Exploring the spatial relations between soil physical properties and apparent electrical conductivity

Relations between the apparent electrical conductivity of the soil (ECa) and top- and sub-soil physical properties were examined for two arable fields in southern England (Crowmarsh Battle Farms and the Yattendon Estate). The spatial variation of ECa and the soil properties was explored geostatistically. The variogram ranges showed that ECa varied on a similar spatial scale to many of the soil physical properties in both fields. Several features in the map of kriged predictions of ECa were also evident in maps of the soil properties. In addition, the correlation coefficients showed a strong relation between ECa and several soil properties. A moving correlation analysis enabled differences in the relations between ECa and the soil properties to be examined within the fields. The results indicated that relations were inconsistent; they were stronger in some areas than others. A regression of ECa on the principal component scores of the leading components for both fields showed that the first two components accounted for a large proportion of the variance in ECa, whereas the others accounted for little or none. For Crowmarsh topsoil sand and clay, loss on ignition and volumetric water measured in the autumn had large correlations on the first component, and for Yattendon they were large for topsoil sand and clay, and autumn and spring volumetric water. The cross-variograms suggested strong coregionalization between ECa and several soil physical properties; in particular subsoil sand and silt at Crowmarsh, and subsoil sand and clay at Yattendon. The structural correlations from the linear model of coregionalization confirmed the strength of the relations between ECa and the subsoil properties. Nevertheless, no one property was consistently important for both fields. Although a map of ECa can indicate the general patterns of spatial variation in the soil, it is not a substitute for information on soil properties obtained by sampling and analysing the soil. Nevertheless, it could be used to guide further sampling. (c) 2005 Elsevier B.V. All rights reserved.

Variograms of ancillary data to aid sampling for soil surveys

To provide reliable estimates for mapping soil properties for precision agriculture requires intensive sampling and costly laboratory analyses. If the spatial structure of ancillary data, such as yield, digital information from aerial photographs, and soil electrical conductivity (EC) measurements, relates to that of soil properties they could be used to guide the sampling intensity for soil surveys. Variograins of permanent soil properties at two study sites on different parent materials were compared with each other and with those for ancillary data. The ranges of spatial dependence identified by the variograms of both sets of properties are of similar orders of magnitude for each study site, Maps of the ancillary data appear to show similar patterns of variation and these seem to relate to those of the permanent properties of the soil. Correlation analysis has confirmed these relations. Maps of kriged estimates from sub-sampled data and the original variograrns showed that the main patterns of variation were preserved when a sampling interval of less than half the average variogram range of ancillary data was used. Digital data from aerial photographs for different years and EC appear to show a more consistent relation with the soil properties than does yield. Aerial photographs, in particular those of bare soil, seem to be the most useful ancillary data and they are often cheaper to obtain than yield and EC data.

Determining nugget: sill ratios of standardized variograms from aerial photographs to krige sparse soil data

Maps of kriged soil properties for precision agriculture are often based on a variogram estimated from too few data because the costs of sampling and analysis are often prohibitive. If the variogram has been computed by the usual method of moments, it is likely to be unstable when there are fewer than 100 data. The scale of variation in soil properties should be investigated prior to sampling by computing a variogram from ancillary data, such as an aerial photograph of the bare soil. If the sampling interval suggested by this is large in relation to the size of the field there will be too few data to estimate a reliable variogram for kriging. Standardized variograms from aerial photographs can be used with standardized soil data that are sparse, provided the data are spatially structured and the nugget:sill ratio is similar to that of a reliable variogram of the property. The problem remains of how to set this ratio in the absence of an accurate variogram. Several methods of estimating the nugget:sill ratio for selected soil properties are proposed and evaluated. Standardized variograms with nugget:sill ratios set by these methods are more similar to those computed from intensive soil data than are variograms computed from sparse soil data. The results of cross-validation and mapping show that the standardized variograms provide more accurate estimates, and preserve the main patterns of variation better than those computed from sparse data.

