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.

The Representative Soil Sampling Scheme of England and Wales: a statistical analysis of topsoil nutrient status and pH between 1971 and 2001

The Representative Soil Sampling Scheme of England and Wales has recorded information on the soil of agricultural land in England and Wales since 1969. It is a valuable source of information about the soil in the context of monitoring for sustainable agricultural development. Changes in soil nutrient status and pH were examined over the period 1971-2001. Several methods of statistical analysis were applied to data from the surveys during this period. The main focus here is on the data for 1971, 1981, 1991 and 2001. The results of examining change over time in general show that levels of potassium in the soil have increased, those of magnesium have remained fairly constant, those of phosphorus have declined and pH has changed little. Future sampling needs have been assessed in the context of monitoring, to determine the mean at a given level of confidence and tolerable error and to detect change in the mean over time at these same levels over periods of 5 and 10 years. The results of a non-hierarchical multivariate classification suggest that England and Wales could be stratified to optimize future sampling and analysis. To monitor soil quality and health more generally than for agriculture, more of the country should be sampled and a wider range of properties recorded.

Typification of farming systems for constructing representative farm models: two illustrations of the application of multi-variate analyses in Chile and Pakistan

If the fundamental precepts of Farming Systems Research were to be taken literally then it would imply that for each farm 'unique' solutions should be sought. This is an unrealistic expectation, but it has led to the idea of a recommendation domain, implying creating a taxonomy of farms, in order to increase the general applicability of recommendations. Mathematical programming models are an established means of generating recommended solutions, but for such models to be effective they have to be constructed for 'truly' typical or representative situations. The multi-variate statistical techniques provide a means of creating the required typologies, particularly when an exhaustive database is available. This paper illustrates the application of this methodology in two different studies that shared the common purpose of identifying types of farming systems in their respective study areas. The issues related with the use of factor and cluster analyses for farm typification prior to building representative mathematical programming models for Chile and Pakistan are highlighted. (C) 2003 Elsevier Science Ltd. All rights reserved.

Democracy and identity: educating the student voice

Considering the role of student voice in music education in connection with the role of music in identity formation. A report on a small-scale study.

Changes in the intestinal microbiota after a short period of dietary over-indulgence, representative of a holiday or festival season

The effects on the intestinal microbiota of a short period of marginal over-eating, characteristic of holiday or festival periods, were investigated in a pilot study. Fourteen healthy male subjects consumed a diet rich in animal protein and fat for seven days. During this period, the subjects significantly increased their dietary energy, protein, carbohydrate and fat intakes by 56, 59, 53 and 58%, respectively (all P < 0.05). The mean weight gain of 0.27 kg was less than the expected 1 kg, but this was consistent with a degree of under-reporting on the baseline diet. Fluorescence in situ hybridisation analysis confirmed the relative stability of each individual’s faecal microbiota but showed considerable variations between them. The diet was associated with a significant increase in numbers of total faecal bacteria and the bacteroides group, as detected by the universal bacterial probe (DAPI) and Bacteroides probe (Bac 303), respectively. Overall, there was a decrease in numbers of the Lactobacillus/Enterococcus group (Lab 158 probe; 2.8 ± 3.0% to 1.8 ± 1.8%) and the Bifidobacterium group (Bif 164 probe; 3.0 ± 3.7% to 1.7 ± 1.2%), although there was considerable inter-individual variation. Analysis of the relative proportions of each bacterial group as a percentage of the subject’s total bacteria showed a trend for a change in the intestinal microbiota that might be considered potentially unhealthy.