Fire exclusion in the dry forests of the western US has created homogenous landscapes of continuous forest canopy and fuels. When these conditions are coupled with climate-driven increases in wildfire size, the landscape is increasingly characterized by large patches of homogenous fire severity; this combination results in large areas of uniform post-fire vegetation composition. Large areas of high severity fire can transition the landscape to a non-forested condition and these post-fire outcomes can be further reinforced by subsequent burning. To identify effective post-fire landscape management options, we propose to conduct a field experiment to improve our understanding of planted seedling establishment in severely burned landscapes and use this information to improve our ability to simulate post-fire landscape development. We will use this model to identify emergent properties in landscape development as a function of post-fire management decision-making. The overall objective of this research is to develop a set of post-fire management recommendations that are based on emergent ecosystem properties stemming from an improved understanding of post-fire vegetation dynamics and decision making informed by model simulations that elucidate the net effect of strategic deployment of post-fire management resources.