Monitoring effectiveness of forest restoration treatments: the importance of space and time

Research Sponsored By: USDI Bureau of Land Management
Principal Investigator: Jonathan Bakker
Project Description
Forests throughout much of the western interior United States are widely recognized to be at risk due to a history of fire exclusion. As a result, fuel reduction treatments (thinning and prescribed burning) are occurring throughout this area. These treatments are intended to restore ecosystem structure and function and to enhance resilience to disturbances (fire and insect outbreaks) in the face of climate change. The effectiveness of treatments in meeting these restoration objectives requires that appropriate metrics (or indicators) be identified and assessed at temporal and spatial scales relevant to management. This project addresses the effects of fuel reduction treatments on overstory and understory vegetation. We have two primary objectives. First, we will assess the range of metrics used by managers and scientists to characterize the effects of fuels treatments on overstory and understory vegetation. Metrics will be identified through a review of the published and unpublished literature supplemented by interviews as needed. Metrics will be assessed in terms of their consistency and sensitivity both to treatments and to spatial scale of observation. We will identify those metrics that yield predictable responses and have broad usability, as these are of primary interest to land managers. Second, we will use long-term experimental data to assess the consistency of conclusions drawn from measurements made 2-3 years after fuels treatments (a factorial design of mechanical thinning and prescribed burning) with those made a decade later (12-13 years after treatments). Analyses will be based on a remeasurement of the overstory and understory vegetation at the Mission Creek Fire and Fire Surrogates site in the eastern Cascade Mountains of Washington, and will capitalize on an existing sampling design that enables hierarchical analyses at spatial scales from 1 m2 to 10 ha.