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View workshop recording at the SETAC Live Learning Center.


Sunday, November 17, 2013, 1:00 pm – 6:30 pm (13:00-17:30)

SETAC North America, Nashville, Tennessee

Sponsors: Global Ecological Risk Assessment Advisory Group
Mechanistic Effect Models for Ecological Risk Assessment of Chemicals


Global Ecological Risk Assessment Advisory Group (ERA AG)

Mechanistic Effect Models for Ecological Risk Assessment of Chemicals (MeMoRisk)


Workshop Chair: Valery E. Forbes

Director, School of Biological Sciences

University of Nebraska-Lincoln, Professor

Lincoln, Nebraska, USA

Workshop Co-Chair: Diane Nacci

Research Biologist


Narragansett, RI, USA

Workshop Co-Chair: Mary Sorensen

Chair of SETAC's Global Ecological Risk Assessment Advisory Group

ENVIRON International Corporation, Senior Science Advisor

Georgia, USA.


There are various pressures to develop new approaches to the ecological risk assessment of chemicals. On the one hand there is pressure to test more chemicals, leading to economic pressures to reduce the costs of tests and to speed them up, and also ethical pressures to reduce the use of animals in testing. One response to these pressures is to make better use of observations on suborganismal responses arising from chemical perturbations to make an assessment of the likelihood of impact on targets of concern. Frameworks such as Adverse Outcome Pathway (AOP) take this approach. This framework offers the promise of identifying mechanisms that are responsive to chemical perturbation and of building in vitro testing methods around them. On the other hand, there are also calls for developing more holistic risk assessments that are more in tune with the needs of risk management, that relate more obviously to the objects of protection, and that thus express impacts in terms of health and/or ecosystem services. Finally, there are calls for approaches that make more explicit links between exposure and effects and that move away from expressing risks in terms of simple thresholds and toward outputs that can better inform management decisions. Mechanistic effect models encompass a broad range of quantitative tools to address these issues and support the quantification of risks for tested and untested chemical stressors.

Speakers representing the academia, regulatory agencies, and industry tripartite are participating in a workshop intended to discuss how lessons learned from recent and ongoing initiatives in Europe and North America could facilitate the development and implementation of predictive modeling tools in the regulatory risk assessment of chemicals. The workshop is a mix of invited talks and panel discussions where audience participation will be encouraged.

Opening Remarks from OrganizerS

· Valery Forbes, University of Nebraska, Lincoln, USA

· Diane Nacci, US EPA, Narragansett, Rhode Island, USA

· Mary Sorensen, ENVIRON International Corporation, Georgia, USA


· Peter Calow, University of Nebraska, Lincoln, NE, USA

· Virginie Ducrot, INRA France

· Udo Hommen, Fraunhofer IME, Germany

· Tom Purucker, US EPA, Athens, GA, USA

· Christopher Mebane, US Geological Survey, Boise, ID, USA

· Anne Fairbrother, Exponent, Inc., WA, USA

· Annemette Palmqvist, Roskilde University, Roskilde, Denmark

· Mattia Meli, Roskilde University, Roskilde, Denmark

· Kristina Garber, US EPA, Environmental Fate and Effects Division (EFED), Washington, DC, USA

· Irvin Schultz, Battelle Pacific Northwest National Laboratory, Sequim, WA, USA

· Valery Forbes, University of Nebraska, Lincoln, USA

Speakers DETAIL

Peter Calow

University of Nebraska, Lincoln, NE, USA

Research Professor

Getting at What Really Matters in Managing Ecological Risks Through Mechanistic Effect Models

Ecological risk assessments ought to be expressed in terms of the way ecological things that matter to the public are affected by exposure to a chemical. They rarely are. There is a big gap between these protection goals and the endpoints that we measure and use in assessments. This means that judgments (involving values) on what the assessments mean for management are often made by assessors and managers. Mechanistic effect models, in association with ecosystem service thinking, have the potential for making the links between test endpoints and what managers need to manage more explicit and (hopefully) more transparent.

Virginie Ducrot

UMR INRA - Agrocampus ESE, Ecologie et Santé des Ecosystèmes, France


Overview of CREAM Accomplishments

CREAM is a Marie Curie Initial Training Network funded by the EC, which involves 23 partners from academia, regulatory authorities and industry. It aimed at training 23 PhD/post-docs over Europe in ecological modeling and risk assessment. It allowed developing mechanistic effect models (MEMs) for a suite of species/systems relevant for the risk assessment of plant protection products (PPP) in Europe. The emphasis was put on exploring links between exposure and effects and forecasting population-level effects, so as to meet protection goals defined by the recent EU regulation, and on developing guidance for good modelling practice. Models were experimentally validated and documented using the TRACE framework. Overall, CREAM has provided models, guidance on good modelling practices and trained modelers/stakeholders, which will contribute to MEM implementation in future risk assessments of PPP in Europe.

