Approaches for establishing predicted-no-effect concentrations for population-level ecological risk assessment in the context of chemical substances management |
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Authors: | Lin Bin-Le Tokai Akihiro Nakanishi Junko |
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Affiliation: | Research Center for Chemical Risk Management, National Institute of Advanced Industrial Science and Technology, 16-1 Onogawa, Tsukuba, Ibaraki Prefecture 305-8569, Japan. binle-lin@aist.go.jp |
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Abstract: | The establishment of rational frameworks for population-level ecological risk assessment (PLERA) in the context of chemical substances management is an important issue. We illustrate two feasible approaches for establishing predicted-no-effect concentrations (PNECs)for PLERA through a case study of 4-nonylphenol (4-NP) using life-cycle toxicity data for medaka (Oryzias latipes). We first quantified the potential impacts of 4-NP on medaka in terms of reduction of population growth rate (i). An age-classified population matrix model (daily time-step) was developed and used to combine life-cycle survivorship and fecundity data obtained from individual-level responses of medaka expDsed to 4-NP into population-level responses defined by the parameter lambda. Thereafter, from the resulting lambdas, two approaches for establishing population-level PNEC values were proposed and examined. We then derived the PNEC values for population-level impacts, based on (a) the threshold concentration, defined as the chemical concentration at which lambda = 1 as a value with a 95% confidence interval, and (b) the no-observed-effect concentration (NOEC) and the maximum-acceptable-toxic concentration (MATC). The results suggest that PNEC values of 4-NP ranging between 0.82 and 2.10 microg/L affect medaka population growth. Although these approaches have their limitations, current knowledge indicates that they are reasonable and practical for evaluating population-level impacts of chemicals, thereby serving as a case study for establishing PNEC values for PLERA in the context of chemical substances management and decision-making. |
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