根据最近的气候和整个大沙棘灌木地区的细小燃料估算出的野火概率

IF 3.6 3区 环境科学与生态学 Q1 ECOLOGY Fire Ecology Pub Date : 2024-02-28 DOI:10.1186/s42408-024-00252-4
Martin C. Holdrege, Daniel R. Schlaepfer, Kyle A. Palmquist, Michele Crist, Kevin E. Doherty, William K. Lauenroth, Thomas E. Remington, Karin Riley, Karen C. Short, John C. Tull, Lief A. Wiechman, John B. Bradford
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引用次数: 0

摘要

野火是导致完整的大鼠尾草(Artemisia tridentata Nutt.)近几十年来,火灾发生的时间间隔缩短了,一些地区的焚烧面积增加了,在火灾后重新建立的鼠尾草受到入侵一年生草类的阻碍时,栖息地正在退化。在未来几十年中,气候的变化可能会加速这些野火和入侵的反馈作用,但预测未来的野火动态需要更好地了解整个大鼠尾草地区的长期野火驱动因素。在这里,我们将野火观测数据与气候和植被数据相结合,为整个大鼠尾草地区推导出了一个统计模型,该模型体现了每年野火发生的概率是如何受到气候和精细燃料特征的影响的。整个鼠尾草地区的野火频率变化很大,我们的统计模型代表了其中的大部分变化。一年生和多年生禾本科及草本植物的生物量(我们将其作为精细燃料的代用指标)影响着野火发生的概率。野火发生概率在一年生草本植物生物量高的地区最高,这与文献记载的一年生草本植物入侵后野火增加的现象一致。在夏季干燥的地方,一年生草对野火概率的影响最大。野火概率随多年生禾本科和草本植物生物量的变化而变化,在生物量处于中等水平时野火概率最高。整个鼠尾草地区的气候差异很大,气候也能预测野火发生概率,夏季降水比例低、降水量中等和温度高的地区野火发生概率最高。我们开发了一个经过仔细验证的模型,该模型包含相对简单且在生物学上合理的关系,目的是在新条件下充分发挥其性能,以便在条件发生普遍变化时对年平均野火发生概率做出有用的预测。以前关于植被和气候对鼠尾草生态系统野火发生概率的影响的研究通常使用较为复杂的机器学习方法,而且通常只适用于部分鼠尾草地区。因此,我们的模型是对现有工作的补充,是了解整个鼠尾草地区未来野火和生态动态的又一工具。
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Wildfire probability estimated from recent climate and fine fuels across the big sagebrush region
Wildfire is a major proximate cause of historical and ongoing losses of intact big sagebrush (Artemisia tridentata Nutt.) plant communities and declines in sagebrush obligate wildlife species. In recent decades, fire return intervals have shortened and area burned has increased in some areas, and habitat degradation is occurring where post-fire re-establishment of sagebrush is hindered by invasive annual grasses. In coming decades, the changing climate may accelerate these wildfire and invasive feedbacks, although projecting future wildfire dynamics requires a better understanding of long-term wildfire drivers across the big sagebrush region. Here, we integrated wildfire observations with climate and vegetation data to derive a statistical model for the entire big sagebrush region that represents how annual wildfire probability is influenced by climate and fine fuel characteristics. Wildfire frequency varied significantly across the sagebrush region, and our statistical model represented much of that variation. Biomass of annual and perennial grasses and forbs, which we used as proxies for fine fuels, influenced wildfire probability. Wildfire probability was highest in areas with high annual forb and grass biomass, which is consistent with the well-documented phenomenon of increased wildfire following annual grass invasion. The effects of annuals on wildfire probability were strongest in places with dry summers. Wildfire probability varied with the biomass of perennial grasses and forbs and was highest at intermediate biomass levels. Climate, which varies substantially across the sagebrush region, was also predictive of wildfire probability, and predictions were highest in areas with a low proportion of precipitation received in summer, intermediate precipitation, and high temperature. We developed a carefully validated model that contains relatively simple and biologically plausible relationships, with the goal of adequate performance under novel conditions so that useful projections of average annual wildfire probability can be made given general changes in conditions. Previous studies on the impacts of vegetation and climate on wildfire probability in sagebrush ecosystems have generally used more complex machine learning approaches and have usually been applicable to only portions of the sagebrush region. Therefore, our model complements existing work and forms an additional tool for understanding future wildfire and ecological dynamics across the sagebrush region.
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来源期刊
Fire Ecology
Fire Ecology ECOLOGY-FORESTRY
CiteScore
6.20
自引率
7.80%
发文量
24
审稿时长
20 weeks
期刊介绍: Fire Ecology is the international scientific journal supported by the Association for Fire Ecology. Fire Ecology publishes peer-reviewed articles on all ecological and management aspects relating to wildland fire. We welcome submissions on topics that include a broad range of research on the ecological relationships of fire to its environment, including, but not limited to: Ecology (physical and biological fire effects, fire regimes, etc.) Social science (geography, sociology, anthropology, etc.) Fuel Fire science and modeling Planning and risk management Law and policy Fire management Inter- or cross-disciplinary fire-related topics Technology transfer products.
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