Soil factors associated with zinc deficiency in crops and humans

Zinc deficiency is the most ubiquitous micronutrient deficiency problem in world crops. Zinc is essential for both plants and animals because it is a structural constituent and regulatory co-factor in enzymes and proteins involved in many biochemical pathways. Millions of hectares of cropland are affected by Zn deficiency and approximately one-third of the human population suffers from an inadequate intake of Zn. The main soil factors affecting the availability of Zn to plants are low total Zn contents, high pH, high calcite and organic matter contents and high concentrations of Na, Ca, Mg, bicarbonate and phosphate in the soil solution or in labile forms. Maize is the most susceptible cereal crop, but wheat grown on calcareous soils and lowland rice on flooded soils are also highly prone to Zn deficiency. Zinc fertilizers are used in the prevention of Zn deficiency and in the biofortification of cereal grains.

Assessment of soil particle redistribution on two contrasting cultivated hillslopes

The particle size distributions of surface soils from two cultivated silty fields (Moorfield and Railway South) in Herefordshire, UK, were assessed by sampling on 20-m grids across the fields. Moorfield (8 ha) had a uniform landscape sloping mainly in a North-South direction while Railway South (12 ha) had complex undulating landscape characteristics. Samples from 3 surficial layers were also taken at 3 landscape positions at Moorfield to investigate recent (within-season) soil particle redistribution. Size fractions were determined using chemical dispersion, wet sieving (to separate the sand fractions) and laser gramilometry (for the finer fractions). The distribution of various fractions and the relationships between elevation and the various fractions suggest preferential detachment and movement of coarse to very coarse silt fractions (16-63 mu m), which were found mostly at downslope or depositional areas. Upper slope samples had higher clay to fine silt (< 16 mu m) contents than bottom slope samples. The upslope-downslope patterns of size fractions, particularly on uniformly sloping areas, of the 2 fields were similar and their deposited sediments were dominated by coarse silt fractions. Samples from 3 landscape positions at Moorfield became coarser from the less eroded summit, through the eroding side-slope to the bottom-slope depositional area. Within each of these landscape positions the top 0-2.5 cm layers were more enriched in coarse silt fractions than the bottom layers. The spatial patterns of soil particle size distributions in the 2 fields may be a result of sediment detachment and deposition caused by water erosion and tillage operations. (c) 2005 Elsevier B.V. All rights reserved.

Evidence of heavy metal movement down the profile of a heavily-sludged soil

Two sites in central England where sewage sludge has been deposited for decades were studied to measure the heavy metal distribution in the soil profiles. The first site (S 1) was a field receiving heavy loads sludge from a nearby wastewater treatment plant, and the second (S2) was a farm applying 'normal' sludge rates of 8 t ha(-1) y(-1) of the same sludge. Soil samples were also taken by a near-by untreated control site. In S I the movement of heavy metals was significant even down to 80 cm depth compared to the control. In S2, the concentrations of lead (Pb) and zinc (Zn) and the organic matter content were higher than the control down to 20 cm, while nickel (Ni) moved significantly down to 80 cm. This underlies. the possibility that the metals bound onto organic surfaces moved along with organic matter down to that depth. The movement of metals in S2 points out the potential risks of applying sewage sludge for a long time.

The influence of mineral solubility and soil solution concentration on the toxicity of copper to Eisenia fetida Savigny

The OECD 14 d earthworm acute toxicity test was used to determine the toxicity of copper added as copper nitrate (Cu(NO3)(2)), copper sulphate (CuSO4) and malachite (Cu-2(OH)(2)(CO3)) to Eisenia fetida Savigny. Cu(NO3)(2), and CuSO4 were applied in both an aqueous (aq) and solid (s) form, Cu-2(OH)(2)(CO3) was added as a solid. Soil solution was extracted by centrifugation, and analysed for copper. Two extractants [0.01 M CaCl2 and 0.005 M diethylenetriminpentaacetic acid (DTPA)] were used as a proxy of the bioavailable copper fraction in the soil. For bulk soil copper content the calculated copper toxicity decreased in the order nitrate > sulphide > carbonate, the same order as decreasing solubility of the metal compounds. For Cu(NO3)(2) and CuSO4, the LC50s obtained were not significantly different when the compound was added in solution or solid form. There was a significant correlation between the soil solution copper concentration and the percentage earthworm mortality for all 3 copper compounds (P less than or equal to 0.05) indicating that the soil pore water copper concentration is important for determining copper availability and toxicity to E. fetida. In soil avoidance tests the earthworms avoided the soils treated with Cu(NO3)(2) (aq and s) and CuSO4 (aq and s), at all concentrations used (110-8750 mug Cu g(-1), and 600-8750 mug Cu g(-1) respectively). In soils treated with Cu-2(OH2)CO3, avoidance behaviour was exhibited at all concentrations greater than or equal to3500 mug Cu g(-1). There was no significant correlation between the copper extracted by either CaCl2 or DTPA and percentage mortality. These two extractants are therefore not useful indicators of copper availability and toxicity to E. fetida.

