八达岭林场油松林冠层可燃物特征及潜在火行为

陈敏斯; 杜建华; 王薇; 于海晨; 王博; 顾泽; 刘晓东

doi:10.12171/j.1000-1522.20210084

八达岭林场油松林冠层可燃物特征及潜在火行为

陈敏斯^1,,
杜建华²,
王薇²,
于海晨¹,
王博¹,
顾泽¹,
刘晓东^1, ,

1.
北京林业大学生态与自然保护学院，北京 100083
2.
应急管理部森林防火预警监测信息中心，北京 100055

基金项目: 国家自然科学基金项目（31770696）

详细信息

作者简介:
陈敏斯。主要研究方向：森林防火。Email：925913259@qq.com　地址：100083 北京市海淀区清华东路35号北京林业大学生态与自然保护学院

责任作者:
刘晓东，教授。主要研究方向：森林防火。Email：xd-liu@bjfu.edu.cn　地址：同上

中图分类号: S762.1
计量
- 文章访问数: 964
- HTML全文浏览量: 319
- PDF下载量: 82
出版历程
- 收稿日期: 2021-03-10
- 修回日期: 2021-03-16
- 录用日期: 2022-02-21
- 网络出版日期: 2022-02-23
- 发布日期: 2022-03-24

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

1.
School of Nature Conservation, Beijing Forestry University, Beijing 100083, China
2.
Forest Fire Prevention Early Warning and Monitor Center of Ministry of Emergency Management, Beijing 100055, China

摘要

摘要:
目的研究冠层可燃物特征和树冠火发生条件，模拟潜在火行为特征，对于森林可燃物管理及树冠火有效防控均具有重要意义。
方法本文以北京市八达岭林场油松林为研究对象，利用破坏性取样方法，选择具有代表性的18株油松样木进行采伐，自第一活枝高始，以1 m为一个层次对油松林冠层由下而上进行划分，不足1 m的按照1 m层次划分，并按照冠层可燃物枝条径阶大小（针叶；大枝直径 ≥ 0.64 cm；小枝直径 < 0.64 cm）调查冠层总可燃物生物量，结合样地面积和油松林平均冠长，计算样地平均冠层可燃物负荷量（CFL）和冠层容积密度（CBD）。基于林分因子，建立与林分结构参数（胸径、第一活枝高、冠长、树高、冠幅）的多元回归模型；根据冠层可燃物负荷量模型可估算样地平均冠层容积密度，结合研究区防火期内月平均最大风速和地表可燃物负荷量，在3种细小可燃物含水率条件下（6%、10%、14%），利用van Wagner和Cruz的树冠火蔓延模型，预测油松林树冠火的发生，利用Byram模型计算冠层潜在火行为特征（如火线强度和火焰高度）。
结果（1）油松林平均冠层可燃物负荷量为4.54 t/hm²，冠层容积密度为0.21 kg/m³，可燃物负荷量分布呈现由下而上逐层递减的趋势。林冠底层（0 ~ 1 m）可燃物占冠层总可燃物比例最大，为54.03%，大枝在林冠底层分布比例较大且快速逐层递减，针叶在各层次均有较大比例分布。（2）基于林分因子建立的冠层可燃物负荷量非线性模型具有较高的拟合度，其中胸径和第一活枝高与冠层可燃物负荷量呈极显著相关（P < 0.01），在不破坏林木的情况下，根据林分易测因子可较好地估测油松林冠层可燃物负荷量。（3）在低燃烧条件下，除4月份外油松林发生间歇型树冠火的概率均低于0.5；在中度燃烧条件下，春季（3—5月份）风速较大，均存在发生连续型树冠火的可能；在极端干燥的高燃烧条件下，2—5月连续型树冠火的潜在火行为指标较高，4月份发生的连续型树冠火，表现出最高的潜在火行为指标，蔓延速度为46 m/min，火线强度为8 062 kW/m，火焰高度为15 m。
结论冠层可燃物是影响林火发生的重要因素，胸径和第一活枝高为冠层可燃物负荷量的主要影响因子。通过破坏性取样直接获得冠层可燃物实测数据，所构建的冠层可燃物负荷量估测模型具有较高精度。风速、冠层容积密度和细小可燃物含水率与树冠火的发生和蔓延关系密切，油松林春季存在的树冠火发生隐患较大，大风和极端干燥气候条件下易发生高强度树冠火，通过营林抚育措施（抚育间伐，修枝）可有效降低可燃物密度，增大活枝高，以降低树冠火发生概率及危害程度。
- 油松 /
- 冠层可燃物负荷量 /
- 冠层容积密度 /
- 树冠火 /
- 火行为
Abstract:
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.
- Pinus tabuliformis /
- canopy fuel load /
- canopy bulk density /
- crown fire /
- fire behavior

