An FSim burn probability (BP) map for the conterminous US was compared with observed wildfires from 2016 to 2022 in order to evaluate the suitability of wildfire simulation models for quantifying near-future wildfire risk. Our results highlight where burn probability models may be improved by incorporating dynamic weather and human influences.

We conduct a review of different fire behaviour proxies and real fire methods that have been used to assess the mechanisms of fire-induced mortality. We conclude that further research should assess mechanisms of fire-induced tree mortality using live plants in paired combustion laboratory and landscape fire experiments.

This effort produced novel burn severity data for many small and prescribed fires on both public and private lands across the Southeast. We evaluated spatial and temporal patterns in regional burn severity by vegetation type, as well as for fires attributed as prescribed or wildfire.

Fourier Transform Infrared spectra are presented for swamp sediments in the Blue Mountains, Australia. Fire-affected sediments show an increase in the aromatic/aliphatic ratio. C and N content show no consistent trend with hypothesised fire layers. Existing fire record was extended by several decades to centuries.

This study utilises a neural network model to analyse historical land management data in Colorado’s national forests. It incorporates environmental variables to understand factors influencing past fuel treatment decisions. This method offers insights for improving future forest management and wildfire prevention strategies.

This study presents a proof-of-concept for estimating fine fuel consumption and accumulation by integrating forest inventory and fire records, aiming to refine fuel dynamics estimates and enhance current practices. We estimated FFL changes across different vertical strata in southeast Australian eucalypt forests, considering burn severity, fire type and forest cover.