Small-scale spatial variability of selected soil biological properties

A strategy for sampling soil from intact monolith lysimeters was established based on measurements of spatial heterogeneity within the lysimeter area. This was part of an ongoing study to determine relationships between soil microbial diversity and nutrient loss by leaching. The sampling protocol had to allow collection of soil on a regular basis (as opposed to destructive sampling) and ensure high spatial independence of subsamples. On each of the two sites (one developed under organic crop management and the other under conventional crop management), ten 15 cm soil cores (sampling points) were taken from three areas (replicates) of 50 cm diameter (lysimeter surface area) and separately analysed for biotic (microbial biomass carbon and nitrogen; arginine deaminase activity) and abiotic (total carbon and nitrogen) soil properties. The data were tested for variability, expressed as coefficient of variance (biotic and abiotic), and spatial heterogeneity using geostatistics (biotic properties). The biotic soil properties showed significant differences among sampling points, whereas the abiotic parameters were useful in differentiating on a larger scale, i.e. between sites. For all soil properties tested, the differences among the replicates were smaller than those between the sites or among points indicating that, in the main experiment, all treatments can be sampled following the same pattern. Geostatistical analysis and fitting of an exponential model showed that a spatial structure exists in the biotic soil properties and that the samples are independent beyond separation distances of 25-30 cm. A revised sampling pattern consisting of 11 samples per lysimeter is described.     

Spatial variability of physico-chemical properties and hydraulic characteristics of a gravelly calcareous soil

Due to the existence of gravelly soils and the lack of sufficient research on such soils, this study was carried out on a gravelly calcareous soil. Selected physico–chemical and hydraulic soil attributes were determined at 69 points on a nested-sampling design. Hydraulic characteristics including unsaturated hydraulic conductivity (K _ψ) and sorptivity coefficient (S) at six applied tensions of 0 to 0.2 m, and sorptive number (α) and macroscopic capillary length (λ) at five applied tensions of 0.03 to 0.2 m were determined using a tension disc infiltrometer. Hydraulic and chemical soil attributes were the highest and the lowest variants, respectively. The maximum and minimum values for the coefficient of variation (CV) in all the measured physico-chemical and hydraulic soil attributes were obtained for α_0.2 and soil pH, respectively. Minimum, maximum, mean and variance values of K _ψ, S and α decreased as applied tension increased. Although the pattern was reversed for λ. The majority of soil attributes showed the spatial structure with dominant spherical and exponential models for physico-chemical and hydraulic attributes, respectively. Range values of semi-variograms were obtained between 4.6 m (for α_0.03) and 211 m (for clay, gravel content and soluble Mg). In general, range values were 99.60, 82.05 and 40.2 m for physical, chemical and hydraulic soil attributes, respectively, indicating that the physical soil attributes influenced neighboring values over greater distances than the other soil attributes. This enables soil scientists to use measured soil physical data over greater distances to estimate attributes in the unsampled locations.     

Short-term CO2 emissions from planted soil subject to elevated CO2 and simulated precipitation

