A Bayesian approach to assessing the uncertainty in estimating bioconcentration factors in earthworms-the example of quinoxyfen

Ettore Capri, Graham Reeves, Giovanna Meregalli, Kristofer Stenberg

Risultato della ricerca: Contributo in rivistaArticolo in rivista

1 Citazioni (Scopus)

Abstract

Background: Quinoxyfen is a fungicide of the phenoxyquinoline class used to control powdery mildew, Uncinula necator (Schw.) Burr. Owing to its high persistence and strong sorption in soil, it could represent a risk for soil organisms if they are exposed at ecologically relevant concentrations. The objective of this paper is to predict the bioconcentration factors (BCFs) of quinoxyfen in earthworms, selected as a representative soil organism, and to assess the uncertainty in the estimation of this parameter. Three fields in each of four vineyards in southern and northern Italy were sampled over two successive years. Results: The measured BCFs varied over time, possibly owing to seasonal changes and the consequent changes in behaviour and ecology of earthworms. Quinoxyfen did not accumulate in soil, as the mean soil concentrations at the end of the 2 year monitoring period ranged from 9.16 to 16.0 μg kg -1 dw for the Verona province and from 23.9 to 37.5 μg kg -1 dw for the Taranto province, with up to eight applications per season. To assess the uncertainty of the BCF in earthworms, a probabilistic approach was used, firstly by building with weighted bootstrapping techniques a generic probabilistic density function (PDF) accounting for variability and incompleteness of knowledge. The generic PDF was then used to derive prior distribution functions, which, by application of Bayes' theorem, were updated with the new measurements and a posterior distribution was finally created. Conclusion: The study is a good example of probabilistic risk assessment. The means of mean and SD posterior estimates of log BCFworm (2.06, 0.91) are the 'best estimate values'. Further risk assessment of quinoxyfen and other phenoxyquinoline fungicides and realistic representative scenarios for modelling exercises required for future authorization and post-authorization requirements can now use this value as input. © 2011 Society of Chemical Industry.
Lingua originaleEnglish
pagine (da-a)656-664
Numero di pagine9
RivistaPest Management Science
Stato di pubblicazionePubblicato - 2011

Keywords

  • Animals
  • Ascomycetes
  • Ascomycota
  • Bayes Theorem
  • Bayes theorem
  • EMTREE drug terms: fungicide
  • Erysiphe necator
  • Fungicides, Industrial
  • Italy
  • Necator
  • Oligochaeta
  • Pest Control
  • Pesticides
  • Plant Diseases
  • Puglia
  • Quinolines
  • Risk Assessment
  • Soil
  • Taranto
  • Time Factors
  • Uncertainty
  • Veneto
  • Verona Species Index: Erysiphales
  • Vitis MeSH: Agriculture
  • Vitis Medline is the source for the MeSH terms of this document. Regional Index: Italy
  • animal
  • article
  • bioaccumulation
  • bootstrapping
  • chemistry
  • drug effect
  • earthworm
  • fungal disease
  • methodology
  • microbiology
  • pest control
  • pesticide
  • pesticide application
  • pesticide resistance
  • plant disease
  • probability
  • quinoline derivative
  • quinoxyfen
  • quinoxyfen GEOBASE Subject Index: Bayesian analysis
  • risk assessment
  • seasonal variation
  • soil
  • time
  • uncertainty
  • uncertainty analysis
  • vineyard EMTREE medical terms: agriculture

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