• Scopus
  • Chinese Science Citation Database (CSCD)
  • A Guide to the Core Journal of China
  • CSTPCD
  • F5000 Frontrunner
  • RCCSE
Advanced search
Chen Minsi, Du Jianhua, Wang Wei, Yu Haichen, Wang Bo, Gu Ze, Liu Xiaodong. Characteristics and potential fire behavior of combustibles in the canopy of Pinus tabuliformis forest in Badaling Forest Farm of Beijing[J]. Journal of Beijing Forestry University, 2022, 44(3): 55-64. DOI: 10.12171/j.1000-1522.20210084
Citation: Chen Minsi, Du Jianhua, Wang Wei, Yu Haichen, Wang Bo, Gu Ze, Liu Xiaodong. Characteristics and potential fire behavior of combustibles in the canopy of Pinus tabuliformis forest in Badaling Forest Farm of Beijing[J]. Journal of Beijing Forestry University, 2022, 44(3): 55-64. DOI: 10.12171/j.1000-1522.20210084

Characteristics and potential fire behavior of combustibles in the canopy of Pinus tabuliformis forest in Badaling Forest Farm of Beijing

More Information
  • Received Date: March 10, 2021
  • Revised Date: March 16, 2021
  • Accepted Date: February 21, 2022
  • Available Online: February 23, 2022
  • Published Date: March 24, 2022
  •   Objective  Canopy fire is a type of high-energy fire which severely damages forest resources. It is difficult to extinguish and threatens the safety of fire fighting personnel. Analyzing the characteristics of canopy combustibles and the occurrence conditions of canopy fires, and simulating potential fire behavior characteristics are of great significance for forest combustibles management and effective prevention and control of canopy fires.
      Method  The study took the Pinus tabuliformis forest in the Beijing Badaling Forest Farm as the research object. Using destructive sampling methods to harvest 18 representative samples of P. tabuliformis, starting from the first living branch height, the canopy of the P. tabuliformis forest was divided from bottom to top with 1 m as a level, those less than 1 m were divided into 1 m level, and investigated the total biomass of combustibles in the canopy according to the diameter of the canopy combustible branches (needles; bough diameter ≥ 0.64 cm; twig diameter < 0.64 cm), which combined the plot area and the average canopy length of the P. tabuliformis forest to calculate the canopy fuel load (CFL) and canopy bulk density (CBD). Based on stand factors, we established a multiple regression model with stand structure parameters (DBH, height of the first living branch, crown length, tree height, crown width); estimated the sample plot based on the canopy fuel load model. Under the conditions of three fine combustibles moisture content (6%, 10%, 14%), the average CBD, combining with the average monthly maximum wind speed and the surface fuel load in the study area, the canopy fire spread rate model of van Wagner and Cruz was used to predict the occurrence of canopy fire in the P. tabuliformis forest, and the Byram model was used to simulate potential fire behavior characteristics (such as the intensity of the fire line and the height of the flame).
      Result  (1) The average canopy fuel load of P. tabuliformis forest was 4.54 t/ha, the CBD was 0.21 kg/m3, and the fuel load distribution was gradually decreasing from bottom to top. The combustibles at the bottom of the canopy (0−1 m) accounted for the largest proportion of the total combustibles in the canopy, which was 54.03%. The boughs distributed at the bottom of the canopy and rapidly decreased layer by layer, and the needles were distributed in a large proportion at each layer. (2)The non-linear model of canopy fuel load based on stand factors had a high degree of fit, in which DBH and height of the first living branch were extremely significantly correlated with CFL (P < 0.01). Under the condition of not destroying the forest, the canopy fuel load of P. tabuliformis forest can be better estimated according to the easy-to-test factor of the forest stand. (3) Under moderate burning conditions, the wind speed was high in spring (March to May), and there was a possibility of continuous canopy fire; under extremely dry and high combustion conditions, the potential fire behavior index of continuous canopy fires from February to May was relatively high. The continuous canopy fire that occurred in April showed the highest potential fire behavior index, with a spreading rate of 46 m/min. The fire line intensity was 8 062 kW/m, and the flame height was 15 m.
      Conclusion  Canopy combustible is an important factor affecting the occurrence of forest fires, and the DBH and the height of first living branch are the main influencing factors of CFL. The measured data of canopy combustibles are directly obtained through destructive sampling, and the constructed canopy fuel load estimation model has high accuracy. Wind speed, CBD and moisture content of fine combustibles are closely related to the occurrence and spread of canopy fires. The forests in the study are prone to high-intensity canopy fires under extreme dry climate conditions. The hidden dangers of canopy fire in the P. tabuliformis forest in spring are greater, high winds and extreme dry climate conditions are prone to high-intensity canopy fires. Through forest tending measures (thinning and pruning), the density of combustibles can be effectively reduced, and the height of live branches can be increased to reduce the probability and harm of canopy fire degree.
  • [1]
    陶长森, 牛树奎, 陈锋, 等. 北京山区主要针叶林潜在火行为及冠层危险指数研究[J]. 北京林业大学学报, 2018, 40(9): 55−62.