Carbon dioxide emissions from soils beneath canopies of two Mediterranean plants, Artemisia absinthium L. and Festuca pratensis Huds. cv. Demeter, were monitored over a 7-day period that included an artificial precipitation event of 4 cm. The experiments were conducted using 0.2 m³ soil microcosms inside greenhouses with CO₂ concentrations of either 360 or 500 μmol mol⁻¹. Carbon dioxide flux from the soil surface, as calculated using a diffusive transport model agreed well with CO₂ flux measurements made using a dynamic flow system. Soil CO₂ emissions did not differ significantly between the 360 and 500 μmol mol⁻¹ CO₂ treatments when soils were dry (volumetric soil moisture content ≤9%). A simulated precipitation event caused an immediate exhalation of CO₂ from soil, after which CO₂ emissions declined slightly and remained constant for approximately 36 h. CO₂ emissions from soil microcosms with F. pratensis plants growing in 500 μmol mol⁻¹ CO₂ then rose to levels that were significantly greater than CO₂ emissions from soils in the microcosms exposed to 360 μmol mol⁻¹ CO₂. For A. absinthium growing in 500 μmol mol⁻¹ CO₂, the rise in soil CO₂ emissions following the wetting event was not significantly greater than emissions from soils with A. absinthium growing under 360 μmol mol⁻¹ CO₂. A. absinthium above ground biomass increased by 46.1 ± 17.9% (mean ± S.E., n = 4, P ≤ 0.05). Above ground biomass did not significantly increase for F. pratensis (14.4 ± 6.5%, P ≥ 0.10). Root biomass, on the other hand, increased for both species; by 50.6 ± 17.9% (P ≤ 0.05) for A. absinthium and by 55.9 ± 12.7% (P ≤ 0.05) for F. pratensis. Our results demonstrate two events following precipitation onto dry soils, an immediate release of CO₂ followed by a gradual increase from enhanced biological activity The gradual increase was greater for the herbaceous ruderal perennial F. pratensis under elevated CO₂.     

Short-range spatial variability of soil physico-chemical variables related to earthworm clustering in a neotropical gallery forest

In this study, we investigated the spatial distribution of an earthworm community together with the heterogeneity of selected soil properties in a gallery forest (GF) of the Colombian “Llanos”. We performed fine-scale spatial variability by intensively sampling 100 points distributed in the nodes of a regular grid with 5 m inter-sample distance. Non-parametric statistics were used and included SADIE analysis and partial Mantel test, in addition to geostatistics (semi-variograms) and correlogram computation. Our results indicated that the spatial distribution of earthworms was characterized by areas of presence (patches) and absence (gaps), although the general pattern was random at the scale of this study (<5 m), while soil physico-chemical characteristics showed a clumped spatial distribution. Contrary to previous results reported for the nearby savanna, a significant spatial association was found for two competing endogeic species Andiodrilus sp. and Glossodrilus sp. in the GF. Semi-variograms of soil environmental factors were adjusted to model families most commonly used (spherical and linear), and correlograms for earthworms showed significant positive and negative spatial autocorrelation for lag distances <15 m and >30 m, respectively. Partial Mantel test revealed specific significant relationships between soil variables and some species. The earthworm community of the GF displayed a random structure in a spatially clumped soil environment, and our results suggested that spatial distribution observed for some species could be the result of preferential selection of soil environmental factors. In other words, soil heterogeneity contributed to the formation of population patches for some earthworm species. The variability of suitable sites (resource availability patchiness) exerted an influence in the spatial distribution of earthworms at the scale used in this study, and we identified the spatial scale at which both environmental heterogeneity could influence and express earthworm impact on soil properties.     

紫色土坡耕地土壤物理性质空间变异对土壤侵蚀的响应

为了研究不同坡度和坡长的耕地上土壤侵蚀对土壤物理性质空间变异的影响,通过地形测量、137 Cs示踪、土壤物理性质分析等方法对川中丘陵紫色土区土壤物理性质对土壤侵蚀的响应进行了研究,结果表明：在中等坡度（16.60%～25.10%）的梯坡地上,耕作侵蚀处于主导地位,是导致耕层土壤物理性黏粒含量和容重在梯坡地上总体差异不大（CV＜6.3%）,且与137Cs含量不相关的主要原因;在已退耕还林的陡梯坡地上（35.60%）,水蚀占据主导地位,导致耕层土壤物理性黏粒含量和容重均与137Cs的含量显著相关。在长坡耕地上(10.10%),具有分选搬运能力的水力侵蚀占据主导地位,致使耕层土壤物理性黏粒含量与137Cs的含量具有显著的相关关系,而容重却与137Cs含量没有显著的相关关系。川中丘陵区坡耕地上,耕作侵蚀和水蚀共同作用于土层深度,使土层深度在坡顶、上坡最浅,在坡脚最深,顺坡向下逐渐增加。因此,在川中丘陵区不同坡长的坡耕地上,占主导地位的土壤侵蚀类型导致坡耕地上土壤物理性质出现相应的变化。     

