Stochastic optimization modeling reveals front-loaded road restoration mitigates wildfire risk in boreal forests, suggesting earlier intervention preserves carbon storage.
This poster presents a stochastic extension of a Mixed-Integer Linear Programming (MILP) framework for prioritizing the restoration of abandoned forest roads under wildfire risk. Building on a deterministic carbon-optimization model (Vega-Escobar et al. 2026, Ecological Modelling), this work integrates fire regime uncertainty through two mechanisms: a carbon survival factor and an ignition-frequency penalty. Applied to a boreal Forest Management Unit in Saguenay–Lac-Saint-Jean, Quebec (2025–2050 planning horizon), the analysis shows that survival and ignition frequency interact rather than act additively under severe fire risk, and that risk-aware restoration schedules concentrate activity earlier in the planning horizon without systematically sacrificing carbon. Poster prepared as part of a PhD dissertation chapter at the Institut de Recherche sur les Forêts, UQAT.
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Valeria et al. (2026) studied this question.
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