Join Oregon State University, the Fire Adapted Communities Network, and partners for an engaging workshop to transform how we adapt and coexist with wildfire in light of dynamic ecological, social, and economic challenges. As new fire policies and adaptation strategies have grown across the Northwest, it is essential that we work together to learn, share, and craft actionable visions.
With approximately 15 million hectares burned, the 2023 wildfire season in Canada was exceptional. However, it remains unclear whether such recent increases in burned areas exceed the range of variability observed over past centuries.
Communities can face significant risk from wildfire, often compounded by climate change and legacies of industrial forest management.
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.
Dangerous fire weather is increasing under climate change, but there is limited knowledge of how this will affect fire intensity, a critical determinant of the socioecological effects of wildfire.
The frequency, severity, and scale of extreme wildfire events is increasing globally, with certain regions such as the western United States disproportionately impacted. As attention shifts toward understanding how to adapt to and recover from extreme wildfire, there is a need to prioritize where additional research and evidence are needed to inform decision-making.
Wildfire’s destruction of homes is an increasingly serious global problem. Research indicates that characterizing home hardening and defensible space at the individual structure level may reduce loss through enriched understanding of structure susceptibility in the built environment. However, improved data and methods are required to accurately characterize these features at scale.