市域尺度的稀有濒危土壤类型的界定与评价——以郑州市为例

在当今世界城市化高速发展的背景下,土壤资源的保护也越来越受到人们的关注,土壤多样性骤减也成为了全球关注的焦点,界定和评价稀有濒危土壤对于保护土壤资源及其多样性具有非常重要的指导意义。本文以郑州市为例,应用土壤类型密度和土壤多样性两种多样性测度方法分别对郑州市1 km×1 km和5 km×5 km网格尺度下基于不同分类级别的土壤空间多样性分布格局进行了分析和定量化研究;利用1988、2001、2007和2013年4期遥感资料进行土地利用分类,结合基于第二次土壤普查的1∶20万郑州市土壤图,采用多时相连续对比法对郑州市近25年来土地利用变化对土壤的扰动情况进行了分析;结合土壤多样性方法和传统评价方法界定和评价了稀有濒危土壤。结果表明,郑州市土壤整体分布较为均匀,且随着分类单元级别的降低,构成组分多样性指数升高,即分类越细,土壤类型分布越均匀;1988~2013年郑州市土壤受到非农建设扰动剧烈,干扰比例为16.01%,随着时间的推移,土壤受扰动的速度是呈上升趋势的;稀有土属有16种,濒危土属有2种,稀有濒危土属有4种。截止2013年濒危土属整体受到扰动比例高达35.38%,而稀有土属受到扰动比例为8.76%。     

Filling the European blank spot—Swiss soil erodibility assessment with topsoil samples

Soil erodibility, commonly expressed as the K‐factor in USLE‐type erosion models, is a crucial parameter for determining soil loss rates. However, a national soil erodibility map based on measured soil properties did so far not exist for Switzerland. As an EU non‐member state, Switzerland was not included in previous soil mapping programs such as the Land Use/Cover Area frame Survey (LUCAS). However, in 2015 Switzerland joined the LUCAS soil sampling program and extended the topsoil sampling to mountainous regions higher 1500 m asl for the first time in Europe. Based on this soil property dataset we developed a K‐factor map for Switzerland to close the gap in soil erodibility mapping in Central Europe. The K‐factor calculation is based on a nomograph that relates soil erodibility to data of soil texture, organic matter content, soil structure, and permeability. We used 160 Swiss LUCAS topsoil samples below 1500 m asl and added in an additional campaign 39 samples above 1500 m asl. In order to allow for a smooth interpolation in context of the neighboring regions, additional 1638 LUCAS samples of adjacent countries were considered. Point calculations of K‐factors were spatially interpolated by Cubist Regression and Multilevel B‐Splines. Environmental features (vegetation index, reflectance data, terrain, and location features) that explain the spatial distribution of soil erodibility were included as covariates. The Cubist Regression approach performed well with an RMSE of 0.0048 t ha h ha^?1 MJ^?1 mm^?1. Mean soil erodibility for Switzerland was calculated as 0.0327 t ha h ha^?1 MJ^?1 mm^?1 with a standard deviation of 0.0044 t ha h ha^?1 MJ^?1 mm^?1. The incorporation of stone cover reduces soil erodibility by 8.2%. The proposed Swiss erodibility map based on measured soil data including mountain soils was compared to an extrapolated map without measured soil data, the latter overestimating erodibility in mountain regions (by 6.3%) and underestimating in valleys (by 2.5%). The K‐factor map is of high relevance not only for the soil erosion risk of Switzerland with a particular emphasis on the mountainous regions but also has an intrinsic value of its own for specific land use decisions, soil and land suitability and soil protection.     

河南省多级地貌特征及与土壤多样性的关系

从土壤多样性向地多样性发展符合土壤地理学的研究趋势,选择河南省作为研究区,将地貌这一主要的地学要素加入到土壤多样性的研究中,并用改进的仙农熵公式对多级地貌空间分布多样性及其与土壤多样性的相关性进行探讨。首先,对河南省1︰175万地貌类型图进行矢量化得到地貌类型等级系统;然后,对地貌和土壤的构成组分多样性和2种不同分类体系的分支率进行计算并分析其特征;最后,在3 km×3 km网格尺度下分析地貌和土壤多样性间的相关性。研究表明:河南省共有3个一级地貌,12个二级地貌和37个三级地貌;随着土壤和地貌分类的等级细化,其分类个数和构成组分多样性值均呈上升趋势,即土壤和地貌所有分类单元在数量构成上的均匀程度越来越高;两种分类系统中,土壤分类较地貌分类有更详细的分类体系,且分支率有较大范围的变化;河南省一级地貌、二级地貌和三级地貌的空间分布多样性值和面积值均最大的类型分别是流水地貌、冲积平原和泛滥平坦地,是不同级别的优势地貌类型;一级地貌类型与土类、亚类和土属多样性间存在紧密的相关关系,且以流水地貌与土壤多样性间的相关性最强。     

Are There Arid Land Soilscapes in Southwestern Europe?

