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长白落叶松人工林林分碳储量生长模型系研究

何潇 周超凡 雷相东 李海奎

何潇, 周超凡, 雷相东, 李海奎. 长白落叶松人工林林分碳储量生长模型系研究[J]. 北京林业大学学报, 2021, 43(11): 1-10. doi: 10.12171/j.1000-1522.20210040
引用本文: 何潇, 周超凡, 雷相东, 李海奎. 长白落叶松人工林林分碳储量生长模型系研究[J]. 北京林业大学学报, 2021, 43(11): 1-10. doi: 10.12171/j.1000-1522.20210040
He Xiao, Zhou Chaofan, Lei Xiangdong, Li Haikui. Stand carbon stock growth model system for Larix olgensis plantation[J]. Journal of Beijing Forestry University, 2021, 43(11): 1-10. doi: 10.12171/j.1000-1522.20210040
Citation: He Xiao, Zhou Chaofan, Lei Xiangdong, Li Haikui. Stand carbon stock growth model system for Larix olgensis plantation[J]. Journal of Beijing Forestry University, 2021, 43(11): 1-10. doi: 10.12171/j.1000-1522.20210040

长白落叶松人工林林分碳储量生长模型系研究

doi: 10.12171/j.1000-1522.20210040
基金项目: 国家自然科学基金项目(31870623),林业公益性行业科研专项(201504303)
详细信息
    作者简介:

    何潇,博士生。主要研究方向:森林生长模型。Email:hexiaonuist@163.com 地址:100091 北京市海淀区东小府 1 号中国林业科学研究院资源信息研究所

    责任作者:

    雷相东,研究员,博士生导师。主要研究方向:森林生长模型与模拟。Email:xdlei@ifrit.ac.cn 地址:同上

  • 中图分类号: S791.22

Stand carbon stock growth model system for Larix olgensis plantation

  • 摘要:   目的  目前关于林分碳储量随年龄动态变化的模型研究较少,本研究通过建立林分水平的碳储量生长模型系,为区域尺度的森林碳储量动态预估提供方法。  方法  以吉林省长白落叶松人工林为对象,使用立地质量分级算法将所有样地划分为3个立地等级,并将其作为哑变量引入模型系中,使用联立方程组的方法将林分平均高、断面积生长模型和林分碳储量模型3个方程进行联合估计,建立林分碳储量生长模型系。采用调整确定系数($ {{R}}_{{\text{adj}}}^2 $)、估计值的标准误(SEE)和平均预估误差(MPE)来评价模型的表现,分析不同立地等级和林分密度指数(SDI)下林分碳储量的生长过程,及林分断面积和平均高对林分碳储量的影响。  结果  (1)林分碳储量生长模型系中林分平均高生长模型、林分断面积生长模型和林分碳储量模型的$ {{R}}_{{\text{adj}}}^2 $分别为0.879、0.977和0.953,MPE均 < 2%,具有较好的拟合优度。(2)直接利用林分平均高和断面积或由生长模型得到林分平均高和断面积的这两种途径都可以准确估计林分碳储量,结果仅相差0.02 t/hm2,模型系具有良好的通用性与稳定性。(3)林分碳储量生长量随立地质量的提高而增加;立地等级相同时,SDI < 1 500株/hm2时生长较慢,SDI > 1 500株/hm2时,在40年以后的林分密度对碳储量生长过程基本无影响;林分密度指数控制在1 500 ~ 2 000株/hm2时可实现较快的碳储量生长。(4)林分碳储量随林分断面积和平均高的增加而增加,林分断面积与林分碳储量的关系更为密切。  结论  林分碳储量的生长和立地等级、林分平均年龄、密度、断面积、平均高等因子有密切联系,采用联立方程组方法是建立林分碳储量生长模型系的有效方法。本研究建立的林分碳储量生长模型系可以对林分碳储量动态进行有效预测,为了解林分碳储量的生长过程和森林碳汇评估提供了工具。

     

  • 图  1  吉林省落叶松人工林样地分布图

    Figure  1.  Distribution of sample plots of larch plantation in Jilin Province

    图  2  林分碳储量生长过程

    Figure  2.  Growth process of stand carbon stock

    图  3  林分碳储量与林分断面积、平均高的关系

    Figure  3.  Relationship between stand carbon stock andstand basal area as well as average height

    表  1  林分因子概况(n = 150)

    Table  1.   Summary statistics of stand variables (n = 150)

    变量 Variable平均值 Mean最小值 Min.最大值 Max.标准差 SD
    林分平均高 Stand average height (H)/m 13.2 5.0 22.0 3.8
    林分公顷断面积/(m2·hm−2) Stand basal area (Ba)/(m2·ha−1) 13.41 3.67 27.97 6.28
    林分公顷蓄积/(m3·hm−2) Stand volume (V)/(m3·ha−1) 90.75 16.92 229.78 49.97
    平均胸径 Average DBH (Dg)/cm 13.6 6.7 26.1 3.8
    林分碳储量/(t·hm−2) Stand carbon stock (C)/(t·ha−1) 37.64 8.11 91.79 19.80
    林分密度指数/(株·hm−2) Stand density index (SDI)/(tree·ha−1) 494 159 1 086 212
    林分平均年龄/a Stand average age (A)/year 30 11 50 10
    下载: 导出CSV

    表  2  不同立地等级的林分平均高生长模型结果

    Table  2.   Results of stand average height growth model with different site grades

