Managing natural populations and communities requires detailed information regarding demographic processes (or status of a population) at large spatial and temporal scales. This combination is challenging for both traditional scientific surveys, which often operate at localized scales, and citizen science designs, which often provide data with few auxiliary information (i.e. no information about individual age or condition). The authors of this study combine citizen science data collected at large scales (REEF Volunteer Fish Survey Project data) with recently developed statistical demographic modeling techniques. The model analysis included two managed reef fishes in the Gulf of Mexico to estimate demographic trends, habitat associations, and interannual variability in recruitment of Goliath Grouper and Mutton Snapper. The results identify strong preferences for artificial structure for the recovering Goliath Grouper, while revealing little evidence of either habitat associations or trends in abundance for Mutton Snapper. Results are also contrasted with a typical modeling approach to demonstrate the importance of accounting for the statistical complexities implied by spatially structured citizen science data. Results also highlight the utility and management benefits of combining demographic models and citizen science data.