The multilayer model of soil mineral–organic interfaces—a review

Association of organic matter (OM) with minerals is an important pathway in the formation of stable OM in soil. While the importance of mineral–organic associations (MOA) in regulating soil carbon cycling has been rigorously demonstrated by empirical evidence, knowledge about the molecular‐scale arrangement of OM at mineral surfaces is still lacking. Such knowledge is urgently needed to disentangle the mechanisms of long‐term storage of soil OM. Based on indirect observations regarding the formation, composition, and structure of MOA, a conceptual multilayer model was proposed by Kleber et al. in 2007 to foster debate and help elucidating the structure and reactivity of MOA. According to this model, the associated OM at mineral surfaces is discrete and self‐organized into a multilayer structure. In this review, we aim to collect and evaluate existing studies that used this model to explain biogeochemical processes at mineral–organic interfaces, and based on this, assess the applicability of the model. The multilayer model has seen extensive adoption within soil science and related fields. In general, existing studies either support the concept of a patchy distribution of adsorbed OM on mineral surfaces or advocate that OM can be coprecipitated with nanosized poorly crystalline minerals or hydrolysable metals. However, the evidence for the patchy distribution of adsorbed OM cannot support the multilayer model on its own. There is little consensus about the role of N‐rich OM in forming the contact zone according to the multilayer model but surface conditioning by different classes of organic compounds appears to be an essential factor for the overall adsorption of OM. Nevertheless, large uncertainty still remains with respect to multilayer‐like organization of MOA. By taking advantage of recent developments in surface analytical sciences and computational chemistry, a rigid experimental testing of the multilayer model at the molecular level is still required and awaits to be integrated into improved concepts of MOA formation and OM stabilization.     

ECOWAT—A model for ecosystem evapotranspiration estimation

In recent years, the availability of near real-time and forecast standardized reference evapotranspiration (E₀) has increased dramatically. Use of the E₀ information in conjunction with calibration coefficients that adjust for differences between the vegetation and the reference surface provides a method to greatly improve the estimates of actual evapotranspiration (E_a) from landscapes (or ecosystems). Difficulties in estimating evapotranspiration (ET) of well-watered vegetation in an ecosystem depend on local advection and edge effects, wide variations in radiation resulting from undulating terrain, wind blockage or funnelling, and differences in temperature due to spatial variation in radiation, wind, etc. Estimating the ET of an ecosystem that is water stressed is even further complicated because of stomatal closure and reduced transpiration. The Ecosystem Water Program (ECOWAT) was developed to help improve estimates of E_a of ecosystems by accounting for microclimate, vegetation type, plant density, and water stress. The first step in estimating E_a is to calculate E₀ using monthly climate data from one representative weather station in the study area. Then, local microclimate data are used to determine a standardized reference evapotranspiration for the local microclimate (E_m). The ratio K_m = E_m/E₀ is calculated and applied as a microclimate correction factor to estimate E_m. The product of E_m and a vegetation coefficient (K_v = E_v/E_m) is used to estimate the evapotranspiration of the ecosystem vegetation (E_v) under well-watered conditions with a full-canopy cover within the same microclimate. Next, a coefficient for plant density (K_d), which is based on the percentage ground cover, is used to adjust the full-canopy E_v to the evapotranspiration of a sparse canopy from a well-watered ecosystem (E_w). A stress (K_s) coefficient, which varies between 1.0 with no stress to 0.0 with full stress, is determined as a function of available water in the root zone. The predicted actual ecosystem evapotranspiration (E_p) is estimated as E_p = E_w × K_s. In this paper, we present how the ECOWAT model works and how it performs when the predicted actual evapotranspiration (E_p) is compared with measured actual evapotranspiration (E_a) collected in several Mediterranean ecosystems (three in Italy and two in California) over a number of years. The potential use of ECOWAT in integrated fire danger systems is discussed.     

Integrating socio‐economic and biophysical models: revision of a land‐use allocation model

Integration of large‐area, economically driven macro‐models and small‐area, biophysically based models in the Canadian agricultural sector was described recently in the development of a land‐use allocation model (LUAM). We have since developed and integrated an improved methodology for allocating crop area changes generated for large areas by the Canadian Regional Agricultural Model (CRAM) to much smaller Soil Landscapes of Canada (SLC) polygons. Validation of outputs showed considerable improvement. The new coefficients of determination (R²) between simulated and actual data, with previous values in brackets, were 0.69 for fodder corn (0.54), 0.88 for wheat (0.62), 0.77 for hay (0.26), 0.54 for alfalfa (not previously reported), 0.88 for soya bean (0.26) and 0.86 for grain corn (0.22). The best result was obtained for soya bean, with a normalized root mean square error (NRMSE) of 0.31%, and the poorest for alfalfa, with NRMSE = 17.34%.     