Investigation and prediction spatial variability in chemical properties of agricultural soil using geostatistics

Determination of the chemical characteristics of soil for balanced fertilization on large scales is an important factor in achieving a precision agriculture. Laboratory analyses of soil properties are usually expensive and time consuming. Surmounting these problems is possible using geostatistics. Therefore, this research aims at selecting a proper interpolation method using 213 soil samples for alfalfa farmland in Hamadan Province, Iran. Various factors such as pH, EC, , , K, P, Fe, Zn, B and Co were measured. Ordinary kriging and co-kriging were assessed to derive maps of soil physico-chemical properties, using mean absolute error (MAE), mean bias error (MBE), root mean squared error (RMSE) and average kriging standard error (AKSE) as statistical criteria. Variography analysis indicated that the ranges of influence for pH, EC, , , K, P, Zn, Fe, B and Co were 65, 55, 78, 79, 75, 60, 50, 65, 70 and 30 km, respectively, and the measuring error varied between 0.366 and 0.843. The results revealed that, based on precision criteria, co-kriging was the best method for interpolating the chemical properties of soil. Finally, using to the co-kriging for each determined variable, a related zoning map for fertility management of the study area was prepared.     

华北半干旱区土壤养分和植被特征的小尺度空间异质性研究

A field experiment was conducted at Kezuohouqi County, Inner Mongolia Autonomous Region of China, which was located on the southeastern edge of the Horqin Sandy Land, to study the spatial variability of soil nutrients for a small-scale, nutrient-poor, sandy site in a semi-arid region of northern China; to investigate whether or not there were ＂islands of fertility＂ at the experimental site; and to determine the key nutrient elements that sustained ecosystem stability. Results obtained from geostatistical analysis indicated that the spatial distribution pattern of soil total nitrogen （STN） was far different from those of soil organic matter （SOM）, total phosphorus （STP）, and total potassium （STK）. Compared to SOM, STP, and STK, STN had a lower structural heterogeneity ratio and a longer range, while other elements were all similar. In addition, STN had an isotropic spatial structure, whereas the others had an anisotropic spatial structure. The spatial structure patterns of herbage species, cover, and height also differed, indicating that spatial variability was subjected to different ecological factors. Differences in the spatial variability patterns among soil nutrients and vegetation properties showed that soil nutrients for a small-scale were not the primary limiting factors that influenced herbage spatial distribution patterns. Incorporating spatial distribution patterns of tree species, namely, Pinus sylvestris var. mongolica Litv. and shrub Lespedeza bicolor Turcz. in a research plot and using fractal dimension, SOM, STP, and STK were shown to contribute to the ＂islands of fertility＂ phenomenon, however STN was not, possibly meaning that nitrogen was a key limiting element. Therefore, during restoration of similar ecosystems more attention should be given to soil nitrogen.     

利用MATLAB研究土壤水分空间变异初探

本文利用强大的数据计算分析软件MATLAB对土壤水分空间变异进行分析,并通过对样地数据插值和趋势面分析,方便地得出了样地土壤水分的变化趋势,计算分析结果对水土保持和农田灌溉都有很好的指导作用。     

Neural network ensemble residual kriging application for spatial variability of soil properties

High quality, agricultural nutrient distribution maps are necessary for precision management, but depend on initial soil sample analyses and interpolation techniques. To examine the methodologies for and explore the capability of interpolating soil properties based on neural network ensemble residual kriging, a silage field at Hayes, Northern Ireland, UK, was selected for this study with all samples being split into independent training and validation data sets. The training data set, comprised of five soil properties: soil pH, soil available P, soil available K, soil available Mg and soil available S,was modeled for spatial variability using 1) neural network ensemble residual kriging, 2) neural network ensemble and 3) kriging with their accuracies being estimated by means of the validation data sets. Ordinary kriging of the residuals provided accurate local estimates, while final estimates were produced as a sum of the artificial neural network (ANN) ensemble estimates and the ordinary kriging estimates of the residuals. Compared to kriging and neural network ensemble,the neural network ensemble residual kriging achieved better or similar accuracy for predicting and estimating contour maps. Thus, the results demonstrated that ANN ensemble residual kriging was an efficient alternative to the conventional geo-statistical models that were usually used for interpolation of a data set in the soil science area.     

