FUNDAMENTAL OBJECTIONS TO THE 7TH APPROXIMATION

The 7th Approximation suffers from three fundamental ills. It demands an unattainable degree of precision and its exactly defined, mutually exclusive classes lead to inconsistency or absurdity when the system is used. Logical division is used out of context to construct a hierarchical structure, while the dispersed nature of soil distribution does not lend itself to hierarchical arrangement in any form. Its search for genetically significant properties on which to define classes involves circular reasoning, since the genetic significance of a property can usually be discovered only after the soils have been classified. Mutual exclusion and rigid adherence to the hierarchy result in the system failing to serve adequately the requirements of soil survey. The 7th Approximation explores to the limit the potential of logical division for soil classification yet remains unsatisfactory. The nature of soil distribution and the requirements demanded of soil classification suggest that a co-ordinate system would be more profitable, and a study of such systems is urged.     

WILKS'S CRITERION: A MEASURE FOR COMPARING THE VALUE OF GENERAL PURPOSE SOIL CLASSIFICATIONS

Wilks's Criterion, the ratio of the determinants of the within-class and total dispersion matrices, is described. It can measure the relative goodness of a general purpose soil classification, and can be used to determine how many clusters are present in a population, and hence how many classes can reasonably be recognized. Its use is illustrated with two examples. In the first, three soil maps of the same area, but at different scales, are compared. In the second, classifications of a set of profiles are shown to have recognized only three clusters.     

CANONICAL CORRELATION IN PEDOLOGY: HOW USEFUL?

Canonical correlation is an analytical technique for relating one multivariate set of measurements on a population to another in terms of linear functions of the two sets. It can express quantitatively the relation between the soil, described by one set of variates, and its environment, described by another, and attempt statistical prediction of the one from a knowledge of the other. The method is described briefly, and applied to soil and environmental data from soil surveys in Britain (the Dee catchment of North Wales) and Australia (Ginninderra in the Australian Capital Territory and the Wungong Brook catchment near Perth, Western Australia). The technique is judged to be a useful exploratory tool for seeking relations in situations that are little known or understood.     

SULPHATE DISTRIBUTION IN SOLONETZIC SOIL WITH A WATER TABLE

Soil columns were used to study sulphate distribution in Thin Duagh Loam soil as influenced by the presence of a water table. The concentration pattern showed that retention was greater in the surface soil than at lower depths. The data suggest that sulphate tends to move more slowly than water in soil.     

OPTIMAL INTERPOLATION AND ISAR1THMIC MAPPING OF SOIL PROPERTIES

Kriging is a means of spatial prediction that can be used for soil properties. It is a form of weighted local averaging. It is optimal in the sense that it provides estimates of values at unrecorded places without bias and with minimum and known variance. Isarithmic maps made by kriging are alternatives to conventional soil maps where properties can be measured at close spacings. Kriging depends on first computing an accurate semi-variogram, which measures the nature of spatial dependence for the property. Estimates of semi-variance are then used to determine the weights applied to the data when computing the averages, and are presented in the kriging equations. The method is applied to three sets of data from detailed soil surveys in Central Wales and Norfolk. Sodium content at Plas Gogerddan was shown to vary isotropically with a linear semi-variogram. Simple punctual kriging produced a map with intricate isarithms and fairly large estimation variance, attributed to a large nugget effect. Sloniness on the same land varied anisotropically with a linear semi-variogram. and again the estimation error of punctual kriging was fairly large. At Hole Farm. Norfolk, the thickness of cover loam varied isotropically, but with a spherical semi-variogram. Its parameters were estimated and used to krige point values and produce a map showing substantial short-range variation.     

DPTIMAL INTERPOLATION AND ISARITHMIC MAPPING OF SOIL PROPERTIES. IV SAMPLING STRATEGY

A sampling strategy is presented for soil survey in which an individual soil property is of interest and can be measured. It depends on first determining accurately the semi-variogram for the property, and this must be done in a prior reconnaissance stage of a survey. Then from the semi-variogram estimation variances can be found for any combination of block size and sampling density by the methods of kriging. Alternatively for a given block size the sampling density needed to achieve a predetermined precision (maximum estimation variance) can be determined. The strategy is optimal in the sense that the sampling effort is the least possible to achieve the precision desired. An equilateral triangular configuration of sampling points is best where variation is isotropic, but a square grid at the same density is very nearly as good, and will usually be preferred for convenience. Where there is simple anisotropic variation optimal sampling is achieved by choosing a rectangular grid with sides in the same proportion to one another as the slopes of the semi-variogram in the directions of maximum and minimum variation.     

