Direct soil moisture controls of future global soil carbon changes: An important source of uncertainty

The nature of the climate–carbon cycle feedback depends critically on the response of soil carbon to climate, including changes in moisture. However, soil moisture–carbon feedback responses have not been investigated thoroughly. Uncertainty in the response of soil carbon to soil moisture changes could arise from uncertainty in the relationship between soil moisture and heterotrophic respiration. We used twelve soil moisture–respiration functions (SMRFs) with a soil carbon model (RothC) and data from a coupled climate–carbon cycle general circulation model to investigate the impact of direct heterotrophic respiration dependence on soil moisture on the climate carbon cycle feedback. Global changes in soil moisture acted to oppose temperature‐driven decreases in soil carbon and hence tended to increase soil carbon storage. We found considerable uncertainty in soil carbon changes due to the response of soil respiration to soil moisture. The use of different SMRFs resulted in both large losses and small gains in future global soil carbon stocks, whether considering all climate forcings or only moisture changes. Regionally, the greatest range in soil carbon changes across SMRFs was found where the largest soil carbon changes occurred. Further research is needed to constrain the soil moisture–respiration relationship and thus reduce uncertainty in climate–carbon cycle feedbacks. There may also be considerable uncertainty in the regional responses of soil carbon to soil moisture changes since climate model predictions of regional soil moisture changes are less coherent than temperature changes.

The relationship between diffuse spectral reflectance of the soil and its cation exchange capacity is scale-dependent

Diffuse reflectance spectroscopy (DRS) is increasingly being used to predict numerous soil physical, chemical and biochemical properties. However, soil properties and processes vary at different scales and, as a result, relationships between soil properties often depend on scale. In this paper we report on how the relationship between one such property, cation exchange capacity (CEC), and the DRS of the soil depends on spatial scale. We show this by means of a nested analysis of covariance of soils sampled on a balanced nested design in a 16 km × 16 km area in eastern England. We used principal components analysis on the DRS to obtain a reduced number of variables while retaining key variation. The first principal component accounted for 99.8% of the total variance, the second for 0.14%. Nested analysis of the variation in the CEC and the two principal components showed that the substantial variance components are at the > 2000-m scale. This is probably the result of differences in soil composition due to parent material. We then developed a model to predict CEC from the DRS and used partial least squares (PLS) regression do to so. Leave-one-out cross-validation results suggested a reasonable predictive capability (R2 = 0.71 and RMSE = 0.048 molc kg− 1). However, the results from the independent validation were not as good, with R2 = 0.27, RMSE = 0.056 molc kg− 1 and an overall correlation of 0.52. This would indicate that DRS may not be useful for predictions of CEC. When we applied the analysis of covariance between predicted and observed we found significant scale-dependent correlations at scales of 50 and 500 m (0.82 and 0.73 respectively). DRS measurements can therefore be useful to predict CEC if predictions are required, for example, at the field scale (50 m). This study illustrates that the relationship between DRS and soil properties is scale-dependent and that this scale dependency has important consequences for prediction of soil properties from DRS data

Biodegradation of the herbicide mecoprop-p with soil depth and its relationship with class III tfdA genes

Mecoprop-p [(R)-2-(4-chloro-2-methylphenoxy) propanoic acid) is widely used in agriculture and poses an environmental concern because of its susceptibility to leach from soil to water. We investigated the effect of soil depth on mecoprop-p biodegradation and its relationship with the number and diversity of tfdA related genes, which are the most widely known genes involved in degradation of the phenoxyalkanoic acid group of herbicides by bacteria. Mecoprop-p half-life (DT50) was approximately 12 days in soil sampled from <30 cm depth, and increased progressively with soil depth, reaching over 84 days at 70–80 cm. In sub-soil there was a lag period of between 23 and 34 days prior to a phase of rapid degradation. No lag phase occurred in top-soil samples prior to the onset of degradation. The maximum degradation rate was the same in top-soil and sub-soil samples. Although diverse tfdAα and tfdA genes were present prior to mecoprop-p degradation, real time PCR revealed that degradation was associated with proliferation of tfdA genes. The number of tfdA genes and the most probable number of mecoprop-p degrading organisms in soil prior to mecoprop-p addition were below the limit of quantification and detection respectively. Melting curves from the real time PCR analysis showed that prior to mecoprop-p degradation both class I and class III tfdA genes were present in top- and sub-soil samples. However at all soil depths only tfdA class III genes proliferated during degradation. Denaturing gradient gel electrophoresis confirmed that class III tfdA genes were associated with mecoprop-p degradation. Degradation was not associated with the induction of novel tfdA genes in top- or sub-soil samples, and there were no apparent differences in tfdA gene diversity with soil depth prior to or following degradation.

