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Forbes VE, Galic N, Schmolke A, Vavra J, Pastorok R, Thorbek P. Assessing the risks of pesticides to threatened and endangered species using population modeling: A critical review and recommendations for future work. Environ Toxicol Chem 2016; 35:1904-13. [PMID: 27037541 DOI: 10.1002/etc.3440] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/21/2016] [Revised: 02/26/2016] [Accepted: 03/29/2016] [Indexed: 05/28/2023]
Abstract
United States legislation requires the US Environmental Protection Agency to ensure that pesticide use does not cause unreasonable adverse effects on the environment, including species listed under the Endangered Species Act (ESA; hereafter referred to as listed species). Despite a long history of population models used in conservation biology and resource management and a 2013 report from the US National Research Council recommending their use, application of population models for pesticide risk assessments under the ESA has been minimal. The pertinent literature published from 2004 to 2014 was reviewed to explore the availability of population models and their frequency of use in listed species risk assessments. The models were categorized in terms of structure, taxonomic coverage, purpose, inputs and outputs, and whether the models included density dependence, stochasticity, or risk estimates, or were spatially explicit. Despite the widespread availability of models and an extensive literature documenting their use in other management contexts, only 2 of the approximately 400 studies reviewed used population models to assess the risks of pesticides to listed species. This result suggests that there is an untapped potential to adapt existing models for pesticide risk assessments under the ESA, but also that there are some challenges to do so for listed species. Key conclusions from the analysis are summarized, and priorities are recommended for future work to increase the usefulness of population models as tools for pesticide risk assessments. Environ Toxicol Chem 2016;35:1904-1913. © 2016 SETAC.
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Affiliation(s)
- Valery E Forbes
- Department of Ecology, Evolution and Behavior, University of Minnesota, St. Paul, Minnesota, USA
| | - Nika Galic
- Department of Ecology, Evolution and Behavior, University of Minnesota, St. Paul, Minnesota, USA
| | - Amelie Schmolke
- Department of Ecology, Evolution and Behavior, University of Minnesota, St. Paul, Minnesota, USA
| | - Janna Vavra
- School of Biological Sciences, University of Nebraska-Lincoln, Lincoln, Nebraska, USA
| | | | - Pernille Thorbek
- Environmental Safety, Jealott's Hill International Research Centre, Syngenta, Bracknell, UK
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Reed M, Alvarez T, Chelinho S, Forbes V, Johnston A, Meli M, Voss F, Pastorok R. A risk assessment example for soil invertebrates using spatially explicit agent-based models. Integr Environ Assess Manag 2016; 12:58-66. [PMID: 26411378 DOI: 10.1002/ieam.1713] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/06/2015] [Revised: 07/24/2015] [Accepted: 09/11/2015] [Indexed: 06/05/2023]
Abstract
Current risk assessment methods for measuring the toxicity of plant protection products (PPPs) on soil invertebrates use standardized laboratory conditions to determine acute effects on mortality and sublethal effects on reproduction. If an unacceptable risk is identified at the lower tier, population-level effects are assessed using semifield and field trials at a higher tier because modeling methods for extrapolating available lower-tier information to population effects have not yet been implemented. Field trials are expensive, time consuming, and cannot be applied to variable landscape scenarios. Mechanistic modeling of the toxicological effects of PPPs on individuals and their responses combined with simulation of population-level response shows great potential in fulfilling such a need, aiding ecologically informed extrapolation. Here, we introduce and demonstrate the potential of 2 population models for ubiquitous soil invertebrates (collembolans and earthworms) as refinement options in current risk assessment. Both are spatially explicit agent-based models (ABMs), incorporating individual and landscape variability. The models were used to provide refined risk assessments for different application scenarios of a hypothetical pesticide applied to potato crops (full-field spray onto the soil surface [termed "overall"], in-furrow, and soil-incorporated pesticide applications). In the refined risk assessment, the population models suggest that soil invertebrate populations would likely recover within 1 year after pesticide application, regardless of application method. The population modeling for both soil organisms also illustrated that a lower predicted average environmental concentration in soil (PECsoil) could potentially lead to greater effects at the population level, depending on the spatial heterogeneity of the pesticide and the behavior of the soil organisms. Population-level effects of spatial-temporal variations in exposure were elucidated in the refined risk assessment, using ABMs and population-level endpoints while yielding outputs that directly address the protection goals. We recommend choosing model outputs that are closely related to specific protection goals, using available toxicity data and accepted fate models to the extent possible in parameterizing models to minimize additional data needs and testing, evaluating, and documenting models following recent guidance.
