大兴安岭天然次生林林木补植空间优化
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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。
[Objective] This 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. [Method] Taking 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 to0.78, 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. [Conclusion] Harvesting 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.
[Objective] This 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. [Method] Taking 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 to0.78, 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. [Conclusion] Harvesting 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.
引文
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[2]吕英.大兴安岭林区生态可持续发展问题研究[D].北京:中国农业科学院,2009.LüY.Research on sustainable development strategy for Daxing’anling forests region[D].Beijing:Gradeuate School of Chinese Academy Agricultural Sciences,2009.
[3]Yu D,Zhou L,Zhou W,et al.Forest management in Northeast China:history,problems,and challenges[J].Environmental Management,2011,48(6):1122-1135.
[4]于立忠,刘利芳,王绪高,等.东北次生林生态系统保护与恢复技术探讨[J].生态学杂志,2017,36(11):3243-3248.Yu L Z,Liu L F,Wang X G,et al.Discussion on the protcetion and restoration technology of secondary forest esosystems in Northeast China[J].Chinese Journal of Ecology,2017,36(11):3243-3248.
[5]Deng X Z,Jiang Q,Zhan J Y,et al.Simulation on the dynamics of forest area changes in Northeast China[J].Journal of Geographical Sciences,2010,20(4):495-509.
[6]赵春燕,李际平.基于Voronoi图与Delaunay3角网的杉木人工纯林林木补植位置与空间配置[J].中南林业科技大学学报,2017,37(2):1-8.Zhao C Y,Li J P.Spatial location and allocation of replanting trees on pure Chinese fir plantation based on Voronoi diagram and Delaunay triangulation[J].Journal of Central South University of Forestry&Technology,2017,37(2):1-8.
[7]Nordlander G,Hellqvist C,Hjelm K.Replanting conifer seedlings after pine weevil emigration in spring decreases feeding damage and seedling mortality[J].Scandinavian Journal of Forest Research,2017,32(1):60-67.
[8]Sofawi A B,Rozainah M Z,Normaniza O,et al.Mangrove rehabilitation on Carey Island,Malaysia:an evaluation of replanting techniques and sediment properties[J].Marine Biology Research,2017,13(4):390-401.
[9]宋启亮,董希斌.大兴安岭低质阔叶混交林不同改造模式综合评价[J].林业科学,2014,50(9):18-25.Song Q L,Dong X B.Comprehensive evaluation of different transformation models of low-quality broadleaved mixed forest in Daxing’an Mountains[J].Scientia Silvae Sincae,2014,50(9):18-25.
[10]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,2004,40(5):25-31.Tang M P,Tang S Z,Lei X D,et al.Study on spatial structure optimizing model of stand selection cuttuing[J].Scientia Silvae Sincae,2004,40(5):25-31.
[11]姜廷山,董灵波,刘兆刚,等.不同抚育强度对兴安落叶松林空间结构的影响[J].东北林业大学学报,2018,46(12):9-14.Jiang T S,Dong L B,Liu Z G,et al.Effects of different intermediate cutting intensities on the spatial structure of Larix gmelinii forest[J].Journal of Northeast Forestry University,2018,46(12):9-14.
[12]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.Li J P,Feng Y,Zhao C Y,et al.Quantitative analysis of stand spatial structure of Cunninghamia lanceolate non-commercial forest based on Voronoi diagram[J].Journal of Beijing Forestry University,2014,36(4):1-7.
[13]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[J].林业科学,2017,53(1):28-37.Liu S,Zhang J,Li J J,et al.Edge correction of voronoi diagram in forest spatial structure analysis[J].Scientia Silvae Sincae,2017,53(1):28-37.
[14]董灵波,刘兆刚,马妍,等.天然林林分空间结构综合指数的研究[J].北京林业大学学报,2013,35(1):16-22.Dong L B,Liu Z G,Ma Y,et al.A new composite index of stand spatial structure for natural forest[J].Journal of Beijing Forestry University,2013,35(1):16-22.
[15]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,2007,27(11):4707-4716.Tang M P,Chen Y G,Shi Y J,et al.Intranspecific and interspecific competition analysis of community dominant plant populations based on Voronoi diagram[J].Acta Ecologica Sinica,2007,27(11):4707-4716.
[16]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.Tang M P,Zhu G M,Chen Y G,et al.Mingling of evergreen broad-leaved forests in Tianmu Mountain[J].Scientia Silvae Sincae,2009,45(6):1-5.
[17]张弓乔,惠刚盈.Voronoi多边形的边数分布规律及其在林木格局分析中的应用[J].北京林业大学学报,2015,37(4):1-7.Zhang G Q,Hui G Y.Analysis and application of polygon side distribution of Voronoi diagram in tree patterns[J].Journal of Beijing Forestry University,2015,37(4):1-7.
[18]董灵波,刘兆刚.樟子松人工林空间结构优化及可视化模拟[J].林业科学,2012,48(10):77-85.Dong L B,Liu Z G.Visual management simulation for Pinus sylvestris var.mongolica plantation based on optimized spatial structure[J].Scientia Silvae Sincae,2012,48(10):77-85.
[19]张家诚,陈力,蒋有绪,等.演替顶极阶段森林群落优势树种分布的变动趋势研究[J].植物生态学报,1999,23(3):256-268.Zhang J C,Chen L,Jiang Y X,et al.Research on the chang treed of dominant tree population distribution patterns during development process of climax forest communities[J].Acta Phytoecologica Sinica,1999,23(3):256-268.
[20]惠刚盈,Klaus von Gadow,Matthias Albert.角尺度:一个描述林木个体分布格局的结构参数[J].林业科学,1999,35(1):37-42.Hui G y,von Gadow K,Albert M.The neighbourhood pattern:a new structure papameter for describing distribution of forest tree position[J].Scientia Silvae Sincae,1999,35(1):37-42.
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