Estimating the spatial scales of regionalized variables by nested sampling, hierarchical analysis of variance and residual maximum likelihood

The variogram is essential for local estimation and mapping of any variable by kriging. The variogram itself must usually be estimated from sample data. The sampling density is a compromise between precision and cost, but it must be sufficiently dense to encompass the principal spatial sources of variance. A nested, multi-stage, sampling with separating distances increasing in geometric progression from stage to stage will do that. The data may then be analyzed by a hierarchical analysis of variance to estimate the components of variance for every stage, and hence lag. By accumulating the components starting from the shortest lag one obtains a rough variogram for modest effort. For balanced designs the analysis of variance is optimal; for unbalanced ones, however, these estimators are not necessarily the best, and the analysis by residual maximum likelihood (REML) will usually be preferable. The paper summarizes the underlying theory and illustrates its application with data from three surveys, one in which the design had four stages and was balanced and two implemented with unbalanced designs to economize when there were more stages. A Fortran program is available for the analysis of variance, and code for the REML analysis is listed in the paper. (c) 2005 Elsevier Ltd. All rights reserved.

Assessment of the effect of time and temperature on the availability of residual phosphate in a glasshouse study of four soils using the Olsen method

The Olsen method is an indicator of plant-available phosphorus (P). The effect of time and temperature on residual phosphate in soils was measured using the Olsen method in a pot experiment. Four soils were investigated: two from Pakistan and one each from England (calcareous) and Colombia (acidic). Two levels of residual phosphate were developed in each soil after addition of phosphate by incubation at either 10degreesC or 45degreesC. The amount of phosphate added was based on the P maximum of each soil, calculated using the Langmuir equation. Rvegrass was used as the test crop. The pooled data for the four soils incubated at 10degreesC showed good correlation between Olsen P and dry matter yield or P uptake (r(2) = 0.85 and 0.77, respectively), whereas at 45 degreesC, each soil had its own relationship and pooled data did not show correlation of Olsen P with dry matter yield or P uptake. When the data at both temperatures were pooled, Olsen P was a good indicator of yield and uptake for the English soil. For the Pakistani soils, Olsen P after 45 degreesC treatment was an underestimate relative to the 10 degreesC data and for the Colombian soil it was an overestimate. The reasons for these differences need to be explored further before high temperature incubation can be used to simulate long-term changes in the field.

Indicators of nitrate in wetland surface and soil-waters: interactions of vegetation and environmental factors

This paper describes a new bio-indicator method for assessing wetland ecosystem health: as such, the study is particularly relevant to current legislation such as the EU Water Framework Directive, which provides a baseline of the current status Of Surface waters. Seven wetland sites were monitored across northern Britain, with model construction data for predicting, eco-hydroloplical relationships collected from five sites during 1999, Two new sites and one repeat site were monitored during 2000 to provide model test data. The main growing season for the vegetation, and hence the sampling period, was May-August during both years. Seasonal mean concentrations of nitrate (NO3-) in surface and soil water samples during 1999 ranged from 0.01 to 14.07 mg N 1(-1), with a mean value of 1.01 mg N 1(-1). During 2000, concentrations ranged from trace level (<0.01 m- N 1(-1)) to 9.43 mg N 1(-1), with a mean of 2.73 mg N 1(.)(-1) Surface and soil-water nitrate concentrations did not influence plant species composition significantly across representative tall herb fen and mire communities. Predictive relationships were found between nitrate concentrations and structural characteristics of the wetland vegetation, and a model was developed which predicted nitrate concentrations from measures of plant diversity, canopy structure and density of reproductive structures. Two further models, which predicted stem density and density of reproductive structures respectively, utilised nitrate concentration as one of the independent predictor variables. Where appropriate, the models were tested using data collected during 2000. This approach is complementary to species-based monitoring, representing a useful and simple too] to assess ecological status in target wetland systems and has potential for bio-indication purposes.

Comparing sampling needs for variograms of soil properties computed by the method of moments and residual maximum likelihood

