Aquatic invasions pose challenges to managers due to uncertainty regarding environmental drivers of the invasion, how an invasion would impact the receiving ecosystem, and the effectiveness of alternative management strategies. In a formal adaptive management framework, management can proceed while simultaneously reducing, through monitoring, uncertainty that influences the optimal choice of management strategy. Predictive models are often used to rank the effectiveness of management strategies, but relative performance of alternatives may depend on uncertainties in invasion dynamics. Data to resolve uncertainties are usually sparse at the outset of an invasion. Here, we update predictive models used to rank management strategies under competing hypotheses related to increases in reproductive rate and immigration that drove the expansion of invasive brown trout (Salmo trutta) downstream of Glen Canyon Dam on the Colorado River in Arizona, USA. Competing hypotheses explaining variation in reproductive rate focused on water temperature, spawner interference competition with rainbow trout (Oncorhynchus mykiss), and the potential for an Allee effect. Competing hypotheses regarding variation in immigration focused on the role of flows versus other factors. We forecasted population dynamics under different hypotheses and compared forecasts to annual monitoring data collected since 2017 to calculate the likelihood (weight) of each of these hypotheses. We also analyzed the effects of management actions including incentivized angler harvest and suppression of brown trout through electrofishing. Observations since 2017 supported the hypothesis that immigration was mostly likely driven by flows and reproduction had exceeded an Allee threshold. We demonstrate how adaptive management could be used to confront invasions of aquatic systems, and how learning may improve annual recurrent decisions designed to meet management objectives in a large river ecosystem.