Drivers of harmful algal blooms in coastal areas of Eastern Mediterranean: a machine learning methodological approach.

Harmful algal species are present in the Mediterranean Sea and are often associated with toxic events affecting the nearby coastal zones. The presence of 18 marine microalgae, at genus level, associated with potentially harmful characteristics was predicted using a number of machine learning techniques based exclusively on a small set of abiotic variables, already identified as drivers of blooms. Random Forest (RF) algorithm achieved the best predictive performance by correctly identifying the presence of most genera with a mean of 89.2% of total samples. Although, RF has shown lower predictive performance for genera present in a low number of samples, its predictive power remains at least "fair' in these cases. The main tree-based advantage of RF was thereafter used to assess the importance of the input variables in predicting the presence of the algal genera. Temperature had the most powerful effect on genera's presences, although this effect varies among genera. Finally, the genera were clustered based on their response to the considered abiotic variables and common trends in an ecological context were identified.

Marine water quality monitoring: a review.

Marine water quality monitoring is performed for compliance with regulatory issues, trend detection, model validation and assessment of the effectiveness of adopted policies. As the end users are managers and policy makers, the objectives should be of practical interest and the answers should reduce the uncertainty concerning environmental impact, supporting planning and decision making. Simple and clearcut answers on environmental issues require synthesis of the field information using statistics, simulation models and multiple criteria analysis (MCA). Statistics is easy to apply whereas simulation models enable researchers to forecast future trends as well as test different scenarios. MCA allows the co-estimation of socio-economic variables providing a compromise between scientists' and policy makers' priorities. In addition, stakeholders and the public have the right to know and participate. This article reviews marine water quality monitoring principles, design and data analysis procedures. A brief review of international conventions of regional seas is also included.

Eutrophication and environmental policy in the Mediterranean Sea: a review.

The Mediterranean Sea is a semienclosed basin connected with the open sea mainly through the Strait of Gibraltar. Due to the circulation pattern and the long residence time ranging between 80 and 100 years, the Mediterranean Sea is a sensitive environment to eutrophication pressures. The main body of water of the Mediterranean is characterized by very low nutrient concentrations, and therefore, the Mediterranean is classified among the most oligotrophic (very poor waters in nutrients) seas of the world's oceans. However, some coastal areas, mainly in the northern part of the basin, receive excessive loads of nutrients from sewage effluents, river fluxes, aquaculture farms, fertilizers, and industrial facilities, showing intense eutrophic phenomena with many adverse effects for the marine ecosystem and humans. Various national and international authorities, in addition to monitoring, have taken legal and administrative measures to mitigate eutrophication trends in the area. The Mediterranean environment is a good paradigm of integration of extensive legal framework, scientific knowledge, and administrative practices. The Barcelona Convention, the Mediterranean Action Plan, and European Union Directives on water quality and coastal management, together with scientific information derived from international research programs in the Mediterranean, provide a sound background for practical actions in eutrophication problems. In the present work, the problem of coastal eutrophication in the Mediterranean is reviewed in connection with public policies of the Mediterranean States based on national and international legislation and scientific knowledge on Mediterranean oceanography-ecology and actions coordinated by international bodies. These common actions and practices on coastal management are also discussed in relation to the need for sustainable development and protection of the coastal zone in the Mediterranean Sea.

Coastal marine eutrophication assessment: a review on data analysis.

A wide variety of data analysis techniques have been applied for quantitative assessment of coastal marine eutrophication. Indicators for assessing eutrophication and frequency distributions have been used to develop scales for characterizing oligotrophy and eutrophication. Numerical classification has also contributed to the assessment of eutrophic trends by grouping sampling sites of similar trophic conditions. Applications of eutrophication assessment based on Principal Component Analysis and Multidimensional Scaling have also been carried out. In addition, the rapid development of Geographical Information Systems has provided the framework for applications of spatial methods and mapping techniques on eutrophication studies. Satellite data have also contributed to eutrophication assessment especially at large scale. Multiple criteria analysis methods can integrate eutrophication variables together with socio-economic parameters providing a holistic approach particularly useful to policy makers. As the current concept of eutrophication problems is to be examined as part of a coastal management approach, more complex quantitative procedures are needed to provide a platform useful for implementation of environmental policy. The present work reviews methods of data analysis used for the assessment of coastal marine eutrophication. The difficulties in applying these methods on data collected from the marine environment are discussed as well as the future perspectives of spatial and multiple criteria choice methods.

Scaling the trophic index (TRIX) in oligotrophic marine environments.

The TRIX index used for the assessment of trophic status of coastal waters has been applied in many European seas (Adriatic, Tyrrhenian, Baltic, Black Sea, and North Sea). However, all these waters are characterized by high nutrient levels and phytoplankton biomass; index calibration based on systems that are principally eutrophic may introduce bias to the index scaling. In the present work the TRIX trophic index is evaluated using three standard sets of data characterizing oligotrophy, mesotrophy, and eutrophication in the Aegean (Eastern Mediterranean) marine environment. A natural eutrophication scale based on the TRIX index that is suitable to characterize trophic conditions in oligotrophic Mediterranean water bodies is proposed. This scale was developed into a five-grade water quality classification scheme describing different levels of eutrophication. It is questionable whether this index can form a universal index of eutrophication or the scaling of TRIX should be region specific.

Improving statistical distinctness in assessing trophic levels: the development of simulated normal distributions.

The statistical distinctness in assessing differences of the trophic status between sampling sites was investigated in the present study. Nutrient (phosphate, nitrate, nitrite, ammonia) and phytoplankton (chlorophyll, cell number) variables from nine sampling stations were used for the validation of the statistical procedures. Raw data, transformed data, and simulated data derived on normalized nutrient-phytoplankton frequency distribution were tested. The Kruskal-Wallis (KW) nonparametric statistical procedure was also applied on the raw data as well as the analysis of variance on transformed and simulated data. In all cases, pairwise comparisons for each parameter between stations were performed. The results showed that maximum distinctness between sampling sites for all the six variables was attained using the simulated data. The KW method showed the poorest discrimination between stations. The methodology of producing and using simulated data is described step by step, and the advantages in cases of unequal sampling design or small sample size are discussed.

Multi-dimensional evaluation and ranking of coastal areas using GIS and multiple criteria choice methods.

Coastal ecosystems are increasingly threatened by short-sighted management policies that focus on human activities rather than the systems that sustain them. The early assessment of the impacts of human activities on the quality of the environment in coastal areas is important for decision-making, particularly in cases of environment/development conflicts, such as environmental degradation and saturation in tourist areas. In the present study, a methodology was developed for the multi-dimensional evaluation and ranking of coastal areas using a set of criteria and based on the combination of multiple criteria choice methods and Geographical Information Systems (GIS). The northeastern part of the island of Rhodes in the Aegean Sea, Greece was the case study area. A distinction in sub-areas was performed and they were ranked according to socio-economic and environmental parameters. The robustness of the proposed methodology was assessed using different configurations of the initial criteria and reapplication of the process. The advantages and disadvantages, as well as the usefulness of this methodology for comparing the status of coastal areas and evaluating their potential for further development based on various criteria, is further discussed.