Sampling the soil in long-term forest plots: The implications of spatial variation

Long-term monitoring of forest soils as part of a pan-European network to detect environmental change depends on an accurate determination of the mean of the soil properties at each monitoring event. Forest soil is known to be very variable spatially, however. A study was undertaken to explore and quantify this variability at three forest monitoring plots in Britain. Detailed soil sampling was carried out, and the data from the chemical analyses were analysed by classical statistics and geostatistics. An analysis of variance showed that there were no consistent effects from the sample sites in relation to the position of the trees. The variogram analysis showed that there was spatial dependence at each site for several variables and some varied in an apparently periodic way. An optimal sampling analysis based on the multivariate variogram for each site suggested that a bulked sample from 36 cores would reduce error to an acceptable level. Future sampling should be designed so that it neither targets nor avoids trees and disturbed ground. This can be achieved best by using a stratified random sampling design.

Interactions between earthworms and arsenic in the soil environment: a review

Chemical pollution of the environment has become a major source of concern. In particular, many studies have investigated the impact of pollution on biota in the environment. Studies on metalliferous contaminated mine spoil wastes have shown that some soil organisms have the capability to become resistant to metal/metalloid toxicity. Earthworms are known to inhabit arsenic-rich metalliferous soils and, due to their intimate contact with the soil, in both the solid and aqueous phases, are likely to accumulate contaminants present in mine spoil. Earthworms that inhabit metalliferous contaminated soils must have developed mechanisms of resistance to the toxins found in these soils. The mechanisms of resistance are not fully understood; they may involve physiological adaptation (acclimation) or be genetic. This review discusses the relationships between earthworms and arsenic-rich mine spoil wastes, looking critically at resistance and possible mechanisms of resistance, in relation to soil edaphic factors and possible trophic transfer routes. (C) 2003 Elsevier Science Ltd. 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.

Morphology, biomass and nutrient status of fine roots of Scots pine (Pinus sylvestris) as influenced by seasonal fluctuations in soil moisture and soil solution chemistry

A field monitoring study was carried out to follow the changes of fine root morphology, biomass and nutrient status in relation to seasonal changes in soil solution chemistry and moisture regime in a mature Scots pine stand on acid soil. Seasonal and yearly fluctuations in soil moisture and soil solution chemistry have been observed. Changes in soil moisture accounted for some of the changes in the soil solution chemistry. The results showed that when natural acidification in the soil occurs with low pH (3.5-4.2) and high aluminium concentration in the soil solution (> 3-10 mg l(-1)), fine root longevity and distribution could be affected. However, fine root growth of Scots pine may not be negatively influenced by adverse soil chemical conditions if soil moisture is not a limiting factor for root growth. In contrast, dry soil conditions increase Scots pine susceptibility to soil acidification and this could significantly reduce fine root growth and increase root mortality. It is therefore important to study seasonal fluctuations of the environmental variables when investigating and modelling cause-effect relationships.

Molecular genetic differentiation in earthworms inhabiting a heterogeneous Pb-polluted landscape

A Pb-mine site situated on acidic soil, but comprising of Ca-enriched islands around derelict buildings was used to study the spatial pattern of genetic diversity in Lumbricus rubellus. Two distinct genetic lineages ('A' and 'B'), differentiated at both the mitochondrial (mtDNA COII) and nuclear level (AFLPs) were revealed with a mean inter-lineage mtDNA sequence divergence of approximately 13%, indicative of a cryptic species complex. AFLP analysis indicates that lineage A individuals within one central 'ecological island' site are uniquely clustered, with little genetic overlap with lineage A individuals at the two peripheral sites. FTIR microspectroscopy of Pb-sequestering chloragocytes revealed different phosphate profiles in residents of adjacent acidic and calcareous islands. Bioinformatics found over-representation of Ca pathway genes in ESTPb libraries. Subsequent sequencing of a Ca-transport gene, SERCA, revealed mutations in the protein's cytosolic domain. We recommend the mandatory genotyping of all individuals prior to field-based ecotoxicological assays, particularly those using discriminating genomic technologies.

