Abstract: In managing invasions and colonizations of non-native species, eradication or control efforts must proceed quickly. There are 2 challenges in taking such quick action. First, managers frequently have to choose among complex and often competing environmental, social, and economic objectives. Second, the effects are highly uncertain. We applied participatory structured decision making (SDM) to develop a response plan for the recent invasion of non-native myrtle rust (Uredo rangelii) in Australia. Structured decision making breaks a complex decision process into 5 steps: identify problems (i.e., decisions to be made), formulate objectives, develop management alternatives, estimate consequences of implementing those alternatives, and select preferred alternatives by evaluating trade-offs among alternatives. To determine the preferred mid- to long-term alternatives to managing the rust, we conducted 2 participatory workshops and 18 interviews with individuals to elicit stakeholders’ key concerns and convert them into 5 objectives (minimize management cost, minimize economic cost to industry, minimize effects on natural ecosystems and landscape amenities, and minimize environmental effects associated with use of fungicide) and to identify the 5 management alternatives (full eradication, partial eradication, slow spread, live with it [i.e., major effort invested in mitigation of effects], and do nothing). We also developed decision trees to graphically represent the essence of the decision by displaying the relations between uncertainties and decision points. In the short term or before local expansion of myrtle rust, the do-nothing alternative was not preferred, but an eradication alternative was only recommended if the probability of eradication exceeded about 40%. After the expansion of myrtle rust, the slow-the-spread alternative was preferred regardless of which of the short-term management alternatives was selected at an earlier stage. The participatory SDM approach effectively resulted in informed and transparent response plans that incorporated multiple objectives in decision-making processes under high uncertainty.