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Research And Application For Fine Root Vertical Distribution Of Main Planting Tree Species' Model In The Loess Plateau

Posted on:2006-03-31Degree:MasterType:Thesis
Country:ChinaCandidate:X R ChengFull Text:PDF
GTID:2133360155455631Subject:Forest cultivation
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Method of soil-drilling was used to research fine root vertical distribution characters of Robinia pseudoacacia,Pinus tabulaeformis,Platycladus orientalis,Populus simonii and Caragana korshinkii in different sites in Ansai county and Changwu county in the Loess Plateau. The results showed as follows: â‘ The fine root vertical distribution characters of these tree species manifest analogous change pattern both in north-site and south-site in Ansai county, and all of them got their maximal distribution values under the soil surface (0~20cm), then decreasing slowly with soil depth going down until 250cm. â‘¡Robinia pseudoacacia's fine root vertical distribution characters values (away from stem 0.5 m) gradually augmented with the increase of soil depth in different sites in Changwu county, which got its maximal distribution characters values in a certain soil depth that was 60cm away from soil surface, and fine root slowly decrease until 180cm, another distribution peak appeared in soil depth from 180cm to 200cm; the whole distribution in section showed two different peaks. â‘¢The fine root vertical distribution characters (away from stem 0.5 m) of Robinia pseudoacacia was significant different in Ansai and Changwu. The depth of fine root vertical distribution was 250cm in Ansai, and was only 200cm in Changwu. The fine root surface areas values in Ansai were obviously more than Changwu, the average values both in north-site and south-site in Ansai were 5.06 times and 8.29 times respectively compared with Changwu's. Robinia pseudoacacia's fine root vertical distribution characters of the whole section also had many differences both in north-site and south-site in these two places. The fine root surface areas values showed maximal distribution values under the soil surface (0~20cm) and then slowly decrease in Ansai. But the whole distribution in section showed two different peaks in Changwu. In addition, the fine root surface areas values were bigger in north-site than in south-site both in Ansai and Changwu. The difference of Robinia pseudoacacia's fine root vertical distribution characters was significantly related to soil water environment, which was a key factor to influence fine root distribution. Take Robinia pseudoacacia as a research object because it was one of the most extensive planting tree species in the Loess Plateau, according to its fine root vertical distribution characters, through compare and analysis to different mathematical model, a model which had six parameters to describe Robinia pseudoacacia's fine root vertical distribution was established, with fine root surface areas as index. The model can better reflected Robinia pseudoacacia's fine root vertical distribution characters in this area, the fit decide coefficient ( R2 ) more than 0.94. B was most important among the parameters, which decided the depth of the fine root most distribution values, as B was smaller, the fine root distribution was closer to the soil surface. The maximal depth of fine root distribution and the depth of fine root got maximal distribution values hp in theory can be determined, and also can got the fine root growth's maximal depth hq which influenced by soil permeate water, hq approximately was considered as the boundary point of soil permeate water and deep-site water to fine root growth. According to the model of Robinia pseudoacacia's fine root vertical distribution, the soil water of Robinia pseudoacacia's woodland in section can be divided into three layers: the first layer was water exchange activity layer, which was from soil surface to hp, which was greatest influenced by precipitation; the second was soil water attenuation layer, which was between hp and hq , influenced by precipitation, water and fine root vertical distribution had the same change trend in the layer, they were all slow decreases from hp to hq; the third was soil water relative stabilization layer, which was under hq, hereunder soil water became relative stabilization. The model explained the relationship between fine root distribution and soil water in this area of Loess Plateau, which opened out root system and soil water's mutual mechanism in a certain extent, and helped to lucubrate the reason of soil drification. In order to extend the model's applicability, used the model to fit Robinia pseudoacacia's fine root vertical distribution in Changwu county in the southern Loess Plateau and got better result. Meanwhile, according to fine root vertical distribution characters of different tree species, other main tree species'fine root vertical distribution were also be fitted in Ansai. The fitted results showed that the model better simulated Pinus tabulaeformis,Platycladus orientalis and Caragana korshinkii's fine root vertical distribution (R2 were respective 0.8602,0.8884,0.8401),but for Populus simonii's simulates was not good(R2=0.6786). Synthetically analysis these tree species'fine root vertical distribution characters and brought forward a new concept-fine root dense distribution exponential (FRDDE),which can be quantitatively showed the fine root shape distribution character. FRDDE referred to the ratio between the soil depth of fine root denseness distribution and the maximal soil depth. The ratio was bigger, the range of fine root denseness distribution was wider. On the contrary, the ratio was smaller which showed there were many fine root distribute in the soil surface. From what has discussed above can drawn the conclusion that the model can best be reflected different tree species'fine root vertical distribution characters when FRDDE was about 0.5, and if the exponential was belong to the range from 0.4 to 0.65 which also can better simulates, whereas if FRDDE was too big or small can't got good simulation effect.
Keywords/Search Tags:Loess Plateau, planting tree species, fine root vertical distribution, model, sites
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