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DOI | 10.1007/s11069-021-04733-6 |
Modeling wildfire drivers in Chinese tropical forest ecosystems using global logistic regression and geographically weighted logistic regression | |
Su Z.; Zheng L.; Luo S.; Tigabu M.; Guo F. | |
发表日期 | 2021 |
ISSN | 0921030X |
起始页码 | 1317 |
结束页码 | 1345 |
卷号 | 108期号:1 |
英文摘要 | The tropics is an area with high incidence of wildfire all over the world in recent years, and the forest ecosystem in the tropics is extremely fragile. Thus, it is very important to identify drivers of wildfire in the tropics for developing effective fire management strategy. In this paper, global logistic regression (GLR) and geographically weighted regression (GWLR) models were employed to analyze the spatial distribution and drivers of tropical wildfires in Xishuangbanna and Leizhou Peninsula in tropical China from 2001 to 2018. The results show that the overall distribution of wildfire in Xishuangbanna and Leizhou Peninsula from 2001 to 2018 was spatially aggregated. In these tropical seasonal forest ecosystems, wildfire was mainly driven by meteorological factors, particularly by daily temperature range and precipitation. In Xishuangbanna (inland) peninsula, the impact of driving factors tended to be global, and the GLR model predicted the probability of wildfire occurrence better than the GWLR model. Drivers of wildfire in Leizhou Peninsula (coastal area) had clear spatial variation, and the GWLR model better explained the relationship. Furthermore, wildfire in Leizhou was more driven by human activities, especially management of agricultural lands. Our results demonstrate that effective forest management practice needs to adopt fire management practices with regional characteristics. The forest management strategy and traditional agriculture production system should pay more attention to changes in these driving factors and their relationship with wildfire. © 2021, The Author(s), under exclusive licence to Springer Nature B.V. |
关键词 | Fire preventionSpatial fire distributionTropical ecosystemWildfire drivers |
语种 | 英语 |
来源期刊 | Natural Hazards |
文献类型 | 期刊论文 |
条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/206582 |
作者单位 | Zhangzhou Institute of Technology, Zhangzhou, 363000, China; College of Forestry, Fujian Agriculture and Forestry University, Fuzhou, 350002, China; Guangdong Provincial Key Laboratory of Silviculture, Protection and Utilization, Guangdong Academy of Forestry, Guangzhou, Guangdong 510520, China |
推荐引用方式 GB/T 7714 | Su Z.,Zheng L.,Luo S.,et al. Modeling wildfire drivers in Chinese tropical forest ecosystems using global logistic regression and geographically weighted logistic regression[J],2021,108(1). |
APA | Su Z.,Zheng L.,Luo S.,Tigabu M.,&Guo F..(2021).Modeling wildfire drivers in Chinese tropical forest ecosystems using global logistic regression and geographically weighted logistic regression.Natural Hazards,108(1). |
MLA | Su Z.,et al."Modeling wildfire drivers in Chinese tropical forest ecosystems using global logistic regression and geographically weighted logistic regression".Natural Hazards 108.1(2021). |
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