A fundamental goal of population ecologists is to identify drivers responsible for temporal variation in abundance. Understanding whether variation is associated with environmental stochasticity or anthropogenic disturbances, which are more amenable to management action, is crucial yet difficult to achieve. Here, we present a hierarchical monitoring framework that models rates of change in abundance from spatially structured populations and identifies when local declines fall out of synchrony with trends at larger spatial scales. Importantly, the framework provides signals that alert managers to the categorical significance of observed declines while avoiding signals where declines result from drivers operating at larger spatial scales (e.g., periodic reductions in primary productivity owing to drought). We demonstrate utility through application to a rapidly declining sagebrush (Artemisia spp.) indicator species (greater sage-grouse; Centrocercus urophasianus) using 30 years (1990–2019) of count data collected from greater than 4,400 leks (habitual breeding sites) distributed across the western United States. Results revealed population declines, immediately preceding triggers (2–4-year period), ranging between 58 and 68%. Conversely, population trends unassociated with triggers showed little-to-no sign of decline. Retrospective application of the monitoring framework indicated an average annual rate of 1.7% of leks or 1.3% of neighborhood clusters (lek aggregations) would have required management intervention to reverse range-wide declines and stabilize the U.S. population as a whole.