Would banning atrazine benefit farmers?

Ackerman, Frank; Whited, Melissa; Knight, Patrick

doi:10.1179/2049396713y.0000000054

Cited by 11 publications

(1 citation statement)

References 18 publications

(20 reference statements)

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“…3C) quantify the extent to which reducing the amounts applied to the crop or reducing fraction of the lands dedicated to corn production will reduce the concentration of atrazine in lakes and reservoirs. Barring a full ban on atrazine (which, we note, might benefit farmers [ see Ackerman et al 2014]), reducing application could be achieved using alternative herbicides or changes in agricultural practices (Ponisio et al 2014; Hunt et al 2017). Furthermore, reducing land dedicated to corn production could be achieved by diversifying cultures, longer rotations between corn production years or reduction of the fraction of land dedicated to agriculture.…”

Section: Discussionmentioning

confidence: 99%

Predicting atrazine concentrations in waterbodies across the contiguous United States: The importance of land use, hydrology, and water physicochemistry

Beaulieu

Cabana

Taranu

et al. 2020

Limnology & Oceanography

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Atrazine contamination is ubiquitous in North American surface waters, but the dependency of the herbicide's distribution on landscape and within-lake processes is currently poorly known. We sought to identify novel predictors of atrazine and to build a coherent framework to model its concentration in waterbodies through the development of binomial-gamma hurdle models and LASSO regression models. We constructed models for over 900 waterbodies in the contiguous United States using data from the 2012 U.S. EPA National Lake Assessment, the 2012 U.S. Department of Agriculture CropScape and the Global HydroLAB HydroLAKES databases. Atrazine was detected in 32% of U.S. waterbodies, with a mean concentration of 0.17 μg L −1 when detected. The two-part hurdle model explained as much as 75% of the variance in atrazine across a spatially and temporally heterogeneous landscape. Three predictors explained 31% of the variability in atrazine detection in U.S. waterbodies, where the proportion of corn + soy cultures in the watershed was the most important variable. Once atrazine was detected, our models explained an additional 29% of the variability in atrazine concentrations, where the estimated areal weight of atrazine application (kg atrazine km 2) in the watershed was the most important predictor. Spatially, water quality variables associated with eutrophication were linked to increased levels of atrazine contamination while cooler water temperatures and natural lakes and landscapes were associated with decreased levels of contamination. Our results suggest that changes in land-use practices may be the most effective way to mitigate atrazine contamination in waterbodies.

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Section: Discussionmentioning

confidence: 99%