Widespread tree mortality caused by outbreaks of native bark beetles (Circulionidae: Scolytinae) in recent decades has raised concern among scientists and forest managers about whether beetle outbreaks fuel more ecologically severe forest fires and impair postfire resilience.
Wildfire activity in boreal forests is anticipated to increase dramatically, with far-reaching ecological and socioeconomic consequences. Paleorecords are indispensible for elucidating boreal fire regime dynamics under changing climate, because fire return intervals and successional cycles in these ecosystems occur over decadal to centennial timescales.
Understanding the causes and consequences of wildfires in forests of the western United States requires integrated information about fire, climate changes, and human activity on multiple temporal scales.
Background: Previous work by the author and others has examined weather associated with growth of exceptionally large fires (‘Fires of Unusual Size’, or FOUS), looking at three of four factors associated with critical fire weather patterns: antecedent drying, high wind and low humidity. However, the authors did not examine atmospheric stability, the fourth factor.
Foliar moisture content influences crown fire ignition and behaviour. Some spatial variation in foliar moisture is attributable to differences in stand conditions but evidence describing this role is lacking or contradicting. Aims.
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).
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.
The Composite Burn Index (CBI) is commonly linked to remotely sensed data to understand spatial and temporal patterns of burn severity. However, a comprehensive understanding of the tradeoffs between different methods used to model CBI with remotely sensed data is lacking.
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.
Human land use practices, altered climates, and shifting forest and fire management policies have increased the frequency of large wildfires several-fold. Mitigation of potential fire behaviour and fire severity have increasingly been attempted through pre-fire alteration of wildland fuels using mechanical treatments and prescribed fires.