Population Modeling in Metal Risk Assessment: Extrapolation of Toxicity Tests to the Population Level

Area of Science:

• Environmental Toxicology
• Ecological Modeling
• Risk Assessment

Background:

• Ecological risk assessment benefits from increased realism using population models.
• Extrapolating laboratory toxicity data to the population level is crucial for accurate environmental risk assessment.

Purpose of the Study:

• To utilize population models for extrapolating metal toxicity test results (Ag, Cu, Ni, Zn) to the population level.
• To evaluate the ecological modeling-based laboratory to population effect extrapolation factor (ECOPEX factor).
• To explore the regulatory applicability of population models in environmental risk assessment.

Main Methods:

• Applied population models to toxicity data for three primary producers, five invertebrate, and five fish species.
• Calculated the ECOPEX factor, the ratio of population-level EC10 to laboratory-level EC10.
• Integrated population extrapolations into species sensitivity distributions and applied models to regulatory case studies.

Main Results:

• The ECOPEX factor ranged from 0.7 to 78.6 (median 2.8), indicating higher population-level effect concentrations in most cases.
• Identified key contributors to ECOPEX factor variability, including toxicity model uncertainty, metal mechanisms, test design, environmental factors, and endpoint choice.
• Population modeling generally reduced EC10 variability between tests and influenced regulatory metrics like hazardous concentrations.

Conclusions:

• Population models are valuable tools for ecological risk assessment, enhancing realism and reducing uncertainty.
• Incorporating population extrapolations can refine regulatory risk assessments for metals.
• Further research and data are needed to optimize the use of population models in regulatory frameworks.