The number of submarine power cables (SPC) will drastically increase in the next decades with the development of Marine Renewable Energy (MRE). Thus it becomes vital to better understand their potential impacts on the benthic compartment. Unburied SPC and associated protection/stabilisation structures represent artificial hard substrates available for benthic species. The spatio-temporal dynamics of this ‘reef effect‘ depend on physical parameters (size, nature of structure) but also on biological characteristics of the surrounding area.
Underwater imagery is a relevant approach to monitor benthic colonisation at sites difficult to access (e.g. tidal sites) and to rapidly collect biodiversity data in a non-destructive way and with high spatial resolution. Although image acquisition is rapid, analysis is time-consuming, thus requiring optimised exploitation methods. A method to estimate benthic community on sill images is the random point count method, this method is organized in three successive steps: randomly distribute a number of points on an image, identify the features (e.g. taxa or substrate-type) lying under each point, and then estimate the different covering rates. We used this method to estimate change of biodiversity on cable protection devices, concrete mattresses and natural substratum (taken as a reference) at the Paimpol-Bréhat tidal test site in France.
The aim of this study was to optimise methods of underwater imagery analysis to efficiently characterise the reef effect of SPC on epibenthic communities of the study site. To reach this objective, the authors answered three distinct questions:
1) What is the optimum point density (number of points/area) needed for the random point count approach?
2) What is the optimum number of photographs to analyse?
3) What is the taxonomic level of identification needed?
Our results showed that the random point count applied with underwater imagery can be an efficient and standardized tool (in terms of time allocated and accuracy achieved) used to investigate the reef effect of MRE structures. Although we optimised this method for a single French MRE site, this approach should be useful to compare the extent of reef effects in different ecological contexts.
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