Texas A&M University (TAMU) supports a substantial breeding population of mourning doves (Zenaida macroura) with one of the highest nest densities in Texas. There has been a long history of mourning dove research on the TAMU Campus, with initial population studies conducted in the 1950’s, and the most recent studies occurring in the 1980’s. The TAMU Campus and surrounding areas have experienced substantial changes associated with urbanization and expansion over the last 50 years, altering mourning dove habitat on and around campus. The objective of this study was to examine mourning dove nesting and production in an urban setting and determine how microhabitat and landscape features affect nest-site selection and nest success. Specifically, I (1) examined trends in mourning dove nesting density and nest success on the TAMU Campus, and (2) identified important microhabitat and landscape features associated with nest-site selection and nesting success. Mourning dove nests were located by systematically searching potential nest sites on a weekly basis from the late-March through mid-September. Nests were monitored until they either failed or successfully fledged at least 1 young. A total of 778 nests was located and monitored on campus. All nest locations were entered into ArcView GIS. An equal number of nests were randomly generated in ArcView and assigned to non-nest trees to evaluate habitat variables associated with nest-site selection for mourning doves. Binary logistic regression was used to evaluate the significance of microhabitat and landscape variables to nest-site selection and nest success. Comparisons with data collected in 1950, 1978, and 1979 showed relatively similar nesting densities, but a significant decrease in nest success over time. A comparison of microhabitat features between actual nest trees and random locations (non-nest trees) indicated increasing values of tree diameter at breast height and tree species were important predictors of mourning dove nest-site selection. Landscape features found important in dove nest-site selection were proximity to open fields, roads, and buildings. Proximity to roads and buildings also were significant predictors of nest success. Combining significant microhabitat and landscape variables for nest-site selection increased the predictability of the model indicating a possible hierarchical nest-site selection strategy.