澳大利亚亚热带地区二代肯宁南洋杉林早期测定土壤C、N所需采集土壤样大小研究

Investigations into forest soils face the problem of the high level of spatial variability that is an inherent property of all forest soils. In order to investigate the effect of changes in residue management practices on soil properties in hoop pine （Araucaria cunninghamii Aiton ex A. Cunn.） plantations of subtropical Australia it was important to understand the intensity of sampling effort required to overcome the spatial variability induced by those changes. Harvest residues were formed into windrows to prevent nitrogen （N） losses through volatilisation and erosion that had previously occurred as a result of pile and burn operations. We selected second rotation （2R） hoop pine sites where the windrows （10-15 m apart） had been formed 1, 2 and 3 years prior to sampling in order to examine the spatial variability in soil carbon （C） and N and in potential mineralisable N （PMN） in the areas beneath and between （inter-） the windrows. We examined the implications of soil variability on the number of samples required to detect differences in means for specific soil properties, at different ages and at specified levels of accuracy. Sample size needed to accurately reflect differences between means was not affected by the position where the samples were taken relative to the windrows but differed according to the parameter to be sampled. The relative soil sampling size required for detecting differences between means of a soil property in the inter-windrow and beneath-windrow positions was highly dependent on the soil property assessed and the acceptable relative sampling error. An alternative strategy for soil sampling should be considered, if the estimated sample size exceeds 50 replications. The possible solution to this problem is collection of composite soil samples allowing a substantial reduction in the number of samples required for chemical analysis without loss in the precision of the mean estimates for a particular soil property.     

普通克里格法在土壤有机碳制图中的应用

The quantification of the pattern and spatial distribution of soil organic carbon (SOC) is fundamental to understand many ecosystem processes.This study aimed to apply ordinary kriging (OK) to model the spatial distribution of SOC in a selected part of Zambia.A total of 100 soil samples were collected from the study area and analyzed for SOC by determining soil oxidizable carbon using the Walkley-Black method.An automated fitting procedure was followed when modeling the spatial structure of the SOC data with the exponential semivariogram.The results indicated that the short range spatial dependence of SOC was strong with a nugget close to zero.The spatial autocorrelation was high to medium with a nugget to sill ratio of 0.25.The root mean square error of the predictions was 0.64,which represented 58.18％ of the mean observed data for SOC.It can be concluded that the generated map could serve as a proxy for SOC in the region where evidence of spatial structure and quantitative estimates of uncertainty are reported.Therefore,the maps produced can be used as guides for various uses including optimization of soil sampling.     

中国东南地区两土链土壤中土壤性质和水稻产量的空间变异研究

In the light of an increasing demand for staple food, especially rice, in southeast China, investigations on the specific site potential expressed as the relationship between soil and crop yield parameters gain increasing importance. Soil texture and several soil chemical parameters as well as plant properties such as crop height, biomass and grain yield were investigated along two terraced catenas with contrasting soil textures cropped with wet rice. We were aiming at identifying correlative relationships between soil and crop properties. Data were analyzed both statistically and geostatistically on the basis of semivariograms. Statistical analysis indicated a significant influence of the relief position on the spatial distribution of soil texture, total carbon and total nitrogen contents. Significant correlations were found for the catena located in a sandstone area （Catena A） between rice yield and silt as well as total nitrogen content. Corresponding relationships were not detectable for paddy fields that developed from Quaternary clays （Catena B）. As suggested by the nugget to sill ratio, spatial variability of soil texture, total carbon and nitrogen was mainly controlled by intrinsic factors, which might be attributed to the erosional transport of fine soil constituents, indicating the importance of the relief position and slope in soil development even in landscapes that are terraced. The crop parameters exhibited short ranges of influence and about one third of their variability was unexplained. Comparable ranges Of selected crop and soil parameters, found only for Catena A, are indicative of close spatial interactions between rice yield and soil features. Our findings show that especially in sandstone-dominated areas, a site-specific management can contribute to an environmentally safe rice production increase.     

