大兴安岭天然次生林林木补植空间优化

王涛; 董灵波; 刘兆刚; 张凌宇; 陈莹

doi:10.13332/j.1000-1522.20190025

大兴安岭天然次生林林木补植空间优化

王涛^1,,
董灵波^1,2,
刘兆刚^1,2, ,,
张凌宇¹,
陈莹¹

1.
东北林业大大学林学院，黑龙江省哈尔滨 150040
2.
东北林业大学森林生态系统可持续经营教育部重点实验室，黑龙江省哈尔滨 150040

基金项目: 国家重点研发计划项目（2017YFC0504103）,黑龙江省森林可持续经营试验示范区建设项目（201522-2）

详细信息

作者简介:
王涛。主要研究方向：森林可持续经营。Email：376557961@qq.com　地址：150040 黑龙江省哈尔滨市香坊区和兴路26号东北林业大学林学院

责任作者:
刘兆刚，博士，教授。主要研究方向：森林可持续经营。Email：lzg19700602@163.com　地址：同上

中图分类号: S725.71
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出版历程
- 收稿日期: 2019-01-14
- 修回日期: 2019-03-03
- 网络出版日期: 2019-05-07
- 发布日期: 2019-04-30

Optimization of replanting space of natural secondary forest in Daxing’anling Mountains of northeastern China

1.
School of Forestry, Northeast Forestry University, Harbin 150040, Heilongjiang, China
2.
Key Laboratory of Sustainable Forest Ecosystem Management of Ministry of Education, Northeast Forestry University, Harbin 150040, Heilongjiang, China

摘要

摘要:
目的为优化林分空间结构，提高现有林分质量，加速森林生态系统恢复，加速大兴安岭地区森林群落向顶级群落演替，确定天然次生林林下补植树种和补植位置，为大兴安岭地区的森林经营提供理论支持和方法。
方法本文以大兴安岭地区白桦纯林、落叶松白桦混交及针叶混交3种典型的林分类型为例，在次生林原有天然更新的基础上，利用Voronoi图进行空间单元确定和Voronoi结点边缘校正，并使用反距离插值使林木空间结构参数可视化，预测林分中未含林木区域的空间结构信息，将其作为补植依据，使用熵权法确定各空间结构参数权重，将各空间结构参数插值后图像进行加权叠加，以林分非空间结构为约束条件，优化林分空间结构为目标，探讨次生林林下补植树种和位置。
结果（1）选取兴安落叶松为补植树种，各林型幼树补植数量分别为660、1 970、315。（2）补植后白桦纯林样地中白桦幼树幼苗混交度增加为0.52，其他树种幼树幼苗混交度增加为0.51；落叶松白桦混交林中白桦幼树幼苗混交度增加为0.84，其他树种幼树幼苗混交度增加为0.70；针叶混交林中白桦幼树幼苗增加为0.78，其他树种幼树幼苗混交度增加为0.50。（3）补植后各林型样地林下幼树幼苗Voronoi图多边形边数标准差分别为1.31、1.41、1.36，均处于随机分布状态。白桦纯林、落叶松白桦混交林及针叶混交林中落叶松幼树幼苗Voronoi图多边形边数标准差分别为1.27、1.40、1.37，均呈随机分布。
结论采伐和补植是两种相反的空间优化方式，将林木空间结构参数进行反距离插值，可以预测林分中无林木区域的空间结构参数值，插值后的图像像元大小可以设定为补植幼树所需要的林地面积大小，依据林分空间结构的优化目标和补植数量的调控目标，提取样地未含林木区域空间参数值，进而确定补植的树种和位置。
- 天然次生林 /
- 生态恢复 /
- 林下补植 /
- 空间结构优化
Abstract:
ObjectiveThis paper aims to optimize the spatial structure of stand, improve the quality of existing stands, accelerate the restoration of forest ecosystems, accelerate the succession of forest communities to top communities in the Daxing’anling Mountains of northeastern China, and determine the replanting species and replanting sites of natural secondary forests.
MethodTaking three typical forest types of birch, birch-larch mixed forest and larch coniferous mixed forest in the Daxing’anling area as an example, based on the natural regeneration of the secondary forest, the Voronoi diagram was used to determine the spatial unit and correct the edge by Voronoi nodal. The inverse distance weighted method was used to visualize the spatial structure parameters of the forest, and the spatial structure information of the forest area was not included in the forest stand and it was used as the basis for replanting. The entropy method was used to determine the weight of each spatial structure parameter, and the image interpolated by spatial structure parameters was weighted superimposed. With the non-spatial structure as the constraint and the optimization of the stand structure, we discussed the species and location of replanting trees under canopy of secondary forest, and provide theoretical support and methods for forest management in the Daxing'anling Mountains.
Result(1) Larix gmelinii was selected as replanting tree species. The number of replanting trees of each forest type was 660, 1 970, 315, respectively. (2) After the replanting, the mingling degree of birch seedings and saplings in the pure birch forest increased to 0.52, and that of other tree species seedings and saplings increased to 0.51. The mingling degree of birch seedings and saplings in larch and birch mixed forest increased to 0.84, and that of other tree species seedings and saplings increased to 0.70; the mingling degree of birch species seedings and saplings in larch mixed coniferous forest increased to 0.78, and the mingling degree of other tree species seedings and saplings increased to 0.50. (3) After replanting, the coefficients of variation of the Voronoi diagram polygons of forest seedings and saplings under canopy of each forest type were 1.31, 1.41, 1.36, and they were all in random distribution state. The variation coefficient of the Voronoi diagram polygon of larch tree seedings and saplings in the pure birch forest, larch and birch mixed forest and larch mixed coniferous forest was 1.27, 1.40 and 1.37, respectively, they were also all in random distribution state.
ConclusionHarvesting and replanting are two opposite spatial optimization methods. The inverse distance weight of the spatial structure parameters of trees can predict the spatial structure parameters of non-forest areas in forests. The interpolated image pixel size can be set to the forest area for replanting trees. According to the optimization goal of stand spatial structure and the regulation goal of replanting quantity, extracting the spatial structure parameter value of forest area that does not contain tree, we can determine the species and location of the replanted forest under the canopy.
- natural secondary forest /
- ecological restoration /
- replanting under the forest /
- spatial structure optimization

