庐山常绿阔叶林不同生长阶段林木空间结构特征及其评价

余枭; 欧阳勋志; 潘萍; 邓文平; 彭松立; 臧颢; 胡茸茸

doi:10.12171/j.1000-1522.20210450

庐山常绿阔叶林不同生长阶段林木空间结构特征及其评价

余枭^1,,
欧阳勋志^{1, 2},
潘萍^{1, 2, ,},
邓文平^{1, 2},
彭松立³,
臧颢¹,
胡茸茸¹

1.
鄱阳湖流域森林生态系统保护与修复国家林业和草原局重点实验室，江西农业大学林学院，江西南昌 330045
2.
江西庐山森林生态系统国家定位观测研究站，江西九江 332900
3.
江西庐山国家级自然保护区管理局，江西九江 332000

基金项目: 国家自然科学基金项目（31760207、31360181），林业公益性行业科研专项（201504301）

详细信息

作者简介:
余枭。主要研究方向：森林资源管理与监测。Email：15770526896@163.com　地址：330045 江西省南昌市昌北经济技术开发区志敏大道1101号

责任作者:
潘萍，博士，讲师。主要研究方向：森林资源管理与监测和森林生态。Email：panping0306@163.com　地址：同上

中图分类号: S759.9
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出版历程
- 收稿日期: 2021-11-09
- 修回日期: 2022-01-19
- 录用日期: 2022-07-28
- 网络出版日期: 2022-07-31
- 发布日期: 2023-12-24

Spatial structure characteristics and its evaluation of evergreen broadleaved forest at different growth stages in Lushan Mountain, Jiangxi Province of eastern China

Yu Xiao^1,,
Ouyang Xunzhi^{1, 2},
Pan Ping^{1, 2, ,},
Deng Wenping^{1, 2},
Peng Songli³,
Zang Hao¹,
Hu Rongrong¹

1.
Key Laboratory of National Forestry and Grassland Administration for the Protection and Restoration of Forest Ecosystem in Poyang Lake Basin, College of Forestry, Jiangxi Agricultural University, Nanchang 330045, Jiangxi, China
2.
Lushan National Observation and Research Station of Chinese Forest Ecosystem, Jiujiang 332900, Jiangxi, China
3.
Jiangxi Lushan National Nature Reserve Administration, Jiujiang 332000, Jiangxi, China

摘要

摘要:
目的分析林木不同生长阶段的空间结构特征有利于认识林分更新及其稳定性，为优化林分空间结构及自然植被恢复等提供参考依据。
方法以庐山常绿阔叶林为研究对象，将林木生长划分为幼树（1 cm ≤ DBH < 5 cm）、小树（5 cm ≤ DBH < 10 cm）、中树（10 cm ≤ DBH < 20 cm）和大树（DBH ≥ 20 cm）4个阶段，选用混交度、大小比数、密集度、角尺度4种空间结构参数构建空间结构综合指数，采用熵权法进行权重赋值。
结果（1）幼树、小树、中树、大树的株数占林分总株数的比例分别为72.7%、16.8%、6.5%和4.0%，林分径级结构整体上呈倒“J”型。（2）幼树、小树、中树、大树的平均混交度分别为0.609、0.746、0.815和0.822，平均大小比数分别为0.545、0.268、0.132和0.089，平均密集度分别为0.852、0.895、0.871和0.842，平均角尺度分别为0.576、0.563、0.553和0.507；随着径级的增大，林木的混交、生长优势程度不断增大，密集程度先增大后减小，分布格局逐渐由聚集分布转变为随机分布。（3）小树、中树、大树的大小比数的权重均超过75.0%，优化其空间结构主要应调控其林木分化程度；幼树混交度和大小比数的权重分别为0.364和0.388，优化其空间结构则主要调控林木混交程度及分化程度。空间结构综合指数为大树（0.054） < 中树（0.082） < 小树（0.117） < 幼树（0.265）。
结论庐山常绿阔叶林中林木随着径级的增大其空间结构逐步得到改善，大树的空间结构最好，幼树的空间结构最差；针对不同生长阶段林木空间结构特征，可以采取不同的经营措施以优化其空间结构。
- 常绿阔叶林 /
- 空间结构 /
- 生长阶段 /
- 庐山
Abstract:
Objective The analysis of stand spatial structure at different growth stages is conductive to understanding stand regeneration and stability, which can provide reference for optimizing stand spatial structure and natural vegetation restoration.
Method In the study, the evergreen broadleaved forest in Lushan Mountain, Jiangxi Province of eastern China was taken as the research object. The tree growth was divided into four stages: sapling (1 cm ≤ DBH < 5 cm), small tree (5 cm ≤ DBH < 10 cm), middle tree (10 cm ≤ DBH < 20 cm) and large tree (DBH ≥ 20 cm). The comprehensive index of spatial structure was constructed by four kinds of spatial structure parameters: mingling, neighborhood comparison, crowding degree and uniform angle index. The weight was assigned by entropy weight method.
Result (1) The proportions of sapling, small tree, medium tree and large tree were 72.7%, 16.8%, 6.5% and 4.0%, respectively. The diameter class structure of the stand was generally inverse ‘J’ type. (2) The average mingling of sapling, small tree, middle tree and large tree were 0.609, 0.746, 0.815 and 0.822, respectively. The average neighborhood comparison of them was 0.545, 0.268, 0.132 and 0.089, respectively. The average crowding degree of them was 0.852, 0.895, 0.871 and 0.842, respectively. The average uniform angle index of them was 0.576, 0.563, 0.553 and 0.507, respectively. With the increase of diameter class, the degree of mingling and growth dominance of trees increased, and the density of trees first increased and then decreased. The distribution pattern gradually changed from aggregation distribution to random distribution. (3) The weight of neighborhood comparison of small tree, medium tree and large tree was more than 75.0%. The way of optimizing spatial structure should mainly regulate the degree of forest differentiation. The weight of mingling and neighborhood comparison of sapling were 0.364 and 0.388, respectively. To optimize its spatial structure, the degree of forest mingling and differentiation should be mainly controlled simultaneously. The comprehensive index of spatial structure was large tree (0.054) < middle tree (0.082) < small tree (0.117) < sapling (0.265).
Conclusion The spatial structure of evergreen broadleaved forest in Lushan Mountain was gradually improved with the increase of diameter class. The best spatial structure was the large tree and the worst was the sapling. According to the spatial structure characteristics of trees at different growth stages, different forest management measures can be taken to optimize the spatial structure.
- evergreen broadleaved forest /
- spatial structure /
- growth stage /
- Lushan Mountain

