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The spatial distribution of fine root can reflect the forests to adapt and improve the function of the environment. The study by coring samples of the Loess Hilly District Yangou basin 10a and 25a of Health artificial locust woodland roots in the growing season, and its root biomass, fine root root length, the fine root root length density and fine roots The spatial distribution of the root area index characteristics, as well as the analysis of these root parameters and soil physical properties (soil moisture, soil temperature and soil bulk density) and soil nutrient relationships. Made the following findings: (1) plantation locust root standing biomass characteristics: both plantation locust roots the standing biomass 11316.54 gm -2 and 17621.10gm -2 , where the biomass of live fine roots (≤ 2mm) accounted for 16.59% and 11.73%, respectively, live coarse roots (gt; 2mm) biomass accounted for 81.52% and 86.16 dead fine root biomass accounted for 1.89% and 2.11% respectively. . Meanwhile, age greater the bigger root diameter, root spatial distribution of the heterogeneity of the greater. (2) Seasonal dynamics of the plantation locust roots: both plantation locust roots (fine roots and coarse roots) biomass has the summer (July) and fall (October) two peak seasonal variation differences reached significant level (except 25a Lin coarse root biomass) (p lt; 0.05); same root length density and root area index and biomass seasonal variation, showed a \) 25a Lin seasonal changes differences significant (p lt; 0.05); specific root length as \· g -1 , the seasonal variation was highly significant or significant level. (3) the spatial distribution characteristics of plantation locust fine roots: both plantation locust fine roots 0 2 00 cm soil layer was layered with depth attenuation (a, b, c, d e 5 layers); fine root biomass, root length density and root area index decreased with soil depth variation are available negative exponential function description, the root system is concentrated in the 0 6 0 cm soil layer, the peak are in the 0 2 0 cm soil layer, respectively, accounting for each 0 6 0 cm soil 42.56% and 46.66%, 47.12% and 50.00%, 43.44% and 47.60% ; rather than the root length with depth attenuation trend weakened repeatedly appear in the profiles of 60 ~ 140 cm with soil depth cubic polynomial can be used to describe. Both plantation locust fine root biomass, root length density and root area index are decreased with distance to increase the distance of the base of the trunk, the increased trend of first increase and then decreases with the distance from the stem than root length, maximum 80 cm away from the base of the trunk, but the various parameters in the plant spacing within a minor change. (4) plantation locust root distribution the feature parameter β performance: of both plantation fine root root weaken coefficient decreases with increasing distance from the stem, max 40cm at 0.989 and 0.990, respectively, the minimum value in the 160cm at, respectively, 0.983 and 0.986; coarse roots the roots weaken coefficient with fine root variation, maximum at 40cm at 0.984 and 0.985, respectively, minimum 120cm Department, are 0.982; plant spacing range, both plantation average fine root root weaken coefficient β value (0.988 and 0.991) were greater than the coarse root root weaken coefficient β value (0.983 and 0.984), 25a forest the roots weaken coefficient greater than 10a Lin, said the breakdown of the root distribution depth in coarse roots, stand age increased rooting depth increased, conducive to locust on deep soil moisture and nutrient absorption and utilization. (5) plantation locust fine roots and soil environment relations: the locust fine root distribution by soil physical properties affect the order of soil moisture gt; soil bulk density gt; soil temperature; locust fine root distribution by the degree of soil chemical properties in order soil total nitrogen gt; soil organic matter gt; soil ammonium nitrogen gt; soil nitrate, established root parameters and soil physical and chemical factors, multiple linear regression model, the model reached the 95% level of significance.
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