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.     

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.     

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.     

Temporal and spatial variability of enantiomeric fractions (EFs) of chiral organochlorines in relation to soil properties

Purpose

The scope of this article was to investigate the spatial and temporal variability of enantiomeric fractions (EFs) of persistent organic pollutants (POPs) in soil compared to the uncertainty of the analytical data.

Materials and methods

Soil samples were taken with high spatial resolution at two sites in Czech Republic in 2008 to investigate variability on a small spatial scale. In addition, composite soil samples were taken from ten sites in 2005 and 2008 to investigate temporal variations. All samples were analysed for a suite of soil properties as well as concentrations and EFs of polychlorinated biphenyl (PCB) -95, PCB-132 and PCB-149; α-hexachlorocyclohexane (HCH); o,p′-dichlorodiphenyltrichloroethane (DDT); and o,p′-dichlorodiphenyldichloroethane (DDD).

Results and discussion

Median EFs of PCB-95 and PCB-149, α-HCH, o,p′-DDT and o,p′-DDD did not change significantly on the sites sampled in 2005 and again in 2008, while PCB-132 changed from EF?=?0.38 to EF?=?0.53. The sampling methodology is therefore very important, and composite samples will not be the best option if enantioselective degradation processes are investigated. Non-racemic EFs of POPs in the subsampled sites in 2008 were correlated to soil parameters, such as total organic carbon (TOC), total nitrogen and humic acids. These parameters are site specific and might vary on a small scale. This can explain why certain soil parameters are reported as significantly correlated with non-racemic EFs of chiral POPs in some studies, but not always in other similar studies.

Conclusions

While composite samples may still represent the overall prevailing EF range, they are not ideally suited to study enantiomeric degradation processes, which are taking place at a relative small scale, depending on the heterogeneity of soil parameters such as TOC, total organic nitrogen (TON) and humic acids.

     

Multiscale sources of spatial variation in soil. II. A non-Brownian fractal model and its application in soil survey

Stochastic fractals (for example, the fractional Brownian noises) model the often observed power law relation between the variance of a soil property and the length of transect sampled, but fail to account for abrupt changes of the mean (i.e. soil boundaries), for second-order stationarity and for the non self-similarity of variations at different scales that are observed in real data. This paper proposes a non-Brownian, nested model to account for situations where differences of soil have been caused by superimposed, independently acting soil-forming processes having different weights and acting at separate, discrete scales. The model is explained and theoretical examples of the semivariograms and confidence limits that arise from it are given. The model is applied to three sets of experimental data and is found to give a remarkably good fit where lateral mixing of soil has been negligible and soil boundaries are sharp. The implications for efficient mapping in situations where the soil results from a number of superimposed, independent causes are discussed.     

Nitrogen mineralization and CO2 and N2O emissions in a sandy soil amended with original or acidified pig slurries or with the relative fractions

The following six pig slurries obtained after acidification and/or solid/liquid separation were used in the research: original (S) and acidified (AS) pig slurry, nonacidified (LF) and acidified (ALF) pig slurry liquid fraction, and nonacidified (SF) and acidified (ASF) pig slurry solid fraction. Laboratory incubations were performed to assess the effect of the application of these slurries on N mineralization and CO₂ and N₂O emissions from a sandy soil. Acidification maintained higher NH₄ ⁺-N contents in soil particularly in the ALF-treated soil where NH₄ ⁺-N contents were two times higher than in LF-treated soil during the 55–171-day interval. At the end of the incubation (171 days), 32.9 and 24.2 mg N kg⁻¹ dry soil were mineralized in the ASF- and SF-treated soils, respectively, but no mineralization occurred in LF- and S-treated soils, although acidification decreased N immobilization in ALF- (−25.3 mg N kg⁻¹ soil) and AS- (−12.7 mg N kg⁻¹ soil) compared to LF- (−34.4 mg N kg⁻¹ soil) and S-treated (−18.6 mg N kg⁻¹ soil) soils, respectively. Most of the dissolved CO₂ was lost during the acidification process. More than 90% of the applied C in the LF-treated soil was lost during the incubation, indicating a high availability of the added organic compounds. Nitrous oxide emissions occurred only after day 12 and at a lower rate in soils treated with acidified than nonacidified slurries. However, during the first 61 days of incubation, 1,157 μg N kg⁻¹ soil was lost as N₂O in the AS-treated soil and only 937 in the S-treated soil.     

