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Eutrophication is a major environmental issue with many negative consequences, such as hypoxia and harmful cyanotoxin production. Monitoring coastal eutrophication is crucial, especially for island countries like the Republic of Cyprus, which are economically dependent on the tourist sector. Additionally, the open-sea aquaculture industry in Cyprus has been exhibiting an increase in recent decades and environmental monitoring to identify possible signs of eutrophication is mandatory according to the legislation. Therefore, in this modeling study, two different types of artificial neural networks (ANNs) are developed based on in situ data collected from stations located in the coastal waters of Cyprus. These ANNs aim to model the eutrophication phenomenon based on two different data-driven modeling procedures. Firstly, the self-organizing map (SOM) ANN examines several water quality parameters’ (specifically water temperature, salinity, nitrogen species, ortho-phosphates, dissolved oxygen, and electrical conductivity) interactions with the Chlorophyll-a (Chl-a) parameter. The SOM model enables us to visualize the monitored parameters’ relationships and to comprehend complex biological mechanisms related to Chl-a production. A second feed-forward ANN model is also developed for predicting the Chl-a levels. The feed-forward ANN managed to predict the Chl-a levels with great accuracy (MAE = 0.0124; R = 0.97). The sensitivity analysis results revealed that salinity and water temperature are the most influential parameters on Chl-a production. Moreover, the sensitivity analysis results of the feed-forward ANN captured the winter upwelling phenomenon that is observed in Cypriot coastal waters. Regarding the SOM results, the clustering verified the oligotrophic nature of Cypriot coastal waters and the good water quality status (only 1.4% of the data samples were classified as not good). The created ANNs allowed us to comprehend the mechanisms related to eutrophication regarding the coastal waters of Cyprus and can act as useful management tools regarding eutrophication control.

Pistacia spp. remains are common finds among archaeobotanical assemblages in prehistoric sites in Southwest Asia, both in the form of endocarps and charcoal remains. However, in the absence of a systematic study of the fruit morphology, the archaeobotanical remains of Pistacia cannot be identified to the species level and this deprives us of important information on their past geographical distribution and uses. This paper presents a comprehensive study of morphological and traditional morphometric characteristics of modern endocarps of six Pistacia species indigenous to Southwest Asia: P. atlantica Desf., P. eurycarpa Yalt., P. khinjuk Stocks, P. lentiscus L., P. terebinthus L. and P. vera L. The observation of recurring morphological features that were shown to remain stable during experimental carbonisation allowed us to set up an identification key whose efficiency was tested through a blind test. The application of established identification criteria to archaeobotanical material from the Late Aceramic Neolithic site of Khirokitia-Vounoi in Cyprus, enables an in-depth discussion on the biogeography and use of Pistacia species in prehistoric Cyprus. Finally, the paper identifies directions for future research on a major plant resource of the past.

Good coastal water quality is important for human well-being but also for marine organisms. The European Water Framework Directive (2000/60/EC) has established threshold values for regional seas, with Cyprus collaborating with Greece to assess conditions and set common chlorophyll-a (chl-a) thresholds. In the Levantine Basin, known for its oligotrophic waters, chl-a levels categorize water quality: under 0.1 (μg/l) indicates high quality, 0.1 to 0.4 (μg/l) indicates good quality, and over 0.4 (μg/l) indicates moderate quality. A study developed a Probabilistic Neural Network (PNN) to classify coastal water quality based on factors such as dissolved nitrogen (DIN), ortho-phosphates (PO43−), salinity, dissolved oxygen (DO), pH, electrical conductivity (EC), and water temperature (WT). Over a 20-year monitoring period (2000-2020), the PNN demonstrated impressive accuracy, achieving 98.1% overall classification accuracy and a macro-averaged F1-score of 97.9%. This model serves as an effective tool for environmental management, capable of accurately predicting the water quality status of the Cypriot coastline based on various measurements, thus contributing to better understanding and preservation of coastal ecosystems.

