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Predicting the probability of detecting organochlorine pesticides and polychlorinated biphenyls in stream systems on the basis of land use in the Pacific Northwest, USA
Author(s) -
Black Robert W.,
Haggland Alan L.,
Voss Frank D.
Publication year - 2000
Publication title -
environmental toxicology and chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.1
H-Index - 171
eISSN - 1552-8618
pISSN - 0730-7268
DOI - 10.1002/etc.5620190434
Subject(s) - sediment , environmental science , pesticide , fish <actinopterygii> , drainage basin , organochlorine pesticide , hydrology (agriculture) , fishery , environmental chemistry , ecology , biology , geography , geology , chemistry , paleontology , cartography , geotechnical engineering
We analyzed streambed sediment and fish tissue ( Cottus sp.) at 30 sites in the Puget Sound and Willamette basins in Washington and Oregon, USA, respectively, for organochlorine pesticides and polychlorinated biphenyls (PCBs). The study was designed to determine the concentrations of organochlorine pesticides and PCBs in fish tissue and sediment by land use within these basins and to develop an empirical relation between land use and the probability of detecting these compounds in fish tissue or sediment. We identified 14 organochlorines in fish tissue and sediment; three compounds were unique to either fish tissue or sediment samples. The highest number of organochlorines detected in both fish tissue and streambed sediment was at those sites located in watersheds dominated by urban land uses. Using logistic regression, we found a significant relation between percentage agriculture and urban land use and organochlorines in fish tissue. The results of this study indicate that organochlorine pesticides and PCBs are still found in fish tissues and bed sediments in these two basins. In addition, we produced statistically significant models capable of predicting the probability of detecting specific organochlorines in fish on the basis of land use. Although the presented models are specific to the two study basins, the modeling approach could be applied to other basins as well.