岷江上游山地森林—干旱河谷交错带土壤抗蚀力研究
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摘要
环境问题是当今国际关注的热点问题,而土壤侵蚀则是全球性主要生态环境问题之一。土壤侵蚀可导致土地资源退化和损失,是限制当今人类生存与发展的全球性环境灾害。本研究通过野外调查和室内分析相结合的方法,针对岷江上游山地森林-干旱河谷交错带生态环境建设的需求和土壤侵蚀研究的重要内容,研究了不同植被条件下土壤抗蚀、抗冲性特征、土壤可蚀性K值变化特征及其影响因素,以期揭示区域土壤侵蚀的本质,为研究区域退耕还林及生态环境建设提供理论依据。主要研究结果如下:
     1、不同植被条件下土壤抗蚀性变化特征及其影响因素
     阳坡坡面,退耕岷江柏林地土壤抗蚀性最好,岷江柏幼林和天然次生林地土壤抗蚀性次之,刺槐林地土壤抗蚀性最小。0-10 cm土层土壤抗蚀性强于10-20 cm,且在各土层间不同植被条件下土壤抗蚀性指数均达显著差异。阴坡坡面,杂草地土壤抗蚀性最强,灌木林和岷江柏幼林地土壤抗蚀性次之,天然次生林地土壤抗蚀性最小。
     阳坡坡面,0—10 cm土层,土壤机械组成中砂粒与抗蚀指数、水稳性指数、团聚度呈显著或极显著负相关;物理性粘粒与抗蚀指数、水稳性指数、结构系数、团聚度呈显著或极显著正相关,中、细粉粒与水稳性指数和结构系数呈显著或极显著正相关,与分散系数均呈极显著负相关。微团聚体组成中,<0.001 mm颗粒与抗蚀指数呈显著负相关,与水稳性指数呈显著正相关。10-20 cm土层,机械组成中砂粒与团聚度、物理性粘粒与分散系数呈极显著负相关;粗粉粒与团聚度、物理性粘粒与结构系数和团聚度呈极显著正相关。微团聚体组成中,1-0.05 mm颗粒与团聚度呈显著负相关。阴坡坡面,0-10cm土层,砂粒与抗蚀指数、结构系数、团聚度之间呈显著或极显著负相关,与分散系数呈显著正相关;粗粉粒与团聚度之间呈极显著正相关;物理性粘粒与结构系数呈显著正相关,中、细粉粒与抗蚀指数、水稳性指数、结构系数之间呈显著或极显著正相关,与分散系数均呈极显著负相关。微团聚体组成中,1—0.05 mm颗粒与分散系数之间呈显著正相关,与结构系数呈显著负相关;<0.001 mm颗粒与抗蚀指数、水稳性指数、结构系数、团聚度之间呈显著或极显著负相关,与分散系数呈显著正相关。10-20 cm土层,机械组成和微团聚体中不同粒级的颗粒与各抗蚀指标之间的的相关性均不显著。
     阳坡坡面,0-10 cm土层,抗蚀指数、水稳性指数、结构系数、团聚度与有机质、全氮含量之间呈显著正相关;水稳性指数、结构系数、团聚度与速效钾含量之间呈显著负相关;分散系数与有机质、全氮含量之间呈显著负相关,与速效钾含量之间呈显著正相关。10-20 cm土层,抗蚀指数、水稳性指数与有机质含量之间呈显著正相关;水稳性指数、结构系数与速效钾含量之间呈显著负相关;分散系数与速效钾含量之间呈显著正相关;团聚度与土壤化学性质的相关性均未达到显著。阴坡坡面,0-10 cm土层,抗蚀指数、水稳性指数、结构系数与有机质含量之间呈显著正相关;抗蚀指数、水稳性指数、团聚度与速效磷含量之间呈极显著负相关;分散系数与有机质含量之间呈显著负相关。10-20 cm土层,抗蚀指数、水稳性指数与有机质含量之间呈显著正相关,与速效磷含量之间呈极显著负相关。
     2、不同植被条件下表层土壤侵蚀率与其物理性质的关系
     不同植被条件下表层(0—10 cm)土壤侵蚀率介于6.51%-21.34%之间,平均土壤侵蚀率为13.18%,以土壤侵蚀率>10%的样地为主体,土壤侵蚀较为严重。退耕岷江柏林地土壤侵蚀率最低;刺槐林植被的土壤侵蚀率最高。土壤有机质含量、结构破坏率、团聚体MWD和团聚体GMW、>0.25 mm水稳性团聚体含量对表层不同植被条件下土壤侵蚀率影响较大。
     3、不同植被条件下土壤抗冲性变化特征及其影响因素
