James Devillers 
Ecotoxicology Modeling [PDF ebook] 

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Ecotoxicology Modeling is a comprehensive and well-documented text providing a collection of computational methods to the ecotoxicologists primarily interested in the study of the adverse effects of chemicals, their mechanisms of action and/or their environmental fate and behavior. Avoiding mathematical jargon, the book presents numerous case studies to enable the reader to understand the interest but also the limitations of linear and nonlinear models in ecotoxicology.

Written by an international team of scientists, Ecotoxicology Modeling is of primary interest to those whose research or professional activity is directly concerned with the development and application of models in ecotoxicology. It is also intended to provide the graduate and post-graduate students with a clear and accessible text covering the main types of modeling approaches used in environmental sciences.

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Table of Content

Artificial Neural Network Modeling of the Environmental Fate and Ecotoxicity of Chemicals.- (Q)SAR Models for Genotoxicity Assessment.- Chemistry Based Nonanimal Predictive Modeling for Skin Sensitization.- Interspecies Correlations for Predicting the Acute Toxicity of Xenobiotics.- Use of Multicriteria Analysis for Selecting Ecotoxicity Tests.- Physiologically Based Toxicokinetic (PBTK) Modeling in Ecotoxicology.- Earthworms and Their Use in Eco(toxico)logical Modeling.- The Potential for the Use of Agent-Based Models in Ecotoxicology.- Ecotoxicological Applications of Dynamic Energy Budget Theory.- Matrix Population Models as Relevant Modeling Tools in Ecotoxicology.- Bioaccumulation of Polar and Ionizable Compounds in Plants.- The Evolution and Future of Environmental Fugacity Models.- The Application of Structurally Dynamic Models in Ecology and Ecotoxicology.

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Language English ● Format PDF ● Pages 412 ● ISBN 9781441901972 ● File size 5.6 MB ● Editor James Devillers ● Publisher Springer US ● City NY ● Country US ● Published 2009 ● Downloadable 24 months ● Currency EUR ● ID 2149669 ● Copy protection Social DRM

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