Field-scale spatial variability of soil calcium in a semi-arid region: Implications for soil erosion and site-specific management

Excess calcium(Ca) in soils of semi-arid and arid regions has negative effects on soil structure and chemical properties, which limits the crop root growth as well as the availability of soil water and nutrients. Quantifying the spatial variability of soil Ca contents may reveal factors influencing soil erosion and provide a basis for site-specific soil and crop management in semi-arid regions. This study sought to assess the spatial variability of soil Ca in relation to topography, hydraulic attributes, and soil types for precision soil and crop management in a 194-ha production field in the Southern High Plains of Texas,USA. Soils at four depth increments(0–2, 0–15, 15–30, and 30–60 cm) were sampled at 232 points in the spring of 2017. The Ca content of each sample was determined with a DP-6000 Delta Premium portable X-ray fluorescence(PXRF) spectrometer. Elevation data was obtained using a real-time kinematic GPS receiver with centimeter-level accuracy. A digital elevation model(DEM) was derived from the elevation data, and topographic and hydraulic attributes were generated from this DEM. A generalized least-squares model was then developed to assess the relationship between soil Ca contents of the four layers and the topographic and hydraulic attributes. Results showed that topographic attributes, especially slope and elevation, had a significant effect on soil Ca content at different depths(P 0.01). In addition, hydraulic attributes, especially flow length and sediment transport index(STI), had a significant effect on the spatial distribution of soil Ca. Spatial variability of soil Ca and its relationships with topographic and hydraulic attributes and soil types indicated that surface soil loss may occur due to water or wind erosion, especially on susceptible soils with high slopes. Therefore, this study suggests that the application of PXRF in assessing soil Ca content can potentially facilitate a new method for soil erosion evaluation in semi-arid lands. The results of this study provide valuable information for site-specific soil conservation and crop management.     

结合多等级代表性采样和模糊隶属度的区域土壤制图方法

High-resolution and detailed regional soil spatial distribution information is increasingly needed for ecological modeling and land resource management. For areas with no point data, regional soil mapping includes two steps: soil sampling and soil mapping. Because sampling over a large area is costly, efficient sampling strategies are required. A multi-grade representative sampling strategy, which designs a small number of representative samples with different representative grades to depict soil spatial variations at different scales,could be a potentially efficient sampling strategy for regional soil mapping. Additionally, a suitable soil mapping approach is needed to map regional soil variations based on a small number of samples. In this study, the multi-grade representative sampling strategy was applied and a fuzzy membership-weighted soil mapping approach was developed to map soil sand percentage and soil organic carbon(SOC) at 0–20 and 20–40 cm depths in a study area of 5 900 km2 in Anhui Province of China. First, geographical sub-areas were delineated using a parent lithology data layer. Next, fuzzy c-means clustering was applied to two climate and four terrain variables in each stratum. The clustering results(environmental cluster chains) were used to locate representative samples. Evaluations based on an independent validation sample set showed that the addition of samples with lower representativeness generally led to a decrease of root mean square error(RMSE). The declining rates of RMSE with the addition of samples slowed down for 20–40 cm depth, but fluctuated for 0–20 cm depth. The predicted SOC maps based on the representative samples exhibited higher accuracy, especially for soil depth 20–40 cm, as compared to those based on legacy soil data. Multi-grade representative sampling could be an effective sampling strategy at a regional scale. This sampling strategy, combined with the fuzzy membership-based mapping approach, could be an optional effective framework for regional soil property mapping. A more detailed and accurate soil parent material map and the addition of environmental variables representing human activities would improve mapping accuracy.     

