The Origin, Development, Application, Lessons Learned, and Future Regarding the Bayesian Network Relative Risk Model for Ecological Risk Assessment

Abstract

Abstract In 2012, a regional risk assessment was published that applied Bayesian networks (BN) to the structure of the relative risk model. The original structure of the relative risk model (RRM) was published in the late 1990s and developed during the next decade. The RRM coupled with a Monte Carlo analysis was applied to calculating risk to a number of sites and a variety of questions. The sites included watersheds, terrestrial systems, and marine environments and included stressors such as nonindigenous species, effluents, pesticides, nutrients, and management options. However, it became apparent that there were limits to the original approach. In 2009, the relative risk model was transitioned into the structure of a BN. Bayesian networks had several clear advantages. First, BNs innately incorporated categories and, as in the case of the relative risk model, ranks to describe systems. Second, interactions between multiple stressors can be combined using several pathways and the conditional probability tables (CPT) to calculate outcomes. Entropy analysis was the method used to document model sensitivity. As with the RRM, the method has now been applied to a wide series of sites and questions, from forestry management, to invasive species, to disease, the interaction of ecological and human health endpoints, the flows of large rivers, and now the efficacy and risks of synthetic biology. The application of both methods have pointed to the incompleteness of the fields of environmental chemistry, toxicology, and risk assessment. The low frequency of exposure-response experiments and proper analysis have limited the available outputs for building appropriate CPTs. Interactions between multiple chemicals, landscape characteristics, population dynamics and community structure have been poorly characterized even for critical environments. A better strategy might have been to first look at the requirements of modern risk assessment approaches and then set research priorities. Integr Environ Assess Manag 2021;17:79–94. © 2020 SETAC KEY POINTS The paper reviews the development of the relative risk model (RRM) and the follow on Bayesian network relative risk model (BN-RRM) from the late 1990s to 2020. The RRM and BN-RRM have been demonstrated to describe risk due to chemicals, disease, land use change, and nonindigenous species to a variety of biotic and abiotic endpoints including human wellbeing at sites across the world. Adaptive management in collaboration with diverse stakeholders and incorporating ecological risk assessment is applicable to long-term restoration and conservation. Contrary to many claims, much research in the field of environmental toxicology is not done in a manner appropriate to the quantitative risk assessment. Risk assessment depends on understanding exposure-response relationships as curves and distributions, not point estimates, and p values.

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