Fuels and Fuel Treatments

Costs of fighting wildfires have increased substantially over the past several decades. Yet surprisingly little is known about the effectiveness of wildfire suppression or how wildfire incident managers prioritize resources threatened within a wildfire incident.

Background: In wildland–urban interface (WUI) fires, particulates from the combustion of both natural vegetative fuels and engineered cellulosic fuels may have deleterious effects on the environment. Aims: The research was conducted to investigate the morphology of the particulate samples generated from the combustion of oriented strand board (OSB).

• Effective wildland fire response and suppression are critical for reducing the size of frequent and severe wildfires, thereby reducing the risk of post-fire conversion to invasive annual grass-dominated plant communities. • Wildland firefighter safety and strategic deployment of resources are paramount for timely initial attack to prevent incidents from escalating.

Rangeland wildfire is a wicked problem that cuts across a mosaic of public and private rangelands in the western United States and countless countries worldwide. Fine fuel accumulation in these ecosystems contributes to large-scale wildfires and undermines plant communities’ resistance to invasive annual grasses and resilience to disturbances such as fire.

Forest biological disturbance agents (BDAs) are insects, pathogens, and parasitic plants that affect tree decline, mortality, and forest ecosystems processes. BDAs are commonly thought to increase the likelihood and severity of fire by converting live standing trees to more flammable, dead and downed fuel.

Background. Fire models use pyrolysis data from ground samples and environments that differ from wildland conditions. Two analytical methods successfully measured oxidative pyrolysis gases in wind tunnel and field fires: Fourier transform infrared (FTIR) spectroscopy and gas chroma- tography with flame-ionisation detector (GC-FID). Compositional data require appropriate statistical analysis.

Wildland fire is a common occurrence in western Canada, with record-setting area burned recorded in British Columbia (BC) in the past decade. Here, we used the unsupervised machine learning algorithm HDBSCAN to identify high-density clusters of both human- and lightning- caused wildfire ignitions in BC using data from 2006 to 2020.

Wildfire is a keystone ecological process in many forests worldwide, but fire exclusion and suppression have driven profound shifts in forest structure (e.g., increased density, canopy cover, biomass) that have contributed to increases in large, high-severity fire in many seasonally dry forests and woodlands of the western United States.

Supporting wildfire management activities is frequently identified as a benefit of forestroads. As such, there is a growing body of research into forest road planning, construction, andmaintenance to improve fire surveillance, prevention, access, and control operations.