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当前位置: 首页 > 文章 > 长白山阔叶红松林表层土壤木本植物细根生物量及其空间分布 应用生态学报 2010,21 (3) 583-589
Position: Home > Articles > Woody plant fine root biomass and its spatial distribution in top soil of broad-leaved Korean pine forest in Changbai Mountain Chinese Journal of Applied Ecology 2010,21 (3) 583-589

长白山阔叶红松林表层土壤木本植物细根生物量及其空间分布

作  者：
王树堂;韩士杰;张军辉;王存国;徐媛;李雪峰;王树起
单  位：
中国科学院沈阳应用生态研究所
关键词：
细根;地统计学;变异函数;贝叶斯统计
摘  要：
2008年在长白山北坡原始阔叶红松林内选择3块50m×50m样地,采用地统计学方法对表层土壤中木本植物细根生物量及其分布特征进行了定量研究.结果表明:3块样地0～20cm土层中木本植物活细根生物量分别为3.195、1.930和2.058t·hm-2,死细根生物量分别为0.971、0.581和0.790t·hm-2,0～10cm土层中,死、活细根生物量之间无显著相关关系,而10～20cm土层中,二者呈显著正相关关系(r=0.352,P<0.05),死、活细根生物量的实际变异函数大多符合球状理论模型.空间自相关引起的空间异质性占总空间异质性的百分比平均大于70%,各样地活、死细根生物量变程分别为5.2、14.6、9.8m和4.3、20.4、20.1m.采用贝叶斯统计方法对3块样地活细根生物量空间自相关范围进行估计的结果与地统计学方法的统计结果一致.
译  名：
Woody plant fine root biomass and its spatial distribution in top soil of broad-leaved Korean pine forest in Changbai Mountain
作  者：
WANG Shu-tang1,2, HAN Shi-jie1, ZHANG Jun-hui1, WANG Cun-guo1, XU Yuan1, LI Xue-feng1, WANG Shu-qi1 (1Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China; 2Graduate University of Chinese Academy of Sciences, Beijing 100049, China).
关键词：
fine roots; geostatistics; semivariogram; Bayesian statistics
摘  要：
Geostatistic method was applied to study the spatial distribution of woody plant fine root biomass in a natural broad-leaved Korean pine (Pinus koraiensis)mixed forest soil in Changbai Mountain. The investigation was carried out in three selected plots, sized 50 m×50 m, in 2008. In the three plots, the living fine root biomass in surface soil (0-20 cm) was 3.195, 1.930, and 2.085 t·hm-2, and the dead fine root biomass was 0.971, 0.581, and 0.790 t ·hm-2, respectively. In 0-10 cm soil layer, the living fine root biomass had no correlation with the dead fine root biomass; but in 10-20 cm soil layer, a significant positive correlation was found between them (r=0.352,P<0.05). The variograms of living fine root biomass and dead fine root biomass could be well fitted by spherical model. Spatial variation explained more than 70% of the total variance of fine root biomass across three plots. The regressed ranges were 5.2, 14.6, and 9.8 m for living fine root biomass, and 4.3, 20.4, and 20.1 m for dead fine root biomass in plots 1, 2, and 3, respectively. For comparison, Bayesian method was also used to estimate the ranges for the fine root biomass. The results obtained by geostatistic method and Bayesian method were consistent with each other.

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