Functional dependencies of soil CO2 emissions on soil biological properties in northern German agricultural soils derived from a glacial till

Agricultural soil CO₂ emissions and their controlling factors have recently received increased attention because of the high potential of carbon sequestration and their importance in soil fertility. Several parameters of soil structure, chemistry, and microbiology were monitored along with soil CO₂ emissions in research conducted in soils derived from a glacial till. The investigation was carried out during the 2012 growing season in Northern Germany. Higher potentials of soil CO₂ emissions were found in grassland (20.40 µg g^?1 dry weight h^?1) compared to arable land (5.59 µg g^?1 dry weight h^?1) within the incubating temperature from 5°C to 40°C and incubating moisture from 30% to 70% water holding capacity (WHC) of soils taken during the growing season. For agricultural soils regardless of pasture and arable management, we suggested nine key factors that influence changes in soil CO₂ emissions including soil temperature, metabolic quotient, bulk density, WHC, percentage of silt, bacterial biomass, pH, soil organic carbon, and hot water soluble carbon (glucose equivalent) based on principal component analysis and hierarchical cluster analysis. Slightly different key factors were proposed concerning individual land use types, however, the most important factors for soil CO₂ emissions of agricultural soils in Northern Germany were proved to be metabolic quotient and soil temperature. Our results are valuable in providing key influencing factors for soil CO₂ emission changes in grassland and arable land with respect to soil respiration, physical status, nutrition supply, and microbe-related parameters.     

Grassland rehabilitation significantly increases soil carbon stocks by reducing net soil CO2 emissions

Restoration of degraded grasslands through improved management is among the possible sustainable solutions to compensate for anthropogenic soil carbon (C) emissions. While several studies have shown a positive effect of rehabilitation on soil C, the impact on soil CO₂ emissions is still uncertain. Therefore, this study aimed at quantifying the impact of grassland rehabilitation on soil CO₂ emissions in a degraded grassland, South Africa. Commonly used rehabilitation practices were considered, that is rotational grazing (RG), livestock exclosure with fertilizer application (EF) and annual burning (AB), all being compared with traditional free grazing (FG). A total of 2880 in situ measurements of CO₂ emissions were performed over 2.5 years under field conditions simultaneously with aboveground biomass, soil temperature, water content and soil organic C (SOC) to understand the changes in C fluxes. The RG performed the best under degraded grasslands by decreasing net CO₂ emissions (per g of C) by 17% compared to FG, while EF increased emissions by 76% and AB had similar emissions to FG. The lower net emission under RG is associated with an increase in SOC stocks by 50% and aboveground biomass by 93%, after three years of implementation. Soil CO₂ emissions were correlated positively to aboveground biomass and topsoil temperature (r = 0.91 and 0.60, respectively), implying a high effect of grass cover on soil microclimate and microbial activity. These results suggested RG as a potential cost-effective nature-based soil management strategy to increase SOC stocks into degraded grassland. However, long-term trials replicated in different environments are still required.     

