Modeling relationships between Baltic Sea herring (Clupea harengus) biology and contaminant concentrations using multivariate data analysis.
Baltic Sea herring (Clupea harengus) is a pelagic, zoo-planktivorous fish and young (2-5 years old) individuals of this species are sampled annually in the Swedish marine monitoring program. This study determined concentrations of organochlorines (OCs) and brominated flame retardants (BFRs) in dorsal muscle from herring (n = 60) of varying age (2-13 years), weight (25-200 g), and body length (16-29 cm) caught at three locations in the Swedish part of the Baltic Proper. In order to ensure that the fish biology was as varied as possible, though still similar from all sampling sites, the fish to be chemically analyzed were selected from a large number of fish with determined biology using Multivariate Design. In statistical evaluation of the data, univariate and multivariate data analysis techniques, e.g. principal components analysis (PCA), partial least-squares regression (PLS), and orthogonal PLS (OPLS), were used. The results showed that the fish are exposed to a cocktail of contaminants and levels are presented. Significant OPLS models were found for all biological variables versus concentrations of OCs and BFRs, showing that fish biology covaries with fish contaminant concentrations. Correlation coefficients were as high as 0.98 for e.g. βHCH concentration (wet weight) versus the lipid content. Lastly, the OC concentrations in herring muscle were modeled against the BFR concentrations to determine whether concentrations of either could be used to predict the other. It was found that OPLS models allowed BFR concentrations to be predicted from OC concentrations with high, but varying, accuracy (R(2)Ys between 0.93 to 0.75). Thus, fish biology and contaminant concentrations are interwoven, and fish biological parameters can be used to calculate (predict) contaminant concentrations. It is also possible to predict the BFR concentrations in an individual fish from its concentrations of OCs with very high accuracy.
Environmental Toxicology, Department of Organismal Biology, Evolutionary Biology Centre, Uppsala University, Norbyvägen 18A, SE-752 36, Sweden. katrin.lundstedt-enkel@ebc.uu.se
Katrin
K
Lundstedt-Enkel
Rickard
R
Bjerselius
Lillemor
L
Asplund
Kerstin
K
Nylund
Yang
Y
Liu
Mathias
M
Södervall
D000818:Animals; D017605:Bromine Compounds / Q000378:metabolism; D004784:Environmental Monitoring; D005399:Fishes / Q000378:metabolism*; D005411:Flame Retardants / Q000378:metabolism*; D006843:Hydrocarbons, Chlorinated / Q000378:metabolism*; D008954:Models, Biological; D015999:Multivariate Analysis; D009132:Muscles / Q000378:metabolism; D014874:Water Pollutants, Chemical / Q000378:metabolism*; D014877:Water Pollution, Chemical / Q000706:statistics & numerical data
D017605:Bromine Compounds; D005411:Flame Retardants; D006843:Hydrocarbons, Chlorinated; D014874:Water Pollutants, Chemical