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The New Seafloor Observatory (OBSEA) for Remote and Long-Term Coastal Ecosystem Monitoring

A suitable sampling technology to identify species and to estimate population dynamics based on individual counts at different temporal levels in relation to habitat variations is increasingly important for fishery management and biodiversity studies. In the past two decades, as interest in explorin...

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Autores principales: Aguzzi, Jacopo, Mànuel, Antoni, Condal, Fernando, Guillén, Jorge, Nogueras, Marc, del Rio, Joaquin, Costa, Corrado, Menesatti, Paolo, Puig, Pere, Sardà, Francesc, Toma, Daniel, Palanques, Albert
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Molecular Diversity Preservation International (MDPI) 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3231463/
https://www.ncbi.nlm.nih.gov/pubmed/22163931
http://dx.doi.org/10.3390/s110605850
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author Aguzzi, Jacopo
Mànuel, Antoni
Condal, Fernando
Guillén, Jorge
Nogueras, Marc
del Rio, Joaquin
Costa, Corrado
Menesatti, Paolo
Puig, Pere
Sardà, Francesc
Toma, Daniel
Palanques, Albert
author_facet Aguzzi, Jacopo
Mànuel, Antoni
Condal, Fernando
Guillén, Jorge
Nogueras, Marc
del Rio, Joaquin
Costa, Corrado
Menesatti, Paolo
Puig, Pere
Sardà, Francesc
Toma, Daniel
Palanques, Albert
author_sort Aguzzi, Jacopo
collection PubMed
description A suitable sampling technology to identify species and to estimate population dynamics based on individual counts at different temporal levels in relation to habitat variations is increasingly important for fishery management and biodiversity studies. In the past two decades, as interest in exploring the oceans for valuable resources and in protecting these resources from overexploitation have grown, the number of cabled (permanent) submarine multiparametric platforms with video stations has increased. Prior to the development of seafloor observatories, the majority of autonomous stations were battery powered and stored data locally. The recently installed low-cost, multiparametric, expandable, cabled coastal Seafloor Observatory (OBSEA), located 4 km off of Vilanova i la Gertrú, Barcelona, at a depth of 20 m, is directly connected to a ground station by a telecommunication cable; thus, it is not affected by the limitations associated with previous observation technologies. OBSEA is part of the European Multidisciplinary Seafloor Observatory (EMSO) infrastructure, and its activities are included among the Network of Excellence of the European Seas Observatory NETwork (ESONET). OBSEA enables remote, long-term, and continuous surveys of the local ecosystem by acquiring synchronous multiparametric habitat data and bio-data with the following sensors: Conductivity-Temperature-Depth (CTD) sensors for salinity, temperature, and pressure; Acoustic Doppler Current Profilers (ADCP) for current speed and direction, including a turbidity meter and a fluorometer (for the determination of chlorophyll concentration); a hydrophone; a seismometer; and finally, a video camera for automated image analysis in relation to species classification and tracking. Images can be monitored in real time, and all data can be stored for future studies. In this article, the various components of OBSEA are described, including its hardware (the sensors and the network of marine and land nodes), software (data acquisition, transmission, processing, and storage), and multiparametric measurement (habitat and bio-data time series) capabilities. A one-month multiparametric survey of habitat parameters was conducted during 2009 and 2010 to demonstrate these functions. An automated video image analysis protocol was also developed for fish counting in the water column, a method that can be used with cabled coastal observatories working with still images. Finally, bio-data time series were coupled with data from other oceanographic sensors to demonstrate the utility of OBSEA in studies of ecosystem dynamics.
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spelling pubmed-32314632011-12-07 The New Seafloor Observatory (OBSEA) for Remote and Long-Term Coastal Ecosystem Monitoring Aguzzi, Jacopo Mànuel, Antoni Condal, Fernando Guillén, Jorge Nogueras, Marc del Rio, Joaquin Costa, Corrado Menesatti, Paolo Puig, Pere Sardà, Francesc Toma, Daniel Palanques, Albert Sensors (Basel) Article A suitable sampling technology to identify species and to estimate population dynamics based on individual counts at different temporal levels in relation to habitat variations is increasingly important for fishery management and biodiversity studies. In the past two decades, as interest in exploring the oceans for valuable resources and in protecting these resources from overexploitation have grown, the number of cabled (permanent) submarine multiparametric platforms with video stations has increased. Prior to the development of seafloor observatories, the majority of autonomous stations were battery powered and stored data locally. The recently installed low-cost, multiparametric, expandable, cabled coastal Seafloor Observatory (OBSEA), located 4 km off of Vilanova i la Gertrú, Barcelona, at a depth of 20 m, is directly connected to a ground station by a telecommunication cable; thus, it is not affected by the limitations associated with previous observation technologies. OBSEA is part of the European Multidisciplinary Seafloor Observatory (EMSO) infrastructure, and its activities are included among the Network of Excellence of the European Seas Observatory NETwork (ESONET). OBSEA enables remote, long-term, and continuous surveys of the local ecosystem by acquiring synchronous multiparametric habitat data and bio-data with the following sensors: Conductivity-Temperature-Depth (CTD) sensors for salinity, temperature, and pressure; Acoustic Doppler Current Profilers (ADCP) for current speed and direction, including a turbidity meter and a fluorometer (for the determination of chlorophyll concentration); a hydrophone; a seismometer; and finally, a video camera for automated image analysis in relation to species classification and tracking. Images can be monitored in real time, and all data can be stored for future studies. In this article, the various components of OBSEA are described, including its hardware (the sensors and the network of marine and land nodes), software (data acquisition, transmission, processing, and storage), and multiparametric measurement (habitat and bio-data time series) capabilities. A one-month multiparametric survey of habitat parameters was conducted during 2009 and 2010 to demonstrate these functions. An automated video image analysis protocol was also developed for fish counting in the water column, a method that can be used with cabled coastal observatories working with still images. Finally, bio-data time series were coupled with data from other oceanographic sensors to demonstrate the utility of OBSEA in studies of ecosystem dynamics. Molecular Diversity Preservation International (MDPI) 2011-05-31 /pmc/articles/PMC3231463/ /pubmed/22163931 http://dx.doi.org/10.3390/s110605850 Text en © 2011 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).
spellingShingle Article
Aguzzi, Jacopo
Mànuel, Antoni
Condal, Fernando
Guillén, Jorge
Nogueras, Marc
del Rio, Joaquin
Costa, Corrado
Menesatti, Paolo
Puig, Pere
Sardà, Francesc
Toma, Daniel
Palanques, Albert
The New Seafloor Observatory (OBSEA) for Remote and Long-Term Coastal Ecosystem Monitoring
title The New Seafloor Observatory (OBSEA) for Remote and Long-Term Coastal Ecosystem Monitoring
title_full The New Seafloor Observatory (OBSEA) for Remote and Long-Term Coastal Ecosystem Monitoring
title_fullStr The New Seafloor Observatory (OBSEA) for Remote and Long-Term Coastal Ecosystem Monitoring
title_full_unstemmed The New Seafloor Observatory (OBSEA) for Remote and Long-Term Coastal Ecosystem Monitoring
title_short The New Seafloor Observatory (OBSEA) for Remote and Long-Term Coastal Ecosystem Monitoring
title_sort new seafloor observatory (obsea) for remote and long-term coastal ecosystem monitoring
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3231463/
https://www.ncbi.nlm.nih.gov/pubmed/22163931
http://dx.doi.org/10.3390/s110605850
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