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.

The analysis of ranked observations of soil structure using indicator geostatistics

Structure is an important physical feature of the soil that is associated with water movement, the soil atmosphere, microorganism activity and nutrient uptake. A soil without any obvious organisation of its components is known as apedal and this state can have marked effects on several soil processes. Accurate maps of topsoil and subsoil structure are desirable for a wide range of models that aim to predict erosion, solute transport, or flow of water through the soil. Also such maps would be useful to precision farmers when deciding how to apply nutrients and pesticides in a site-specific way, and to target subsoiling and soil structure stabilization procedures. Typically, soil structure is inferred from bulk density or penetrometer resistance measurements and more recently from soil resistivity and conductivity surveys. To measure the former is both time-consuming and costly, whereas observations made by the latter methods can be made automatically and swiftly using a vehicle-mounted penetrometer or resistivity and conductivity sensors. The results of each of these methods, however, are affected by other soil properties, in particular moisture content at the time of sampling, texture, and the presence of stones. Traditional methods of observing soil structure identify the type of ped and its degree of development. Methods of ranking such observations from good to poor for different soil textures have been developed. Indicator variograms can be computed for each category or rank of structure and these can be summed to give the sum of indicator variograms (SIV). Observations of the topsoil and subsoil structure were made at four field sites where the soil had developed on different parent materials. The observations were ranked by four methods and indicator and the sum of indicator variograms were computed and modelled for each method of ranking. The individual indicators were then kriged with the parameters of the appropriate indicator variogram model to map the probability of encountering soil with the structure represented by that indicator. The model parameters of the SIVs for each ranking system were used with the data to krige the soil structure classes, and the results are compared with those for the individual indicators. The relations between maps of soil structure and selected wavebands from aerial photographs are examined as basis for planning surveys of soil structure. (C) 2007 Elsevier B.V. All rights reserved.

Spatial analysis of the error in a model of soil nitrogen

Models of the dynamics of nitrogen in soil (soil-N) can be used to aid the fertilizer management of a crop. The predictions of soil-N models can be validated by comparison with observed data. Validation generally involves calculating non-spatial statistics of the observations and predictions, such as their means, their mean squared-difference, and their correlation. However, when the model predictions are spatially distributed across a landscape the model requires validation with spatial statistics. There are three reasons for this: (i) the model may be more or less successful at reproducing the variance of the observations at different spatial scales; (ii) the correlation of the predictions with the observations may be different at different spatial scales; (iii) the spatial pattern of model error may be informative. In this study we used a model, parameterized with spatially variable input information about the soil, to predict the mineral-N content of soil in an arable field, and compared the results with observed data. We validated the performance of the N model spatially with a linear mixed model of the observations and model predictions, estimated by residual maximum likelihood. This novel approach allowed us to describe the joint variation of the observations and predictions as: (i) independent random variation that occurred at a fine spatial scale; (ii) correlated random variation that occurred at a coarse spatial scale; (iii) systematic variation associated with a spatial trend. The linear mixed model revealed that, in general, the performance of the N model changed depending on the spatial scale of interest. At the scales associated with random variation, the N model underestimated the variance of the observations, and the predictions were correlated poorly with the observations. At the scale of the trend, the predictions and observations shared a common surface. The spatial pattern of the error of the N model suggested that the observations were affected by the local soil condition, but this was not accounted for by the N model. In summary, the N model would be well-suited to field-scale management of soil nitrogen, but suited poorly to management at finer spatial scales. This information was not apparent with a non-spatial validation. (c),2007 Elsevier B.V. All rights reserved.

A geostatistical analysis of soil, vegetation, and image data characterizing land surface variation

The elucidation of spatial variation in the landscape can indicate potential wildlife habitats or breeding sites for vectors, such as ticks or mosquitoes, which cause a range of diseases. Information from remotely sensed data could aid the delineation of vegetation distribution on the ground in areas where local knowledge is limited. The data from digital images are often difficult to interpret because of pixel-to-pixel variation, that is, noise, and complex variation at more than one spatial scale. Landsat Thematic Mapper Plus (ETM+) and Satellite Pour l'Observation de La Terre (SPOT) image data were analyzed for an area close to Douna in Mali, West Africa. The variograms of the normalized difference vegetation index (NDVI) from both types of image data were nested. The parameters of the nested variogram function from the Landsat ETM+ data were used to design the sampling for a ground survey of soil and vegetation data. Variograms of the soil and vegetation data showed that their variation was anisotropic and their scales of variation were similar to those of NDVI from the SPOT data. The short- and long-range components of variation in the SPOT data were filtered out separately by factorial kriging. The map of the short-range component appears to represent the patterns of vegetation and associated shallow slopes and drainage channels of the tiger bush system. The map of the long-range component also appeared to relate to broader patterns in the tiger bush and to gentle undulations in the topography. The results suggest that the types of image data analyzed in this study could be used to identify areas with more moisture in semiarid regions that could support wildlife and also be potential vector breeding sites.