No studies have proven the existence of soil assemblages typical of arid lands in Europe. This study was carried out in a representative territory of the southeastern part of the Iberian Peninsula, Almería province, which is the driest part of Europe, to determine if soils characteristic of arid lands are present. In order to analyse the spatial distribution of soils, the authors made use of mathematical tools previously developed in biodiversity and pedodiversity analysis, such as richness, entropy indices, abundance distribution models, diversity‐area relationships and nested subset analysis. The study demonstrates that the soil types or pedotaxa are typical of mountainous arid lands. Shallow and weakly developed soils (e.g. Leptosols, Regosols and Arenosols), Calcisols, Gypsisols and Solonchaks, cover most of the study area, and pedodiversity analysis demonstrates that the pedotaxa spatial patterns follow the same regularities as in other areas, environments and scales. In view of the fact that the class of landscapes identified in this study is unique in Europe, the Tarbernas desert and other arid lands sites of the study area merit preservation as part of the European geological, geomorphological and pedological heritage. Copyright © 2015 John Wiley & Sons, Ltd.     

Preparing a soil carbon inventory of Saxony‐Anhalt,Central Germany using GIS and the state soil data base SABO_P

To obtain information on regional soil carbon (C) stocks, we prepared a soil C inventory for the central German State Saxony‐Anhalt. We used the State Soil Database SABO_P ( S achsen‐ A nhalt Bo den_ P rofildatenbank), which contains data from 3,600 soil profiles with 16,300 individual soil horizons and combined it with a geographic information system (GIS ArcView). Soil C stocks down to a depth of 100 cm were compiled for the three major soil regions of Saxony‐Anhalt (soil region 2: river valleys and floodplains; soil region 4: pre‐Weichselian moraines, and soil region 6: loess‐covered areas), which represent 83 % of the total state territory. The three major soil regions in Saxony‐Anhalt comprise on average 12.7 (soil region 2), 8.9 (soil region 4), and 12.8 kg C m^–2 (soil region 6). Total C content of the area investigated was 191 tg. The typical soils of the region, Haplic Chernozems, contain on average 13.9 kg C m^–2. With few exceptions, soil C did not vary significantly within identical taxonomic groups among different soil subregions. However, Chernozems of soil subregion 3 (Wanzlebener Löß‐Plateau; 19.8 kg C m^–2) contain significantly more C than the Chernozems of soil subregions 9 (Pollebener, Gerbstedter and Lettewitzer Löß‐Plateau; 12.1 kg C m^–2) and 15 (Barnstädter Löß‐Plateau 12.2 kg C m^–2). The spatial distribution of C stocks in Saxony‐Anhalt was represented in a map which suggests the existence of a strong link between the geomorphologic position of a given soil and its capacity to store organic C. Within the same taxonomic unit, finer textured soils stored more carbon than coarse‐textured ones.     

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.     

Spatial variation of soil test phosphorus in a long‐term grazed experimental grassland field

The spatial variation of soil test P (STP) in grassland soils is becoming important because of the use of STP as a basis for policies such as the recently EU‐introduced Nitrate Directive. This research investigates the spatial variation of soil P in grazed grassland plots with a long‐term (38 y) experiment. A total of 326 soil samples (including 14 samples from an adjacent grass‐wood buffer zone) were collected based on a 10 × 10 m² grid system. The samples were measured for STP and other nutrients. The results were analyzed using conventional statistics, geostatistics, and a geographic information system (GIS). Soil test P concentrations followed a lognormal distribution, with a median of 5.30 mg L^–1 and a geometric mean of 5.35 mg L^–1. Statistically significant (p < 0.01) positive correlation between STP and pH was found. Spatial clusters and spatial outliers were detected using the local Moran's I index (a local indicator of spatial association) and were mapped using GIS. An obvious low‐value spatial‐cluster area was observed on the plots that received zero‐P fertilizer application from 1968 to 1998 and a large high‐value spatial‐cluster area was found on the relatively high‐P fertilizer application plots (15 kg ha^–1 y^–1). The local Moran's I index was also effective in detecting spatial outliers, especially at locations close to spatial‐cluster areas. To obtain a reliable and stable spatial structure, semivariogram of soil‐P data was produced after elimination of spatial outliers. A spherical model with a nugget effect was chosen to fit the experimental semivariogram. The spatial‐distribution map of soil P was produced using the kriging interpolation method. The interpolated distribution map was dominated by medium STP values, ranging from 3 mg to 8 mg L^–1. An evidently low‐P‐value area was present in the upper side of the study area, as zero or short‐term P fertilizer was applied on the plots. Meanwhile, high‐P‐value area was located mainly on the plots receiving 15 kg P ha^–1 y^–1 (for 38 y) as these plots accumulated excess P after a long‐term P‐fertilizer spreading. The high‐ or low‐value patterns were in line with the spatial clusters. Geostatistics, combined with GIS and the local spatial autocorrelation index, provides a useful tool for analyzing the spatial variation in soil nutrients.     