     不同植被条件下土壤径流量随冲刷时间的变化较明显,总体上曲线呈单峰变化、先增大后减小。对照裸地(CK)径流随时间变化量低于灌木林地,但高于其他植被条件。灌木林地和对照裸地(CK)随着冲刷时间延长,径流量变化幅度较大;天然次生林、岷江柏幼林地在冲刷全过程中径流量变化幅度较小。不同植被条件下土壤冲刷过程中含沙量呈先降低后趋于平缓的变化规律。退耕岷江柏林、灌木林和岷江柏幼林地在产流过程中径流含沙量随时间变化较平稳,其中退耕岷江柏林地林含沙量最小。混交林地含沙量总体较小,趋于稳定的时间滞后于其他植被条件。不同植被条件下土壤抗冲指数依次为退耕岷江柏林>岷江柏幼林>刺槐林>灌木林>天然次生林>混交林幼林>裸地(CK)。
     不同植被条件下,土壤容重与抗冲指数呈显著负相关,微团聚体组成中<0.001 mm颗粒与土壤抗冲指数间呈显著正相关,其他粒级颗粒与与土壤抗冲指数之间的相关性也均未达到显著。土壤速效磷与抗冲指数呈显著负相关,土壤有机质、全氮、速效钾与抗冲指数之间的相关性均未达到显著。
     4、不同植被条件下土壤可蚀性变化特征及其影响因素
     0-10 cm土层,阳坡坡面各植被条件下土壤的可蚀性K值大小表现为:刺槐林>混交林幼林>灌木林>岷江柏幼林>天然次生林>退耕岷江柏林;阴坡各植被条件下土壤的可蚀性K值大小表现为:天然次生林>灌木林>杂草地>岷江柏幼林。10-20 cm土层,阳坡坡面各植被条件下土壤的可蚀性K值大小表现为:刺槐林>混交林幼林>天然次生林>退耕岷江柏林>岷江柏幼林>灌木林;阴坡各植被条件下土壤的可蚀性K值大小表现为:杂草地>天然次生林>灌木林>岷江柏幼林。不同植被条件下土壤可蚀性变化与其抗蚀性较为一致,可见,采用EPIC模型估算研究区域土壤可蚀性K值是可行的。
     0-10 cm土层,不同植被条件下土壤可蚀性K值与土壤有机碳、全氮和粉粒含量呈极显著负相关,与砂粒含量呈极显著正相关。10-20 cm土层,不同植被条件下土壤可蚀性K值与土壤有机碳、全氮含量呈极显著负相关,与粉粒含量却呈极显著正相关。
The environmental issues have been arisen broad attention, while the soil erosion is one of the global environment problems. Soil erosion is the main cause the degeneration and loss of land source, which is an kind of natural disaster to restrict the human survival and the development for today's global environment. By the methods of field investigation and laboratory analysis, change characteristics of soil anti-erodibility, soil anti-scourability, soil erodibility and their influence factors were studied under different vegetations in dry valley and montane forest at the upstream of Minjiang River. The study is not only the need of ecology construction, but also it is the important contents of soil erosion. At the same time, the study would help to reveal the essence of soil erosion and provide theoretical basis for the ecology construction and conversion of farmland to forestry.
