Across the Western United States, human development into the wildland urban interface (WUI) is contributing to increasing wildfire damage. Given that natural disasters often cause greater harm within socio-economically vulnerable groups, research is needed to explore the potential for disproportionate impacts associated with wildfire.

As wildfire activity increases and fire-size distributions potentially shift in many forested regions worldwide, anticipating the spatial patterns of burn severity expected with future fire activity is critical for ecological understanding and informing management and policy.

Background

Formal requirements of wildfire mitigation on private properties are increasingly being considered as one avenue for “scaling up” wildfire management and voluntary mitigation actions to landscape scales.

Western Canada is increasingly experiencing impactful and complex wildfire seasons. In response, there are urgent calls to implement prescribed and cultural fire as a key solution to this complex challenge.

While it is well known that wildfires can greatly contribute to soil water repellency by changing soil chemical composition, the mechanisms of these changes are still poorly understood. In the past decade, the number, size, and intensity of wildfires have greatly increased in the western USA.

The effects of wildfire on the power grid are a recurring concern for utility companies who need reliable information about where to prioritize infrastructure hardening. Though there are existing data layers that provide measures of burn probability, these models predominately consider long-term climate variables, which are not helpful when analyzing current season trends.

In early 2020 the US Forest Service (USFS) recognized the need to gather real-time information from its wildland fire management personnel about their challenges and adaptations during the unfolding COVID-19 pandemic. The USFS conducted 194 virtual focus groups to address these concerns, over 32 weeks from March 2020 to October 2020.

Background

Background

Near-term forecasts of fire danger based on predicted surface weather and fuel dryness are widely used to support the decisions of wildfire managers. The incorporation of synoptic-scale upper-air patterns into predictive models may provide additional value in operational forecasting.

Aims