Uncertainties in Forest Management Timing, Forest Structure, and Ecosystem Function: Simulating Delayed Timber Harvest

The United States Forest Service manages a large portion of forested land within the western US, impacting the land surface through projects that remove or add biomass. Though planned, these forest treatments can be delayed for a variety of reasons. For example, litigation and appeals decisions can delay approval and implementation. Limited resources of time, money, or tools, and exogenous forces, such as economic cycles and changes to environmental laws, may all inhibit the implementation of specific management activities. These delays contribute to uncertainty in ecosystem functioning due to the dynamic nature of forests and the impact of their structure on feedbacks and interactions with biogeochemical (e.g. water and carbon cycling) and biophysical (e.g. heat exchange and turbulence) processes. Here we addressed this uncertainty by asking the question: does a delay in project implementation result in different forest productivity and structure compared to a project completed as planned? We answered this question by using the Functionally Assembled Terrestrial Ecosystem Simulator within the Community Land Model (CLM-FATES) to simulate an on-time and delayed timber harvest project at a single point scale in southern Idaho using a single plant functional type. The simulations were calibrated to observations from remotely sensed leaf area index and allometric data for ponderosa pine from census data in an experimental forest. Project level data from the US Forest Service was used to inform the timing of a typical timber harvest project and the average length of an implementation delay. Modeled outputs of age class distribution, tree density, surface runoff, above ground biomass, and gross primary productivity were compared across scenarios. Results show that the timing of harvest treatments contributes to changes in modeled outputs between scenarios. These results have implications for the future of forest management representation in land surface models and its application to regional managers and stakeholders. Future work will seek to scale these scenarios to a regional level with coexisting plant functional types representing a typical forest in the area.