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Area of Science:

  • Ecological risk assessment (ERA)
  • Population modeling
  • Environmental toxicology

Background:

  • Ecological risk assessment (ERA) employs a tiered strategy, progressing from conservative assumptions in lower tiers to more realistic models in higher tiers.
  • Higher tiers demand more time and effort, necessitating efficiency, especially when assessing multiple stressors, species, and habitats.
  • Conservative approaches are established in lower-tier ERA, but less explored in higher-tier, accuracy-focused models.

Purpose of the Study:

  • To articulate and evaluate a principle of efficiency for population-level ecological risk assessment models.
  • To compare avian chemical risk assessment models of increasing realism.
  • To investigate how conservatism changes with increasing model realism in ERA.

Main Methods:

  • Reviewed four avian population models for chemical risk assessment, ordered by increasing realism: risk quotient, Markov chain nest productivity, endogenous lifecycle, and spatially explicit population models.
  • Compared models pairwise based on increasing realism.
  • Evaluated changes in conservatism with each step of increasing model realism.

Main Results:

  • The principle of efficiency in ecological modeling for ERA is challenging to achieve.
  • Conservatism does not consistently increase with model realism across all tiers.
  • Some aspects of efficiency in higher-tier modeling offer optimism for risk assessment.

Conclusions:

  • Strategies are proposed for investigating efficiency in the deployment of tiered ecological models.
  • Further research is needed to optimize the balance between accuracy and conservatism in higher-tier ERA models.
  • Balancing efficiency and conservatism is crucial for effective ecological risk assessment with complex stressors.