Estimation of no effect concentrations from exposure experiments when values scatter among individuals

• Published in: Ecological modelling 2009-02, Vol.220 (3), p.411-418
• Main Authors: Baas, J., Jager, T., Kooijman, S.A.L.M.
• Format: Article
• Language: English
• Subjects: Animal, plant and microbial ecology; Applied ecology; Biological and medical sciences; Ecotoxicology, biological effects of pollution; Fundamental and applied biological sciences. Psychology; General aspects. Techniques; Individual tolerance distribution; Methods and techniques (sampling, tagging, trapping, modelling...); Monte Carlo simulation; No effect concentration; Survival; Toxicity
• ISSN: 0304-3800; 1872-7026
• DOI: 10.1016/j.ecolmodel.2008.10.008

The parameters that are most commonly used in risk assessment, LC x values or no observed effect concentrations, both have serious drawbacks. As an alternative, No effect concentrations (NEC) as a parameter in a process-based model, offer great potential in risk assessment. So far estimates of the NEC assume that all individuals have the same NEC, but it is to be expected that organism differ in their physiology and therefore individuals in a cohort do not all have the same value for the NEC. We investigated how much variation in the NEC is allowed before an estimate of a NEC from a survival experiment fails. We therefore assumed that each individual organism has its own NEC, drawn independently from a log-normal distribution around a mean NEC. In addition we also investigated if the standard deviation in the log-normal distribution itself could be estimated from a survival experiment. It showed that for a wide range of individual differences in the NEC the estimates of the NEC are accurate and precise. Only if the differences between individuals become much larger than what could be derived from survival experiments reported in the open literature the estimated NEC becomes unreliable. The standard deviation in the log-normal distribution of the NEC can also be estimated but with a high uncertainty. When a standard model is used where all exposed individuals have the same NEC on data where there is a different NEC for individuals, the NEC can still be estimated with high accuracy and precision.