identify the major forcing mechanisms. A principal component analysis based on the XRF geochemical composition identifies the variation between carbonate-rich material, precipitating predominantly under drier and/or warmer conditions, and terrigenous sediment input, with it being more prominent during wetter and/or colder conditions. The first principal component (PC1) shows a very strong correlation with the weathering proxy log (Rb∕Sr), and we interpret both proxies as depicting fluctuations in the hydrological conditions. A cluster analysis, conducted on the continuous geochemical and colour parameters, highlights the similarities in the sediment characteristics deposited during wetter phases, notably during 1850–1750, 1500–1400, ca. 1100, and ca. 100 cal BP. When comparing the PC1 Trichonida record to independent records from the Balkans, we find generally concurring patterns on a multi-decadal to centennial scale. We show that phases with wetter conditions at Lake Trichonida coincide with a more negative North Atlantic Oscillation (NAO) index, suggesting that the precipitation variability in southern Greece is linked to changes in the NAO atmospheric pattern, as one major driving force. The 2600-year-long sedimentary record of Lake Trichonida contributes to a better understanding of Late Holocene palaeohydrological changes in an important climatic transitional zone in the eastern Mediterranean.

A phytosociological survey of aquatic vegetation in the main freshwater lakes of Greece

Aims: This study aims to contribute to the knowledge of European freshwater lake ecosystems with updated and new information on aquatic plant communities, by conducting national-scale phytosociological research of freshwater lake vegetation in Greece. Moreover, it investigates the relationship between aquatic plant communities and lake environmental parameters, including eutrophication levels and hydro-morphological conditions.Study area: Lakes in Greece, SE Europe.Methods: 5,690 phytosociological relevés of aquatic vegetation were sampled in 18 freshwater lake ecosystems during 2013–2016. The relevés were subjected to hierarchical cluster and indicator species analyses in order to identify associations and communities of aquatic vegetation, as well as to describe their syntaxonomy. Multiple regression analysis was applied to investigate the relationship between vegetation syntaxa and environmental parameters of lakes, i.e. physico-chemical parameters and water level fluctuation.Results: Ninety-nine plant taxa belonging to 30 different families were recorded. Forty-six vegetation types were identified and described by their ecological characteristics, diagnostic taxa and syntaxonomical status. Thirteen vegetation types, the largest number belonging to the vegetation classCharetea, are considered to be new records for Greece. The distribution of the vegetation types recorded in the 18 freshwater lakes was found to depend on environmental parameters and levels of eutrophication.Conclusions: An updated aquatic vegetation inventory was produced for Greek lakes, and primary results showed that the presence/absence of aquatic plant communities and the community composition in freshwater lakes can be utilized to assess the pressure of eutrophication on lake ecosystems.Taxonomic reference: Euro+Med (2006–).Abbreviations: MNT = Mean number of taxa; WFD = Water Framework Directive.

Short-term water quality variable prediction using a hybrid CNN–LSTM deep learning model

Water quality monitoring is an important component of water resources management. In order to predict two water quality variables, namely dissolved oxygen (DO; mg/L) and chlorophyll-a (Chl-a; µg/L) in the Small Prespa Lake in Greece, two standalone deep learning (DL) models, the long short-term memory (LSTM) and convolutional neural network (CNN) models, along with their hybrid, the CNN–LSTM model, were developed. The main novelty of this study was to build a coupled CNN–LSTM model to predict water quality variables. Two traditional machine learning models, support-vector regression (SVR) and decision tree (DT), were also developed to compare with the DL models. Time series of the physicochemical water quality variables, specifically pH, oxidation–reduction potential (ORP; mV), water temperature (°C), electrical conductivity (EC; µS/cm), DO and Chl-a, were obtained using a sensor at 15-min intervals from June 1, 2012 to May 31, 2013 for model development. Lag times of up to one (t − 1) and two (t − 2) for input variables pH, ORP, water temperature, and EC were used to predict DO and Chl-a concentrations, respectively. Each model’s performance in both training and testing phases was assessed using statistical metrics including the correlation coefficient (r), root mean square error (RMSE), mean absolute error (MAE), their normalized equivalents (RRMSE, RMAE; %), percentage of bias (PBIAS), Nash–Sutcliffe coefficient ($$E_{NS}$$), Willmott’s Index, and graphical plots (Taylor diagram, box plot and spider diagram). Results showed that LSTM outperformed the CNN model for DO prediction, but the standalone DL models yielded similar performances for Chl-a prediction. Generally, the hybrid CNN–LSTM models outperformed the standalone models (LSTM, CNN, SVR and DT models) in predicting both DO and Chl-a. By integrating the LSTM and CNN models, the hybrid model successfully captured both the low and high levels of the water quality variables, particularly for the DO concentrations.

