林业科学2024，Vol.60Issue(5)：158-168,11.DOI:10.11707/j.1001-7488.LYKX20230388
赣南马尾松林地表细小死可燃物含水率动态及模型
Moisture Dynamics and Modeling of Ground Surface Fine Dead Combustibles in Pinus massoniana Forest in Southern Jiangxi,China
摘要
Abstract
[Objective]The moisture content of the surface fine dead combustibles(SFDC,including dead leaves,thin branches,dead grass,needles,etc.)significantly influences forest fire ignition and behavior.Understanding of the SFDC is essential for early warning of forest fire in a region.This study focuses on predicting SFDC in Masson pine forests in southern Jiangxi Province.[Method]We conducted long-term field observations of SFDC in Masson pine,a prevalent vegetation type in southern Jiangxi.The study involved a comparative analysis of various predictive models,considering meteorological factors'random forest relative importance and Pearson correlation in different terrains and times.[Result]SFDC in Masson pine forests shows a notable variability,with higher moisture content on shady slopes compared to sunny slopes,especially at the early time of fire prevention periods.A strong correlation(P<0.001)exists between SFDC and meteorological factors(temperature,humidity,wind speed,sunlight).The random forest model outperformed the meteorological factor regression model in accuracy,particularly on shady slopes.Sunlight,with a lag effect,and air humidity on sunny slopes and wind speed on shady slopes were the most influential factors.[Conclusion]Meteorological factors with time lag critically affect SFDC in Masson pine forests.Improved consideration of these factors enhances the prediction accuracy of the moisture content of the SFDC,offering a reliable basis for early warning of fire risk.关键词
地表细小死可燃物含水率/预测模型/气象要素回归模型/随机森林/赣南地区Key words
moisture content of surface fine dead combustibles/prediction model/meteorological regression model/random forest/southern Jiangxi分类
农业科技引用本文复制引用
朱诗豪,吴志伟,李政杰,李顺..赣南马尾松林地表细小死可燃物含水率动态及模型[J].林业科学,2024,60(5):158-168,11.基金项目
国家自然科学基金项目(32271897). （32271897）