Soil sampling based on field spatial variability of soil microbial indicators

Microbial indicators exhibit a high spatial heterogeneity which often masks comparison of the effects of different soil management treatments. It is therefore desirable to use a proper sampling design which integrates spatial heterogeneity at field level. Thus, the objectives were: (1) to study the spatial heterogeneity of biological and chemical soil variables, and (2) with obtained maps of spatial variability to test different sampling strategies to assess the usefulness of this ‘new’ soil map unit. 63 soil samples were collected according to a 10 m × 10 m grid on a 0.48 ha plot. On each of these samples, 10 variables were measured: soil water content, cation exchange capacity (CEC), organic carbon (OC) and total nitrogen (N), C/N, soil microbial biomass (SMB), labile soil organic matter (LOM), mineralisable C (C_min) and N (N_min), inverse of specific respiratory activity (1/SRA = SBM/C_min). The spatial heterogeneity of each variable was charted with geostatistics. The biological variables exhibited spatial variability of the same order of magnitude as physicochemical parameters. From the maps, zones with different levels of organic matter, microbial biomass and specific respiratory activity were identified. The spatial patterns of SMB and SRA were related to CEC (positively for SMB and negatively for SRA), pointing out the effects of soil protection on microbial biomass and availability of organic substrates. The definition of these zones for a pool of variables (OC, N, SMB, LOM, CEC) is useful at 3 levels: (1) to record the initial values of the measured variables for each plot, (2) to integrate these zones as blocks in experimental design for future experiments, and (3) to focus analysis of specific biological mechanisms such as activity of micro-organisms.     

CO2 and N2O emissions in response to dolomite application are moisture dependent in an acidic paddy soil

Journal of Soils and Sediments - Liming is the most widely used agricultural practice for acidic paddy soils amelioration, which is usually applied before rice transplanting. Both liming and soil...     

The soil solution chemistry of some Oxfordshire soils: temporal and spatial variability

The immiscible liquid displacement method was used to displace soil solutions from a variety of Oxfordshire soils. These included grassland, arable, and woodland soils. The results of detailed chemical analyses demonstrated that for most solutes there were significant seasonal differences as well as differences both within and between soil series. The variation over time intervals of a few days or weeks appeared to be relatively small in relation to sampling errors. Median concentrations (in mmol m⁻³) for soil solutions derived from 21 grassland sites and six arable sites sampled six or seven times throughout 1 year were: _pH 7.7, alkalinity 1810, Na 465, K 390, Mg 135, Ca 2120, Sr 1.9, Ba 0.16, Mn 0.52, Fe 3.4, Cu 0.25, TON 860, Cl 1590, S 327, P 64, Si 220, B 5.1, and DOC 4250. For many solutes, the individual soil solution concentrations spanned a range from approximately five-times less than these median values to approximately five-times more.     

Soil CO2 emission and its relationship to soil properties under different tillage systems

There is a lack of understanding as to which soil property is the most important at regulating the temporal variability of soil CO₂ emissions on China’s Loess Plateau. The objective of this study was to evaluate the CO₂ emissions and their relationships to certain soil properties in a winter wheat (Triticum aestivum L.) field subject to no-till (NT) and conventional tillage (CT) practices. The CO₂ emissions were signi?cantly higher in the CT (257.6 mg CO₂ m^?2 h^?1), compared with the NT (143.8 mg CO₂ m^?2 h^?1), treatment. Soil organic matter content and carbon stock were 8% and 14% higher, respectively, in the NT, compared with the CT, treatment. Regression analyses between the CO₂ emissions and soil properties, including soil temperature and carbon stock, explained up to 88% and 60% of the temporal variability in CO₂ emissions in the NT and CT treatments, respectively. Linear correlations between the soil temperature and CO₂ emissions were recorded in both the NT and CT treatments. Soil temperature was the most important factor in terms of understanding the temporal variability in CO₂ emissions in wheat fields of the study area.     

