Get reliable science

Larger and more frequent wildfires are a primary threat to sagebrush ecosystems and populations of Greater sage-grouse in the Great Basin. The threat is exacerbated by the invasion of annual grasses that drive an accelerated grass-fire cycle, which hinder recovery of fire-intolerant and slow-growing sagebrush. Moreover, recent research has quantified how increasing rates of cumulative (rather than instantaneous) area burned have long-term negative impacts on sage-grouse annual rates of population change. If these rates of cumulative area burned continue unabated, projections indicate that populations of sage-grouse in the Great Basin will be reduced to 43% of their current numbers over the next 3 decades. Managers have two broad sets of tools available for slowing the loss of sagebrush and reduced persistence probability of sage-grouse in face of wildfire threats: post-wildfire restoration and wildfire suppression. To help identify how much effort from each tool is required to slow or nullify the cumulative effects of fire, we describe preliminary results of retrospective and prospective simulation analyses that model effects of: 1) increased suppression while accounting for current rates and restoration (i.e., seeding and seedling application); and 2) increasing restoration while accounting for current rates of suppression. These simulations account for factors influencing ecosystem resilience to disturbance and resistance to invasion (R&R), sagebrush return rates influenced by R&R, biophysical setting, and restoration type, and (eventually) juxtaposition of fuel breaks and assumed future annual grass control. Model output highlight that restoration and suppression activities are not mutually exclusive of one another, but also point out that the current rate of cumulative area burned in the Great Basin may outpace the rate at the which sage-grouse populations can respond positively as sagebrush recovers. This information is preliminary and is subject to revision. It is being provided to meet the need for timely best science.