HTML全文

图 1 油松林冠层可燃物负荷量垂直分布特征

Figure 1. Vertical distribution characteristics of canopy fuel load in Pinus tabuliformis forest

下载: 全尺寸图片幻灯片

表 1 油松样木基本情况

Table 1 Basic information of Pinus tabuliformis sample wood

树号 Tree No.	胸径 DBH/cm	地径 Ground diameter/cm	第一活枝高 Height of the first living branch/m	冠长 Crown length/m	树高 Tree height/m	冠幅 Crown width/m
1	7.20	10.50	3.20	3.10	6.30	1.05
2	6.80	9.60	3.40	1.85	5.25	1.90
3	5.40	6.50	3.52	1.30	4.82	1.55
4	6.50	7.10	2.30	2.45	4.75	2.50
5	14.40	18.60	4.70	2.62	7.32	2.95
6	10.40	12.60	5.40	2.75	8.15	1.60
7	8.50	10.40	4.80	1.50	6.30	1.70
8	5.40	6.80	3.20	3.10	6.30	1.35
9	7.80	10.20	3.70	1.20	4.90	1.05
10	8.70	11.60	5.00	2.20	7.20	1.60
11	5.40	8.60	3.30	1.40	4.70	1.45
12	6.70	8.50	5.30	2.70	8.00	1.50
13	8.20	10.60	5.20	2.05	7.25	1.65
14	9.00	10.30	5.20	1.00	6.20	2.00
15	7.10	10.50	3.50	1.40	4.90	2.30
16	8.30	11.40	4.90	2.50	7.40	1.70
17	7.90	10.30	5.30	1.40	6.70	1.65
18	10.00	13.00	4.00	4.00	8.00	2.80
注：表中数据均为实测原始数据。Note: data in the table are the measured original data.

下载: 导出CSV

表 2 油松冠层可燃物分布特征

Table 2 Distribution characteristics of combustibles in Pinus tabuliformis canopy

树号 Tree No.	针叶生物量 Needle biomass/kg	小枝生物量 Twig biomass/kg	大枝生物量 Bough biomass/kg	冠层总生物量 Total canopy biomass/kg	冠层可燃物负荷量 Canopy fuel load/(kg·m⁻²)	冠层容积密度 Canopy bulk density/(kg·m⁻³)
1	0.72	0.45	0.83	2.00	0.50	0.23
2	0.82	0.58	1.27	2.67	0.67	0.31
3	0.20	0.22	0.19	0.61	0.15	0.07
4	1.34	0.67	2.00	4.01	1.00	0.47
5	0.63	1.44	1.77	3.84	0.96	0.45
6	1.53	1.00	2.31	4.84	1.21	0.56
7	0.16	0.29	0.29	0.74	0.19	0.09
8	0.77	0.26	0.00	1.03	0.26	0.12
9	0.15	0.24	0.91	1.30	0.33	0.15
10	1.04	0.43	0.81	2.28	0.57	0.27
11	0.71	0.41	0.63	1.75	0.44	0.20
12	0.41	0.28	0.32	1.01	0.25	0.12
13	0.66	0.33	0.38	1.37	0.34	0.16
14	0.14	0.10	0.30	0.54	0.14	0.06
15	0.23	0.25	0.25	0.73	0.18	0.09
16	0.48	0.34	0.04	0.86	0.22	0.10
17	0.24	0.29	0.11	0.64	0.16	0.07
18	0.70	0.63	1.01	2.44	0.61	0.29