Udo Hommen

Fraunhofer IME, Department Ecotoxicology, Germany


How to use effects models in pesticide risk assessment – recommendations of the MODELINK workshop

Mechanistic effect models offer several possibilities to improve our environmental risk assessments but until now they have not often been accepted in the regulatory risk assessment of plant protection products in Europe. However, now some initiatives and projects address the different challenges to improve the situation. The SETAC Europe workshop MODELINK focused on when and how to use such models within our risk assessment schemes. Six case studies cover the different groups of non- target organisms which are routinely considered in the environmental risk assessment of pesticides and models were used to extrapolate e.g. from the constant exposure situation in the laboratory to variable exposure in space and time in the field or from measured individual level endpoints to effects on populations. Examples of problem definitions, species and scenario selection, and model outputs will be shown. The models provided more detailed and more realistic outputs compared to the tiered experimental approach alone. However, for using these outputs for risk management more explicit decisions on acceptable effects have to be made. One of the main MODELINK recommendations is to define specific quantitative protection goals for the different potentially affected key drivers of the ecosystem services we want to protect in agricultural landscapes.

Tom Purucker



Web-Enabling Ecological Risk Assessment for Accessibility and Transparency

Ecological risk methods and tools are necessarily diverse to account for different combinations of receptors, exposure processes, effects estimation, and degree of conservatism/realism necessary to support chemical-based assessments. These tools have been continuously developed since the early 1980s and are currently accessible through a number of software platforms (e.g., DOS-based FORTAN executables, spreadsheet-based calculations, form-based Windows programs) that can lead to inefficiencies and inconsistencies when used together to inform an assessment. Recent advances in cloud-based computing provides an opportunity to integrate commonly used ecological risk models as a web application dashboard that allows for the modular execution of individual models as well as the simultaneous execution of multiple models in a serial or parallel manner. We have created an integrated web-based tool, the übertool (, designed to run EPA models that estimate exposure doses and ecological risks under the Federal Insecticide, Fungicide, and Rodenticide Act (FIFRA) and the Endangered Species Act (ESA). These models include a number of aquatic, terrestrial, and atmospheric deposition fate and transport models used to estimate pesticide exposures and effects for a range of ecological receptors. We have also extended the übertool's web-based framework to create the untertool (, which gives examples of population dynamic models that are often used for educational and research purposes. By aggregating such models into a virtual dashboard and providing them as web services, we hope to help narrow the gap between ecological hazard assessment/risk quotient approaches that address individual effects endpoints and the difficult task of reliably assessing ecological endpoints at the population level. Closing this gap is necessary to create a common, scientifically credible approach to resolve such endpoint assessment discrepancies and is a current focus of interagency discussion in the US with respect to ecological risk activities in support of the Endangered Species Act.

Christopher Mebane

US Geological Survey, Boise, ID, USA

Water Quality Specialist

Evaluating the Protectiveness of Water Quality Criteria for Threatened or Resilient Species: Judgments, Models, and Back to Judgments

Water quality criteria are often derived with at least an implicit goal of protecting populations, communities, and ecosystems. This is usually done by extrapolating laboratory toxicity data to populations in the wild through informal assumptions and judgments. Population modeling can be useful exercises for extrapolating laboratory effects data to populations, sensitivity analyses, and contrasting management alternatives. However, the construction of population models requires many decisions, some of which in turn must be based on assumptions and judgments. Finally, the modeling results must be interpreted and presented to managers, which requires additional judgments by the analysts how to portray the results. These ideas will be illustrated through examples with a threatened anadromous Chinook Salmon population and with a resilient, "weedy” invertebrate, the amphipod Hyalella sp.

Coffee Break

Anne Fairbrother

Exponent, Inc., WA, USA

Principal Scientist & Office Director

Recommendations for Ecological Models to Assess Risks to Endangered and Threatened Species

Species in danger of local or global extinction typically are granted a special status and a higher level of protection from the adverse consequences of exposure to toxic chemicals and/or pesticides. Recent legal challenges in the United States have questioned the methods used to assess risks of existing or new pesticides to such species, highlighting the differences between the chemocentric approach used by the U.S. Environmental Protection Agency when registering pesticides, and the biocentric approach use by the U.S. Fish and Wildlife Service or the National Oceanic and Atmospheric Administration when writing their biological opinions. The National Academy of Sciences (NAS) convened a special committee to identify commonalities between the approaches and recommend a unified method for assessing risks to listed species. The NAS committee ultimately recommended a tiered approach that looks first at exposure and use patterns to determine species potentially at risk, then applies screening tools to assess the relationship between the toxicological mechanisms of action and the physiology of the species of concern. Those chemicals that result in a conclusion of "likely to affect” a listed species' survival or reproduction are further evaluated at the highest tier, where population models and environmental monitoring are employed to estimate whether, and by how much, the trend towards extinction would be exacerbated by chemical exposure. To account for uncertainty in both effects and exposure assessments, a probabilistic approach is preferred. The recommended tiered approach highlights the need for the integration of toxicological and ecological methods when addressing questions of populations and extinction rates.