Simultaneous Preservation of Soil Structural Properties and Phospholipid Profiles: A Comparison of Three Drying Techniques

There is a need to simultaneously preserve evidence of interactions between the biological community and soil structural properties of a soil in as near an intact (natural) state as possible.Three dehydration techniques were implemented and assessed for their ability to minimise disruption of both biological and physical properties of the same arable soil sample.Dehydration techniques applied until samples were at constant weight were i) air-drying at 20℃ (AD); ii)-80℃ freeze for 24 h,followed by freeze-drying (-80FD); and iii) liquid nitrogen snap freeze,followed by freeze-drying(LNFD) and were compared to a moist control.Physical structure was determined and quantified in three dimensions using X-ray computed tomography and microbial phenotypic community composition was assessed using phospholipid fatty acid (PLFA) profiling.This study confirms that any form of dehydration,when preparing soil for simultaneous biological and physical analysis,will alter the soil physical properties,and cause some change in apparent community structure.Freeze-drying (both the LNFD and -80FD treatments) was found to minimise disruption (when compared to the moist control soil) to both the soil physical properties and the community structure and is a preferable technique to air-drying which markedly alters the size and character of the pore network,as well as the phenotypic profile.The LNFD was the preferred treatment over the -80FD treatment as samples show low variability between replicates and a fast turn-around time between samples.Therefore snap freezing in liquid nitrogen,followed by freeze drying is the most appropriate form of dehydration when two sets of data,both physical and biological,need to be preserved simultaneously from a soil core.     

印度的主要茶叶产区土壤的主要化学性质

Major chemical properties of tea-growing soils are of paramount importance for better management in a sustainable fashion.Therefore,this study was carried out to understand the major soil chemical properties of major tea（Camellia sinensis L.）-growing areas,Dibrugarh and Tinsukia districts,in the state of Assam,India.A total of 991 surface soil samples were collected from 15 large tea estates（TEs） for analysis of their major chemical properties.Soil pH ranged from 3.61 to 6.81.Total organic carbon and total nitrogen ranged from 2.4 to 47.3 and 0.24 to 3.60 g kg^-1,respectively.All soils were sufficiently rich in plant-available potassium（as K₂O）,which ranged from 127.71 to 252.33 mg kg^-1,exceeding the amount prescribed for optimum tea yield of > 100 mg kg^-1.Plant-available sulfur among soil samples widely varied from 4 to 129 mg kg^-1.Results of hierarchical clustering analysis for homogenous grouping of the 15 TEs based on soil chemical properties showed that the 15 TEs could be classified into three distinct groups which consisted of6,8 and 1 TEs,respectively.Based on the Kolmogorov-Smirnov（K-S） test,the best fitted theoretical probability distributions were found out for different soil chemical properties.It could be concluded that a balanced fertilizer application would be needed as a part of tea improvement program using soil chemical test.     

江苏省外生菌根真菌资源调查

A total of 1400 soil samples from the plow layer （0-20 cm） at an approximate interval of 5 km were collected in the autumn of 2002 over the entire black soil arable crops region to determine the spatial variability of seven variables, such as total organic matter content （OMC）, total N, total P, total K, alkali-dissolvable N （AN）, available P （AP） and available K （AK）, with classical statistics and geostatistical analysis across the entire black soil area in Northeast China. In nonsampled areas ordinary kriging was utilized for interpolation of estimated nutrient determinations. Classical statistics revealed highly significant （P ≤ 0.01） correlations with all seven of the soil properties, except for OMC with AP and total K with AK. In addition, using coefficients of variation, all soil properties, except for total K, were moderately variable. A geostatistical analysis indicated that structural factors, such as parent material, terrain, and water table, were the main causes of the spatial correlations. Strong spatial correlations were noted with OMC, total N, total P, AN, and AP, while they were moderate for total K and AK. The effective spatial autocorrelation of OMC, total N, total P, and AN ranged from 1 037 to 1353 km, whereas the ranges of total K, AP, and AK were only from 6 to 138 km. The fit of the experimental scmi-variograms to the theoretical models indicated that except for AN, kriging could successfully interpolate other six variables. Thns, the geostatistical method used on a large scale could accurately evaluate the spatial variability of most black soil nutrient properties in Northeast China.     

