Paul, Maike and Lefebvre, Alice and Manca, Eleonora and Amos, Carl L. (2011) An Acoustic method for the remote measurement of seagrass metrics. Estuarine, Coastal and Shelf Science, Vol. 93 (1), p. 68-79. ISSN 0272-7714. Article.
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Seagrass meadows are ecosystems of great ecological and economical value and their monitoring is an important task within coastal environmental management. In this paper, an acoustic mapping technique is presented using a profiling sonar. The method has been applied to three different sites with meadows of Zostera marina, Zostera noltii and Posidonia oceanica respectively, with the aim to test the method’s applicability. From the backscatter data the seabed could be identified as the strongest scatterer along an acoustic beam. The presented algorithm was used to compute water depth, seagrass canopy height and seagrass coverage and to produce maps of the survey areas. Canopy height was estimated as the distance between the bed and the point where backscatter values decrease to water column values. The algorithm was extended from previous methods to account for a variety of meadow types. Seagrass coverage was defined as the percentage of beams in a sweep where the backscatter 5e10 cm above the bed was higher than a threshold value. This threshold value is dynamic and depends on the average backscatter value throughout the water column. The method is therefore applicable in a range of turbidity conditions. Comparison with results from other survey techniques (i.e. dive surveys, underwater videos) yielded a high correlation which indicates that the method is suited to measure seagrass coverage and height. Analysis of the data showed that each seagrass species has a characteristic canopy height and spatial coverage distribution. These differences were used to undertake a preliminary species identification, as each species has a typical canopy height and preferred depth range. Furthermore, the results show that these differences can be used to track boundaries between species remotely. Finally, the application of the meadow distribution pattern to the health of a meadow is discussed.
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