| A series of eco-environmental problems, such as severe soil erosion, decreases in soilfertility and productivity, land degradation and desertification, have threatened thesustainable development of the ecosystems and social economy on the Loess Plateau ofChina. Regional and local projects aiming on ecological restoration and reconstructionhave been launched to combat these problems on this area, practically through land useoptimization, vegetation recovery and soil and water conservation. Soils on the LoessPlateau are poverty due to the scarcity of both soil nutrients and water resources. Thesetwo factors together greatly limit plant growth and agricultural production, controlling thespatial variations of land use and vegetation. From regional perspective, systematic andaccurate information on the spatial variations of soil nutrients and the impact factors atdifferent scales is basic and essential for effective applications of these ecological projects,and would be helpful in related macro policy makings.The main purposes of this dissertation were to （1） explore the current level and stocksof several main soil nutrients across the entire Loess Plateau region;（2） to reveal thespatial variability of these soil nutrients and illustrate their distribution patterns;（3） toinvestigate the relationships between these soil nutrients and pertinent environmentalfactors at different scales;（4） and to generate accurate prediction models usingeasy-to-measure variables. An intensive soil survey with a sampling interval of about30-50km was accomplished within one year during2008, by investigating382representative sampling sites across the entire Loess Plateau region （62.4×104km2）. Atotal of1528composite soil samples were corrected using a handy soil auger （5cm indiameter） from0-20cm and20-40cm topsoil layers, and0-100cm and100-200cm deepsoil layers. Additionally,764undisturbed soil cores were collected with cutting rings （100 cm3in volume）. The environmental conditions of each sampling site were recorded, suchas latitude, longitude, elevation, aspect, slope gradient, slope position, land use type andvegetation type. All the soil samples were taken to the laboratory for measurements of soilorganic carbon （SOC）, soil total nitrogen （STN）, soil total phosphorus （STP）, soil totalpotassium （STK）, soil pH, soil mechanical composition and bulk density （BD）. Traditionalstatistics methods （correlation analysis, linear regression, ANOVA and post-hoc）,geostatistics methods （semivariogram, kriging interpolation, factorial kriging analysis） andstate-space modeling approach were used for spatial analysis and generation of predictionmodels. The main resultes are listed as follows:（1） Soil organic carbon concentrations （SOCC） varied within a wide range throughout theregion from0.38g kg-1to54.03g kg-1, with mean values of10.34g kg-1and6.78gkg-1for the topsoil （0-20cm） and subsoil （20-40cm）, respectively. The mean SOCdensity （SOCD） was2.64kg m-2in the0-20cm soil layer and4.57kg m-2in the0-40cm soil layer, and it was estimated that1.64and2.86Pg (1Pg=1015g) of organiccarbon were stored in these soil layers, respectively. Estimates for deeper soil layersindicated that mean SOCD in the0-100cm and0-200cm layers was7.70and12.45kgm-2, respectively, while the total organic carbon stocks amount to4.78Pg （0-100cm）and5.85Pg （0-200cm）, respectively. The SOC stocks in the0-20cm and0-100cm ofsoils in the Loess Plateau region contribute0.36%and0.31%to the global SOC storedin these respective layers. In addition, our results indicated that the0-20and0-100cmsoil layers of the Loess Plateau, which covers nearly6.5%of the area of China,currently holds about8.21%and5.32%of the total SOC stocks in these layers in China,respectively. Coefficient of variation values showed moderate variation for both SOCconcentration and density values in both0-20cm and20-40cm soil layers. Significantcorrelations were detected between SOCC and these environmental variables, notablywith soil total nitrogen （STN）, soil pH and clay content. Multiple linear regressionanalysis indicated that STN, clay content, soil pH, elevation and temperature hadgreater effects on regional SOCC variability, among all the selected soil and sitevariables. The results of ANOVA showed that precipitation, temperature, elevation,clay plus silt contents and land use showed significant regional impacts on SOCD. Theresults also show that human activities have heavily affected SOC accumulation. Measured SOCD under cropland was relatively higher than under grassland andforestland.Geostatistics analysis showed that the maximum autocorrelation ranges were384km,393km and339km for SOCC （0-20cm and20-40cm） and SOCD （0-40km）,respectively. Nugget-to-sill ratios were0.52,0.50and0.45, which also indicatedmoderate spatial dependence. The distribution maps of SOCC in both topsoil layers andSOCD in0-40cm soil layers were produced by geostatistical method showed that theoverall spatial pattern was characterized by an area of low SOC content surrounded bybands with higher values that generally increased towards the region’s boundaries. Thedistribution pattern corresponded to that of the major regional landforms, which alsoinfluenced land use, whereby the sandy Ordos Plateau is surrounded by relativelyfertile plains and valleys, where the human population density is highest, and theregional boundary is mountainous.（2） In0-20cm soil layers, mean STN concentrations （STNC） and STP concentrations（STPC） ranged from0.58g kg-1to0.81g kg-1and from0.50g kg-1to0.73g kg-1,respectively, under different land types. In20-40cm soil layers, mean STNC and STPCranged from0.46g kg-1to0.60g kg-1and from0.48g kg-1to0.61g kg-1, respectively.Mean STN and STP densities in0-40cm soil layers ranged from0.27kg m-2to0.39kgm-2and from0.27kg m-2to0.38kg m-2, respectively, under different land use types.All the concentrations and densities of STN and STP under different land use typesshowed moderate variations, which was indicated by the values of coefficient ofvariation. We detected significant （p<0.05） effects of land use, precipitation andtemperature on both STN and STP. But the results varied among different precipitationand temperature regions and different land use types. Generally, croplands had higherconcentrations and densities of STN and STP than forestlands and grasslands, andregions with more precipitation and higher temperature had higher STN and STPdensities. Significant correlations were found between