华北平原土壤质量与农业生产的关系

Sustainable agricultural production is of vital importance to food supply security. This study aimed to investigate crop yield response to spatial variability of soil quality at a county scale in the North China Plain(NCP) and subsequently derive key soil quality indicators. Soil samples were geo-referenced and taken in 2008 from both surface(0–20 cm) and subsurface(20–40 cm) layers in132 fields throughout the Fengqiu County, located in the centre of the NCP, for subsequent soil properties' analyses. Annual crop yields were obtained from the same fields where soil samples were collected. Soil quality was evaluated based on a fuzzy set with 13 soil properties, and its spatial distributions were investigated by integrating geostatistical analysis and geographic information system(GIS) techniques. Soil quality indices were classified into five grades, and their spatial distributions were mapped within the county.The surface soil qualities were about one to two grades higher than the subsurface soil. The quality indices for surface and subsurface soils were positively associated with the annual crop yields, suggesting the importance of both. Soil organic matter, total nitrogen,available P, and available K contributed 50% of the combined weight to the soil quality index and were identified as key indicators of soil quality status in the area in terms of sustainability.     

基于土壤传递函数的土壤持水特性间接估计及其空间变异性研究

A total of 107 soil samples were taken from the city of Qingdao,Shandong Province,China.Soil water retention data at 2.5,6,10,33,100,300,and 1 500 kPa matric potentials were measured using a pressure membrane apparatus.Multiple linear regression (MLR) was used to develop pedotransfer functions (PTFs) for single point estimation and van Genuchten parameter estimation based on readily measurable soil properties,i.e.,MLR-based point (MLRP) PTF and MLR-based parametric (MLRV) PTF.The double cross-validation method was used to evaluate the accuracy of PTF estimates and the stability of the PTFs developed in this study.The performance of MLRP and MLRV PTFs in estimating water contents at matric potentials of 10,33,and 1 500 kPa was compared with that of two existing PTFs,the Rawls PTF and the Vereecken PTF.In addition,geostatistical analyses were conducted to assess the capabilities of these PTFs in describing the spatial variability of soil water retention characteristics.Results showed that among all PTFs only the Vereecken PTF failed to accurately estimate water retention characteristics.Although the MLRP PTF can be used to predict retention characteristics through traditional statistical analyses,it failed to describe the spatial variability of soil water retention characteristics.Although the MLRV and Rawls PTFs failed to describe the spatial variability of water contents at a matric potential of 10 kPa,they can be used to quantify the spatial variability of water contents at matric potentials of 33 and 1 500 kPa.     

不同样点数量对土壤有机质空间变异表达的影响

以南京市六合区为研究区,通过完全随机和限制最小采样间距抽样分别设置5个样点系列,基于每个样点系列100次重复抽样的变异结构推断及空间预测误差结果,探讨了不同样点数量对土壤有机质(SOM)空间变异表达的影响。结果表明,两种抽样方式降低样点数量后推断的SOM含量的块金效应(C0/C0+C)均随样点数量减少而降低且限制最小采样间距抽样推断的C0/C0+C要低于完全随机抽样方法,说明适当的减少样点数量以便降低与SOM变异尺度不匹配的样点对变异结构推断的影响有助于提高SOM空间变异结构表达的可靠性。普通Kriging预测的SOM误差对比则表明,尽管两种抽样方式下空间预测的均方根误差(RMSE)随样点数量变化而波动,但均低于全部样点的预测误差;通过限制最小采样间距减少样点至250个时,SOM空间预测的RMSE最低,较全部样点预测误差降低了6%,因此,为了实现样点密度与SOM变异尺度相匹配,合理设置土壤采样点的间距及样点数量较单纯的增加采样点数量更为重要。     

