欢迎访问林草资源研究
Scientific Research

Research on the Difference of Mingling Degree under Different Selection Schemes of Adjacent Trees

  • Dongsheng QING ,
  • Jiang ZHANG ,
  • Jianjun LI ,
  • Jinxiang PENG ,
  • Shuai LIU
Expand
  • 1. Central South University of Forestry Science and Technology,Changsha 410000,China
    2. Hunan Applied Technology College,Changde,Hunan 415000,China
    3 National Engineering Laboratory of Forestry Ecological Application Technology in South China,Changsha 410000,China

Received date: 2021-06-07

  Revised date: 2021-07-14

  Online published: 2021-09-26

Abstract

In order to clarify the difference of stand mingling degree under different adjacent tree selection schemes,and find the evidence of which stand type is suitable for different adjacent tree selection schemes,this paper can provide reference for the research of stand spatial structure related issues.31 sample plots were set up in Longhu Mountain of South Dongting Lake area according to the types of aggregated distribution stand,random distribution stand,uniform distribution stand and sparse distribution stand.The methods based on "1+4" nearest adjacent trees,radius R(R=3.05 m) circle and Voronoi diagram were used to solve the number of adjacent trees per plot,the mingling degree of single tree and the average mingling degree of stand in various places,and explore the correlation between different schemes in different forest types.1) From the point of view of the overall stand average mingling degree,the average mingling degree values of the other stands in the experimental plots were not greatly different,except that the average mingling degree value of the adjacent trees based on the radius R(R=3.05 m) circle in the sparse distribution was low.2) From the point of view of individual tree,the mingling degree values of target trees in different stand types were different under different adjacent tree selection schemes.3) The correlation between "1+4" nearest adjacent tree and Voronoi diagram was relatively high in different stand types.Different selection schemes of adjacent trees had their own advantages under different stand types,but on the whole,the stability and accuracy of the adjacent selection schemes based on "1+4" nearest adjacent tree and Voronoi diagram were relatively high in solving mingling degrees of different stand types.

Cite this article

Dongsheng QING , Jiang ZHANG , Jianjun LI , Jinxiang PENG , Shuai LIU . Research on the Difference of Mingling Degree under Different Selection Schemes of Adjacent Trees[J]. Forest and Grassland Resources Research, 2021 , 0(4) : 69 -78 . DOI: 10.13466/j.cnki.lyzygl.2021.04.010

