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Quantitative Evaluation of the Environmental Impact Quotient (EIQ) for Comparing Herbicides.

Kniss AR, Coburn CW - PLoS ONE (2015)

Bottom Line: 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.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.

View Article: PubMed Central - PubMed

Affiliation: Department of Plant Sciences, University of Wyoming, Laramie, Wyoming, United States of America.

ABSTRACT
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.

No MeSH data available.


Related in: MedlinePlus

The relationship between plant surface half-life risk factor (P) and EIQ value for 116 herbicides (Senseman data set).Filled circles with error bars represent means and standard errors, grey open circles represent individual herbicides (N = 116). For box-plots, dark bars represent median EIQ value, boxes enclose the first and third quartiles; preemergence (PRE) and postemergence (POST) boxplots represent the data for P = 1 and P = 3, respectively.
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pone.0131200.g004: The relationship between plant surface half-life risk factor (P) and EIQ value for 116 herbicides (Senseman data set).Filled circles with error bars represent means and standard errors, grey open circles represent individual herbicides (N = 116). For box-plots, dark bars represent median EIQ value, boxes enclose the first and third quartiles; preemergence (PRE) and postemergence (POST) boxplots represent the data for P = 1 and P = 3, respectively.

Mentions: When herbicide EIQ values were regressed against the P risk factor values using the Senseman data set, a similar trend was observed as with the simulated EIQ values (Fig 4). The P risk factor had a relatively large influence on the resulting EIQ, explaining 26% of the variation in the EIQ (compared to 28% of the variation using the simulated EIQ values). This confirms that the P risk factor has a rather large effect on the resulting EIQ for herbicides. Unlike most of the other risk factors used in the EIQ, herbicide application timing relative to crop emergence is not a characteristic inherent to a herbicide. For example, many herbicides that are only effective when applied to plant foliage (like glyphosate and carfentrazone) are often applied before planting the crop, but have a value of 3 for plant surface half-life. Conversely, dimethenamid is not effective when applied foliarly, and thus was given a value of 1 for plant surface half-life; but dimethenamid is commonly applied after crop emergence for late-season residual weed control. Because application timing relative to crop emergence can vary for many herbicides, the use of PRE vs POST as a risk factor in the EIQ formula is arbitrary.


Quantitative Evaluation of the Environmental Impact Quotient (EIQ) for Comparing Herbicides.

Kniss AR, Coburn CW - PLoS ONE (2015)

The relationship between plant surface half-life risk factor (P) and EIQ value for 116 herbicides (Senseman data set).Filled circles with error bars represent means and standard errors, grey open circles represent individual herbicides (N = 116). For box-plots, dark bars represent median EIQ value, boxes enclose the first and third quartiles; preemergence (PRE) and postemergence (POST) boxplots represent the data for P = 1 and P = 3, respectively.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4487257&req=5

pone.0131200.g004: The relationship between plant surface half-life risk factor (P) and EIQ value for 116 herbicides (Senseman data set).Filled circles with error bars represent means and standard errors, grey open circles represent individual herbicides (N = 116). For box-plots, dark bars represent median EIQ value, boxes enclose the first and third quartiles; preemergence (PRE) and postemergence (POST) boxplots represent the data for P = 1 and P = 3, respectively.
Mentions: When herbicide EIQ values were regressed against the P risk factor values using the Senseman data set, a similar trend was observed as with the simulated EIQ values (Fig 4). The P risk factor had a relatively large influence on the resulting EIQ, explaining 26% of the variation in the EIQ (compared to 28% of the variation using the simulated EIQ values). This confirms that the P risk factor has a rather large effect on the resulting EIQ for herbicides. Unlike most of the other risk factors used in the EIQ, herbicide application timing relative to crop emergence is not a characteristic inherent to a herbicide. For example, many herbicides that are only effective when applied to plant foliage (like glyphosate and carfentrazone) are often applied before planting the crop, but have a value of 3 for plant surface half-life. Conversely, dimethenamid is not effective when applied foliarly, and thus was given a value of 1 for plant surface half-life; but dimethenamid is commonly applied after crop emergence for late-season residual weed control. Because application timing relative to crop emergence can vary for many herbicides, the use of PRE vs POST as a risk factor in the EIQ formula is arbitrary.

Bottom Line: 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.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.

View Article: PubMed Central - PubMed

Affiliation: Department of Plant Sciences, University of Wyoming, Laramie, Wyoming, United States of America.

ABSTRACT
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.

No MeSH data available.


Related in: MedlinePlus