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Monitoring is an essential component of adaptive management, and a carefully designed program is needed to ensure high-quality data and inferences over realistic time scales. Co-operation among agencies and incorporating citizen science may help enhance learning while reducing the financial costs of monitoring. We seek to realise this potential while conserving the Australian malleefowl (Leipoa ocellata). An established network of citizen scientists provide low-cost, sustainable annual monitoring data, yet the most effective actions for conserving malleefowl remain highly uncertain. The continent-wide species' distribution presents significant challenges, including multiple environmental strata to sample and numerous management jurisdictions. We outline an adaptive management framework that aims to unify malleefowl conservation priorities nationally, and target monitoring efforts. We elicited a model structure for the drivers of, and threats to, malleefowl persistence in a workshop with land managers and advocates. We parameterised 80 uncertain interactions within this structure using novel ensemble modelling techniques and identified the effectiveness of predator control as a critical uncertainty affecting malleefowl persistence. We developed a classical, spatially replicated experimental design to test whether malleefowl breed more frequently where predators are suppressed. The proposed monitoring design will rely on the contributions of several dozen land managers and 200–300 citizen scientists annually. We have developed a broad stakeholder base, a proactive communication strategy, and an agile approach to accessing resources to foster resilience and longevity in the monitoring program. If malleefowl conservation successfully adapts in response to monitoring outcomes, it will become one of the largest adaptive management programs on the planet. • Our adaptive management plan unifies work from many agencies and citizen scientists. • Malleefowl response to predator control is a critical and reducible uncertainty. • Monitoring of 36 sites can detect a 22% increase in breeding activity with 89% probability. • We take a proactive, flexible approach to sustain funding and to respond to change. • If new data prompt new actions, we will achieve successful adaptive management. [ABSTRACT FROM AUTHOR]