Making Species Salinity Sensitivity Distributions Reflective Of Naturally Occurring Communities: Using Rapid Testing And Bayesian Statistics

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dc.contributor.author Hickey, Gl en_US
dc.contributor.author Dunlop, J en_US
dc.contributor.author Craig, Ps en_US
dc.contributor.author Kefford, Ben en_US
dc.contributor.editor en_US
dc.date.accessioned 2011-02-07T06:25:05Z
dc.date.available 2011-02-07T06:25:05Z
dc.date.issued 2008 en_US
dc.identifier 2009006145 en_US
dc.identifier.citation Hickey Gl et al. 2008, 'Making Species Salinity Sensitivity Distributions Reflective Of Naturally Occurring Communities: Using Rapid Testing And Bayesian Statistics', Soc Environmental Toxicology & Chemistry-Setac, vol. 27, no. 11, pp. 2403-2411. en_US
dc.identifier.issn 0730-7268 en_US
dc.identifier.other C1UNSUBMIT en_US
dc.identifier.uri http://hdl.handle.net/10453/13832
dc.description.abstract Species sensitivity distributions (SSDs) may accurately predict the proportion of species in a community that are at hazard from environmental contaminants only if they contain sensitivity data from a large sample of species representative of the mix of species present in the locality or habitat of interest. With current widely accepted ecotoxicological methods, however, this rarely occurs. Two recent suggestions address this problem. First, use rapid toxicity tests, which are less rigorous than conventional tests, to approximate experimentally the sensitivity of many species quickly and in approximate proportion to naturally occurring communities. Second, use expert judgements regarding the sensitivity of higher taxonomic groups (e. g., orders) and Bayesian statistical methods to construct SSDs that reflect the richness (or perceived importance) of these groups. Here, we describe and analyze several models from a Bayesian perspective to construct SSDs from data derived using rapid toxicity testing, combining both rapid test data and expert opinion. We compare these new models with two frequentist approaches, Kaplan-Meier and a log-normal distribution, using a large data set on the salinity sensitivity of freshwater macroinvertebrates from Victoria (Australia). The frequentist log-normal analysis produced a SSD that overestimated the hazard to species relative to the Kaplan-Meier and Bayesian analyses. Of the Bayesian analyses investigated, the introduction of a weighting factor to account for the richness (or importance) of taxonomic groups influenced the calculated hazard to species. Furthermore, Bayesian methods allowed us to determine credible intervals representing SSD uncertainty. We recommend that rapid tests, expert judgements, and novel Bayesian statistical methods be used so that SSDs reflect communities of organisms found in nature. en_US
dc.language en_US
dc.publisher Soc Environmental Toxicology & Chemistry-Setac en_US
dc.relation.isbasedon http://dx.doi.org/10.1897/08-079.1 en_US
dc.title Making Species Salinity Sensitivity Distributions Reflective Of Naturally Occurring Communities: Using Rapid Testing And Bayesian Statistics en_US
dc.parent Environmental Toxicology and Chemistry en_US
dc.journal.volume 27 en_US
dc.journal.number 11 en_US
dc.publocation Pensacola en_US
dc.identifier.startpage 2403 en_US
dc.identifier.endpage 2411 en_US
dc.cauo.name SCI.Faculty of Science en_US
dc.conference Verified OK en_US
dc.for 060200 en_US
dc.personcode 0000062839 en_US
dc.personcode 109859 en_US
dc.personcode 0000062837 en_US
dc.personcode 0000062840 en_US
dc.percentage 100 en_US
dc.classification.name Ecology en_US
dc.classification.type FOR-08 en_US
dc.edition en_US
dc.custom en_US
dc.date.activity en_US
dc.location.activity ISI:000260201800027 en_US
dc.description.keywords Rapid testing; Species sensitivity distribution; Bayesian; Risk assessment; Salinity en_US
dc.staffid en_US


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