Exploring the enzymatic landscape: distribution and kinetics of hydrolytic enzymes in soil particle-size fractions

The location of extracellular enzymes within the soil architecture and their association with the various soil components affects their catalytic potential. A soil fractionation study was carried out to investigate: (a) the distribution of a range of hydrolytic enzymes involved in C, N and P transformations, (b) the effect of the location on their respective kinetics, (c) the effect of long-term N fertilizer management on enzyme distribution and kinetic parameters. Soil (silty clay loam) from grassland which had received 0 or 200 kg N ha(-1) yr(-1) was fractionated, and four particle-size fractions (> 200, 200-63, 63-2 and 0. 1-2 mum) were obtained by a combination of wet-sieving and centrifugation, after low-energy ultrasonication. All fractions were assayed for four carbohydrases (beta-cellobiohydrolase, N-acetyl-beta-glucosammidase, beta-glucosidase and beta-xylosidase), acid phosphatase and leucine-aminopeptidase using a microplate fluorimetric assay based on MUB-substrates. Enzyme kinetics (V-max and K-m) were estimated in three particle-size fractions and the unfractionated soil. The results showed that not all particle-size fractions were equally enzymatically active and that the distribution of enzymes between fractions depended on the enzyme. Carbohydrases predominated in the coarser fractions while phosphatase and leucine-aminopeptidase were predominant in the clay-size fraction. The Michaelis constant (K.) varied among fractions, indicating that the association of the same enzyme with different particle-size fractions affected its substrate affinity. The same values of Km were found in the same fractions from the soil under two contrasting fertilizer management regimes, indicating that the Michaelis constant was unaffected by soil changes caused by N fertilizer management. (C) 2004 Elsevier Ltd. All rights reserved.

Is there a relationship between soil and groundwater toxicity?

Part IIA of the Environmental Protection Act 1990 requires environmental regulators to assess the risk of contaminants leaching from soils into groundwater (DETR, 1999). This newly introduced legislation assumes a link between soil and groundwater chemistry, in which rainwater leaches contaminants from soil into the saturated zone. As the toxicity of both groundwater and overlying soils is dependent upon the chemicals present, their partitioning and their bioavailability, similar patterns of soil, leachates and groundwater toxicity should be observed at contaminated sites. Soil and groundwater samples were collected from different contaminated land sites in an urban area, and used to determine relationships between soil chemistry and toxicity, mobility of contaminants, and groundwater chemistry and toxicity. Soils were leached using water to mimic rainfall, and both the soils and leachates tested using bioassays. Soil bioassays were carried out using Eisenia fetida, whilst groundwater and leachates were tested using the Microtox(TM) test system and Daphnia magna 48 h acute tests. Analysis of the bioassay responses demonstrated that a number of the samples were toxic to test organisms, however, there were no significant statistical relationships between soil, groundwater and leachate toxicity. Nor were there significant correlations between soil, leachates and groundwater chemistry.

Abiotic drivers and plant traits explain landscape-scale patterns in soil microbial communities

The controls on aboveground community composition and diversity have been extensively studied, but our understanding of the drivers of belowground microbial communities is relatively lacking, despite their importance for ecosystem functioning. In this study, we fitted statistical models to explain landscape-scale variation in soil microbial community composition using data from 180 sites covering a broad range of grassland types, soil and climatic conditions in England. We found that variation in soil microbial communities was explained by abiotic factors like climate, pH and soil properties. Biotic factors, namely community- weighted means (CWM) of plant functional traits, also explained variation in soil microbial communities. In particular, more bacterial-dominated microbial communities were associated with exploitative plant traits versus fungal-dominated communities with resource-conservative traits, showing that plant functional traits and soil microbial communities are closely related at the landscape scale.

