While the effects of top-down and bottom-up forces on aboveground plant growth have been extensively examined, less is known about the relative impacts of these factors on other aspects of plant life history. In a fully-factorial, field experiment in a salt marsh in Virginia, USA, we manipulated grazing intensity (top-down) and nutrient availability (bottom-up) and measured the response in a suite of traits for smooth cordgrass (Spartina alterniflora). The data presented within this manuscript are unpublished, original data that were collected from the same experiment presented in Silliman and Zieman 2001. Three categories of traits and characteristics were measured: belowground characteristics, litter production, and reproduction, encompassing nine total responses. Of the nine response variables measured, eight were affected by treatments. Six response variables showed main effects of grazing and/ or fertilization, while three showed interactive effects. In general, fertilization led to increased cordgrass belowground biomass and reproduction, the former of which conflicts with predictions based on resource competition theory. Higher grazing intensity had negative impacts on both belowground biomass and reproduction. This result contrasts with past studies in this system that concluded grazer impacts are likely relegated to aboveground plant growth. In addition, grazers and fertilization interacted to alter litter production so that litter production disproportionately increased with fertilization when grazers were present. Our results revealed both predicted and unexpected effects of grazing and nutrient availability on understudied traits in a foundational plant and that these results were not fully predictable from understanding the impacts on aboveground biomass alone. Since these diverse traits link to diverse ecosystem functions, such as carbon burial, nutrient cycling, and ecosystem expansion, developing future studies to explore multiple trait responses and synthesizing the ecological knowledge on top-down and bottom-up forces with trait-based methodologies may provide a promising path forward in predicting variability in ecosystem function.