FN Archimer Export Format
PT J
TI Modelling spatial distribution of epibenthic communities in the Gulf of St. Lawrence (Canada)
BT 
AF MORITZ, Charlotte
   LEVESQUE, Melanie
   GRAVEL, Dominique
   VAZ, Sandrine
   ARCHAMBAULT, Diane
   ARCHAMBAULT, Philippe
AS 1:1;2:1;3:2;4:3;5:4;6:1;
FF 1:;2:;3:;4:PDG-RBE-HMMN-RHBL;5:;6:;
C1 Univ Quebec, Inst Sci Mer, Rimouski, PQ G5L 3A1, Canada.
   Univ Quebec, Rimouski, PQ G5L 3A1, Canada.
   French Res Inst Exploitat Sea, IFREMER, Channel & North Sea Fisheries Unit, F-62321 Boulogne Sur Mer, France.
   Fisheries & Oceans Canada, Inst Maurice Lamontagne, Mont Joli, PQ G5H 3Z4, Canada.
C2 UNIV QUEBEC (UQAR), CANADA
   UNIV QUEBEC (UQAR), CANADA
   IFREMER, FRANCE
   MPO, CANADA
SI BOULOGNE
SE PDG-RBE-HMMN-RHBL
IN WOS Ifremer jusqu'en 2018
   copubli-int-hors-europe
IF 1.855
TC 17
UR https://archimer.ifremer.fr/doc/00138/24972/23997.pdf
LA English
DT Article
DE ;Biodiversity;Epibenthic Communities;Estuary and Northern Gulf of St. Lawrence;Generalized Linear Model;Community Distribution Model;Redundancy Analysis
AB 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. (C) 2012 Elsevier B.V. All rights reserved.
PY 2013
PD APR
SO Journal Of Sea Research
SN 1385-1101
PU Elsevier Science Bv
VL 78
UT 000316583400008
BP 75
EP 84
DI 10.1016/j.seares.2012.10.009
ID 24972
ER

EF