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Biomonitoring aquatic pollution with feral ell (Anguilla Anguilla). III. Statistical analyses of relationships between contaminant exposure and biomarkers
- Source :
- Aquatic Toxicology, 39, 45-75, van der Oost, R, Vindimian, E, van den Brink, P J, Satumalay, K, Heida, H & Vermeulen, N P E 1997, ' Biomonitoring aquatic pollution with feral ell (Anguilla Anguilla). III. Statistical analyses of relationships between contaminant exposure and biomarkers. ', Aquatic Toxicology, vol. 39, pp. 45-75 . https://doi.org/10.1016/S0166-445X(96)00851-X, Aquatic Toxicology, 39, 45-75. Elsevier, Aquatic Toxicology 39 (1997)
- Publication Year :
- 1997
- Publisher :
- Elsevier, 1997.
-
Abstract
- In a large-scale field study, sediments and eel ( Anguilla anguilla ) samples were collected from six Amsterdam freshwater sites with varying degrees of pollution. All sediment and eel samples were analyzed for organic trace pollutants, such as polychlorinated biphenyls (PCBs), organochlorine pesticides (OCPs) and polycyclic aromatic hydrocarbons (PAHs). In addition, the pollution-induced responses of a suite of 21 biochemical parameters in eel (notably phase I and phase II biotransformation enzymes, antioxidant enzymes, PAH metabolites, DNA adducts and serum transaminases) were measured. The resulting comprehensive database was subjected to statistical analyses in order to determine the biomarkers which were most suitable to assess inland water pollution and to classify the environmental quality of the sites. Bivariate correlation analysis, principal component analysis (PCA) and residual maximum likelihood analysis (REML) all revealed that the eel tissue levels of most PCB and OCP analyte groups were suitable to assess exposure to these contaminants, whereas PAH tissue levels were not. The phase I biotransformation enzymes in eel were found to be the most responsive to organic pollutants in the environment. Phase II enzymes and cofactors, as well as DNA adducts, were found to be less sensitive biomarkers, whereas the antioxidant enzymes and the serum transaminases did not show statistically significant correlations with pollutant levels. Similar results were obtained by means of the postulated bivariate correlation-significance index (CSI) and the multivariate PCA analysis. Discriminant analysis (DA) was used to classify the pollution status of the various sites. It appeared that the best discrimination between reference sites, moderately polluted sites and heavily polluted sites was obtained using DA on data of the nine most responsive biochemical markers. The importance of monitoring biota for the classification of the pollution status or environmental quality of freshwater sites was demonstrated in the present study, since no clear discrimination between moderately and heavily polluted sites could be made using sediment pollutant levels only. The results indicate that biological effect monitoring is the only appropriate method providing a reliable environmental risk assessment.
- Subjects :
- Pollution
Multivariate analyses (PCA, DA)
Health, Toxicology and Mutagenesis
media_common.quotation_subject
Winand Staring Centre for Integrated Land, Soil and Water Research
Soil and Water Research
DA)
Aquatic Science
Biology
Biotransformation
Feral eel (Anguilla anguilla)
Staring Centrum
Biomonitoring
Multivariate analyses (PCA
Uni- and bivariate correlation analyses
SDG 14 - Life Below Water
Water pollution
media_common
Pollutant
Biota
Contamination
Environmental risk assessment
REML analysis
Bioaccumulation
Environmental chemistry
Winand Staring Centre for Integrated Land
Organic trace pollutants
SDG 6 - Clean Water and Sanitation
Biomarkers
Subjects
Details
- Language :
- English
- ISSN :
- 18791514 and 0166445X
- Volume :
- 39
- Database :
- OpenAIRE
- Journal :
- Aquatic Toxicology
- Accession number :
- edsair.doi.dedup.....8f91aad2cba65fa98619fbd3cc5af02f