Soil tillage and cover crop on soil CO2 emissions from sugarcane fields

Soil tillage is an agricultural practice that directly affects the global carbon cycle. Our study sought to assess the implications of adopting sunn hemp cover crops with different tillage practices on CO₂ emissions for two soil types (clayey and sandy soil) cultivated with sugarcane in Brazil. The experimental design was a split‐plot with randomized blocks, with the main plots being with cover crop or fallow and sub‐plots being under conventional or minimum tillage. Our results indicate that during the first 50 days after soil tillage, the variation in soil CO₂ emissions was stimulated by cover crop and soil tillage, while after that, it became dominated by the root respiration of sugarcane plants. We also found that over the first 97 days after the tillage, the clayey soil showed differences between minimum tillage with cover crop and fallow. Conversely, for sandy soil over the first 50 days following, there were differences between the tillage systems under cover cropping. Emissions from sugarcane rows were found to be greater than those from inter‐row positions. We concluded that soils under different textural classes had distinct patterns in terms of soil CO₂ emissions. The correct quantification of CO₂ emissions during the sugarcane renovation period should prioritize having a short assessment period (~50 days after soil tillage) as well as including measurements at row and inter‐row positions.     

Linkages between soil micro-site properties and CO2 and N2O emissions during a simulated thaw for a northern prairie Mollisol

Biologically derived emissions of carbon dioxide (CO₂) and nitrous oxide (N₂O) at 0 °C vary with soil depth during soil thawing. Micro-site soil properties, especially those which influence porosity and substrate availability, also vary with depth and may help explain gas emissions. Intact soil cores collected to a depth of 80 cm from an undisturbed prairie Mollisol in central North Dakota were uniformly subjected to distinct temperature steps during a simulated soil thaw (−15 to 5 °C) and sampled for CO₂ and N₂O emissions throughout the soil profile. Emission data were fit to a first order exponential equation (E = αe^βT). Cores were then analyzed in 10 cm depth increments for micro-site properties including root length and mass, aggregation, and organic substrate availability (available, aggregate-protected and mineral-bound pools). Both CO₂ and N₂O emissions at 0 °C declined exponentially with depth. Emissions of CO₂ and N₂O at 0 °C were strongly related to root length (R² = 0.80 and 0.76, respectively), root mass (R² = 0.56 and 0.74), large macroaggregate mass (R² = 0.63 and 0.54), and aggregate-protected organic matter (R² > 0.57), while available organic matter was related to CO₂ (R² > 0.60) and not N₂O. When CO₂ and N₂O emissions were normalized by available and aggregate-protected carbon pools, respectively, nutrient use efficiency increased significantly with depth. Results suggest CO₂ and N₂O emissions are (1) positively influenced by the rhizosphere and (2) differentially affected by substrate pool or location. CO₂ emissions were more positively affected by available substrate, while N₂O emissions were more positively affected by less labile, aggregate-protected substrate.     

灌溉方式和秸秆还田对设施番茄田CO2排放的影响

中国北方下沉式设施菜田表层土壤缺失,以及高温高湿的环境条件,导致耕层土壤有机质含量低、矿化快。如何减缓土壤有机质矿化,是该文所关注的焦点问题。该研究采用二因素试验设计,主因素为灌溉方式（传统畦灌施肥、滴灌施肥）,副因素为秸秆（含C量为0、3 500 kg/hm2）。测定了48 h内每3 h的CO2排放通量,以及全生育期CO2日排放通量、土壤温度。结果表明：1）08:00−09:00测定的土壤CO2排放通量与CO2日均排放通量不存在显著差异,二者呈极显著线性正相关关系,其决定系数为0.987;而其他时段测定值与日均值均存在显著差异。2）与传统畦灌相比,无论是否添加秸秆,滴灌处理均显著降低了CO2累积排放量。3）CO2排放高峰出现在定植后8～15 d,随后逐渐降低并趋于平稳;定植后40 d内能检测到处理间CO2日排放通量的差异,此后处理间差异不显著。4）CO2累积排放通量和土壤积温呈显著正相关关系。综上所述,滴灌施肥栽培体系可显著降低土壤CO2排放量,有利于设施菜田土壤有机质的积累。     

分形方法在土壤特性空间变异研究中的应用

土壤特性空间变异研究对土壤制图、精准施肥、农业可持续发展等方面具有重要意义。分形几何学是一种探索复杂性的事物的新科学方法和理论,在研究土壤特性空间变异中将有大有可为。本文主要综述了 2000 年以后分形理论在土壤物理特性、化学特性、水分特征及状态参数的空间变异研究中的应用进展,最后对分形理论在土壤特性空间变异研究中的发展方向进行了展望。     

