Literature DB >> 27509762

Evolutionary patterns and physicochemical properties explain macroinvertebrate sensitivity to heavy metals.

Egina Malaj, Guillaume Guénard, Ralf B Schäfer, Peter C von der Ohe.   

Abstract

Ecological risk assessment depends strongly on species sensitivity data. Typically, sensitivity data are based on laboratory toxicity bioassays, which for practical constraints cannot be exhaustively performed for all species and chemicals available. Bilinear models integrating phylogenetic information of species and physicochemical properties of compounds allow to predict species sensitivity to chemicals. Combining the molecular information (DNA sequences) of 31 invertebrate species with the physicochemical properties of six bivalent metals, we built bilinear models that explained 70-80% of the variability in species sensitivity to heavy metals. Phylogeny was the most important component of the bilinear models, as it explained the major part of the explained variance (> 40%). Predicted values from bilinear modeling were in agreement with experimental values (> 50%); therefore, this approach is a good starting point to build statistical models which can potentially predict heavy metal toxicity for untested invertebrate species based on empirical values for similar species. Despite their good performance, development of the presented bilinear models would benefit from improved phylogenetic and toxicological datasets. Our analysis is an example for linking evolutionary biology with applied ecotoxicology. Its future applications may encompass other stress factors or traits influencing the survival of aquatic organisms in polluted environments.

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Year:  2016        PMID: 27509762     DOI: 10.1890/15-0346

Source DB:  PubMed          Journal:  Ecol Appl        ISSN: 1051-0761            Impact factor:   4.657


  8 in total

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3.  Can we predict diatoms herbicide sensitivities with phylogeny? Influence of intraspecific and interspecific variability.

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Journal:  Ecotoxicology       Date:  2017-07-06       Impact factor: 2.823

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5.  Empirically-based modeling and mapping to consider the co-occurrence of ecological receptors and stressors.

Authors:  Roy W Martin; Eric R Waits; Christopher T Nietch
Journal:  Sci Total Environ       Date:  2017-09-24       Impact factor: 7.963

6.  Modeling the Sensitivity of Aquatic Macroinvertebrates to Chemicals Using Traits.

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7.  Correcting for Phylogenetic Autocorrelation in Species Sensitivity Distributions.

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Journal:  Integr Environ Assess Manag       Date:  2019-11-18       Impact factor: 2.992

8.  The Application of a Macroinvertebrate Indicator in Afrotropical Regions for Pesticide Pollution.

Authors:  Wynand Malherbe; Johan H J van Vuren; Victor Wepener
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  8 in total

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