Integrating Wildfire Risk into Robust Forest Management Optimization
Abstract
Increasingly severe and unpredictable extreme weather events-such as high-intensity forest firesthreaten long-term ecosystem service provision, driving a critical reassessment of current forest management planning. While planning frameworks exist, few incorporate optimization methods that account for the uncertainty and variability introduced by such extremes. Meanwhile, process-based models have advanced our understanding of fire impacts on forest dynamics and ecosystem services, yet their potential to inform strategic management decisions remains largely untapped. Focusing on intensive plantation forests, we propose a combined approach that uses fire simulation within a growth model to optimize forested landscape management under increasing fire risk. We demonstrate that incorporating fire behavior and its uncertainties significantly alters management outcomes, favoring diversified portfolios that balance high-yield but fire-prone regimes with lowerrisk alternatives. While diversification improves robustness for objectives like timber provision, it does not guarantee complementary benefits for carbon storage. Our method exposes the limitations of current management regimes and identifies key areas for improved planning to better mitigate fire risk and strengthen long-term resilience.
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BibTeX
@misc{labarre2026integrating,
title = {{Integrating Wildfire Risk into Robust Forest Management Optimization}},
author = {Clémence Labarre and Denis Loustau and Jean-Christophe Domec and Mengistie Kindu and Thomas Knoke},
howpublished = {HAL},
year = {2026},
month = aug,
doi = {10.48550/arxiv.2609.16865},
eprint = {2609.16865},
archivePrefix = {arXiv},
url = {https://hal.science/hal-05716980v1},
note = {CC BY-NC-SA 4.0},
}
RIS
TY - UNPB
TI - Integrating Wildfire Risk into Robust Forest Management Optimization
AU - Clémence Labarre
AU - Denis Loustau
AU - Jean-Christophe Domec
AU - Mengistie Kindu
AU - Thomas Knoke
PY - 2026
DA - 2026/08/13
PB - HAL
DO - 10.48550/arxiv.2609.16865
UR - https://hal.science/hal-05716980v1
AB - Increasingly severe and unpredictable extreme weather events-such as high-intensity forest firesthreaten long-term ecosystem service provision, driving a critical reassessment of current forest management planning. While planning frameworks exist, few incorporate optimization methods that account for the uncertainty and variability introduced by such extremes. Meanwhile, process-based models have advanced our understanding of fire impacts on forest dynamics and ecosystem services, yet their potential to inform strategic management decisions remains largely untapped. Focusing on intensive plantation forests, we propose a combined approach that uses fire simulation within a growth model to optimize forested landscape management under increasing fire risk. We demonstrate that incorporating fire behavior and its uncertainties significantly alters management outcomes, favoring diversified portfolios that balance high-yield but fire-prone regimes with lowerrisk alternatives. While diversification improves robustness for objectives like timber provision, it does not guarantee complementary benefits for carbon storage. Our method exposes the limitations of current management regimes and identifies key areas for improved planning to better mitigate fire risk and strengthen long-term resilience.
ER -