Τομπουλίδου, Μαρία

Preferred name

Τομπουλίδου, Μαρία

Translated Name

Tompoulidou, Maria

Alternative Name

Tompoulidou, M.

Τομπουλίδου, Μ.

Job Title

Μέλος Τομέα Έρευνας και Προστασίας της Βιοποικιλότητας

Main Affiliation

ORCID

0000-0001-9711-591X

Scopus Author ID

https://www.scopus.com/authid/detail.uri?authorId=55848423100

ResearchGate ID

https://www.researchgate.net/profile/Maria-Tompoulidou?ev=hdr_xprf

https://www.linkedin.com/in/maria-tompoulidou-8456867b/

Now showing 1 - 7 of 7

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Τhe fish fauna in lentic ecosystems of Greece
(2022)
Vardakas, Leonidas
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Koutsikos, Nickolas
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Perdikaris, Costas
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Petriki, Olga
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Bobori, Dimitra
This study provides an annotated checklist of the freshwater fish species recorded in lentic ecosystems of Greece. Species distributional data were derived from an extensive review of published and unpublished sources and were evaluated for their consistency, adequacy and reliability. Overall, 650 freshwater lentic ecosystems (149 natural and 501 artificial) were investigated from which, 480 were fishless or fish data were unavailable. In the remaining 170 ecosystems, 122 taxa were recorded (belonging to 22 families and 57 genera). Some of the records concerned species with extirpated populations, species of doubtful occurrences and taxa of uncertain taxonomic status. The highest species richness (52 species) was recorded in the Ionian ecoregion while endemicity was highest in the Macedonia-Thessaly ecoregion (43.75%). The Eastern Aegean ecoregion presented the highest level of introduced species (75%). Only eight ecosystems hosted 20 or more species, while 92 ecosystems had over 50% of introduced species. The most widespread native species (Anguilla anguilla and Luciobarbus albanicus) were two highly migratory species, highlighting the importance of connectivity of aquatic ecosystems. The most widespread translocated species was Cyprinus carpio due its high commercial and recreational value, whereas Gambusia holbrooki confirmed its high dispersal ability being the most widespread alien species. More than one third of the species recorded (37.23 %) are threatened based on the IUCN Red List. The ultimate contribution of this study is to support the coordination and dissemination of baseline information on the freshwater fishes of Greek lentic ecosystems, required by a range of users. This knowledge will enable further understanding of the regional assemblage structure and other biogeographical patterns of the ichthyofauna of Greece and will contribute to species conservation by prioritising areas hosting species in need of protection. Finally, this study reveals the high knowledge gap regarding species composition in many Greek lentic ecosystems and highlights the need for relevant primary research including more systematic and standardised samplings.
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Οι υγρότοποι της Θεσσαλίας
(Περιφέρεια Θεσσαλίας, 2020)
Ινστιτούτο Ανάπτυξης Επιχειρηματικότητας
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Ζέρβας, Δημήτρης
Η παρούσα έκδοση αποτελεί παραδοτέο του έργου "Improving the conservation effectiveness of wetlands-WetMainAreas", το οποίο υλοποιήθηκε στο πλαίσιο του Ευρωπαϊκού Προγράμματος Εδαφικής Συνεργασίας Interreg Balkan-Mediterranean 2014-2020.
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Υγρότοποι στην Ηπειρωτική Ελλάδα: πλήθος, έκταση, χωρική κατανομή
(Ελληνικό Κέντρο Βιοτόπων-Υγροτόπων (ΕΚΒΥ), 2020)
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Η παρούσα έκδοση αποτελεί παραδοτέο του έργου "Improving the conservation effectiveness of wetlands-WetMainAreas", το οποίο υλοποιήθηκε στο πλαίσιο του Ευρωπαϊκού Προγράμματος Εδαφικής Συνεργασίας Interreg Balkan-Mediterranean 2014-2020. Η έκδοση δομείται σε τρεις ενότητες. Η πρώτη παρέχει ορισμούς, στοιχεία τυπολογίας και αναφορά στις λειτουργίες και τις υπηρεσίες των υγροτόπων. Η δεύτερη συνοψίζει το υφιστάμενο θεσμικό πλαίσιο για τη διατήρηση και προστασία των υγροτόπων της χώρας. Η τρίτη ενότητα παρουσιάζει τη μεθοδολογική προσέγγιση που υιοθετήθηκε για τον εντοπισμό και τη χαρτογραφική αποτύπωση των ορίων των υγροτόπων στην ηπειρωτική Ελλάδα και παρέχει αποτελέσματα ως προς το πλήθος, την έκταση και τη χωρική κατανομή των υγροτόπων που εντοπίστηκαν.
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Water-related ecosystems' mapping and assessment based on remote sensing techniques and geospatial analysis: The SWOS national service case of the Greek Ramsar sites and their catchments
(2020)
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Hofer, Rene
Mapping and assessment of water-related ecosystems is a challenging task that requires advanced processing techniques with clear rules and standards in terminology and definition of class features. These ecosystems are hydrologically and ecologically connected at catchment level and co-exist within a human context. The SWOS (Satellite based Wetland Observation Service - Horizon 2020) national service case for mapping and assessing the 10 Greek Ramsar wetland sites and their catchment areas is built on the requirements of the Ramsar Convention on Wetlands and of the Aichi Biodiversity Targets of the Strategic Plan for Biodiversity 2011–2020. It contributes directly to Sustainable Development Goal (SDG) Global Indicator 6.6.1 “Sub-Indicator 1 – spatial extent of water-related ecosystems”. An Object-Based Image Analysis (OBIA) approach was adopted using Sentinel-2 satellite images for the year 2017, to discriminate 31 classes (wetland and non-wetland) over an area of 2,015,591 ha. The classification model was further adjusted to Landsat 5 TM imagery of previous years (1986–1987) in order to extract possible changes in the spatial extent of water-related ecosystems. The Mapping and Assessment of Ecosystems and their Services (MAES) ecosystem typology, as this was enhanced within SWOS, was applied. Results demonstrate the effectiveness of the employed classification model, techniques and rules, in obtaining highly accurate (over 90%) mapping results on the spatial extent of water-related ecosystems. Also, they highlight the contribution of Earth Observation (EO) and geospatial analysis in assessments of area- based changes and their causes, as well as in identification of conservation and management priorities (i.e. areas for restoration). In addition, to address the need to strengthen national capacities, the established SWOS service lines have been used as a contribution to the user community.