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图 1 Voronoi结构单元

1081、1082等数字代表单株林木编号。The number of 1081, 1082, etc. in the figure represent individual forest No.

Figure 1. Voronoi structural unit

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图 2 落叶松白桦混交林空间结构参数反距离插值

Figure 2. Spatial structure parameter IDW of mixed forest of Larix gmelinii and Betula platyphylla

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图 3 V-Heygi指数像元邻域窗口

Figure 3. Pixel neighborhood window of V-Heygi index

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图 4 V-M_i像元邻域窗口

Figure 4. Pixel neighborhood window of V-M_i

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图 5 V-U_i像元邻域窗口

Figure 5. Pixel neighborhood window of V-U_i

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图 6 V-W_i像元邻域窗口

Figure 6. Pixel neighborhood window of V-W_i

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图 7 各林型补植区域与补植位置

Figure 7. Replanting area and replanting position of each forest type

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图 8 补植前后空间结构参数值比较

Ⅰ为白桦，Ⅱ为落叶松，Ⅲ为其他树种，Ⅳ林分空间结构参数，样地中白桦和落叶松以外的树种记为其他树种。Ⅰ is Betula platyphylla, Ⅱ is Larix gmelinii, Ⅲ is other tree species, and Ⅳ is the spatial structure parameters of forest stand. The tree species except Betula platyphylla and Larix gmelinii in the sample plot are recorded as other tree species.

Figure 8. Comparison of spatial structure parameter values before and after replanting

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表 1 各林型样地基本信息表

Table 1 Basic information of sample plots in each forest type

林型 Forest type	树种组成 Species composition	海拔 Elevation/m	郁闭度 Canopy density	坡度 Slope gradient/(°)	土壤类型 Soil type	平均胸径 Mean DBH/cm	平均高 Mean height/m
白桦纯林 Betula platyphylla forest	10白桦Betula platyphylla	566	0.5	< 5	暗棕壤 Dark brown soil	12.5 ± 4.2	13.3 ± 3.4
落叶松白桦混交林 Larix gmelinii and Betula platyphylla mixed forest	6落叶松Larix gmelinii 4白桦Betula platyphylla	546	0.7	< 5	暗棕壤 Dark brown soil	13.1 ± 4.7	13.7 ± 3.5
针叶混交林 Larch coniferous mixed forest	6落叶松Larix gmelinii 2樟子松Pinus sylvestris var. mongolica 1云杉Picea abies 1白桦Betula platyphylla	457	0.6	6	暗棕壤 Dark brown soil	10.5 ± 4.4	11.2 ± 2.9

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表 2 各林型样地幼苗幼树信息统计表

Table 2 Statistical table of seedlings and saplings in sample plot of each forest type

林分类型 Forest type	树种 Species	幼苗 Seedling (H ≤ 30.0 cm)			幼树 Sapling (30.0 cm < H & DBH < 5.0 cm)
林分类型 Forest type	树种 Species	地径 Ground diameter/cm	树高 Tree height/cm	密度/(株·hm²) Density/(plant·ha^{− 1})	地径 Ground diameter/cm	树高 Tree height/cm	密度/(株·hm²) Density/(plant·ha^{− 1})
白桦纯林 Betula platyphylla forest	白桦 Betula platyphylla	0.7	19.3	63	1.5	185.1	802
	落叶松 Larix gmelinii	0.3	24.0	1	2.3	212.6	221
	山杨 Populus davidiana				1.8	199.5	1 317
落叶松白桦混交林 Larix gmelinii and Betula platyphylla mixed forest	白桦 Betula platyphylla	0.3	22.1	9	1.5	172.8	142
	落叶松 Larix gmelinii	0.3	16.8	4	2.3	210.0	129
	山杨 Populus davidiana	0.6	20.5	2	1.3	151.2	759
	落叶松 Larix gmelinii	0.6	22.1	12	3.2	274.6	1 013
	云杉 Picea asperata	0.3	15.4	546	1.8	117.6	975
针叶混交林 Larch coniferous mixed forest	白桦 Betula platyphylla	0.2	19.5	6	1.8	295.3	375
	樟子松 Pinus sylvestris var. mongolica	1.1	16.5	49	1.6	157.3	141
	山杨 Populus davidiana	4.1	7.0	2	1.8	234.0	59
	柳树 Salix matsudana	0.3	23.5	2	1.1	123.7	119
	柞树 Quercus mongolica	0.2	14.5	22	0.5	35.0	3