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图 1 林分直径分布特征

Figure 1. Distribution characteristics of stand diameter

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图 2 不同生长阶段空间结构参数的频率分布

Figure 2. Frequency distribution of spatial structure parameters in different growth stages

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表 1 样地基本概况

Table 1 Basic situation of sample plots

样地号 Sample plot No.	群落结构 Community structure	最大胸径 Maximum DBH/cm	平均胸径 Mean DBH/cm	树高 Tree height/m	郁闭度 Canopy density	坡度 Slope/（°）	海拔 Altitude/m
1	苦槠 Castanopsis sclerophylla + 檵木 Loropetalum chinense	48.0	7.7	5.1 ± 3.3	0.7	17	229
2	樟树 Cinnamomum camphora + 檵木 Loropetalum chinense	44.0	6.4	6.0 ± 2.3	0.7	17	319
3	樟树 Cinnamomum camphora + 檵木 Loropetalum chinense	51.9	7.5	5.8 ± 3.2	0.8	19	330
4	甜槠 Castanopsis eyrei + 山鸡椒 Litsea cubeba	46.2	4.2	4.2 ± 2.3	0.8	26	410
5	石栎 Lithocarpus glaber + 连蕊茶 Camellia cuspidata	51.8	5.4	4.0 ± 2.5	0.7	24	435
6	石栎 Lithocarpus glaber + 檵木 Loropetalum chinense	53.9	4.7	4.0 ± 2.4	0.8	23	452
7	石栎 Lithocarpus glaber + 檵木 Loropetalum chinense	38.9	4.2	3.9 ± 1.8	0.8	21	420

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表 2 各生长阶段林木基本信息

Table 2 Basic information of trees at different growth stages

生长阶段 Growth stage	径级范围 Diameter range/cm	株数 Number of tree	平均胸径 Average DBH/cm	标准差 Standard deviation/cm
幼树 Sapling	1 ≤ DBH < 5	3 547	2.7	0.97
小树 Small tree	5 ≤ DBH < 10	819	7.0	1.45
中树 Middle tree	10 ≤ DBH < 20	319	13.3	2.77
大树 Large tree	DBH ≥ 20	196	30.4	7.70