Hay strewing, brush harvesting of seed and soil disturbance as tools for the enhancement of botanical diversity in grasslands

Since the middle of the last century agricultural intensification within Europe has led to a drastic decline in the extent of botanically diverse grasslands. Whilst measures to enhance the diversity of agriculturally-improved grasslands are in place, success has often been limited. One of the primary factors limiting success is the paucity of sources of propagules of desirable species in the surrounding landscape. The restoration of two contrasting grassland types lowland hay meadow and chalk grassland) was examined using a replicated block experiment to assess the effectiveness of two methods of seed application (hay strewing and brush harvesting) and two methods of pre-treatment disturbance (power harrowing and turf stripping). The resulting changes in botanical composition were monitored for 4 years. Seed addition by both methods resulted in significant temporal trends in plant species composition and increases in plant species richness, which were further enhanced by disturbance. Power harrowing increased the effectiveness of the seed addition treatments at the lowland hay meadow site. At the chalk grassland site a more severe disturbance created by turf stripping was used and shown to be preferable. Whilst both hay strewing and brush harvesting increased plant species richness, hay strewing was more effective at creating a sward similar to that of the donor site. Soil disturbance and seed application rate at the recipient site and timing of the hay cut at the donor site are all factors to be considered prior to the commencement of restoration management. (c) 2006 Elsevier Ltd. All rights reserved.

The use of a multiple criteria decision analysis to evaluate the effectiveness of landscape and habitat enhancement mechanisms: an example from the South Downs

A range of funding schemes and policy instruments exist to effect enhancement of the landscapes and habitats of the UK. While a number of assessments of these mechanisms have been conducted, little research has been undertaken to compare both quantitatively and qualitatively their relative effectiveness across a range of criteria. It is argued that few tools are available for such a multi-faceted evaluation of effectiveness. A form of Multiple Criteria Decision Analysis (MCDA) is justified and utilized as a framework in which to evaluate the effectiveness of nine mechanisms in relation to the protection of existing areas of chalk grassland and the creation of new areas in the South Downs of England. These include established schemes, such as the Countryside Stewardship and Environmentally Sensitive Area Schemes, along with other less common mechanisms, for example, land purchase and tender schemes. The steps involved in applying an MCDA to evaluate such mechanisms are identified and the process is described. Quantitative results from the comparison of the effectiveness of different mechanisms are presented, although the broader aim of the paper is that of demonstrating the performance of MCDA as a tool for measuring the effectiveness of mechanisms aimed at landscape and habitat enhancement.

Arthropod diversity and community structure in relation to land use in the mekong delta, vietnam

Declining biodiversity in agro-ecosystems, caused by intensification of production or expansion of monocultures, is associated with the emergence of agricultural pests. Understanding how land-use and management control crop-associated biodiversity is, therefore, one of the key steps towards the prediction and maintenance of natural pest-control. Here we report on relationships between land-use variables and arthropod community attributes (for example, species diversity, abundance and guild structure) across a diversification gradient in a rice-dominated landscape in the Mekong delta, Vietnam. We show that rice habitats contained the most diverse arthropod communities, compared with other uncultivated and cultivated land-use types. In addition, arthropod species density and Simpson's diversity in flower, vegetable and fruit habitats was positively related to rice cover in the local landscape. However, across the landscape as a whole, reduction in heterogeneity and the amount of uncultivated cover was associated, generally, with a loss of diversity. Furthermore, arthropod species density in tillering and flowering stages of rice was positively related to crop and vegetation richness, respectively, in the local landscape. Differential effects on feeding guilds were also observed in rice-associated communities with the proportional abundance of predators increasing and the proportional abundance of detritivores decreasing with increased landscape rice cover. Thus, we identify a range of rather complex, sometimes contradictory patterns concerning the impact of rice cover and landscape heterogeneity on arthropod community attributes. Importantly, we conclude that that land-use change associated with expansion of monoculture rice need not automatically impact diversity and functioning of the arthropod community.

Population performance of collembolans feeding on soil fungi from different ecological niches

The potential reproductive value of arbuscular mycorrhizal fungi (Gloinus intraradices and Glomus invermaium), root pathogenic fungi (Rhizoctonia solani and Fusarium culmorum) and saprotrophic fungi (Penicillium hordei and Trichoderma harzianum) were examined for the collembolans Folsomia candida Willem and Folsomia fimetaria L. Dried baker's yeast (Saccharomyces cerevisiae) was used as a reference standard food in laboratory cultures. Collembolan performance was determined as final size, fecundity and population growth rate after when fed the fungal food sources for 31 days. The mycorrhizal fungi gave the least growth and fecundity compared with the other fungi, but G. intraradices gave good fecundity for F. candida. In terms of growth, Baker's yeast was a high-quality food for both adults and juveniles of both species, but it was a poorer food in terms of fecundity of F. candida. Preference of the fungi in all possible pairwise combinations showed that although F. fimetaria did not perform well on Glomus spp. and F. candida did not grow well on Glomus spp. their preference for these fungi did not reflect this. The highest fecundity was seen with the root pathogen F. culmorum. Different quality indicators such as the C:N ratio of the fungal food sources as well as other biological parameters are discussed in relation to their reproductive value and Collembola preferential feeding. (c) 2007 Elsevier Ltd. All rights reserved.

