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Prediction of Pesticide Toxicity in Midwest Streams

Overview of attention for article published in Journal of Environmental Quality, November 2016
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Title
Prediction of Pesticide Toxicity in Midwest Streams
Published in
Journal of Environmental Quality, November 2016
DOI 10.2134/jeq2015.12.0624
Pubmed ID
Authors

Megan E. Shoda, Wesley W. Stone, Lisa H. Nowell

Abstract

The occurrence of pesticide mixtures is common in stream waters of the United States, and the impact of multiple compounds on aquatic organisms is not well understood. Watershed Regressions for Pesticides (WARP) models were developed to predict Pesticide Toxicity Index (PTI) values in unmonitored streams in the Midwest and are referred to as WARP-PTI models. The PTI is a tool for assessing the relative toxicity of pesticide mixtures to fish, benthic invertebrates, and cladocera in stream water. One hundred stream sites in the Midwest were sampled weekly in May through August 2013, and the highest calculated PTI for each site was used as the WARP-PTI model response variable. Watershed characteristics that represent pesticide sources and transport were used as the WARP-PTI model explanatory variables. Three WARP-PTI models-fish, benthic invertebrates, and cladocera-were developed that include watershed characteristics describing toxicity-weighted agricultural use intensity, land use, agricultural management practices, soil properties, precipitation, and hydrologic properties. The models explained between 41 and 48% of the variability in the measured PTI values. WARP-PTI model evaluation with independent data showed reasonable performance with no clear bias. The models were applied to streams in the Midwest to demonstrate extrapolation for a regional assessment to indicate vulnerable streams and to guide more intensive monitoring.

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 10 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 3 30%
Student > Ph. D. Student 2 20%
Unspecified 1 10%
Researcher 1 10%
Student > Master 1 10%
Other 0 0%
Unknown 2 20%
Readers by discipline Count As %
Agricultural and Biological Sciences 3 30%
Environmental Science 2 20%
Mathematics 1 10%
Unspecified 1 10%
Engineering 1 10%
Other 0 0%
Unknown 2 20%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 27 September 2016.
All research outputs
#8,095,077
of 10,691,358 outputs
Outputs from Journal of Environmental Quality
#1,189
of 1,485 outputs
Outputs of similar age
#167,510
of 258,514 outputs
Outputs of similar age from Journal of Environmental Quality
#27
of 37 outputs
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So far Altmetric has tracked 1,485 research outputs from this source. They receive a mean Attention Score of 4.5. This one is in the 18th percentile – i.e., 18% of its peers scored the same or lower than it.
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We're also able to compare this research output to 37 others from the same source and published within six weeks on either side of this one. This one is in the 24th percentile – i.e., 24% of its contemporaries scored the same or lower than it.