县域土壤有机质空间变异特征及合理采样数的确定

以有机质为例,以高密度土壤养分采样数据为数据源,通过随机抽取生成不同采样密度的样点数据,分析了不同采样密度下土壤有机质的空间变异特征及县域合理采样数。研究结果表明,在一定研究尺度下采样密度对土壤养分的模型拟合、变程和空间相关性没有显著影响,即适当减少样点数可以满足插值分析的需要,充分考虑土壤养分空间变异评价的精度分析,确定县域土壤有机质合理采样数应控制在400个以上。     

Sampling procedure simulating on‐the‐go sensing for soil nutrients

The emergence of a new sensor technology based on the use of ion‐selective membranes provides an increasing number of opportunities for on‐the‐go field measurements of soil nutrients and soil pH. In the future, on‐the‐go sensing should provide a cost‐effective monitoring of heterogeneous soils with high sampling resolution. It is suitable for site‐specific management because it can be focused on the spatial representativity of observation. This study evaluates the on‐the‐go‐sensing sampling design by comparing it with a standard approach to soil sampling for soil pH and the base nutrients P, K, and Mg under local field conditions in Germany. Soil samples were taken in two test sites at a resolution and in a manner as if they were sampled with an on‐the‐go sensing system and were compared with soil samples taken at a coarser resolution and with standard methods. In general, a higher variability was observed among the on‐the‐go samples due to their smaller sample support. The finer sampling resolution of the on‐the‐go design improved field‐scale semivariogram‐analysis results, identifying the spatial structures for soil pH, P, and Mg clearly. In addition, kriged maps of these soil parameters had predominantly higher estimation accuracies. However, the on‐the‐go samples were strongly influenced by the small‐scale variability of K in one of the test sites. This variability increased the kriging standard deviation for K by 50% compared with standard sampling design. Despite of this problem, the on‐the‐go‐sensing sampling design revealed field‐scale spatial variability for base nutrient status more accurately. Except for K, the mean absolute error of fertilizer‐application maps was reduced when using the on‐the‐go sample design in comparison with the standard sample design (Ca: 210/268 kg ha^–1, P: 2.85/6.75 kg ha^–1, K: 13.7/6.0 kg ha^–1, Mg 5.7/6.8 kg ha^–1). This will reduce over‐ and underfertilization using variable‐rate fertilizer‐application systems. In the future, it will be of interest if real on‐the‐go soil‐sensor measurements exhibit the same variability behavior addressed here or if results will differ substantially.     

不同取样方式下土壤质地空间插值的精度分析

为研究土壤质地的合理取样方式,进而研究其空间变异情况,为田间施肥及灌溉提供依据,本试验利用地统计学方法和GIS技术,在重庆市彭水县重庆烟草试验站,利用289个表层土样,研究了16 m间距的栅格取样法(对照,253个土样,扣除36个验证样点)、34 m间距的栅格取样法(115个土样)和随机取样法(115个土样)3种取样方式下土壤质地的空间插值精度。3种土壤颗粒指标中粉粒占68.43%,砂粒含量最少,占12.68%,黏粒含量略高于砂粒。砂粒和黏粒具有中等强度的变异性,粉粒具弱变异性,且数据符合正态分布。地统计分析显示,在分析该区域土壤质地时,采用栅格取样方法应适当增大取样间距,而采用随机取样方法可适当缩小取样间距。交叉检验显示,土壤质地成分在3种取样方式下的插值精度均以对照最大,栅格取样次之,随机取样最小。综合考虑插值误差、样品采集和分析成本及时效性等因素,本研究建议在该区域进行土壤质地空间变异规律分析为生产服务时应采用随机取样。     

A New Method for Computing Reliable Sample Size for Prescribing Soil Test Based Nutrient Management Interventions