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表 3 空间结构参数计算方法

Table 3 Calculation method of spatial structure parameters

参数名称 Parameter name	计算公式 Computing formula	说明 Explanation
混交度 Mingling (M)	$M = \dfrac{1}{n}\displaystyle \sum \limits_{j = 1}^n {{v_{ij}}}$	① M为第i棵对象木的混交度；n是对象木i的邻近株数；当对象木与相邻木非同种时v_ij = 1，否则v_ij = 0；M为0、0.25、0.5、0.75、1，分别代表着零度、弱度、中度、强度和极强度混交 ① M is the mingling of the reference tree i, n is the number of nearest neighboring trees of the reference tree i. When the species of the nearest neighbor is not the same as the reference tree, v_ij = 1. Otherwise, v_ij = 0. M has 5 grades, 0, 0.25, 0.5, 0.75, 1, representing not mixed, weakly mixed, medium mixed, strongly mixed, extremely strongly mixed, respectively ② 混交度数值越大，代表林木混交程度越强 ② As the mingling value of trees increases, the degree of mixed of trees is enhanced
大小比数 Neighborhood comparison (U)	$U = \dfrac{1}{n}\displaystyle \sum \limits_{j = 1}^n {{v_{ij}}}$	① U为第i棵对象木的大小比数；n是对象木i的邻近株数；当对象木比相邻木大时，v_ij = 1，否则v_ij = 0；U为0、0.25、0.5、0.75、1，分别代表优势、亚优势、中庸、劣势及绝对劣势 ① U is the neighborhood comparison of the reference tree i, n is the number of nearest neighboring trees of the reference tree i. When the reference tree is larger than the nearest neighbor tree, v_ij = 1. Otherwise, v_ij = 0. U has 5 grades, 0, 0.25, 0.5, 0.75, 1, representing predominant, subdominant, moderate, inferior, extremely inferior, respectively ②大小比数数值越小，代表林木的生长状态越优 ②The smaller the value of size ratio is, the better the growth state of the representative tree is
密集度 Crowding degree (C)	$C = \dfrac{1}{n}\displaystyle \sum \limits_{j = 1}^n {{v_{ij}}}$	① C为第i棵对象木的密集度；n是对象木i的邻近株数；当对象木与相邻木的树冠投影重叠时，v_ij = 1，否则v_ij = 0；C为0、0.25、0.5、0.75、1，分别代表着非常稀疏、稀疏、中等密集、比较密集、很密集 ① C is the crowding degree of the reference tree i, n is the number of nearest neighboring trees of the reference tree i. When the canopy projection of the reference tree overlaps that of the adjacent tree, v_ij = 1. Otherwise, v_ij = 0. C has 5 grades, 0, 0.25, 0.5, 0.75, 1, representing extremely sparse, sparse, moderately dense, relatively dense, extremely dense, respectively ②密集度数值越大，代表林木密集程度越高 ② The higher the concentration is, the higher the forest density degree is
角尺度 Uniform angle index (W)	$W = \dfrac{1}{n}\displaystyle \sum \limits_{j = 1}^n {{v_{ij}}}$	① W为第i棵对象木的角尺度；n是对象木i的邻近株数；当相邻木与对象木的α角小于标准角α₀（α₀ = 72°）时，v_ij = 1，否则v_ij = 0。W为0、0.25、0.5、0.75、1，分别代表着很均匀、均匀、随机、不均匀、很不均匀 ① W is the uniform angle index of the reference tree i, n is the number of nearest neighboring trees of the reference tree i. When the angle (α) of an adjacent tree compared to the reference tree is less than the standard angle α₀(α₀ = 72°), v_ij = 1. Otherwise, v_ij = 0. W has 5 grades, 0, 0.25, 0.5, 0.75, 1, representing absolutely uniform, uniform, random, nonuniform, clumped, respectively ②均匀分布的置信区间为[0，0.475）、随机分布的置信区间为[0.475，0.517]、聚集分布的置信区间为（0.517，1] ②The confidence interval of uniform distribution is [0, 0.475), that of random distribution is [0.475, 0.517], and that of aggregation distribution is (0.517, 1]

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表 4 不同生长阶段林分空间结构综合评价

Table 4 Comprehensive evaluation of stand spatial structure at different growth stages

生长阶段 Growth stage	混交度 Mingling (M)		大小比数 Neighborhood comparison (U)		密集度 Crowding degree (C)		角尺度 Uniform angle index (W)		综合指数 Aggregative index (FSI)
生长阶段 Growth stage	权重 Weight	平均值 Mean	权重 Weight	平均值 Mean	权重 Weight	平均值 Mean	权重 Weight	平均值 Mean	综合指数 Aggregative index (FSI)
幼树 Sapling	0.364	0.609	0.388	0.545	0.103	0.852	0.145	0.576	0.265
小树 Small tree	0.111	0.746	0.753	0.268	0.046	0.895	0.091	0.563	0.117
中树 Middle tree	0.065	0.815	0.845	0.132	0.030	0.871	0.060	0.553	0.082
大树 Large tree	0.037	0.822	0.889	0.089	0.038	0.842	0.036	0.507	0.054

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