毛乌素沙漠-黄土高原过渡带土壤养分空间异质性

毛乌素沙漠-黄土高原过渡带土壤养分的空间异质性和生态学过程,对沙荒地整治的机理研究具有重要的意义。以毛乌素沙漠-黄土过渡带为研究区,结合布点取样和室内分析,运用经典统计学和地统计学方法对其全氮、有效磷、速效钾含量的空间异质性进行分析。结果表明,(1)土壤全氮、有效磷、速效钾的平均含量分别为0.39 g/kg、9.65 mg/kg和106.84 mg/kg。3种养分的变异系数为40.54%—84.62%,均属于中等程度变异,其中全氮变异系数最大,速效钾变异系数最小。(2)半方差分析结果显示,3种养分空间变异性的最佳拟合模型均为高斯模型,空间自相关性均随着滞后距离的增加而呈下降趋势。3种养分空间变异性的块金值/基台值比值在0.09%—32.82%,全氮、有效磷具有强烈的空间相关性,结构性因素对变异起主导作用;速效钾具有中等强度的空间相关性,结构性因素和随机性因素共同对变异起主导作用。(3)克里金插值图显示3种养分含量均表现为随着地势的降低而逐渐升高的趋势,全氮含量整体呈斑点状分布,插值图较破碎,有效磷和速效钾含量整体呈条带状分布,连续性较好。(4)毛乌素沙漠-黄土过渡带土壤养分的空间变异性与地形、地貌、植物分布以及非自然因素都有关,但是以地形因素的影响为主。开展沙漠-黄土过渡带土壤养分空间异质性特征研究,为开展沙荒地整治工程,生态系统修复提供了理论依据。     

基于神经网络模型和地统计学方法的土壤养分空间分布预测

采用径向基函数神经网络模型与普通克里格法相结合的方法,预测川中丘陵区县域尺度土壤养分(有机质和全氮)的空间分布,并与普通克里格法和回归克里格法进行比较.结果表明：各方法对研究区土壤养分的预测结果相似.与多元回归模型相比,神经网络模型对验证样点土壤有机质和全氮的预测值与样点实测值的相关系数分别提高了12.3%和16.5%,表明神经网络模型能更准确地捕捉土壤养分与定量环境因子间的复杂关系.对469个验证样点预测结果的误差分析表明,神经网络模型与普通克里格法相结合的方法对土壤有机质和全氮预测结果的平均绝对误差、平均相对误差、均方根误差较普通克里格法分别降低了6.9%、7.4%、5.1%和4.9%、6.1%、4.6%,降低幅度达到极显著水平(P<0.01);与回归克里格法相比则分别降低了2.4%、2.6%、1.8%和2.1%、2.8%、2.2%,降低幅度达显著水平(P<0.05).     

基于神经网络模型和地统计学方法的土壤养分空间分布预测

采用径向基函数神经网络模型与普通克里格法相结合的方法,预测川中丘陵区县域尺度土壤养分(有机质和全氮)的空间分布,并与普通克里格法和回归克里格法进行比较.结果表明：各方法对研究区土壤养分的预测结果相似.与多元回归模型相比,神经网络模型对验证样点土壤有机质和全氮的预测值与样点实测值的相关系数分别提高了12.3%和16.5%,表明神经网络模型能更准确地捕捉土壤养分与定量环境因子间的复杂关系.对469个验证样点预测结果的误差分析表明,神经网络模型与普通克里格法相结合的方法对土壤有机质和全氮预测结果的平均绝对误差、平均相对误差、均方根误差较普通克里格法分别降低了6.9%、7.4%、5.1%和4.9%、6.1%、4.6%,降低幅度达到极显著水平(P<0.01);与回归克里格法相比则分别降低了2.4%、2.6%、1.8%和2.1%、2.8%、2.2%,降低幅度达显著水平(P<0.05).     

