Many invasive and opportunistic pests cause multiple, interdependent adverse outcomes on agricultural production. Often, however, these impacts are modeled independently, which can bias empirical inferences and contribute to inaccurate recommendations. We use a copula function to more accurately model the joint behavior and provide an empirical example of its application to assess the impacts of the wheat stem sawfly (WSS). We use a unique farm-level dataset to estimate the expected losses associated with WSS and then evaluate two popular WSS management strategies. We find that strategies minimizing long-run infestation levels are preferred to those that seek to maximize yield potential in exchange for higher risk of intertemporal infestation.