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基于树木雷达的小兴安岭典型树种粗根分布及其影响因素研究

纪文文 王立海 时小龙 许明贤 郝泉龄 张广晖 孟庆凯 侯胜铭

纪文文, 王立海, 时小龙, 许明贤, 郝泉龄, 张广晖, 孟庆凯, 侯胜铭. 基于树木雷达的小兴安岭典型树种粗根分布及其影响因素研究[J]. 北京林业大学学报, 2020, 42(5): 33-41. doi: 10.12171/j.1000-1522.20190285
引用本文: 纪文文, 王立海, 时小龙, 许明贤, 郝泉龄, 张广晖, 孟庆凯, 侯胜铭. 基于树木雷达的小兴安岭典型树种粗根分布及其影响因素研究[J]. 北京林业大学学报, 2020, 42(5): 33-41. doi: 10.12171/j.1000-1522.20190285
Ji Wenwen, Wang Lihai, Shi Xiaolong, Xu Mingxian, Hao Quanling, Zhang Guanghui, Meng Qingkai, Hou Shengming. Coarse root distribution and its influencing factors of typical species in Lesser Xing’an Range based on tree radar unit[J]. Journal of Beijing Forestry University, 2020, 42(5): 33-41. doi: 10.12171/j.1000-1522.20190285
Citation: Ji Wenwen, Wang Lihai, Shi Xiaolong, Xu Mingxian, Hao Quanling, Zhang Guanghui, Meng Qingkai, Hou Shengming. Coarse root distribution and its influencing factors of typical species in Lesser Xing’an Range based on tree radar unit[J]. Journal of Beijing Forestry University, 2020, 42(5): 33-41. doi: 10.12171/j.1000-1522.20190285

基于树木雷达的小兴安岭典型树种粗根分布及其影响因素研究

doi: 10.12171/j.1000-1522.20190285
基金项目: 国家自然科学基金项目(31570547)
详细信息
    作者简介:

    纪文文。主要研究方向:森林工程。Email:2263498593@qq.com 地址:150040 黑龙江省哈尔滨市和兴路 26 号东北林业大学工程技术学院

    责任作者:

    王立海,博士,教授。主要研究方向:森林工程。Email:lihaiwang@yahoo.com 地址:同上

Coarse root distribution and its influencing factors of typical species in Lesser Xing’an Range based on tree radar unit

  • 摘要: 目的  探究小兴安岭典型树种粗根分布规律及其影响因素,为小兴安岭树木良好生长提供科学依据和数据支撑。 方法  以红松、落叶松、红皮云杉、樟子松为研究对象,在凉水实验林场选取了8个样地进行试验。以样木为圆心,采用树木雷达扫描以0.5、1、1.5、2 m为半径的圆周上的根系,采用环刀法和取土样法测定土壤理化性质,并测量树高、胸径、冠幅等树木因子,分析小兴安岭树木粗根分布状况,并对粗根密度与树木因子及土壤因子指标进行相关性分析。 结果  (1)小兴安岭4个典型树种在水平方向粗根密度随着与树干距离的增加而减少;在垂直方向上,随着土壤深度的增加,红松和落叶松粗根密度逐渐减少,红皮云杉和樟子松粗根密度先增加后减少。红松、落叶松、红皮云杉、樟子松分别有82.1%、82.0%、89.6%、67.6%的粗根分布在0 ~ 40 cm土层深度。(2)树木粗根密度与树高、胸径、冠幅呈显著正相关关系(P < 0.05),与树木平均阻力值无显著相关关系(P > 0.05)。(3)树木粗根密度与土壤含水量、饱和持水量、毛管持水量呈显著正相关关系(P < 0.05),与土壤密度呈显著负相关关系(P < 0.05),与毛管持水量相关程度最高(r = 0.538,P = 0.012)。树木粗根密度与土壤有机质、全氮、全磷、水解氮含量呈显著正相关关系(P < 0.05),与全氮含量相关程度最高(r = 0.646,P = 0.002)。 结论  研究结果表明树木因子和土壤因子均对小兴安岭4个典型树种粗根分布产生不同程度影响,树木粗根分布不仅与自身特性有关,还与其生存环境有关,而与树木材质状况无关。

     

  • 图  1  不同树种粗根分布特征

    不同小写字母表示落叶松、红皮云杉和樟子松之间差异显著(P < 0.05)。Different lowercase letters represent significant differences between Larix gmelinii, Picea koraiensis and Pinus sylvetris at P < 0.05 level.