     1.Characteristics and influence factors of soil anti-erodibility under different vegetations
     On sunny slopes, soil anti-erodibility was the strongest for the conversion of farmland to Minjiang cypress, followed Minjiang young cypress and natural secondary forests. However, soil anti-erodibility was the poorest for the Robinia pseudoacacia. Soil anti-erodibility of 0-1 Ocm layer was higher than that of 10-20 cm layer. At the same time, there were significant difference among the index of soil anti-erodibility in the 0-10 cm and 10-20 cm layer under the different vegetations. On shady slopes, soil anti-erodibility was the strongest for the weed, followed the shrub and Minjiang young cypress. However, soil anti-erodibility was the poorest for the natural secondary forests.
     On sunny slopes, they were significantly negative correlation between sand fraction of mechanical composition and index of soil anti-erodibility, water stable index, aggregation degree in 0-10 cm layer. However, they were significantly positive correlation between physical clay and index of soil anti-erodibility, water stable index, structural granular index, aggregation degree. They were significantly positive correlation between medium-fine dust and water stable index, structural granular index. However, they were significantly negative correlation between medium-fine dust and soil dispersion coefficient. They were significantly negative correlation between<0.001mm content of micro-aggregate composition and index of soil anti-erodibility, they were significantly positive correlation between<0.001mm content of micro-aggregate composition and water stable index. In 10-20 cm layer, they were significantly negative correlation between sand fraction of mechanical composition and aggregation degree, physical clay, soil dispersion coefficient, however, they were significantly positive correlation between coarse dust of mechanical composition and aggregation degree. They were significantly positive correlation between physical clay of mechanical composition and aggregation degree, structural granular index. They were significantly negative correlation between content of at the size of 1-0.05mm in micro-aggregate composition and aggregation degree.
     On shady slopes, they were significantly negative correlation between sand fraction of mechanical composition and index of soil anti-erodibility, structural granular index, soil aggregation degree in 0-10 cm layer. However, they were significantly positive correlation between sand fraction of mechanical composition and soil dispersion coefficient. They were significantly positive correlation between coarse dust of mechanical composition and soil aggregation degree.They were significantly positive correlation between physical clay and structural granular index. They were also significantly positive correlation between medium-fine dust and index of soil anti-erodibility, water stable index, soil structural granular index. However, they were significantly negative correlation between medium-fine dust of mechanical composition and soil dispersion coefficient. In 0-10 cm layer, they were significantly positive correlation between content of at the size of 1-0.05 mm in micro-aggregate composition and soil dispersion coefficient, however, they were significantly negative correlation between content of at the size of 1-0.05mm in micro-aggregate composition and soil structural granular index. They were significantly negative correlation between content of at the size of<0.001 mm in micro-aggregate composition and index of soil anti-erodibility, water stable index, soil structural granular index,soil aggregation degree, however, they were significantly positive correlation between content of at the size of<0.001 mm in micro-aggregate composition and soil dispersion coefficient. In 10-20 cm layer, there were no significantly different between content of different particles and all indexes of soil anti-erodibilityfor the micro-aggregate composition and soil mechanical composition under different vegetations.
     On sunny slopes, they were significantly positive correlation between index of soil anti-erodibility, water stable index, structural granular index, soil aggregation degree and soil organic mater, content of soil total N in 0-10 cm layer, however, they were significantly negative correlation between water stable index structural granular index, soil aggregation degree and content of soil available K. They were significantly negative correlation netween soil dispersion coefficient and soil organic mater, content of total N, however, they were significantly negative correlation between soil dispersion coefficient and content of soil available K. In 10-20cm layer, they were significantly positive correlation between index of soil anti-erodibility, water stable index and soil organic mater. However, they were significantly negative correlation between water stable index, soil structural granular index and content of soil available K. They were also significantly positive correlation between soil dispersion coefficient and content of soil available K. However, there were no significant differences between soil aggregation degree and soil chemical properties.
     On shady slopes, they were significantly positive correlation between index of soil anti-erodibility, water stable index, structural granular index and soil organic mater in 0-10 cm layer. However, they were significantly negative correlation between index of soil anti-erodibility, water stable index, soil aggregation degree and content of soil available P. At the same time, they were significantly negative correlation between soil dispersion coefficient and soil organic mater. In 10-20cm layer, they were significantly positive correlation between index of soil anti-erodibility, water stable index and soil organic mater. However, they were significantly negative correlation between index of soil anti-erodibility, water stable index and content of soil available P.