The pore–solid fractal model of soil density scaling

We have developed the fractal approach to modelling variations in soil bulk density and porosity with scale of measurement or sample size. A new expression is derived for each quantity based on the pore–solid fractal (PSF) model of soil structure. This new general expression covers a range of fractal media and accommodates existing fractal models as special cases. Model outputs cover a range of scaling behaviour expressed in terms of monotonic functions, from increasing density and decreasing porosity, through constant porosity and density to decreasing density and increasing porosity with increasing scale of measurement. We demonstrate the link between this new model for the scaling of porosity and bulk density and the water retention model for the PSF. The model for scaling bulk density is fitted to data on aggregate bulk density and shown to yield good fits describing bulk density decreasing with increasing aggregate size. Porosity scaling is also inferred from the fitting of water retention data. Inferred porosities from different fittings are shown to follow decreasing, scale‐invariant and increasing values with decreasing size of structural unit, and these theoretical results emphasize the need for further experimental investigation on the basic issue of density scaling in soil science.     

Integrating socio‐economic and biophysical assessments using a land use allocation model

This work is devoted to bridging the gap between large‐area, economically driven macromodels such as the Canadian Regional Agriculture Model (CRAM) and small‐area biophysically based process models used in environmental assessments through the development of a Land Use Allocation Model (LUAM). LUAM is designed to enable environmental assessments of economic scenarios to be conducted by allocating crop area changes predicted for large areas by CRAM to much smaller Soil Landscapes of Canada (SLC) polygons through an optimization method based on land capability, relative crop productivity and current land use. To develop the procedures, we used linear programming to optimize crop production for large areas under current commodity prices and land productivity ratings and then allocated the results to much smaller soil‐landscape polygons based on land capability. To assess the validity of our prototype LUAM, we compared the predicted crop areas with actual crop data from the Census of Agriculture using the method of cumulative residuals (MCR). We concluded that this version of the LUAM model can predict the location of land use to some extent, but requires further refinement. The potential for further development of LUAM using the Land Suitability Rating System (LSRS) is discussed.     

A semi‐analytical model for solute transport in layered dual‐porosity media

The vulnerability of groundwater from chemical leaching through soil is a concern at some locations. Because measurements are laborious, time‐consuming, and expensive, simulation models are frequently used to assess leaching risks. But the significance of simulated solute movement through a layered soil is questionable if vertical homogeneity of physical soil properties has been assumed. In the present study, a semi‐analytical model for solute leaching in soils is presented. The model is relatively simple, but it does account for soil layers having different physical properties. The model includes the mobile‐immobile model (MIM) to describe one‐dimensional (1‐D) nonequilibrium, transient solute transport under steady‐state flow conditions. The MIM is rewritten as a second‐order differential equation and solved by a numerical scheme. Differing from fully analytical or fully numerical solutions, the new approach solves the differential equation numerically with respect to time and analytically with respect to distance. Numerical experiments for a single layered soil profile show that the semi‐analytical solution (SA‐MIM) is numerically stable for a wide range of parameter values. The accuracy of SA‐MIM predictions is comparable to that of analytical solutions. Numerical experiments for a multilayered profile indicate that the model correctly predicts effluent curves from finite layered soil profiles under steady‐state flow conditions. The SA‐MIM simulations with typical parameter values suggest that neglecting vertical heterogeneity of flow paths in a layered soil can lead to inaccurate prediction of soil‐solute leaching. The quality of predictions is generally improved if parameter estimates for the different soil layers are considered. However, the mobile‐immobile‐parameter estimates obtained in a number of previous studies may not be transferable to a field situation that is characterized by a slow and steady flow of water. Further field experiments to determine mobile‐immobile parameters under such conditions are desirable.     

