Society For Risk Analysis Annual Meeting 2017

Session Schedule & Abstracts


* Disclaimer: All presentations represent the views of the authors, and not the organizations that support their research. Please apply the standard disclaimer that any opinions, findings, and conclusions or recommendations in abstracts, posters, and presentations at the meeting are those of the authors and do not necessarily reflect the views of any other organization or agency. Meeting attendees and authors should be aware that this disclaimer is intended to apply to all abstracts contained in this document. Authors who wish to emphasize this disclaimer should do so in their presentation or poster. In an effort to make the abstracts as concise as possible and easy for meeting participants to read, the abstracts have been formatted such that they exclude references to papers, affiliations, and/or funding sources. Authors who wish to provide attendees with this information should do so in their presentation or poster.

Common abbreviations

W4-E
Complex Models to Solve Complex Problems

Room: Salon E   3:30 pm–5:00 pm

Chair(s): Amanda Bailey   abailey@slrconsulting.com

Sponsored by Ecological Risk Assessment Specialty Group



W4-E.1  3:30 pm  Evaluation of Risk Models for the Holistic Integration of Social Science Metrics into Watershed-Scale Risk Assessment. Cains MG*, Henshel DS, Landis WG; Indiana University   mgcains@indiana.edu

Abstract: Risk assessment in its traditional implementation is the simplification of a complex problem in order to better understand and predict from the basic cause and effect relationships of a system. This approach allows risk assessors to distill a complex issue into a manageable equation that produces quantitative, semi-quantitative, or qualitative answers. Defining characteristics (i.e. emergent properties) of complex systems are not easily distilled down to the component level (e.g. target organisms, stressors); rather, the most critical and defining risk characteristics emerge from the organization and interaction of components in the system. Many large scale risk assessments are limited by the focus on only a single risk domain within the interacting, complex system. This research emphasizes the inclusion of multiple influencing factors within a specific landscape of interest, not just singular and/or siloed risk assessments for ecology, human health, social studies, economic development, or policy impact. Such an endeavor requires the incorporation of all key aspects and risk domains (e.g. human health) of the landscape, combined with metrics reflecting the human infrastructure in order to understand the interactive relationships and effects of processes and stressors within the complex system. One of the challenges of integrating multiple domains and interactive relationships is the need to reconcile dissimilar assessment metrics and measurement metrics. This challenge is further amplified by differing scales of spatial, temporal, and biological units of organization for each domain. We discuss risk modeling challenges posed by the integration of societal and policy related assessment and measurement metrics. A suite of progressively integrative models (e.g. Total Environment, One Health Frameworks) are evaluated for their ability to holistically integrate social science metrics with human health and ecological metrics into a holistic and quantitative risk model.

W4-E.2  3:50 pm  Quantitative Tools for Linking Adverse Outcome Pathways with Process Models: Bayesian Relative Risk Networks. von Stackelberg KE*, Chu V, Mitchell C, Wallis L, Stark J, Landis W; Harvard Center for Health and the Global Environment   kvon@hsph.harvard.edu

Abstract: In a complex and changing environment (e.g., in the face of climate change) and with an increasing emphasis on sustainability of coupled human-natural systems, reductionist approaches to environmental management that fail to consider interactions, multiple stressors, and spatial and temporal characteristics of exposures and populations no longer suffice. Chemical risks and effects research has traditionally focused on adverse biological effects of chemical exposure to individuals.  A more comprehensive assessment of ecological risk links chemical effects on individuals to those at increasing levels of biological complexity and to evaluate the spatial and temporal context in which chemical exposures occur.  An integrated understanding of species activities (e.g., migration), physical stressors (e.g., habitat, climate, etc.) and biological factors (e.g., trophic interactions) is required to link individual-level exposures to population-, community- and ecosystem-level consequences. Adverse outcome pathways (AOPs) consider the continuum from molecular initiating events through a series of key events to adverse outcomes of regulatory interest. Here we demonstrate how existing data and models can be integrated through a Bayesian Relative Risk (BN-RRM) framework that explicitly links molecular initiating events to regulatory outcomes of interest and incorporates the influences of multiple stressors. The flexible approach allows multiple stressors linked to multiple outcomes based on integrating existing data and underlying process models. We provide several examples of ongoing case studies – one for chlorpyrifos exposures and an existing AOP based on acetylcholinesterase inhibition in fish in the Pacific Northwest, and another with a less well understood AOP based on immunotoxic effects of pefluorinated compounds.

W4-E.3  4:10 pm  Urban agglomeration nitrogen ecological risk assessment based on risk information model in Pearl River Delta. DONG YUE*, XU LINYU; Beijing Normal University   lvcanger@163.com

Abstract: The nitrogen cycle of urban agglomeration ecosystems have been widely altered by human activities,which in turn cause the endangerment at the whole city level. Ecological risk assessment(ERA) is capable of modeling and quantifying the potential impact on ecosystems and their components initiated by human disturbance.In this study,a conceptual conversion of flow currency in network was accomplished,i.e. from the material flow to the risk information flow.Based on the introduction of control allocation analysis and the estimation of the components’ sensitivities to the stressor,we developed a new type of network analysis for urban agglomeration ecological risk assessment.so-called risk information-based network model.The nitrogen ecological risk information network in urban agglomeration was used as a case study,The initial ecological risks were calculated based on the changes of nitrogen,and the propagation of resultant risk between all functional components of the ecosystem was tracked.By incorporating both direct and indirect ecosystem interactions,the risk conditions of the whole ecosystem and its components were quantified and illustrated in the information networks.The results showed that:(1)on both ecosystem level and component level,there were significant differences between integral risk and initial risk after disturbance due to network amplification effect; (2)almost all components had multiple sources of risk rather than solely received from the original input source(except the absolute controller,who only gives off risks but never receive one from other components);(3)the number of risk flow pathways notably increased from the input situation to network direct situation and to integral situation,implicating that the dynamics of the ecosystem are better manifested through a network perspective.

W4-E.4  4:30 pm  Mental models of climate change and food security in northwest Ghana. Wood AL*; North Carolina State University   alexa.l.wood@gmail.com

Abstract: Though climate change is expected to impact populations across the globe, marginalized communities will experience its most severe effects. At-risk communities are expected to face food shortages and decreased access to water. Sub-Saharan Africa is widely considered to be among the most vulnerable regions of the world, as semi-arid conditions are expected to expand southward. As temperatures increase, rainfall patterns will become less predictable, which will threaten the livelihoods of people across the region. Conditions in the Upper West region of Ghana reflect this trend; unpredictable rainfall has impacted the livelihoods of subsistence farmers. At present, there is a lack of research that focuses on the experiences and needs of individual farmers. It is thought that a more thorough understanding of the individuals’ experiences can help inform policymakers and lead to more effective strategies to mitigate climate stress. This project explores the perspectives of over 70 subsistence farmers in the Lawra District, located in the Upper West region of Ghana. The interview data will be translated into mental models, which graphically represent the decision-making processes of the farmers in the study. Mental models of two contrasting scenarios will be compared: customary practices versus responses to external pressure. The two models will depict how climate change has shifted traditional farming practices along with the new behaviors farmers have developed in response to environmental stress. This work will be used as part of a larger project to understand and model the impacts of climate change upon food security on a variety of social scales across Western Africa.



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