Study On Structural And Nutrient Characters Of Picea Crassifolia Forest Community In Qilian Mountains

Qilian Mountains has continental climate characterized by in alpine and semi-arid, semi-humid. Forest vegetation distribution in shaded slopes and half shaded slopes, in addition to affected by the adverse climates weather and interference by comprehensive effect of the topography, soil and biological characteristics,forest ecosystem environment is relatively fragile, ecosystem characterized by poor stability and anti-interference.The forest ecosystem degradation serious, service function reduced, reverse evolution significantly, process accelerated combined with long-term human activity disturbance, for the regional ecological environment construction and economic development has brought negative impact. Through study on vegetation and nutrient characters of forest vegetation in Qilian Mountains, help understanding recovery and rebuilding the damaged forest ecological system, also has a certain important scientific significance to rational regulation the forest vegetation, thus better displays its role in ecological service function.This study selected the Picea crassifolia forest community as the research object which lived in Dayekou basin of Qilian Mountains. Based on the theories of Forest Ecology, Pedology, Stoichiometry and other disciplines theory, vegetation survey and indoors experiments test the leaf, the litter and soil nutrient,by using of a dynamical plot of Picea crassifolia forest and fixed sample plot different elevation gradient in Qilian Mountains which lived in Qilian Mountains Forest Ecology Station, by application of classical mathematical statistics analysis method, research reveals stand structure characteristics, spatial heterogeneity of community structure, spatial heterogeneity of soil nutrients and change rule, relationship between soil organic carbon and nutrients, further understand interactions between carbon, nitrogen and phosphorus in the three components of the Picea crassifolia forest system and their laws and mechanisms.The main conclusions are as follows:(1) Higher plants has a total of 30 families and 63 genera and 63 species at dynamicals monitoring large plot of Picea crassifolia forest in Qilian Mountains, mainly in compositae, rosaceae, labiatae, gentianaceae, scrophulariaceae, leguminosae, buttercup etc. supporting the main.Vertical structure can be divided into four layers, including tree layer, shrub layer, herb layer and moss layer. Size distribution of all individuals shows an invert “J” shape, which indicates that the community diameter class structure has no obvious fault phenomenon and in a stable and normal growth status.Space distribution pattern of young trees characterized by obvious aggregation distribution, spatial distribution of median size trees are slightly gathered and big tree distribution characterized by obvious random distribution. At the same time, spatial distribution of different diameter grade of Picea crassifolia forest individuals has the spatial distribution of complementarity.(2) The order of spatial variation in these characteristics was: density > average crown breadth > conspicuousness > coverage > average height, with variation coefficient of ranging from 43.7% to 79.6% in dynamicals monitoring large plot of Picea crassifolia forest in Qilian Mountains. Moran’s index indicates that the structural variables have different degrees of spatial autocorrelation, the autocorrelation was density > average height > coverage > average crown breadth > conspicuousness according to the size of order, the ranging from-0.047 to 0.382. The exponential semivariation model provided a good fitting to spatial variability in different structural features, the range values is from 24.6 m to 68.1 m. The variables displayed moderate spatial autocorrelation except for coverage, while other variables had strong spatial autocorrelation; the fractal dimension of the variables is close to 2, indicating a low spatial dependence among variables. The variables presents a superposing characteristic of zonal and patchy structures except for density and coverage, while other variables presents strong patchiness property; density and coverage has a certain spatial dependence to average crown breadth, conspicuousness and average height. The spatial heterogeneity of community structural of Picea crassifolia forests were 10 m and 0.5 hm2, respectively.(3) Soil pH, hydrolyze nitrogen and total phosphorus showed small variation, soil organic carbon, total nitrogen, available phosphorus, total potassium and available potassium showed moderate variation of dynamicals monitoring large plot of Picea crassifolia forest in Qilian Mountains, the variation intensity of soil pH and nutrients ranked from high to low as follows: available potassium(29.68%),organic carbon(19.81%), available phosphorus(19.37%), total nitrogen(18.08%),total potassium(15.58%), hydrolyze nitrogen(8.18%),total phosphorus(6.77%), pH(2.52%).Analysis of variance showed that soil pH and nutrients reached an extremely significant levels. Parameters of theoretical variogram models for soil pH and nutrients showed that soil pH, total nitrogen, hydrolyze nitrogen, total phosphorus, available phosphorus and available potassium all fitted spherical model, organic carbon and total potassium can be best described by exponential model; Soil pH, organic carbon, total nitrogen, hydrolyze nitrogen, total phosphorus, available phosphorus, total potassium and available potassium variation are 108.8 m, 88.5 m, 112.8 m, 131.9 m, 143.3 m, 73.3 m, 73.2 m and 134.71 m. In terms of spatial structure, soil pH indicated moderate spatial autocorrelation, which was resulted from both soil structural factors and random factors, but soil nutrients showed high spatial autocorrelation, which was greatly affected by structural factors. Soil pH and nutrients presented patch distribution, distribution of pH showed that soil mainly alkaline, organic carbon and nitrogen has similar spatial distribution pattern, soil total phosphorus and available potassium distribution change are more obvious, available phosphorus and total potassium content change relatively moderate. The study results may provide reference to sampling design and spatial distribution of soil pH and nutrients of Picea crassifolia forest in Qilian Mountains.