It has been generally accepted that the method of moments (MoM) variogram, which has been widely applied in soil science, requires about 100 sites at an appropriate interval apart to describe the variation adequately. This sample size is often larger than can be afforded for soil surveys of agricultural fields or contaminated sites. Furthermore, it might be a much larger sample size than is needed where the scale of variation is large. A possible alternative in such situations is the residual maximum likelihood (REML) variogram because fewer data appear to be required. The REML method is parametric and is considered reliable where there is trend in the data because it is based on generalized increments that filter trend out and only the covariance parameters are estimated. Previous research has suggested that fewer data are needed to compute a reliable variogram using a maximum likelihood approach such as REML, however, the results can vary according to the nature of the spatial variation. There remain issues to examine: how many fewer data can be used, how should the sampling sites be distributed over the site of interest, and how do different degrees of spatial variation affect the data requirements? The soil of four field sites of different size, physiography, parent material and soil type was sampled intensively, and MoM and REML variograms were calculated for clay content. The data were then sub-sampled to give different sample sizes and distributions of sites and the variograms were computed again. The model parameters for the sets of variograms for each site were used for cross-validation. Predictions based on REML variograms were generally more accurate than those from MoM variograms with fewer than 100 sampling sites. A sample size of around 50 sites at an appropriate distance apart, possibly determined from variograms of ancillary data, appears adequate to compute REML variograms for kriging soil properties for precision agriculture and contaminated sites. (C) 2007 Elsevier B.V. All rights reserved.

Estimating the spatial scale of herbicide and soil interactions by nested sampling, hierarchical analysis of variance and residual maximum likelihood

An unbalanced nested sampling design was used to investigate the spatial scale of soil and herbicide interactions at the field scale. A hierarchical analysis of variance based on residual maximum likelihood (REML) was used to analyse the data and provide a first estimate of the variogram. Soil samples were taken at 108 locations at a range of separating distances in a 9 ha field to explore small and medium scale spatial variation. Soil organic matter content, pH, particle size distribution, microbial biomass and the degradation and sorption of the herbicide, isoproturon, were determined for each soil sample. A large proportion of the spatial variation in isoproturon degradation and sorption occurred at sampling intervals less than 60 m, however, the sampling design did not resolve the variation present at scales greater than this. A sampling interval of 20-25 m should ensure that the main spatial structures are identified for isoproturon degradation rate and sorption without too great a loss of information in this field.

Estimating the spatial scales of regionalized variables by nested sampling, hierarchical analysis of variance and residual maximum likelihood

The variogram is essential for local estimation and mapping of any variable by kriging. The variogram itself must usually be estimated from sample data. The sampling density is a compromise between precision and cost, but it must be sufficiently dense to encompass the principal spatial sources of variance. A nested, multi-stage, sampling with separating distances increasing in geometric progression from stage to stage will do that. The data may then be analyzed by a hierarchical analysis of variance to estimate the components of variance for every stage, and hence lag. By accumulating the components starting from the shortest lag one obtains a rough variogram for modest effort. For balanced designs the analysis of variance is optimal; for unbalanced ones, however, these estimators are not necessarily the best, and the analysis by residual maximum likelihood (REML) will usually be preferable. The paper summarizes the underlying theory and illustrates its application with data from three surveys, one in which the design had four stages and was balanced and two implemented with unbalanced designs to economize when there were more stages. A Fortran program is available for the analysis of variance, and code for the REML analysis is listed in the paper. (c) 2005 Elsevier Ltd. All rights reserved.

North Atlantic subtropical mode waters and ocean memory in HadCM3

A study of the formation and propagation of volume anomalies in North Atlantic Mode Waters is presented, based on 100 yr of monthly mean fields taken from the control run of the Third Hadley Centre Coupled Ocean-Atmosphere GCM (HadCM3). Analysis of the temporal and. spatial variability in the thickness between pairs of isothermal surfaces bounding the central temperature of the three main North Atlantic subtropical mode waters shows that large-scale variability in formation occurs over time scales ranging from 5 to 20 yr. The largest formation anomalies are associated with a southward shift in the mixed layer isothermal distribution, possibly due to changes in the gyre dynamics and/or changes in the overlying wind field and air-sea heat fluxes. The persistence of these anomalies is shown to result from their subduction beneath the winter mixed layer base where they recirculate around the subtropical gyre in the background geostrophic flow. Anomalies in the warmest mode (18 degrees C) formed on the western side of the basin persist for up to 5 yr. They are removed by mixing transformation to warmer classes and are returned to the seasonal mixed layer near the Gulf Stream where the stored heat may be released to the atmosphere. Anomalies in the cooler modes (16 degrees and 14 degrees C) formed on the eastern side of the basin persist for up to 10 yr. There is no clear evidence of significant transformation of these cooler mode anomalies to adjacent classes. It has been proposed that the eastern anomalies are removed through a tropical-subtropical water mass exchange mechanism beneath the trade wind belt (south of 20 degrees N). The analysis shows that anomalous mode water formation plays a key role in the long-term storage of heat in the model, and that the release of heat associated with these anomalies suggests a predictable climate feedback mechanism.

