Comprehensive evaluation of stand state in Pinus massoniana plantations based on multi-dimensional indicators

doi:10.13466/j.cnki.lczyyj.2026.01.004

Abstract

Abstract:

Accurate assessment of stand state is of great significance for optimizing forest structure and improving timber production and ecological functions.In this study,Pinus massoniana plantations were selected as the research objects.A total of 24 sample plots were established across four age groups,including young,middle-aged,near-mature,and mature stands.Based on the unit circle method,the distance-independent evaluation index(ω₁),the distance-dependent evaluation index(ω₂),and the comprehensive evaluation index(ω)were constructed to characterize macroscopic stand attributes,microscopic spatial structure,and overall stand state,respectively.Differences in stand state among age groups and their dynamic change patterns with stand age were then analyzed.The results showed that:1)Stand states differed significantly among age groups.Tree dominance,health status,tree species composition,species diversity and mingling degree increased significantly with stand age.The stand structure gradually transitioned from a simple and single-species state in young stands toward a more complex,highly mixed and optimized state in mature stands.2)Differences among age groups exhibited distinct stage-specific patterns across the evaluation indices。The ω₁ and ω were significantly higher in near-mature stands than in young and middle-aged stands (P<0.05),with no significant differences between near-mature and mature stands; ω₂ was significantly higher in near-mature stands than in young stands and significantly higher in mature stands than in the other three age groups.The near-mature stage was a key stage at which the overall stand state improved significantly.3)Regression analysis showed thatω₁,ω₂ and ω were significantly positively correlated with stand age,with coefficients of determination(R²)of 0.292(P<0.05),0.761(P<0.001),and 0.682(P<0.001),respectively,indicating that stand states were gradually optimized with increasing stand age.Among them,ω₂ had stronger explanatory ability in characterizing changes in stand state,while ω integrated both macroscopic and microscopic information,maintaining relatively high explanatory power while providing a more comprehensive reflection of the overall stand state.These results provide a reference for stand state evaluation,structural optimization and stage-specific management of Pinus massoniana plantations.

Key words: Pinus massoniana plantation, stand state, forest management, unit circle method

CLC Number:

S791.248

LI Xingzhi, ZHU Jie, CHAI Zongzheng. Comprehensive evaluation of stand state in Pinus massoniana plantations based on multi-dimensional indicators[J]. Forest and Grassland Resources Research, 2026, (1): 34-45.

Figures/Tables 8

Tab.1

Tab.2

Distance-independent stand state indicators and formulas

维度	林分状态指标	公式及定义
结构	胸径分布(A)	将林木胸径以2 cm为径阶距进行划分,按Meyer负指数分布模型表示胸径结构:N=ke^-^ad,式中:N为株数;e为自然对数的底;d为胸径;a为负指数分布结构常数,k为常数。A=e^ah,式中:h表示径阶距为2 cm。若A为1.2~1.7,则表示处在合理的异龄林径阶分布范围内^[16]
	树高分布(V)	用基尼系数来表示树高分布。V=1-$\sum _{\mathit{i}=1}^{\mathit{n}}\left(2{\mathit{Q}}_{\mathit{i}}-{\mathit{W}}_{\mathit{i}}\right)$/n,式中:n为林木个体数,W_i为第i个个体树高占树高综合的比例,Q_i为W_i的累加值^[17]
	林木拥挤度(K)	用郁闭度表示,若郁闭度K值在0.6~0.8,则表示林分密度合理^[18]
活力	林木优势度(E)	E=$\frac{{\mathit{N}}_{\mathit{d}}}{\mathit{N}}$,式中:N_d为优势层林木株数,N为林分总株数。同时,林木株数也可以考虑用断面积或蓄积来替换,用于反映优势层林木占比
	林分长势(B)	B=$\frac{\stackrel{—}{\mathit{G}}}{{\mathit{G}}_{\mathit{m}\mathit{a}\mathit{x}}}$,式中:$\stackrel{—}{\mathit{G}}$为林分断面积,G_max为林分潜在最大断面积,林分长势指现实林分断面积接近潜在最大断面积的程度,本研究将G_max定义为林分中50%较大个体的平均断面积与林木株数的乘积。
	林木健康(Q)	健康林木(无病虫害且非断梢、弯曲、空心等)株数占林分总株数的比例^[7-8]
多样性	树种组成(Z)	Z=-$\sum _{\mathit{i}=1}^{\mathit{S}}$P_ilnP_i,式中:P_i为第i树种的蓄积比例;S为样方中出现的树种数,树种组成按十分法表示^[19]
	树种多样性(D)	D=1-$\sum _{\mathit{i}=1}^{\mathit{S}}{\mathit{P}}_{\mathit{i}}^{2}$,式中:P_i为第i树种的个体数比例;S为样方中出现的树种数^[16]
	树种均匀度(J)	J=-$\sum _{\mathit{i}=1}^{\mathit{S}}$P_ilnP_i/lnS,式中:P_i为第i个树种的个数比例;S为样方中出现的树种数^[16]