Following the decomposition of ryegrass labelled with 13C and 15N in soil by solid-state nuclear magnetic resonance spectroscopy

Investigating the biogeochemistry of plant material decomposition in soil has been restricted by difficulties extracting and identifying organic compounds. In this study the decomposition of ¹³C- and ¹⁵N-labelled Lolium perenne leaves mixed with mineral soil has been investigated over 224 days of incubation under laboratory conditions. Decomposition was followed using short-term rates of CO₂ evolution, the amounts of ¹³C and ¹⁵N remaining were determined by mass spectrometry, and ¹³C and ¹⁵N solid-state nuclear magnetic resonance (NMR) spectroscopy was used to characterize chemically the plant material as it decomposed. After 224 days 48% of the added ¹³C had been lost with a rapid period of C0₂ evolution over the first 56 days. The fraction of cross-polarization magic angle spinning (CP MAS) ¹³C NMR spectra represented by O-alkyl-C signal probably in carbohydrates (chemical shift, 60–90 p.p.m.) declined from 60 to 20% of the spectrum (chemical shift, 0–200 p.p.m.) over 224 days. The rate of decline of the total ¹³C exceeded that of the 60–90 p.p.m. signal during the first 56 days and was similar thereafter. The fraction of the CP MAS ¹³C NMR spectra represented by the alkyl- and methyl-C (chemical shift, 10–45 p.p.m.) signal increased from 5 to 14% over the first 14 days and was 19% after 224 days. CP MAS ¹³C NMR of ¹³C- and ¹⁵N-L. perenne contained in 100-μm aperture mesh bags incubated in the soil for 56 days indicated that the remaining material was mainly carbohydrate but there was an increase in the alkyl- and methyl-C associated with the bag's contents. After 224 days incubation of the labelled ¹³C- and ¹⁵N-L. perenne mixed with the soil, 40% of the added N had been lost. Throughout the incubation there was only one signal centred around 100 p.p.m. detectable in the CP MAS ¹⁵N NMR spectra. This signal corresponded to amide ¹⁵N in peptides and may have been of plant or microbial origin or both. Although there had been substantial interaction between the added ¹⁵N and the soil microorganisms, the associated redistribution of ¹⁵N from plant to microbial tissues occurred within the amide region. The feasibility of following some of the component processes of plant material decomposition in soil using NMR has been demonstrated in this study and evidence that microbial synthesis contributes to the increase in alkyl- and methyl-C content of soil during decomposition has been represented.     

Estimating temporal change in soil monitoring: I. Statistical theory

Detecting small temporal change of spatially varying soil properties demands precise estimation. Design– and model–based methods are compared for estimating temporal change of soil properties over finite areas. Analytical expressions for the estimators and their variances arc derived for the two approaches, and formulae for the expectations of the variances under the random–process model are developed. Among the randomized designs simple, stratified, and systematic random sampling using the arithmetic mean as estimator have been studied. Pairing the sampling positions on the different occasions increases the precision of design–based estimation if the observations are positively cross–correlated. The relative precisions of the means of stratified and systematic samples depends on the spatial correlation. Neither is more precise than the other in all circumstances. The stratified design provides an unbiased estimator for the sampling error, which is not available from systematic samples. Theoretically, the geostatistical global estimator is more precise than the estimates derived from any of the classical designs when many realizations arc repeatedly sampled at random. In practice, with only a single realization of the process, this is no longer relevant. Moreover, errors in estimating the variograms add to the total error of the method. It seems that only by sampling from large auto–correlated random fields can the precisions of the methods be compared in practice.     

Comparisons of methods for measuring the leaching of mineral nitrogen from arable land

Comparisons were made between 1988 and 1991 to evaluate three methods of estimating the leaching of mineral nitrogen (N) from unstructured freely draining sandy loam and loamy sand soils. The studies compared the drainage patterns and quantities of N (almost exclusively nitrate) leached from monolith lysimeters with those estimated from ceramic suction cups and soil core extracts. The latter two methods gave direct measurements of the mineral N concentrations in drainage, but required an estimate of the drainage volume calculated from meteorological observations and evapotranspiration equations to give total N leached. A bromide tracer was also used to confirm conclusions from nitrate leaching studies. There was a delay in the onset of drainage from free draining lysimeters because they lack the subsoil matric potential of field soils. However, total annual drainage measured by lysimeters or calculated from meteorological observations was similar, providing that return to field capacity was correctly identified in the field soil. During the first year there were discrepancies between methods which were attributed to soil disturbance during lysimeter and/or ceramic cup installation. In the second and third years of the experiment, estimates of N leaching losses using the lysimeters and ceramic cups were in good agreement. Nitrate concentrations in soil solution at a depth of 130 cm measured from soil core extracts were smaller than found by the other methods during the second year and the peak concentrations were significantly different (P<0.05). However, total overwinter N leached was not significantly different. Thus, while lysimeters and cups can be used to quantify leaching losses on unstructured, free draining soils if used correctly, the use of soil core extracts is questionable.     

The elucidation of soil pattern in the Wyre Forest of the West Midlands, England. II. Spatial distribution

The spatial distribution of soil in the Wyre Forest of England was analysed in two phases. In the first the soil was examined at sites chosen using a five-stage nested design with spacings increasing geometrically from 6 m to 600 m. Some 80% of the variance was contributed by components for the spacings between 6 m and 60 m. Measurements were then made on transects at 5 m intervals and semi-variograms estimated to 70 m. Except for those of pH the semi-variograms of the soil properties had the same general transitive form and a common effective range of about 40 m. This short range meant that very intensive sampling, approximately one point per 400 m², is needed to map the soil variation. A survey was made of a small portion of the forest on a 20m × 25 m grid to test the inference. Maps of clay and sand content were made successfully by kriging from the data. The mutual correlations between soil properties and the common range of their semi-variograms enabled a general purpose and spatially coherent soil classification to be created from the data. Its mapping confirmed the intricacy of the soil pattern in the Forest.