References

[1] Schlamadinger B, Marland G. The role of forest and bioenergy strategies in the global carbon cycle[J]. Biomass and Bioenergy, 1996, 10(5-6):275-300.
[2] Pugh T A M, Lindeskog M, Smith B, et al. Role of forest regrowth in global carbon sink dynamics[J]. Proceedings of the National Academy of Sciences, 2019, 116(10):4382-4387.
[3] Nisbet T R. The role of forest management in controlling diffuse pollution in UK forestry[J]. Forest Ecology and Management, 2001, 143(1-3):215-226.
[4] Brunner I. Ectomycorrhizas:their role in forest ecosystems under the impact of acidifying pollutants[J]. Perspectives in plant ecology,Evolution and Systematics, 2001, 4(1):13-27.
[5] Roland J, Taylor P D. Insect parasitoid species respond to forest structure at different spatial scales[J]. Nature, 1997, 386(6626):710-713.
[6] 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[J]. 林业科学研究, 2003(5):523-530.
[7] González-Moreno P, Quero J L, Poorter L, et al. Is spatial structure the key to promote plant diversity in Mediterranean forest plantations?[J]. Basic and Applied Ecology, 2011, 12(3):251-259.
[8] Tang M P. Advances in study of forest spatial structure[J]. Scientia Silvae Sinicae, 2010, 46(1):117-122.
[9] Zehr S C. Public representations of scientific uncertainty about global climate change[J]. Public understanding of science, 2000, 9(2):85.
[10] Von Gadow K, Hui G. Modelling forest development[M]. Springer Science & Business Media, 1999.
[11] 汤孟平, 周国模, 陈永刚, 等. 基于Voronoi图的天目山常绿阔叶林混交度[J]. 林业科学, 2009, 45(6):1-5.
[12] 胡艳波, 惠刚盈. 优化林分空间结构的森林经营方法探讨[J]. 林业科学研究, 2006(1):1-8.
[13] 汤孟平, 唐守正, 雷相东, 等. 林分择伐空间结构优化模型研究[J]. 林业科学, 2004(5):25-31.
[14] 汤孟平, 唐守正, 雷相东, 等. 两种混交度的比较分析[J]. 林业资源管理, 2004(4):25-27.
[15] 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.
[16] Ricklefs R E, He F. Region effects influence local tree species diversity[J]. Proceedings of the National Academy of Sciences, 2016, 113(3):674-679.
[17] Lima J S, Ballesteros-Mejia L, Lima-Ribeiro M S, et al. Climatic changes can drive the loss of genetic diversity in a Neotropical savanna tree species[J]. Global change biology, 2017, 23(11):4639-4650.
[18] Zhao Zhonghua, Hui Gangying, Hu Yanbo, et al. Comparison of tree species diversity calculated[J]. Scientia Silvae Sinicae, 2012, 48(11):1-8.
[19] Mori A S. Environmental controls on the causes and functional consequences of tree species diversity[J]. Journal of Ecology, 2018, 106(1):113-125.
[20] Zhao Chunyan, Li Jiping, Li Jianjun. Quantitative analysis of forest stand spatial structure based on Voronoi diagram & Delaunay triangulated network[J]. Scientia Silvae Sinicae, 2010, 46(6):78-84.
[21] Li Yuanfa, Ye Shaoming, Hui Gangying, et al. Spatial structure of timber harvested according to structure-based forest management[J]. Forest Ecology and Management, 2014, 322:106-116.
[22] Daniels R F. Simple competition indices and their correlation with annual loblolly pine tree growth[J]. Forest Science, 1976, 22(4):454-456.
[23] Sannikova N S, Sannikov S N, Petrova I V, et al. Competition factors of edificator tree stand:Quantitative analysis and synjournal[J]. Russian Journal of Ecology, 2012, 43(6):426-432.
[24] 汤孟平, 陈永刚, 施拥军, 等. 基于Voronoi图的群落优势树种种内种间竞争[J]. 生态学报, 2007(11):4707-4716.
[25] 刘帅. 天然次生林林分结构分析及多目标智能优化研究[D]. 长沙:中南林业科技大学, 2017.
[26] 方景, 孙玉军, 郭孝玉, 等. 基于Voronoi图和Delaunay三角网的杉木游憩林空间结构[J]. 林业科学, 2014, 50(12):1-6.
[27] 赵春燕, 李际平, 李建军. 基于Voronoi图和Delaunay三角网的林分空间结构量化分析[J]. 林业科学, 2010, 46(6):78-84.
[28] 曹小玉, 李际平, 封尧, 等. 杉木生态公益林林分空间结构分析及评价[J]. 林业科学, 2015, 51(7):37-48.
[29] 李建军, 李际平, 刘素青, 等. 红树林空间结构均质性指数[J]. 林业科学, 2010, 46(6):6-14.
[30] 赵中华, 惠刚盈, 袁士云, 等. 小陇山锐齿栎天然林的树种多样性和结构特征[J]. 林业科学研究, 2008(5):605-610.
[31] 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[J]. 北京林业大学学报, 2014, 36(4):1-7.
[32] Li Jianjun, Zhu Kaiwen, Liu Shuai, et al. Introducing tree neighbouring relationship factors in forest pattern spatial analysis:weighted Delaunay triangulation method[J/OL]. Journal of Forestry Research, 2021:1-11. http://Introducing tree neighbouring relationship factors in forest pattern spatial analysis:weighted Delaunay triangulation method(cnki.net).
[33] 刘玉平, 杨志高, 李丹, 等. 基于加权三角网的林分空间结构综合指数模型[J]. 中南林业科技大学学报, 2020, 40(9):79-87.
[34] 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).
Outlines

/