边缘校正方法对空间结构参数影响的尺度效应

doi:10.11707/j.1001-7488.LYKX20210872

摘要/Abstract

摘要：

目的: 选择合适的边缘校正方法，消除边缘效应对样地空间结构参数的影响，为森林空间结构分析提供理论依据。方法: 选取不同大小样地，采用3种边缘校正方法（缓冲区校正法、Voronoi图近邻校正法和NN近邻校正法）消除边缘效应，计算样地空间结构参数，比较不同边缘校正方法计算的空间结构参数随样地大小的变化情况，判断不同边缘校正方法在不同样地上的适用性。结果: 当样地边长小于等于40 m时，缓冲区校正法消除边缘木最少，随着样地增大，缓冲区校正法成为消除边缘木最多的方法；NN近邻校正法消除边缘木株数多于Voronoi图近邻校正法，但差别不大；小样地空间分布格局多以随机或团状分布方式出现，大样地空间分布格局趋于一致且多为接近随机的团状分布方式；各样地大小比数林分均值随样地边长增大林分逐渐向中庸木过渡；简单混交度各均值曲线呈强混交趋势，树种多样性混交度介于中混交和强混交之间。结论: 当样地边长小于等于40 m时，空间结构参数随样地大小变化较大；当样地边长大于60 m时，边缘校正与否对空间结构参数大小比数、简单混交度、树种多样性混交度的影响不大。缓冲区校正法在角尺度计算中有适用局限性，其未像Voronoi图近邻校正法和NN近邻校正法一样随着样地增大角尺度收敛于林分均值；从对3个空间结构参数的综合影响看，NN近邻校正法相较缓冲区校正法对样地尺度依赖性小，是3种边缘校正方法中表现最优的方法。空间结构参数计算与样地内保留木数量有关，镜像复制或八邻域平移校正法组成一个大样地来抵消边缘效应，其是否存在尺度效应问题有待今后进一步研究。

关键词: 边缘效应, 缓冲区法, 最近邻法, 空间分布, 混交度

Abstract:

Objective: Suitable edge correction methods were selected to eliminate the influence of edge effects on the spatial structure parameters of the sample plots and to provide a theoretical basis for forest spatial structure analysis. Method: The edge trees were removed according to different edge correction methods such as the Voronoi diagram-based method, the internal buffer method and the nearest-neighbor (NN) method in the sample plots of different sizes, then the structural parameters i.e. the uniform angle index, the size differentiation index, the mingling index and the tree species diversity mingling were calculated in terms of those remained trees within the different-size plots, and we further analyzed how these structural parameters varied against the changes of the sample plots' sizes so as to recognize the applicability of the three different correction methods on different plots. Result: For those plots with each side length of no more than 40 m, the internal buffer method removed the least amount of edge wood. As the scale of plots increased furthermore, the internal buffer method started to removed the most amount of edge wood while the NN method removed more edge trees than the Voronoi diagram-based method, but the differences were not significant. The spatial distribution patterns of small sample plots mostly appeared as clumped or random, and the spatial distribution pattern of large sample plots tends to be clumped but close to random. The mean value of size differentiation index of each sample plot gradually transitioned to intermediate wood status when the side length of the sample plot increased. The mean curves of the simple mingling index showed a trend of strong mixed degree, and the tree species diversity minglings were between medium and strong mixed degree. Conclusion: When the side length of the sample plot was no more than 40 m, the structural parameters varied greatly with the size of the sample plots changing. When the side length of the sample plot was greater than 60m, the edge correction or not had little effect on the calculation of the size differentiation index, the mingling index, and the tree species diversity mingling. The internal buffer method has applicability limitations in calculating the uniform angle index since it did not induce convergence of the index like the other two methods. In general, the NN method is less dependent on the plot scale than the internal buffer method, and is the best performing one among the three methods. The three methods used in this paper all belong to minus-sampling method, the calculation of the structural parameters only utilized the retained trees in the sample plots and wasted part of the survey information. As an alternative, the mirror replication or eight-neighborhood translation correction method may form a larger sample plot (i.e. plus-sampling method) to offset the edge effects, but whether they have scale effects is a question that needs to be further investigated in the future.