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Affiliation(s)
- Melissa Reed
- Chemicals Regulation Directorate, HSE, Mallard House, Kings Pool, York, UK
| | - Tania Alvarez
- EcoRisk Solutions Ltd., The Kernel, Walnut Hill, Surlingham, Norwich, Norfolk, UK
| | - Sónia Chelinho
- CFE-Centre for Functional Ecology, Department of Life Sciences, University of Coimbra, Coimbra, Portugal
| | - Valery Forbes
- School of Biological Sciences, University of Nebraska-Lincoln, Lincoln, Nebraska, USA
| | - Alice Johnston
- School of Biological Sciences, University of Reading, UK
| | - Mattia Meli
- Department of Environmental, Social and Spatial Change, Roskilde University, Denmark
- Current address: Rifcon GmbH, Hirschberg, Germany
| | - Frank Voss
- Dr. Knoell Consult GmbH, Mannheim, Germany
| | - Rob Pastorok
- Integral Consulting, Inc., Woodinville, Washington, USA
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Forbes VE, Brain R, Edwards D, Galic N, Hall T, Honegger J, Meyer C, Moore DRJ, Nacci D, Pastorok R, Preuss TG, Railsback SF, Salice C, Sibly RM, Tenhumberg B, Thorbek P, Wang M. Assessing pesticide risks to threatened and endangered species using population models: Findings and recommendations from a CropLife America Science Forum. Integr Environ Assess Manag 2015; 11:348-354. [PMID: 25655086 DOI: 10.1002/ieam.1628] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/22/2014] [Revised: 10/29/2014] [Accepted: 01/20/2015] [Indexed: 06/04/2023]
Abstract
This brief communication reports on the main findings and recommendations from the 2014 Science Forum organized by CropLife America. The aim of the Forum was to gain a better understanding of the current status of population models and how they could be used in ecological risk assessments for threatened and endangered species potentially exposed to pesticides in the United States. The Forum panelists' recommendations are intended to assist the relevant government agencies with implementation of population modeling in future endangered species risk assessments for pesticides. The Forum included keynote presentations that provided an overview of current practices, highlighted the findings of a recent National Academy of Sciences report and its implications, reviewed the main categories of existing population models and the types of risk expressions that can be produced as model outputs, and provided examples of how population models are currently being used in different legislative contexts. The panel concluded that models developed for listed species assessments should provide quantitative risk estimates, incorporate realistic variability in environmental and demographic factors, integrate complex patterns of exposure and effects, and use baseline conditions that include present factors that have caused the species to be listed (e.g., habitat loss, invasive species) or have resulted in positive management action. Furthermore, the panel advocates for the formation of a multipartite advisory committee to provide best available knowledge and guidance related to model implementation and use, to address such needs as more systematic collection, digitization, and dissemination of data for listed species; consideration of the newest developments in good modeling practice; comprehensive review of existing population models and their applicability for listed species assessments; and development of case studies using a few well-tested models for particular species to demonstrate proof of concept. To advance our common goals, the panel recommends the following as important areas for further research and development: quantitative analysis of the causes of species listings to guide model development; systematic assessment of the relative role of toxicity versus other factors in driving pesticide risk; additional study of how interactions between density dependence and pesticides influence risk; and development of pragmatic approaches to assessing indirect effects of pesticides on listed species.
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Affiliation(s)
- V E Forbes
- School of Biological Sciences, University of Nebraska-Lincoln, Lincoln, Nebraska, USA
| | - R Brain
- Syngenta Crop Protection, Greensboro, North Carolina, USA
| | - D Edwards
- BASF Corporation, Research Triangle Park, North Carolina, USA
| | - N Galic
- School of Biological Sciences, University of Nebraska-Lincoln, Lincoln, Nebraska, USA
| | - T Hall
- Bayer CropScience, Research Triangle Park, North Carolina, USA
| | | | - C Meyer
- ARCADIS, Lakewood, Colorado, USA
| | - D R J Moore
- Intrinsik Environmental Sciences (US), New Gloucester, Maine
| | - D Nacci
- USEPA, Narragansett, Rhode Island
| | - R Pastorok
- Integral Consulting, Woodinville, Washington, USA
| | - T G Preuss
- Bayer CropScience AG, Monheim am Rhein, Germany
| | - S F Railsback
- Department of Mathematics, Humboldt State University, Arcata, California, USA
| | - C Salice
- Towson University, Environmental Science and Studies Program, Towson, Maryland, USA
| | - R M Sibly
- School of Biological Sciences, University of Reading, Reading, UK
| | - B Tenhumberg
- School of Biological Sciences, University of Nebraska-Lincoln, Lincoln, Nebraska, USA
| | - P Thorbek
- Syngenta, Jealott's Hill International Research Centre, Bracknell, UK
| | - M Wang
- WSC Scientific GmbH, Heidelberg, Germany
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Forbes VE, Calow P, Grimm V, Hayashi T, Jager T, Palmqvist A, Pastorok R, Salvito D, Sibly R, Spromberg J, Stark J, Stillman RA. Integrating population modeling into ecological risk assessment. Integr Environ Assess Manag 2010; 6:191-3. [PMID: 20821684 DOI: 10.1002/ieam.25] [Citation(s) in RCA: 13] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
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