Constructing Time-Resolved Species Sensitivity Distributions Using a Hierarchical Toxico-Dynamic Model.
Identifieur interne : 002F96 ( Main/Exploration ); précédent : 002F95; suivant : 002F97Constructing Time-Resolved Species Sensitivity Distributions Using a Hierarchical Toxico-Dynamic Model.
Auteurs : Guillaume Kon Kam King [France] ; Marie Laure Delignette-Muller [France] ; Ben J. Kefford [Australie] ; Christophe Piscart [France] ; Sandrine Charles [France]Source :
- Environmental science & technology [ 1520-5851 ] ; 2015.
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Abstract
Classical species sensitivity distribution (SSD) is used to assess the threat to ecological communities posed by a contaminant and derive a safe concentration. It suffers from several well-documented weaknesses regarding its ecological realism and statistical soundness. Criticism includes that SSD does not take time-dependence of the data into account, that safe concentrations obtained from SSD might not be entirely protective of the target communities, and that there are issues of statistical representativity and of uncertainty propagation from the experimental data. We present a hierarchical toxico-dynamic (TD) model to simultaneously address these weaknesses: TD models incorporate time-dependence and allow improvement of the ecological relevance of safe concentrations, while the hierarchical approach affords appropriate propagation of uncertainty from the original data. We develop this model on a published data set containing the salinity tolerance over 72 h of 217 macroinvertebrate taxa, obtained through rapid toxicity testing (RTT). The shrinkage properties of the hierarchical model prove particularly adequate for modeling inhomogeneous RTT data. Taking into account the large variability in the species response, the model fits the whole data set well. Moreover, the model predicts a time-independent safe concentration below that obtained with classical SSD at 72 h, demonstrating under-protectiveness of the classical approach.
DOI: 10.1021/acs.est.5b02142
PubMed: 26406398
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The shrinkage properties of the hierarchical model prove particularly adequate for modeling inhomogeneous RTT data. Taking into account the large variability in the species response, the model fits the whole data set well. Moreover, the model predicts a time-independent safe concentration below that obtained with classical SSD at 72 h, demonstrating under-protectiveness of the classical approach.</div></front></TEI><affiliations><list><country><li>Australie</li><li>France</li></country><region><li>Auvergne-Rhône-Alpes</li><li>Rhône-Alpes</li></region><settlement><li>Lyon</li></settlement></list><tree><country name="France"><region name="Auvergne-Rhône-Alpes"><name sortKey="Kon Kam King, Guillaume" sort="Kon Kam King, Guillaume" uniqKey="Kon Kam King G" first="Guillaume" last="Kon Kam King">Guillaume Kon Kam King</name></region><name sortKey="Charles, Sandrine" sort="Charles, Sandrine" uniqKey="Charles S" first="Sandrine" last="Charles">Sandrine Charles</name><name sortKey="Delignette Muller, Marie Laure" sort="Delignette Muller, Marie Laure" uniqKey="Delignette Muller M" first="Marie Laure" last="Delignette-Muller">Marie Laure Delignette-Muller</name><name sortKey="Piscart, Christophe" sort="Piscart, Christophe" uniqKey="Piscart C" first="Christophe" last="Piscart">Christophe Piscart</name></country><country name="Australie"><noRegion><name sortKey="Kefford, Ben J" sort="Kefford, Ben J" uniqKey="Kefford B" first="Ben J" last="Kefford">Ben J. 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