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Influence of the choice of physical and chemistry variables on interpreting patterns of sediment contaminants and their relationships with estuarine macrobenthic communities
53
Citations
30
References
2010
Year
Ecological ResponseEngineeringMetal ContaminationMetal ExtractionOrganic GeochemistryEnvironmental ChemistryEstuarine Macrobenthic CommunitiesMetalloid ContaminationBioremediationMarine PollutionManagementSediment AnalysisChemistry VariablesBiogeochemistrySediment QualitySediment-water InteractionTrace MetalWater QualityEcotoxicologyEnvironmental Risk AssessmentSedimentologySediment TransportEstuarine GeochemistrySediment ContaminantsEnvironmental ToxicologyEnvironmental AnalysisEstuaryCarbon Normalisation
A primary objective of contaminated sediment risk assessments is to identify if contaminant enrichment is eliciting an ecological response. Using complementary environmental and biotic datasets, we examined five scenarios with respect to: dataset complexity; metal extraction; normalisation of organics; the inclusion/exclusion of acid-volatile sulfide data, and iron and manganese concentrations. Spatial distributions of abiotic variables were examined by principal components analysis, with canonical correspondence analysis used to examine the total and partitioning of biological variation. Metals were the dominant contaminant and explained the largest proportion of variation in the macrobenthic data. Extraction procedure and carbon normalisation of organics had little influence on the overall analysis. Porewater metal data was essential for interpretation, with excess of acid-volatile sulfide over simultaneously extractable metals being a poor surrogate. In the canonical correspondence analyses, the inclusion of Fe/Mn accentuated the covariation between the ecological and contaminant variables. Multimodel comparisons aided interpretation by emphasising specific relationships among environmental variables and their interactions with the biotic data. Furthermore, for future examinations of the described system, the findings can be used to reduce the collection of redundant environmental variables or variables that are poorly correlated with changes in macrobenthic assemblages.
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