IDEAS home Printed from https://ideas.repec.org/a/wly/riskan/v14y1994i4p405-419.html
   My bibliography  Save this article

Uses of Probabilistic Exposure Models in Ecological Risk Assessments of Contaminated Sites

Author

Listed:
  • David L. Macintosh
  • Glenn W. Suter
  • F. Owen Hoffman

Abstract

Food web models have two uses in assessments of environmental contaminants. First, they are used to determine whether remediation is needed by estimating exposure of end‐point species and subsequent effects. Second, they are used to establish cleanup goals by estimating concentrations of contaminants in ambient media that will not cause significant effects. This paper demonstrates how achievement of these goals can be enhanced by the use of stochastic food web models. The models simulate the dynamics of PCBs and mercury in the food webs of mink and great blue herons. All parameters of the models are treated as having knowledge uncertainty, due to imperfect knowledge of the actual parameter values for the site, chemicals, and species of interest. This uncertainty is an indicator of the potential value of additional measurements. In addition, those parameters that are responsible for variance among individual organisms are assigned stochastic uncertainty. This uncertainty indicates the range of body burdens that are expected when the end‐point species are monitored. These two types of uncertainty are separately accounted for in Monte Carlo simulations of the models. Preliminary monitoring results indicate that the models give reasonably good estimates of heron egg and nestling body burdens and of variance among individuals.

Suggested Citation

  • David L. Macintosh & Glenn W. Suter & F. Owen Hoffman, 1994. "Uses of Probabilistic Exposure Models in Ecological Risk Assessments of Contaminated Sites," Risk Analysis, John Wiley & Sons, vol. 14(4), pages 405-419, August.
  • Handle: RePEc:wly:riskan:v:14:y:1994:i:4:p:405-419
    DOI: 10.1111/j.1539-6924.1994.tb00259.x
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/j.1539-6924.1994.tb00259.x
    Download Restriction: no

    File URL: https://libkey.io/10.1111/j.1539-6924.1994.tb00259.x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. H. Christopher Frey & David E. Burmaster, 1999. "Methods for Characterizing Variability and Uncertainty: Comparison of Bootstrap Simulation and Likelihood‐Based Approaches," Risk Analysis, John Wiley & Sons, vol. 19(1), pages 109-130, February.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wly:riskan:v:14:y:1994:i:4:p:405-419. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: https://doi.org/10.1111/(ISSN)1539-6924 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.