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Provedor de dados:  ArchiMer
País:  France
Título:  Optimization of sampling, cell collection and counting for the monitoring of benthic harmful algal blooms: Application to Ostreopsis spp. blooms in the Mediterranean Sea
Autores:  Jauzein, Cecile
Acaf, Laury
Accoroni, Stefano
Asnaghi, Valentina
Fricke, Anna
Hachani, Mohamed Amine
Saab, Marie Abboud-abi
Chiantore, Mariachiara
Mangialajo, Luisa
Totti, Cecilia
Zaghmouri, Imen
Lemee, Rodolphe
Data:  2018-08
Ano:  2018
Palavras-chave:  Patchiness
Macrophyte substrate
Artificial substrate
Recommendations for monitoring
Resumo:  Toxic blooms of Ostreopsis spp. are greatly challenging to monitor due to the complexity and variability of cell repartition among benthic and pelagic compartments. This results in marked differences in employed methodologies for the survey of their dynamics and hampers the definition of the associated toxic risk. The present study aims at testing and improving common methodologies used for sampling, processing and counting of field samples. It contributes to the identification of the most suitable strategies for the monitoring and mitigation of Ostreopsis blooms in coastal waters. For a sampling based on the collection of macrophytes, the role of the fixative addition and of agitation steps in the efficiency of epiphytic cell collection was defined. For planktonic estimations, the influence of the volume used for concentrating water samples was characterized as a function of Ostreopsis cell abundance. The deployment of artificial substrates was tested and confirmed strong advantages of this new sampling methodology, including an integration of a part of the spatial and temporal variability of the cell distribution.
Tipo:  Text
Idioma:  Inglês
Identificador:  https://archimer.ifremer.fr/doc/00436/54714/56188.pdf

DOI:10.1016/j.ecolind.2018.03.089

https://archimer.ifremer.fr/doc/00436/54714/
Editor:  Elsevier Science Bv
Formato:  application/pdf
Fonte:  Ecological Indicators (1470-160X) (Elsevier Science Bv), 2018-08 , Vol. 91 , P. 116-127
Direitos:  2018 Elsevier Ltd. All rights reserved.

info:eu-repo/semantics/openAccess

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