A framework for linking population model development with ecological risk assessment objectives.

Area of Science:

• Environmental Science
• Ecotoxicology
• Risk Assessment

Background:

• Population models are valuable for ecological risk assessments (ERAs), translating organism-level impacts to population responses.
• Despite demonstrated utility, population models are not commonly applied in regulatory ERAs due to a lack of guidance.
• Existing frameworks lack specifics on model selection, form, and output interpretation for risk managers.

Purpose of the Study:

• To propose a framework for developing and applying population models in regulatory decision-making.
• To focus on the trade-offs between generality, realism, and precision for both ERAs and population models.
• To define regulatory needs for specific models commensurate with assessment objectives.

Main Methods:

• Developed a framework from a regulator's perspective to define model needs based on assessment objectives.
• Compared model requirements and limitations with regulatory needs to understand barriers to adoption.
• Used case studies within regulatory frameworks to classify ERA objectives and demonstrate how population model outputs inform them.

Main Results:

• Classified ERA objectives based on trade-offs of generality, realism, and precision.
• Demonstrated how population models, developed with similar trade-offs, inform ERA objectives.
• Identified key attributes for assessments and models that facilitate discussions on trade-offs.

Conclusions:

• The proposed framework assists risk assessors and managers in selecting models of appropriate complexity.
• It enhances understanding of model utility, limitations, and uncertainty within specific assessment goals.
• Facilitates better integration of population models into regulatory ecological risk assessments.