Abstract Background Prescribed burning is an important silvicultural tool used to reduce wildfire hazard by removing accumulated forest floor debris to improve wildlife habitat and to mimic the natural role of fire in the environment. Ladder fuels, which provide vertical fuel continuity between ground and crown fuels, pose a risk to the use of prescribed burning by increasing the likelihood that a surface fire may spread vertically resulting in undesirable fire behavior and unplanned fire effects. To minimize this risk, an improved understanding of the ignition criteria of ladder fuels is essential. We investigated the effect of ambient temperature, relative humidity, plant species, live fuel moisture content, live fuel bulk density, season of year, and fuel base height on ladder fuel ignition success via 92 controlled experiments. Ladder fuels were live manzanita and incense cedar foliage and branches placed above a surface fire burning in a pine needle fuel bed. In addition, we applied the Fire Dynamic Simulator (FDS), a Computational Fluid Dynamics (CFD) based model specifically designed to simulate fire scenarios, to replicate the experiment and compare the results with the experimental data. Results Using experimental data, we developed a logistic-regression model that characterizes empirical relationships and allows rapid estimation of ignition probability. The results show that ladder fuel burning behavior is highly sensitive to ambient temperature, fuel species, and fuel base height: ignition probability increases with temperature and varies systematically across species, while increasing fuel base height substantially reduces the likelihood of ignition. Moreover, FDS predictions are in good agreement with our experimental outcomes, reinforcing the robustness and potential applicability of FDS for operational prescribed-fire planning and risk assessment. Conclusion The experimental results provide a more comprehensive understanding of the ladder fuel ignition. The empirical logistic model offers an operationally useful basis for anticipating ladder-fuel ignition. The experimental data also supplies novel and realistic validation cases for FDS. The empirical ignition-prediction model as well as FDS can be incorporated to inform burn prescriptions, refine go/no-go decisions, and ultimately support safer, more effective use of prescribed fire.
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Yucheng He
Sanika Ravindra Nishandar
University of California, Riverside
Jiachen Zhang
University of Southern California
Fire Ecology
University of Southern California
University of California, Riverside
Pacific Southwest Research Station
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He et al. (Sat,) studied this question.
synapsesocial.com/papers/69b79e488166e15b153ab643 — DOI: https://doi.org/10.1186/s42408-026-00462-y
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