Soil mobility of sewage sludge-derived dissolved organic matter, copper, nickel and zinc

A soil (sandy loam) column leaching study aimed to determine the extent of mobility and co-mobility of Cu, Ni, Zn and dissolved organic matter (DOM) released from a surface-application (equivalent to 50 t ds ha(-1)) of anaerobically-digested sewage sludge. Leaching of DOM through It the soil column was found to be almost un-retarded. Decidedly similar behaviour was exhibited by Ni suggesting that it migrated as organic complexes. Whilst Cu was also found to be leached, significant retardation was evident. However, the importance of DOM in promoting the mobility of both Cu and Ni was evidenced by their lack of mobility when added to the soil column as inorganic forms. The presence of DOM did not prevent Zn from becoming completely adsorbed by the soil solid phase. In relation to WHO drinking water guidelines, only Ni concentrations showed potential environmental significance. due to the relatively poor retention of Ni by the sludge solid phase. (C) 2003 Elsevier Ltd. All rights reserved.

Complexation of copper by sewage sludge-derived dissolved organic matter: Effects on soil sorption behaviour and plant uptake

The complexation of Cu by sewage sludge-derived dissolved organic matter (SSDOM) is a process by which the environmental significance of the element may become enhanced due to reduced soil sorption and, hence, increased mobility. The work described in this paper used an ion selective electrode procedure to show that SSDOM complexation of Cu was greatest at intermediate pH values because competition between hydrogen ions and Cu for SSDOM binding sites, and between hydroxyl ions and SSDOM as Cu ligands, was lowest at such values. Batch sorption experiments further showed that the process of Cu complexation by SSDOM provided an explanation for enhanced desorption of Cu from the solid phase of a contaminated, organic matter-rich, clay loam soil, and reduced adsorption of Cu onto the solid phase of a sandy loam soil. Complexation of Cu by SSDOM did not affect uptake of Cu by spring barley plants, when compared to free ionic Cu, in a sand-culture pot experiment. However, it did appear to lead to greater biomass yields of the plant; perhaps indicating that the Cu-SSDOM complex had a lower toxicity towards the plant than the free Cu ion.

Spatial covariation of Azotobacter abundance and soil properties: A case study using the wavelet transform

The soil microflora is very heterogeneous in its spatial distribution. The origins of this heterogeneity and its significance for soil function are not well understood. A problem for understanding spatial variation better is the assumption of statistical stationarity that is made in most of the statistical methods used to assess it. These assumptions are made explicit in geostatistical methods that have been increasingly used by soil biologists in recent years. Geostatistical methods are powerful, particularly for local prediction, but they require the assumption that the variability of a property of interest is spatially uniform, which is not always plausible given what is known about the complexity of the soil microflora and the soil environment. We have used the wavelet transform, a relatively new innovation in mathematical analysis, to investigate the spatial variation of abundance of Azotobacter in the soil of a typical agricultural landscape. The wavelet transform entails no assumptions of stationarity and is well suited to the analysis of variables that show intermittent or transient features at different spatial scales. In this study, we computed cross-variograms of Azotobacter abundance with the pH, water content and loss on ignition of the soil. These revealed scale-dependent covariation in all cases. The wavelet transform also showed that the correlation of Azotobacter abundance with all three soil properties depended on spatial scale, the correlation generally increased with spatial scale and was only significantly different from zero at some scales. However, the wavelet analysis also allowed us to show how the correlation changed across the landscape. For example, at one scale Azotobacter abundance was strongly correlated with pH in part of the transect, and not with soil water content, but this was reversed elsewhere on the transect. The results show how scale-dependent variation of potentially limiting environmental factors can induce a complex spatial pattern of abundance in a soil organism. The geostatistical methods that we used here make assumptions that are not consistent with the spatial changes in the covariation of these properties that our wavelet analysis has shown. This suggests that the wavelet transform is a powerful tool for future investigation of the spatial structure and function of soil biota. (c) 2006 Elsevier Ltd. All rights reserved.

