A bayesian method for deriving species-sensitivity distributions: Selecting the best-fit tolerance distributions of taxonomic groups

Human and Ecological Risk Assessment

Volumn 16, Issue 2, 2010, Pages 251-263

  Hayashi, Takehiko I ^a   Kashiwagi, Nobuhisa ^b  

^a NATIONAL INSTITUTE FOR ENVIRONMENTAL STUDIES   (Japan)

^b INSTITUTE OF STATISTICAL MATHEMATICS   (Japan)

Author keywords

Bayesian statistics; Deviance Information Criterion; Ecological risk assessment; Model selection; Species sensitivity distribution

Indexed keywords

EID: 77950973127     PISSN: 10807039     EISSN: 15497860     Source Type: Journal    
DOI: 10.1080/10807031003670279     Document Type: Article

References (37)

1. Aldenberg T and Jaworska JS. 2000. Uncertainty of the hazardous concentration and proportion affected for normal species sensitivity distributions. Ecotoxicol Environ Saf 46:1-18.
2. Anderson DR, Burnham KP, and Thompson WL. 2000. Null hypothesis testing: Problems, prevalence, and an alternative. J Wildl Manag 64:912-23
3. Duboudin C, Ciffroy P, and Magaud H. 2004. Effects of data manipulation and statistical methods on species sensitivity distributions. Environ Toxicol Chem 23:489-99
4. EC (European Commission). 2003. Technical Guidance Document on Risk Assessment. European Chemicals Bureau, Ispara, Italy
5. Ellison AM. 1996. An introduction to Bayesian inference for ecological research and environmental decision-making. Ecol Appl 6:1036-46
6. Forbes VE and Calow P. 2002. Species sensitivity distribution revisited: A critical appraisal. Hum Ecol Risk Assess 8:473-92
7. Forbes TL and Forbes VE. 1993. A critique of the use of distribution-based extrapolation models in ecotoxicology. Funct Ecol 7:249-54
8. Gelman A and Rubin DB. 1992. Inference from iterative simulation using multiple sequences. Stat Sci 7:457-72
9. Gelman A, Carlin JB, Stern HS, et al. (eds). 2004. Bayesian Data Analysis. Lewis Publishers, Boca Raton, FL, USA
10. Grist EPM, Leung KMY, Wheelers JR, et al. 2002. Better bootstrap estimation of hazardous concentration threshold for aquatic assemblages. Environ Toxicol Chem 21:1515-24
11. Grist EPM, O'Hagan A, Crane M, et al. 2006. Bayesian and time-independent species sensitivity distribution for risk assessment of chemicals. Environ Sci Technol 40:395-401
12. Hayashi TI. 2007. Ecological risk assessment of chloroform in Japanese surface waters considering the difference in the reliability of ecotoxicological data. Australasian J Ecotoxicol 13:119-130
13. Hickey GL, Kefford BJ, Dunlop JE, et al. 2008. Making species salinity sensitivity distributions reflective of naturally occurring communities: Using rapid testing and Bayesian statistics. Environ Toxicol Chem 27:2403-11
14. Iino F, Takasuga T, Senthilkumar K, et al. 2005. Risk assessment of short-chain chlorinated paraffins in Japanese based on the first market basket study and sensitivity distribution. Environ Sci Tech 39:859-66
15. Lunn DJ, Thomas A, Best N, et al. 2000. WinBUGS-A Bayesian modeling framework: Concepts, structure, and extensibility. Stat Com 10:325-37
16. Nakanishi J and Ono K. 2008. Series of Detailed Risk Assessment 21: Chromium hexavalent. Maruzen, Tokyo, Japan (in Japanese)
17. Nakanishi J and Tsunemi K. 2005. Series of Detailed Risk Assessment 5: Short-chain Chlorinated Paraffins. Maruzen, Tokyo, Japan (in Japanese)
18. Nakanishi J and Tsunemi K. 2008. Series of Detailed Risk Assessment 19: Nickel. Maruzen, Tokyo, Japan (in Japanese)
19. Nakanishi J, Kobayashi N, and Naito K. 2006. Series of Detailed Risk Assessment 9: Lead. Maruzen, Tokyo, Japan (in Japanese)
20. Nakanishi J, Ono K, Gamo M, et al. 2007. Series of Detailed Risk Assessment 13: Cadmium. Maruzen, Tokyo, Japan (in Japanese)
21. Nakanishi J, Ishikawa Y, and Kawasaki H. 2008a. Series of detailed risk assessment 15: Chloroform. Maruzen, Tokyo, Japan (in Japanese)
22. Nakanishi J, Naito K, and Kamo M. 2008b. Series of Detailed Risk Assessment 20: Zinc. Maruzen, Tokyo, Japan (in Japanese)
23. Newman MC, Ownby DR, Mezin LCA, et al. 2000. Applying species-sensitivity distributions in ecological risk assessment: Assumptions of distribution type and sufficient numbers of species. Environ Toxicol Chem 19:508-15
24. OECD (Organisation for Economic Co-operation and Development). 1995. Guidance Document for Aquatic Effects Assessment. OECD Environment Monograph No. 92. Available at http://www.oecd.lorg/dataoecd/5/42/34290206.pdf
25. O'Hagan A, Crane M, Grist EPM, et al. 2005. Estimating Species Sensitivity Distributions with theAidofExpertJudgements. Report No. 556/05. Department of Probability and Statistics, University of Sheffield. Available at http://www.tonyohagan.co.uk/academic/pub.html
26. Posthuma L, Traas TP, and Suter GW II (eds). 2002. Species Sensitivity Distributions in Ecotoxicology. Lewis Publishers, Boca Raton, FL, USA
27. Qian SS, Schulman A, Koplos J, et al. 2004. A hierarchical modeling approach for estimation national distribution of chemicals in public drinking water systems. Environ Sci Technol 38:1176-82
28. R Development Core Team. 2007. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. Available at http://www.R-project.org/
29. Spigelhalter DJ, Best NG, Carlin BP, et al. 2002. Bayesian measures of model complexity and fit. J Roy Stat Soc B 64:583-639
30. Spiegelhalter DJ, Thomas A, Best N, et al. 2004. WinBUGS User Manual. Version 1.4.1. MRC Biostatistics Unit, Cambridge, UK
31. Suter GW (ed) 2006. Ecological Risk Assessment. CRC Press, Boca Raton, FL, USA
32. van Den Brink PJ, Blake N, Brock TCM, et al. 2006. Predictive value of species sensitivity distributions for effects of herbicides in freshwater ecosystems. Hum Ecol Risk Assess 12:645-74
33. van Der Hoeven N. 2000. Estimating the 5-percentile of the species sensitivity distribution without any assumptions about the distribution. Ecotoxicology 10:25-34
34. van Sprang SV, Verdonck FAM, Vanrolleghem PA, et al. 2004. Probabilistic environmental risk assessment of zinc in Dutch surface waters. Environ Toxicol Chem 23:2993-3002
35. van Straalen NM. 2002. Threshold models for species sensitivity distributions applied to aquatic risk assessment for zinc. Environ Toxicol Pharmacol 11:167-72
36. Verdonck FAM, Jaworska J, Thas O, et al. 2001. Determining environmental standards using bootstrapping, Bayesian and maximum likelihood techniques: A comparative study. Anal Chim Acta 446:429-38
37. Wheeler JR, Grist EPM, Leung KMY, et al. 2002. Species sensitivity distributions: Data and model choice. Mar Pollut Bull 45:192-202