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.

Plant roots release phospholipid surfactants that modify the physical and chemical properties of soil

Plant root mucilages contain powerful surfactants that will alter the interaction of soil solids with water and ions, and the rates of microbial processes. The lipid composition of maize, lupin and wheat root mucilages was analysed by thin layer chromatography and gas chromatography-mass spectrometry. A commercially available phosphatidylcholine (lecithin), chemically similar to the phospholipid surfactants identified in the mucilages, was then used to evaluate its effects on selected soil properties. The lipids found in the mucilages were principally phosphatidylcholines, composed mainly of saturated fatty acids, in contrast to the lipids extracted from root tissues. In soil at low tension, lecithin reduced the water content at any particular tension by as much as 10 and 50% in soil and acid-washed sand, respectively. Lecithin decreased the amount of phosphate adsorption in soil and increased the phosphate concentration in solution by 10%. The surfactant also reduced net rates of ammonium consumption and nitrate production in soil. These experiments provide the first evidence we are aware of that plant-released surfactants will significantly modify the biophysical environment of the rhizosphere.

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.

Promoting microbial immobilization of soil nitrogen during restoration of abandoned agricultural fields by organic additions

Application of organic materials to soils to enhance N immobilization into microbial biomass, thereby reducing inorganic N concentrations, was studied as a management option to accelerate the reestablishment of the native vegetation on abandoned arable fields on sandy soils the Kiskunsag National Park, Hungary. Sucrose and sawdust were used at three different topographic sites over 4 years. N availability and extractable inorganic N concentrations were significantly reduced in all sites. Soil microbial biomass C and microbial biomass N increased significantly following C additions, but the microbial C to microbial N ratio remained unaffected. It is concluded that the combined application of the rapidly utilized C source (sucrose) promoted N immobilization, whereas the addition of the slowly utilized C source (sawdust) maintained the elevated microbial biomass C and microbial biomass N in the field.

The diurnal course of soil moisture as measured by various dielectric sensors: Effects of soil temperature and the implications for evaporation estimates

Soil moisture content, theta, of a bare and vegetated UK gravelly sandy loam soil (in situ and repacked in small lysimeters) was measured using various dielectric instruments (single-sensor ThetaProbes, multi-sensor Profile Probes, and Aquaflex Sensors), at depths ranging between 0.03 and I m, during the summers of 2001 (in situ soil) and 2002 (mini-lysimeters). Half-hourly values of evaporation, E, were calculated from diurnal changes in total soil profile water content, using the soil water balance equation. For the bare soil field, Profile Probes and ML2x ThetaProbes indicated a diurnal course of theta that did not concur with typical soil physical observations: surface layer soil moisture content increased from early morning until about midday, after which theta declined, generally until the early evening. The unexpected course of theta was positively correlated to soil temperature, T-s, also at deeper depths. Aquaflex and ML1 ThetaProbe (older models) outputs, however, reflected common observations: 0 increased slightly during the night (capillary rise) and decreased from the morning until late afternoon (as a result of evaporation). For the vegetated plot, the spurious diurnal theta fluctuations were less obvious, because canopy shading resulted in lower amplitudes of T-s. The unrealistic theta profiles measured for the bare and vegetated field sites caused diurnal estimates of E to attain downward daytime and upward night-time values. In the mini-lysimeters, at medium to high moisture contents, theta values measured by (ML2x) ThetaProbes followed a relatively realistic course, and predictions of E from diurnal changes in vertically integrated theta generally compared well with lysimeter estimates of E. However, time courses of theta and E became comparable to those observed for the field plots when the soil in the lysimeters reached relatively low values of theta. Attempts to correct measured theta for fluctuations in T, revealed that no generally applicable formula could be derived. (c) 2005 Elsevier B.V. All rights reserved.

A sensitivity analysis of soil moisture retrieval from the t-w microwave emission model

The potential of the τ-ω model for retrieving the volumetric moisture content of bare and vegetated soil from dual polarisation passive microwave data acquired at single and multiple angles is tested. Measurement error and several additional sources of uncertainty will affect the theoretical retrieval accuracy. These include uncertainty in the soil temperature, the vegetation structure and consequently its microwave singlescattering albedo, and uncertainty in soil microwave emissivity based on its roughness. To test the effects of these uncertainties for simple homogeneous scenes, we attempt to retrieve soil moisture from a number of simulated microwave brightness temperature datasets generated using the τ-ω model. The uncertainties for each influence are estimated and applied to curves generated for typical scenarios, and an inverse model used to retrieve the soil moisture content, vegetation optical depth and soil temperature. The effect of each influence on the theoretical soil moisture retrieval limit is explored, the likelihood of each sensor configuration meeting user requirements is assessed, and the most effective means of improving moisture retrieval indicated.

The effect of soil phosphorus on particulate phosphorus in land runoff

Accumulation of surplus phosphorus (P) in the soil and the resulting increased transport of P in land runoff contribute to freshwater eutrophication. The effects of increasing soil P (19–194 mg Olsen-P (OP) kg−1) on the concentrations of particulate P (PP), and sorption properties (Qmax, k and EPCo) of suspended solids (SS) in overland flow from 15 unreplicated field plots established on a dispersive arable soil were measured over three monitoring periods under natural rainfall. Concentrations of PP in plot runoff increased linearly at a rate of 2.6 μg litre−1 per mg OP kg−1 of soil, but this rate was approximately 50% of the rate of increase in dissolved P (< 0.45 μm). Concentrations of SS in runoff were similar across all plots and contained a greater P sorption capacity (mean + 57%) than the soil because of enrichment with fine silt and clay (0.45–20 μm). As soil P increased, the P enrichment ratio of the SS declined exponentially, and the values of P saturation (Psat; 15–42%) and equilibrium P concentration (EPCo; 0.7–5.5 mg litre−1) in the SS fell within narrower ranges compared with the soils (6–74% and 0.1–10 mg litre−1, respectively). When OP was < 100 mg kg−1, Psat and EPCo values in the SS were smaller than those in the soil and vice-versa, suggesting that eroding particles from soils with both average and high P fertility would release P on entering the local (Rosemaund) stream. Increasing soil OP from average to high P fertility increased the P content of the SS by approximately 10%, but had no significant (P > 0.05) effect on the Psat, or EPCo, of the SS. Management options to reduce soil P status as a means of reducing P losses in land runoff and minimizing eutrophication risk may therefore have more limited effect than is currently assumed in catchment management.