DRIFTSIM can be used to determine the effects of major drift-causing factors on the mean drift distances up to 656 feet from the release point for individual water droplets or classes of droplets. Unlike other computer simulation software, DRIFTSIM requires no special skills to operate and computer system requirements are minimal: Pentium processor, CD drive, MS-Windows version 3.1 or later, 8 Mb of memory, 30 Mb free hard drive space and a mouse. Large amounts of pesticides are applied worldwide on a wide variety of crops. While pesticides are essential for high quality, abundant food, they pose risks if applied improperly. Of particular concern is the potential for spray droplets to drift to areas other than the intended targets. In order to assist applicators choose the optimum spray conditions to minimize spray drift, Heping Zhuand Robert Foxof the USDA Agricultural Research Service and Erdal Ozkan of the Ohio State University have developed DRIFTSIM--a user-friendly computer program capable of predicting drift distances of spray droplets under a wide variety of conditions. Unlike other computer simulation software, DRIFTSIM requires no special skills to operate and computer system requirements are minimal: Pentium processor, CD drive, MS-Windows version 3.1 or later, 8 Mb of memory, 30 Mb free hard drive space and a mouse. DRIFTSIM rapidly estimates the mean drift distances of water droplets discharged from atomizers on field sprayers. The program, which is the only spray drift estimation software that works on portable computers, enables researchers to predict and calculate spray drift potentials which previously was not possible. Extension agencies and researchers can use the program to evaluate spray drift problems and train spray operators to adjust sprayer settings to improve the application performance. To download and install the Driftsim software: Fill in the form below and click Take me to the download Create a folder named Driftsim on your hard drive. Click DriftsimInstall.exe and choose to save the file to your Driftsim folder When the download is complete, double-click DriftsimInstall.exe. In the Win-zip Self-Extractor window, click Unzip to extract the program files to the DepositScan folder. Refer to the Manual.pdf in the Driftsim folder for guidance in using DepositScan. Additional information is available at https://www.ars.usda.gov/Research/docs.htm?docid=11228

In sechs kleinen bis mittelgrossen Fliessgewässern wurden die für aquatische Organismen extrem toxischen Pyrethroid- und Organophosphatinsektizide mittels einer Spezialanalytik bis in den Picogramm pro-Liter Bereich quantifiziert. An fünf der sechs untersuchten Standorte überschritten die gemessenen Insektizidkonzentrationen regelmässig chronische und zum Teil akute Qualitätskriterien und die chronische Mischungsrisiko¬bewertung zeigte während 43-100% des Untersuchungszeitraums hohe Risiken für die Invertebratengemeinschaft an. Werden Pyrethroid- und Organophosphatinsektizide nicht in die Beurteilung der Gewässerqualität miteinbezogen, kann das Gesamtrisiko für aquatische Organismen erheblich unterschätzt werden.

Surface runoff represents a major pathway for pesticide transport from agricultural areas to surface waters. The influence of man-made structures (e.g. roads, hedges, ditches) on surface runoff connectivity has been shown in various studies. In Switzerland, so-called hydraulic shortcuts (e.g. inlets and maintenance manholes of road or field storm drainage systems) have been shown to influence surface runoff connectivity and related pesticide transport. Their occurrence, and their influence on surface runoff and pesticide connectivity have however not been studied systematically. To address that deficit, we randomly selected 20 study areas (average size = 3.5 km2) throughout the Swiss plateau, representing arable cropping systems. We assessed shortcut occurrence in these study areas using three mapping methods: field mapping, drainage plans, and high-resolution aerial images. Surface runoff connectivity in the study areas was analysed using a 2x2 m digital elevation model and a multiple-flow algorithm. Parameter uncertainty affecting this analysis was addressed by a Monte Carlo simulation. With our approach, agricultural areas were divided into areas that are either directly connected to surface waters, indirectly (i.e. via hydraulic shortcuts), or not connected at all. Finally, the results of this connectivity analysis were scaled up to the national level using a regression model based on topographic descriptors and were then compared to an existing national connectivity model. Inlets of the road storm drainage system were identified as the main shortcuts. On average, we found 0.84 inlets and a total of 2.0 manholes per hectare of agricultural land. In the study catchments between 43 and 74 % of the agricultural area is connected to surface waters via hydraulic shortcuts. On the national level, this fraction is similar and lies between 47 and 60 %. Considering our empirical observations led to shifts in estimated fractions of connected areas compared to the previous connectivity model. The differences were most pronounced in flat areas of river valleys. These numbers suggest that transport through hydraulic shortcuts is an important pesticide flow path in a landscape where many engineered structures exist to drain excess water from fields and roads. However, this transport process is currently not considered in Swiss pesticide legislation and authorisation. Therefore, current regulations may fall short to address the full extent of the pesticide problem. However, independent measurements of water flow and pesticide transport to quantify the contribution of shortcuts and validating the model results are lacking. Overall, the findings highlight the relevance of better understanding the connectivity between fields and receiving waters and the underlying factors and physical structures in the landscape.