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Monitoring the Impact of Floods on Water Quality Using Optical Remote Sensing Imagery: The Case of Lake Karla (Greece)
(2024)
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This study investigates the performance of published bio-optical remote sensing indices/ algorithms for monitoring water quality changes in Lake Karla, Greece, caused by Storm Daniel after the September 2023 flooding event. Commonly applied indices were utilised to estimate chlorophyll-a (Chl-a) and total suspended solids (TSS) using Sentinel-2 high-resolution optical imagery. In situ measurements were undertaken and water samples were collected during the pre-flooding period, post-flooding, and one-year post-flood, providing a basis for validating the remote sensing models. Monitoring results showed that most physicochemical parameters changed considerably. Chl-a and TSS were estimated by testing five and seven indices, respectively. Regarding the Chl-a estimation, the NDCI and 2-BDA indices outperformed other models, having high correlations with in situ Chl-a measurements and effectively following the in situ Chl-a temporal trends. Among the TSS indices, NDWI and TUR-IND demonstrated better performances, effectively capturing the variations in suspended solids. Overall, this study highlights the potential of Sentinel-2 imagery in assessing water quality changes, particularly in response to flooding events. It is an exploratory approach to assess the feasibility of utilising optical satellite data for evaluating the environmental impacts of natural disasters on lake water quality and supports decision-making in environmental management. Additionally, it identifies potential challenges and considerations that must be addressed to ensure effective application.
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A Geographic Object-Based Image Approach Based on the Sentinel-2 Multispectral Instrument for Lake Aquatic Vegetation Mapping: A Complementary Tool to In Situ Monitoring
(2024)
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Karadimou, E.
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Aquatic vegetation is an essential component of lake ecosystems, used as a biological indicator for in situ monitoring within the Water Framework Directive. We developed a hierarchical object-based image classification model with multi-seasonal Sentinel-2 imagery and suitable spectral indices in order to map the aquatic vegetation in a Mediterranean oligotrophic/mesotrophic deep lake; we then applied the model to another lake with similar abiotic and biotic characteristics. Field data from a survey of aquatic macrophytes, undertaken on the same dates as EO data, were used within the accuracy assessment. The aquatic vegetation was discerned into three classes: emergent, floating, and submerged aquatic vegetation. Geographic object-based image analysis (GEOBIA) proved to be effective in discriminating the three classes in both study areas. Results showed high effectiveness of the classification model in terms of overall accuracy, particularly for the emergent and floating classes. In the case of submerged aquatic vegetation, challenges in their classification prompted us to establish specific criteria for their accurate detection. Overall results showed that GEOBIA based on spectral indices was suitable for mapping aquatic vegetation in oligotrophic/mesotrophic deep lakes. EO data can contribute to large-scale coverage and high-frequency monitoring requirements, being a complementary tool to in situ monitoring.
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The impact of submerged aquatic vegetation on satellite-derived bathymetry in shallow waters: an accuracy assessment
(2026)
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Mouratidis, Antonios
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The aim of this study was to evaluate the performance of four widely used Satellitederived Bathymetry (SDB) models (Stumpf, Lyzenga, Random Forest and XGBoost) in different scenarios of varying proportions of bare substrate and submerged aquatic vegetation in lake shallow-waters. Particularly, six scenarios were created, ranging from 0% to 100% submerged vegetation within a depth range of 0–10 m. The predictive accuracy of SDB models was assessed using an updated reference digital terrain model (DTM). The performance of the models was evaluated across multiple depth ranges and bottom types (bare substrate and submerged vegetation). Evaluation metrics included root mean square error (RMSE), mean absolute error (MAE), coefficient of determination (R²). One to one scatterplots demonstrated higher model performance in bare substrate, with R² values ranging from 0.56 to 0.63 for Stumpf/Lyzenga and 0.65–0.70 for XGBoost/Random Forest in bare substrate areas. Scenario-level CV of RMSE remained acceptable (<30%), decreasing from ~0.058 (0% vegetation) to ~0.022 (100% vegetation). Random Forest and XGBoost outperformed Lyzenga and Stumpf models under mixed scenarios. This study improves the understanding of SDB training requirements in mixed lake bottom types and offers valuable insights for improving the application of SDB in lakes.

Τομπουλίδου, Μαρία

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