Challenges of pedodiversity in soil science

Soil diversity is not a completely new concept in soil science. It has been discussed from early times but it was not challenged this much broad. Ibañez with introducing the pedodiversity opened a new conceptual window to ease the induction of the soils complexity, spatial and temporal evolution and distribution. Pedodiversity now attracts more attention and goes to open new windows in soil science. Pedodiversity faces now with different challenges, which could be critical in its way on. Do the current soil diversity indices conceptually define all aspects of soil variability, or do we need to bind them with other characteristics like taxonomic distances? How is the soil individualism defined within the context of spatial variability and soil continuum? How are pedocomplexity, connectance, pedodiversity and soil spatial structure related? Can the changes of soil diversity be accounted as the rate of soil development? Can a range of pedodiversity index be a scale for soil series definition? Initial and some of current pedodiversity studies were/are focused on the concepts and measurement of pedodiversity and soil complexity indices of soilscape compared with the biological diversity and complexity. However, for the pedogenetic studies, the most important issues are the evolutionary concerns out of this approach compared with the other biotic systems. The new contexts, which should be more undertaken in future studies are: functional diversity, temporal diversity, study of soil and landform extinction and preservation. The last question could be: how pedodiversity could be changed under different understanding levels? A case study has been carried out in Charmahal and Bakhtiary province, Iran. Its objectives are the following: comparing the pedodiversity indices combined with and without taxonomic distances within tow replication of a geomorphic surface (Pi 111). What the pedodiversity says here? Did the unique calcification process which rules the soil formation here result in endemism or soil zonality? Do different pedodiversity indices correlate with the soil patterns?     

A method to generate soilscapes from soil maps

Digital soil mapping for large areas is challenging if mapping resolution should be as high as possible and sampling should be as sparse as possible. Generally, the more complex the soil associations in a landscape, the more samples are required to systematically cover the entire feature space. Moreover, regions should be modeled separately if the patterns of spatial variation vary on subregion level. A systematic segmentation of a landscape into soilscapes is additionally important for a feasible application of soil‐sensing approaches. In this paper, we introduce a semiautomated approach to segment nominal spatial datasets based on the local spatial frequency distribution of the mapping units. The aim is to provide homogeneous and nonfragmented segments with smoothed boundaries. The methodological framework for the segmentation comprises different spatial and nonspatial techniques and focuses mainly on a moving‐window analysis of the local frequency distribution and a k‐means cluster analysis. Based on an existing soil map (1:50,000), we derived six segments for the Nidda catchment (Central Hesse, Germany), comprising 1600 km². As segmentation is based on a soil map, soilscapes are derived. In terms of the feature space, these soilscapes show a higher homogeneity compared to the entire landscape. Advantages compared to an existing map of landscape units are discussed. Segmenting a landscape as introduced in this study might also be of importance for other disciplines and can be used as a first step in biodiversity analysis or setting up environmental‐monitoring sites.     

