贵州喀斯特生态系统典型针叶林地表火蔓延速度影响因子及预测模型

Influencing factors and prediction models of surface fire spreading rate of typical coniferous forest in karst ecosystem of Guizhou Province,southwestern China

【目的】喀斯特生态系统农林交错,火源复杂,极易发生森林火灾,对喀斯特生态系统恢复等造成严重影响,研究该区域典型针叶床层平地无风条件下的林火蔓延速度,对于该区域植被恢复和森林防灭火工作具有重要意义。【方法】以喀斯特生态系统内3种典型针叶林下地表可燃物为研究对象,在室内平地无风条件下,构造与野外结构相似的针叶床层,以床层含水率、厚度和载量因子的不同梯度组合为变量,进行了188次点烧实验。【结果】(1)相同条件下,云南松和华山松针叶床层的林火蔓延速度没有显著差异,但显著高于马尾松针叶床层(P<0.001)。(2)可燃物床层含水率对针叶床层蔓延速度有显著的阻滞作用,床层厚度有显著的促进作用,床层载量对云南松和华山松针叶床层的蔓延速度有促进作用。(3)马尾松、云南松和华山松针叶床层林火蔓延速度的加式模型平均绝对误差分别为0.013、0.029和0.020 m/min,乘式模型的平均绝对误差分别为0.014、0.023、0.018 m/min,两种预测模型能解释75%以上的林火蔓延速度变化情况。(4)加式模型的外推误差的平均绝对误差和相对误差分别为0.108 m/min和42.50%,乘式模型外推效果优于加式模型,误差均值分别为0.086 m/min和28.20%。【结论】研究揭示喀斯特生态系统典型针叶林可燃物床层特征对林火蔓延速度的影响情况,3种针叶床层平地无风条件下蔓延速度较大,具有蔓延成灾的可能。综合预测精度和外推效果,建议选择乘式模型建立林火蔓延速度预测模型,为该生态系统内森林防灭火工作提供基础。

[Objective]The karst ecosystem is relatively vulnerable to forest fire due to interlaced agriculture and forestry and the fire source,which poses serious impact on the restoration of karst ecosystem.Thus,investigating the spreading rate of forest fire under no-wind and zero-slope conditions was of great significance for the restoration of vegetation and forest fire prevention in this region.[Method]This study focuses on the surface combustibles under three typical coniferous forests within the karst ecosystem.Under indoor no-wind and zero-wind conditions,coniferous beds layers similar to those found in the wild were constructed,and 188 ignition experiments were conducted with different gradient combinations of moisture content,thickness,and loads factors as variables.[Result](1)Under the same conditions,there was no significant difference in forest fire spreading rate between Pinus yunnanensis and Pinus armandii,but both rates were significantly higher than that of Pinus massoniana(P<0.001).(2)The moisture content of fuelbed could significantly retard the spreading rate of all fuelbed,while the height of fuelbed had a significant promoting effect,and the loading had promoting effect on the spreading rate of the needle bed of Pinus yunnanensis and Pinus armandii.(3)Fitting with additive model,the mean absolute error of spreading rate of fuelbed of Pinus massoniana,Pinus yunnanensis and Pinus armandii was 0.013,0.029 and 0.020 m/min,respectively,and the mean absolute error of multiplier model of forest fire spreading rate of fuelbed of Pinus massoniana,Pinus yunnanensis and Pinus armandii was 0.014,0.023,0.018 m/min,respectively.Besides,both prediction models could explain over 75%of the dynamic of forest fire spreading rate.(4)The mean absolute error and mean relative error of the extrapolation error of additive model were 0.108 m/min and 42.50%,respectively.The extrapolation effect of multiplicative model was better than that of the additive model,with the mean absolute error and relative error of 0.086 m/min and 28.20%,respectively.[Conclusion]This study reveals the influence of fulebed characteristics on the forest fire spreading rate in karst ecosystem.The spreading rate of three coniferous beds is high under the experiment condition,and it is possible to spread and cause disasters.Based on prediction accuracy and extrapolation effect,it is suggested to select multiple model to simulate forest fire spreading rate.These findings provide valuable understandings and insights for forest fire prevention in karst ecosystem.