MoritzLevesqueGravelEtAl2013

Référence

Moritz, C., Levesque, M., Gravel, D., Vaz, S., Archambault, D. and Archambault, P. (2013) Modelling spatial distribution of epibenthic communities in the Gulf of St. Lawrence (Canada). Journal of Sea Research, 78:75-84. (Scopus )

Résumé

Correlative habitat models using relationships between marine organisms and their surrounding environment can be used to predict species distribution, and the results can assist management of human activities sharing the marine space (e.g. fisheries, MPAs, tourism). Here, epi-benthic megafauna was sampled at 755 stations in the Lower Estuary and Northern Gulf of St. Lawrence (EGSL) each summer between 2006 and 2009. We combined various types of multivariate analyses to 1) describe the structure and spatial distribution of benthic communities, 2) analyse the relationship between these communities and environmental parameters, and subsequently 3) build a community distribution model to predict the spatial distribution of the communities, creating community distribution maps covering the entire area to be used for marine management and conservation. We identified distinct benthic communities in the study area that closely correlate with the 200. m depth contour and with major environmental variables. A redundancy analysis revealed that communities were associated with depth, oxygen saturation, temperature, bottom current, seabed uniformity, distance to coast and type of sediment. Together these environmental descriptors explained 38% of the variation in megafaunal community composition. The environmental variables were used to build a community distribution model using generalized linear models to predict high and low suitability zones of each community in the EGSL. © 2012 Elsevier B.V.

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@ARTICLE { MoritzLevesqueGravelEtAl2013,
    AUTHOR = { Moritz, C. and Levesque, M. and Gravel, D. and Vaz, S. and Archambault, D. and Archambault, P. },
    TITLE = { Modelling spatial distribution of epibenthic communities in the Gulf of St. Lawrence (Canada) },
    JOURNAL = { Journal of Sea Research },
    YEAR = { 2013 },
    VOLUME = { 78 },
    PAGES = { 75-84 },
    NOTE = { cited By 3 },
    ABSTRACT = { Correlative habitat models using relationships between marine organisms and their surrounding environment can be used to predict species distribution, and the results can assist management of human activities sharing the marine space (e.g. fisheries, MPAs, tourism). Here, epi-benthic megafauna was sampled at 755 stations in the Lower Estuary and Northern Gulf of St. Lawrence (EGSL) each summer between 2006 and 2009. We combined various types of multivariate analyses to 1) describe the structure and spatial distribution of benthic communities, 2) analyse the relationship between these communities and environmental parameters, and subsequently 3) build a community distribution model to predict the spatial distribution of the communities, creating community distribution maps covering the entire area to be used for marine management and conservation. We identified distinct benthic communities in the study area that closely correlate with the 200. m depth contour and with major environmental variables. A redundancy analysis revealed that communities were associated with depth, oxygen saturation, temperature, bottom current, seabed uniformity, distance to coast and type of sediment. Together these environmental descriptors explained 38% of the variation in megafaunal community composition. The environmental variables were used to build a community distribution model using generalized linear models to predict high and low suitability zones of each community in the EGSL. © 2012 Elsevier B.V. },
    AUTHOR_KEYWORDS = { Biodiversity; Community Distribution Model; Epibenthic Communities; Estuary and Northern Gulf of St. Lawrence; Generalized Linear Model; Redundancy Analysis },
    DOCUMENT_TYPE = { Article },
    DOI = { 10.1016/j.seares.2012.10.009 },
    KEYWORDS = { aquatic organism; benthos; community structure; conservation management; ecological modeling; estuarine environment; human activity; linearity; numerical model; oxygen; spatial distribution; temperature effect, Atlantic Ocean; Gulf of Saint Lawrence },
    SOURCE = { Scopus },
    URL = { http://www.scopus.com/inward/record.url?eid=2-s2.0-84875236285&partnerID=40&md5=1e071aebbd5c3632854b28cb64dba2c0 },
}

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