     2. Relationships between soil erosion rate and soil physical properties in 0-10 cm layer under different vegetations
     Soil erosion rates were from 21.34% to 60.51% under different vegetations, and the average value of soil erosion rate was 13.18%. Soil erosion rate of six vegetations had high proportions of>10%. The value of soil erosion rate was the lowest for the conversion of farmland to Minjiang cypress. However, the value of soil erosion rate was the highest for the Robinia pseudoacacia. These factors had the important effect on soil erosion rate, and these factors included soil organic mater, structure ped breaking ration aggregate mean weight diameter, geometric mean diameter and water stable aggregate of>0.25mm.
     3. Characteristics and influence factors of soil anti-scourability under different vegetations
     Changes of runoff amount were obvious with scouring time under different vegetations. Runoff amount was decrease after increase with the increasing of scouring time under different vegetations. Runoff amount of the control (CK) was lower than that of the shrub, and was higher than that of the other vegetations. Change amplitudes of runoff amount were the higher with the increasing of scouring time for the shrub and the control (CK). Change amplitudes of runoff amount were the lower with the increasing of scouring time for natural secondary forests and Minjiang young cypress. Sediment concentration was flat after decrease with the increasing of scouring time under different vegetations. Sediment concentration was the lowest with the increasing of scouring time for the conversion of farmland to Minjiang cypress. Sediment concentration was the lower with the increasing of scouring time for the mixed young stands, and the time of steady sediment concentration was later than that of the other vegetations.The results demonstrated that soil anti-scouring index changed in the following order of treatments: the conversion of farmland to Minjiang cypress> Minjiang young cypress> Robinia pseudoacacia> the shrub> the mixed young stands> the control (CK).
     Under different vegetations, they were significantly negative correlation between soil anti-scouring index and soil bulk density. They were significantly positive correlation between content of at the size of<0.001 mm in micro-aggregate composition and soil anti-scouring index. They were no significantly diffrent between content of the other particles in micro-aggregate composition and soil anti-scouring index. They were significantly negative correlation between content of soil available P and soil anti-scouring index. However, they were no significantly diffrent between soil anti-scouring index and soil organic mater, content of soil total N, content of soil available K.
     4. Characteristics and influence factors of soil erodibility under different vegetations
     In 0-10 cm layer, the results demonstrated that the value of soil erodibility(K) changed in the following order of treatments:Robinia pseudoacacia> mixed young stands>the shrub> Minjiang young cypress> natural secondary forests> the conversion of farmland to Minjiang cypress on sunny slopes under different vegetations. The results demonstrated that the value of soil erodibility(K) changed in the following order of treatments:natural secondary forests> the shrub>the weed> the conversion of farmland to Minjiang cypress on shady slopes under different vegetations.
     In 10-20cm layer, the results demonstrated that the value of soil erodibility(K) changed in the following order of treatments:Robinia pseudoacacia>mixed young stands>natural secondary forests> the conversion of farmland to Minjiang cypress> Minjiang young cypress>the shrub on sunny slopes under different vegetations.The results demonstrated that the value of soil erodibility(K) changed in the following order of treatments:the weed> natural secondary forests> Robinia pseudoacacia> Minjiang young cypress on shady slopes under different vegetations. They showed the same change between soil anti-scourability and soil erodibility under different vegetations. So, EPIC model was available for estimating soil erodibility in ecotone between dry valley and montane forest.
     In 0-10 cm layer, they were significantly negative correlation between soil erodibility and soil organic carbon, the content of soil total N, content of soil silt under different vegetations. However, they were significantly positive correlation between soil erodibility and content of soil sand under different vegetations. In 10-20 cm layer, they were significantly negative correlation between soil erodibility and soil organic carbon, the content of soil total N under different vegetations. However, they were significantly positive correlation between soil erodibility and content of soil silt under different vegetations.
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