Making Species Salinity Sensitivity Distributions Reflective of Naturally Occurring Communities: Using Rapid Testing and Bayesian Statistics

Graeme Hickey, Ben Kefford, Jason Dunlop, Peter Craig

    Research output: Contribution to journalArticle

    27 Citations (Scopus)

    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 lognormal 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.
    Original languageEnglish
    Pages (from-to)2403-2411
    Number of pages9
    JournalEnvironmental Toxicology and Chemistry
    Volume27
    Issue number11
    Publication statusPublished - 2008

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    Bayes Theorem
    Salinity
    Hazards
    Statistics
    salinity
    Toxicity
    Statistical methods
    Testing
    Toxicity Tests
    Impurities
    Victoria
    Expert Testimony
    Fresh Water
    hazard
    Uncertainty
    Ecosystem
    distribution
    statistics
    toxicity test
    macroinvertebrate

    Cite this

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    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 lognormal 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.",
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    Making Species Salinity Sensitivity Distributions Reflective of Naturally Occurring Communities: Using Rapid Testing and Bayesian Statistics. / Hickey, Graeme; Kefford, Ben; Dunlop, Jason; Craig, Peter.

    In: Environmental Toxicology and Chemistry, Vol. 27, No. 11, 2008, p. 2403-2411.

    Research output: Contribution to journalArticle

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