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Zhalong natural wetlands typical wet meadow as experimental subjects, microbial characteristics and soil nutrient spatial distribution pattern of the different degree of salinization and impact factor, reveals a the wetland degradation process driven mechanism, for the first time. build the wetlands soil nutrient evaluation model and Microbiology prediction model, to provide a theoretical basis for the ecological restoration of degraded natural wetlands. The study also explored through different anthropogenic interference intensity Ribbon wet meadow microbial biomass carbon, nitrogen spatial and temporal dynamic wetland soil microbial biomass anthropogenic interference with the intensity of the response and its impact factors, natural wetlands, the special The in-depth study of the carbon and nitrogen biogeochemical cycles of habitat provide an important reference. The main results are as follows: Zhalong wetlands degradation of the soil microbial community structure of the wet meadow, bacteria dominant, followed by actinomycetes, fungi minimum number, proportion followed by 73.73% to 91.64%, from 0.32% to 16.90 % and 0.01% -0.33%. 2 different rebate (salinity) degree wet meadow soil nutrients, microbial communities quantity, microbial biomass carbon, nitrogen showed significant vertical distribution characteristics, but its spatial distribution and there are some differences, soil nutrients, microbial activity with soil Refund (saline) the degree of intensification significantly reduced. The soil activity space distribution is due to many factors, is more complicated. 3, wet meadow wetland degradation process, the close relationship between the soil nutrients and soil microbial characteristics, specific performance: Microbial biomass carbon and nitrogen, respectively, with p-glucosidase, urease, phosphatase correlated significantly with (P lt; 0.05); organic carbon and actinomyces hydrogen peroxide activity correlated significantly (P lt; 0.05); available K, total N, hydrolysable nitrogen, C / N sequence, respectively, with the number of actinomycetes, the number of bacteria p-glucosidase activity, microbial biomass nitrogen was significantly correlated (P lt; 0.05); total P, pH and soil microbial activity relationship is not significant (P gt; 0.05). 4, the principal component analysis to first build a predictive model of soil nutrients in natural wetland degradation process evaluation model and its microbiology, are as follows: (1) comprehensive evaluation of the total soil nutrient model: Y = 0.3116x1 0.2438x2 0.2659x3 0.2770x4 where 0.2012x5 0.3116x6 0.1913x7: Y1, Y2, Y xl as the organic matter content of the total N content; x2; x3 total P content; x4 hydrolysable nitrogen content; x5 available potassium total nutrient value of the soil; ; x6 is an organic C content; X7 as C / N. (2) the microbiology of the soil nutrient prediction model: Y = 0.0952x1 0.1146x2-0.0363x3 0.1085x4 0.1288x5 0.2039x6 0.1681x7 0.1758x8 0.1747x9 0.1361x10 0.1410x11 0.1935x12 where: Y is the total soil microbial activity; x1 urease activity; x2 acid phosphatase activity; x3 alkaline phosphatase activity; x4 polyphenol oxidase activity; x5 hydrogen peroxide activity of p-glucosidase activity; x6; x7 microbial biomass carbon (MBC ); x8 microbial biomass nitrogen (MBN); x9 number of bacteria; x10 fungi; x1l number of actinomycetes; x12 as the total number of bacteria. Different functional areas wet soil microbial biomass carbon, nitrogen with soil depth significantly decreasing, and the experimental areas and buffer zones decline rate was significantly greater than the core area. The research places the same soil, the soil microbial biomass are quite different. In addition, the soil MBN in research different soil spatial variability significantly less than MBC. 6, soil MBN season, more even distribution of the law, are generally presented to the changing patterns of the \7, correlation analysis showed that the wet meadow wetland soil microbial biomass carbon, nitrogen spatial and temporal distribution of soil organic carbon, available phosphorus content was significantly positively correlated (P lt; 0.05) and positively correlated with soil moisture content was significantly (P lt ; 0.01), soil environmental factors affect the distribution of the various functional areas and there are some differences. In addition, human disturbance on soil microbial biomass is also very significant, its the microbial spatial and temporal distribution mainly indirect impact by changing the the original moisture characteristics of wetlands, wetland vegetation communities.
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