The extrapolation problem and how population modeling can help

Valery E. Forbes, Peter Calow, Richard M. Sibly

Research output: Contribution to journalReview articlepeer-review

121 Scopus citations

Abstract

We argue that population modeling can add value to ecological risk assessment by reducing uncertainty when extrapolating from ecotoxicological observations to relevant ecological effects. We review other methods of extrapolation, ranging from application factors to species sensitivity distributions to suborganismal (biomarker and "-omics") responses to quantitative structureactivity relationships and model ecosystems, drawing attention to the limitations of each. We suggest a simple classification of population models and critically examine each model in an extrapolation context. We conclude that population models have the potential for adding value to ecological risk assessment by incorporating better understanding of the links between individual responses and population size and structure and by incorporating greater levels of ecological complexity. A number of issues, however, need to be addressed before such models are likely to become more widely used. In a science context, these involve challenges in parameterization, questions about appropriate levels of complexity, issues concerning how specific or general the models need to be, and the extent to which interactions through competition and trophic relationships can be easily incorporated.

Original languageEnglish (US)
Pages (from-to)1987-1994
Number of pages8
JournalEnvironmental Toxicology and Chemistry
Volume27
Issue number10
DOIs
StatePublished - Oct 2008

Keywords

  • Demographic models
  • Ecological relevance
  • Ecological risk assessment
  • Individual-based models
  • Uncertainty

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