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Predicting ecological outcomes from exposure to chemicals and other stressors

Description:

While regulations have traditionally been based upon adverse biological effects of chemicals to individuals, environmental sustainability requires healthy populations, communities, and ecosystems. Thus, more comprehensive ecological risk assessment must link chemical effects on individuals to those at increasing levels of biological complexity, and take into account the context in which chemical exposures occur, including physical stressors (e.g., habitat availability and quality) and biological factors (e.g., prey availability, predation). Integrated systems approaches can provide the necessary frameworks and mechanisms to account for relevant environmental, chemical, biological, and ecological information, resulting in more efficient, comprehensive, and realistic ecological risk assessments.

Rationale and Research Approach:

In this task, ORD and Program Office staff will collaboratively address high priority needs for Tier II and III level ecological risk assessments that require methods to integrate environmentally realistic chemical exposures into the prediction of effects at the levels of the population, community, and ultimately, whole ecosystems. Research described in this task will culminate in the development and testing of integrated systems and their components to link chemical exposures and ecological effects. Methods and diagnostic metrics will be developed for well-studied chemicals and those of emerging concern that more accurately predict realistic spatial and temporal distributions of chemicals in various environments. The output from these environmental exposure models will be linked to ecological models that translate chemical distributions into biological and ecological outcomes.

An important overarching strategy for this task will be to bring together state-of-science components into these integrated systems. Thus, significant integration and synergy will occur with CSS Biomarkers and Extrapolation topics, where molecular- and population-level approaches and tools are being developed, and the Systems Models Adverse Outcome Pathway Project (CSS 2.1), where biologically-based models linking molecular to population effects of chemical stressors are being explored. Although methods to extrapolate adverse outcomes to higher levels of biological organization are in exploratory stages of development, research proposed in this task will advance important goals for assessing ecological risks to communities and ecosystems, evolving towards the incorporation into environmental regulations of sustainability endpoints. This research will result in the development and evaluation of source-to-outcome pathways, their components, and information needs to develop systems model approaches. The systems approaches being developed here will be designed explicitly to link exposure and ecological effects in a manner not currently available.

While the systems approaches and components are designed to be broadly useful, application and testing of these methods will address an assortment of environments, chemicals, and faunal groups considered high priority, and to fill or quantify the uncertainty associated with existing gaps as identified by Program Offices and Regions. System components and approaches will reflect current advances in ecological knowledge to better understand chemical risks, such as methods to evaluate competing risks from chemical and other stressors and the relative cost/benefit of complexity in population models. We will also advance next-generation genetic and genomic approaches to assess risk of chemical contaminant (e.g., pesticides) and non-contaminant (e.g., habitat fragmentation) stressors to the persistence of key aquatic populations. Individual and population level metrics will be developed using innovative molecular tools to provide information needed for training and evaluating spatially explicit models, thereby improving the realism of predictions of population level outcomes (in coordination with SSWR Goal 2, Themes 1.2 and 2.2).

Systems approaches will be developed and tested using case studies that reflect high priorities and needs for the Program Office and Regions, such as a novel ecosystem modeling approach to integrate ecological effects of multiple stressors as applied to urban/residential estuaries (coordination with SSWR Question 6 project, Narragansett Bay Signature Project). This approach will link watershed-based exposures to ecological effects, e.g., evaluating existing/development of urban/residential exposure models for selected high priority chemicals of (e.g., pyrethroids, nanomaterials). Our research will also further the development and application of a spatially-explicit model (i.e., HexSim) for evaluating the risks from spatially structured chemical and non-chemical stressors on wildlife and human populations across small and large areas or regions.

MED Scientists:

Matt Etterson

Publications:

Custer, C., T.W. Custer, P.W. Dummer, M.A. Etterson, W.E. Thogmartin, Q. Wu, K. Kannan,
A. Trowbridge, and P.A. McKann. Exposure and effects of perfluorinated compounds in tree swallows nesting in Minnesota and Wisconsin, USA. Archives of Environmental Contamination and Toxicology (in press).

Etterson, M.A. A transition-matrix approach to estimating animal mortality from anthropogenic hazards.
Ecological Applications (in press).

Custer, C.M., T.W. Custer, P.M. Dummer, M.A. Etterson, W.E. Thogmartin, Q. Wu, K. Kannan, A. Trowbridge, and P.C. McKann. 2014. Exposure and effects of perfluoroalkyl substances in tree swallows nesting in Minnesota and Wisconsin, USA.  Archives of Environmental Contamination and Toxicology 66:120-138.

Etterson, M.A. 2013. Hidden Markov models for estimating animal mortality from anthropogenic hazards. Ecological Applications 23:1915-1925.

Etterson, M.A. 2013. Technical Manual for MCestimate. EPA report, EPA/600/B-13/164, 22 pp.

Etterson, M.A. 2013. User's Guide for MCestimate. EPA report, EPA/600/R-13/270, 41 pp.

Johnson, T.N., P.L. Kennedy, and M.A. Etterson. 2012. Nest success and cause-specific nest failure of grassland passerines breeding in prairie grazed by livestock. Journal of Wildlife Management 76:1607-1616.

Jackson, A.K., D.C. Evers, M.A. Etterson, A.M. Condon, S.B. Folsom, J. Detweiler, J. Schmerfeld, and D.A. Cristol. 2011. Mercury exposure affects the reproductive success of a free-living terrestrial songbird, the Carolina wren (Thryothorus ludovicianus). The Auk 128: 759-769.

Expected Products:

Date

Product

Contact

Sep 30, 2013

Software, guidance describing Markov Chain estimation of survival probabilities in presence of competing risks (MCestimate) for application to human health and ecological risk case studies.

Matthew Etterson

Sep 30, 2016

Evaluation and guidance on the application to human and ecological risk assessment of statistical approaches to provide time and cost efficient assessment of competing risks through MCestimate software multiple-decrement life table analysis, and classical survival analysis.

Matthew Etterson

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