Agricultural production is an intrinsically risky business that involves many sources of risk, including production, market, institutional, and personal risks. The ever-changing bio-physical environments under which farmers operate result in highly uncertain production outcomes that vary markedly across space and over time. To cope with these multitude of risks, farmers’ risk management strategies also vary over space and time. In this dissertation, I use U.S. wheat production to exemplify some novel, risk-centric assessments of the adoption of new crop varieties and the purchase of crop insurance as alternative, somewhat complementary risk management strategies. First, I characterize the spatial and temporal dynamics of wheat varieties grown by U.S. farmers over the past century. Based on state-level area-by-variety data, and contrary to commonly held belief, I show that the landscape of wheat varieties grown in the United States became increasingly diverse both across space and over time during the study period 1919-2016. I then analyzed the effects of various risks on the spatio-temporal pattern of adoption of new wheat varieties, and find that past losses attributable to biotic risks are significantly correlated with the adoption of new varieties. Intuitively, farmers who experienced losses from crop pests and diseases are more likely than those not subject to pest losses to adopt new varieties with improved disease resistance. Lastly, I ask and answer the question “do biotic and abiotic risks have different consequences on the demand for crop insurance?” Using spatially disaggregated wheat production and insurance data in the United States for the period 1989-2016, my empirical results reinforce the implications of my theoretical model that farmers facing biotic risks are more likely to select lower amounts of crop insurance coverage compared with farmers facing abiotic risks. Depending on the spatio-temporal dynamics of different types of risks, farmers draw on a number of technical, management, or market options to mitigate the negative consequences of these risks. Studying these agricultural risk management options from a bio-spatially sensitive perspective reveals new insights that can help policy makers and farmers implement better risk management strategies.