Species non-exchangeability in probabilistic ecotoxicological risk assessment

Current ecotoxicological risk assessment for chemical substances is based on the assumption that tolerances of all species in a specified ecological community are a priori exchangeable for each new substance. We demonstrate non-exchangeability by using a large database of tolerances to pesticides fo...

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Bibliographic Details
Published in:Journal of the Royal Statistical Society. Series A, Statistics in society Statistics in society, 2012-01, Vol.175 (1), p.243-262
Main Authors: Craig, Peter S., Hickey, Graeme L., Luttik, Robert, Hart, Andy
Format: Article
Language:English
Subjects:
Applications
Assessment factors
Calculus of variations and optimal control
Chemicals
Ecological analysis
Ecological risk assessment
Ecology
Ecotoxicology
Environmental assessment
Environmental economics
Exact sciences and technology
Exchangeability
Food safety
General topics
Global analysis, analysis on manifolds
Mathematical analysis
Mathematics
Modelling
Parameter estimation
Parametric models
Probability
Probability and statistics
Risk assessment
Risk management
Sciences and techniques of general use
Species
Species sensitivity
Standard deviation
Statistical models
Statistics
Synecology
Topology. Manifolds and cell complexes. Global analysis and analysis on manifolds
Toxicology
Toxins
Uncertainty
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Summary:Current ecotoxicological risk assessment for chemical substances is based on the assumption that tolerances of all species in a specified ecological community are a priori exchangeable for each new substance. We demonstrate non-exchangeability by using a large database of tolerances to pesticides for fish species and extend the standard statistical model for species tolerances to allow for the presence of a single species which is considered non-exchangeable with others. We show how to estimate parameters and adjust decision rules that are used in ecotoxicological risk management. Effects of parameter uncertainty are explored and our model is compared with a previously published less tractable alternative. We conclude that the model and decision rules that we propose are pragmatic compromises between conflicting needs for more realistic modelling and for straightforwardly applicable decision rules.
ISSN:0964-1998
1467-985X
DOI:10.1111/j.1467-985X.2011.00716.x