Tab.2

Tab.3

Tab.4

Tab.5

Tab.6

Fig.1

Fig.2

References 42

[1]	Liu Ziye, Feng Zhongke, Chang Chen. GEF Innovative forest management plan:taking grassland forest farm in Fengning county as an example[J]. Sustainability, 2022, 14(13):7795. doi: 10.3390/su14137795
[2]	Borecki T. Importance of the forest management in the sustainable forest economy[J]. Sylwan, 2008, 152(1):9-14.
[3]	Başkent E Z, Keleş S, Kadloğulla A İ, et al. Quantifying the effects of forest management strategies on the production of forest values:timber,carbon,oxygen,water,and soil[J]. Environmental Modeling and Assessment, 2011, 16(2):145-152. doi: 10.1007/s10666-010-9238-y
[4]	Sheng Qi, Dong Lingbo, Chen Ying, et al. Selection of the optimal timber harvest based on optimizing stand spatial structure of broadleaf mixed forests[J]. Forests, 2023, 14(10):2046. doi: 10.3390/f14102046
[5]	Canton H. Food and agriculture organization of the United Nations:FAO[M]// Europa Publications.The Europa Directory of International Organizations 2021.23rd ed. London: Routledge, 2021.
[6]	Luyssaert S, Schulze E D, Börner A, et al. Old-growth forests as global carbon sinks[J]. Nature, 2008, 455(7210):213-215. doi: 10.1038/nature07276
[7]	Zhang Ganggang, Hui Gangying, Zhang Gongqiao, et al. A novel comprehensive evaluation method of forest state based on unit circle[J]. Forests, 2019, 10(1):5. doi: 10.3390/f10010005
[8]	惠刚盈, 张弓乔, 赵中华, 等. 天然混交林最优林分状态的π值法则[J]. 林业科学, 2016, 52(5):1-8.
[9]	Pommerening A. Approaches to quantifying forest structures[J]. Forestry, 2002, 75(3):305-324. doi: 10.1093/forestry/75.3.305
[10]	Dong Lingbo, Wei Hongyang, Liu Zhaogang. Optimizing forest spatial structure with neighborhood-based indices:four case studies from northeast China[J]. Forests, 2020, 11(4):413. doi: 10.3390/f11040413
[11]	Wan Pan, Zhang Gongqiao, Wang Hongxiang, et al. Impacts of different forest management methods on the stand spatial structure of a natural Quercus aliena var.acuteserrata forest in Xiaolongshan,China[J]. Ecological Informatics, 2019, 50:86-94. doi: 10.1016/j.ecoinf.2019.01.007
[12]	Fu Liyong, Lei Xiangdong, Hu Zongda, et al. Integrating regional climate change into allometric equations for estimating tree aboveground biomass of Masson pine in China[J]. Annals of Forest Science, 2017, 74(2):42. doi: 10.1007/s13595-017-0636-z
[13]	Zhang Yan, Zhang Danju, Li Xun, et al. Contribution of soil fauna to the degradation of recalcitrant components in cinnamomum camphora foliar litter in different-sized gaps in Pinus massoniana plantations[J]. Journal of Forestry Research, 2019, 30(3):931-941. doi: 10.1007/s11676-018-0609-6
[14]	申鹏, 周雯, 柴宗政. 近自然经营对马尾松种群结构及分布格局的影响[J]. 西南林业大学学报(自然科学), 2024, 44(3):35-42.
[15]	Tu Jing, Zhao Zhongwen, Chai Zongzheng. The short-term impact of logging intensity on the stand state of middle-aged Masson pine(pinus massoniana Lamb.) Plantations[J]. Forests, 2025, 16(1):183. doi: 10.3390/f16010183
[16]	赵中华, 惠刚盈. 基于林分状态特征的森林自然度评价:以甘肃小陇山林区为例[J]. 林业科学, 2011, 47(12):9-16.
[17]	Pukkala T, Lähde E, Laiho O. Continuous cover forestry in Finland-recent research results[M]. Dordrecht: Springer, 2012.
[18]	惠刚盈, 张连金, 胡艳波, 等. 林分拥挤度及其应用[J]. 北京林业大学学报, 2016, 38(10):1-6.
[19]	汤孟平, 唐守正, 李希菲, 等. 树种组成指数及其应用[J]. 林业资源管理, 2003(2):33-36.
[20]	Cabello-Solorzano K, Ortigosa De Araujo I, Peña M, et al. The impact of data normalization on the accuracy of machine learning algorithms:a comparative analysis[C]//García Bringas P,Pérez García H,Martínez De Pisón F J,et al. 18th International conference on soft computing models in industrial and environmental applications(SOCO 2023). Cham: Springer Nature Switzerland, 2023:344-353.