插值方法与样点数对县域土壤有效磷空间变异特征评价的影响

与欧美大规模农场经营不同,土地分散经营使我国县域土壤养分空间变异特征评价更加困难.本研究以安徽芜湖土壤有效磷为例,系统地评价插值方法与样点数对县域土壤养分空间变异特征评价准确性的影响.结果表明：局部多项式、普通克里格、简单克里格和析取克里格插值方法的评价效果优于反距离加权法、全局多项式、径向基插值和泛克里格等插值方法,考虑到实际操作简单,推荐用普通克里格方法进行县域土壤有效磷空间变异特征评价.随着参与空间插值样点数的增加,县域土壤有效磷空间变异特征预测的准确性增加,充分考虑评价的准确性和田间取样费用,建议县域土壤有效磷空间变异特征评价的适宜样点数应介于500～1000个.     

Bioclimatic and vegetation mapping of a topographically complex oceanic island applying different interpolation techniques

Different spatial interpolation techniques have been applied to construct objective bioclimatic maps of La Palma, Canary Islands. Interpolation of climatic data on this topographically complex island with strong elevation and climatic gradients represents a challenge. Furthermore, meteorological stations are not evenly distributed over the island, with few stations at high elevations. We carried out spatial interpolations of the compensated thermicity index (Itc) and the annual ombrothermic Index (Io), in order to obtain appropriate bioclimatic maps by using automatic interpolation procedures, and to establish their relation to potential vegetation units for constructing a climatophilous potential natural vegetation map (CPNV). For this purpose, we used five interpolation techniques implemented in a GIS: inverse distance weighting (IDW), ordinary kriging (OK), ordinary cokriging (OCK), multiple linear regression (MLR) and MLR followed by ordinary kriging of the regression residuals. Two topographic variables (elevation and aspect), derived from a high-resolution digital elevation model (DEM), were included in OCK and MLR. The accuracy of the interpolation techniques was examined by the results of the error statistics of test data derived from comparison of the predicted and measured values. Best results for both bioclimatic indices were obtained with the MLR method with interpolation of the residuals showing the highest R ² of the regression between observed and predicted values and lowest values of root mean square errors. MLR with correction of interpolated residuals is an attractive interpolation method for bioclimatic mapping on this oceanic island since it permits one to fully account for easily available geographic information but also takes into account local variation of climatic data.     

基于序贯指示模拟的农田土壤重金属风险区域识别

农田土壤重金属的日益累积已对农作物安全、生态环境和人类健康造成严重威胁,高效、精确地识别农田土壤重金属风险区对农田的环境保护、污染预警和风险管控等有重要意义.以广州市增城区为研究对象,共采集204个农田土壤样点,测定了铜(Cu)、锌(Zn)、铅(Pb)、镉(Cd)、铬(Cr)、砷(As)和汞(Hg)7种重金属含量.针对实际采样数据中存在异常值与偏态分布,以及传统克里格法存在的平滑效应等问题,将序贯指示模拟引入农田土壤重金属的风险识别中,与常用识别方法进行比较,并根据Hakanson风险指数评价进行风险区划.结果表明:(1)对比普通克里格法,在精度相似情况下,序贯指示模拟法较为精细地模拟了重金属的空间分布,平滑效应低,预测的细节表现好;对比指示克里格法,其在划分风险区域时的不确定评估中准确度较高,其误判率仅为4.9%~17.1%,表明其能更好地适用于模拟农田土壤重金属的空间分布和风险识别;(2)增城区的农田土壤重金属均未超标,但在南部的极少数区域存在潜在中等风险,主要成因是包括企业生产、人类活动和河流沉积物等.本研究以序贯指示模拟为基础,有效克服了传统克里格法存在的异常值信息丢失和平滑效应问题,结合Hakanson风险指数法,为非均匀采样的土壤重金属空间风险的识别提供一种新的尝试.     

