Neonicotinoid insecticides have come under scrutiny for their potential unintended effects on non-target organisms, particularly pollinators in agro-ecosystems. As part of a larger study of neonicotinoid residues associated with maize (corn) production, 76 water samples within or around the perimeter of 18 commercial maize fields and neighbouring apiaries were collected in 5 maize-producing counties of southwestern Ontario. Residues of clothianidin (mean = 2.28, max. = 43.60 ng/mL) and thiamethoxam (mean = 1.12, max. = 16.50 ng/mL) were detected in 100 and 98.7% of the water samples tested, respectively. The concentration of total neonicotinoid residues in water within maize fields increased six-fold during the first five weeks after planting, and returned to pre-plant levels seven weeks after planting. However, concentrations in water sampled from outside the fields were similar throughout the sampling period. Soil samples from the top 5 cm of the soil profile were also collected in these fields before and immediately following planting. The mean total neonicotinoid residue was 4.02 (range 0.07 to 20.30) ng/g, for samples taken before planting, and 9.94 (range 0.53 to 38.98) ng/g, for those taken immediately after planting. Two soil samples collected from within an conservation area contained detectable (0.03 and 0.11 ng/g) concentrations of clothianidin. Of three drifted snow samples taken, the drift stratum containing the most wind-scoured soil had 0.16 and 0.20 ng/mL mainly clothianidin in the melted snow. The concentration was at the limit of detection (0.02 ng/mL) taken across the entire vertical profile. With the exception of one sample, water samples tested had concentrations below those reported to have acute, chronic or sublethal effects to honey bees. Our results suggest that neonicotinoids may move off-target by wind erosion of contaminated soil. These results are informative to risk assessment models for other non-target species in maize agro-ecosytems.

Substantial economic losses have occurred because of unacceptable concentrations of deoxynivalenol (DON) in wheat. Accurate predictions of DON in mature grain at wheat heading are needed to make decisions on whether a control strategy is needed. Our objective was to identify important weather variables, and their timing, for predicting concentrations of DON in mature grain at wheat heading. We measured the concentration of DON in 399 farm fields in southern Ontario, Canada, from 1996 to 2000. DON varied in field samples from undetectable to over 29 μg g^-1. Weather variables, such as daily rainfall, daily minimum and maximum air temperatures, and hourly relative humidity, were estimated for each field from nearby weather stations and were normalized to the date of 50% head emergence. Stepwise multiple regression procedures determined the most important weather variables and their timing around heading. DON was responsive to weather in three critical periods around heading. In the first period, 4 to 7 days before heading, DON generally increased with the number of days with >5 mm of rain and decreased with the number of days of 3 mm and decreased with days exceeding 32°C. In the third period, 7 to 10 days after heading, DON increased with number of days with >3 mm of rain. A relationship between relative humidity and DON was not detected. Overall, 73% of the variation in the concentration of DON was explained by using weather from all three critical periods. Concentrations of DON <2.0 μg g^-1 were predicted best; in fact, concentrations of DON of <1.0 μg g^-1 were predicted correctly on over 89% of the fields used to train the model.

Wheat fields under an array of agronomic practices were studied during harvest across southern and eastern Ontario. Mature wheat grain samples were harvested by hand and analyzed for deoxynivalenol (DON). DON levels from wheat grain samples harvested by hand were likely more representative of levels in the field than samples that are typically harvested by machine. The amount of variation in DON levels associated with year and agronomic effects were calculated from simple linear models. As expected, the largest factor associated with variation in DON levels was the year. Year effects accounted for 48% of the variation in DON levels across all fields during 4 years of the survey, followed by cultivar (27%), and the crop 1 year previous to wheat (14–28% depending on the year). No effect on DON could be detected from other agronomic factors including tillage system, crops planted 3 years before wheat, or type of nitrogen fertilizer applied in the spring.

Selection of pesticides with small ecological footprints is a key factor in developing sustainable agricultural systems. Policy guiding the selection of pesticides often emphasizes natural products and organic-certified pesticides to increase sustainability, because of the prevailing public opinion that natural products are uniformly safer, and thus more environmentally friendly, than synthetic chemicals. We report the results of a study examining the environmental impact of several new synthetic and certified organic insecticides under consideration as reduced-risk insecticides for soybean aphid (Aphis glycines) control, using established and novel methodologies to directly quantify pesticide impact in terms of biocontrol services. We found that in addition to reduced efficacy against aphids compared to novel synthetic insecticides, organic approved insecticides had a similar or even greater negative impact on several natural enemy species in lab studies, were more detrimental to biological control organisms in field experiments, and had higher Environmental Impact Quotients at field use rates. These data bring into caution the widely held assumption that organic pesticides are more environmentally benign than synthetic ones. All pesticides must be evaluated using an empirically-based risk assessment, because generalizations based on chemical origin do not hold true in all cases.