Expert judgment based multicriteria decision models to assess the risk of pesticides on reproduction failures of grey partridge - INRAE - Institut national de recherche pour l’agriculture, l’alimentation et l’environnement
Article Dans Une Revue SAR and QSAR in Environmental Research Année : 2017

Expert judgment based multicriteria decision models to assess the risk of pesticides on reproduction failures of grey partridge

Résumé

A suite of models is proposed for estimating the risk of pesticides against the grey partridge (Perdix perdix) and their clutches. Radio-tracked data of females, description and location of the clutches, and data on the pesticide treatments during the laying periods of the partridges were used as basic information. Quantitative structure-activity relationship (QSAR) and quantitative structure-property relationship (QSPR) modelling allowed us to characterize the pesticides by their 1-octanol/water partition coefficient (log P), vapour pressure, primary and ultimate biodegradation potential, acute toxicity (LD50) on P. perdix, and endocrine disruption potential. From these physicochemical and toxicological data, the system of integration of risk with interaction of scores (SIRIS) method was used to design scores of risk for pesticides, alone or in mixture. A program, written in R (version 3.1.1), called Simulation of Toxicity in Perdix perdix (SimToxPP), was designed for estimating the risk of substances, considered alone or in mixture, against the grey partridge during breeding. The software tool is flexible enough to simulate realistic in situ scenarios. Different examples of applications are shown. The advantages and limitations of the approach are briefly discussed.

Dates et versions

hal-02625439 , version 1 (26-05-2020)

Identifiants

Citer

James Devillers, Hugo Devillers, Elisabeth Bro, Florian Millot. Expert judgment based multicriteria decision models to assess the risk of pesticides on reproduction failures of grey partridge. SAR and QSAR in Environmental Research, 2017, 28 (11), pp.889-911. ⟨10.1080/1062936X.2017.1402449⟩. ⟨hal-02625439⟩
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