(4) In the case of increasing soil depth, soil organic carbon content gradually decreasing, at below 20~ 30 cm beginning to stabilize(p > 0.05) of dynamicals monitoring large plot of Picea crassifolia forest in Qilian Mountains; soil pH value gradually increasing, only in 0 ~ 10 cm and 10 ~ 20 cm significant difference(p< 0.05); soil total nitrogen, available nitrogen, total phosphorus and cation exchange capacity are gradually increasing, total nitrogen content below 30 ~ 40 cm towards stability(p > 0.05), available nitrogen content change dramatically(p < 0.05), total phosphorus content difference was not significant(p > 0.05), the variation of cation exchange capacity organic carbon content same as the organic carbon content; Soil available phosphorus, total potassium and available potassium content had no obvious change rule, available phosphorus and total potassium content has no significant difference(p > 0.05), available potassium content has significant difference only at 0~10 cm and 10~20 cm layer(p < 0.05). Relevant analysis results showed the relationships were highly significant positive or significant positive between soil organic carbon content and total nitrogen, available nitrogen, total phosphorus, available phosphorus, available potassium and cation exchange capacity, the soil pH and total potassium content has very significant and significant negative. The regression equation has high precision of soil organic carbon content and other basic chemical properties(R2 = 0.793), affect soil organic carbon content main chemical factors are: soil cation exchange capacity, available potassium and total phosphorus content.(5) The order of the average content of soil available microelements in different soil profile of dynamicals monitoring large plot of Picea crassifolia forest in Qilian Mountains are: Fe > Mn > Cu > B > Zn, soil available microelements obviously gather in the soil surface. The content of Zn, Mn, Cu, Fe, B in 0 ~ 60 cm soil profile were respectively: 0.52 ± 0.27 mg·kg-1, 6.26 ± 1.76 mg·kg-1, 2.44 ± 0.98 mg·kg-1, 94.69 ± 25.48 mg·kg-1, 2.19 ± 0.70 mg·kg-1. The density of Zn、Mn、Cu、Fe、B in 0 ~ 60 cm soil profile were: 2.21±1.27 mg·m-2、 26.24±7.64 mg·m-2、11.50±6.41 mg·m-2、447.78±178.04 mg·m-2、9.76±3.32 mg·m-2.The order of efficacy index were: Fe > B > Cu > Mn > Zn, including: efficacy index of Fe, B, Cu is greater than 1, and Zn, Mn is less than 1.The content of soil organic matter has a highly significant and significantly positive correlation with Zn, Mn, Cu, Fe, B and other available microelements. The pH value of soil has a highly significant and significantly negative correlation with Zn, Mn, Cu, Fe, B and other available microelements, rapid available phosphorus only were very significant positive correlation with B.Soil organic matter and pH have important influence on soil available microelements content.(6) Carbon, nitrogen and phosphorus ecological stoichiometric ratios of Picea crassifolia forest in elevation gradient indicate that different variation laws and significance of difference with altitude increasing. Among them, C:N ratio in leaf and soil of Picea crassifolia forest increased gradually, C:N ratio in litter increased gradually with the increase of altitude and then decreased at 3 300 m. C:P ratio in leaf first increase and then decrease, at an altitude of 2 900 m was significantly lower than other altitude C:P(p< 0.05). C:P ratio in litter has no obvious change. C:P ratio in soil first increases and then decreases, only at an altitude of 2 900 m was significantly lower than other altitude C:P(p < 0.05). N:P ratio in leaf and soil first increases and then decreases, the N:P ratio of the low altitude(2 900 m~3 100 m) was significantly higher than that of the high altitude(3 200 ~ 3 300 m)(p < 0.05). In this systems along the elevation gradient, C:N ratio in leaf, litters and soil varied in the range of 22.95~36.72, 21.41~41.61 and 12.41~20.70, respectively, and in terms of average of the ratios, the three components of the system followed an order of litters > leaf > soil; C:P ratio did in the range of 510.19~739.81, 398.57~698.07 and 134.11~219.67, respectively, and C:N ratio did in the range of 22.95~36.72, 21.41~41.61 and 21.41~41.61, respectively, and in terms of average of either C:P or C:N ratio, the three followed an order of leaf > litters > soil. All the ratios in all the three components varied sharply with rising altitude, except for soil C: N ratio, which did not as much(p>0.05). Three components were significantly positively related(p>0.05) to each other in C:N ratio, while both leaf and soil were negatively related to litters in C:P ratio(p>0.05). And the relationships of leaf with soil C:P ratio and with litters and soil in N:P ratio were not obvious(p>0.05).