Three-Dimensional Mapping of Soil Organic Carbon by Combining Kriging Method with Profile Depth Function

Understanding spatial variation of soil organic carbon (SOC) in three-dimensional direction is helpful for land use management. Due to the effect of profile depths and soil texture on vertical distribution of SOC, the stationary assumption for SOC cannot be met in the vertical direction. Therefore the three-dimensional (3D) ordinary kriging technique cannot be directly used to map the distribution of SOC at a regional scale. The objectives of this study were to map the 3D distribution of SOC at a regional scale by combining kriging method with the profile depth function of SOC (KPDF), and to explore the effects of soil texture and land use type on vertical distribution of SOC in a fluvial plain. A total of 605 samples were collected from 121 soil profiles (0.0 to 1.0 m, 0.20 m increment) in Quzhou County, China and SOC contents were determined for each soil sample. The KPDF method was used to obtain the 3D map of SOC at the county scale. The results showed that the exponential equation well described the vertical distribution of mean values of the SOC contents. The coefficients of determination, root mean squared error and mean prediction error between the measured and the predicted SOC contents were 0.52, 1.82 and -0.24 g kg^-1 respectively, suggesting that the KPDF method could be used to produce a 3D map of SOC content. The surface SOC contents were high in the mid-west and south regions, and low values lay in the southeast corner. The SOC contents showed significant positive correlations between the five different depths and the correlations of SOC contents were larger in adjacent layers than in non-adjacent layers. Soil texture and land use type had significant effects on the spatial distribution of SOC. The influence of land use type was more important than that of soil texture in the surface soil, and soil texture played a more important role in influencing the SOC levels for 0.2-0.4 m layer.     

利用辅助变量对污染土壤锌分布的克里格估值

采用协同克里格及与回归相结合的克里格方法,以36个下层(10～20 cm)土壤锌数据为目标变量、另36个下层土壤锌数据为校验数据、72个上层(0～10 cm)土壤锌为辅助变量,对沈阳市南郊某有色金属加工厂附近农田0.1 mol·L^-1 HCl浸提态土壤锌进行插值分析,并对这两种利用辅助变量的克里格方法在土壤锌空间分布研究中的适用性进行评价.结果表明,与回归相结合的克里格的估值效果明显优于协同克里格及普通克里格法.结合回归模型的变异函数理论模型决定系数较大、残差较小,估值精度比普通克里格法提高4%,且基于回归克里格的土壤锌分布图与利用72个样点普通克里格插值图具有高度的相似性.而协同克里格与普通克里格相比未表现出明显优势.借助辅助变量,采用基于回归模型的克里格方法是进行土壤重金属空间分布估值的一种有效方法.     

Prediction of soil property distribution in paddy soil landscapes using terrain data and satellite information as indicators

Sustainable land management and land use planning require reliable information about the spatial distribution of the physical and chemical soil properties affecting both landscape processes and services. Although many studies have been conducted to identify the spatial patterns of soil property distribution on various scales and in various landscapes, only little is known about the relationships underlying the spatial distribution of soil properties in intensively used, finely structured paddy soil landscapes in the southeastern part of China. In order to provide adequate soil information for the modelling of landscape processes, such as soil water movement, nutrient leaching, soil erosion and plant growth, this study investigates to what extent cheap and readily available ancillary information derived from digital elevation models and remote sensing data can be used to support soil mapping and to indicate soil characteristics on the landscape scale. This article focuses on the spatial prediction of the total carbon and nitrogen content and of physical soil properties such as topsoil silt, sand and clay content, topsoil depth and plough pan thickness. Correlation analyses indicate that, on the one side, the distribution of C, N and silt contents is quite closely related to the NDVI of vegetated surfaces and that, on the other side, it corresponds significantly to terrain attributes such as relative elevation, elevation above nearest drainage channel and topographical wetness index. Geostatistical analyses furthermore reflect a moderately structured spatial correlation of these soil variables. The combined use of the above mentioned terrain variables and the NDVI in a multiple linear regression accounted for 29% (silt) to 41% (total C) of the variance of these soil properties. In order to select the best prediction method to accurately map soil property distribution, we compared the performance of different regionalization techniques, such as multi-linear regression, simple kriging, inverse distance to a power, ordinary kriging and regression kriging. Except for the prediction of topsoil clay content, in all cases regression kriging model “C” performed best. Compared to simple kriging, the spatial prediction was improved by up to 14% (total C), 13% (total N) and 10% (silt). Since the autocorrelation lengths of these spatially well correlated soil variables range between three and five times the soil sampling density, we consider regression kriging model “C” to be a suitable method for reducing the soil sampling density. It should help to save time and costs when doing soil mapping on the landscape scale, even in intensively used paddy soil landscapes.     