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表 3 空间结构参数计算公式及变量定义

Table 3 Calculation formula of spatial structure parameters and its significance

空间结构参数 Spatial structure parameter	计算公式 Formula	变量定义 Variable definition
V-Hegyi指数 V-Hegyi index	$\scriptstyle {{\rm{CI}}_i = \sum\limits_{j = 1}^n {\frac{{d_j}}{{d_i L_{ij}}}} }$	L_ij为对象木i与竞争木j之间的距离；d_i为对象木i的胸径；d_j为竞争木j的胸径；n为竞争木株数。L_ij is the distance between the object tree i and the competition tree j; d_i is the DBH of the object tree i; d_jis the DBH of the competition tree j; n is the number of competing trees
V-混交度 V-M_i	$\scriptstyle {M_i = \frac{1}{n}\sum\limits_{j = 1}^n {v_{ij}} }$	n为邻近木株数；当参照树i与相邻木j非同种时v_ij = 1；否则v_ij = 0。n is the number of adjacent trees; v_ij = 1 when the reference tree i is not the same as the adjacent tree j; otherwise v_ij = 0
V-大小比 V-U_i	$\scriptstyle {U_i = \frac{1}{n}\sum\limits_{j = 1}^n {k_{ij}} }$	n为邻近木株数；当参照树j的胸径小于中心木 i的胸径，k_ij = 1；否则k_ij = 0。n is the number of adjacent trees; when the DBH of the reference tree j is smaller than the DBH of the central tree i, k_ij = 1; otherwise k_ij = 0
分布格局 Spatial pattern	SD = [1.264, 1.402]	SD为Voronoi图多边形边数的标准差，当SD = [1.264, 1.402]，林分呈随机分布；当SD < 1.264时，林分呈均匀分布；当SD > 1.402时，林分呈聚集分布。SD is the coefficient of variation of the number of polygons in the Voronoi diagram. When SD = [1.264, 1.402], the stands are randomly distributed; when SD < 1.264, the stands are evenly distributed; when SD > 1.402, the stands are aggregated distributed

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表 5 各林型空间结构参数与补植幼树信息表

Table 5 Spatial structure parameters and replanting sapling information table for each forest type

林分类型 Forest type	林分空间结构参数 Forest spatial structure index				补植幼树 Replanting sapling
林分类型 Forest type	V-Hegyi指数 V-Heygi index	V-混交度 V-M_i	V-大小比 V-U_i	分布格局 Spatial pattern	树种 Species	株数 Tree number
白桦纯林 Betula platyphylla forest	2.58	0.14	0.50	随机 Random	兴安落叶松 Larix gmelinii	660
落叶松白桦混交林 Larix gmelinii and Betula platyphylla mixed forest	3.13	0.41	0.50	随机 Random	兴安落叶松 Larix gmelinii	1 970
针叶混交林 Larch coniferous mixed forest	3.96	0.40	0.50	聚集 Aggregation	兴安落叶松 Larix gmelinii	315

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表 4 空间结构参数分级表

Table 4 Classification table of spatial structure parameters

等级 Grade	V-Hegyi指数 V-Hegyi index		V-混交度 V-M_i		V-大小比 V-U_i
等级 Grade	取值区间 Value range	状态描述 State description	取值区间 Value range	状态描述 State description	取值区间 Value range	状态描述 State description
Ⅰ	(0.00, 2.50]	极弱度竞争 Extremely weak competition	0.00	零度混交 Zero mixture	0.00	优势 Dominant
Ⅱ	(2.50, 5.00]	弱度竞争 Weak competition	(0.00, 0.25]	弱度混交 Weak mixture	(0.00, 0.25]	亚优势 Subdominant
Ⅲ	(5.00, 7.50]	中度竞争 Medium competition	(0.25, 0.50]	中度混交 Medium mixture	(0.25, 0.50]	中庸 Medium
Ⅳ	(7.50, 10.00]	强度竞争 Intensive competition	(0.50, 0.75]	强度混交 Intensive mixture	(0.50, 0.75]	劣势 Inferior
Ⅴ	(> 10.00)	极强度竞争 Extremely intensive competition	(0.75, 1.00]	极强度混交 Extremely intensive mixture	(0.75, 1.00]	绝对劣势 Absolute inferior

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