土壤与地表水体空间分布格局的交互关系研究

水要素是重要的成土因素之一，土壤与地表水体空间分布格局之间存在密切联系。以中国中部典型农业区的土壤和地表水体数据为例，基于改良的土壤多样性计量方法计算并统计了1km网格尺度下的土壤类型个数、土壤构成组分多样性、土壤空间分布多样性和地表水体空间分布多样性等多类数据指数，探索了区域土壤与地表水体在地理空间分布格局上的内在联系。结果表明：①研究区内最具代表性土类潮土和褐土（两者面积加和占研究区总面积85%，两者空间分布多样性均大于0.8）的空间分布格局与区域地表水体的空间分布格局之间存在数据联系，回归分析中的判定系数R2大于0.5，这与水要素在两种土壤类型成土过程中所起的作用密切相关。②研究区面积的增加一般会造成地表水体对区域内土壤类型数量的影响作用减弱。与其他成土因素相比，水要素在土壤形成中影响作用的重要程度与研究尺度的大小有关。③基于资源地理空间分布离散性分析的土壤多样性计量方法及理论为水、土等不同资源类型的空间分布格局评价及其交互关系研究提供了理论及数据支持。     

Fertigation of humic substances improves yield and quality of broccoli and nutrient retention in a sandy soil

There is lack of information available concerning the effect of humic substances (HS) applied via fertigation on plant growth in sandy soils. Therefore, a field experiment was carried out at El‐Saff district (20 km southwest of Cairo), Egypt, to investigate the role of HS fertigation on water retention of a sandy soil, yield and quality of broccoli (Broccoli oleracea L.) as well as on soil nutrient concentration retained after harvest. The experiment consisted of six fertigation treatments (50%, 75%, and 100% of the recommended NPK‐fertilizer rate for broccoli combined with and without HS application at 120 L ha^–1) in a complete randomized block design with three replicates. Humic substances affected spatial water distribution and improved water retention in the root zone. Furthermore, application of HS increased total marketable yield and head diameter of broccoli as well as quality parameters (i.e., total soluble solids, protein, and vitamin C). Higher nutrient concentrations were found in the broccoli heads and concentrations of plant‐available nutrients in soil after harvesting were also higher, indicating an improvement in soil fertility. In conclusion, HS fertigation can be judged as an interesting option to improve soil water and nutrient status leading to better plant growth.     

紫色土区小流域土壤保持服务功能的空间分布特征

[目的]分析不同坡度、土壤类型、土地利用下的土壤保持服务功能分布,为减少土壤流失和改进土地利用规划提供科学依据。[方法]结合修正通用土壤流失方程(RUSLE)和GIS技术,以曲水河小流域为典型研究区,基于DEM、土壤、土地利用等基础数据,分析了研究区土壤保持服务功能的分布现状及影响因素。[结果](1)该流域土壤保持总量为1.10×107 t/a,单位面积土壤保持量为384.74t/(hm2·a),具有较高的生态系统服务功能重要性;(2)土壤保持服务功能总体呈现从河谷阶地逐渐向周边丘陵坡地递增的空间分布特征;(3)强烈及以上侵蚀强度区、8°~25°的坡度区、耕地、钙质紫泥田区和红棕紫泥土区应为土壤保持工作的热点区域。[结论]不同坡度、土壤类型、土地利用类型下土壤保持服务功能差异显著,可以通过改良土壤、提高植被覆盖和采取土壤侵蚀防治措施提高土壤保持服务功能水平。     

Root renewal of sugar beet as a mechanism of P uptake efficiency

Sugar beet (Beta vulgaris L.) was grown in two different long‐term P fertilization experiments on a sandy and a loamy soil. The P supply levels of the soils were ”︁low”, ”︁sufficient”, and ”︁high”, according to the German recommendation scheme. The low P level decreased shoot and storage root yield only on the loam soil, where the recovery of the P‐deficient plants after a drought period was slower than at a sufficient P supply. The size of the living root system, as determined by a conventional auger sampling method, peaked at early July and decreased until harvest on the sandy soil without any influence of the P level. On loam, the living root systems were more constant and larger at P shortage. Total root production, as determined by the ingrowth core method, was about 120 km m^—2 in the well P supplied loam treatments and 200 km m^—2 at P deficiency, which was 3—4 times and 5 times higher than the average size of the living root systems, respectively. Hence, a rapid root renewal took place. On sand, where no P deficiency occurred, total root production was not different between the P supply levels but higher than in the well‐supplied loam treatments. Modelling P uptake revealed that this root turnover and the concomitant better exploitation of the soil facilitates P uptake at a low P level in soil, but is of no advantage at a sufficient P supply. The increase of root production at P shortage increased calculated P uptake by 25% compared to a calculation with the ”︁usual” root production at a sufficient supply.     