[21]	惠刚盈, 胡艳波. 混交林树种空间隔离程度表达方式的研究[J]. 林业科学研究, 2001(1):23-27.
[22]	Clark P J, Evans F C. Distance to nearest neighbor as a measure of spatial relationships in populations[J]. Ecology, 1954, 35(4):445-453. doi: 10.2307/1931034
[23]	邹丰虎, 赵中文, 黄建平, 等. 基于模拟采伐马尾松人工林的空间结构优化决策[J]. 温带林业研究, 2021, 4(4):11-16.
[24]	柴宗政. 基于相邻木关系的森林空间结构量化评价及R语言编程实现:以秦岭中山带典型次生林为例[D]. 杨凌: 西北农林科技大学, 2017.
[25]	严兰, 谭伟, 柴宗政. 不同龄组柳杉人工林林分结构分析[J]. 福建农林大学学报(自然科学版), 2019, 48(3):316-324.
[26]	惠刚盈, 赵中华, 胡艳波, 等. 基于结构参数均值的林分空间结构综合评价研究[J]. 林业科学研究, 2023, 36(2):12-21.
[27]	Bāders E, Jõgiste K, Elferts D, et al. Storm legacies shaping post-windthrow forest regeneration:learnings from spatial indices in unmanaged Norway spruce stands[J]. European Journal of Forest Research, 2021, 140(4):819-833. doi: 10.1007/s10342-021-01368-x
[28]	Kassier H W. Forest dynamics,growth and yield:from measurement to model[J]. Southern Forests:A Journal of Forest Science, 2011, 73(1):63-65. doi: 10.2989/20702620.2011.574816
[29]	Messier C, Puettmann K J. Forests as complex adaptive systems:implications for forest management and modelling[J]. L’italia Forestale E Montana, 2011, 66(3):249-258.
[30]	Kint V. Structural development in ageing temperate Scots pine stands[J]. Forest Ecology and Management, 2005, 214(1):237-250. doi: 10.1016/j.foreco.2005.04.014
[31]	O’hara K L. Multiaged silviculture:managing for complex forest stand structures[M]. Oxford: Oxford University Press, 2014.
[32]	Zeller L, Prechzsch H. Effect of forest structure on stand productivity in central european forests depends on developmental stage and tree species diversity[J]. Forest Ecology and Management, 2019, 434:193-204. doi: 10.1016/j.foreco.2018.12.024
[33]	朱洁, 李兴志, 刘云山, 等. 马尾松人工林空间结构评价及动态分析[J]. 西部林业科学, 2025, 54(3):9-17.
[34]	Prechzsch H. Forest dynamics,growth and yield:from measurement to model[M]. Berlin: Springer-Verlag, 2009.
[35]	Wang Boheng, Zhou Chaofan, Liu Di, et al. Stability and spatial structure of Chinese pine(Pinus tabuliformis carr.) plantations in loess hilly region:a case study from Huanglong mountain[J]. Forests, 2023, 14(9):1921. doi: 10.3390/f14091921
[36]	姜俊, 谢阳生, 陆元昌, 等. 不同林龄阶段马尾松人工林群落结构特征及经营策略[J]. 西北林学院学报, 2015, 30(6):1-7.
[37]	陈超, 赵吟吟, 俞家聪, 等. 基于角尺度、混交度和胸径优势度的杉木混交林空间结构优化[J]. 林草资源研究, 2025(1):38.
[38]	李佳妮, 胡杨, 杨君珑. 基于无人机激光雷达的贺兰山青海云杉林空间结构分析与促进更新模拟研究[J]. 林草资源研究, 2025(4):52-61.
[39]	Zhao Zhonghua, Hui Gangying, Yang Aimin, et al. Assessing tree species diversity in forest ecosystems:a new approach[J]. Frontiers in Ecology and Evolution, 2022, 10:971585. doi: 10.3389/fevo.2022.971585
[40]	Dong Lingbo, Bettinger Pete, Liu Zhaogang. Optimizing neighborhood-based stand spatial structure:four cases of boreal forests[J]. Forest Ecology and Management, 2022, 506:119965. doi: 10.1016/j.foreco.2021.119965
[41]	Fang Xianfeng, Tan Wei, Chai Zongzheng. Close-to-nature management positively improves the spatial structure of Masson pine forest stands[J]. Web Ecology, 2021, 21:45-54. doi: 10.5194/we-21-45-2021
[42]	Yang Senlin, Mao Kangshan, Yang Hao, et al. Stand characteristics and ecological benefits of Chinese fir,Chinese cedar,and mixed plantations in the mountainous areas of the Sichuan basin[J]. Forest Ecology and Management, 2023, 544:121168. doi: 10.1016/j.foreco.2023.121168

