Management plays an important role in the structure and functioning of forest ecosystems and, therefore, potentially in regional and global climate. Yet, forest management exists at the intersection between dynamic biophysical and policy environments. Changes in policy can amplify or alleviate “analysis-paralysis” in natural resource management and the speed at which management plans are implemented. Here we analyze U.S. Forest Service treatment data in Idaho and show how emergent patterns fit into established policy frameworks, and how the data can be used to inform forest management scenarios in an ecosystem dynamics model. Historically in Idaho nearly all planned timber harvest treatments are eventually carried to fruition. However, there is a significant time lag from the original planned completion date and the actual completion date, which likely reflects changes in forest policy. Additionally, we found that the sequencing of activities within forest management projects occur on longer timescales than originally planned. These sequence lags are important for accurately assessing management’s impact on forest structure and biomass accumulation. This sequence variability will be incorporated into the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) module of the Community Land Model (CLM). FATES-CLM has size-specific harvesting by species; a marked improvement over most land surface models that characterize vegetation as broad classes without size-structure. This improvement allows for a more detailed representation of logging and other forest management practices than are typically used within land surface models. We model three scenarios at a plot scale: no management, simple management with biomass removal at one time step, and sequential management with biomass removal occurring at different time steps. Post treatment gross primary production, above ground biomass, and species level canopy and leaf biomass are compared across treatments. These results have implications for the larger managed forested regions of Idaho. Future work will seek to combine these results with a dynamic policy model that can be used to create more accurate future projections of forest management trends and the temporal variation of management implementation.