Micropollutants are ubiquitously found in natural surface waters and pose a potential risk to aquatic organisms. Stream biofilms, consisting of bacteria, algae and other microorganisms potentially contribute to bioremediating aquatic environments by biotransforming xenobiotic substances. When investigating the potential of stream biofilms to remove micropollutants from the water column, it is important to distinguish between different fate processes, such as biotransformation, passive sorption and active bioaccumulation. However, due to the complex nature of the biofilm community and its extracellular matrix, this task is often difficult. In this study, we combined biotransformation experiments involving natural stream biofilms collected up- and downstream of wastewater treatment plant outfalls with the QuEChERS extraction method to distinguish between the different fate processes. The QuEChERS extraction proved to be a suitable method for a broad range of micropollutants (> 80% of the investigated compounds). We found that 31 out of 63 compounds were biotransformed by the biofilms, with the majority being substitution-type biotransformations, and that downstream biofilms have an increased biotransformation potential towards specific wastewater-relevant micropollutants. Overall, using the experimental and analytical strategy developed, stream biofilms were demonstrated to have a broad inherent micropollutant biotransformation potential, and to thus contribute to bioremediation and improving ecosystem health.

The dataset contains concentrations profiles of 213 agricultural pesticides in surface water samples. Half-day composite samples were taken from five small streams in Switzerland from the beginning of March to the end of August 2015. Half-day samples from discharge events were measured individually, whereas half-day samples taken during dry weather periods between discharge events were pooled to samples of variable lengths (five days on average) and then measured resulting in 34 to 60 measured samples per site.

Pesticides used in agriculture can end up in nearby streams and can have a negative impact on nontarget organisms such as aquatic invertebrates. During registration, bioaccumulation potential is often investigated using laboratory tests only. Recent studies showed that the magnitude of bioaccumulation in the field substantially differs from laboratory conditions. To investigate this discrepancy, we conducted a field bioaccumulation study in a stream known to receive pollutant loadings from agriculture. Our work incorporates measurements of stream pesticide concentrations at high temporal resolution (every 20 min), as well as sediment, leaves, and caged gammarid analyses (every 2-24 h) over several weeks. Of 49 investigated pesticides, 14 were detected in gammarids with highly variable concentrations of up to 140 ± 28 ng/gww. Toxicokinetic modeling using laboratory-derived uptake and depuration rate constants for azoxystrobin, cyprodinil, and fluopyram showed that despite the highly resolved water concentrations measured, the pesticide burden on gammarids remains underestimated by a factor of 1.9 ± 0.1 to 31 ± 3.0, with the highest underestimations occurring after rain events. Including dietary uptake from polluted detritus leaves and sediment in the model explained this underestimation only to a minor proportion. However, suspended solids analyzed during rain events had high pesticide concentrations, and uptake from them could partially explain the underestimation after rain events. Additional comparison between the measured and modeled data showed that the pesticide depuration in gammarids is slower in the field. This observation suggests that several unknown mechanisms may play a role, including lowered enzyme expression and mixture effects. Thus, it is important to conduct such retrospective risk assessments based on field investigations and adapt the registration accordingly.

