Black bears (Ursus americanus) are an important game species in New York State. In the last two decades, the bear population in the state has been growing due to conservative bear management and increasing anthropogenic resources. Successful management of the population requires estimating population and home range sizes, and understanding patterns of resources selection and population density in relation to landcover. New York covers approximately 141,000 km2, and so, to collect spatially representative data for such a large region, we must consider approaches to sampling that supplement intensive, traditional capture-recapture and occupancy methods. Such an addition could utilize citizen science, which engages a disperse but wide-ranging network of the public in the scientific research process, often through assistance with data collection. Citizen science has a long and successful history in monitoring natural systems over large spatial and temporal ranges, and recent advances in technology and computation have made the large quantity and variable quality of citizen science data more tractable. We describe a conceptual framework for joining non-invasive citizen science efforts with telemetry, spatial capture recapture, and occupancy methods into a single integrated population model for managing black bears. This integrated approach would be valuable for identifying patterns of black bear distribution, resource selections and movement across a range of spatial scales, for gaining a more mechanistic understanding of black bear population dynamics, and for helping to develop a comprehensive management plan for black bears in New York.