Environmental factors as predictors of epibenthic assemblage biomass in the St. Lawrence system

• Published in: Estuarine, coastal and shelf science Vol. 57; no. 4; pp. 641 - 652
• Main Authors: Bourget, E, Ardisson, P.-L, Lapointe, L, Daigle, G
• Format: Journal Article
• Language: English
• Published: London Elsevier Ltd 01.07.2003; Elsevier
• Subjects: Animal and plant ecology; Animal, plant and microbial ecology; Arctica; Balanus crenatus; benthos; Biological and medical sciences; biomass; Brackish water ecosystems; environmental conditions; Fundamental and applied biological sciences. Psychology; Gulf of St. Lawrence; Hiatella arctica; Marine; Mytilus edulis; Obelia longissima; scales; Sea water ecosystems; Semibalanus balanoides; spatial distribution; St. Lawrence Estuary; Synecology; North Atlantic; Gulf of Saint Lawrence; Atlantic Ocean; Saint Lawrence Estuary; ANW, Canada, Quebec, St. Lawrence Estuary; Gulf of St. Lawrence; models; biomass; benthos; scales; St. Lawrence Estuary; environmental conditions; spatial distribution; Brackish water environment; Temperature; Transparency; Fauna; Environmental factor; Zoobenthos; Biomass; Epifauna; Spatial variation; Marine environment; Regression model; Sessile; Invertebrata
• ISSN: 0272-7714; 1096-0015
• DOI: 10.1016/S0272-7714(02)00404-3

The distribution of epibenthic invertebrate biomass in relation to environmental factors was examined in the St. Lawrence system. Biomass estimates for epibenthos sampled yearly for 9 years on 102 suspended collectors (navigation buoys), were related to environmental data from the literature (surface water temperature, water salinity, water transparency, current velocity, chlorophyll a and primary production) using a weighted multiple linear regression analysis. Regression models were generated for total biomass and the biomass of the single dominant sessile species: Mytilus edulis, Semibalanus balanoides, Balanus crenatus, Obelia longissima and Hiatella arctica. Water temperature and water transparency, as well as some biogeographic groups of buoys represented by dummy variables, collectively explained 90.6% of the variance in total biomass. Water temperature, water transparency, biogeographic groups and, to a lesser degree, primary production, were the variables having a significant influence on the biomass of individual species. The lognormal weighted multiple regression model explained up to 84.5% of the variance in M. edulis biomass data and 67.9, 70.0, 71.6 and 38.9%, respectively, of the variance in S. balanoides, O. longissima, B. crenatus and H. arctica biomass data. The need to consider simultaneous biological and environmental sampling at the relevant temporal and spatial scales to model large marine coastal ecosystems is discussed.