Large wildfires with extreme behavior are increasingly frequent, causing significant environmental and social losses worldwide. Prescribed burning (Rx) is a crucial tool to mitigate these impacts. Although Rx activity is relatively high in some regions, such as Portugal, treatment efforts fall short of targets. Therefore, optimizing the spatial allocation of Rx is essential for mitigating wildfire hazards. This study evaluated the hazard-reduction effect of a shrubland Rx program in a mountainous area of Portugal. Fire hazard indicators, including burned area, fireline intensity, burn probability, and flame length, were compared among business-as-usual (BAU), Rx allocation, and optimized scenarios obtained using the FlamMap software treatment optimization tool. Two scenarios were tested: Rx limited to shrublands, and Rx applied to both shrublands and pine stands. Additionally, two ignition distribution strategies were considered for optimization: historical large fires and systematic landscape-wide ignition patterns. Results show that optimization reduced wildfire hazard indicators relative to BAU: burned area is reduced by up to 26%, fireline intensity by up to 22%, burn probability by up to 13%, and area with uncontrollable flame lengths by up to 1.7%. Therefore, the current BAU strategy can be improved. Optimization performs better when using systematic ignition patterns rather than historical fire locations, and extending Rx to pine stands further enhanced the hazard reduction. Allocating treatments to slopes steeper than those in BAU also improved the outcomes. Overall, this study highlights the need for locally tailored optimization strategies to enhance the effectiveness and impact of Rx programs.
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Laura Alonso
Paulo M. Fernandes
SHILAP Revista de lepidopterología
Frontiers in Forests and Global Change
Universidade de Vigo
University of Trás-os-Montes and Alto Douro
Xerox (France)
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Alonso et al. (Fri,) studied this question.
www.synapsesocial.com/papers/69e7132bcb99343efc98ce47 — DOI: https://doi.org/10.3389/ffgc.2026.1782881