Risk assessment using the species sensitivity distribution method: Data quality versus data quantity

Dowse, R; Tang, D; Palmer, CG; Kefford, BJ

Risk assessment using the species sensitivity distribution method: Data quality versus data quantity

Dowse, R

Tang, D Palmer, CG

Kefford, BJ

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Publication Type:: Journal Article
Citation:: Environmental Toxicology and Chemistry, 2013, 32 (6), pp. 1360 - 1369
Issue Date:: 2013-06-01

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Field	Value	Language
dc.contributor.author	Dowse, R https://orcid.org/0000-0003-2074-9943	en_US
dc.contributor.author	Tang, D	en_US
dc.contributor.author	Palmer, CG https://orcid.org/0000-0001-7349-1304	en_US
dc.contributor.author	Kefford, BJ https://orcid.org/0000-0001-6789-4254	en_US
dc.date.available	2013-01-21	en_US
dc.date.issued	2013-06-01	en_US
dc.identifier.citation	Environmental Toxicology and Chemistry, 2013, 32 (6), pp. 1360 - 1369	en_US
dc.identifier.issn	0730-7268	en_US
dc.identifier.uri	http://hdl.handle.net/10453/27454
dc.description.abstract	Species sensitivity distributions (SSDs) are cumulative distributions of measures of species sensitivity to a stressor or toxicant, and are used to estimate concentrations that will protect p% of a community (PCp). There is conflict between the desire to use high-quality sensitivity data in SSDs, and to construct them with a large number of species forming a representative sample. Trade-offs between data quality and quantity were investigated using the effects of increasing salinity on the macroinvertebrate community from the Hunter River catchment, in eastern Australia. Five SSDs were constructed, representing five points along a continuum of data quality versus data quantity and representativeness. This continuum was achieved by the various inclusion/exclusion of censored data, nonmodeled data, and extrapolation from related species. Protective concentrations were estimated using the Burr type III distribution, Kaplan-Meier survival function, and two Bayesian statistical models. The dominant taxonomic group was the prime determinant of protective concentrations, with an increase in PC95 values resulting from a decrease in the proportion of Ephemeropteran species included in the SSD. In addition, decreases in data quantity in a SSD decreased community representativeness. The authors suggest, at least for salinity, that the inclusion of right censored data provides a more representative sample of species that reflects the natural biotic assemblage of an area to be protected, and will therefore improve risk assessment. © 2013 SETAC.	en_US
dc.relation.ispartof	Environmental Toxicology and Chemistry	en_US
dc.relation.isbasedon	10.1002/etc.2190	en_US
dc.subject.classification	Environmental Sciences	en_US
dc.subject.mesh	Animals	en_US
dc.subject.mesh	Invertebrates	en_US
dc.subject.mesh	Hazardous Substances	en_US
dc.subject.mesh	Water Pollutants, Chemical	en_US
dc.subject.mesh	Models, Statistical	en_US
dc.subject.mesh	Bayes Theorem	en_US
dc.subject.mesh	Risk Assessment	en_US
dc.subject.mesh	Rivers	en_US
dc.subject.mesh	Environmental Monitoring	en_US
dc.subject.mesh	Species Specificity	en_US
dc.subject.mesh	Research Design	en_US
dc.subject.mesh	Australia	en_US
dc.subject.mesh	Salinity	en_US
dc.subject.mesh	Aquatic Organisms	en_US
dc.title	Risk assessment using the species sensitivity distribution method: Data quality versus data quantity	en_US
dc.type	Journal Article
utslib.citation.volume	6	en_US
utslib.citation.volume	32	en_US
utslib.for	0602 Ecology	en_US
utslib.for	03 Chemical Sciences	en_US
utslib.for	05 Environmental Sciences	en_US
utslib.for	06 Biological Sciences	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of the Environment
utslib.copyright.status	closed_access
pubs.issue	6	en_US
pubs.publication-status	Published	en_US
pubs.volume	32	en_US

Abstract:

Species sensitivity distributions (SSDs) are cumulative distributions of measures of species sensitivity to a stressor or toxicant, and are used to estimate concentrations that will protect p% of a community (PCp). There is conflict between the desire to use high-quality sensitivity data in SSDs, and to construct them with a large number of species forming a representative sample. Trade-offs between data quality and quantity were investigated using the effects of increasing salinity on the macroinvertebrate community from the Hunter River catchment, in eastern Australia. Five SSDs were constructed, representing five points along a continuum of data quality versus data quantity and representativeness. This continuum was achieved by the various inclusion/exclusion of censored data, nonmodeled data, and extrapolation from related species. Protective concentrations were estimated using the Burr type III distribution, Kaplan-Meier survival function, and two Bayesian statistical models. The dominant taxonomic group was the prime determinant of protective concentrations, with an increase in PC95 values resulting from a decrease in the proportion of Ephemeropteran species included in the SSD. In addition, decreases in data quantity in a SSD decreased community representativeness. The authors suggest, at least for salinity, that the inclusion of right censored data provides a more representative sample of species that reflects the natural biotic assemblage of an area to be protected, and will therefore improve risk assessment. © 2013 SETAC.

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http://hdl.handle.net/10453/27454