典型岩溶洼地土壤水分的空间分布及影响因素

在桂西北典型岩溶洼地的旱季和雨季,用地统计学结合GIS方法研究了洼地表层(0—16cm)土壤水分的空间分布特征及其影响因素。结果表明:土壤含水量受前期降雨量的影响,且旱季土壤水分对降雨量的反应较雨季敏感。土壤水分均呈中等变异且变异系数随着平均含水量的增加而减少。土壤水分的半方差参数显示土壤水分空间变异及其主导因素随旱、雨季而不同。此外,不同取样区域及取样时段内土壤含水量高低差别明显,分布格局及空间变异程度各异,这主要与当地环境和人为因素的综合影响有关。旱、雨季土壤水分均与前期降雨导致的土壤平均含水量变化呈相反趋势,且不同土地利用方式下的土壤含水量不同。土壤含水量还与土壤有机碳含量呈显著正相关,此外,地势及裸岩率也是造成洼地土壤水分变异及其分布差异的重要因素。下一步应根据旱季和雨季土壤水分分布及影响因素的差异,在岩溶洼地采取有针对性地土壤水资源利用及其水分管理策略。     

Spatial distribution of pH and organic matter in urban soils and its implications on site-specific land uses in Xuzhou,China

The spatial variation of soil pH and soil organic matter (SOM) in the urban area of Xuzhou, China, was investigated in this study. Conventional statistics, geostatistics, and a geographical information system (GIS) were used to produce spatial distribution maps and to provide information about land use types. A total of 172 soil samples were collected based on grid method in the study area. Soil pH ranged from 6.47 to 8.48, with an average of 7.62. SOM content was very variable, ranging from 3.51 g/kg to 17.12 g/kg, with an average of 8.26 g/kg. Soil pH followed a normal distribution, while SOM followed a log-normal distribution. The results of semi-variograms indicated that soil pH and SOM had strong (21%) and moderate (44%) spatial dependence, respectively. The variogram model was spherical for soil pH and exponential for SOM. The spatial distribution maps were achieved using kriging interpolation. The high pH and high SOM tended to occur in the mixed forest land cover areas such as those in the southwestern part of the urban area, while the low values were found in the eastern and the northern parts, probably due to the effect of industrial and human activities. In the central urban area, the soil pH was low, but the SOM content was high, which is mainly attributed to the disturbance of regional resident activities and urban transportation. Furthermore, anthropogenic organic particles are possible sources of organic matter after entering the soil ecosystem in urban areas. These maps provide useful information for urban planning and environmental management.     

基于协同克里格的橡胶园土壤速效钾空间变异性

选取有效变量的协同克里格方法能够提高县域尺度橡胶园土壤速效钾的空间预测精度,对橡胶树精准施肥管理具有重要意义。本研究以海南省白沙县橡胶园0～20 cm耕层土壤为对象,采用地统计学分析土壤速效钾的空间变异特征,运用相关分析筛选显著的特征变量,并比较不同变量的协同克里格(COK)空间插值精度。结果表明: 研究区土壤速效钾平均含量为44.65 g·kg^-1,总体处于缺乏状态;变异系数为52.6%,属中等变异强度;块金效应为12.5%,存在较强的空间自相关。有机质、高程与土壤速效钾含量关系密切,均呈极显著相关;有机质(COK₁)、高程(COK₂)、有机质+高程(COK₃)3种协变量的COK空间插值预测精度均高于普通克里格法(OK),交叉验证模型拟合精度为COK₁>COK₃> COK₂>OK;拟合精度与协变量选取的数量不呈正比,选取相关性更高的协变量更有利于反映区域土壤属性的空间异质性。研究区土壤速效钾含量具有西北部较高、中偏东部地区较低的分布特点。研究结果为今后开展橡胶园土壤钾素管理提供了理论依据。     