ABSTRACT

Conventional sampling schemes for soil test guided nutrient management do not duly consider spatial variability. Fisher’s least significant difference (LSD) classical technique is sometimes manipulated for computing minimum sample size. However, it does not consider spatial dependence and relies on sample variance. Here, we present a new LSD-based robust method that uses semivariogram sill as a variance surrogate and then explore through sensitivity analysis novel alternative measurement units to reduce sample size rendered large by spatial variability. For differentiating crop response based categories, 273–22,320 samples were required for primary nutrients. Required sample size for detecting desired critical shifts in micronutrient status varied from 16–28,854. Changing to millimole units for potassium (K) and iron (Fe) further reduced sample size significantly. Thus, LSD-based technique can be made robust by using geostatistical techniques. Conventional measuring units in highly variable plant nutrients can be replaced with more practicable and economical units.     

基于方差四叉树法的滨海盐土电导率采样布局研究

利用土壤空间变异特性和空间分布特征进行采样设计是当前土壤采样研究的重要内容。采用方差四叉树法（Variance quad-tree method，简称VQT），结合半方差函数，设计滨海盐土采样的最优布局。并利用普通克立格法对传统网格采样法与方差四叉树采样法所得到的不同的样点数目进行插值，计算估值误差并进行精度比较。结果发现，同样的样本数目，利用方差四叉树法得到的克立格估值误差明显地较利用网格采样法得到的克立格估值误差小，其采样效率提高约16％一25％。该方法的优势在于，可设计在土壤特性变异大的区域密集采样而在变异较小的区域稀疏地采样，从而在有效表达土壤空间变异性的同时，提高了采样效率，减少了采样成本。     

盐碱地土壤养分的空间变异及合理取样密度研究

本研究以东营市河口区新户土地开发项目二期为研究区,运用经典统计法和地统计分析相结合的方法,对土壤有机质、速效磷、速效钾、碱解氮等养分以及土壤全盐的空间变异性质进行研究,并对不同采样密度下有机质的空间插值结果进行分析比较,用均方根误差和相关系数检验不同密度下的插值精度,以确定盐碱地有机质的合理取样密度。结果表明,研究区速效钾的变异系数为18.4%,属于低等程度的变异;有机质、碱解氮、速效磷、土壤全盐的变异系数在57.4%~76.9%之间,属中等程度变异。研究区的各种土壤属性均具有较好的空间结构,表现出一定的空间自相关性。有机质和速效钾的空间变异性主要影响因素与成土母质、土壤类型、气候条件等有关,而碱解氮、速效磷、土壤全盐的空间变异性与耕作方式及农业生产中施肥等有关。随着采样点密度的增加,克里格插值精度提高,适当减小样点密度可以满足插值分析的需要,充分考虑土壤养分空间变异评价的精度分析,确定研究区土壤有机质合理取样数为111个,合理取样单元为48 hm~2,合理取样间距为692 m。     

Spatial distribution of soil physical properties of alluvial soils: a geostatistical approach

Knowledge of spatial variation of soil is important in site-specific farming and environmental modeling. Soil particles size and water distribution are most important soil physical properties that governing nearly all of the other attributes of soils. The objectives of this study were to determine the degree of spatial variability of sand, silt and clay contents, and water content at field capacity (FC), permanent wilting point (PWP), and available water content (AWC) of alluvial floodplain soils. Data were analyzed both statistically and geostatistically to describe the spatial distribution of soil physical properties. Soil physical properties showed large variability with greatest variation was observed in sand content (68%). Exponential and spherical models were fit well for the soil physical properties. The nugget/sill ratio indicates except clay all other soil physical properties were moderate spatially dependent (37–70%). Cross-validation of the kriged map shows that prediction of the soil physical properties using semivariogram parameters is better than assuming mean of observed value for any unsampled location. The spatial distribution of water retention properties closely followed the distribution pattern of sand and clay contents. These maps will help to planner to develop the variable rate of irrigation (VRI) for the study area.