The sustainable production of large quantities of biomass from dedicated energy crops will be necessary to meet renewable fuel and power mandates being implemented in the United States at the federal and state level.  However, fundamental questions about the relative merits of cultivation strategies based on intensification versus extensification (or land-sharing versus land-sparing) remain unsettled.  Production on marginal lands is an attractive prospect, though recent research suggests that inherently low yields of even perennial grass crops may be problematic in such areas.  The use of well-validated biogeochemical process models at fine scales, coupled with multi-criteria optimization techniques, can help identify practical cultivation strategies and bioenergy landscape designs that maximize system-level greenhouse gas (GHG) mitigation within economic and environmental constraints.  In this work, the DayCent model was parameterized to reflect the productivity of upland and lowland switchgrass ecotypes across a variety of climates and soil types, including results from recent field trials on marginal lands.  The model was then run for a case study across a heterogeneous landscape in the Great Plains where one of the first commercial scale cellulosic biorefineries is currently under construction.  Switchgrass production and soil GHG balance (CO₂, N₂O, and CH₄) were simulated spatially across the landscape and in a third dimension representing management intensity.  These data were then integrated into a lifecycle assessment framework and a crop production budget to estimate total supply chain environmental impacts and economic viability, and optimized using a heuristic multi-criteria optimization routine and non-market valuation approach.  This work helps to identify potential synergies and fundamental tradeoffs between environmental and economic outcomes in a real-world bioenergy feedstock production landscape, and helps to advance the state-of-the-art for biofuel regulatory assessment tools.