Investigating translated data of the German soil‐quality assessment using pinpoint field validation

In contrast to modern soil‐profile characterization, alternative soil classifications, such as the German soil‐quality assessment (Bodenschätzung), bear a lower degree of scientific quality. However, despite originally created to determine the tax value of arable land and grassland, its high spatial resolution and complete areal coverage makes soil‐quality assessment a valuable tool. To assess its performance in a mountainous setting soil‐layer data of 60 soil pits, recorded in Bavaria (SE Germany) in the course of the soil‐quality assessment, were translated into German soil‐science terminology using the translation program NIBIS®. With regard to soil type and texture the translation was checked using pinpoint field validation based on soil‐science terminology. 57% of soil types and 61% of texture were correctly translated by NIBIS®. To obtain information about probable parameters that can explain the different results readily available parameters such as elapsed time between soil‐quality assessment and validation, altitude, slope, aspect, horizon thickness, lower edge of horizon, as well as weathering surface and silicate‐weathering rate derived from geological maps were used. Differences in topsoil texture were somewhat related to petrographic parameters, those of the lower subsoil showed a weak dependence to topographic parameters. The NIBIS® translation overrated the silt content to the expense of sand. Clay was the best‐matched texture class. The shift towards silty texture classes was the dominant factor for the differences of texture‐related values of the available water capacity and hydraulic conductivity. Both parameters as derived from the NIBIS® translation on the one and from field validation on the other hand were used to evaluate the water‐retention capacity of individual soil profiles. Despite differing input data the soils' water‐retention capacity was rated identical. Thus, a certain degree of disagreement between the texture data obtained from NIBIS® translation and from field validation is tolerable, if the eventual soil‐function evaluation is based on wide classes of texture or of secondary parameters derived from texture.     

Digital soil mapping using artificial neural networks

In the context of a growing demand of high‐resolution spatial soil information for environmental planning and modeling, fast and accurate prediction methods are needed to provide high‐quality digital soil maps. Thus, this study focuses on the development of a methodology based on artificial neural networks (ANN) that is able to spatially predict soil units. Within a test area in Rhineland‐Palatinate (Germany), covering an area of about 600 km², a digital soil map was predicted. Based on feed‐forward ANN with the resilient backpropagation learning algorithm, the optimal network topology was determined with one hidden layer and 15 to 30 cells depending on the soil unit to be predicted. To describe the occurrence of a soil unit and to train the ANN, 69 different terrain attributes, 53 geologic‐petrographic units, and 3 types of land use were extracted from existing maps and databases. 80% of the predicted soil units (n = 33) showed training errors (mean square error) of the ANN below 0.1, 43% were even below 0.05. Validation returned a mean accuracy of over 92% for the trained network outputs. Altogether, the presented methodology based on ANN and an extended digital terrain‐analysis approach is time‐saving and cost effective and provides remarkable results.     

Image analysis for non‐destructive and non‐invasive quantification of root growth and soil water content in rhizotrons

Studies aiming at quantification of roots growing in soil are often constrained by the lack of suitable methods for continuous, non‐destructive measurements. A system is presented in which maize (Zea mays L.) seedlings were grown in acrylic containers — rhizotrons — in a soil layer 6‐mm thick. These thin‐layer soil rhizotrons facilitate homogeneous soil preparation and non‐destructive observation of root growth. Rhizotrons with plants were placed in a growth chamber on a rack slanted to a 45° angle to promote growth of roots along the transparent acrylic sheet. At 2‐ to 3‐day intervals, rhizotrons were placed on a flatbed scanner to collect digital images from which root length and root diameters were measured using RMS software. Images taken during the course of the experiment were also analyzed with QUACOS software that measures average pixel color values. Color readings obtained were converted to soil water content using images of reference soils of known soil water contents. To verify that roots observed at the surface of the rhizotrons were representative of the total root system in the rhizotrons, they were compared with destructive samples of roots that were carefully washed from soil and analyzed for total root length and root diameter. A significant positive relation was found between visible and washed out roots. However, the influence of soil water content and soil bulk density was reflected on seminal roots rather than first order laterals that are responsible for more than 80 % of the total root length. Changes in soil water content during plant growth could be quantitifed in the range of 0.04 to 0.26 cm³ cm^—3 if image areas of 500 x 500 pixel were analyzed and averaged. With spatial resolution of 12 x 12 pixel, however, soil water contents could only be discriminated below 0.09 cm³ cm^—3 due to the spatial variation of color readings. Results show that this thin‐layer soil rhizotron system allows researchers to observe and quantify simultaneously the time courses of seedling root development and soil water content without disturbance to the soil or roots.     

