One of the more salient management challenges surrounding fisheries in the Gulf of America (Gulf) is how to more directly incorporate ecosystem effects into stock assessments. The main impediment to progress on this front is not analytical however; it is empirical. In many cases, observational times series are of insufficient length and resolution to identify and quantify the relative influences of drivers of population dynamics at appropriate scales. Filling this gap in data availability is a primary goal of the Gulf Fishery Independent Survey of Habitat and Ecosystem Resources (G-FISHER) program, which is a multi-agency underwater video survey that collects data Gulf-wide on reef fish distribution, abundance, and size composition, as well as habitat coverage and composition in a standardized manner. Using data collected under G-FISHER and its survey predecessors, we created an 18-year time series of reef fish abundance indices (n=20) in the eastern Gulf to be analyzed via state-spaced dynamic factor analysis (DFA). Dynamic factor analysis is a dimensional reduction technique for time series that can be used to identify common population trends amongst species as well as the potential impact of environmental drivers on these trends. Of the DFA models considered, those that best fit the data included two and three shared trends. When we the influence of El Niño–Southern Oscillation, North Atlantic Oscillation and red tide occurrence were also considered, there were no appreciable improvements to model fits. As several of the species assessed here initially recruit to estuarine systems, particularly in the eastern Gulf, our eventual goal is to use these results to inform the development of species-specific state-space models to assess potential linkages between inshore trends in recruitment to offshore abundances. Overall, the DFA proved useful for examining population trends amongst both similar and disparate species while also providing an avenue for examining the impacts of global environmental drivers.