Annemette Palmqvist

Roskilde University, Roskilde, Denmark

Associate Professor

Linking exposure and effects in ERA – lessons learned from a nanoparticle example

In environmental risk assessment (ERA) of chemicals the procedures for assessing exposure and effects are largely uncoupled, and the methods accepted and used in the two aspects of ERA are immensely different. For exposure assessment it is widely accepted to use models of differing complexity based on certain release- and environmental scenarios. On the other hand, effect assessments are largely based on results from simplified laboratory experiments, that rarely include environmental variability and which are analyzed by simple static models such as dose-response models or species sensitivity distribution models. More recently the use of mechanistic effects models (MEMs) in ERA of, in particular, pesticides has been promoted and is gaining momentum. So far attempts to explore the use of MEMs in ERA of other types of chemicals are more limited. In this talk I will present to you some of the lessons learned from an EU financed project on Modeling Nanoparticle Toxicity (ModNanoTox) related to the potential implementation and use of MEMs in nanoparticle ERA. The aim of the presentation is twofold: 1) to show that MEMs offer an ecologically more relevant way of addressing effects of chemicals in the environment, both with regard to including the appropriate protection goal and the relevant environmental compartment, and 2) to show that such models may also provide an opportunity to directly link exposure and effect assessments.

Mattia Meli

Roskilde University, Roskilde, Denmark


Mechanistic Models to Explore Population Impacts of Spatially Variable Exposure

In assessing ecological risks for terrestrial ecosystems, heterogeneous distribution of contaminants is often disregarded. We developed a spatially explicit individual-based model to explore how the interaction of different patterns of microscale fragmentation caused by the presence of a persistent pollutant heterogeneously distributed in soil, combined with disturbance events, which can be both natural (e.g. drought) and anthropogenic (e.g. pesticide applications) stress factors, affects the population dynamics of the collembolan, F. candida, and its recovery after stress. Individuals in the model can sense and avoid contaminated habitat. Avoidance of toxicant influences the feeding behavior of the organisms, and this in turn affects all the other biological processes. Simulation results show that when the uncontaminated area is small (< 10%), stable population size is bigger in the case of spatially correlated distributions of toxicant, whereas as the proportion of clean habitat increases, population growth is higher with uncorrelated contamination. This pattern changes when avoidance behavior is excluded from the model, as does population recovery after a series of disturbance events. The model suggests that a combination of heterogeneous contamination and multiple stressors can lead to unexpected effects of toxicants at the population level. Individual-based models can help to understand these effects and can add ecological realism to environmental risk assessment of chemicals.

Kristina Garber

US EPA, Environmental Fate and Effects Division (EFED), Washington, DC, USA

Senior Scientist

Multiple Stressors Affecting Bees: Population Modeling Approach

This presentation will provide an overview of the models currently used by the office of United States Environmental Protection Agency's Office of Pesticide Programs for assessing the environmental fate and associated ecological risks of pesticides. Models that are currently in development, including probabilistic approaches for assessing effects to birds and honey bee colony simulation models will also be discussed.

Irvin Schultz

Battelle Pacific Northwest National Laboratory, Sequim, WA, USA

Senior Scientist

Recent Developments in Adverse Outcome Pathway Models

An adverse outcome pathway (AOP) is a conceptual framework linking molecular-level initiating event(s) with adverse effects at the individual and population level. Future environmental risk assessments are anticipated to rely heavily on QSAR and in vitro derived toxicity data, which will need to be extrapolated across biological scales to relevant risk assessment endpoints. To provide a stronger mechanistic basis for extrapolation, computational models are being developed that more closely link toxicant induced cellular or sub-cellular perturbations with traditional apical or whole organism measures of response. An additional component of the AOP is to incorporate environmental fate and toxicokinetic models to convert in vitro exposure levels into the corresponding environmental levels needed to achieve relevant target organ concentrations (sometimes referred to as reverse toxicokinetics). In this presentation, I will provide a description of the AOP process with examples of approaches being used for in vitro extrapolation and reverse toxicokinetics including recent developments in computational models for aquatic species.

Valery Forbes

University of Nebraska, Lincoln, NE, USA

Director, School of Biological Sciences

Where do we go from here?