[Note: this dataset has been superseded by version 2: https://doi.org/10.15482/USDA.ADC/1522673 ] This collection contains supplementary data for the manuscript "Legacy genetics of Arachis cardenasii in the peanut crop shows profound benefits of international seed exchange," which describes the impact of alleles from a wild relative of peanut, Arachis cardenasii, through analysis of those alleles across cultivars and breeding lines across many countries. The initial challenging cross, between tetraploid cultivated peanut (Arachis hypogaea) and the diploid species A. cardenasii, was carried out in the late 1960s. Subsequent work produce a tetraploid line that contained introgressed regions from A. cardenasii. Those chromosomal regions, several containing important resistance genes, were used in numerous breeding lines. The genetic legacy from A. cardenasii is documented in the files in this collection. The information includes genotyping data across peanut cultivars and breeding lines, generated through both genotyping arrays ("SNP chips") and whole-genome sequencing. Information in this collection also includes data related to impact of A. cardenasii on disease- and pest resistance in modern peanut varieties.

[Note: This version supersedes version 1: https://doi.org/10.15482/USDA.ADC/1520889 Changes in version 2: A new Dataset was added - DataSet1-CardAlleles-iii.xlsx Datasets were renamed and renumbered in accordance to article revisions, and some changes made (see below for details): SupplementaryData1-Worldwide-genotypes-ii.xlsx => DataSet3-Worldwide-genotypes-ii.xlsx (Data with very minor changes, including the removal of three of 710 markers) SupplementaryData2-Lineages-FieldData-ii.xlsx => DataSet4-Lineages-FieldData-iv.xlsx (this file underwent minor revisions, with some extra comments added) SupplementaryData3-Fingerprints.tar => DataSet5-Fingerprints.tar (Data unchanged) SupplementaryData4-Austp183.xlsx => DataSet6-Austp183.xlsx (Data unchanged) SupplementaryData5-introgression.tar => DataSet2-WGSIntrogression.tar (A Dataset more stringently filtered with more control genotypes was used, cutting the number of markers from 2,566,180 to 2,337,866. More genotype output files were added, including controls. A genome-ordered list of A. cardenasii GKP 10017 diagnostic bases was added (Acard-diag_bases.txt.gzip).] Description This collection contains supplementary data for the manuscript "Legacy genetics of Arachis cardenasii in the peanut crop shows profound benefits of international seed exchange," which describes the impact of alleles from a wild relative of peanut, Arachis cardenasii, through analysis of those alleles across cultivars and breeding lines across many countries. The initial challenging cross, between tetraploid cultivated peanut (Arachis hypogaea) and the diploid species A. cardenasii, was carried out in the late 1960s. Subsequent work produce a tetraploid line that contained introgressed regions from A. cardenasii. Those chromosomal regions, several containing important resistance genes, were used in numerous breeding lines. The genetic legacy from A. cardenasii is documented in the files in this collection. The information includes genotyping data across peanut cultivars and breeding lines, generated through both genotyping arrays ("SNP chips") and whole-genome sequencing. Information in this collection also includes data related to impact of A. cardenasii on disease- and pest resistance in modern peanut varieties.

