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Position: Home > Articles > Spatial structure characteristics of Cyclobalanopsis elevaticostata natural forests in the Zhiti Mountain of Fujian Province Journal of Gansu Agricultural University 2012,47 (6) 101-107

福建支提山突脉青冈天然林林分空间结构研究

作  者:
盖新敏
单  位:
福建省宁德市林业局
关键词:
突脉青冈;空间结构;混交度;大小比数;角尺度;支提山
摘  要:
利用混交度、大小比数和角尺度等3种结构参数,分析了福建支提山突脉青冈天然林的空间结构.结果表明:突脉青冈、少叶黄杞、细柄阿丁枫、白楠等优势树种混交度低,呈弱度混交,同树种单种聚集在一起的情况较多;其他树种中,较强度、强度混交占了很大的比例.突脉青冈天然林分的树种空间大小分化和大小组合的差异极大,枫香、罗浮栲、椤木石楠在空间大小对比上占有一定的优势,而杨梅、槭树、山茶、锥栗等树种受压严重.根据角尺度分析,福建支提山突脉青冈天然林整体分布格局属不均匀分布.
译  名:
Spatial structure characteristics of Cyclobalanopsis elevaticostata natural forests in the Zhiti Mountain of Fujian Province
作  者:
GAI Xin-min(Ningde Municipal Forestry Bureau,Ningde 352100,China)
关键词:
Cyclobalanopsis elevaticostata;spatial structure;mingling degree;neighborhood comparison;uniform angle index;the Zhiti Mountain
摘  要:
Three spatial structure parameters,mingling degree,neighborhood comparison and uniform angle index,were used to analyze the spatial structure characteristics of Cyclobalanopsis elevaticostata natural forests in the Zhiti Mountain of Fujian Province.The results showed that the mingling degree of Cyclobalanopsis elevaticostata,Engelhardtia fenzelii,Altingia graeilipes,Phoebe neurantha and other dominant tree species were low,indicating mixed at low level,and the same single species had the high degree of aggregation.Among the other species,mingling degree was high.There were great differences in differentiation and composition of spatial structure of Cyclobalanopsis elevaticostata natural forests.When using neighborhood differentiation and contrasting to characterize the size differentiation of trees,the Liquidambar formosana,Castanopsis fabri,Photinia davidsoniae had an advantage over other species,and Myrica rubra,Acer campbellii,Camellia japonica,Castanea henryi and other species were under serious pressure.According to angle criterion analysis,spatial distribution pattern of Cyclobalanopsis elevaticostata natural forest in the Zhiti Mountain should belong to the pattern of clustering distribution.

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