    Figure  1.  Distribution characteristics of coarse roots for different tree species

    表  1  试验样地及试验样木基本信息

    Table  1.   Basic information of test sample plots and test sample trees

    样地编号
    Sample plot No.
    样地类型
    Sample plot type
    主要树种
    Principal tree species
    树木平均胸径
    Mean DBH of trees/cm
    海拔高度
    Altitude/m
    1 原始林 Virgin forest 红松 Pinus koraiensis 52.58 ± 23.63 398.00
    2 原始林 Virgin forest 红松 Pinus koraiensis 82.64 ± 13.13 404.97
    3 人工林 Plantation 红松 Pinus koraiensis 24.68 ± 2.63 436.00
    4 人工林 Plantation 红松 Pinus koraiensis 28.44 ± 2.90 449.50
    5 人工林 Plantation 落叶松 Larix gmelinii 38.42 ± 5.10 439.50
    6 人工林 Plantation 落叶松 Larix gmelinii 30.42 ± 6.10 443.00
    7 平坦开阔地带 Open flat land 红皮云杉 Picea koraiensis 38.28 ± 4.10 341.20
    8 平坦开阔地带 Open flat land 樟子松 Pinus sylvestris 40.40 ± 7.87 343.60
    下载: 导出CSV

    表  2  土壤化学性质指标测定方法

    Table  2.   Methods for determining soil chemical properties

    土壤化学性质指标
    Soil chemical property index
    测定方法
    Assay method
    中国林业行业标准
    China forestry industry standard
    pH 电位法
    Potentiometry
    LY/T 1237—1999
    全氮 Total nitrogen 凯式定氮法
    Kjeldahl determination
    LY/T 1228—2015
    水解氮 Hydrolyzable nitrogen 碱解扩散法
    Alkaline hydrolysis diffusion
    全钾 Total potassium 酸溶−火焰光度法
    Acid dissolution-flame photometry
    LY/T 1234—2015
    速效钾 Available potassium 乙酸铵浸提−火焰光度法
    Extraction with ammonium acetat-flame photometry
    全磷 Total phosphorus 酸溶−钼锑抗比色法
    Acid dissolution-Mo sb colorimetry method
    LY/T 1232—2015
    有效磷 Available phosphorus 氢氧化钠浸提−钼锑抗比色法
    Extraction with sodium hydroxide-Mo sb colorimetry method
    有机质 Organic matter 油浴重铬酸钾氧化法
    Oil bath heating oxidized by potassium dichromate volumetric method
    LY/T 1237—1999
    下载: 导出CSV

    表  3  人工林和原始林红松平均粗根密度                 根/m

    Table  3.   Average coarse root density of Pinus koraiensis in plantation and primary forests root number/m

    项目 Item扫描半径 Scanning radius/m土壤深度 Soil depth/cm
    0.511.520 ~ 2020 ~ 40 40 ~ 60
    人工林红松 Pinus koraiensis plantation 7.60 7.66 7.355.7813.3710.874.14
    原始林红松 Primary Pinus koraiensis forest12.0410.9610.018.0821.4511.368.28
    下载: 导出CSV

    表  4  不同土层粗根密度与土壤物理性质指标相关性分析

    Table  4.   Correlation analysis of coarse root density and soil physical property indexes in different soil layers