Integrated hydrological modelling of surface water and groundwater under climate change: the case of the Mygdonia basin in Greece

Abstract Lakes Volvi and Koronia are located in the Mygdonia basin and constitute the second and fifth largest natural lakes in Greece, respectively. The lakes along with the Mygdonia basin aquifer have undergone severe quantitative and qualitative degradation, while Lake Koronia has been totally depleted in recent years. In this study, a fully integrated hydrological analysis of the Mygdonia basin for historical and future periods is carried out. Future climatic data were derived and analyzed from a Regional Climate Model, while the implications of climate change on the water balance of both lakes and the Mygdonia basin aquifer until 2100 were projected by developing a modelling system which includes coupled hydrological and hydraulic models, such as UTHBAL, MIKE SHE, MIKE HYDRO River and the MIKE HYDRO Basin. The results indicated that the precipitation is expected to decrease by 17%, the temperature to increase by 2.90 °C and as a result, the surface runoff is projected to decrease by 21% and the groundwater recharge to decrease by 38% in the Mygdonia basin at the end of the century. The above changes would have a direct negative impact on the Lakes Koronia and Volvi and the Mygdonia basin aquifer future water balance necessitating adaptation measures.

Linkages between Macrophyte Functional Traits and Water Quality: Insights from a Study in Freshwater Lakes of Greece

Freshwater ecologists have shown increased interest in assessing biotic responses to environmental change using functional community characteristics. With this article, we investigate the potential of using functional traits of the aquatic plants to assess eutrophication in freshwater lakes. To this end we collected macrophyte and physicochemical data from thirteen lakes in Greece and we applied a trait-based analysis to first identify discrete groups of macrophytes that share common functional traits and then to assess preliminary responses of these groups to water quality gradients. We allocated 11 traits that cover mostly growth form and morphological characteristics to a total of 33 macrophyte species. RLQ and fourth corner analysis were employed to explore potential relationships between species, trait composition and environmental gradients. In addition, a hierarchical cluster analysis was conducted to discriminate groups of plants that share common trait characteristics and then the position of the groups along the environmental gradients was assessed. The results showed total phosphorus, chlorophyll-a, conductivity, pH and Secchi disk depth as main drivers of the environmental gradients. Hierarchical cluster analysis showed a clear separation of macrophyte assemblages with discrete functional characteristics that appeared to associate with different environmental drivers. Thus, rooted submerged plants were related with higher Secchi disk depth, conductivity and alkalinity whereas rooted floating-leaved plants showed a preference for enriched waters with phosphorus and nitrogen. In addition, free-floating plants were related positively with nitrogen and increased pH. Although we did not identify specific trait patterns with environmental drivers, our findings indicate a differentiation of macrophytes based on their functional characteristics along water quality gradients. Overall, the presented results are encouraging for conducting future monitoring studies in lakes focused on the functional plant trait composition, as expanding the current approach to additional lakes and using quantifiable functional characteristics will provide more insight about the potential of trait-based approaches as ecological assessment systems.

