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Sericea lespedeza (Lespedeza cuneata) is an invasive legume rapidly establishing and spreading throughout the tallgrass prairie landscape. Allelopathic polyphenols in sericea displace native plants, alter soil chemistry and microbial communities, and reduce forage availability, but traditional sericea control efforts have been independently ineffective: fire promotes germination, grazing pressure is limited by condensed tannin levels, and herbicides provide only short-term control. We suggest the integration of mechanical, biological, and chemical management tools increases the efficacy of sericea management efforts, while improving ecosystem function and minimizing collateral impacts to the native plant community. We sought to determine the environmental and management factors most influential on sericea control. We established 21, 14, and 12 permanent transects in 2010, 2011, and 2012, respectively, within recently burned patches at the Tallgrass Prairie Preserve of Oklahoma. Within 16, 1-m2 quadrats along each transect, we quantified initial sericea density, percent canopy cover, and stems grazed. Following seasonal fire and [steer] grazing, one fourth of each transect received a spot-spray treatment of early- or mid-season triclopyr, late-season metsulfuron-methyl, or no treatment.�� Using ANOVA and multiple regression, we analyzed sericea control as the proportion of initial stem density each growing season after treatment (GSAT). One GSAT, densities were 0.42, 0.46, 0.80, and 1.86 times the initial density for early-, mid-, late-season spray, and control treatments.� Two GSAT, densities were 0.71, 0.55, 1.39, and 2.86 times the initial density for respective treatments. At 2 GSAT, we found spray timing, pasture burn treatment, initial density, and fire return interval (FRI) were best predictors of sericea control. Preliminary results indicated greatest control was attained with a 3-yr FRI receiving both spring and summer burns and mid-season treatments of triclopyr. Final results and management implications from the comprehensive dataset will be presented.