菜田土壤养分空间变异特征

采用传统统计和地统计相结合的方法，对55hm^2菜田耕层土壤养分空间变异特征进行了研究。结果表明，土壤养分主要限制因子是N、P、K和Zn。不同土壤养分的变异情况各不相同。土壤养分速效含量一般呈斑块状分布；土壤NO3^- -N、P、K和Zn含量在空间分布上具有明显的空间相似性。土壤NO3^- -N、P、K含量分别与种菜历史及肥料用量（N、P2O5和K2O）之间均呈极显著的正相关。     

The methods of geomorphometry and digital soil mapping for assessing spatial variability in the properties of agrogray soils on a slope

The relationships between the morphometric parameters (MPs) of topography calculated on the basis of digital elevation model (АSTER GDEM, 30 m) and the properties of the plow layer of agrogray soils on a slope were analyzed. The contribution of MPs to the spatial variability of the soil moisture reached 42%; to the content of physical clay (<0.01 mm particles), 59%; to the humus content, 46%; to the total nitrogen content, 31%; to the content of nitrate nitrogen, 28%; to the content of mobile phosphorus, 40%; to the content of exchangeable potassium, 45%; to the content of exchangeable calcium, 67%; to the content of exchangeable magnesium, 40%; and to the soil pH, 42%. A comparative analysis of the plow layer within the eluvial and transitional parts of the slope was performed with the use of geomorphometric methods and digital soil mapping. The regression analysis showed statistically significant correlations between the properties of the plow layer and the MPs describing surface runoff, geometric forms of surface, and the soil temperature regime.     

Multiscale sources of spatial variation in soil. I. The application of fractal concepts to nested levels of soil variation

Soil variation has often been considered to be composed of‘functional’ or ‘systematic’ variation that can be explained, and random variation (‘noise’) that is unresolved. The distinction between systematic variation and noise is entirely scale dependent because increasing the scale of observation almost always reveals structure in the noise. The white noise concept of a normally distributed random function must be replaced to take into account the nested, autocorrelated and scale-dependent nature of unresolved variations. Fractals are a means of studying these phenomena. The Hausdorff-Besicovitch dimension D is introduced as a measure of the relative balance between long- and short-range sources of variation; D can be estimated from the slope of a double logarithmic plot of the semivariogram. The family of Brownian linear fractals is introduced as the model of ideal stochastic fractals. Data from published and unpublished soil studies are examined and compared with other environmental data and simulated fractional Brownian series. The soil data are fractals because increasing the scale of observation continues to reveal more and more detail. But soil does not vary exactly as a Brownian fractal because its variation is controlled by many independent processes that can cause abrupt transitions or local second order stationarity. Estimates of D values show that soil data usually have a much higher proportion of short-range variation than landform or ground water surfaces. The practical implication is that interpolation of soil property values based on observations from single 10 cm auger observations will be unsatisfactory and that some method of bulking or block kriging should be used whenever longrange variations need to be mapped.     

Influence of industrial wastes on physico-chemical properties of soil and germination and mineral composition of wheat

The effect of chemical effluents discharged from a chemical and fertilizer factory on physicochemical properties of soil and germination and mineral composition of wheat was studied at Varanasi, India. Forty times higher concentration of Na was observed in the effluent than that of the nearby well water. It showed a positive (significant) correlation with Na and a negative (significant) with K and Ca of the soil. Cation exchange capacity (CEC), porosity and water holding capacity were reduced by effluent affected soil. the germination percentage of wheat was negatively correlated with the Na of effluent and Na+Mg/Ca of the soil. A significant (positive) correlation existed between Na of effluent and Na content of the plants. Calcium percentage on the other hand, exhibited a reverse trend.     