The Mediterranean Sea has the highest accumulation of microplastics in the world. Although numerous studies about microplastic’s abundance and distribution have been conducted, the majority sampled surface waters. Especially for the Eastern Mediterranean, there is no information concerning the deeper strata. This study fills this gap by studying the microplastic spatial and temporal distribution along the coasts of Cyprus, utilizing zooplankton samples collected from the entire 0–50 m depth layer. The average microplastics’ abundance was 41.31 ± 22.41 items/m3 indicating that the Eastern Mediterranean seems to be much more polluted than the western basin. The fibers outnumbered the abundance of the fragments by a factor of ten. Most fibers were sized between 0.5 and 1.0 mm, and 81.24% were transparent. The average area of the fragments was ≤0.05 mm2, and most of them were hard-rounded (53.38%). The microplastics to zooplankton ratio ranged between 0.021 and 0.241. A positive correlation was found between the abundance of microplastics and the total zooplankton, especially the copepods. Studies of microplastics in zooplankton samples taken from the water column are expected to provide better insights into the role of these pollutants in marine ecosystems.

The diversity and distribution of polychaetes in the coastal area and the EEZ of the Republic of Cyprus is presented based on both the literature records and new data acquired in a wide range of environmental monitoring programmes and research projects. A total of 585 polychaete species belonging to 49 families were reported in Cyprus waters; among them, 205 species (34%) were recorded based on the literature only, 149 (26%) were new records based on our own data, and a total of 231 spp. (40%) were recorded from both the literature and new data. A total of 51 polychaete species were identified as non-indigenous; among them, 32 were confirmed as alien species, 4 were considered cryptogenic, and 15 were considered questionable as there were doubts about their identity. The Indo-Pacific Schistomeringos loveni was reported for the first time in the Mediterranean Sea, while four species already reported in the literature, namely, Bispira melanostigma, Fimbriosthenelais longipinnis Leonnates aylaoberi, and Rhodopsis pusilla, were added to the list of non-indigenous polychaetes in the Mediterranean Sea. The current work highlights the importance of implementing environmental monitoring programmes and carrying out research surveys targeting benthic macrofauna assemblages.

A surfeit of Dissolved Inorganic Nitrogen (DIN), which is defined as the total amount of nitrite, nitrate, and ammonium levels in water, may cause negative effects to the marine environment. For example, elevated levels of DIN may promote surplus production of algae and possible depletion of oxygen in the water column. The DIN in the marine water column is monitored as part of the Water Framework Directive (WFD), the Nitrates Directive and the EU Marine Strategy Framework Directive (MSFD). Data-driven models have been proved to be an excellent management tool for environmental issues related to coastal water quality protection and management. Based on data-drive models, and specifically the Artificial Neural Networks (ANNs), the DIN levels from coastal stations in Cyprus were predicted. To do so, three different ANNs models were created, each of them calculating nitrite, nitrate, and ammonium levels respectively with high accuracy ( r >0.95). The results derived from these models can be used to identify hot-spot areas with increased DIN levels and to evaluate management scenarios and measures to be implemented in order to maintain the good Environmental Status and quality of the coastal waters.

The diversity and distribution of polychaetes in the coastal area and the EEZ of the Republic of Cyprus is presented based on both the literature records and new data acquired in a wide range of environmental monitoring programmes and research projects. A total of 585 polychaete species belonging to 49 families were reported in Cyprus waters; among them, 205 species (34%) were recorded based on the literature only, 149 (26%) were new records based on our own data, and a total of 231 spp. (40%) were recorded from both the literature and new data. A total of 51 polychaete species were identified as non-indigenous; among them, 32 were confirmed as alien species, 4 were considered cryptogenic, and 15 were considered questionable as there were doubts about their identity. The Indo-Pacific Schistomeringos loveni was reported for the first time in the Mediterranean Sea, while four species already reported in the literature, namely, Bispira melanostigma, Fimbriosthenelais longipinnis Leonnates aylaoberi, and Rhodopsis pusilla, were added to the list of non-indigenous polychaetes in the Mediterranean Sea. The current work highlights the importance of implementing environmental monitoring programmes and carrying out research surveys targeting benthic macrofauna assemblages.

