In this study, we present a framework for seagrass habitat mapping in shallow (5–50 m) and very shallow water (0–5 m) by combining acoustic, optical data and Object-based Image classification. The combination of satellite multispectral images-acquired from 2017 to 2019, together with Unmanned Aerial Vehicle (UAV) photomosaic maps, high-resolution multibeam bathymetry/backscatter and underwater photogrammetry data, provided insights on the short-term characterization and distribution of Posidonia oceanica (L.) Delile, 1813 meadows in the Calabrian Tyrrhenian Sea. We used a supervised Object-based Image Analysis (OBIA) processing and classification technique to create a high-resolution thematic distribution map of P. oceanica meadows from multibeam bathymetry, backscatter data, drone photogrammetry and multispectral images that can be used as a model for classification of marine and coastal areas. As a part of this work, within the SIC CARLIT project, a field application was carried out in a Site of Community Importance (SCI) on Cirella Island in Calabria (Italy); different multiscale mapping techniques have been performed and integrated: the optical and acoustic data were processed and classified by different OBIA algorithms, i.e., k-Nearest Neighbors’ algorithm (k-NN), Random Tree algorithm (RT) and Decision Tree algorithm (DT). These acoustic and optical data combinations were shown to be a reliable tool to obtain high-resolution thematic maps for the preliminary characterization of seagrass habitats. These thematic maps can be used for time-lapse comparisons aimed to quantify changes in seabed coverage, such as those caused by anthropogenic impacts (e.g., trawl fishing activities and boat anchoring) to assess the blue carbon sinks and might be useful for future seagrass habitats conservation strategies.

Underwater photogrammetry provides a means of generating high-resolution products such as dense point clouds, 3D models, and orthomosaics with centimetric scale resolutions. Underwater photogrammetric models can be used to monitor the growth and expansion of benthic communities, including the assessment of the conservation status of seagrass beds and their change over time (time lapse micro-bathymetry) with OBIA classifications (Object-Based Image Analysis). However, one of the most complex aspects of underwater photogrammetry is the accuracy of the 3D models for both the horizontal and vertical components used to estimate the surfaces and volumes of biomass. In this study, a photogrammetry-based micro-bathymetry approach was applied to monitor Posidonia oceanica restoration actions. A procedure for rectifying both the horizontal and vertical elevation data was developed using soundings from high-resolution multibeam bathymetry. Furthermore, a 3D trilateration technique was also tested to collect Ground Control Points (GCPs) together with reference scale bars, both used to estimate the accuracy of the models and orthomosaics. The root mean square error (RMSE) value obtained for the horizontal planimetric measurements was 0.05 m, while the RMSE value for the depth was 0.11 m. Underwater photogrammetry, if properly applied, can provide very high-resolution and accurate models for monitoring seagrass restoration actions for ecological recovery and can be useful for other research purposes in geological and environmental monitoring.

Posidonia oceanica beds form one of the most important coastal ecosystems in the Mediterranean basin and represent a good indicator of the seawater quality, being strongly sensitive to human perturbations. The aim of the present study is to verify whether changes in cytophysiological features of this seagrass could mark early altered environmental conditions. In this context, we investigated in juvenile and intermediate leaves: (1) the presence and structure of phenolic compounds, due to their role in the defence response against biotic and abiotic stress; (2) the presence and distribution of cytokinins, because of their key role in leaf growth and senescence as well as in relation to their interaction in light signalling. Significant and measurable increases in the amount of phenols as well as changes in cytokinins distribution were detected in Posidonia leaves collected from meadows subjected to disturbed environmental conditions as compared to those of preserved ones. These results clearly indicated that these variables could be used as early biomarkers of environmental quality.

The aim of the study was to evaluate the effectiveness of the application of multiple environmental descriptors through an asymmetrical sampling design to detect possible impacts related to the Costa Concordia event on the coastal marine environment. The Costa Concordia shipwreck occurred on a submerged rocky reef in the north-western Mediterranean Sea and the wreck was removed 2 years later. To achieve the proposed objective two main coastal ecosystems, the seagrass Posidonia oceanica and coralligenous assemblages were studied using two ecological indices, PREI and ESCA, respectively. Both indices show a lower ecological quality in the disturbed sites compared with the control ones. Differences between the disturbed and control sites observed in both studied ecosystems would seem to indicate an increase of turbidity around the shipwreck as the most plausible cause of impact. The concurrent use of different ecological indices and asymmetrical sampling designs allowed detection of differences in ecological quality of the disturbed sites compared with the controls. This approach may represent an interesting tool to be employed in impact evaluation studies.