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Spatial Distribution of Fine Roots of a Robinia pseudoacacia Plantation in Yangou Watershed in the Hilly Region of the Loess Plateau

黄土丘陵区燕沟流域人工刺槐林的细根空间分布特征


对黄土丘陵区燕沟流域10年生人工刺槐林的细根生物量、比根长、根长密度和根面积指数的空间分布特征,以及这些根系参数与土壤物理因子(土壤含水量、土壤温度和土壤密度)的关系进行研究。结果表明: 1) 人工刺槐林细根在 0~180 cm土层中随深度呈层次性衰减(a,b,c,d,e); 其中,细根生物量、根长密度和根面积指数等随深度变化均可用负指数函数描述,根系集中分布在0~60 cm土层,峰值都在0~20 cm土层,该土层3项指标分别占各自0~60 cm土层总量的42.72%,44.44%和47.14%; 比根长随深度增加衰减趋势较弱,在80~140 cm 土层中出现反复,其随土层深度的变化可用三次多项式描述。 2) 细根生物量、根长密度和根面积指数等均随距树干基部的距离增加而减小,比根长在0~40 cm随距树干距离增加而增加,在40~80 cm达到最大值,120~160 cm内最少。 3) 根系分布受环境因子影响,其影响程度依次为: 土壤温度>土壤含水量>土壤密度,建立根系参数与土壤物理因子的多元线性回归模型,模型均达到95%以上显著水平。

The spatial distribution of fine root biomass, specific root length(SRL), root length density(RLD), the root surface area index of the 10-year-old Robinia pseudoacacia plantation were investigated in hilly Loess Plateau region, and relationships between these root parameters and the soil environment factors(e.g. soil moisture content, soil temperature and soil bulk density) were analyzed. The results showed that, 1) the amount of fine roots decreased with depth of soil from 0 to 180 cm (the soil was divided into five layers; a, b, c, d and e layer). The change of the fine root biomass, RLD and the root area index with the depth could be described by a negative exponential function. The roots distributed mainly in the 0-60 cm soil layers and the peaks of the three parameters all appeared in the 0-20 cm, accounted for 42.72%, 44.44% and 47.14% of those amounts from 0-60 cm soil layers, respectively. SRL did not decrease much with soil depth, and even appeared reverse in the 80-140 cm soil layers. The relationship between the SRL and the soil depth could be described by a cubic polynomial. 2) With increasing horizontal distance from the tree trunk, the fine root biomass, RLD and the root area index decreased gradually. The SRL increased in the range of 40-80 cm and 120-160 cm respectively. 3) The environmental factors strongly influenced the root distribution, and the influence degree was in an order: Soil temperature>soil moisture content>soil bulk density. A multivariate linear regression model was established between root parameters and environmental factors and the model achieved 95% significant level.


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