Exploring environmental predictors of aquatic macrophytes in water‐dependent Natura 2000 sites of high conservation value: Results from a long‐term study of macrophytes in Greek lakes

Abstract Aquatic macrophytes play a key role in lake dynamics, but human activities and eutrophication have resulted in macrophyte loss in many lakes throughout Europe. In this study, the relationships between aquatic macrophytes and gradients of environmental factors were explored using an extensive set of data collected from 13 lakes of the Greek mainland that are part of the European network Natura 2000. The main objectives were to assess the importance of key abiotic predictors and estimate possible environmental thresholds of macrophyte richness, diversity, and abundance using boosted regression trees (BRTs), as well as to explore further the distribution of dominant macrophyte taxa along environmental gradients. The results reveal conductivity as a significant predictor of macrophyte total cover and diversity. In addition, orthophosphate and nitrate nitrogen appear to play an important role for several macrophyte species and assemblages, reflecting a major effect of eutrophication on the distribution of taxa. The majority of macrophyte assemblages were found in waters characterized by high nutrient content, although their distribution extends along a wide range of phosphorus and nitrogen concentration. In contrast, charophyte species show the optimum of their distribution in clear, oligotrophic waters. This integrated study can be used for ranking environmental factors that influence macrophyte distribution in the lakes of Greece and for identifying taxa or macrophyte assemblages that can be used as effective indicators of changes in the abiotic environment. In addition, the results can contribute to the conservation of freshwater habitats in the protected areas studied. In particular, measures that aim to improve water quality are expected also to restore oligotrophic habitats that are characterized by benthic charophyte vegetation. Overall, the links between macrophyte assemblages and abiotic factors are critically important in improving freshwater biodiversity management and environmental policies in east Mediterranean lakes.

Evaluation of Water Quality Indices Adequacy in Characterizing the Physico-Chemical Water Quality of Lakes

The accurate and comprehensive characterization/classification of a water system presents a significant challenge. Over the last decades, a number of water quality indices (WQI) has been created and applied towards this goal. In most cases, the WQI is applied in characterizing the overall quality of a water system by integrating all available data, regardless of sampling station and time. This approach may result in misleading interpretation of data and wrong or ineffective policy responses to water quality deterioration. The present study investigates whether this approach is the most appropriate or if it is necessary to take into consideration the water quality of each individual sampling. Two natural lakes in Greece were chosen as case studies and an alternative to National Sanitation Foundation Water Quality Index was applied at each sampling site and at the overall water body. The use of the water quality index presented in this study is proved to be good practice in evaluating and characterizing the water quality of lakes as it can be easily adjusted to local specific conditions. The physico-chemical characterization of an aquatic system by water quality indices is preferable to be made only if the water quality indices, calculated for each individual sampling site, show homogeneity. The identification of the considered critical parameters, which significantly affect the quality of a water body, is of high importance in order to reduce the monitoring cost without influencing the reliability of the final result.

Erratum to: Influence of hydrophyte abundance on the spatial distribution of zooplankton in selected lakes in Greece

Erratum to: Influence of hydrophyte abundance on the spatial distribution of zooplankton in selected lakes in Greece

Implications of Human Activities, Land Use Changes and Climate Variability in Mediterranean Lakes of Greece

Lakes in the Mediterranean climate zone experience high variation in rainfall and are vulnerable to changes in climate, land cover and anthropogenically induced effects on water level and salinity. This paper presents the results from the analyses of spatiotemporal changes of land cover/uses at catchment scale of two connected lakes in Greece that have recently exhibited a dramatic loss of water volume, and investigates the potential role of climate change as a main driver of the lake water loss. The classification of the historical land cover/uses was based on a series of LANDSAT images from 1972 to 2011. Changes in the landscape structure were assessed using landscape metrics that were calculated with FRAGSTATS software. Climate data and temporal series of water level, conductivity and chloride concentration, were analyzed to investigate the potential role of climate variability to the lake hydrology and water quality. The results showed that between 1972 and 2011 almost 28% of Lake Vegoritis and 13% of Lake Petron were replaced by cultivations and reed beds. Landscape metrics showed that the lake catchment’s area is highly fragmented, indicating a heterogeneous spatial pattern and degradation of the rural habitats. Regarding the climatic factors, it appears that precipitation follows a declining trend correlating with water level fluctuations. The water level in Lake Vegoritis also correlated with the conductivity and chloride concentration, indicating a relationship between hydrological alteration and water quality. Overall, a combined effect of climate- and human-induced land cover changes appeared to be responsible for the drastic environmental changes that urge the need for implementing effective restoration and mitigation measures.

