The understanding of the coastal environment is fundamental for efficiently and effectively facing the pollution phenomena as expected by the Marine Strategy Framework Directive, and for limiting the conflicts between anthropic activities and sensitivity areas, as stated by Maritime Spatial Planning Directive. To address this, the Laboratory of Experimental Oceanology and Marine Ecology developed a multi-platform observing network that has been in operation since 2005 in the coastal marine area of Civitavecchia (Latium, Italy) where multiple uses and high ecological values closely coexist. The Civitavecchia Coastal Environment Monitoring System (C-CEMS), implemented in the current configuration, includes various components allowing one to analyze the coastal conflicts by an ecosystem-based approach. The long-term observations acquired by the fixed stations are integrated with in situ data collected for the analysis of the physical, chemical and biological parameters of the water column, sea bottom and pollution sources detected along the coast. The in situ data, integrated with satellite observations (e.g., temperature, chlorophyll a and TSM), are used to feed and validate the numerical models, which allow the analysis and forecasting of the dynamics of pollutant dispersion under different conditions. To test the potential capabilities of C-CEMS, two case studies are reported here: (1) the analysis of fecal bacteria dispersion for bathing water quality assessment, and (2) the evaluation of the effects of the dredged activities on Posidonia meadows, which make up most of the two sites of community importance located along the Civitavecchia coastal zone. The simulation outputs are overlapped by the thematic maps showing bathing areas and Posidonia oceanica distribution, thus giving a first practical tool that could improve the resolution of the conflicts between coastal uses (in terms of stress produced by anthropic activities) and sensitivity areas.

This study reports the quantification and analysis of the ecosystem services (ESs) value of Posidonia oceanica (L.) Delile (1813) meadows in Italy (Liguria, Tuscany, Latium, Campania, Calabria, Apulia, Sardinia, and Sicily regions). The ES evaluation method of P. oceanica meadows applied in this study was obtained from a previous study in which the site-specific approach for the definition of the benefits and services was applied. The distribution of P. oceanica and the ESs economic value have been managed through an open-source geographic information system (QGIS), focusing on five essential ESs: carbon sequestration, bioremediation, oxygen production, erosion protection, and food production. The average value of the ESs obtained on the Italian national scale is €21,660.5 ha⁻¹ yr⁻¹, which is comparable with the values reported in the international literature concerning P. oceanica ESs. The results of this study confirm that the economic evaluation of ESs is an essential tool for the management of the coastal marine environment, especially considering the modularity of the applied approach. The value of the total benefits, considering the entire extension of the national P. oceanica meadows, represents significant value with respect to the Italian gross domestic product, and the individual budgets of the considered Italian regions.

The benthic seabeds and seagrass ecosystems, in particular the vulnerable Posidonia oceanica (PO), are increasingly threatened by climate change and other anthropogenic pressures. Along the 8000 km coastline of Italy, they are often poorly mapped and monitored to properly evaluate their health status. Thus to support these monitoring needs, the improved capabilities of the Landsat 8 Operational Land Imager (OLI) Earth Observation (EO) satellite system were tested for PO mapping by coupling its atmospherically corrected multispectral data with near-synchronous sea truth information. Two different approaches for the necessary atmospheric correction were exploited focusing on the Aerosol Optical Depth (AOD) and adjacency noise effects, which typically occur at land–sea interfaces. The general achievements demonstrated the effectiveness of High Resolution (HR) spectral responses captured by OLI sensor, for monitoring seagrass and sea beds in the optically complex Tyrrhenian shallow waters, with performance level dependent on the type of applied atmospheric pre-processing. The distribution of the PO leaf area index (LAI) on different substrates has been most effectively modelled using on purpose developed spectral indices. They were based on the coastal and blue-green OLI bands, atmospherically corrected using a recently introduced method for AOD retrieval, based on the Short Wave Infrared (SWIR) reflectance. The alternative correction method including a less effective AOD assessment but the removal of adjacency effects has proven its efficacy for improving the thematic discriminability of the seabed types characterized by different PO cover–substrate combinations.

The Arctic region is known to be severely affected by climate change, with evident alterations in both physical and biological processes. Monitoring the Arctic Ocean ecosystem is key to understanding the impact of natural and human-induced change on the environment. Large data sets are required to monitor the Arctic marine ecosystem and validate high-resolution satellite observations (e.g., Sentinel), which are necessary to feed climatic and biogeochemical forecasting models. However, the Global Observing System needs to complete its geographic coverage, particularly for the harsh, extreme environment of the Arctic Region. In this scenario, autonomous systems are proving to be valuable tools for increasing the resolution of existing data. To this end, a low-cost, miniaturized and flexible probe, ArLoC (Arctic Low-Cost probe), was designed, built and installed on an innovative unmanned marine vehicle, the PROTEUS (Portable RObotic TEchnology for Unmanned Surveys), during a preliminary scientific campaign in the Svalbard Archipelago within the UVASS project. This study outlines the instrumentation used and its design features, its preliminary integration on PROTEUS and its test results.