Risk management decisions for pesticides and threatened and endangered species: The role of uncertainty analysis

ABSTRACT Despite data gaps and information shortfalls, government agencies in the United States are expected to produce timely and defensible decisions to regulate pesticide use under the Federal Insecticide, Fungicide, and Rodenticide Act and in compliance with the Endangered Species Act. The decision to register a pesticide is predicated on a conclusion that no unreasonable effects will accrue to the environment, including threatened and endangered species. We recognize that the definition of acceptable risk is a policy judgment stemming from legislative language and judicial interpretation. However, a common risk assessment approach with similar technical underpinnings and a high degree of transparency used by all the agencies would be cost effective and more likely to achieve consensus among interested parties. Quantitative probabilistic risk assessment (PRA) methods can be used to develop risk estimates and to describe the level of confidence in these estimates. PRA methods can also differentiate among the contributions of natural stochasticity, measurement variability, and lack of knowledge. Because this approach enhances transparency and increases understanding of the implications of limited data sets and associated assumptions, we encourage the appropriate agencies to implement PRA methods as a means of reaching common ground when assessing risks of pesticides to listed species.

[1]  Bruce K. Hope,et al.  A Strategy for Using Weight-of-Evidence Methods in Ecological Risk Assessments , 2014 .

[2]  Anne Fairbrother,et al.  Ecological Risk Assessment and the Precautionary Principle , 1999 .

[3]  Larry Kapustka,et al.  Limitations of the Current Practices Used to Perform Ecological Risk Assessment , 2008, Integrated environmental assessment and management.

[4]  Jonathan I Levy,et al.  Science and Decisions: Advancing Risk Assessment , 2010, Risk analysis : an official publication of the Society for Risk Analysis.

[5]  D E Burmaster,et al.  Principles of good practice for the use of Monte Carlo techniques in human health and ecological risk assessments. , 1994, Risk analysis : an official publication of the Society for Risk Analysis.

[6]  Bruce K. Hope Exposure Gone “Wild”: A Call for Rational Exposure Scenarios , 2012 .

[7]  Timothy Barry,et al.  Health Risk Assessment Under Certainty: A Fuzzy-Risk Methodology , 1990 .

[8]  H M van der Werf,et al.  An indicator of pesticide environmental impact based on a fuzzy expert system. , 1998, Chemosphere.

[9]  Ethel Eljarrat,et al.  Application of fuzzy logic to the preliminary assessment of fish pollution due to lipophilic substance releases in rivers , 2007 .

[10]  Pernille Thorbek,et al.  Risk assessment considerations with regard to the potential impacts of pesticides on endangered species , 2015, Integrated environmental assessment and management.

[11]  Glenn W Suter,et al.  A Framework for Fully Integrating Environmental Assessment , 2008, Environmental management.

[12]  Roland W. Scholz,et al.  Low Risks, High Public Concern? The Cases of Persistent Organic Pollutants (POPs), Heavy Metals, and Nanotech Particles , 2010 .

[13]  Stan Kaplan,et al.  The Words of Risk Analysis , 1997 .

[14]  Max Henrion,et al.  Uncertainty: A Guide to Dealing with Uncertainty in Quantitative Risk and Policy Analysis , 1990 .

[15]  D. Burmaster,et al.  The Magnitude of Compounding Conservatisms in Superfund Risk Assessments1 , 1993 .

[16]  Nicholas P. Cheremisinoff,et al.  Federal Insecticide, Fungicide and Rodenticide Act , 1995 .

[17]  S. Kaplan,et al.  On The Quantitative Definition of Risk , 1981 .

[18]  A. Fairbrother,et al.  Are environmental regulations keeping up with innovation? A case study of the nanotechnology industry. , 2009, Ecotoxicology and environmental safety.

[19]  U. Epa,et al.  Guiding Principles for Monte Carlo Analysis , 1997 .

[20]  Chandler Stolp,et al.  The Visual Display of Quantitative Information , 1983 .

[21]  Andy Hart,et al.  Application of Uncertainty Analysis to Ecological Risks of Pesticides , 2010 .

[22]  Katherine McCoy,et al.  Information and Persuasion: Rivals or Partners? , 2000, Design Issues.

[23]  P. Slovic Perception of risk. , 1987, Science.

[24]  Edward Rolf Tufte,et al.  The visual display of quantitative information , 1985 .

[25]  D Moore,et al.  Uncertainty Analysis Using Classical and Bayesian Hierarchical Models , 2010 .

[26]  M. Kaul,et al.  OFFICE OF PREVENTION, PESTICIDES AND TOXIC SUBSTANCES , 2005 .

[27]  Lucien Duckstein,et al.  Fuzzy set and probabilistic techniques for health-risk analysis , 1991 .

[28]  Ocspp,et al.  Assessing Risks to Endangered and Threatened Species from Pesticides – 4th Interagency Workshop on Joint Interim Approaches to NAS Recommendations , 2015 .