Key words: edge effect, internal buffer method, the nearest-neighbor method, spatial distribution, mingling index

中图分类号:

S758

于帅,蔡体久,张丕德,任铭磊,张海宇,琚存勇. 边缘校正方法对空间结构参数影响的尺度效应[J]. 林业科学, 2023, 59(10): 57-65.

Shuai Yu,Tijiu Cai,Pide Zhang,Minglei Ren,Haiyu Zhang,Cunyong Ju. Scaling Effects of Edge Correction Methods on Spatial Structure Parameters[J]. Scientia Silvae Sinicae, 2023, 59(10): 57-65.

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参考文献 0

	安慧君, 张　韬. 聚集指数边界效应的校正方法与应用. 南京林业大学学报(自然科学版), 2005, 29 (3): 57- 60.
	An H J, Zhang T. Studies on adjustment approach and its application of bounder effect on aggregation index. Journal of Nanjing Forestry University (Natural Sciences Edition), 2005, 29 (3): 57- 60.
	曹小玉, 李际平. 林分空间结构指标研究进展. 林业资源管理, 2016, (4): 65- 73.
	Cao X Y, Li J P. Research progress on indicators of the stand spatial structure. Forest Resources Management, 2016, (4): 65- 73.
	陈　军, 赵仁亮, 乔朝飞. 基于Voronoi图的GIS空间分析研究. 武汉大学学报(信息科学版), 2003, 28 (S1): 32- 37.
	Chen J, Zhao R L, Qiao C F. Voronoi diagram-based GIS spatial analysis. Geomatics and Information Science of Wuhan University, 2003, 28 (S1): 32- 37.
	杜秀芳, 汤孟平, 郦　青, 等. 临安不同森林类型混交度的对比研究. 西南林业大学学报, 2019, 39 (3): 101- 108.
	Du X F, Tang M P, Li Q, et al. Comparative study on the mixed degree of different forest types in Lin’an. Journal of Southwest Forestry University, 2019, 39 (3): 101- 108.
	高　伟, 黄雍容, 林建丽, 等. 濒危树种闽桦天然林优势种群种间相关性. 林业科学, 2021, 57 (10): 1- 14.
	Gao W, Huang Y R, Lin J L, et al. Interspecific correlations among dominant populations of natural forest of endangered species Betula fujianensis . Scientia Silvae Sinicae, 2021, 57 (10): 1- 14.
	郝月兰, 张会儒, 唐守正. Voronoi图方法确定云冷杉林最近邻木的适用性研究. 林业资源管理, 2011, (6): 59- 64.
	Hao Y L, Zhang H R, Tang S Z. Study on the adaptability of Voronoi diagram on determining the nearest neighboring trees of natural mixed spruce-fir forests. Forest Resources Management, 2011, (6): 59- 64.
	和敬渊, 王新杰, 郭韦韦, 等. 金沟岭林场两种天然起源的杨桦次生林空间结构特征. 东北林业大学学报, 2020, 48 (9): 1- 7.
	He J Y, Wang X J, Guo W W, et al. Spatial structure of two natural origin poplar-birch secondary forests in Jingouling forest farm. Journal of Northeast Forestry University, 2020, 48 (9): 1- 7.
	胡艳波, 惠刚盈, 戚继忠, 等. 吉林蛟河天然红松阔叶林的空间结构分析. 林业科学研究, 2003, 16 (5): 523- 530.
	Hu Y B, Hui G Y, Qi J Z, et al. Analysis of the spatial structure of natural Korean pine broad leaved forest. Forest Research, 2003, 16 (5): 523- 530.
	胡艳波, 惠刚盈, 王宏翔, 等. 随机分布的角尺度置信区间及其应用. 林业科学研究, 2014, 27 (3): 302- 308.
	Hu Y B, Hui G Y, Wang H X, et al. Uniform angle index (w) confidence interval of the random distribution and its application . Forest Research, 2014, 27 (3): 302- 308.
	胡艳波, 惠刚盈. 一种新的基于混交度的林木种群分布格局测度方法. 北京林业大学学报, 2015, 37 (1): 9- 14.
	Hu Y B, Hui G Y. A new method for measuring population distribution patterns of forest trees based on the mingling degree. Journal of Beijing Forestry University, 2015, 37 (1): 9- 14.
