Wetlands are highly dynamic, with many natural and anthropogenic drivers causing seasonal, periodic or permanent changes in their structure and composition. Thus, it is necessary to use time series of images for accurate classifications and monitoring. We used all available Sentinel-1 and Sentinel-2 images to produce a national wetlands map for Albania. We derived different indices and temporal metrics and investigated their impacts and synergies in terms of mapping accuracy. Best results were achieved when combining Sentinel-1 with Sentinel-2 and its derived indices. We reduced systematic errors and increased the thematic resolution using morphometric characteristics and knowledge-based rules, achieving an overall accuracy of 82%. Results were also validated against field inventories. This methodology can be reproducible to other countries and can be made operational for an integrated planning that considers the food, water, and energy nexus.

The wetlands are often coupled with anthropogenic systems. This makes them highly dynamic, and thus difficult to map and monitor from space. The Sentinel-1 constellation allows monitoring land changes regardless of cloud conditions and with a high frequency of pass. We use a time series of 33 Sentinel-1 dual-polarized images from 2016 to map seasonal changes at the artificial Lake of Kerkini, in Greece. The images are accessed and processed in Google Earth Engine via a Flask web application. Points of change within the time series and frequency of change were determined according to an omnibus-test statistic. The results were compared to an optical-based land cover map and gaging measurements. Frequency of change patterns matched different land cover types, indicating that frequency of change is related to the physical and structural properties of the land cover. This methodology can be used operationally to improve our understanding of ecosystems, enhance land cover maps, and to monitor wetland dynamics as well as cover changes caused by human activities.

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 Species distributional data were derived from an extensive review of published and unpublished sources and were evaluated for their consistency, adequacy and reliability.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.

In recent years, the need to protect and conserve biodiversity has become more critical than ever before, as a prerequisite for both sustainable development and the very survival of the human species. This has made it a priority for the scientific community to develop technological solutions that provide data and information for monitoring, directly or indirectly, biodiversity and the drivers of change. A new era of satellite earth observation upgrades the potential of Remote Sensing (RS) to support, at relatively low cost, but with high accuracy the extraction of information over large areas, at regular intervals, and over extended periods of time. Also, the recent development of the Earth Observation Data Cubes (EODC) framework facilitates EO data management and information extraction, enabling the mapping and monitoring of temporal and spatial patterns on the Earth’s surface. This submission presents the ELBIOS EODC, specifically developed to support the biodiversity management and conservation over Greece. Based on the Open Data Cube (ODC) framework, it exploits multi-spectral optical Copernicus Sentinel-2 data and provides a series of Satellite Earth Observation (SEO) biodiversity products and spectral indices nationwide.