Farming Systems Study for Greenhouse gas Reduction through Agricultural Carbon Enhancement network in Morris, Minnesota Tillage is decreasing globally due to recognized benefits of fuel savings and improved soil health in the absence of disturbance. However, a perceived inability to control weeds effectively and economically hinders no-till adoption in organic production systems in the Upper Midwest, USA. A strip-tillage (ST) strategy was explored as an intermediate approach to reducing fuel use and soil disturbance, and still controlling weeds. An 8-year comparison was made between two tillage approaches, one primarily using ST the other using a combination of conventional plow, disk and chisel tillage [conventional tillage (CT)]. Additionally, two rotation schemes were explored within each tillage system: a 2-year rotation (2y) of corn (Zea mays L.), and soybean (Glycine max [L.] Merr.) with a winter rye (Secale cereale L.) cover crop; and a 4-year rotation (4y) of corn, soybean, spring wheat (Triticum aestivum L.) underseeded with alfalfa (Medicago sativa L.), and a second year of alfalfa. These treatments resulted in comparison of four main management systems CT-2y, CT-4y, ST-2y and ST-4y, which also were managed under fertilized and non-fertilized conditions. Yields, whole system productivity (evaluated with potential gross returns), and weed seed densities (first 4 years) were measured. Across years, yields of corn, soybean and wheat were greater by 34% or more under CT than ST but alfalfa yields were the same. Within tillage strategies, corn yields were the same in 2y and 4y rotations, but soybean yields, only under ST, were 29% lower in the fertilized 4y than 2 yr rotation. In the ST-4y system yields of corn and soybean were the same in fertilized and non-fertilized treatments. Over the entire rotation, system productivity was highest in the fertilized CT-2y system, but the same among fertilized ST-4y, and non-fertilized ST-2y, ST-4y, and CT-4y systems. Over the first 4 years, total weed seed density increased comparatively more under ST than CT, and was negatively correlated to corn yields in fertilized CT systems and soybean yields in the fertilized ST-2y system. These results indicated ST compromised productivity, in part due to insufficient weed control, but also due to reduced nutrient availability. ST and diverse rotations may yet be viable options given that overall productivity of fertilized ST-2y and CT-4y systems was within 70% of that in the fertilized CT-2y system. Closing the yield gap between ST and CT would benefit from future research focused on organic weed and nutrient management, particularly for corn.

This package contains images and videos of active hydraulic shortcuts in agricultural areas of the municipalities of Zürich and Rümlang, Switzerland. More information on hydraulic shortcuts and their relevance for pesticide transport in agricultural areas are provided in the following doctoral thesis: https://doi.org/10.3929/ethz-b-000539927 The pictures and videos in this package are intended to be used for outreach or training of farmers, etc. and can be used freely (creative commons license). The pictures and videos were taken on 13 July 2021 between 17:23h and 17:55h (UTC+2h), a few hours after a large two-day rain event. The precipitation measured at a nearby rain gage (station Affoltern, MeteoSchweiz; 47.427694, 8.517953) equalled 41.5mm on the 12th of July, and 34.7mm on the 13th of July. The images and videos were taken at six different locations. The situations that are visible on these images and videos are described in the following. For each location, latitude and longitude is indicated in brackets (WGS84 coordinate system). - **Location 1** (47.42726, 8.52567): Surface runoff on a farm track. Since the farm track is elevated in the middle, water flows at the left and right edge of the farm track. Only at one specific location surface runoff changes from the left to the right side. - **Location 2** (47.43118, 8.52572): Surface runoff flows along one edge of a farm track. - **Location 3** (47.43580, 8.52877): Surface runoff accumulates on a potato field, flows on a asphalt road, and then into an inlet of the road storm drainage system. - **Location 4** (47.44077, 8.52534): Surface runoff flows from a corn field on an asphalt road, and then into an inlet of the road storm drainage system. - **Location 5** (47.43819, 8.50848): Surface runoff accumulates on a field with bare soil, causing erosion. At the field border with the lowest elevation, surface runoff flows onto a small asphalt road and then for around 180m along this road. Finally, the surface runoff flows into an inlet of the road storm drainage system of a larger asphalt road. - **Location 6** (47.43837, 8.50621): Surface runoff formed on grassland flows into an inlet of the storm road drainage system. This occurs either directly, or via the road.

The Pesticide Product Information System contains information concerning all pesticide products registered in the United States. It includes registrant name and address, chemical ingredients, toxicity category, product names, distributor brand names, site/pest uses, pesticidal type, formulation code, and registration status.

