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Quantitative Evaluation of the Environmental Impact Quotient (EIQ) for Comparing Herbicides
Various indicators of pesticide environmental risk have been proposed, and one of the most widely known and used is the environmental impact quotient (EIQ). The EIQ has been criticized by others in the past, but it continues to be used regularly in the weed science literature. The EIQ is typically c...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Public Library of Science
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4487257/ https://www.ncbi.nlm.nih.gov/pubmed/26121252 http://dx.doi.org/10.1371/journal.pone.0131200 |
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author | Kniss, Andrew R. Coburn, Carl W. |
author_facet | Kniss, Andrew R. Coburn, Carl W. |
author_sort | Kniss, Andrew R. |
collection | PubMed |
description | Various indicators of pesticide environmental risk have been proposed, and one of the most widely known and used is the environmental impact quotient (EIQ). The EIQ has been criticized by others in the past, but it continues to be used regularly in the weed science literature. The EIQ is typically considered an improvement over simply comparing the amount of herbicides applied by weight. Herbicides are treated differently compared to other pesticide groups when calculating the EIQ, and therefore, it is important to understand how different risk factors affect the EIQ for herbicides. The purpose of this work was to evaluate the suitability of the EIQ as an environmental indicator for herbicides. Simulation analysis was conducted to quantify relative sensitivity of the EIQ to changes in risk factors, and actual herbicide EIQ values were used to quantify the impact of herbicide application rate on the EIQ Field Use Rating. Herbicide use rate was highly correlated with the EIQ Field Use Rating (Spearman’s rho >0.96, P-value <0.001) for two herbicide datasets. Two important risk factors for herbicides, leaching and surface runoff potential, are included in the EIQ calculation but explain less than 1% of total variation in the EIQ. Plant surface half-life was the risk factor with the greatest relative influence on herbicide EIQ, explaining 26 to 28% of the total variation in EIQ for actual and simulated EIQ values, respectively. For herbicides, the plant surface half-life risk factor is assigned values without any supporting quantitative data, and can result in EIQ estimates that are contrary to quantitative risk estimates for some herbicides. In its current form, the EIQ is a poor measure of herbicide environmental impact. |
format | Online Article Text |
id | pubmed-4487257 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-44872572015-07-02 Quantitative Evaluation of the Environmental Impact Quotient (EIQ) for Comparing Herbicides Kniss, Andrew R. Coburn, Carl W. PLoS One Research Article Various indicators of pesticide environmental risk have been proposed, and one of the most widely known and used is the environmental impact quotient (EIQ). The EIQ has been criticized by others in the past, but it continues to be used regularly in the weed science literature. The EIQ is typically considered an improvement over simply comparing the amount of herbicides applied by weight. Herbicides are treated differently compared to other pesticide groups when calculating the EIQ, and therefore, it is important to understand how different risk factors affect the EIQ for herbicides. The purpose of this work was to evaluate the suitability of the EIQ as an environmental indicator for herbicides. Simulation analysis was conducted to quantify relative sensitivity of the EIQ to changes in risk factors, and actual herbicide EIQ values were used to quantify the impact of herbicide application rate on the EIQ Field Use Rating. Herbicide use rate was highly correlated with the EIQ Field Use Rating (Spearman’s rho >0.96, P-value <0.001) for two herbicide datasets. Two important risk factors for herbicides, leaching and surface runoff potential, are included in the EIQ calculation but explain less than 1% of total variation in the EIQ. Plant surface half-life was the risk factor with the greatest relative influence on herbicide EIQ, explaining 26 to 28% of the total variation in EIQ for actual and simulated EIQ values, respectively. For herbicides, the plant surface half-life risk factor is assigned values without any supporting quantitative data, and can result in EIQ estimates that are contrary to quantitative risk estimates for some herbicides. In its current form, the EIQ is a poor measure of herbicide environmental impact. Public Library of Science 2015-06-29 /pmc/articles/PMC4487257/ /pubmed/26121252 http://dx.doi.org/10.1371/journal.pone.0131200 Text en © 2015 Kniss, Coburn http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Kniss, Andrew R. Coburn, Carl W. Quantitative Evaluation of the Environmental Impact Quotient (EIQ) for Comparing Herbicides |
title | Quantitative Evaluation of the Environmental Impact Quotient (EIQ) for Comparing Herbicides |
title_full | Quantitative Evaluation of the Environmental Impact Quotient (EIQ) for Comparing Herbicides |
title_fullStr | Quantitative Evaluation of the Environmental Impact Quotient (EIQ) for Comparing Herbicides |
title_full_unstemmed | Quantitative Evaluation of the Environmental Impact Quotient (EIQ) for Comparing Herbicides |
title_short | Quantitative Evaluation of the Environmental Impact Quotient (EIQ) for Comparing Herbicides |
title_sort | quantitative evaluation of the environmental impact quotient (eiq) for comparing herbicides |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4487257/ https://www.ncbi.nlm.nih.gov/pubmed/26121252 http://dx.doi.org/10.1371/journal.pone.0131200 |
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