	惠刚盈, Von Gadow K, Albert M. 角尺度—一个描述林木个体分布格局的结构参数. 林业科学, 1999, 35 (1): 37- 42. doi: 10.3321/j.issn:1001-7488.1999.01.006
	Hui G Y, Von Gadow K, Albert M. The neighbourhood pattern: a new structure parameter for describing distribution of forest tree position. Scientia Silvae Sinicae, 1999, 35 (1): 37- 42. doi: 10.3321/j.issn:1001-7488.1999.01.006
	惠刚盈, 胡艳波, 陈伯望. 林木分布格局类型的角尺度均值分析方法. 生态学报, 2004, 24 (6): 1225- 1229.
	Hui G Y, Hu Y B, Chen B W. Characterizing forest spatial distribution pattern with the mean value of uniform angle index. Acta Ecologica Sinica, 2004, 24 (6): 1225- 1229.
	惠刚盈, Von Gadow K, 赵中华, 等. 2016a. 结构化森林经营原理. 北京: 中国林业出版社, 3-5
	Hui G Y, Von Gadow K, Zhao Z H, et al. 2016a. Principles of structurebased forest management. Beijing: China Forestry Publishing House, 3-5.［in Chinese］
	惠刚盈, 胡艳波. 角尺度在林分空间结构调整中的应用. 林业资源管理, 2016b, (3): 1- 35.
	Hui G Y, Hu Y B. Application of neighborhood pattern in forest spatial structure regulation. Forest Resources Management, 2016b, (3): 1- 35.
	惠刚盈, 赵中华, 张弓乔, 等. 基于角尺度的随机体在森林稳定性维持中的作用. 林业科学, 2021, 57 (2): 22- 30. doi: 10.11707/j.1001-7488.20210203
	Hui G Y, Zhao Z H, Zhang G Q, et al. The role of random structural pattern based on uniform angle index in maintaining forest stability. Scientia Silvae Sinicae, 2021, 57 (2): 22- 30. doi: 10.11707/j.1001-7488.20210203
	霍艳玲, 金　辉, 李永宁, 等. 冀北山地白桦典型大小比数与直径生长关系研究. 林业资源管理, 2014, (3): 71- 76.
	Huo Y L, Jin H, Li Y N, et al. Relationship between neighborhood comparison and diameter growth of secondary poplar-birch forest in the Mountains of north Hebei. Forest Resources Management, 2014, (3): 71- 76.
	李际平, 封　尧, 赵春燕, 等. 基于Voronoi图的杉木生态公益林空间结构量化分析. 北京林业大学学报, 2014, 36 (4): 1- 7.
	Li J P, Feng Y, Zhao C Y, et al. Quantitative analysis of stand spatial structure of Cunninghamia lanceolata non-commercial forest based on Voronoi diagram . Journal of Beijing Forestry University, 2014, 36 (4): 1- 7.
	李晓婷, 李　彤, 仇宽彪, 等. 城市森林林木斑块特征与降温效应的关系——以北京市城区为例. 林业科学, 2021, 57 (4): 32- 42.
	Li X T, Li T, Qiu K B, et al. Relationship between patterns of urban forest patches and their cooling effects: a case study of Beijing urban area. Scientia Silvae Sinicae, 2021, 57 (4): 32- 42.
	刘　帅, 张　江, 李建军, 等. 森林空间结构分析中基于Voronoi图的样地边缘校正. 林业科学, 2017, 53 (1): 28- 37. doi: 10.11707/j.1001-7488.20170104
	Liu S, Zhang J, Li J J, et al. Edge correction of Voronoi diagram in forest spatial structure analysis. Scientia Silvae Sinicae, 2017, 53 (1): 28- 37. doi: 10.11707/j.1001-7488.20170104
	刘　月, 王　君, 杨雨春, 等. 不同林分密度胡桃楸胸径、树高、材积与冠幅关系. 森林工程, 2021, 37 (3): 28- 35.
	Liu Y, Wang J, Yang Y C, et al. Relationship between crown width and DBH, tree height or volume of Juglans mandshurica in stands of different density . Forest Engineering, 2021, 37 (3): 28- 35.
	刘忠玲, 刘建明, 胡　伟, 等. 不同密度胡桃楸次生林枯落物和土壤持水特性的研究. 森林工程, 2021, 37 (3): 52- 59,66.