Accumulation soils like “Ockererde”—forgotten soil units in soil‐classification systems

Accumulation soils like those known as “Ockererde” are not yet represented in the German and in international soil‐classification systems, even though they represent important members of catenas found in humid low‐mountain areas influenced by the translocation of interpedon matter. Currently, this soil is referred to as “(Hang‐)Oxigley”, though this does not take into account its water and matter dynamics. Six representative catenas in the Black Forest (SW Germany) will be used to describe the occurrence, extent, and properties of the accumulation‐affected “Ockererde” derived from a variety of parent materials at specific altitudes. On the basis of their morphological, chemical, and physical properties as well as matter dynamics, it is possible to distinguish “Ockererde” clearly from soil units with similar characteristics (“Lockerbraunerde”, Andosols). Finally, suggestions will be given for the classification of “Ockererde”.     

Effect of sampling density on regional soil organic carbon estimation for cultivated soils

An extensive knowledge of how sampling density affects soil organic C (SOC) estimation at regional scale is imperative to reduce uncertainty to a meaningful confidence level and aid in the development of sampling schemes that are both rational and economical. Using kriging prediction, this paper examined the effect of sampling density on regional SOC‐concentration estimations in cultivated topsoils at six scales in a 990 km² area of Yucheng County, a typical region in the N China Plain. Except the original data set (n = 394), five other sampling densities were recalculated using grids of 8 km × 8 km (n = 28), 8 km × 4 km (n = 44), 4 km × 4 km (n = 82), 4 km × 2 km (n = 142), and 2 km × 2 km (n = 257), respectively. Experimental SOC semivariances and kriging interpolations at six sampling density scales were calculated and modeled to estimate regional SOC variability. Accuracy of the effects of the five sampling densities on regional SOC estimations was assessed using the indices of mean error (ME) and root mean square error (RMSE) with 100 independent validation samples. By comparison with the kriged grid map derived from the 394 samples data set, the relative error (RE,%) was spatially calculated to highlight the spatial variability of prediction errors at five sampling‐density scales due to the intrinsic limitations of ME and RMSE in accuracy assessment. The results indicated that sampling density significantly affected the estimation of regional SOC concentration. Particularly when the sampling density was < 4 km × 4 km, the large spatial variation of SOC was concealed. Semivariance analysis indicated that different sampling density had significant effect on reasonable detection of the dominant factors which influenced SOC spatial variation. Greater sampling density could more exactly reveal regional SOC variation caused by human management. The prediction accuracy for regional SOC estimation increased with the increasing of sampling density. The critical areas with larger RE values should be intensified in the future sampling scheme, and the areas of lower RE values should be decreased relatively. A specific sampling scheme should be considered in accordance with the demand to the estimation accuracy of regional SOC stock at a certain confidence level. Our results will facilitate a better understanding of the effect of sampling density on regional SOC estimation for future sampling schemes by providing meaningful confidence levels.     

GIS‐based regionalization of soil profiles with Classification and Regression Trees (CART)

A map of soil texture profiles was derived from readily available spatial data in combination with information from soil profiles using CART (classification and regression trees). The primary purpose was to provide a regionalized predictor for the vertical hydraulic conductivity profiles to be used as an input variable to an evapo‐transpiration model. In contrast to former studies, the texture of 110 soil profiles taken in the 10 km² area was not averaged vertically but the profiles were grouped according to their hydraulic properties. Therefore, it was possible to include site specific profiles, e.g. with histic or argillic horizons. Despite of small sampling quantities (110 soil profiles grouped into 8 classes) a prediction probability of 60 to 70 % was achieved in most classes. The resulting map provides valuable information for the granulometric and hydrologic characterization of the study area.<?show $6#>     

The carbon content of soil and its geographical distribution in Great Britain

Abstract. England and Wales have 155 314 1 × 1 km squares, of which 140049 have more than 50% soil cover. The total soil organic carbon content, based on the dominant soil series and dominant land cover type, is estimated to be 2773 × 10⁶ t C. Scotland has 84929 1 × 1 km squares, of which 82 420 have a nominated dominant soil series. The total soil organic carbon content is estimated to be 19011 × 10⁶ t C, 6.85 times the total organic carbon content of the soil of England and Wales. The total organic carbon content of the soil of Great Britain is estimated to be 21 784 × 10⁶ t C, of which 87% is in Scottish soils and 75% is in Scottish peats. A map of the mean soil organic carbon content of 10 × 10 km squares of the National Grid using classes of equal range illustrates the narrow range of organic carbon contents of the soils of England and Wales and the dominance of organic carbon in Scottish soils. A map using the same data, but with classes of unequal ranges increasing in size with increasing carbon content, is better for showing detailed differences within England and Wales.