A sensitivity analysis of soil moisture retrieval from the t-w microwave emission model

The potential of the τ-ω model for retrieving the volumetric moisture content of bare and vegetated soil from dual polarisation passive microwave data acquired at single and multiple angles is tested. Measurement error and several additional sources of uncertainty will affect the theoretical retrieval accuracy. These include uncertainty in the soil temperature, the vegetation structure and consequently its microwave singlescattering albedo, and uncertainty in soil microwave emissivity based on its roughness. To test the effects of these uncertainties for simple homogeneous scenes, we attempt to retrieve soil moisture from a number of simulated microwave brightness temperature datasets generated using the τ-ω model. The uncertainties for each influence are estimated and applied to curves generated for typical scenarios, and an inverse model used to retrieve the soil moisture content, vegetation optical depth and soil temperature. The effect of each influence on the theoretical soil moisture retrieval limit is explored, the likelihood of each sensor configuration meeting user requirements is assessed, and the most effective means of improving moisture retrieval indicated.

Moving towards a more mechanistic approach in the determination of soil heat flux from remote measurements - II. Diurnal shape of soil heat flux

For vegetated surfaces, calculation of soil heat flux, G, with the Exact or Analytical method requires a harmonic analysis of below-canopy soil surface temperature, to obtain the shape of the diurnal course of G. When determining G with remote sensing methods, only composite (vegetation plus soil) radiometric brightness temperature is available. This paper presents a simple equation that relates the sum of the harmonic terms derived for the composite radiometric surface temperature to that of belowcanopy soil surface temperature. The thermal inertia, Gamma(,) for which a simple equation has been presented in a companion paper, paper I, is used to set the magnitude of G. To assess the success of the method proposed in this paper for the estimation of the diurnal shape of G, a comparison was made between 'remote' and in situ calculated values from described field sites. This indicated that the proposed method was suitable for the estimation of the shape of G for a variety of vegetation types and densities. The approach outlined in paper I, to obtain Gamma, was then combined with the estimated harmonic terms to predict estimates of G, which were compared to values predicted by empirical remote methods found in the literature. This indicated that the method proposed in the combination of papers I and II gave reliable estimates of G, which, in comparison to the other methods, resulted in more realistic predictions for vegetated surfaces. This set of equations can also be used for bare and sparsely vegetated soils, making it a universally applicable method. (C) 2007 Elsevier B.V. All rights reserved.

Can the study of natural vegetation succession assist in the control of soil erosion on abandoned croplands on the Loess Plateau, China?

In the Loess Plateau, China, arable cultivation of slope lands is common and associated with serious soil erosion. Planting trees or grass may control erosion, but planted species may consume more soil water and can threaten long-term ecosystem sustainability. Natural vegetation succession is an alternative ecological solution to restore degraded land, but there is a time cost, given that the establishment of natural vegetation, adequate to prevent soil erosion, is a longer process than planting. The aims of this study were to identify the environmental factors controlling the type of vegetation established on abandoned cropland and to identify candidate species that might be sown soon after abandonment to accelerate vegetation succession and establishment of natural vegetation to prevent soil erosion. A field survey of thirty-three 2 × 2–m plots was carried out in July 2003, recording age since abandonment, vegetation cover, and frequency of species together with major environmental and soil variables. Data were analyzed using correspondence analysis, classification tree analysis, and species response curves. Four vegetation types were identified and the data analysis confirmed the importance of time since abandonment, total P, and soil water in controlling the type of vegetation established. Among the dominant species in the three late-successional vegetation types, the most appropriate candidates for accelerating and directing vegetation succession were King Ranch bluestem (Bothriochloa ischaemum) and Lespedeza davurica (Leguminosae). These species possess combinations of the following characteristics: tolerance of low water and nutrient availability, fibrous root system and strong lateral vegetative spread, and a persistent seed bank.

The influence of organic acids in relation to acid deposition in controlling the acidity of soil and stream waters on a seasonal basis

Much uncertainty still exists regarding the relative importance of organic acids in relation to acid deposition in controlling the acidity of soil and surface waters. This paper contributes to this debate by presenting analysis of seasonal variations in atmospheric deposition, soil solution and stream water chemistry for two UK headwater catchments with contrasting soils. Acid neutralising capacity (ANC), dissolved organic carbon (DOC) concentrations and the Na:Cl ratio of soil and stream waters displayed strong seasonal patterns with little seasonal variation observed in soil water pH. These patterns, plus the strong relationships between ANC, Cl and DOC, suggest that cation exchange and seasonal changes in the production of DOC and seasalt deposition are driving a shift in the proportion of acidity attributable to strong acid anions, from atmospheric deposition, during winter to predominantly organic acids in summer.

