Synergies Between Forest Biomass Extraction for Bioenergy and Fire Suppression in Mediterranean Ecosystems: Insights from a Storyline-and-Simulation Approach
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Increases in fire impacts over many regions of the world have led to large-scale investments in fire-suppression efforts. There is increasing recognition that biomass extraction for energy purposes may become an important forest-management practice in fire-prone ecosystems. However, at present, very few studies have explicitly assessed biomass extraction as a fuel treatment at landscape scale. Here, we use a landscape fire-succession model in Catalonia (NE Spain) to quantitatively evaluate the potential effects of a biomass extraction-based strategy on essential fire-regime attributes after considering different levels of fire suppression, biomass extraction intensity, and spatial allocation of such efforts. Our simulations indicated that the effectiveness (area suppressed in relation to expected area to burn) at suppressing wildfires was determined by extraction intensity, spatial allocation of the extraction effort, and the fire-suppression levels involved. Indeed, the highest suppressed-area values were found with lower harvesting intensities, especially under high fire-suppression capabilities and strategies focused on bioenergy goals (figures close to 0.7). However, the leverage (area suppressed in relation to managed area) was higher when the treatments were based on the fire-prevention strategy and focused on high-fire-risk areas (up to 0.45) than with treatment designed for energy reasons (lower than 0.15). We conclude that biomass extraction for energy purposes has the potential to induce changes in fire regimes and can therefore be considered a cost-effective landscape-level fuel-reduction treatment. However, our results suggest that large-scale biomass extraction may be needed if significant changes in fire regimes are to be expected.
Keywordsfire suppression forest fires forest harvesting MEDFIRE fire-succession model Mediterranean basin process-based model renewable energy scenarios-based analysis landscape simulations
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