    Tao C S, Niu S K, Chen F, et al. Potential fire behavior and canopy hazard index of main coniferous forests in Beijing mountain area[J]. Journal of Beijing Forestry University, 2018, 40(9): 55−62.
    [2]
    杨光, 舒立福, 孙思琦, 等. 我国森林火灾中人员伤亡时空分布特征研究[J]. 灾害学, 2015, 30(2): 21−25. doi: 10.3969/j.issn.1000-811X.2015.02.005

    Yang G, Shu L F, Sun S Q, et al. Temporal-spatial distribution regularities of forest fire casualties in China[J]. Journal of Catastrophology, 2015, 30(2): 21−25. doi: 10.3969/j.issn.1000-811X.2015.02.005
    [3]
    金琳, 刘晓东, 张永福. 森林可燃物调控技术方法研究进展[J]. 林业科学, 2012, 48(2): 155−161. doi: 10.11707/j.1001-7488.20120224

    Jin L, Liu X D, Zhang Y F. A review on the forest fuel treatment and reduction[J]. Scientia Silvae Sinicae, 2012, 48(2): 155−161. doi: 10.11707/j.1001-7488.20120224
    [4]
    牛树奎, 王叁, 贺庆棠, 等. 北京山区主要针叶林可燃物空间连续性研究: 可燃物垂直连续性与树冠火发生[J]. 北京林业大学学报, 2012, 34(3): 1−7.

    Niu S K, Wang S, He Q T, et al. Spatial continuity of fuels in major coniferous forests in Beijing mountainous area: fuel vertical continuity and crown fire occurrence[J]. Journal of Beijing Forestry University, 2012, 34(3): 1−7.
    [5]
    牛树奎, 贺庆棠, 陈锋, 等. 北京山区主要针叶林可燃物空间连续性研究: 可燃物水平连续性与树冠火蔓延[J]. 北京林业大学学报, 2012, 34(4): 1−9.

    Niu S K, He Q T, Chen F, et al. Spatial continuity of fuels in major coniferous forests in Beijing mountainous area: fuel horizontal continuity and crown fire spread[J]. Journal of Beijing Forestry University, 2012, 34(4): 1−9.
    [6]
    Gómez-Vázquez I, Fernandes P M, Arias-Rodil M, et al. Using density management diagrams to assess crown fire potential in Pinus pinaster Ait. stands[J]. Annals of Forest Science, 2014, 71(4): 473−484. doi: 10.1007/s13595-013-0350-4
    [7]
    王成德. 人工林树冠生长模拟及密度控制决策技术研究[D]. 北京: 北京林业大学, 2019.

    Wang C D. Research on crown growth simulation and density control decision-making technology of plantation in the case of Cunninghamia lanceolata and Eucalyptus robusta Smith[D]. Beijing: Beijing Forestry University, 2019.
    [8]
    Cruz M G, Alexander M E. Evaluating the 3-m tree crown spacing guideline for the prevention of crowning wildfires in lodgepole pine forests, Alberta[J]. Forestry Chronicle, 2020, 96(2): 165−173.
    [9]
    陶长森, 牛树奎, 陈羚, 等. 妙峰山林场主要针叶林冠层特征及潜在火行为[J]. 北京林业大学学报, 2018, 40(5): 82−89.