The polychaete Gallardoneris iberica was described in soft-bottom benthic habitats from the Atlantic Iberian Peninsula coasts in 2012. Since then, successive studies have found this species in Spain, Italy and Croatia. The present study is the first to report G. iberica for Greece and Cyprus (42 new records) confirming its wide geographic distribution on southern European coasts. Taxonomic accounts and ecological preferences based on a large survey and review of available literature are being presented. The species was frequently found in habitats characterized by infralittoral muddy sands with variable organic matter and ‘Moderate’ ecological quality status; nevertheless it was also recorded in coarser and finer sediments, circalittoral mixed sediments, phytal substrates and undisturbed sites. Its relative abundance per sample was always lower than 2%. A review of the available ecological and geographic data of the other Gallardoneris species and a worldwide taxonomic key to Gallardoneris species are provided.

Coastal ecosystems are highly complex and driven by multiple environmental factors. To date we lack scientific evidence for the relative contribution of natural and anthropogenic drivers for the majority of marine habitats in order to adequately assess the role of different stressors across the European seas. Such relationship can be investigated by analysing the correlation between environmental variables and biotic patterns in multivariate space and taking into account non-linearities. Within the framework of the EMBOS (European Marine Biodiversity Observatory System) programme, hard bottom intertidal communities were sampled in a standardized way across European seas. Links between key natural and anthropogenic drivers and hard bottom communities were analysed using Boosted Regression Trees modelling. The study identified strong interregional variability and showed that patterns of hard bottom macroalgal and invertebrate communities were primarily a function of tidal regime, nutrient loading and water temperature (anomalies). The strength and shape of functional form relationships varied widely however among types of organisms (understorey algae composing mostly filamentous species, canopy-forming algae or sessile invertebrates) and aggregated community variables (cover or richness). Tidal regime significantly modulated the effect of nutrient load on the cover and richness of understorey algae and sessile invertebrates. In contrast, hydroclimate was more important for canopy algae and temperature anomalies and hydroclimate separately or interactively contributed to the observed patterns. The analyses also suggested that climate-induced shifts in weather patterns may result in the loss of algal richness and thereby in the loss of functional diversity in European hard bottom intertidal areas.

Examining how variability in population abundance and distribution is allotted among different spatial scales can inform of processes that are likely to generate that variability. Results of studies dealing with scale issues in marine benthic communities suggest that variability is concentrated at small spatial scales (from tens of centimetres to few metres) and that spatial patterns of variation are consistent across ecosystems characterized by contrasting physical and biotic conditions, but this has not been formally tested. Here we quantified the variability in the distribution of intertidal rocky shore communities at a range of spatial scales, from tens of centimetres to thousands of kilometres, both in the NE Atlantic and the Mediterranean, and tested whether the observed patterns differed between the two basins. We focused on canopy-forming macroalgae and associated understorey assemblages in the low intertidal, and on the distribution of Patella limpets at mid intertidal levels. Our results highlight that patterns of spatial variation, at each scale investigated, were consistent between the Atlantic and the Mediterranean, suggesting that similar ecological processes operate in these regions. In contrast with former studies, variability in canopy cover, species richness and limpet abundance was equally distributed among spatial scales, possibly reflecting the fingerprint of multiple processes. Variability in community structure of low intertidal assemblages, instead, peaked at the largest scale, suggesting that oceanographic processes and climatic gradients may be important. We conclude that formal comparisons of variability across scales nested in contrasting systems are needed, before any generalization on patterns and processes can be made.