黄土丘陵区小流域土壤碳氮磷生态化学计量特征的空间变异性

土壤碳、氮、磷是植物重要的营养来源和保障生态系统健康的重要生态因子,其含量及化学计量比的动态平衡对生态系统的生产力具有重要影响,分析土壤碳、氮、磷养分含量及化学计量比的空间变异性和影响机制,对区域土壤养分管理以及土地可持续利用具有重要意义。本研究选取位于黄土高原东缘的三眼井小流域,利用经典统计与地统计相结合的方法,分析了研究区表层土壤(0~20 cm)有机碳(SOC)、全氮(TN)和全磷(TP)以及土壤碳氮磷的化学计量比的空间变异性和影响机制。结果表明:(1)研究区表层土壤SOC、TN和TP的平均值分别为3.97、0.83和0.6 g·kg-1,C∶N、C∶P、N∶P的平均值分别为4.73、6.02、1.26,均属于中等变异水平。(2)土地利用类型和地貌类型对研究区土壤SOC、TN具有显著影响,林地和荒草地高于梯田和退耕地,梁上高于沟谷;TP主要受土地利用类型的显著影响,梯田显著高于其他三种土地利用类型;土地利用类型对土壤C∶N、C∶P和N∶P的影响较为一致,表现为梯田显著低于其他土地利用类型;C∶N还受到坡度和地貌类型的显著影响,C∶P和N∶P还分别受到坡度和海拔的显著影响。(3)采用回归克里格法得到的预测图更能体现环境要素的作用,空间预测精度较高,土壤碳、氮、磷生态计量特征的空间分布格局具有明显差异。因此,针对土壤碳、氮、磷生态计量特征的空间分布格局,采取不同的有机旱作、平衡施肥及水土保持措施等,并进行合理的空间配置,有助于改善研究区土壤碳、氮、磷的平衡状况。     

Examining the spatial distribution of flower thrips in southern highbush blueberries by utilizing geostatistical methods

Flower thrips (Frankliniella spp.) are one of the key pests of southern highbush blueberries (Vaccinium corymbosum L. x V. darrowii Camp), a high-value crop in Florida. Thrips' feeding and oviposition injury to flowers can result in fruit scarring that renders the fruit unmarketable. Flower thrips often form areas of high population, termed "hot spots", in blueberry plantings. The objective of this study was to model thrips spatial distribution patterns with geostatistical techniques. Semivariogram models were used to determine optimum trap spacing and two commonly used interpolation methods, inverse distance weighting (IDW) and ordinary kriging (OK), were compared for their ability to model thrips spatial patterns. The experimental design consisted of a grid of 100 white sticky traps spaced at 15.24-m and 7.61-m intervals in 2008 and 2009, respectively. Thirty additional traps were placed randomly throughout the sampling area to collect information on distances shorter than the grid spacing. The semivariogram analysis indicated that, in most cases, spacing traps at least 28.8 m apart would result in spatially independent samples. Also, the 7.61-m grid spacing captured more of the thrips spatial variability than the 15.24-m grid spacing. IDW and OK produced maps with similar accuracy in both years, which indicates that thrips spatial distribution patterns, including "hot spots," can be modeled using either interpolation method. Future studies can use this information to determine if the formation of "hot spots" can be predicted using flower density, temperature, and other environmental factors. If so, this development would allow growers to spot treat the "hot spots" rather than their entire field.     