    模型 Model参数值 Parameter标准差 SD$ {{R}}_{{\text{adj}}}^2 $SEE/mMPE/%
    $ {{\hat H}} = {a_{}}{\left[ {1 - \exp\left( -\left(\displaystyle\sum {{b_i} \cdot {\text{SIT}}{{\text{E}}_i}} \right){A}\right)} \right]^{{\text{ }}c}} $ (i = 1, 2, 3)a = 27.2473.8000.8891.2611.547
    b1 = 0.0270.011
    b2 = 0.0190.007
    b3 = 0.0120.004
    c = 0.7890.107
    下载: 导出CSV

    表  3  划分立地等级后的样地林分因子概况

    Table  3.   A summary of stand factor characteristics after site classification

    林分因子 Stand factor立地等级 Site grade样地数 Sample plot number平均值 Mean最小值 Min.最大值 Max.标准差 SD F
    H 1 38 16.7a 11.0 22.0 2.9 55.652
    2 70 13.2b 7.0 19.0 3.0
    3 42 9.9c 5.0 15.0 2.5
    Ba 1 38 16.58a 6.22 27.09 4.96 17.547
    2 70 14.16b 3.79 27.97 6.61
    3 42 9.29c 3.67 19.90 4.45
    C 1 38 48.53a 15.90 87.69 16.96 19.417
    2 70 39.69b 9.29 91.79 20.39
    3 42 24.36c 8.11 54.95 12.95
    注:H、Ba、C的单位分别为m、m2/hm2、t/hm2。不同小写字母表示各林分因子在不同立地等级下的差异显著(P < 0.05)。Notes: the units of H, Ba, C are m, m2/ha, t/ha, respectively. Different lowercase letters indicate significant differences for varied stand factors under different site grades (P < 0.05).
    下载: 导出CSV

    表  4  林分碳储量生长模型式(1)的结果

    Table  4.   Results of growth model equation (1) of stand carbon stock

    模型 Model参数值 Parameter value标准差 SD$ {{R}}_{{\text{adj}}}^2 $SEE/(t·hm−2) SEE/(t·ha−1)MPE/%
    ${{\hat C}} = \left( {\displaystyle\sum {{a_i} \cdot {\rm{SIT}}{{\rm{E}}_i}} } \right){\left[ {1 - \exp ( - {b_1}{{\left( {\dfrac{{{\rm{SDI}}}}{{1\;000}}} \right)}^{{b_2}}} \cdot {{A}})} \right]^{{\rm{ }}c}}(i = 1, 2, 3) $a1 = 155.89345.1930.9623.8761.662
    a2 = 145.70841.691
    a3 = 120.91934.778
    b1 = 0.012 ns0.008
    b2 = 1.230.109
    c = 0.5610.038
    注:ns表示模型参数在0.05水平不显著。Note: ns indicates that parameters of the model are not significant at 0.05 level.
    下载: 导出CSV

    表  5  独立林分断面积生长模型结果

    Table  5.   Growth model results of independent stand basal area

    模型 Model参数值 Parameter value标准差 SD$ {{R}}_{{\text{adj}}}^2 $SEE/(m2·hm−2) SEE/(m2·ha−1)MPE/%
    $ \widehat {{\text{Ba}}} = {a_{}}{\left[ {1 - \exp\left( - {b_1}{{\left(\dfrac{{{\text{SDI}}}}{{1\;000}}\right)}^{{b_2}}} \cdot {{A}}\right)} \right]^{{\text{ }}c}} $a = 32.3402.2320.9790.9111.097
    b1 = 0.0230.007
    b2 = 3.8880.268
    c = 0.2750.019
    下载: 导出CSV

    表  6  林分碳储量生长模型系的参数估计与刀切法验证结果

    Table  6.   Parameter estimation on growth model system of stand carbon stock and validation results by jackknife method

    模型 Model参数 Parameter平均值 Mean最小值 Min.最大值 Max.标准差 SD${{R} }_{ {\text{adj} } }^2 $SEEMPE/%
    林分平均高生长模型
    Stand average height growth model (4-1)
    a1 29.010 26.866 31.869 0.491 0.889 1.261 1.548
    b11 0.022 0.017 0.028 0.001
    b12 0.016 0.013 0.020 0.001
    b13 0.009 0.007 0.012 0.000
    c1 0.747 0.716 0.820 0.010
    林分断面积生长模型
    Stand basal area growth model (4-2)
    a2 32.171 31.051 34.333 0.286 0.979 0.912 1.097
    b21 0.023 0.017 0.027 0.001
    b22 3.863 3.791 3.948 0.023
    c2 0.275 0.267 0.281 0.002
    林分碳储量模型
    Stand carbon stock model (4-3)
    d1 4.867 4.762 5.028 0.026 0.957 4.108 1.762
    d2 10.124 9.593 10.972 0.134
    注:模型4-1、4-2、4-3的SEE单位分别为m、m2/hm2、t/hm2。Notes: the SEE units of model 4-1, 4-2 and 4-3 are m, m2/ha and t/ha, respectively.
    下载: 导出CSV

    表  7  2种林分碳储量生长模型系林分碳储量估计途径的结果

    Table  7.   Estimation results of stand carbon stock by different methods using stand carbon stock growth model system

    龄组 Age group途径1/(t·hm−2) Method 1/(t·ha−1)途径2/(t·hm−2) Method 2/(t·ha−1)相对差异 Relative difference/%
    幼龄林 Young stand 25.93 26.32 1.51
    中龄林 Middle-aged stand 32.84 32.46 −1.17
    近熟林 Near-mature stand 44.43 44.19 −0.54
    成熟林 Mature stand 53.00 53.89 1.67
    总体 Total 37.51 37.53 0.07
    注:建模样本中没有过熟林。Note: there are no over-mature stand in modeling samples.
    下载: 导出CSV
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出版历程
  • 收稿日期:  2021-02-05
  • 修回日期:  2021-04-20
  • 网络出版日期:  2021-10-20
  • 刊出日期:  2021-11-30

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