STN, or STP, with selectedfactors, i.e. soil organic carbon, precipitation, temperature, elevation, latitude, longitude,slope gradient, clay content, silt content and soil pH. The results were not consistentwithin either the variable or the land use types. We generated land-use specific linearmodels to predict STN and STP using these related variables. Geostatistical analysis showed moderate spatial dependence of both STN and STP, indicated by the values ofnugget to sill ratio. The spatial range of STN and STP ranged from374km to461kmand546km to664km, respectively. This range was much larger than our samplingintervals （30-50km）. The distribution maps of STN and STP densities were made withkriging interpolation. Finally, the stock of STN and STP was estimated to be0.217Pgand0.205Pg in the upper0-40cm soil layers, which was about5.4%and7.3%of thetotal nitrogen and phosphorus stocks in China. Our study suggests that it is important totake land use into account when considering variation of STN and STP at regionalscale.（3） In0-20cm and20-40cm soil layers, soil total potassium （STK） concentration variedfrom10.07-30.97g kg-1and12.82-32.39g kg-1, with mean values of19.25g kg-1and19.10g kg-1, respectively. The coefficients of variation for STK were13.4%and13.3%,defined as moderate variation. The spatial ranges of STK were546km and564km.The nugget-to-sill ratios were31.7%and26.9%, showing moderate spatial dependence.Two methods, state-space modeling and classical linear regression, were used toquantify the relationships between STK （0-20cm） and bulk density, clay and siltcontent, soil pH, precipitation, temperature, and elevation. The best state-space modelsexplained more than97%of the STK variation, while the best linear regression modelexplained less than26%of the STK variation. The results showed that all thestate-space models described the spatial variation of STK much better than thecorresponding linear regression models. Temperature, bulk density and clay contentwere identified as important factors that affected localized variation of STK, since theywere connected to the better performance of the state-space models. State-spacemodeling is recommended as a useful tool for quantifying spatial relationships betweensoil properties and other environmental factors in large-scale regions.（4） In0-20cm soil layers, soil pH values ranged from6.06to10.76, with a mean of8.49and a median of8.48. Land use type had a significant effect （p <0.01） on soil pH;grassland soils had higher pHs than cropland and forestland soils. From a regionalperspective, soil pH showed weak variation and strong spatial dependence, indicatedby the low values of the coefficient of variation （5%） and the nugget-to-sill ratios（<0.25）. Indices of cross-validation, i.e. average error （AE）, mean absolute error （MAE）, root mean square error （RMSE） and model efficiency coefficient （MEC） wereused to compare the performance of the four different interpolation methods, i.e.inverse distance weighting （IDW）, splines, ordinary kriging and cokriging. The resultsshowed that kriging methods interpolated more accurately than IDW and splines.Cokriging performed better than ordinary kriging and the accuracy was improved byusing soil organic carbon as an auxiliary variable. Regional distribution maps of soilpH were produced. The southeastern part of the region had relatively low soil pHvalues, probably due to higher precipitation, leaching, and higher soil organic mattercontents. Areas of high soil pH were located in the north of the central part of theregion, possibly associated with the salinization of sandy soils under inappropriateirrigation practices in an arid climate.（5） Traditional statistical analysis of the correlations between spatially distributed variablestakes no account of their regionalized nature. Factorial kriging analysis （FKA） wasapplied to investigate scale-dependent correlations between selected soil properties （i.e.soil organic carbon （SOC）, soil total nitrogen （STN）, soil total phosphorus （STP）, soiltotal potassium （STK）, soil pH, bulk density （BD）, and clay and silt contents） andenvironmental factors （i.e. elevation, precipitation, temperature, land use type and soiltype）. A linear model of coregionalization, including a nugget effect and two sphericalstructures （effective ranges of200and400km）, was fitted to the experimental auto andcross-variograms of the variables. Scale-dependent correlations were calculated fornugget effect scale （<30-50km）, short-range scale with a range of200km andlong-range scale with a range of400km. Principal component analysis was conductedto clearly illustrate the correlations at each spatial scale. The scale-dependentcorrelations were different from the general correlations and varied at different scales.Generally, SOC and STN were strongly correlated at the nugget effect scale and thelong-range scale, but not at the short-range scale. Precipitation and clay content showedclose correlations with STP at the nugget effect scale and long-range scale. The STKwas weakly correlated with the other variables at each spatial scale, but closelycorrelated with soil type at the long-range scale. Soil pH was closely correlated withBD, soil type and elevation at the nugget effect, short and long spatial scales,respectively. Close correlations were found between BD and land use type at each spatial scale. Land use and soil type were considered to be the important factorscontrolling spatial variation of soil properties at the short-range scale while at thelong-range scale the likely factors were identified as precipitation, temperature andelevation.Based on intensive filed sampling and uniform laboratory measurements, our studyprovided an overview on the spatial variation and impact factors of soil organic carbon,soil total nitrogen, soil total phosphorus, soil total potassium and soil pH across the entireLoess Plateau region of China. The reliable spatial data updated the soil database for thestudy region, and can be used as important input layers in regional digital soil mapping,carbon and nitrogen cycle modeling and evaluation of the potential non-point sourcepollution associated with soil erosion. Moreover, the results presented in this dissertationcan serve as an important background for the future studies in related fields, and can beuseful in macro decision making for regional eco-environment restoration on the LoessPlateau. |
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