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International Journal of Wildland Fire International Journal of Wildland Fire Society
Journal of the International Association of Wildland Fire
International Journal of Wildland Fire

International Journal of Wildland Fire

Volume 31 Number 6 2022

WF21072Reconstructing seasonal fire danger in southeastern Australia using tree rings

Kathryn Allen 0000-0002-8403-4552, Stephen B. Stewart, Carly Tozer, Doug Richardson, Craig Nitschke, James Risbey, Andrew Dowdy, Matthew Brookhouse, Paul Fox-Hughes 0000-0002-0083-9928, Mike Peterson and Patrick J. Baker
pp. 559-571

We use a tree-ring network from southeastern Australia to reconstruct the number of high fire-danger days in January–March, as reflected in the Forest Fire Danger Index (FFDI). Highest quality reconstructions in southwestern Tasmania indicate that the recent persistent increase in seasonal fire danger is unmatched over the past 430 years.

WF21144Comparing geostationary and polar-orbiting satellite sensor estimates of Fire Radiative Power (FRP) during the Black Summer Fires (2019–2020) in south-eastern Australia

Konstantinos Chatzopoulos-Vouzoglanis 0000-0001-7502-4216, Karin J. Reinke, Mariela Soto-Berelov, Chermelle Engel and Simon D. Jones
pp. 572-585

We explore the utility of next-generation satellite observations of fire intensity during the Black Summer Fires. We found that these new datasets capture similar patterns to the previous generation earth-observation data but offer greater temporal detail. These results are significant as they open new opportunities for active fire monitoring.

WF21176An analysis of factors influencing structure loss resulting from the 2018 Camp Fire

Austin Troy 0000-0003-3003-2532, Jason Moghaddas, David Schmidt, J. Shane Romsos, David B. Sapsis, William Brewer and Tadashi Moody
pp. 586-598

This study analysed loss data from the 2018 Camp fire and found numerous building characteristics that were important determinants of structural survival, including double paned windows, enclosed eaves, ignition-resistant roofs/siding, age of structure, lack of vents, improvement value, and decks. Defensible space had only weak associations with structure loss in this data set. Mobile homes were far more likely to be destroyed.

WF20177Preventing wildfires with fire permits in rural Edson, Alberta

Tara K. McGee and Ludwig Paul B. Cabling
pp. 599-606

This study examines wildfire prevention by rural residents in the Edson Forest Area, Alberta, Canada. Awareness of the wildfire risk was high, but there was little recognition that using fire for agricultural purposes contributed to wildfires in the area. Many respondents undertook wildfire prevention activities while using fire for agricultural purposes. Many fire users had not applied for a fire permit. Information about fire permits – and experiencing a wildfire in the Edson Forest Area – influenced wildfire prevention activities.

WF21150Can ash from smoldering fires increase peatland soil pH?

A. L. Marcotte 0000-0003-4149-3473, J. Limpens 0000-0001-5779-0304, C. R. Stoof 0000-0002-0198-9215 and J. J. Stoorvogel 0000-0003-4297-122X
pp. 607-620
Graphical Abstract Image

Peatlands need acidic soil conditions for maintaining proper health and functioning. Wildfire-produced ash is often alkaline, thus potentially impacting soil pH. We observed that soil pH was not affected by the ash generated during a peatland wildfire.

WF22005Do bird communities differ with post-fire age in Banksia woodlands of south-western Australia?

Robert A. Davis, Leonie E. Valentine and Michael D. Craig
pp. 621-633

We explored bird responses to fire in threatened Banksia woodlands in south-western Australia and found post-fire age had little or no effect on the overall bird community. Two species responded to post-fire age but were most abundant early post fire, suggesting the bird community is adaptable to a range of prescribed burning regimes.


A combined experimental and numerical study of firebrand transport is presented. A novel firebrand generator was built to produce specific-shaped burning firebrands and measure landing distributions. A physics-based model is used with four different drag sub-models to reproduce experimental results and results are obtained with various degrees of fidelity.

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