Decontamination studies evaluated the effectiveness of liquid-based surface decontaminants against pesticides on indoor surfaces. Building materials, representing nonporous and porous surfaces, were contaminated with common pesticides, including malathion, carbaryl, fipronil, deltamethrin, and permethrin as well as commercial formulations thereof. Pesticide surface concentrations were representative of the pesticide-specific levels measured during field investigations involving misapplications of pesticides in homes or businesses (25–2,400 µg/100 cm2 surface concentration range). Decontamination testing occurred via a single or repeated application of the decontaminant without further mechanical removal or rinse steps. Decontaminants were both off-the-shelf and specialized solutions representing various chemistries (hypochlorite, hydrogen peroxide, quaternary ammonium compounds and ammonium salts). The persistence of surface residues was also investigated to assess the potential reduction of pesticide mass on surfaces under simulated indoor environmental conditions. The datasets provide the pesticide mass recovered from coupons and the calculated decontamination efficacies for all decontamination studies. This dataset is associated with the following publication: Oudejans, L., A. Mysz, E. Snyder, B. Wyrzykowska-Ceradini, J. Nardin, D. Tabor, J. Starr, D. Stout, and P. Lemieux. Remediating Indoor Pesticide Contamination from Improper Pest Control Treatments: Persistence and Decontamination Studies. D.Aga JOURNAL OF HAZARDOUS MATERIALS. Elsevier Science Ltd, New York, NY, USA, 397(5): 11, (2020).

Wipe sampling variables (such as wipe wetting solvent, pesticide concentration effects, commercial products, number of wipes per tested surface) were evaluated to determine their potential effects on method performance and how they may alter surface recoveries. This dataset is associated with the following publication: Willison, S., D. Stout, A. Mysz, J. Starr, D. Tabor, B. Wyrzykowska-Ceradini, J. Nardin, E. Morris, and E. Snyder. The impact of wipe sampling variables on method performance associate with indoor pesticide misuse and highly contaminated areas. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, NETHERLANDS, 655: 539-546, (2019).

The dataset contains concentrations profiles of 217 agricultural pesticides in surface water samples. Five small streams in Switzerland were sampled from the beginning of March to mid October 2017 using 3.5 day composite samples resulting in 61 to 66 measured samples per site and a total of 313 samples.

individual values for liver detoxification for each human sample and for each chemical. This dataset is associated with the following publication: Moser, G., and S. Padilla. Esterase detoxification of acetylcholinesterase inhibitors using human liver samples in vitro. TOXICOLOGY. Elsevier Science Ltd, New York, NY, USA, 11-20, (2016).

Recent USDA/ARS patented technologies on crop production and protection that are available for licensing are described, including summary, contact, benefits, and applications. Updated June 2018.

Amphibian metabolite data used in Snyder, M.N., Henderson, W.M., Glinski, D.G., Purucker, S. T., 2017. Biomarker analysis of american toad (Anaxyrus americanus) and grey tree frog (Hyla versicolor) tadpoles following exposure to atrazine. Aquatic Toxicology, 182(184-193). doi: 10.1016/j.aquatox.2016.11.018. This dataset is associated with the following publication: Snyder, M., M. Henderson, D. Glinski, and T. Purucker. Biomarker analysis of American toad (Anaxyrus americanus) and grey tree frog (Hyla versicolor) tadpoles following exposure to atrazine.. AQUATIC TOXICOLOGY. Elsevier Science Ltd, New York, NY, USA, 182: 184-193, (2017).

exposure_experiment.csv: time: length of time that amphibian was exposed to that pesticide in hours. parent: is the active ingredient that the amphibian was exposed to. analyte: either the main parent compound or the metabolite that was quantified. matrix: the sample that was analyzed either the amphibian or soil. conc: is the concentration for that specific analyte in that matrix for that specific species in microg/g replicate: is the individual amphibian or soil exposed to that pesticide. microsome_experiment3.csv: time: is the length of time that the microsomes were exposed before being quenched in minutes. parent: is the active ingredient that the amphibian was exposed to. analyte: either the main parent compound or the metabolite that was quantified. matrix: the sample that was analyzed microsomes. conc: is the concentration for that specific analyte in that matrix for that specific species. in micromolar (uM) replicate: is the individual microsome exposed to that pesticide. microMexp: is the concentration in micromolar (uM) that the microsomes were exposed to for that pesticide. This dataset is associated with the following publication: Glinski, D., M. Henderson, R. Van Meter, and T. Purucker. Using in vitro derived enzymatic reaction rates of metabolism to inform pesticide body burdens in amphibians. TOXICOLOGY LETTERS. Elsevier Science Ltd, New York, NY, USA, 288: 9-16, (2018).