Ecological disturbances (i.e. pests, invasive species, floods, fires etc.) are a fundamental challenge in managing connected social-ecological systems. Even if treatment for such disturbances is available, often managers do not act quickly enough or not at all. In this paper we build an agent based model that examines: A) under what circumstances are managers locked into non-Action that favors ecological disturbances? b) what learning strategies are most effective in avoiding management lock-in? The model we develop relates adoption of treatment strategies to eradicate ecological disturbances with the type of learning preferred by individuals (success bias, conformist and individual). We further model treatment strategy adoption as a function of treatment cost, ability of the ecological system to recover once treated and the disturbance effect on the social system. Our model shows the importance of success-bias imitation and system size in affecting the odds of eradicating ecological disturbances on connected landscapes.