	Liu Z L, Liu J M, Hu W, et al. Water-holding characteristics of litter and soil of Juglans mandshurica natural secondary forest with different densities . Forest Engineering, 2021, 37 (3): 52- 59,66.
	孟宪宇. 2007. 测树学. 北京: 中国林业出版社, 59
	Meng X Y. 2007. Forest mensuration. Beijing: China Forestry Publishing House, 59［in Chinese］
	邵国凡, 赵士洞, 舒噶特. 1995. 森林动态模拟: 兼论红松林的优化经营. 北京: 中国林业出版社, 47−49.
	Shao G F, Zhao S D, Shu G T. 1995. Forest dynamics simulation: optimal management of red pine forests. Beijing: China Forestry Publishing House, 47−49.［in Chinese］
	宋语涵, 张　晨, 蔡体久, 等. 基于Voronoi图的阔叶红松林空间结构特征分析. 北京林业大学学报, 2021, 43 (1): 20- 26. doi: 10.12171/j.1000-1522.20200056
	Song Y H, Zhang C, Cai T J, et al. Quantitative analysis of spatial structural characteristics of broadleaved Korean pine forest based on Voronoi diagram. Journal of Beijing Forestry University, 2021, 43 (1): 20- 26. doi: 10.12171/j.1000-1522.20200056
	汤孟平, 唐守正, 雷相东, 等. Ripley's K(d)函数分析种群空间分布格局的边缘校正. 生态学报, 2003, 23 (8): 1533- 1538.
	Tang M P, Tang S Z, Lei X D, et al. Edge correction of Ripley's K(d) function on population spatial pattern analysis. Acta Ecologica Sinica, 2003, 23 (8): 1533- 1538.
	汤孟平. 2003. 森林空间结构分析与优化经营模型研究. 北京: 北京林业大学.
	Tang M P. 2003. Analysis of forest spatial structure and study on optimal management model. Beijing: Beijing Forestry University.［in Chinese］
	汤孟平, 唐守正, 雷相东, 等. 两种混交度的比较分析. 林业资源管理, 2004, (8): 25- 27.
	Tang M P, Tang S Z, Lei X D, et al. Comparison analysis on two minglings. Forest Resource Management, 2004, (8): 25- 27.
	汤孟平. 森林空间结构研究现状与发展趋势. 林业科学, 2010, 46 (1): 117- 122.
	Tang M P. Advances in study of forest spatial structure. Scientia Silvae Sinicae, 2010, 46 (1): 117- 122.
	万　盼, 刘文桢, 刘瑞红, 等. 结构化经营对栎松混交林林分空间结构及稳定性的影响. 林业科学, 2020, 56 (4): 35- 45.
	Wan P, Liu W Z, Liu R H, et al. Effects of structure-based forest management on stand space structure and its stability of mixed oak-pine forest. Scientia Silvae Sinicae, 2020, 56 (4): 35- 45.
	魏红洋, 董灵波, 刘兆刚. 大兴安岭主要森林类型林分空间结构优化模拟. 应用生态学报, 2019, 30 (11): 3824- 3832.
	Wei H Y, Dong L B, Liu Z G. Spatial structure optimization simulation of main forest types in Great Xing’an Mountains, Northeast China. Chinese Journal of Applied Ecology, 2019, 30 (11): 3824- 3832.
	夏富才, 姚大地, 赵秀海, 等. 长白山北坡阔叶红松林空间结构. 东北林业大学学报, 2009, 37 (10): 5- 7.
	Xia F C, Yao D D, Zhao X H, et al. Horizontal spatial structure of Korean pine broad-leaved forest in northern slope of Changbai Mountains. Journal of Northeast Forestry University, 2009, 37 (10): 5- 7.
	辛　力. 2011. 森林抚育对不同林分类型结构及健康的影响研究. 杨凌: 西北农林科技大学.
	Xin L. 2011. Stuying the effects of thinning on the structure and health of different forest stand types. Yangling: Northwest Agriculture and Forestry University.［in Chinese］
	张金屯. 植物种群空间分布的点格局分析. 植物生态学报, 1998, 22 (4): 344- 349. doi: 10.3321/j.issn:1005-264X.1998.04.008
	Zhang J T. An analysis of spatial point pattern for plant species. Acta Phytoecologica Sinica, 1998, 22 (4): 344- 349. doi: 10.3321/j.issn:1005-264X.1998.04.008
