The protection of crops from insect pests and weeds is fundamentally a problem of ecological management. Modern pesticides used to perform such management are essential to efficient production of corn and soybean, the two most widely grown crops in the United States. What pesticides are sprayed where, when, and by whom is both shaped by and shapes ecological conditions. This dissertation consists of three essays on how American corn and soybean growers make insect and weed management decisions, and the impacts of these decisions on the environment.The first essay measures the impact of glyphosate-resistant weeds on farmers' tillage practices using field-level data from across the United States, demonstrating how selection pressure within weed populations can limit the long-term benefits of pesticide technologies. Using a two-stage, panel data econometric model, we estimate that the spread of glyphosate-resistant weeds has led to reduction in the adoption of conservation tillage by soybean growers by as much as 8.5 percentage points. Nationally, we estimate that the reduction in conservation tillage adoption due to glyphosate-resistant weeds has increased soil erosion into water ways by over 65 million metric tons and carbon emissions due to fuel consumption by 226,000 metric tons.The second essay measures the impact of farmers' pesticide use on butterfly abundance. By examining a full suite of pesticides in a single model, we account for substitution effects between products. We find neonicotinoids, the most widely used class of insecticides, have a detrimental impact on butterfly populations, both in aggregate and for prominent species such as Monarchs. Overall, our results show that changes in pesticide use between 1998 and 2014 accounted for a 9% decrease in total butterfly abundance.Finally, the third essay examines farmers' decisions to custom hire to spray insecticides rather than performing such field tasks on their own. Using a pilot choice experiment, we demonstrate how the value farmers place on timeliness when custom hiring varies according to farmer characteristics. We find risk-averse farmers are more sensitive to potential delays, while those with more developed social networks are less sensitive.
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