    Pearson相关系数
    Pearson correlation coefficient
    LmLRLBCLMCLFKLMKLZK
    TRD0.526*− 0.438*0.530*0.538*0.3160.1850.291
    RD0 ~ 200.522*− 0.602**0.534*0.524*0.438*− 0.0210.168
    RD20 ~ 40− 0.3370.369− 0.311− 0.315− 0.121− 0.074− 0.114
    RD40 ~ 600.482*− 0.3000.452*0.478*0.0880.3480.332
    RD0 ~ 400.209− 0.2540.2360.2250.285− 0.0670.063
    注:LmLRLBCLMCLFKLMKLZK分别表示土壤含水量、土壤密度、土壤饱和持水量、土壤毛管持水量、非毛管孔隙度、毛管孔隙度、总孔隙度。*表示在0.05水平上显著相关,**表示在0.01水平上显著相关,未标记表示相关性不显著,TRD、RD0 ~ 20、RD20 ~ 40、RD40 ~ 60、RD0 ~ 40分别表示树木总粗根密度、0 ~ 20 cm土层粗根密度值、20 ~ 40 cm土层粗根密度值、40 ~ 60 cm土层深度粗根密度值、0 ~ 40 cm土层粗根密度值。下同。Notes: Lm, LR, LBC, LMC, LFK, LMK, LZK represent soil moisture content, soil density, saturated soil water holding capacity, soil capillary water holding capacity, non-capillary porosity, capillary porosity and total porosity, respectively. * indicates significant correlation at 0.05 level, ** indicates significant correlation at 0.01 level, unmarked one indicates that the correlation is not significant. TRD, RD0 ~ 20, RD20 ~ 40, RD40 ~ 60, RD0 ~ 40 indicate the total coarse root density value of the tree, coarse root density value of 0−20 cm soil layer, coarse root density value of 20−40 cm soil layer, coarse root density value of 40−60 cm soil layer, coarse root density value of 0−40 cm soil layer, respectively. Same as below.
    下载: 导出CSV

    表  5  不同土层粗根密度与土壤理化性质指标逐步回归分析

    Table  5.   Stepwise regression analysis of coarse root density and soil physical and chemical properties in different soil layers

    回归模型 Regression modelR2P
    TRD = 30.816 + 0.053LMC 0.290 0.012
    RD0 ~ 20 = 21.387 − 7.001LR 0.362 0.004
    RD40 ~ 60 = 3.418 + 0.046Lm 0.232 0.027
    TRD = 30.289 + 0.926XTN 0.418 0.002
    RD0 ~ 20 = 11.987 + 0.657XTN 0.378 0.003
    RD20 ~ 40 = 16.186 − 0.01XHN 0.192 0.047
    RD40 ~ 60 = 1.951 + 0.016XHN 0.352 0.005
    注:TN、HN分别表示全氮和水解氮。 Notes: TN, HN represent total nitrogen and hydrolyzable nitrogen, respectively.
    下载: 导出CSV

    表  6  不同土层深度粗根密度与土壤化学性质指标相关性分析

    Table  6.   Correlation analysis of coarse root density and soil chemical property indexes in different soil layers

    Pearson相关系数
    Pearson correlation coefficient
    pH有机质
    Organic
    matter
    全氮
    Total
    nitrogen
    全磷
    Total phosphorus
    全钾
    Total
    potassium
    水解氮
    Hydrolyzable nitrogen
    有效磷
    Available phosphorus
    速效钾
    Available potassium
    TRD− 0.1930.569**0.646**0.525*0.0250.461*0.3730.220
    RD0 ~ 20− 0.558**0.612**0.615*0.341− 0.0610.4110.495*0.145
    RD20 ~ 400.308− 0.409− 0.295− 0.091− 0.001− 0.439*− 0.093− 0.193
    RD40 ~ 600.0530.509*0.518*0.461*0.1020.593*0.0850.323
    RD0 ~ 40− 0.2590.2340.3150.224− 0.0520.0460.351− 0.009
    下载: 导出CSV
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出版历程
  • 收稿日期:  2019-07-07
  • 修回日期:  2019-10-25
  • 网络出版日期:  2020-03-05
  • 刊出日期:  2020-07-01

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