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  • 1
    ISSN: 1365-2389
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Geosciences , Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition
    Notes: Plant-pathogenic nematodes are a major cause of crop damage worldwide, the current chemical nematicides cause environmental damage, but alternatives such as biological control are less effective, so further understanding of the relationship between nematodes, nematicides, biological control agents and soil and rhizosphere microorganisms is needed.Microbial populations from roots of cabbage and tomato plants infested with the root-knot nematode Meloidogyne incognita were compared with those from plants where the nematode was controlled by the nematicide aldicarb, or a nematophagous fungus with biological control potential, Pochonia chlamydosporia. The total numbers of culturable bacteria and fungi in rhizosphere soil were similar in all three treatments for both plants, around 100-fold more than in control soil in which there were no plants. However, there were clear differences in the catabolic diversity, assessed by Biolog EcoPlate™ carbon substrate utilization assays, between microbial populations from unplanted soil and the rhizosphere. In cabbage, a poor host for M. incognita, the rhizosphere population from P. chlamydosporia-treated plants was distinct from the population from untreated and aldicarb-treated plants. In tomato, a host susceptible to the nematode, the catabolic diversity of populations from aldicarb- and P. chlamydosporia-treated plants was similar and differed from the untreated, nematode-infested plants. The genetic diversity of the fast-growing heterotrophic bacteria in the tomato rhizosphere, indicated by PCR fingerprinting with ERIC primers, was very different in the infested roots, whereas the profiles of isolates from both aldicarb- and P. chlamydosporia-treated roots were similar. Evidently, nematodes have a greater impact on the rhizosphere population of a susceptible host, tomato, than a poor one, cabbage, and nematode-infested roots are colonized by a different subpopulation of soil microbes from that on plants where infection is controlled, illustrating differences in root morphology and physiology.
    Type of Medium: Electronic Resource
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  • 2
    Electronic Resource
    Electronic Resource
    Oxford, UK; Malden, USA : Blackwell Publishing Ltd/Inc.
    European journal of soil science 55 (2004), S. 0 
    ISSN: 1365-2389
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Geosciences , Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition
    Notes: This paper shows how the wavelet transform can be used to analyse the complex spatial covariation of the rate of nitrous oxide (N2O) emissions from the soil with soil properties that are expected to control the evolution of N2O. We use data on N2O emission rates from soil cores collected at 4-m intervals on a 1024-m transect across arable land at Silsoe in England. Various soil properties, particularly those expected to influence N2O production in the soil, were also determined on these cores.We used the adapted maximal overlap discrete wavelet transform (AMODWT) coefficients for the N2O emissions and soil variables to compute their wavelet covariances and correlations. These showed that, over the transect as a whole, some soil properties were significantly correlated with N2O emissions at fine spatial scales (soil carbon content), others at intermediate scales (soil water content) and others at coarse spatial scales (soil pH). Ammonium did not appear to be correlated with N2O emissions at any scale, suggesting that nitrification was not a significant source of N2O from these soils in the conditions that pertained at sampling.We used a procedure to detect changes in the wavelet correlations at several spatial scales. This showed that certain soil properties were correlated with N2O emissions only under certain conditions of topography or parent material. This is not unexpected given that N2O is generated by biological processes in the soil, so the rate of emission may be subject to one limiting factor in one environment and a different factor elsewhere. Such changes in the relationship between variables from one part of the landscape to another is not consistent with the geostatistical assumption that our data are realizations of coregionalized random variables.
    Type of Medium: Electronic Resource
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  • 3
    ISSN: 1365-2389
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Geosciences , Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition
    Notes: We used the wavelet transform to quantify the performance of models that predict the rate of emission of nitrous oxide (N2O) from soil. Emissions of N2O and other soil variables that influence emissions were measured on soil cores collected at 256 locations across arable land in Bedfordshire, England. Rate-limiting models of N2O emissions were constructed and fitted to the data by functional analysis. These models were then evaluated by wavelet variance and wavelet correlations, estimated from coefficients of the adapted maximal overlap discrete wavelet transform (AMODWT), of the fitted and measured emission rates.We estimated wavelet variances to assess whether the partition of the variance of modelled rates of N2O emission between scales reflected that of the data. Where the relative distribution of variance in the model is more skewed to coarser scales than is the case for the observation, for example, this indicates that the model predictions are too smooth spatially, and fail adequately to represent some of the variation at finer scales. Scale-dependent wavelet correlations between model and data were used to quantify the model performance at each scale, and in several cases to determine the scale at which the model description of the data broke down. We detected significant changes in correlation between modelled and predicted emissions at each spatial scale, showing that, at some scales, model performance was not uniform in space. This suggested that the influence of a soil variable on N2O emissions, important in one region but not in another, had been omitted from the model or modelled poorly. Change points usually occurred at field boundaries or where soil textural class changed.We show that wavelet analysis can be used to quantify aspects of model performance that other methods cannot. By evaluating model behaviour at several scales and positions wavelet analysis helps us to determine whether a model is suitable for a particular purpose.
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  • 4
    Electronic Resource
    Electronic Resource
    Oxford, UK; Malden, USA : Blackwell Publishing Ltd/Inc.
    European journal of soil science 55 (2004), S. 0 
    ISSN: 1365-2389
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Geosciences , Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition
    Notes: Emissions of gases from the soil are known to vary spatially in a complex way. In this paper we show how such data can be analysed with the wavelet transform. We analysed data on rates of N2O emission from soil cores collected at 4-m intervals on a 1024-m transect across arable land at Silsoe in England. We used a thresholding procedure to represent intermittent variation in N2O emission from the soil as a sparse wavelet process, i.e. one in which most of the wavelet coefficients are not significantly different from zero. This analysis made clear that the rate of N2O emission varied more intermittently on this transect than did soil pH, for which many more of the wavelet coefficients had to be retained. This account of intermittent variation motivated us to consider a class of random functions, which we call wavelet random functions, for the simulation of spatially intermittent variation. A wavelet random function (WRF) is an inverse wavelet transform of a set of random wavelet coefficients with specified variance at each scale. We generated intermittent variation at a particular scale in the WRF by specifying a binormal process for the wavelet coefficients at this scale. We showed by simulation that adaptive sampling schemes are more efficient than ordinary stratified random sampling to estimate the mean of a spatial variable that is intermittent at a particular scale. This is because the sampling can be concentrated in the more variable regions. When we simulated values that emulate the intermittency of our data on N2O we found that the gains in efficiency from simple adaptive sampling schemes were small. This was because the emission of N2O is intermittent over several disparate scales. More sophisticated adaptive sampling is needed for these conditions, and it should embody knowledge of the relevant soil processes.
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  • 5
    Publication Date: 2003-12-01
    Print ISSN: 1351-0754
    Electronic ISSN: 1365-2389
    Topics: Geosciences , Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition
    Published by Wiley
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