发表机构
Bordeaux Sciences-Agro; INRAE; IGN - Institut National de l'Information Géographique et Forestière（波尔多科学与农业学院; 法国国家农业、食品与环境研究所; 国家地理与林业信息研究所）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对日益严重的野火风险，本研究提出在生长模型中集成火灾模拟的优化方法，用于集约化人工林管理，发现多样化组合可提升木材供给稳健性，但未必利于碳储存，并揭示了现有规划的改进方向。
AI 中文摘要
日益严重且不可预测的极端天气事件——如高强度森林火灾——威胁着长期生态系统服务的供给，推动了对当前森林管理规划的关键性重新评估。尽管已有规划框架存在，但很少有框架纳入考虑此类极端事件所引入的不确定性和变异性的优化方法。与此同时，基于过程的模型增进了我们对火灾对森林动态和生态系统服务影响的理解，但其在指导战略管理决策方面的潜力在很大程度上仍未得到开发。聚焦于集约化人工林，我们提出了一种组合方法，在生长模型内使用火灾模拟，以在日益增加的火灾风险下优化森林景观管理。我们证明，纳入火灾行为及其不确定性会显著改变管理结果，倾向于支持多样化的组合，这些组合在高产但易受火灾影响的经营制度与较低风险的替代方案之间取得平衡。虽然多样化提高了诸如木材供给等目标的稳健性，但它并不能保证对碳储存产生互补性效益。我们的方法揭示了当前管理制度的局限性，并识别了改进规划的关键领域，以更好地减轻火灾风险并增强长期韧性。
英文摘要
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.