Preparation of consistent soil data sets for modelling purposes: Secondary SOTER data for four case study areas

The common GIS-based approach to regional analyses of soil organic carbon (SOC) stocks and changes is to define geographic layers for which unique sets of driving variables are derived, which include land use, climate, and soils. These GIS layers, with their associated attribute data, can then be fed into a range of empirical and dynamic models. Common methodologies for collating and formatting regional data sets on land use, climate, and soils were adopted for the project Assessment of Soil Organic Carbon Stocks and Changes at National Scale (GEFSOC). This permitted the development of a uniform protocol for handling the various input for the dynamic GEFSOC Modelling System. Consistent soil data sets for Amazon-Brazil, the Indo-Gangetic Plains (IGP) of India, Jordan and Kenya, the case study areas considered in the GEFSOC project, were prepared using methodologies developed for the World Soils and Terrain Database (SOTER). The approach involved three main stages: (1) compiling new soil geographic and attribute data in SOTER format; (2) using expert estimates and common sense to fill selected gaps in the measured or primary data; (3) using a scheme of taxonomy-based pedotransfer rules and expert-rules to derive soil parameter estimates for similar soil units with missing soil analytical data. The most appropriate approach varied from country to country, depending largely on the overall accessibility and quality of the primary soil data available in the case study areas. The secondary SOTER data sets discussed here are appropriate for a wide range of environmental applications at national scale. These include agro-ecological zoning, land evaluation, modelling of soil C stocks and changes, and studies of soil vulnerability to pollution. Estimates of national-scale stocks of SOC, calculated using SOTER methods, are presented as a first example of database application. Independent estimates of SOC stocks are needed to evaluate the outcome of the GEFSOC Modelling System for current conditions of land use and climate. (C) 2007 Elsevier B.V. All rights reserved.

Incorporating Legacy Soil pH Databases into Digital Soil Maps

Soil data and reliable soil maps are imperative for environmental management. conservation and policy. Data from historical point surveys, e.g. experiment site data and farmers fields can serve this purpose. However, legacy soil information is not necessarily collected for spatial analysis and mapping such that the data may not have immediately useful geo-references. Methods are required to utilise these historical soil databases so that we can produce quantitative maps of soil propel-ties to assess spatial and temporal trends but also to assess where future sampling is required. This paper discusses two such databases: the Representative Soil Sampling Scheme which has monitored the agricultural soil in England and Wales from 1969 to 2003 (between 400 and 900 bulked soil samples were taken annually from different agricultural fields); and the former State Chemistry Laboratory, Victoria, Australia where between 1973 and 1994 approximately 80,000 soil samples were submitted for analysis by farmers. Previous statistical analyses have been performed using administrative regions (with sharp boundaries) for both databases, which are largely unrelated to natural features. For a more detailed spatial analysis that call be linked to climate and terrain attributes, gradual variation of these soil properties should be described. Geostatistical techniques such as ordinary kriging are suited to this. This paper describes the format of the databases and initial approaches as to how they can be used for digital soil mapping. For this paper we have selected soil pH to illustrate the analyses for both databases.

The spatial prediction of soil mineral N and potentially available N using elevation

The precision farmer wants to manage the variation in soil nutrient status continuously, which requires reliable predictions at places between sampling sites. Ordinary kriging can be used for prediction if the data are spatially dependent and there is a suitable variogram model. However, even if data are spatially correlated, there are often few soil sampling sites in relation to the area to be managed. If intensive ancillary data are available and these are coregionalized with the sparse soil data, they could be used to increase the accuracy of predictions of the soil properties by methods such as cokriging, kriging with external drift and regression kriging. This paper compares the accuracy of predictions of the plant available N properties (mineral N and potentially available N) for two arable fields in Bedfordshire, United Kingdom, from ordinary kriging, cokriging, kriging with external drift and regression kriging. For the last three, intensive elevation data were used with the soil data. The mean squared errors of prediction from these methods of kriging were determined at validation sites where the values were known. Kriging with external drift resulted in the smallest mean squared error for two of the three properties examined, and cokriging for the other. The results suggest that the use of intensive ancillary data can increase the accuracy of predictions of soil properties in arable fields provided that the variables are related spatially. (c) 2005 Elsevier B.V. All rights reserved.

