NCEAS Product 13121

Bartell, S. M.; Pastorok, R. A.; Akçakaya, H. Resit; Regan, Helen M.; Ferson, Scott; Mackay, C. 2003. Realism and relevance of ecological models used in chemical risk assessment. Human and Ecological Risk Assessment. Vol: 9. Pages 907-938. (Abstract) (Online version)

Abstract

Ecological models have been developed and used in management of renewable natural resources, conservation biology, and assessments of ecological risks posed by toxic chemicals and other stressors. Because few models have been developed specifically for use in assessing chemical risks, this study examines the realism and relevance of a wide range of ecological models from the perspective of assessing toxicological risks posed by chemicals. Model realism is evaluated relative to the degree of structural and functional description of the actual (i.e., real-world) ecological entities or systems that is believed necessary for reliable estimation and management of risk. Relevance refers to the usefulness of model outputs in addressing the ecological impacts of interest in either generic or site-specific assessment of risks posed by toxic chemicals. A model becomes increasingly relevant the more closely its outputs correspond to the endpoints of the risk analysis. In addition to the relatively few models (e.g., CASM, IFEM, AQUATOX) that have been designed specifically for ecological risk assessment, we identify several models developed in support of basic research that might be adapted for realistic and relevant risk estimation. Population, ecosystem, and landscape models describe ecological phenomena from different perspectives. Associated with each perspective and resulting modeling approach are hypotheses concerning simplifying assumptions that facilitate the specification of model structure in relation to the ecological topic of interest. The structurally complex system models (e.g., AQUATOX, CASM) attempt to explicitly represent the many biotic and abiotic processes and interactions that are believed to influence the production dynamics of aquatic populations included in the models. Future efforts in ecological risk assessment modeling should focus on identifying the necessary model complexity required to achieve sufficiently accurate and precise estimates of risk, as defined by the needs of risk management and risk-based decision making. Evaluations of model realism, endpoint relevance, flexibility, ease of use, and other characteristics may help to guide model users in their choice of specific models for further development and application to continuing challenges in assessing ecological risks. Clear definition of specific model capabilities and corresponding risk assessment endpoints can help to ensure that applications of existing ecological models to chemical risk assessments are appropriately customized to the needs of environmental risk assessors, managers, and decision-makers.