Marshall Erica, Marcot Bruce G, Parkins Kate, Penman Trent D
FLARE wildfire research, The University of Melbourne, School of Agriculture, Food and Ecosystem Sciences, Melbourne, Victoria, Australia.
Pacific Northwest Research Station, Portland Forestry Sciences Laboratory, US Forest Service, Portland, OR, United States of America.
Sci Total Environ. 2024 Dec 20;957:177863. doi: 10.1016/j.scitotenv.2024.177863. Epub 2024 Dec 4.
Climate change and fire management actions are the two key drivers of fire regime changes now and into the future. The predicted effects of these drivers vary between regions and global climate projections; however, it is expected that fire regimes globally are likely to intensify. Increased wildfire extent, frequency and severity mean impacts to people, property, infrastructure, production and the environment are also likely to increase under worsening climate conditions. Fire management programs aim to reduce the influence of worsening climatic conditions on wildfires and risk to assets now and into the future However, given the pace of changes to fire regimes, trade-offs between assets are increasingly likely. Therefore, understanding the cost-effectiveness of fire management in the form of both fuel management and suppression is critical for managers to make informed decisions regarding resource allocation. We develop and test a Bayesian Decision Network (BDN) incorporating data from ~1200 fire regime simulations capturing 16 management strategies across six regions and six climate models. We quantify the effects of management and climate on fire size and risk to environmental, infrastructure, and production assets, as well as people and property. We calculate the overall cost-effectiveness of the management scenario based on the cost of implementing the program and the subsequent cost of impacts caused by wildfires. We found that costs increased under future climate conditions for all management scenarios in most regions. Despite some regional variation in the cost-effectiveness of management scenarios we were able to identify key scenarios which consistently had high cost-effectiveness. These were combinations of prescribed burning and suppression. Importantly, the model clearly demonstrates the risk of a do-nothing approach and highlights that action is needed to prevent high impacts now and into the future and to reduce the overall costs of wildfires.
气候变化和火灾管理行动是当前及未来火灾状况变化的两个关键驱动因素。这些驱动因素的预测影响因地区和全球气候预测而异;然而,预计全球火灾状况可能会加剧。野火范围、频率和严重程度的增加意味着在气候条件恶化的情况下,对人员、财产、基础设施、生产和环境的影响也可能增加。火灾管理计划旨在降低气候条件恶化对野火的影响以及当前和未来对资产的风险。然而,鉴于火灾状况的变化速度,资产之间的权衡取舍越来越可能出现。因此,了解燃料管理和灭火等形式的火灾管理的成本效益对于管理者做出关于资源分配的明智决策至关重要。我们开发并测试了一个贝叶斯决策网络(BDN),该网络纳入了来自约1200次火灾状况模拟的数据,涵盖六个地区的16种管理策略和六个气候模型。我们量化了管理和气候对火灾规模以及对环境、基础设施、生产资产以及人员和财产的风险的影响。我们根据实施该计划的成本以及野火造成的后续影响成本来计算管理方案的总体成本效益。我们发现,在未来气候条件下,大多数地区所有管理方案的成本都有所增加。尽管管理方案的成本效益存在一些地区差异,但我们能够确定始终具有高成本效益的关键方案。这些是规定燃烧和灭火的组合。重要的是,该模型清楚地展示了无所作为方法的风险,并强调需要采取行动以防止现在和未来产生高影响,并降低野火的总体成本。