Marine coastal ecosystems are facing structural and functional changes due to the increasing human footprint worldwide, and the assessment of their long-term changes becomes particularly challenging.

In this paper, a geospatial modelling approach based on 2D mapping and morphodynamic data was used to predict the natural position of the upper limit of Posidonia oceanica seagrass meadows settled on soft bottom. The predictive model used was applied in eight coastal areas of Spain, France, Italy, and Greece showing different coastal morphologies and hydrodynamic characteristics, and affected by a number of natural and/or human disturbances.

The results show the effectiveness of the model in measuring the regression of the meadow upper limit. In fact, in all the meadows investigated the upper limit was regressed, laying deeper that the reference condition. The highest values of regression were found in Spain and France, and were consistent with the highest levels of fragmentation and coastal pressures.

The authors conclude that this geospatial modelling approach represents an effective tool to define the reference conditions when proper pristine areas or historical data are not available, thus allowing the assessment of long-time changes experienced by seagrass ecosystems due to human impacts.

Montefalcone et al. (2018) Geospatial modelling and map analysis allowed measuring regression of the upper limit of Posidonia oceanica seagrass meadows under human pressure. Estuarine, Coastal and Shelf Science. 217:148-157.