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• W2973417346 abstract "ABSTRACT Despite widespread acceptance of the utility of population modeling and advocacy of this approach for a more ecologically relevant perspective, it is not routinely incorporated in ecological risk assessments (ERA). A systematic framework for situation‐specific model development is one of the major challenges to broadly adopting population models in ERA. As risk assessors confront the multitude of species and chemicals requiring evaluation, an adaptable stepwise guide for model parameterization would facilitate this process. Additional guidance on interpretation of model output and evaluating uncertainty would further contribute to establishing consensus on good modeling practices. We build on previous work that created a framework and decision guide for developing population models for ERA by focusing on data types, model structure, and extrinsic stressors relevant to anuran amphibians. Anurans have a unique life cycle with varying habitat requirements and high phenotypic plasticity. These species belong to the amphibian class, which is facing global population decline in large part due to anthropogenic stressors, including chemicals. We synthesize information from databases and literature relevant to amphibian risks to identify traits that influence exposure likelihood, inherent sensitivity, population vulnerability, and environmental constraints. We link these concerns with relevant population modeling methods and structure in order to evaluate pesticide effects with appropriate scale and parameterization. A standardized population modeling approach, with additional guidance for anuran ERA, offers an example method for quantifying population risks and evaluating long‐term impacts of chemical stressors to populations. Integr Environ Assess Manag 2020;16:223–233. © 2019 SETAC" @default.
• W2973417346 created "2019-09-26" @default.
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• W2973417346 date "2019-11-27" @default.
• W2973417346 modified "2023-10-14" @default.
• W2973417346 title "Guidance for Developing Amphibian Population Models for Ecological Risk Assessment" @default.
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• W2973417346 doi "https://doi.org/10.1002/ieam.4215" @default.
• W2973417346 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/8425957" @default.
• W2973417346 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/31538699" @default.
• W2973417346 hasPublicationYear "2019" @default.
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