Assessing the role of the relief in the spatial variability of agriculturally important soil properties for intensively cultivated agricultural land

An intensively cultivated field of 0.4 ha (sod-podzolic soils) shows considerable variability of agriculturally important soil properties, the rank and direction of the highest variation of which occurred to be close. Therefore, the factor that determines the variation is anthropogenic. The influence of the morphometric characteristics of the relief on the variability of soil properties was described by the multiple linear regression equation. The strongest impact of the relief falls on the thickness of the surface horizon (up to 40%); for pH and the mobile phosphorus content this figure is only 10–15% and decreases with depth, while for mobile potassium it increases with depth.     

Influence of water table level and soil properties on emissions of greenhouse gases from cultivated peat soil

A lysimeter method using undisturbed soil columns was used to investigate the effect of water table depth and soil properties on soil organic matter decomposition and greenhouse gas (GHG) emissions from cultivated peat soils. The study was carried out using cultivated organic soils from two locations in Sweden: Örke, a typical cultivated fen peat with low pH and high organic matter content and Majnegården, a more uncommon fen peat type with high pH and low organic matter content. Even though carbon and nitrogen contents differ greatly between the sites, carbon and nitrogen density are quite similar. A drilling method with minimal soil disturbance was used to collect 12 undisturbed soil monoliths (50 cm high, Ø29.5 cm) per site. They were sown with ryegrass (Lolium perenne) after the original vegetation was removed. The lysimeter design allowed the introduction of water at depth so as to maintain a constant water table at either 40 cm or 80 cm below the soil surface. CO₂, CH₄ and N₂O emissions from the lysimeters were measured weekly and complemented with incubation experiments with small undisturbed soil cores subjected to different tensions (5, 40, 80 and 600 cm water column). CO₂ emissions were greater from the treatment with the high water table level (40 cm) compared with the low level (80 cm). N₂O emissions peaked in springtime and CH₄ emissions were very low or negative. Estimated GHG emissions during one year were between 2.70 and 3.55 kg CO₂ equivalents m⁻². The results from the incubation experiment were in agreement with emissions results from the lysimeter experiments. We attribute the observed differences in GHG emissions between the soils to the contrasting dry matter liability and soil physical properties. The properties of the different soil layers will determine the effect of water table regulation. Lowering the water table without exposing new layers with easily decomposable material would have a limited effect on emission rates.     

Climatic effect on soil organic carbon variability as a function of spatial scale

Soil organic carbon (SOC) is spatially heterogeneous. Understanding SOC variability as a function of varying scale is important for accurately estimating the SOC stock. We selected three zones in the Huang-Huai-Hai agricultural region of China to define temperature (T Zone), precipitation (P Zone) and temperature + precipitation (PT Zone) gradients, respectively. The zonal differences in SOC variability as a function of increasing scale were examined. The results demonstrated that the SOC stock varied substantially among the different zones. The coefficient of variation (CV) of the SOC stock was more elevated in the PT Zone and was influenced by scale level. The mean CV increased by 12.5%, 4.6% and 2.9% from 1C to 12C for PT, T and P Zone, respectively. Zonal SOC variability differences were not obvious at small scale, with the CV ratio consistently less than 0.003 in the three zones; however, they became detectable at higher scales (6C and 12C), with the CV ratio showing as: PT Zone > T Zone > P Zone. SOC zonal variability must be considered to reduce uncertainty for soil carbon stock estimation.     

Integrating soil map information in modelling the spatial variation of continuous soil properties

This paper presents two indicator algorithms that integrate soil map information into modelling the spatial variation of continuous soil properties: these are simple indicator kriging with varying means and the Markov–Bayes algorithm. Both methods are used to evaluate probabilities for copper and cobalt deficiencies in the Borders Region of Scotland. Results are compared with maps obtained by the polygonal method (Thiessen polygons) and an indicator kriging algorithm that does not use soil map information. Accounting for soil map information is shown to improve delineation of the deficient areas, especially where the sampling is sparse. Test locations are classified as deficient or not so as to minimize an expected cost of mis-classification that is derived from local probability distributions of copper or cobalt and functions measuring the cost of overestimating or underestimating metal concentrations. The comparison of classification results with actual copper and cobalt concentrations at test locations shows that the two proposed algorithms can decrease substantially the economic loss attached to misclassification.