下载: 导出CSV

表 3 油松林冠层总可燃物负荷量估测模型

Table 3 Estimation model of total canopy fuel load in Pinus tabuliformis forest

估测模型 Estimation model	R²	调整R² Adjusted R²	P
Y = −0.27 + 1.41X₁−0.85X₃ + 0.40X₃² + 0.33X₄ + 0.46X₅²−0.58X₆²	0.867 2	0.794 8	0.000 3
注：Y为冠层可燃物负荷量（kg/m²）；X₁为胸径（cm）；X₂为地径（cm）；X₃为第一活枝高（m）；X₄为冠长（m）；X₅为树高（m）；X₆为冠幅（m）。Notes: Y, canopy fuel load (kg/m²); X₁, DBH (cm); X₂, ground diameter (cm); X₃, height of the first living branch (m); X₄, crown length (m); X₅, tree height (m); X₆, crown width (m).

下载: 导出CSV

表 4 不同燃烧条件下每个月油松林树冠火发生概率

Table 4 Occurrence probability of canopy fire in Pinus tabuliformis forest in each month under different combustion conditions %

月份 Month	不同燃烧条件树冠火类型及发生概率 Type and occurrence probability of crown fire under different combustion conditions
	低 Low			中度 Moderate			高 High
	A	P	S	A	P	S	A	P	S
11	−	9	91	−	28	72	22	38	40
12	−	6	94	−	20	80	−	49	51
1	−	3	97	−	9	91	−	28	72
2	−	13	87	−	36	64	24	44	32
3	−	49	51	41	37	22	26	67	7
4	−	52	48	41	39	20	26	68	6
5	−	35	65	38	29	33	26	62	12
注：A.连续型树冠火；P.间歇型树冠火；S.地表火。Notes: A, continuous crown fire; P, intermittent crown fire; S, surface fire.

下载: 导出CSV

表 5 中度燃烧条件下每个月油松林连续型树冠火潜在火行为

Table 5 Potential fire behavior of continuous canopy fire in Pinus tabuliformis forest every month under moderate burning conditions

火行为 Fire behavior	月份 Month
火行为 Fire behavior	11	12	1	2	3	4	5
蔓延速度 Spreading rate/(m·min⁻¹)	−	−	−	−	23	24	22
火线强度 Fire line intensity/(kW·m⁻¹)	−	−	−	−	4 022	4 085	3 742
火焰高度 Flame height/m	−	−	−	−	11	11	10

下载: 导出CSV

表 6 高燃烧条件下每个月油松林连续型树冠火潜在火行为

Table 6 Potential fire behavior of continuous canopy fire in Pinus tabuliformis forest every month under high burning conditions

火行为 Fire behavior	月份 Month
火行为 Fire behavior	11	12	1	2	3	4	5
蔓延速度 Spreading rate/(m·min⁻¹)	33	−	−	35	46	46	43
火线强度 Fire line intensity/(kW·m⁻¹)	5 787	−	−	6 132	7 932	8 062	7 386
火焰高度 Flame height/m	13	−	−	13	15	15	14

下载: 导出CSV

参考文献(39)

[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

施引文献(12)

期刊类型引用(6)

1.	高文于，杨红，邢震，柳文杰，吕庆鑫，顾琪，余应鹏. 外源赤霉素对须弥红豆杉生长生理指标的影响. 四川林业科技. 2024(01): 8-14 . 百度学术
2.	苗婷婷，吴中能，刘俊龙，丁昌俊，曹志华，孙慧，闫彩霞. 7个杨树品种苗期叶片解剖结构和叶绿素荧光特性研究. 中国农学通报. 2024(24): 51-59 . 百度学术
3.	孙晓，李春友，贺红月，单媛媛. ‘107杨’一级枝条基径和长度的动态模拟研究. 林业与生态科学. 2018(04): 364-372 . 百度学术
4.	王兴胜，李斌，陈勇，夏黎，夏诗书，程平，李宏. 不同派系杨树品种(系)光合特性评价. 南方农业学报. 2018(12): 2476-2485 . 百度学术
5.	吴敏，汤玉喜，唐洁，李永进，吴立勋. 杨树苗期光合特征值与无性系产能相关性的探讨. 湖南林业科技. 2016(06): 60-63 . 百度学术
6.	吴敏，汤玉喜，唐洁，李永进，吴立勋. 影响杨树苗期光合速率多因素研究. 湖南林业科技. 2015(06): 94-98 . 百度学术