Spatial and temporal patterns and driving factors of forest fires based on an optimal parameter-based geographic detector in the Panxi region, Southwest China

IF 3.6 3区 环境科学与生态学 Q1 ECOLOGY Fire Ecology Pub Date : 2024-03-15 DOI:10.1186/s42408-024-00257-z
Jia Liu, Yukuan Wang, Haiyan Guo, Yafeng Lu, Yuanxin Xu, Yu Sun, Weiwei Gan, Rui Sun, Zhengyang Li
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Abstract

The Panxi region in China is among the areas that are most severely impacted by forest fires. Despite this, there is currently a lack of comprehensive and systematic research on the spatial and temporal distribution patterns, as well as the drivers, of forest fires in the region. To reveal bio-geo-climatic and anthropogenic influences, this study investigated the temporal and spatial characteristics of forest fires and migration patterns of the center of gravity of forest fires in Panxi. A parametric optimal geographical detection model was utilized to quantify the influence of various individual factors and their combinations on the spatial patterns of forest fire occurrence in the whole Panxi region and sub-region, by analyzing the forest fire dataset from 2004 to 2020. From 2004 to 2020, the Panxi region experienced an upward trend in the number of forest fires and the area burned. However, the trends were not consistent over the entire period. Between 2004 and 2014, both the number of fires and the area burned showed fluctuations and an overall increase. In contrast, between 2015 and 2020, there was a significant decrease in the number of fires, while the area burned showed a continued upward trend. The study identified abrupt changes in the frequency of forest fires and burned areas, primarily in 2007 and 2016. Spatially, forest fires in Panxi exhibited a positive correlation and local clustering. The river valley basin and hilly regions displayed a higher incidence of forest fires, which were concentrated mainly along the hill edges. In the whole area of Panxi, climatic factors have a predominant influence on forest fire occurrences. Specifically, evaporation, maximum temperature, average temperature, number of days without rain, and minimum temperature demonstrated the strongest explanatory power. Furthermore, this relationship was found to be reinforced when combined with topographical, human activities, and vegetation factors. The spatial variation of drought within each sub-district has a stronger explanatory power for the distribution characteristics of forest fires in the region than at the Panxi-wide scale. The factor with the maximum interaction in most regions was the dual factor of rainfall and drought. The study’s findings validate the applicability of geographic probes for identifying the drivers of fire occurrence and enhance our understanding of the drivers and their combined effects on the spatial context of the fire-incident study area.
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基于最优参数地理探测器的中国西南攀西地区森林火灾时空模式及驱动因素
中国攀西地区是受森林火灾影响最严重的地区之一。尽管如此,目前对该地区森林火灾的时空分布模式和驱动因素还缺乏全面系统的研究。为了揭示生物地理气候和人为因素的影响,本研究调查了攀西地区森林火灾的时空特征和森林火灾重心的迁移规律。通过对 2004-2020 年森林火灾数据集的分析,利用参数最优地理探测模型,量化了各种单独因素及其组合对整个攀西地区和次区域森林火灾发生空间格局的影响。从 2004 年到 2020 年,攀西地区的森林火灾次数和燃烧面积呈上升趋势。然而,整个期间的趋势并不一致。2004 年至 2014 年期间,火灾次数和燃烧面积均呈波动和总体上升趋势。相比之下,在 2015 年至 2020 年期间,火灾次数显著减少,而燃烧面积则呈持续上升趋势。研究发现,森林火灾频率和烧毁面积的突然变化主要发生在 2007 年和 2016 年。从空间上看,攀西地区的森林火灾呈现出正相关性和局部聚集性。河谷盆地和丘陵地区森林火灾发生率较高,主要集中在山体边缘。在整个攀西地区,气候因素对森林火灾的发生具有主导影响。其中,蒸发量、最高气温、平均气温、无雨日数和最低气温的解释力最强。此外,这种关系在与地形、人类活动和植被因素相结合时得到了加强。与全攀西范围相比,各分区干旱的空间变化对该地区森林火灾分布特征的解释力更强。在大多数地区,降雨和干旱双重因子的交互作用最大。研究结果验证了地理探针在识别火灾发生驱动因素方面的适用性,并加深了我们对火灾发生驱动因素及其对火灾发生研究区域空间环境的综合影响的理解。
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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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