Effects of dissolved organic carbon concentration and source, pH, and water hardness on chronic toxicity of copper to Daphnia magna
De Schamphelaere, K.A.C.; Janssen, C.R. (2004). Effects of dissolved organic carbon concentration and source, pH, and water hardness on chronic toxicity of copper to Daphnia magna. Environ. Toxicol. Chem. 23(5): 1115-1122. https://dx.doi.org/10.1897/02-593
In: Environmental Toxicology and Chemistry. Setac Press: New York. ISSN 0730-7268; e-ISSN 1552-8618, more
The effects of pH (5.3-8.7), water hardness (CaCO, at 25-500 mg/L), dissolved organic carbon (DOC) concentration (1.6-18.4 mg/L), and DOC source on the chronic toxicity of copper to Daphnia magna were investigated by using a multifactorial, central composite test design. Natural dissolved organic matter (DOM) was collected at three sites in Belgium and The Netherlands by using reverse osmosis. For a total number of 35 toxicity tests performed, 21-d no-observed-effect concentrations (NOECs) of copper based on reproduction ranged from 29.4 to 228 μg/L and 21-d concentrations of copper causing 50% reduction of reproduction (EC50s) ranged from 41.5 to 316 μg/L. Statistical analysis revealed that DOC concentration and pH had a significant effect on copper toxicity but hardness (at the levels tested) did not. In general, an increase in pH or DOC resulted in a linear increase of 21-d NOEC and EC50 values. All DOMs (originating from three different sources) reduced copper toxicity to the same extent. Multiple linear regression analysis on the results of all 35 toxicity tests revealed that DOC concentration is the most important factor for chronic toxicity of copper to D. magna, explaining about 60% of the observed variability, whereas pH only explained about 15% of the observed variability. Regression models were developed (with DOC and pH as parameters) that were capable of predicting NOECs and EC50s within a factor of 1.9 from observed NOEC and EC50 values obtained with eight natural surface waters spiked with copper. Until future research further elucidates the mechanisms underpinning the observed bioavailability relations, these empirical regression models can become a first simple tool for regulatory applications.
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