	赵中华, 惠刚盈, 胡艳波, 等. 结构化森林经营方法在阔叶红松林中的应用. 林业科学研究, 2013, 26 (4): 467- 472. doi: 10.3969/j.issn.1001-1498.2013.04.012
	Zhao Z H, Hui G Y, Hu Y B, et al. Application of structure-based forest management in broadleaved Korean pine mixed forest. Forest Research, 2013, 26 (4): 467- 472. doi: 10.3969/j.issn.1001-1498.2013.04.012
	周红敏, 惠刚盈, 赵中华, 等. 林分空间结构分析中样地边界木的处理方法. 林业科学, 2009, 45 (2): 1- 5.
	Zhou H M, Hui G Y, Zhao Z H, et al. Treatment methods of plot boundary trees in spatial forest structure analysis. Scientia Silvae Sinicae, 2009, 45 (2): 1- 5.
	朱万才, 吴　瑶, 李亚洲, 等. 不同保留密度对落叶松水曲柳混交林的影响. 森林工程, 2021, 37 (2): 50- 56,94. doi: 10.3969/j.issn.1006-8023.2021.02.008
	Zhu W C, Wu Y, Li Y Z, et al. Effect of different reserve density on Larix gmelinii-Fraxinus mandshurica mixed forest . Forest Engineering, 2021, 37 (2): 50- 56,94. doi: 10.3969/j.issn.1006-8023.2021.02.008
	Ali A. Forest stand structure and functioning: current knowledge and future challenges. Ecological Indicators, 2018, 98, 665- 677.
	Diggle P J. 2003. Statistical analysis of spatial point patterns. 2nd ed. New York: Oxford University Press Inc, 1−65.
	Dong L B, Wei H Y, Liu Z G. Optimizing forest spatial structure with neighborhood-based indices: four case studies from northeast China. Forests, 2020, 11 (4): 413. doi: 10.3390/f11040413
	Ghalandarayeshi S, Nord-Larsen T, Johannsen V K, et al. Spatial patterns of tree species in Suserup Skov - a semi-natural forest in Denmark. Forest Ecology and Management, 2017, 406, 391- 401. doi: 10.1016/j.foreco.2017.10.020
	Lilleleht A, Sims A, Pommerening A. Spatial forest structure reconstruction as a strategy for mitigating edge-bias in circular monitoring plots. Forest Ecology and Management, 2014, 316, 47- 53. doi: 10.1016/j.foreco.2013.08.039
	Nguyen H H. Erfanifard Y, Petritan I C. Nearest neighborhood characteristics of a tropical mixed broadleaved forest stand. Forests, 2018, 9 (33): 1- 14.
	Põldveer E, Korjus H, Kiviste A, et al. Assessment of spatial stand structure of hemiboreal conifer dominated forests according to different levels of naturalness. Ecological Indicators, 2020, 110, 105944. doi: 10.1016/j.ecolind.2019.105944
	Pommerening A, Stoyan D. Edge-correction needs in estimating indices of spatial forest structure. Canadian Journal of Forest Research, 2006, 36 (7): 1723- 1739. doi: 10.1139/x06-060
	Pommerening A. Approaches to quantifying forest structures. Forestry:an International Journal of Forest Research, 2002, 75 (3): 305- 324. doi: 10.1093/forestry/75.3.305
	Radtke P J, Burkhart H E. A comparison of methods for edge-bias compensation. Canadian Journal of Forest Research, 1998, 28 (6): 942- 945. doi: 10.1139/x98-062
	Von Gadow K, Hui G Y. 2001. Characterizing forest spatial structure and diversity. Proceedings of the SUROR International Workshop “Sustainable Forestry in Temperate Regions”, Sweden: Lund University, 20−30.

