Anthropogenic environmental change is driving the rapid loss of biodiversity. Large declines in the abundance of historically common species are now emerging as a major concern. Identifying declining populations through long-term biodiversity monitoring is vital for implementing timely conservation measures. It is, therefore, critical to evaluate the likelihood that persistent long-term population trends of a given size could be detected using existing monitoring data and methods. Here, we test the power to detect declines in Australia's common landbirds using long-term citizen science monitoring. We use spatially explicit simulations of occupancy dynamics and virtual sampling, designed to mimic bird monitoring in better-sampled regions of Australia, to assess likely power in these data to detect trends relevant for conservation. We predict the statistical power for 326 common species that meet minimum requirements for monitoring data across 10 regions of Australia, estimating the number of species for which we would have a high (≥80%) chance of detecting declines of different sizes. The power to detect declines of ≥30% per decade was predicted to be high for at least one-third of the common species in 7 of 10 regions, with a total of 103 (32% of 326) unique species sufficiently monitored in at least one region. These species spanned 12 taxonomic orders, four orders of magnitude in body mass, and a broad diversity of dietary guilds, suggesting the current species pool will likely serve as robust indicators for a broad range of environmental states and pressures. Power was strongly affected by species' detectability, and power to detect even large declines was negligible when species are detected on ≤50% of visits to an occupied site. Predicted power for many species fell just short of the 80% threshold in one or more regions, which suggests an increase in effort targeting these species could greatly enhance the species and regional representation of these data. Against the backdrop of unprecedented biodiversity losses, this study shows how critical evaluation of existing monitoring schemes is valuable both for assessing the contribution of citizen science schemes to biodiversity monitoring and for designing strategic monitoring to significantly improve the knowledge these schemes provide.