    Tao C S, Niu S K, Chen L, et al. Canopy characteristics and potential crown fire behavior of main coniferous forest in Miaofeng Mountain Forest Farm in Beijing[J]. Journal of Beijing Forestry University, 2018, 40(5): 82−89.
    [10]
    Mitsopoulos I D, Dimitrakopoulos A P. Canopy fuel characteristics and potential crown fire behavior in Aleppo pine (Pinus halepensis Mill. ) forests[J]. Annals of Forest Science, 2007, 64(3): 287−299. doi: 10.1051/forest:2007006
    [11]
    Keane R E, Reinhardt E D, Scott J, et al. Estimating forest canopy bulk density using six indirect methods[J]. Canadian Journal of Forest Research, 2005, 35: 724−739.
    [12]
    Botequim B, Fernandes P M, Borges J G, et al. Improving silvicultural practices for Mediterranean forests through fire behaviour modelling using LiDAR-derived canopy fuel characteristics[J/OL]. International Journal of Wildland Fire, 2019, 28(11): 823[2021−01−15]. https://www.publish.csiro.au/wf/WF19001.
    [13]
    Cortés-Molino Á, Aulló-Maestro I, Fernandez-Luque I, et al. Using ForeStereo and LIDAR data to assess fire and canopy structure-related risks in relict Abies pinsapo Boiss. forests[J/OL]. PeerJ, 2020, 8(2): 10158[2021−01−12]. https://peerj.com/articles/10158/.
    [14]
    Cruz M G, Alexander M E. Evaluating regression model estimates of canopy fuel stratum characteristics in four crown fire-prone fuel types in western North America[J/OL]. International Journal of Wildland Fire, 2012, 21(2): 168[2021−01−19]. https://www.publish.csiro.au/wf/WF10066.
    [15]
    Fernández-Alonso J M, Alberdi I, Álvarez-González J G, et al. Canopy fuel characteristics in relation to crown fire potential in pine stands: analysis, modelling and classification[J]. European Journal of Forest Research, 2013, 132(2): 363−377. doi: 10.1007/s10342-012-0680-z
    [16]
    韩梅, 温鹏, 许惠敏, 等. 北京市十三陵林场油松林地表火行为模拟[J]. 北京林业大学学报, 2018, 40(10): 95−101.

    Han M, Wen P, Xu H M, et al. Simulation of surface fire behavior of Pinus tabuliformis forest in Ming Tombs Forest Farm in Beijing[J]. Journal of Beijing Forestry University, 2018, 40(10): 95−101.
    [17]
    Varner J M, Keyes C. Fuel treatments and fire models: error and correction[J]. Fire Management Today, 2009, 3(69): 47−50.
    [18]
    Molina J R, Rodriguez Y, Silva F, et al. Potential crown fire behavior in Pinus pinea stands following different fuel treatments[J]. Forest Systems, 2011, 20(2): 266−277. doi: 10.5424/fs/2011202-10923
    [19]
    Banerjee T, Heilman W, Goodrick S, et al. Effects of canopy midstory management and fuel moisture on wildfire behavior[J/OL]. Scientific Reports, 2020, 10(1): 17312[2021−02−15]. https://www.nature.com/articles/s41598-020-74338-9.
    [20]
    Mitsopoulos I D, Dimitrakopoulos A P. Estimation of canopy fuel characteristics of Aleppo pine (Pinus halepensis Mill. ) forests in Greece based on common stand parameters[J]. European Journal of Forest Research, 2014, 133(1): 73−79. doi: 10.1007/s10342-013-0740-z
    [21]
    Dimitrakopoulos A P, Mitsopoulos I D, Raptis D I. Nomographs for predicting crown fire initiation in Aleppo pine (Pinus halepensis Mill.) forests[J]. European Journal of Forest Research, 2007, 126(4): 555−561. doi: 10.1007/s10342-007-0176-4
    [22]
    王叁, 牛树奎, 李德, 等. 云南松林可燃物的垂直分布及影响因子[J]. 应用生态学报, 2013, 24(2): 331−337.

