Are Climate Factors Driving the Contemporary Wildfire Occurrence in China?

Abstract

Understanding the drivers of wildfire occurrence is of great value for fire prevention and management, but due to the variation in research methods, data sources, and data resolution of those studies, it is challenging to conduct a large-scale comprehensive comparative qualitative analysis on the topic. China has diverse vegetation types and topography, and has undergone rapid economic and social development, but experiences a high frequency of wildfires, making it one of the ideal locations for wildfire research. We applied the Random Forests modelling approach to explore the main types of wildfire drivers (climate factors, landscape factors and human factors) in three high wildfire density regions (Northeast (NE), Southwest (SW), and Southeast (SE)) of China. The results indicate that climate factors were the main driver of wildfire occurrence in the three regions. Precipitation and temperature significantly impacted the fire occurrence in the three regions due to the direct influence on the moisture content of forest fuel. However, wind speed had important influence on fire occurrence in the SE and SW. The explanation power of the landscape and human factors varied significantly between regions. Human factors explained 40% of the fire occurrence in the SE but only explained less than 10% of the fire occurrence in the NE and SW. The density of roads was identified as the most important human factor driving fires in all three regions, but railway density had more explanation power on fire occurrence in the SE than in the other regions. The landscape factors showed nearly no influence on fire occurrence in the NE but explained 46.4% and 20.6% in the SE and SW regions, respectively. Amongst landscape factors, elevation had the highest average explanation power on fire occurrence in the three regions, particularly in the SW. In conclusion, this study provides useful insights into targeted fire prediction and prevention, which should be more precise and effective under climate change and socio-economic development.

RETRACTED: The Temporal-Spatial Distribution and Information-Diffusion-Based Risk Assessment of Forest Fires in China

“…In addition to great temporal differences, forest fires in the complex topography of China are characterized by significant regional differences. From 1998 to 2017, the highest number of forest fires occurred in Hunan (26,344), which is followed by Guizhou (19,299), Guangxi (11,341), and Hubei (10,203) (see Figure 3). As the province with a high forest coverage rate in China, Hunan has a large population density and a high fire frequency for domestic use and production use, resulting in many forest fires [66].…”

Indonesian Forest and Land Fire Prevention Patrol System

“…The mobile application is used to manage the influencing factors of fire occurrence, including the vegetation, weather, and human activities in the fire-prone areas. The vegetation and weather factors are essential to be analyzed because they have a significant relationship with the occurrence of fires, as reported in the previous studies [4][5][6][7][8][9][10][11]16,19]. Because Indonesian fires are frequently caused by human activities, socio-economic aspects are important in fire-risk modeling [6][7][8]11,13,16,18,19,21].…”

“…The vegetation and weather factors are essential to be analyzed because they have a significant relationship with the occurrence of fires, as reported in the previous studies [4][5][6][7][8][9][10][11]16,19]. Because Indonesian fires are frequently caused by human activities, socio-economic aspects are important in fire-risk modeling [6][7][8]11,13,16,18,19,21]. Therefore, the Forest and Land Fire Prevention Patrol Information System has significantly contributed to providing field data related to vegetation, weather, and human activities for forest and land fire risk modeling in Indonesia.…”

Spatiotemporal Dynamics and Climate Influence of Forest Fires in Fujian Province, China

“…Most forest fire studies show that human activities [22], vegetation [47] and climate [48,49] are the main factors determining the temporal and spatial pattern of forest fires. Human activities, vegetation cover, and climate are different in different time scales, as are their impacts on forest fires and their temporal trends.…”