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Toxicity Testing in Animals01:23

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Toxicity tests in animals are grounded on two main assumptions: first, the effects observed in laboratory animals can be extrapolated to humans, especially when adjusted for body surface area; second, high-dose exposure in animals is essential to identify potential human hazards from lower doses. This is based on the quantal dose-response concept, which faces the challenge of extrapolating results from relatively few test animals to much larger human populations. For example, a 0.01% incidence...
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Regional models for sediment toxicity assessment.

L Jay Field1, Susan B Norton

  • 1Office of Response and Restoration, National Oceanic and Atmospheric Administration, Seattle, Washington, USA.

Environmental Toxicology and Chemistry
|December 6, 2013
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Summary

Calibrating nationwide sediment toxicity models to regional data improves predictive performance. This approach is more efficient and effective than developing region-specific models for environmental risk assessment.

Keywords:
Logistic regression modelsSedimentToxicity

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Area of Science:

  • Environmental chemistry
  • Ecotoxicology
  • Ecological modeling

Background:

  • Empirical models are crucial for predicting sediment toxicity from chemical data.
  • Nationwide datasets offer broad applicability but may lack regional specificity.
  • Regional models can improve accuracy but require extensive regional data.

Purpose of the Study:

  • To enhance the performance of empirical sediment toxicity models for regional applications.
  • To evaluate calibration strategies using nationwide and regional datasets.
  • To compare the effectiveness of calibrated nationwide models versus region-specific models.

Main Methods:

  • Developed four multiple chemical (PMax) models using diverse datasets and variables.
  • Applied nationwide and regional data for model development and calibration.
  • Tested model performance using an independent regional dataset.

Main Results:

  • Calibrated PMax models showed substantial performance improvement over uncalibrated nationwide models.
  • Model performance was enhanced by selecting optimal individual chemical models and excluding poor performers.
  • A PMax model using only nationwide data achieved performance nearly as good as models including regional data.

Conclusions:

  • Calibrating nationwide sediment toxicity models to regional data significantly improves predictive accuracy.
  • This calibration approach offers a more efficient and effective strategy than developing entirely new region-specific models.
  • Nationwide models, when calibrated, provide a robust foundation for regional sediment toxicity predictions.