将植物、动物和土著实践整合到规定燃烧的空间优化中

IF 8.4 2区 环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES Journal of Environmental Management Pub Date : 2025-04-01 Epub Date: 2025-03-09 DOI:10.1016/j.jenvman.2025.124833
Jie Xi , Wei Fu , Luca Maria Francesco Fabris , Jiping Wen , Zhouyu Fan , Yitong Pan , Siyu Wang
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引用次数: 0

摘要

气候变化加剧了野火活动,有必要转向可持续的火灾管理战略,包括火灾共存的概念。“火共存”认识到火作为一个自然生态过程的作用,并整合了植物(例如,防火树皮,再生能力),动物(例如,通过放牧减少燃料,创建自然防火带)和传统土地管理实践(例如,控制燃烧,农业防火带)的适应性,使生态系统能够与火共存。这些“共存因素”对于有效的规定燃烧至关重要,确保对适应火灾的物种的破坏最小,并最大限度地提高长期生态系统的恢复能力。虽然规定燃烧是一种公认的管理工具,但缺乏将这些共存因素在空间上整合到区域尺度规划中的综合框架。本研究通过开发一种新颖的方法来解决这一差距,该方法通过整合火灾风险和共存能力来优化规定燃烧的空间。将这种方法应用于嘉陵江流域(中国),一个火灾多发的山区,我们使用机器学习和深度学习来预测火灾风险并识别高共存潜力的区域。然后采用分区5进行空间优先排序。结果表明,火灾风险与共存能力之间存在显著的空间相关性,高值集群集中在研究区中南部,特别是嘉陵江周边和森林地区。具体而言,4%的研究区域位于中南地区(value >;0.679)为非常高火灾风险区,而前10%的区域表现出较高的共存能力(值>;0.9)。通过分区5优化,确定了5%的共存能力高的易火森林为规定燃烧优先区域,主要集中在北碚东部。这种综合方法为全球类似山区的政策制定者、土地规划者和利益相关者可持续地管理火灾灾害提供了宝贵的指导。
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Integrating flora, fauna, and indigenous practices into spatial optimization for prescribed burning
Climate change has intensified wildfire activity, necessitating a shift towards sustainable fire management strategies that embrace the concept of fire coexistence. Fire coexistence recognizes the role of fire as a natural ecological process and integrates the adaptations of flora (e.g., fire-resistant bark, regenerative capacity), fauna (e.g., fuel reduction through grazing, creation of natural firebreaks), and traditional land management practices (e.g., controlled burns, agricultural firebreaks) that enable ecosystems to persist with fire. These "coexistence factors" are crucial for effective prescribed burning, ensuring minimal disruption to fire-adapted species and maximizing long-term ecosystem resilience. While prescribed burning is a recognized management tool, a comprehensive framework for spatially integrating these coexistence factors into regional-scale planning is lacking. This study addresses this gap by developing a novel approach that spatially optimizes prescribed burning by integrating fire risk and coexistence capacity. Applying this approach to the Jialing River watershed (China), a fire-prone mountainous region, we use machine learning and deep learning to predict fire risk and identify areas with high coexistence potential. Zonation 5 is then employed for spatial prioritization. Results reveal a significant spatial correlation between fire risk and coexistence capacity, with high-value clusters concentrated in the central and southern parts of the study area, particularly around the Jialing River and forested regions. Specifically, 4% of the study area in the central and southern regions (value > 0.679) was classified as very high fire risk, while the top 10% of the area exhibited high coexistence capacity (value > 0.9). Based on Zonation 5 optimization, 5% of fire-prone forests with high coexistence capacity were identified as priority areas for prescribed burning, concentrated primarily in eastern Beibei. This integrated approach offers valuable guidance for policymakers, land planners, and stakeholders in sustainably managing fire hazards in similar mountainous regions globally.
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来源期刊
Journal of Environmental Management
Journal of Environmental Management 环境科学-环境科学
CiteScore
13.70
自引率
5.70%
发文量
2477
审稿时长
84 days
期刊介绍: The Journal of Environmental Management is a journal for the publication of peer reviewed, original research for all aspects of management and the managed use of the environment, both natural and man-made.Critical review articles are also welcome; submission of these is strongly encouraged.
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