Assessing the Impact of Climate Change on Sediment Loads in a Large Mediterranean Watershed

Acheloos is the second longest and the largest, in terms of discharge, native river in Greece, supplying three hydroelectric dams along its route. The Kremasta dam, which forms the largest artificial lake in Greece, is the first dam fed by Acheloos and two other rivers. Sediment accumulation in such large reservoirs is of major concern, as it reduces storage capacity and hydropower production. In this study, the reservoir is utilized as a live record of constantly renewed sediment deposition data, which is used as a means of assessing the accumulated sediment loads originating from the watershed. The Soil and Water Assessment Tool model was combined with data from previous field surveys, which estimated the volume of deposited sediments in the reservoir. After modeling the discharge of three rivers into the Kremasta reservoir using available monthly field data from 1965 to 2001, the Soil and Water Assessment Tool was successfully calibrated against the deposited sediment mass data, accumulated at the reservoir during the first 34 years of its operation. Simulation results for a set of International Panel on Climate Change “A1B” climate change scenarios suggested a 14.6% decrease in the average rainfall on the watershed, between the 2016–2055 and 2056–2095 time periods, which induces a proportional (19.5%) decrease in flow and a milder (7.9%) decrease in the deposited sediment mass. It was also estimated that by the year 2100 the deposited sediment volume will occupy 6.1% of the effective volume of the reservoir, a value much lower than the estimated dead volume of the dam (17.4%).

Capturing biodiversity: linking a cyanobacteria culture collection to the "scratchpads" virtual research environment enhances biodiversity knowledge.

BackgroundCurrently, cyanobacterial diversity is examined using a polyphasic approach by assessing morphological and molecular data (Komárek 2015). However, the comparison of morphological and genetic data is sometimes hindered by the lack of cultures of several cyanobacterial morphospecies and inadequate morphological data of sequenced strains (Rajaniemi et al. 2005). Furthermore, in order to evaluate the phenotypic plasticity within defined taxa, the variability observed in cultures has to be compared to the range in natural variation (Komárek and Mareš 2012). Thus, new tools are needed to aggregate, link and process data in a meaningful way, in order to properly study and understand cyanodiversity.New informationAn online database on cyanobacteria has been created, namely the Cyanobacteria culture collection (CCC) (http://cyanobacteria.myspecies.info/) using as case studies cyanobacterial strains isolated from lakes of Greece, which are part of the AUTH culture collection (School of Biology, Aristotle University of Thessaloniki). The database hosts, for the first time, information and data such as morphology/morphometry, biogeography, phylogeny, microphotographs, distribution maps, toxicology and biochemical traits of the strains. All this data are structured managed, and presented online and are publicly accessible with a recently developed tool, namely “Scratchpads”, a taxon-centric virtual research environment allowing browsing the taxonomic classification and retrieving various kinds of relevant information for each taxon.

Influence of land use changes on alluviation of Volvi Lake wetland (North Greece)

The study deals with Volvi Lake, the second largest natural lake in Greece, where gradual alleviation and a land use change have taken place in the last 60 years. The aim of the study was to estimate the influence of land use changes of the area on sedimentation and alluviation rate. Due to the lack of sediment measurements the Gavrilovic model was used to calculate the mean annual erosion of the two main drainage basins of the Lake for 1945 and 2007. Field research, orthophotographs, and topographic maps dating from 1945, 1971, and 2007 were used to determine the evolution of the vegetation cover and lake shoreline, in order to compare and evaluate the Gavrilovic model results. An increase of 6% of the forested area in combination with the improvement of scrublands quality were enough to cause a 15% decrease of the mean annual sedimentation, according to the Gavrilovic model, as well as a 50% decrease in alluviation rate, according to delta change measurement, comparing the periods 1945-1971 and 1971-2007. The importance of vegetation for soil protection was clearly demonstrated, indicating that reducing the land use and enhancing the vegetation quality could slow down the erosion process.