The Representative Soil Sampling Scheme of England and Wales: the spatial variation of topsoil nutrient status and pH between 1971 and 2001

The Representative Soil Sampling Scheme (RSSS) has monitored the soil of agricultural land in England and Wales since 1969. Here we describe the first spatial analysis of the data from these surveys using geostatistics. Four years of data (1971, 1981, 1991 and 2001) were chosen to examine the nutrient (available K, Mg and P) and pH status of the soil. At each farm, four fields were sampled; however, for the earlier years, coordinates were available for the farm only and not for each field. The averaged data for each farm were used for spatial analysis and the variograms showed spatial structure even with the smaller sample size. These variograms provide a reasonable summary of the larger scale of variation identified from the data of the more intensively sampled National Soil Inventory. Maps of kriged predictions of K generally show larger values in the central and southeastern areas (above 200 mg L-1) and an increase in values in the west over time, whereas Mg is fairly stable over time. The kriged predictions of P show a decline over time, particularly in the east, and those of pH show an increase in the east over time. Disjunctive kriging was used to examine temporal changes in available P using probabilities less than given thresholds of this element. The RSSS was not designed for spatial analysis, but the results show that the data from these surveys are suitable for this purpose. The results of the spatial analysis, together with those of the statistical analyses, provide a comprehensive view of the RSSS database as a basis for monitoring the soil. These data should be taken into account when future national soil monitoring schemes are designed.

A geostatistical analysis of the spatial variation of soil mineral nitrogen and potentially available nitrogen within an arable field.

The technology for site-specific applications of nitrogen (N) fertilizer has exposed a gap in our knowledge about the spatial variation of soil mineral N, and that which will become available during the growing season within arable fields. Spring mineral N and potentially available N were measured in an arable field together with gravimetric water content, loss on ignition, crop yield, percentages of sand, silt, and clay, and elevation to describe their spatial variation geostatistically. The areas with a larger clay content had larger values of mineral N, potentially available N, loss on ignition and gravimetric water content, and the converse was true for the areas with more sandy soil. The results suggest that the spatial relations between mineral N and loss on ignition, gravimetric water content, soil texture, elevation and crop yield, and between potentially available N and loss on ignition and silt content could be used to indicate their spatial patterns. Variable-rate nitrogen fertilizer application would be feasible in this field because of the spatial structure and the magnitude of variation of mineral N and potentially available N.

Simulating the spatial variation of soil mineral N within fields using the model SUNDIAL

Variable rate applications of nitrogen (N) are of environmental and economic interest. Regular measurements of soil N supply are difficult to achieve practically. Therefore accurate model simulations of soil N supply might provide a practical solution for site-specific management of N. Mineral N, an estimate of N supply, was simulated by the model SUNDIAL (Simulation of Nitrogen Dynamics In Arable Land) at more than 100 locations within three arable fields in Bedfordshire, UK. The results were compared with actual measurements. The outcomes showed that the spatial patterns of the simulations of mineral N corresponded to the measurements but the range of values was underestimated.

Microbial and biochemical soil quality indicators and their potential for differentiating areas under contrasting agricultural management regimes

The aim of this study was to examine interrelationships between functional biochemical and microbial indicators of soil quality, and their suitability to differentiate areas under contrasting agricultural management regimes. The study included five 0.8 ha areas on a sandy-loam soil which had received contrasting fertility and cropping regimes over a 5 year period. These were organically managed vegetable, vegetable -cereal and arable rotations, an organically managed grass clover ley, and a conventional cereal rotation. The organic areas had been converted from conventional cereal production 5 years prior to the start of the study. All of the biochemical analyses, including light fraction organic matter (LFOM) C and N, labile organic N (LON), dissolved organic N and water-soluble carbohydrates showed significant differences between the areas, although the nature of the relationships between the areas varied between the different parameters, and were not related to differences in total soil organic matter content. The clearest differences were seen in LFOM C and N and LON, which were higher in the organic arable area relative to the other areas. In the case of the biological parameters, there were differences between the areas for biomass-N, ATP, chitin content, and the ratios of ATP: biomass and basal respiration: biomass. For these parameters, the precise relationships between the areas varied. However, relative to the conventionally managed area, areas under organic management generally had lower biomass-N and higher ATP contents. Arbuscular mycorrhizal fungus colonization potential was extremely low in the conventional area relative to the organic areas. Further, metabolic diversity and microbial community level physiological profiles, determined by analysis of microbial community metabolism using Biolog GN plates and the activities of eight key nutrient cycling enzymes, grouped the organic areas together, but separated them from the conventional area. We conclude that microbial parameters are more effective and consistent indicators of management induced changes to soil quality than biochemical parameters, and that a variety of biochemical and microbial analyses should be used when considering the impact of management on soil quality. (C) 2004 Elsevier Ltd. All rights reserved.