Evaluation process for matching population models to regulatory decisions regarding threatened or endangered species by considering model risk.

This article focuses on a proposed decision framework to evaluate and manage the use of population models in regulatory decision-making concerning rare and endangered species. It addresses challenges regulators face due to limited species-specific data, model complexity, and uncertainty, emphasizing the need to align model structure, data quality, and regulatory objectives to reduce model risk—the possibility of incorrect or misapplied model output. The framework integrates a weight of evidence approach to assess model appropriateness alongside the regulator's risk tolerance, illustrated through case studies involving species such as northern spotted owls, Pacific salmon, and roseate terns. The authors recommend collaborative model development between regulators and modelers, independent review, and cautious interpretation of model outputs as one line of evidence to enhance confidence and transparency in regulatory decisions.