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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

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 impact...

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Detalles Bibliográficos
Autores principales: Cruz-Marrero, Wilmelie, Cullen, Daniel W., Gay, Najja R., Stevens, Bradley G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6497279/
https://www.ncbi.nlm.nih.gov/pubmed/31048909
http://dx.doi.org/10.1371/journal.pone.0215966
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author Cruz-Marrero, Wilmelie
Cullen, Daniel W.
Gay, Najja R.
Stevens, Bradley G.
author_facet Cruz-Marrero, Wilmelie
Cullen, Daniel W.
Gay, Najja R.
Stevens, Bradley G.
author_sort Cruz-Marrero, Wilmelie
collection PubMed
description 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.
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spelling pubmed-64972792019-05-17 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 Cruz-Marrero, Wilmelie Cullen, Daniel W. Gay, Najja R. Stevens, Bradley G. PLoS One Research Article 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. Public Library of Science 2019-05-02 /pmc/articles/PMC6497279/ /pubmed/31048909 http://dx.doi.org/10.1371/journal.pone.0215966 Text en © 2019 Cruz-Marrero et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Cruz-Marrero, Wilmelie
Cullen, Daniel W.
Gay, Najja R.
Stevens, Bradley G.
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
title 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
title_full 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
title_fullStr 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
title_full_unstemmed 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
title_short 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
title_sort 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
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6497279/
https://www.ncbi.nlm.nih.gov/pubmed/31048909
http://dx.doi.org/10.1371/journal.pone.0215966
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