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Model selection and parameterization of the concentration-response functions for population-level effects.

Y Tanaka1, J Nakanishi

  • 1Institute of Environmental Science and Technology, Yokohama National University, Kanagawa, Japan. ytanaka@tamacc.chuo-u.ac.jp

Environmental Toxicology and Chemistry
|August 9, 2001
PubMed
Summary

The power function model best describes how chemical concentrations affect population growth rates. A generic beta value of 1.84 suggests a nearly quadratic response to chemical exposure.

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Area of Science:

  • Environmental toxicology
  • Mathematical modeling
  • Population dynamics

Background:

  • Assessing chronic population-level effects of pollutants is crucial for ecological risk assessment.
  • Existing models for chemical concentration-response relationships require rigorous evaluation.

Purpose of the Study:

  • To evaluate mathematical models for predicting population-level effects of chemical pollutants.
  • To identify the best-fitting model for concentration-response functions of the intrinsic rate of population growth (r).

Main Methods:

  • Compared three mathematical models for their goodness of fit to toxicological data.
  • Utilized a power function model: r(x) = r(0)[1 - (x/alpha)beta].
  • Employed bootstrap simulation on a comprehensive dataset to analyze parameter variability.

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Main Results:

  • The power function model demonstrated the best fit to the toxicological data.
  • The model's parameters, alpha and beta, represent toxicity and response curvature, respectively.
  • Bootstrap simulations indicated that random error largely explains the variance in beta, leading to a generic beta estimate of 1.84.

Conclusions:

  • The power function model is a robust tool for characterizing chemical impacts on population growth.
  • A generic beta value of 1.84 suggests a near-quadratic relationship between chemical exposure and the intrinsic rate of natural increase (r).
  • Findings support the use of this model for predicting chronic population-level effects of pollutants.