A Bayesian approach to parameter estimation for a crayfish (Procambarus spp.) bioaccumulation model

Hsin I. Lin, David W. Berzins, Leann Myers, William J. George, Assaf Abdelghani, Karen Watanabe-Sailor

Research output: Contribution to journalArticle

22 Citations (Scopus)

Abstract

Bioaccumulation models are used to describe chemical uptake and clearances by organisms. Averaged input parameter values are traditionally used and yield point estimates of model outputs. Hence, the uncertainty and variability of model predictions are ignored. Probabilistic modeling approaches, such as Monte Carlo simulation and the Bayesian method, have been recommended by the U.S. Environmental Protection Agency to provide a quantitative description of the degree of uncertainty and/or variability in risk estimates in ecological hazards and human health effects. In this study, a Bayesian analysis was conducted to account for the combined uncertainty and variability of model parameters in a crayfish bioaccumulation model. After a 5-d exposure in the LaBranche Wetlands (LA, USA), crayfish were analyzed for polycyclic aromatic hydrocarbon concentrations and lipid fractions. The posterior distribution of model parameters were derived from the joint posterior parameter distributions using a Markov chain Monte Carlo approach and the experimental data. The results were then used to predict the distribution of chrysene concentration versus time in the crayfish to compare the predicted ranges at the different study sites.

Original languageEnglish (US)
Pages (from-to)2259-2266
Number of pages8
JournalEnvironmental Toxicology and Chemistry
Volume23
Issue number9
DOIs
StatePublished - Sep 2004

Fingerprint

Astacoidea
Bioaccumulation
Bayes Theorem
crayfish
Parameter estimation
bioaccumulation
Uncertainty
United States Environmental Protection Agency
Markov Chains
Wetlands
Polycyclic Aromatic Hydrocarbons
Joints
Lipids
Bayesian analysis
Health
Environmental Protection Agency
Markov chain
Markov processes
parameter estimation
Hazards

Keywords

  • Bayesian
  • Bioaccumulation
  • Markov chain Monte Carlo
  • Polycyclic aromatic hydrocarbon
  • Uncertainty

ASJC Scopus subject areas

  • Environmental Science(all)
  • Environmental Chemistry
  • Toxicology
  • Health, Toxicology and Mutagenesis

Cite this

Lin, H. I., Berzins, D. W., Myers, L., George, W. J., Abdelghani, A., & Watanabe-Sailor, K. (2004). A Bayesian approach to parameter estimation for a crayfish (Procambarus spp.) bioaccumulation model. Environmental Toxicology and Chemistry, 23(9), 2259-2266. https://doi.org/10.1897/03-303

A Bayesian approach to parameter estimation for a crayfish (Procambarus spp.) bioaccumulation model. / Lin, Hsin I.; Berzins, David W.; Myers, Leann; George, William J.; Abdelghani, Assaf; Watanabe-Sailor, Karen.

In: Environmental Toxicology and Chemistry, Vol. 23, No. 9, 09.2004, p. 2259-2266.

Research output: Contribution to journalArticle

Lin, HI, Berzins, DW, Myers, L, George, WJ, Abdelghani, A & Watanabe-Sailor, K 2004, 'A Bayesian approach to parameter estimation for a crayfish (Procambarus spp.) bioaccumulation model', Environmental Toxicology and Chemistry, vol. 23, no. 9, pp. 2259-2266. https://doi.org/10.1897/03-303
Lin, Hsin I. ; Berzins, David W. ; Myers, Leann ; George, William J. ; Abdelghani, Assaf ; Watanabe-Sailor, Karen. / A Bayesian approach to parameter estimation for a crayfish (Procambarus spp.) bioaccumulation model. In: Environmental Toxicology and Chemistry. 2004 ; Vol. 23, No. 9. pp. 2259-2266.
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