树种 Species	株数 Number of trees	相对丰富度 Relative abundance（%）	平均胸径 Mean DBH/cm	平均树高 Mean height /m	胸高断面积 Basal area of breast height/ (m²·hm^?2)	蓄积 Volume/ （m³·hm^?2）	树种组成系数 Coefficient of species composition
白桦Betula platyphylla	228	20.94	21.04	0.34	8.86	18.00	0.27
红松Pinus koraiensis	94	8.63	17.96	0.54	3.08	6.35	0.10
冷杉Abies fabri	202	18.55	19.56	0.55	7.88	18.14	0.28
鱼鳞云杉Picea jezoensis var. microsperma	49	4.50	22.59	0.57	2.59	6.21	0.09
紫椴Tilia amurensis	156	14.33	14.07	0.64	3.41	6.17	0.09
全样地Total plots	1 089	—	16.60	12.60	31.69	65.63	1.00

校正方法 Correction method	尺度 Scale	株数 Number of trees	$\bar w $	$ {\sigma }_{w} $	下限 Low limit	上限 Upper limits	分布格局 Distribution patterns
未校正 Uncorrected	20 m×20 m	43	0.549	0.034	0.434	0.566	随机Random
	30 m×30 m	92	0.531	0.023	0.455	0.545	随机Random
	40 m×40 m	157	0.534	0.018	0.465	0.535	随机Random
	60 m×60 m	418	0.524	0.011	0.478	0.522	团状Clumped
	80 m×80 m	716	0.525	0.008	0.483	0.517	团状Clumped
	100 m×100 m	1 089	0.521	0.007	0.486	0.514	团状Clumped
NN最近邻校正法 The nearest- neighbor method	20 m×20 m	18	0.570	0.051	0.401	0.599	随机Random
	30 m×30 m	56	0.549	0.029	0.442	0.558	随机Random
	40 m×40 m	109	0.547	0.021	0.458	0.542	团状Clumped
	60 m×60 m	345	0.526	0.012	0.476	0.524	团状Clumped
	80 m×80 m	598	0.524	0.009	0.482	0.518	团状Clumped
	100 m×100 m	953	0.526	0.007	0.486	0.514	团状Clumped
Voronoi图近邻校正法 The Voronoi diagram-based method	20 m×20 m	18	0.592	0.051	0.400	0.600	随机Random
	30 m×30 m	59	0.537	0.029	0.444	0.556	随机Random
	40 m×40 m	103	0.557	0.022	0.457	0.543	团状Clumped
	60 m×60 m	342	0.522	0.012	0.476	0.524	随机Random
	80 m×80 m	614	0.520	0.009	0.482	0.518	团状Clumped
	100 m×100 m	963	0.523	0.007	0.486	0.514	团状Clumped
5%缓冲区校正法 The internal buffer method	20 m×20 m	32	0.553	0.039	0.424	0.576	随机Random
	30 m×30 m	72	0.547	0.026	0.449	0.551	随机Random
	40 m×40 m	127	0.541	0.020	0.461	0.539	团状Clumped
	60 m×60 m	337	0.527	0.012	0.476	0.524	团状Clumped
	80 m×80 m	579	0.523	0.009	0.482	0.518	团状Clumped
	100 m×100 m	903	0.526	0.008	0.485	0.515	团状Clumped

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