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Fires burning under marginal fire-weather conditions tend to be patchy in terms of their spatial coverage. This patchiness is partially driven by variability in the ignitability of the fuel bed. An understanding of fuel-bed ignitability through space and time would help fire managers to more effectively carry out prescribed burns to achieve desired levels of burn coverage in Eucalyptus forests. We sought to identify the key fuel-bed attributes influencing ignitability under marginal weather conditions. We recorded ignition successes and failures at 45 points within 5 operational prescribed burns and used the data to build logistic regression models to predict the probability of ignition as a function of fuel-bed attributes. Models were ranked using an information theoretic approach. The four highest ranked models explained 48–54% of the variance in ignitability. Surface fine-fuel moisture content (FFMC) and overall fuel hazard (i.e. fuel arrangement) were the strongest predictors of ignitability, occurring in all four highest ranking models. Both surface FFMC and overall fuel hazard were negatively related to ignition likelihood, contradicting a commonly assumed positive relationship between fuel hazard and flammability. Our field method to measure ignition success could be applied across more prescribed burns to develop operationally useful models of ignitability.

Forest fuel bed ignitability under marginal fire weather conditions in Eucalyptus forests