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

被引:9
作者
Baas, J. [1 ]
Jager, T. [1 ]
Kooijman, S. A. L. M. [1 ]
机构
[1] Vrije Univ Amsterdam, Dept Theoret Biol, NL-1081 HV Amsterdam, Netherlands
关键词
No effect concentration; Monte Carlo simulation; Toxicity; Survival; Individual tolerance distribution; MODELS; ECOTOXICOLOGY; STATISTICS; BIOASSAYS;
D O I
10.1016/j.ecolmodel.2008.10.008
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
The parameters that are most commonly used in risk assessment, LCx 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. (C) 2008 Elsevier B.V. All rights reserved.
引用
收藏
页码:411 / 418
页数:8
相关论文
共 39 条
[1]  
ALDRIDGE WN, 1986, ANNU REV PHARMACOL, V26, P39
[2]   The influence of design characteristics on statistical inference in nonlinear estimation: A simulation study based on survival data and hazard modeling [J].
Andersen, JS ;
Bedaux, JJM ;
Kooijman, SALM ;
Holst, H .
JOURNAL OF AGRICULTURAL BIOLOGICAL AND ENVIRONMENTAL STATISTICS, 2000, 5 (03) :323-341
[3]  
[Anonymous], 146441 ISO
[4]  
[Anonymous], 2018, Generalized linear models
[5]  
Ashauer R, 2008, ENVIRON TOXICOL CHEM, V27, P1817, DOI 10.1897/07-642
[6]   Approaches for linking whole-body fish tissue residues of mercury or DDT to biological effects thresholds [J].
Beckvar, N ;
Dillon, TM ;
Read, LB .
ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY, 2005, 24 (08) :2094-2105
[7]   Statistical analysis of bioassays, based on hazard modelling [J].
Bedaux, J. J. M. ;
Kooijman, S. A. L. M. .
ENVIRONMENTAL AND ECOLOGICAL STATISTICS, 1994, 1 (04) :303-314
[8]  
Brooke L.T., 1984, Acute toxicities of organic chemicals to fathead minnows Pimephales promelas
[9]   A warning: NOECs are inappropriate for regulatory use [J].
Chapman, PM ;
Caldwell, RS ;
Chapman, PF .
ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY, 1996, 15 (02) :77-79
[10]  
CHEN CW, 1969, J WATER POLLUT CON F, V41, pR294