Important progress has been made in the development, communication, and testing of mechanistic effect models for ecological risk assessment. Much of this progress has come out of European initiatives, and most efforts have been focused on using models to assess the risks of pesticides in agricultural landscapes under European legislation. Given these advances, it is now time to consider whether and how such models have a role to play in the risk assessment of other classes of chemicals, to systematically assess the opportunities and challenges for using models in different regulatory contexts, such as under REACH or for Superfund assessments, and to expand the models' capabilities to cross more levels of biological organization. A key question is whether it is possible to develop a single, integrated modeling framework that would allow robust linkages to be made from molecular events, through organismal responses, to population- and community-level impacts and ultimately to the delivery of ecosystem services that are the targets of protection. Advances in the computational sciences and in sensor technology offer promising tools, but success will require multi-disciplinary collaboration and active engagement of all stakeholder groups.



Background – Activities

During the last decade a series of international workshops, hosted in both Europe and North America, have explored the opportunities and obstacles for implementing ecological modeling into regulatory risk assessment. They include the Pellston Workshop on Population-Level Ecological Risk Assessment held in Roskilde, Denmark in 2003; the LEMTOX Workshop, held in Leipzig, Germany in 2007, the USEPA Risk Assessment Forum Technical Workshop on Population-Level Ecological Risk Assessment held in Washington, DC in 2008, and the Roskilde Workshop on Integrating Population Modeling into Ecological Risk Assessment (RUC09), held in Roskilde, Denmark in 2009.

Chemical Risk Effects Assessment Models (CREAM) is a "Marie Curie Initial Training Network (ITN)” funded by the European Commission within the 7th Framework Programme, from 2009-2013. Its focus has been on developing Good Modeling Practice and on first-class training of early stage researchers. CREAM is very likely the largest joint project worldwide developing mechanistic effect models for risk assessment of chemicals.

A SETAC Advisory Group on Mechanistic Effect Models for Ecological Risk Assessment of Chemicals (MeMoRisk) was established in 2008. The overall aim of the advisory group is to explore and evaluate the benefit of mechanistic effect modeling for the risk assessment of chemicals.

A two-part SETAC Europe technical workshop, MODELINK, was held in the fall of 2012 (Le Croisic, France) and spring 2013 (Monschau, Germany) to provide guidance for when and how to apply ecological models to regulatory risk assessment of pesticides by developing specific case studies representing common risk scenarios.

Background – Scientific papers

Forbes VE, Calow P. 2012. Promises and problems for the new paradigm for risk assessment and an alternative approach involving predictive systems models. Environ Toxicol Chem. 31: 2663-2671.

Forbes VE, Calow P. 2013. Developing predictive systems models to address complexity and relevance for ecological risk assessment. Integr Environ Assess Manag. 9: e75-e80.

Nienstedt K, Brock T, van Wensem J, Montforts M, Hart A, Hardy A, Aagaard A, Alix A, Boesten J, Bopp SK, Brown C, Capri E, Forbes VE, Köpp H, Liess M, Luttik R, Maltby L, Sousa P, Streissl F. 2012. Development of a framework based on an ecosystem services approach for deriving specific protection goals for environmental risk assessment of pesticides. Sci Tot Environ 415: 31-38.

Forbes VE, Calow P, Grimm V, Hayashi TI, Jager T, Katholm A, Palmqvist A, Pastorok R, Salvito D, Sibly RM, Spromberg J, Stark J, Stillman RA. 2011. Adding value to ecological risk assessment with population modeling. Human Ecol Risk Assess 17:287-299.

Preuss TG, Hommen U, Alix A, Ashauer R, van den Brink P, Chapman P, Ducrot V, Forbes VE, Grimm V, Schäfer D, Streissl F, Thorbek P. 2009. Mechanistic effect models for ecological risk assessment of chemicals (MEMoRisk) – a new SETAC-Europe Advisory Group. Environ Sci Pollut Res. 16: 250-252.

Grimm V, Ashauer R, Forbes V, Hommen U, Preuss TG, Schmidt A, van den Brink PJ , Wogram J, Thorbek P. 2009. CREAM: A European project on mechanistic effect models for ecological risk assessment of chemicals. Environ Sci Pollut Res. 16: 614-617.

Forbes VE, Hommen U, Thorbek P, Heimbach F, Van den Brink PJ, Wogram J, Thulke H-H, Grimm V. 2009. Ecological models in support of regulatory risk assessments of pesticides: developing a strategy for the future. Integr Environ Assess Manag 5: 167-172.





Valery E. Forbes



Diane Nacci



Mary Sorensen




Peter Calow



Virginie Ducrot



Udo Hommen



Tom Purucker



Christopher Mebane





Anne Fairbrother



Annemette Palmqvist



Mattia Meli



Kris Garber



Irvin Schultz



Valery Forbes