A framework for ecological risk assessment at the EPA

Norton, Susan B.; Rodier, Donald J.; Schalie, William H. van der; Wood, William R.; Slimak, Michael W.; Gentile, John H.

doi:10.1002/etc.5620111202

Cited by 181 publications

(76 citation statements)

References 4 publications

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“…It could be used as a model by other countries for developing or improving their guidelines. There is an increasing interest in strengthening the assessment of ecological effects, up t o the level of human health risk, with emphasis on both direct and indirect effects of pesticides (or any stressor) to wildlife [95].…”

Section: Harmonizationmentioning

confidence: 99%

Overview and rationale for developing regulatory guidelines for nontarget plant testing with chemical pesticides

Boutin¹,

Freemark²,

Keddy

1995

Enviro Toxic and Chemistry

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In the assessment of ecological risk posed by pesticide use, much greater emphasis has been given to the direct effects on wildlife than on impacts on wildlife habitat. Assessment of indirect effects to wildlife entails an evaluation of pesticide toxicity to plant species (and invertebrates) that make up wildlife habitats. Under the pesticide registration process in Canada and in most other countries, there is no specific requirement for testing the toxicity of pesticides to nontarget plants other than agronomically important species. The proposed nontarget plant testing guidelines summarized in this paper are intended to fill this gap. The chief objectives of the guidelines are to outline data requirements, to suggest methods and approaches for generating the data required, and to facilitate and improve hazard assessment for nontarget plants (and habitats) as a result of chemical pesticide use. The rationale behind decisions reached in the guidelines is also presented. The proposed guidelines are very flexible, as registrants may be granted a waiver for any test required, provided the rationale is justified on appropriate scientific grounds. Harmonization and comparison with other guidelines are discussed. These proposed nontarget plant testing guidelines can serve as a basis for guideline development or modernization for other jurisdictions.

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Section: Harmonizationmentioning

confidence: 99%

Overview and rationale for developing regulatory guidelines for nontarget plant testing with chemical pesticides

Boutin¹,

Freemark²,

Keddy

1995

Enviro Toxic and Chemistry

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“…The ecological risk assessment to wildlife is, in part, determined by evaluating wildlife exposure to the pesticide and the pesticide's toxicological effects. To date, this has been done utilizing the quotient method where risk ϭ exposure/effects [1][2][3]. Exposure is represented by the Expected Environmental Concentration (EEC).…”

Section: Introductionmentioning

confidence: 99%

Field Evaluation of the Epa (Kenaga) Nomogram, a Method for Estimating Wildlife Exposure to Pesticide Residues on Plants

Pfleeger¹,

Fong²,

Hayes³

et al. 1996

Environ Toxicol Chem

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The Kenaga nomogram was developed by the U.S. Environmental Protection Agency (EPA) in the mid 1970s and has since been used prior to the registration of a pesticide to estimate the maximum potential pesticide residue level on plant material in the food chain of wildlife. The objective of this study was to evaluate the nomogram using field data. Six pesticides representing a variety of pesticide classes were applied to 15 plant species. Five of the six nomogram categories were tested with plant parts representing differences in surface morphology (i.e., glabrous vs. pubescent leaves). The sixth category was a mixed-grass community seeded with three grass species. Pesticide residue levels were determined the day of application and up to 32 d afterward. While the linear nomogram model does not represent the data as well as other models, relatively few data points (10%) collected on the day of pesticide application exceeded the nomogram predictions. The one systemic pesticide tested had degradation rates similar to nonsystemic pesticides in most categories. Present nomogram categories were significantly different from each other in most cases. However, the forage category should be combined with the leaves and leafy-crop category and have higher estimated residue levels than the Kenaga nomogram. A considerable amount of variation occurs in the level of pesticide residue on plant materials even under controlled experimental conditions and therefore nomogram values should be used as an estimate only until actual field residue data are available. The nomogram, with modifications, appears to be a reasonable regulatory device if careful thought is given in selecting the plant category for making residue estimates.

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“…However ecological security and ecological risk are related. In fact, parts of the concept of ecological security come from ecological risk [10,11,12]. Because many ecological disasters or degradation are caused by human activities, measurement of ecological security should represent the capability of human activities.…”

Section: Introductionmentioning

confidence: 99%

Urban Ecological Security Simulation and Prediction Using an Improved Cellular Automata (CA) Approach—A Case Study for the City of Wuhan in China

Gao

Zhang

et al. 2017

IJERPH

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Ecological security is an important research topic, especially urban ecological security. As highly populated eco-systems, cities always have more fragile ecological environments. However, most of the research on urban ecological security in literature has focused on evaluating current or past status of the ecological environment. Very little literature has carried out simulation or prediction of future ecological security. In addition, there is even less literature exploring the urban ecological environment at a fine scale. To fill-in the literature gap, in this study we simulated and predicted urban ecological security at a fine scale (district level) using an improved Cellular Automata (CA) approach. First we used the pressure-state-response (PSR) method based on grid-scale data to evaluate urban ecological security. Then, based on the evaluation results, we imported the geographically weighted regression (GWR) concept into the CA model to simulate and predict urban ecological security. We applied the improved CA approach in a case study—simulating and predicting urban ecological security for the city of Wuhan in Central China. By comparing the simulated ecological security values from 2010 using the improved CA model to the actual ecological security values of 2010, we got a relatively high value of the kappa coefficient, which indicates that this CA model can simulate or predict well future development of ecological security in Wuhan. Based on the prediction results for 2020, we made some policy recommendations for each district in Wuhan.

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A framework for ecological risk assessment at the EPA

Cited by 181 publications

References 4 publications

Overview and rationale for developing regulatory guidelines for nontarget plant testing with chemical pesticides

Overview and rationale for developing regulatory guidelines for nontarget plant testing with chemical pesticides

Field Evaluation of the Epa (Kenaga) Nomogram, a Method for Estimating Wildlife Exposure to Pesticide Residues on Plants

Urban Ecological Security Simulation and Prediction Using an Improved Cellular Automata (CA) Approach—A Case Study for the City of Wuhan in China

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