9The purpose of this chapter is to present an indicator of how changes in pesticide use in agriculture have changed the potential for risk to human health and the environment from pesticide contamination of water leaving farm fields. Environmental indicators are designed to be relative estimates of potential risk that are based on pesticide use and on the factors that are known to be important determinants of pesticide loss from farm fields, such as the intrinsic potential of soils to leach or runoff pesticides, the chemical properties of the pesticides, annual rainfall and its relationship to leaching and runoff, and changes in cropping patterns. The analytical framework consists of about 4,700 resource polygons representing the intersection of 48 states, 280 watersheds at the 6-digit Hydrologic Unit level, and 1,400 combinations of climate and soil groups. Twelve crops are included in the analysis: com, soybeans, wheat, cotton, sorghum, barley, rice, potatoes, oats, sugarbeets, tobacco, and peanuts. Model estimates of pounds of pesticides applied, mass loss, and annual concentrations leaving the farm field (edge of field and bottom of root zone) were obtained for pesticides used on each of the 12 crops in each of the resource polygons for each year from 1960 through 1997. Indicators of potential risk are constructed from estimates of annual concentrations that exceed "safe" thresholds for chronic exposure to four target groups -humans, fish, crustaceans, and algae. It is expected that temporal and spatial trends of these indicators will closely track the change in potential risk to human health and the environment from agricultural use of pesticides.

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A cost-function-based production model is used to represent patterns of input use and output production in U.S. agriculture, and the implied costs of induced reductions in risk from agricultural chemicals (“bad outputs”). We estimate and evaluate shadow values for these harmful outputs, and the implied input- and output-specific substitution patterns, with a focus on the impacts on pesticide demand and its quality and quantity components. Using state-level data we find these measures to be statistically significant, vary substantively by region, and imply increased demand for effective pesticides associated with improvements in quality from embodied technology. Copyright 2002, Oxford University Press.

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A dynamic programming model is used to determine approximately optimal management strategies for control of corn rootworm and soybean cyst nematode in Illinois. Decision alternatives for rootworm control include nontreatment, application of a soil insecticide, and rotation to soybeans. Alternatives for cyst nematode control are nontreatment, soil nematicide, resistant cultivars, and rotation to corn. State variables in the dynamic programming model are infestation levels of both pests, previous land use decisions, and expected product prices.