Community patterns of soil bacteria and nematodes in relation to geographic distance

Ecosystems consist of aboveground and belowground subsystems and the structure of their communities is known to change with distance. However, most of this knowledge originates from visible, aboveground components, whereas relatively little is known about how soil community structure varies with distance and if this variability depends on the group of organisms considered. In the present study, we analyzed 30 grasslands from three neighboring chalk hill ridges in southern UK to determine the effect of geographic distance (1e198 km) on the similarity of bacterial communities and of nematode communities in the soil. We found that for both groups, community similarity decayed with distance and that this spatial pattern was not related to changes either in plant community composition or soil chemistry. Site history may have contributed to the observed pattern in the case of nematodes, since the distance effect depended on the presence of different nematode taxa at one of the hill ridges. On the other hand, site-related differences in bacterial community composition alone could not explain the spatial turnover, suggesting that other factors, such as biotic gradients and local dispersal processes that we did not include in our analysis, may be involved in the observed pattern. We conclude that, independently of the variety of causal factors that may be involved, the decay in similarity with geographic distance is a characteristic feature of both communities of soil bacteria and nematodes.

The development of soil organic matter in restored biodiverse Jarrah forests of South-Western Australia as determined by ASE and GCMS

Background, aim and scope Soil organic matter (SOM) is known to increase with time as landscapes recover after a major disturbance; however, little is known about the evolution of the chemistry of SOM in reconstructed ecosystems. In this study, we assessed the development of SOM chemistry in a chronosequence (space for time substitution) of restored Jarrah forest sites in Western Australia. Materials and methods Replicated samples were taken at the surface of the mineral soil as well as deeper in the profile at sites of 1, 3, 6, 9, 12, and 17 years of age. A molecular approach was developed to distinguish and quantify numerous individual compounds in SOM. This used accelerated solvent extraction in conjunction with gas chromatography mass spectrometry. A novel multivariate statistical approach was used to assess changes in accelerated solvent extraction (ASE)-gas chromatography-mass spectrometry (GCMS) spectra. This enabled us to track SOM developmental trajectories with restoration time. Results Results showed total carbon concentrations approached that of native forests soils by 17 years of restoration. Using the relate protocol in PRIMER, we demonstrated an overall linear relationship with site age at both depths, indicating that changes in SOM chemistry were occurring. Conclusions The surface soils were seen to approach native molecular compositions while the deeper soil retained a more stable chemical signature, suggesting litter from the developing diverse plant community has altered SOM near the surface. Our new approach for assessing SOM development, combining ASE-GCMS with illuminating multivariate statistical analysis, holds great promise to more fully develop ASE for the characterisation of SOM.

An integrated model of soil-canopy spectral radiances, photosynthesis, fluorescence, temperature and energy balance

This paper presents the model SCOPE (Soil Canopy Observation, Photochemistry and Energy fluxes), which is a vertical (1-D) integrated radiative transfer and energy balance model. The model links visible to thermal infrared radiance spectra (0.4 to 50 μm) as observed above the canopy to the fluxes of water, heat and carbon dioxide, as a function of vegetation structure, and the vertical profiles of temperature. Output of the model is the spectrum of outgoing radiation in the viewing direction and the turbulent heat fluxes, photosynthesis and chlorophyll fluorescence. A special routine is dedicated to the calculation of photosynthesis rate and chlorophyll fluorescence at the leaf level as a function of net radiation and leaf temperature. The fluorescence contributions from individual leaves are integrated over the canopy layer to calculate top-of-canopy fluorescence. The calculation of radiative transfer and the energy balance is fully integrated, allowing for feedback between leaf temperatures, leaf chlorophyll fluorescence and radiative fluxes. Leaf temperatures are calculated on the basis of energy balance closure. Model simulations were evaluated against observations reported in the literature and against data collected during field campaigns. These evaluations showed that SCOPE is able to reproduce realistic radiance spectra, directional radiance and energy balance fluxes. The model may be applied for the design of algorithms for the retrieval of evapotranspiration from optical and thermal earth observation data, for validation of existing methods to monitor vegetation functioning, to help interpret canopy fluorescence measurements, and to study the relationships between synoptic observations with diurnally integrated quantities. The model has been implemented in Matlab and has a modular design, thus allowing for great flexibility and scalability.

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.