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Prediction of Pesticide Toxicity in Midwest Streams
Author(s) -
Shoda Megan E.,
Stone Wesley W.,
Nowell Lisa H.
Publication year - 2016
Publication title -
journal of environmental quality
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.888
H-Index - 171
eISSN - 1537-2537
pISSN - 0047-2425
DOI - 10.2134/jeq2015.12.0624
Subject(s) - streams , environmental science , watershed , benthic zone , pesticide , invertebrate , hydrology (agriculture) , ecology , cladocera , biology , zooplankton , geology , computer network , geotechnical engineering , machine learning , computer science
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. Core Ideas WARP‐PTI models predicted PTI at unmonitored streams in the Midwest. The taxon‐specific models varied based on explanatory variables and model fit. Pesticide use estimates were important in the development of these predictive models.

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