Near infrared reflectance spectroscopy (NIRS) to predict biological parameters of maize silage: effects of particle comminution, oven drying temperature and the presence of residual moisture

Maize silage nutritive quality is routinely determined by near infrared reflectance spectroscopy (NIRS). However, little is known about the impact of sample preparation on the accuracy of the calibration to predict biological traits. A sample population of 48 maize silages representing a wide range of physiological maturities was used in a study to determine the impact of different sample preparation procedures (i.e., drying regimes; the presence or absence of residual moisture; the degree of particle comminution) on resultant NIR prediction statistics. All silages were scanned using a total of 12 combinations of sample pre-treatments. Each sample preparation combination was subjected to three multivariate regression techniques to give a total of 36 predictions per biological trait. Increased sample preparations procedure, relative to scanning the unprocessed whole plant (WP) material, always resulted in a numerical minimisation of model statistics. However, the ability of each of the treatments to significantly minimise the model statistics differed. Particle comminution was the most important factor, oven-drying regime was intermediate, and residual moisture presence was the least important. Models to predict various biological parameters of maize silage will be improved if material is subjected to a high degree of particle comminution (i.e., having been passed through a 1 mm screen) and developed on plant material previously dried at 60 degrees C. The extra effort in terms of time and cost required to remove sample residual moisture cannot be justified. (c) 2005 Elsevier B.V. All rights reserved.

Evidence for a residual postglacial founder effect in a highly dispersive freshwater invertebrate

In the northern hemisphere, glacial periods have had profound and lasting effects on the population genetics of numerous species, with founder effects often persisting for many generations in formerly glaciated regions. We found an unusual example of this in the freshwater bryozoan Cristatella mucedo, which showed regional differences in haplotype diversity with relatively low levels of haplotype diversity in northern Europe compared to central/southern Europe despite previous evidence for frequent dispersal between C. mucedo populations. Such contradictions between high dispersal and low gene flow have now been reported in several other freshwater taxa and may be attributed to persistent founder effects following colonization of sites by a few individuals whose efficient reproduction leads to rapid population growth. Alternatively, selection may determine which genotypes can thrive in northerly locations, or it may be that C. mucedo has undergone cryptic speciation. Future work on adaptive genomic regions is required before we can understand how gene flow, local adaptation, and speciation influence the current distribution patterns of bryozoans and other freshwater invertebrates.

Photocatalytic degradation of humic acid in saline waters part 2. Effects of various photocatalytic materials

The present study explores for the first time, the effectiveness of photocatalytic oxidation of. humic acid (HA) in the increasingly important highly saline water. TiO2 (Degussa P25), TiO2 (Anatase), TiO2 (Rutile), TiO2 (Mesoporous) and ZnO dispersions were used as catalysts employing a medium pressure mercury lamp. The effect of platinum loading on P25 and zinc oxide was also investigated. The zinc oxide with 0.3% platinum loading was the most efficient catalyst. The preferred medium for the degradation of HA using ZnO is alkaline, whereas for TiO2 it is acidic. In addition, a comparative study of HA decomposition in artificial seawater (ASW) and natural seawater (NSW) is reported, and the surface areas and band gaps of the catalysts employed were also determined. A spectrophotometric method was used to estimate the extent of degradation of HA. (C) 2003 Elsevier Science B.V. All rights reserved.

Photocatalytic degradation of humic acid in saline waters. Part 1. Artificial seawater: influence of TiO2, temperature, pH, and air-flow

We report the first systematic study on the photocatalytic oxidation of humic acid (HA) in artificial seawater (ASW). TiO2 (Degussa P25) dispersions were used as the catalyst with irradiation from a medium-pressure mercury lamp. The optimum quantity of catalyst was found to be between 2 and 2.5 g l(-1); whiled the decomposition was fastest at low pH values (pH 4.5 in the range examined), and the optimum air-flow, using an immersion well reactor with a capacity of 400 ml, was 850 ml min(-1). Reactivity increased with air-flow up to this figure, above which foaming prevented operation of the reactor. Using pure. oxygen, an optimal flow rate was observed at 300 nil min(-1), above which reactivity remains essentially constant. Following treatment for 1 h, low-salinity water (2700 mg l(-1)) was completely mineralised, whereas ASW (46000 mg l(-1)) had traces of HA remaining. These effects are interpreted and kinetic data presented. To avoid problems of precipitation due to change of ionic strength humic substances were prepared directly in ASW, and the effects of ASW on catalyst suspension and precipitation have been taken into account. The Langmuir-Hinshelwood kinetic model has been shown to be followed only approximately for the catalytic oxidation of HA in ASW. The activation energy for the reaction derived from an Arrhenius treatment was 17 ( +/-0.6) kJ mol(-1). (C) 2003 Elsevier Science Ltd. All rights reserved.