A geostatistical approach to the field-scale pattern of heterotrophic soil CO2 emission using covariates

Soil heterotrophic respiration fluxes at field scale may exhibit a substantial spatial variability. The aim of this study was (1) to elucidate the role of soil temperature and different carbon fractions on heterotrophic soil respiration and (2) to test by which of three different statistical approaches (multiple regression, external drift kriging and simulated annealing) such influences may be best represented. Chamber-based measurements of respiration fluxes were carried out within a 180 × 40 m bare soil plot. Soil temperature was measured simultaneously to the flux measurements. Further, we recorded total soil organic carbon content, apparent electrical conductivity as well as mid-infrared spectroscopy-based carbon fractions as co-variates in addition to basic soil properties like stone content and texture. A stepwise multiple linear regression procedure was used to spatially predict bare soil respiration from the co-variates. The results showed that the particulate organic matter (POM) fraction and terrain elevation were able to explain the spatial pattern of heterotrophic soil respiration (R ² = 0.45). In a second step we applied external drift kriging to determine the improvement of using co-variates in an estimation procedure in comparison to ordinary kriging. The maximum relative improvement using the co-variates in terms of the root mean square error was 16%. In a third step we applied simulated annealing to perform stochastic simulations conditioned with external drift kriging to generate more realistic spatial patterns of heterotrophic respiration at plot scale. The conditional stochastic simulations revealed a significantly improved reproduction of the probability density function, the G-statistics value increased from 0.36 to 0.92. Further, the error in the reproduction of the semivariogram of the original point data decreased by more than one order of magnitude. All this confirmed that the mapping of soil respiration patterns may be significantly improved when considering terrain elevation and spatial heterogeneity of POM in combination with a conditional stochastic simulation.     

长白山低山区森林土壤有机碳及养分空间异质性

以吉林延边汪清林业局金仓林场境内森林土壤为对象,采用多元线性回归方法和地统计学回归克里格方法,研究了土壤有机碳及养分的垂直分布规律,预测了其空间分布,并对预测结果进行插值.结果表明: 0～60 cm深度土壤有机碳密度为(16.14±4.58) kg·m^-2.随土壤深度增加,土壤有机碳含量、有机碳密度以及土壤全N、全P、全K、有效P及速效K含量都呈减小趋势,其中不同土层间土壤有机碳含量、有机碳密度差异显著(P<0.01).0～60 cm土层土壤有机碳含量和碳密度的拟合方程中,地形因子中高程和坡向余弦值是最优的拟合因子,方程的决定系数分别为0.34和0.39(P<0.01).0～20和0～60 cm土层的半方差函数模型分别为高斯模型和指数模型,利用回归克里格插值方法得到土壤有机碳的空间分布图.与普通克里格法相比,回归克里格法的空间预测精度改进了18%～58%.利用回归克里格插值方法预测了土壤全N的空间分布特征.     

Spatial Distribution of Soil Organic Carbon and Total Nitrogen Based on GIS and Geostatistics in a Small Watershed in a Hilly Area of Northern China

The spatial variability of soil organic carbon (SOC) and total nitrogen (STN) levels is important in both global carbon-nitrogen cycle and climate change research. There has been little research on the spatial distribution of SOC and STN at the watershed scale based on geographic information systems (GIS) and geostatistics. Ninety-seven soil samples taken at depths of 0–20 cm were collected during October 2010 and 2011 from the Matiyu small watershed (4.2 km²) of a hilly area in Shandong Province, northern China. The impacts of different land use types, elevation, vegetation coverage and other factors on SOC and STN spatial distributions were examined using GIS and a geostatistical method, regression-kriging. The results show that the concentration variations of SOC and STN in the Matiyu small watershed were moderate variation based on the mean, median, minimum and maximum, and the coefficients of variation (CV). Residual values of SOC and STN had moderate spatial autocorrelations, and the Nugget/Sill were 0.2% and 0.1%, respectively. Distribution maps of regression-kriging revealed that both SOC and STN concentrations in the Matiyu watershed decreased from southeast to northwest. This result was similar to the watershed DEM trend and significantly correlated with land use type, elevation and aspect. SOC and STN predictions with the regression-kriging method were more accurate than those obtained using ordinary kriging. This research indicates that geostatistical characteristics of SOC and STN concentrations in the watershed were closely related to both land-use type and spatial topographic structure and that regression-kriging is suitable for investigating the spatial distributions of SOC and STN in the complex topography of the watershed.     