    Wang S, Niu S K, Li D, et al. Vertical distribution of fuels in Pinus yunnanensis forest and related affecting factors[J]. Chinese Journal of Applied Ecology, 2013, 24(2): 331−337.
    [23]
    郭利峰, 牛树奎, 阚振国. 北京市八达岭林场不同林型林下可燃物调查分析[J]. 林业调查规划, 2007, 32(2): 134−137. doi: 10.3969/j.issn.1671-3168.2007.02.036

    Guo L F, Niu S K, Kan Z G. Investigation and analysis of combustible materials under different forest types of Badaling Center in Beijing[J]. Forest Inventory and Planning, 2007, 32(2): 134−137. doi: 10.3969/j.issn.1671-3168.2007.02.036
    [24]
    周娅, 陈宇轩, 邹瑞, 等. 北京八达岭不同密度油松土壤团聚体特征研究[J]. 西南林业大学学报, 2016, 36(2): 25−30.

    Zhou Y, Chen Y X, Zou R, et al. Effect of stand density on characteristics of soil aggregates in Pinus tabuliformis plantation in Badaling Area, Beijing[J]. Journal of Southwest Forestry University, 2016, 36(2): 25−30.
    [25]
    王玲, 赵广亮, 周红娟, 等. 八达岭林场不同密度油松人工林枯落物水文效应[J]. 生态环境学报, 2019, 28(9): 1767−1775.

    Wang L, Zhao G L, Zhou H J, et al. Hydrological characteristics of litter in a Pinus tabulaeformis plantation with different densities in Badaling Forest Farm[J]. Ecology and Environmental Sciences, 2019, 28(9): 1767−1775.
    [26]
    郭利峰. 北京八达岭林场人工油松林燃烧性研究[D]. 北京: 北京林业大学, 2007.

    Guo L F. Research on artificial Pinus tabulaeformis forest combustibility of Badaling Forest Center in Beijing[D]. Beijing: Beijing Forestry University, 2007.
    [27]
    Cruz M G, McCaw W L, Anderson W R, et al. Fire behaviour modelling in semi-arid mallee-heath shrublands of southern Australia[J]. Environmental Modelling & Software, 2013, 40: 21−34.
    [28]
    Cruz M G, Alexander M E, Wakimoto R H. Assessing canopy fuel stratum characteristics in crown fire prone fuel types of western North America[J]. International Journal of Wildland Fire, 2003, 12: 39−50. doi: 10.1071/WF02024
    [29]
    李连强. 北京妙峰山林场潜在火行为及森林燃烧性研究[D]. 北京: 北京林业大学, 2019.

    Li L Q. Study on potential fire behavior and forest combustion of Miaofeng Mountain in Beijing[D]. Beijing: Beijing Forestry University, 2019.
    [30]
    Cruz M G, Alexander M E, Wakimoto R H. Development and testing of models for predicting crown fire rate of spread in conifer forest stands[J]. Canadian Journal of Forest Research, 2005, 35(7): 1626−1639. doi: 10.1139/x05-085
    [31]
    陶长森. 北京山区主要针叶林冠层可燃物特征及潜在火行为研究[D]. 北京: 北京林业大学, 2019.

    Tao C S. Characteristics of canopy fuel and potential fire behavior in major coniferous forests in the Mountainous Area, Beijing[D]. Beijing: Beijing Forestry University, 2019.
    [32]
    Cruz M G, Alexander M E, Wakimoto R H. Modeling the ikelihood of crown fire occurrence in conifer forest stands[J]. Forest Science, 2004, 50(5): 640.
    [33]
    Cruz M G, Alexander M E. Modelling the rate of fire spread and uncertainty associated with the onset and propagation of crown fires in conifer forest stands[J/OL]. International Journal of Wildland Fire, 2017, 26(5): 413[2021−01−15]. https://www.publish.csiro.au/wf/WF16218.
    [34]
    Scott J H, Reinhardt E D, Scott J H, et al. Estimating canopy fuels in conifer forests[J]. Fire Management Today, 2002, 4(62): 45−50.
    [35]
    梁瀛, 李吉玫, 赵凤君, 等. 天山中部天山云杉林地表可燃物载量及其影响因素[J]. 林业科学, 2017, 53(12): 153−160. doi: 10.11707/j.1001-7488.20171218

    Liang Y, Li J M, Zhao F J, et al. Surface fuel loads of Tianshan spruce forests in the Central Tianshan Mountains and the impact factors[J]. Scientia Silvae Sinicae, 2017, 53(12): 153−160. doi: 10.11707/j.1001-7488.20171218
    [36]
    Cruz M G, Alexander M E, Fernandes P M, et al. Evaluating the 10% wind speed rule of thumb for estimating a wildfire’s forward rate of spread against an extensive independent set of observations[J]. Environmetal Modelling & Software, 2020, 133(2): 104818.
    [37]
    田晓瑞, 舒立福, 赵凤君, 等. 气候变化对中国森林火险的影响[J]. 林业科学, 2017, 53(7): 159−169. doi: 10.11707/j.1001-7488.20170716

