Despite widespread concern over increases in wildfire severity, the mechanisms underlying this trend remain unclear, hampering our ability to mitigate the severity of future fires.
The sagebrush biome in the western United States is a focus of widespread conservation concern due to multiple interacting threats including larger, more severe wildfires. Given the immense scale of the region and limited resources, prioritizing restoration treatments is essential for optimizing risk reduction and managing for resilient ecosystems.
Managers across the western US seek effective fuel treatment strategies to mitigate hazardous fuel loads and risks of high severity fire in dry conifer forests. Conventional fuel hazard reduction treatments emphasis reducing canopy fuel continuity and surface fuel loading using an even spaced, thin-from-below approach, with pile or broadcast burning of residual surface fuels.
Wildfire activity has accelerated with climate change, sparking concerns about uncharacteristic impacts on mature and old-growth forests containing large trees.
The social diversity of human populations living in or near wildfire-prone lands are an important influence on the scale at which wildfire mitigation action can occur among residential populations at increasing risk from wildfire.
Wildfires in the western US increasingly threaten infrastructure, air quality, and public health. Prescribed (“Rx”) fire is often proposed to mitigate future wildfires, but treatments remain limited, and few studies quantify their effectiveness on recent major wildfires.
Aspen (Populus tremuloides) forests are generally thought to impede fire spread, yet the extent of this effect is not well quantified in relation to other vegetation types.
Background. Fuel treatments are increasingly used to mitigate wildfire risks.
Aims. Proposing a novel, scalable and transferable methodology, this study investigates which treatment is (more) effective at a regional scale.
Warming temperatures and increasingly variable precipitation patterns are reducing winter snowpack and critical late-season streamflows. Here, we used two models (LANDIS-II and DHSVM) in linked simulations to evaluate the effects of wildfire and forest management scenarios on future snowpack and streamflow dynamics.