Reduction of arsenic uptake by lettuce with ferrous sulfate applied to contaminated soil

Soil contamination by arsenic (As) presents a hazard in many countries and there is a need for techniques to minimize As uptake by plants. A proposed in situ remediation method was tested by growing lettuce (Lactuca sativa L. cv. Kermit) in a greenhouse pot experiment on soil that contained 577 mg As kg(-1), taken from a former As smelter site. All combinations of iron (Fe) oxides, at concentrations of 0.00, 0.22, 0.54, and 1.09% (w/w), and lime, at concentrations of 0.00, 0.27, 0.68, and 1.36% (w/w), were tested in a factorial design. To create the treatments, field-moist soil, commercial-grade FeSO4, and ground agricultural lime were mixed and stored for one week, allowing Fe oxides to precipitate. Iron oxides gave highly significant (P < 0.001) reductions in lettuce As concentrations, down to 11% of the lettuce As concentration for untreated soil. For the Fe oxides and lime treatment combinations where soil pH was maintained nearly constant, the lettuce As concentration declined in an exponential relationship with increasing FeSO4 application rate and lettuce yield was almost unchanged. Iron oxides applied at a concentration of 1.09% did not give significantly lower lettuce As concentrations than the 0.54% treatment. Simultaneous addition of lime with FeSO4 was essential. Ferrous sulfate with insufficient lime lowered soil pH and caused mobilization of Al, Ba, Co, Cr, Cu, Fe, K, Mg, Mn, Na, Ni, Pb, Sr, and Zn. At the highest Fe oxide to lime ratios, Mn toxicity caused severe yield loss.

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.

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.

Effects of sub-pixel heterogeneity on the retrieval of soil moisture from passive microwave radiometry

A simple formulation relating the L-band microwave brightness temperature detected by a passive microwave radiometer to the near surface soil moisture was developed using MICRO-SWEAT, a coupled microwave emission model and soil-vegetation-atmosphere-transfer (SVAT) scheme. This simple model provides an ideal tool with which to explore the impact of sub-pixel heterogeneity on the retrieval of soil moisture from microwave brightness temperatures. In the case of a bare soil pixel, the relationship between apparent emissivity and surface soil moisture is approximately linear, with the clay content of the soil influencing just the intercept of this relationship. It is shown that there are no errors in the retrieved soil moisture from a bare soil pixel that is heterogeneous in soil moisture and texture. However, in the case of a vegetated pixel, the slope of the relationship between apparent emissivity and surface soil moisture decreases with increasing vegetation. Therefore for a pixel that is heterogeneous in vegetation and soil moisture, errors can be introduced into the retrieved soil moisture. Generally, under moderate conditions, the retrieved soil moisture is within 3% of the actual soil moisture. Examples illustrating this discussion use data collected during the Southern Great Plains '97 Experiment (SGP97).

Response of organically managed grassland to available phosphorus and potassium in the soil and supplementary fertilization: field trials using grass-clover leys cut for silage

Effective use and recycling of manures together with occasional and judicious use of supplementary fertilizing materials forms the basis for management of phosphorus (P) and potassium (K) within organic farming systems. Replicated field trials were established at three sites across the UK to compare the supply of P and K to grass-clover swards cut for silage from a range of fertilizing materials, and to assess the usefulness of routine soil tests for P and K in organic farming systems. None of the fertilizing materials (farmyard manure, rock phosphate, Kali vinasse, volcanic tuff) significantly increased silage yields, nor was P offtake increased. However, farmyard manure and Kali vinasse proved effective sources of K to grass and clover in the short to medium term. Available P (measured as Olsen-P) showed no clear relationship with crop P offtake in these trials. In contrast, available K (measured by ammonium nitrate extraction) proved a useful measurement to predict K availability to crops and support K management decisions.