Characterizing the benthic community in Maryland’s offshore wind energy areas using a towed camera sled: Developing a method to reduce the effort of image analysis and community description

Abstract

Offshore wind farms are a crucial component for the improvement of renewable energy in the United States. The Bureau of Ocean Energy Management (BOEM) designated ~170 km 2 of shelf area for wind energy development off the coast of Maryland, USA. In order to understand potential environmental impacts of wind turbine installation on the benthic ecosystem within the designated area, we conducted a study to visually characterize bottom habitats and epibenthic communities in the Mid-Atlantic Outer Continental Shelf blocks of the Maryland wind energy area. Seven 5 km long transects were sampled using a towed camera sled with a downward-facing digital camera that captured images at 5 frames·s -1 s. Additional small-mesh beam trawling was also conducted at selected locations complementary for species identification. Image data were analyzed using two image selection methods, random and systematic (i.e. video frames were selected at various intervals). For both methods, estimates of community diversity (Hill’s N2) stabilized with sample sizes ranging from 316 to 398 frames. Our results allowed us to define distinct epibenthic communities and bottom habitats that are associated with offshore wind energy sites and to develop a sampling technique for digital images that can be applied to other research programs.

What’s in My Toolkit? A Review of Technologies for Assessing Changes in Habitats Caused by Marine Energy Development

“…Divers are usually more suitable in dense kelp fields or close to/underneath artificial structures (e.g., [68,69]), but both divers and underwater vehicles are known to potentially affect the behavior of marine animals during surveys (e.g., [70,71]). Imagery technologies mounted on robotics or drop frames have the advantage of achieving greater depths with longer bottom times than diver surveys [72][73][74]. Drop, sled, or towed cameras are often highly customizable; some are equipped with multiple cameras facing different angles and with other instruments such as a conductivity-temperature-depth sensor (e.g., [52]), while others are built to endure strong currents and navigate rugged terrains (e.g., [75,76]).…”

A quantitative comparison of towed-camera and diver-camera transects for monitoring coral reefs

“…The percent cover of each benthic group was calculated from the number of points assigned to each group in the images divided by the total number of points per transect. All multivariate analyses were conducted in PRIMERv7 (PRIMER-e) using Bray-Curtis dissimilarities calculated from square-root transformed data (Clarke & Gorley, 2015). Community assemblage data were visualised with non-metric multidimensional scaling (nMDS) (Clarke & Gorley, 2015) to examine potential separation between groups associated with the four main factors of interest: method, habitat, reef and year.…”

“…All multivariate analyses were conducted in PRIMERv7 (PRIMER-e) using Bray-Curtis dissimilarities calculated from square-root transformed data (Clarke & Gorley, 2015). Community assemblage data were visualised with non-metric multidimensional scaling (nMDS) (Clarke & Gorley, 2015) to examine potential separation between groups associated with the four main factors of interest: method, habitat, reef and year. Vector overlays of Pearson correlations >0.6 were used to identify the most influential benthic and coral groups driving separation in the data.…”

“…Image-collection platforms such as remotely operated vehicles (Raoult et al, 2020), automated underwater video (Foster et al, 2014;Ludvigsen & Sørensen, 2016) and towed-cameras (Carroll et al, 2020;Davis et al, 2019;Sheehan et al, 2016) using digital stills or video continue to become more sophisticated and economical. Among these remote systems, towed-cameras are a practical and efficient method for mapping reefs (Barker et al, 1999;Carleton & Done, 1995;Carroll et al, 2020;Cruz-Marrero et al, 2019;Davis et al, 2019;Lembke et al, 2017) but diver-based collection of images along transects remain the standard for monitoring reefs, with demonstrated ability to capture changes through time at fine spatial scales.…”