Three-Dimensional Mapping of Soil Chemical Characteristics at Micrometric Scale by Combining 2D SEM-EDX Data and 3D X-Ray CT Images

There is currently a significant need to improve our understanding of the factors that control a number of critical soil processes by integrating physical, chemical and biological measurements on soils at microscopic scales to help produce 3D maps of the related properties. Because of technological limitations, most chemical and biological measurements can be carried out only on exposed soil surfaces or 2-dimensional cuts through soil samples. Methods need to be developed to produce 3D maps of soil properties based on spatial sequences of 2D maps. In this general context, the objective of the research described here was to develop a method to generate 3D maps of soil chemical properties at the microscale by combining 2D SEM-EDX data with 3D X-ray computed tomography images. A statistical approach using the regression tree method and ordinary kriging applied to the residuals was developed and applied to predict the 3D spatial distribution of carbon, silicon, iron, and oxygen at the microscale. The spatial correlation between the X-ray grayscale intensities and the chemical maps made it possible to use a regression-tree model as an initial step to predict the 3D chemical composition. For chemical elements, e.g., iron, that are sparsely distributed in a soil sample, the regression-tree model provides a good prediction, explaining as much as 90% of the variability in some of the data. However, for chemical elements that are more homogenously distributed, such as carbon, silicon, or oxygen, the additional kriging of the regression tree residuals improved significantly the prediction with an increase in the R² value from 0.221 to 0.324 for carbon, 0.312 to 0.423 for silicon, and 0.218 to 0.374 for oxygen, respectively. The present research develops for the first time an integrated experimental and theoretical framework, which combines geostatistical methods with imaging techniques to unveil the 3-D chemical structure of soil at very fine scales. The methodology presented in this study can be easily adapted and applied to other types of data such as bacterial or fungal population densities for the 3D characterization of microbial distribution.     

沈阳城市土壤全钾和碱解氮的空间变异性

采用地统计学和地理信息系统（GIS）相结合的方法研究了沈阳城市土壤全钾、碱解氮2种土壤养分的空间变异性.结果表明：全钾的最佳拟合模型为指数模型,碱解氮的最佳拟合模型为高斯模型;其块金值/基台值［C₀/(C₀+C)］分别为10.65%和17.96%,说明沈阳城市土壤全钾和碱解氮的空间相关性较强,其空间变异主要是由结构性因素引起的.通过克立格插值对沈阳城市土壤全钾和碱解氮的空间分布特征进行分析发现：全钾的空间分布没有明显的规律性;碱解氮的空间分布则为周边高、城区中部低.     

太原市农业土壤全氮和有机质的空间分布特征及其影响因素

利用GPS定位,2005年在山西省太原市主要农业用地采集土样1821个,分析了全氮和有机质的含量.应用传统统计学和地质统计学方法对数据进行了分析.结果表明,按照1980年全国第二次土壤普查养分分级标准,土壤全氮和有机质的平均含量均属中等水平.通过半方差函数分析,土壤全氮和有机质在一定范围内存在空间相关性;它们的空间相关距离分别为122.4 km和75.6 km;全氮的空间变异主要受结构性因素的影响,而土壤有机质的空间变异是由结构性因素和随机性因素共同作用引起的.太原市土壤全氮含量的空间分布呈现由西南向东北逐渐降低的趋势,而有机质的分布规律较为复杂,它们的空间分布主要受土壤类型、海拔高度、土地利用方式和人类生产活动等因素的影响.土壤全氮与有机质的空间分布存在很大的差异,这与娄烦县、古交市当地土壤受煤粉尘污染严重以及所处地形地貌密切相关.研究揭示了在自然和社会条件十分复杂的情况下太原市土壤全氮和有机质的空间变异规律及其影响因素,为实现土壤肥力评价和养分资源精准管理提供了科学依据.