调查因子	幼龄林			中龄林			近熟林			成熟林
主要树种组成	马尾松、柳杉、杉木、枫香、光皮桦			马尾松、杉木、光皮桦、山杨、枫香			马尾松、杉木、枫香、麻栎、漆树			马尾松、杉木、枫香、麻栎、桢楠
样地数量/个	6			6			6			6
林龄/a	6	~	10	11	~	20	21	~	30	31	~	45
密度/(株/hm²)	1 725	~	4 200	1 350	~	3 300	975	~	1 675	600	~	1 100
郁闭度	0.8	~	0.9	0.7	~	0.9	0.7	~	0.9	0.6	~	0.9
平均胸径/cm	9.05	~	11.79	12.78	~	16.96	15.65	~	18.69	20.41	~	23.04
平均树高/m	7.71	~	14.38	12.08	~	16.18	14.73	~	18.89	16.63	~	19.29
平均冠幅/m	2.25	~	2.79	1.56	~	4.09	1.49	~	4.47	2.15	~	5.71
濒死木密度/(株/hm²)	175	~	350	0	~	400	0	~	325	0	~	50

与距离有关的指标	取值范围	最优值	指标类型
混交度(M)	[0,1.0]	1.0	戒上型
林层差异化(H)	[0,1.0]	1.0	戒上型
密集度(C)	[0,1.0]	0.5	中间型
角尺度(W)	[0,1.0]	0.5	中间型
胸径大小比数(U)	[0,1.0]	0.0	戒下型

指标	计算公式	变量说明
混交度(M)	M=$\frac{1}{4}\sum _{\mathit{j}=1}^{4}$v_ij	当参照树i与第j株最近相邻木树种不同时,v_ij=1;否则v_ij=0
林层差异化(H)	H=$\frac{{\mathit{N}}_{\mathit{i}}-1}{4}$	N_i为以参照树i为中心的空间结构单元内不同林层类型的数量。
密集度(C)	C=$\frac{1}{4}\sum _{\mathit{j}=1}^{4}$y_ij	当参照树i与第j株最近相邻木树冠投影相互重叠时,y_ij=1;否则y_ij=0
角尺度(W)	W=$\frac{1}{4}\sum _{\mathit{j}=1}^{4}$z_ij	当以参照树i为顶点,其周围相邻两株相邻木方向线形成的第j个夹角小于标准角α₀时,z_ij=1;否则z_ij=0;其中α₀=72°
胸径大小比数(U)	U=$\frac{1}{4}\sum _{\mathit{j}=1}^{4}$k_ij	当第j株最近相邻木胸径大于参照树i时,k_ij=1;否则k_ij=0

指标类型	指标	幼龄林	中龄林	近熟林	成熟林
与距离无关的指标 (ω₁)	胸径分布(A)	0.284±0.05a	0.199±0.017b	0.178±0.015bc	0.149±0.004c
	树高分布(V)	0.109±0.025a	0.13±0.033a	0.169±0.06a	0.128±0.072a
	林木拥挤度(K)	0.79±0.265ab	0.61±0.239bc	0.958±0.073a	0.52±0.147c
	林木优势度(A)	0.384±0.219b	0.502±0.224b	0.605±0.195ab	0.803±0.147a
	林分长势(B)	0.69±0.017a	0.669±0.028ab	0.636±0.036b	0.664±0.033ab
	林木健康(Q)	0.901±0.022b	0.925±0.054ab	0.934±0.07ab	0.959±0.035a
	树种组成(Z)	0.071±0.076c	0.132±0.143bc	0.225±0.114b	0.364±0.088a
	树种多样性(D)	0.078±0.086c	0.175±0.209bc	0.286±0.164b	0.469±0.106a
	树种均匀度(J)	0.084±0.073b	0.142±0.14b	0.206±0.139ab	0.29±0.044a
与距离有关的指标 (ω₂)	混交度优度系数(M_pv)	0.036±0.039c	0.114±0.137bc	0.226±0.147b	0.41±0.094a
	林层差异化优度系数(H_pv)	0.326±0.1a	0.375±0.082a	0.416±0.056a	0.35±0.119a
	角尺度优度系数(W_pv)	0.802±0.024a	0.788±0.029a	0.806±0.032a	0.81±0.021a
	密集度优度系数(C_pv)	0.557±0.018b	0.6±0.059b	0.586±0.056b	0.672±0.022a
	胸径大小比数优度系数(U_pv)	0.399±0.013ab	0.398±0.015ab	0.405±0.013a	0.386±0.016b