Research Article: 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

Date Published: May 2, 2019

Publisher: Public Library of Science

Author(s): Wilmelie Cruz-Marrero, Daniel W. Cullen, Najja R. Gay, Bradley G. Stevens, Antonio Medina Guerrero.

http://doi.org/10.1371/journal.pone.0215966

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 km2 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-1s. 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.

Partial Text

The construction of offshore wind turbines may significantly impact Mid-Atlantic benthic ecosystems. For example, wind farms have caused changes in commercial vessel routes [1], fish communities [2], and marine mammal foraging behavior [3]. Additionally, the presence of wind farms in certain areas may result in losses of habitat for some sea birds and disrupt marine mammal migration patterns [4,5]. Other known effects on the environment include wave transformations [6], and electromagnetic impacts [4]. Conversely, in addition to providing an alternative energy source and reducing greenhouse gas emissions, the base of windmill, the cable and associated rocks around the structures may serve as artificial reefs, and could enhance the settlement of aquatic species both native and non-native species [4,7,8,9,10].

Scientific collection permit for this research was granted from the Maryland Department of Natural Resources Fisheries Service in 2014 under Permit Number SCP201406.

In the present study, estimates of epibenthic diversity produced by systematic sampling using a camera sled became consistent at a sampling interval of 30 frames, and at sampling intervals of 24 to 30 frames for random sampling. Based on these results, we concluded that unbiased estimates of diversity could be obtained by sampling all of the remaining image files at intervals of 30 frames. At a rate of 5 frames/s, the CamSled produces 300 photographic frames/min, or 18,000 frames per hour, and most Transects lasted from 60–90 min. When sampled at intervals of 30 frames, a one-hour Transect would produce 600 sampled frames. This meant examining 1 frame every 6 s. These results are likely specific to our data, since sampling intervals of 24 to 30 frames were derived from specific sample sizes of 316−398 frames. Different data sets might require smaller or larger samples, and consequently, different sampling intervals. Additionally, some sections of Transects were not photographed due to equipment failures, or were photographed but could not be counted due to poor image quality. This is the case for Transects 2 and 4 which produced a total of 974 and 1016 frames. Subsampling those transects at 30-frame intervals produced less than 316 frames, which could have affected the precision of diversity indices. Subsequent modifications have improved reliability of the CamSled considerably. Although time codes were recorded on the photographs taken for Transects 5−7, they were not recorded for Transects 1−4 due to technical issues. For this reason, we could not subdivide the Transects into smaller samples for comparison to beam trawl samples. Thus we concluded that estimates of organism abundance or density from our data would have been inaccurate.

 

Source:

http://doi.org/10.1371/journal.pone.0215966

 

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