白芷土壤的成土因素与理化特性研究

采用野外调查与室内化学分析相结合的方法,对白芷土壤的成土母质、气候、地形地貌、水文地质等成土因素和土壤物理化学性质进行了研究白芷道地产区气候温和,雨量充沛,热量资源丰富,春季气温回升快,夏季雨热同季、秋季气温下降快,冬无严寒,白芷种植在涪江沿岸一级阶地,土壤沙性重,容重大,质地轻壤,呈微碱性,氮含量中等,磷缺乏,钾含量丰富．     

川麦冬土壤的成土因素与理化特性研究

采用野外调查与室内化学分析相结合的方法,对川麦冬土壤的成土母质、气候、地形地貌、水文地质等成土因素和土壤理化特性作了研究。川麦冬道地产区气候温和、降雨充沛,热量资源丰富。种植川麦冬的土壤结构好、质地适中,呈中性反应,养分含量比较丰富,其中潮沙泥土是种植川麦冬的最好土壤。     

Field-scale variability of topsoil dehydrogenase and cellulase activities as affected by variability of some physico-chemical properties

We have studied spatial field-scale variability of soil dehydrogenase (DH) and cellulase activities (CEL) and their relationship with variability of some physico-chemical properties at the surface horizon of the agricultural field. Soil samples were collected at 50 points from the upper 20 cm of soil. The activity of DH ranged between 0.77 and 1.5 μM TPP·g⁻¹·h⁻¹ while CEL activity ranged from 0.8 to 1.94 μM glucose·g⁻¹·24 h⁻¹. Concentrations of C_ORG and TN varied from 8.5 to 31.7 g·kg⁻¹ and from 0.94 to 3.56 g·kg⁻¹, respectively. The soil data showed that spatial variability and semivariograms describe spherical and linear models with the nugget effect (DH, CEL, C_ORG and TN). Dehydrogenase activity was in the strong variability class, while cellulase activity was situated in the week variability class. Both C_ORG and TN concentrations and pH_KCl values were strongly spatially dependent with the percentage of total variance (sill) presents as nugget variance ranging from 8.9% to 16.1%. Kriged maps displayed the lowest values of CEL activities in the north-east of the area, while the south area showed the highest CEL activity. The DH activity values were irregularly distributed in the surface horizon of the studied soil and this behaviour did not correspond with the spatial distribution of other properties.     

Identification of key soil and terrain properties that influence the spatial variability of soil moisture throughout the growing season

Combining soils and terrain information is the key to understanding hydrological processes at a landscape scale. Increasing the scale of soil maps has been shown to allow the spatial patterns of soil moisture to be more fully represented in the landscape, but soil data are often only available at reconnaissance scales (e.g. 1:250 000). It is widely acknowledged that soil hydrological properties vary within the landscape and there are widely available digital terrain models at a 10-m grid resolution in the UK. The aim of this study was to investigate soil moisture variations and how soil and terrain data can be used in combination to explain the spatial variation in soil moisture contents. Field monitoring of surface soil moisture content on eight occasions in three different fields in Bedfordshire (UK) was undertaken between April and July in 2004 and 2005. Between 100 and 120 points were sampled in each survey using a Delta-T ML2x™ Theta Probe. The results from regression models show that up to 80% of the variation in surface soil moisture can be explained using 1:10 000 soil series maps and terrain variables. Short-wave radiation on a sloping surface (SWRSS), calculated by SRAD, and a topographic wetness index combined explained a maximum of 44% of the variation. The results show that the terrain effect on soil moisture is modified by soils. The additional variation explained by adding 1:10 000 soil series information to terrain variables was up to 50% and adding 1:25 000 soil series information increased the variation explained by up to 29%. The interactions in the variation explained by soils and landscape indices at different scales tie in with the concept of hydropedology. It also has implications for data requirements for modelling soil hydrological response and associated soil functions.