GISQ, a multifunctional indicator of soil quality

We present here an indicator of soil quality that evaluates soil ecosystem services through a set of 5 subindicators, and further combines them into a single general Indicator of Soil Quality (GISQ). We used information derived from 54 properties commonly used to describe the multifaceted aspects of soil quality. The design and calculation of the indicators were based on sequences of multivariate analyses. Subindicators evaluated the physical quality, chemical fertility, organic matter stocks, aggregation and morphology of the upper 5 cm of soil and the biodiversity of soil macrofauna. A GISQ combined the different subindicators providing a global assessment of soil quality. Research was conducted in two hillside regions of Colombia and Nicaragua, with similar types of land use and socio-economic context. However, soil and climatic conditions differed significantly. In Nicaragua, soil quality was assessed at 61 points regularly distributed 200 m apart on a regular grid across the landscape. In Colombia, 8 plots representing different types of land use were arbitrarily chosen in the landscape and intensively sampled. Indicators that were designed in the Nicaragua site were further applied to the Colombian site to test for their applicability. In Nicaragua, coffee plantations, fallows, pastures and forest had the highest values of GISQ (1.00; 0.80; 0.78 and 0.77, respectively) while maize crops and eroded soils (0.19 and 0.10) had the lowest values. Examination of subindicator values allowed the separate evaluation of different aspects of soil quality: subindicators of organic matter, aggregation and morphology and biodiversity of macrofauna had the maximum values in coffee plantations (0.89; 0.72 and 0.56, respectively on average) while eroded soils had the lowest values for these indicators (0.10; 0.31 and 0.33, respectively). Indicator formulae derived from information gained at the Nicaraguan sites were not applicable to the Colombian situation and site-specific constants were calculated. This indicator allows the evaluation of soil quality and facilitates the identification of problem areas through the individual values of each subindicator. It allows monitoring of change through time and can guide the implementation of soil restoration technologies. Although GISQ formulae computed on a set of data were only valid at a regional scale, the methodology used to create these indices can be applied everywhere.

How predation and landscape fragmentation affect vole population dynamics

Background: Microtine species in Fennoscandia display a distinct north-south gradient from regular cycles to stable populations. The gradient has often been attributed to changes in the interactions between microtines and their predators. Although the spatial structure of the environment is known to influence predator-prey dynamics of a wide range of species, it has scarcely been considered in relation to the Fennoscandian gradient. Furthermore, the length of microtine breeding season also displays a north-south gradient. However, little consideration has been given to its role in shaping or generating population cycles. Because these factors covary along the gradient it is difficult to distinguish their effects experimentally in the field. The distinction is here attempted using realistic agent-based modelling. Methodology/Principal Findings: By using a spatially explicit computer simulation model based on behavioural and ecological data from the field vole (Microtus agrestis), we generated a number of repeated time series of vole densities whose mean population size and amplitude were measured. Subsequently, these time series were subjected to statistical autoregressive modelling, to investigate the effects on vole population dynamics of making predators more specialised, of altering the breeding season, and increasing the level of habitat fragmentation. We found that fragmentation as well as the presence of specialist predators are necessary for the occurrence of population cycles. Habitat fragmentation and predator assembly jointly determined cycle length and amplitude. Length of vole breeding season had little impact on the oscillations. Significance: There is good agreement between our results and the experimental work from Fennoscandia, but our results allow distinction of causation that is hard to unravel in field experiments. We hope our results will help understand the reasons for cycle gradients observed in other areas. Our results clearly demonstrate the importance of landscape fragmentation for population cycling and we recommend that the degree of fragmentation be more fully considered in future analyses of vole dynamics.