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油松天然林与人工林物种丰富度及最小面积的比较研究
Study on the species richness and minimum sampling area in both natural and artificial Pinus tabulaeformis forests
【摘要】 天然油松林与人工油松林物种结构等方面存在一定差异,其群落物种丰富度和最小面积也不同。本文对河北蔚县的天然次生油松林和人工油松林的物种丰富度及木本植物群落最小面积进行了探讨。结果表明,油松天然林乔木物种丰富度较人工林高,乔木幼苗幼树差距不大,灌木物种丰富度比人工林高,草本物种丰富度比人工林低。从总的物种组成来看,天然油松林与人工油松林具有较高的相似性。用8个模型对天然林和人工林木本植物种-面积曲线分别进行了拟合,并确定各自的最优模型,得出各取样比例时的最小面积。结果表明,当所取物种比例为0.6及以下时,天然林的最小面积小于人工林;而所取比例为0.7及以上时,天然林的最小面积大于人工林。
【Abstract】 Pinus tabulaeformis is one of the dominant species in Hebei mountainous areas.There are differences in species structures,species richness and the minimum sampling area between the natural and artificial Pinus tabulaeformis forests.This paper discussed the differences of species richness and woody plants’ minimum sampling area between the natural and artificial Pinus tabulaeformis forests in Yuxian County,Hebei province.The results showed that the species richness of arbors in the natural Pinus tabulaeformis forests was higher than that of artificial forest,but there were only a few differences among the arbor seedlings.Compared with the artificial forest,the shrub species richness was higher and the herbage species richness was lower in natural forest.The similarity index of all species was high between the natural and artificial Pinus tabulaeformis forests.With 8 models we fitted the species-area curves of woody plants of both natural and artificial Pinus tabulaeformis forests,chose the respective optimal models, and obtained the minimum sampling area of each sample proportion.The results showed that when the species sample proportion was lower then 0.6,the natural forest’s minimum sampling area was smaller than the artificial forest’s and when the sample proportion was not below 0.7,the natural forest’s minimum sampling area was bigger than that of artificial forest.
【Key words】 Yuxian County of Hebei province; Pinus tabulaeformis forest; natural forest; artificial forest; species richness; minimum sampling area;
- 【文献出处】 河北林果研究 ,Hebei Journal of Forestry and Orchard Research , 编辑部邮箱 ,2007年02期
- 【分类号】S791.254
- 【被引频次】3
- 【下载频次】229