    Tian X R, Shu L F, Zhao F J, et al. Impacts of climate change on forest fire danger in China[J]. Scientia Silvae Sinicae, 2017, 53(7): 159−169. doi: 10.11707/j.1001-7488.20170716
    [38]
    Sieg C, Allen K, Hoffman C, et al. Forest fuelsand predicted fire behavior in the first 5 years after a bark beetle outbreak with and without timber harvest[J]. Forest Health Monitoring, 2016, 12(3): 145−151.
    [39]
    Jain T B, Fried J S, Loreno S M. Simulating the effectiveness of improvement cuts and commercial thinning to enhance fire resistance in west coast dry mixed conifer forests[J]. Forest Science, 2020, 66(2): 157−177. doi: 10.1093/forsci/fxz071
  • Cited by

    Periodical cited type(15)

    1. 李雪,朱宾宾,满秀玲. 温度和水分对寒温带典型森林类型土壤有机碳矿化的影响. 东北林业大学学报. 2025(02): 127-136 .
    2. 王军,满秀玲. 去除凋落物和草毡层对寒温带典型森林土壤活性有机碳的短期影响. 水土保持研究. 2024(01): 168-177 .
    3. 刘巧娟,张之松,满秀玲,高明磊,赵佳龙. 寒温带多年冻土区不同林龄白桦林土壤酶活性动态特征. 东北林业大学学报. 2024(03): 125-131 .
    4. 祝顺万,刘利霞,胡雪凡,代伟,王月容,李芳. 华北落叶松混交林林下植物群落特征对间伐的响应. 森林工程. 2024(03): 47-55 .
    5. 刘贝贝,蔡体久. 大兴安岭北部主要森林类型土壤活性碳组分及碳库稳定性变化特征. 水土保持学报. 2024(06): 203-213 .
    6. 沈健,何宗明,董强,林宇,郜士垒. 滨海防护林土壤CO_2排放和土壤因子对计划火烧的响应. 水土保持学报. 2023(01): 254-261 .
    7. 沈健,何宗明,董强,郜士垒,曹光球,林宇,黄政. 滨海沙地两种防护林土壤呼吸月际动态及影响因素. 应用与环境生物学报. 2023(02): 432-439 .
    8. 王军,满秀玲. 去除凋落物和草毡层对寒温带典型森林土壤氮素的短期影响. 森林工程. 2023(04): 1-9 .
    9. 刘思琪,满秀玲,张頔,徐志鹏. 寒温带4种乔木树种不同径级根系分解及碳氮释放动态. 北京林业大学学报. 2023(07): 36-46 . 本站查看
    10. 沈健,何宗明,董强,林宇,郜士垒. 尾巨桉人工林火烧迹地土壤呼吸组分特征及其与土壤因子的关系. 生态学杂志. 2023(07): 1537-1547 .
    11. 沈健,何宗明,董强,郜士垒,林宇. 轻度火烧对滨海沙地人工林土壤呼吸速率和非生物因子的影响. 植物生态学报. 2023(07): 1032-1042 .
    12. 沈健,何宗明,董强,郜士垒,林宇,石焱. 不同处理方式下湿地松人工林土壤呼吸及温度敏感性变化. 西北林学院学报. 2023(05): 10-18 .
    13. 田慧敏,刘彦春,刘世荣. 暖温带麻栎林凋落物调节土壤碳排放通量对降雨脉冲的响应. 生态学报. 2022(10): 3889-3896 .
    14. 张茹,马秀枝,杜金玲,李长生,梁芝,吴天龙. 模拟增温对大兴安岭兴安落叶松林土壤CO_2通量的影响. 东北林业大学学报. 2022(08): 83-88 .
    15. 张扬,张秋良,李小梅,代海燕,王飞. 兴安落叶松林生长季碳交换对气候变化的响应. 西部林业科学. 2021(05): 73-80+89 .

    Other cited types(4)

Catalog

    Article views (964) PDF downloads (81) Cited by(19)

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return