Remote-sensing data as an alternative input for the ‘STREAM’ runoff model

Water erosion of cropland constitutes an issue for natural environments along runoff flowpaths due to property damage by soil-laden water and the associated transfer of nutrients and pesticides. In the Pays de Caux region of northwestern France, the silty soils with crusting properties induce a high risk of runoff and erosion. Changes in agricultural practices, land use and landscape patterns appear to have increased the occurrence of erosion and mud flows over the past few decades.A runoff and erosion model called STREAM, applicable to single rainfall events at catchment scale, has been developed to simulate the impacts of land-use modifications. The model takes into account processes that degrade surface states when calculating infiltration rates, as well as agricultural aspects when computing the runoff circulation network. STREAM is based on an expert-system approach that focuses on the dominant processes whilst having only a few input parameters: three of these are used to determine the runoff circulation network, and the other four to calculate infiltration rates. Input nevertheless requires field observations, which restricts application of the model to small catchments.Satellite data covering large areas is considered as an alternative input for such a model, the main objectives being to adapt STREAM accordingly, and to compare the obtained results with field data. In view of previous work involving the extraction and validation of roughness indices using RADARSAT data, this study is based on RADARSAT and LANDSAT TM data collected during the winter of 1998.After adaptation to receive remote-sensing data, the resulting STREAM-TED model requires less input, namely (1) slope and orientation, (2) land-use classification from optical remote-sensing data, (3) roughness indices from radar remote-sensing data, and (4) previous rainfall.Runoff volumes at a gauged catchment outlet (Bourville in Upper Normandy, France) are simulated by four successive versions of the model ranging from the original STREAM to the adapted STREAM-TED. Predictions of the four versions are compared, and performance of the successive simulations is assessed in relation to measured values and according to five statistical indices.Predictions of runoff volume at the catchment outlet using STREAM-TED are similar to those using the original STREAM model, but with a tendency towards overestimation. The final STREAM-TED version is capable of identifying areas sensitive to runoff within a group of catchments and could be used as a planning decision tool in the implementation of conservation practices.     

Acute and chronic isopod testing using tropical Porcellionides pruinosus and three model pesticides

An approach for testing acute and chronic ecotoxicological effects of pesticides on isopods in the laboratory is presented. Laboratory cultures of tropical Porcellionides pruinosus were used. The pesticides Benomyl, Carbendazim and lambda-Cyhalothrin served as model chemicals. The toxicity tests were done with five to six concentrations and one untreated control in four replicates containing 10 individuals per vessel. The test was performed at 28 °C, in permanent darkness and it lasted 14 days. Each chemical was mixed in 250 g DW per vessel of OECD artificial, LUFA 2.2 standard, tropical artificial or tropical natural soil in acute tests. Chronic tests were performed using 150 g DW OECD artificial or LUFA 2.2 standard soil. Both adult mortality and number of juveniles showed a high sensitivity of P. pruinosus towards lambda-Cyhalothrin while Carbendazim and Benomyl had a very low and no toxicity, respectively. Further research and optimization of the chronic test design are required.     

A conditional GIS‐interpolation‐based model for mapping soil‐water erosion processes in Lebanon

Soil erosion by water is a major cause of landscape degradation in Mediterranean environments, including Lebanon. This paper proposes a conditional decision‐rule interpolation‐based model to predict the distribution of multiple erosion processes (i.e. sheet, mass and linear) in a representative area of Lebanon from the measured erosion signs in the field (root exposure, earth pillars, soil etching and drift and linear channels). First, erosion proxies were derived from the structural OASIS classification of Landsat thematic mapper (TM) imageries combined with the addition of several thematic erosion maps (slope gradient, aspect and curvature, drainage density, vegetal cover, soil infiltration and erodibility and rock infiltration/movement) under a geographic information systems (GIS) environment. Second, erosion signs were measured in the field, and interpolated by the statistical moments (means and variance) in the defined erosion proxies, thus producing quantitative erosion maps (t ha⁻¹) at a scale of 1:100 000. Seven decision rules were then generated and applied on these maps in order to produce the overall decisive erosion map reflecting all existing erosion processes, that is, equality (ER), dominance (DOR), bimodality (BR), masking (MR), aggravating (AR), dependence (DER) and independence (IR). The produced erosion maps are divided into seven classes ranging between 0 and more than 1·8 t ha⁻¹ for sheet erosion, and 0 and more than 10·5 t ha⁻¹ for mass and linear erosion. They are fairly matching with coincidences values equal to 43 per cent (sheet/linear), 48 per cent (sheet/mass) and 49 per cent (linear/mass). The overall accuracies of these maps were estimated to be 76 per cent (sheet erosion), 78 per cent (mass erosion) and 78·5 per cent (linear erosion). The overall decisive erosion map with 15 classes corresponds well to land management needs. The model used is relatively simple, and may also be applied to other areas. It is particularly useful when GIS database on factors influencing erosion is limited. Copyright © 2007 John Wiley & Sons, Ltd.     

Prediction of model pools for a long‐term experiment using near‐infrared spectroscopy

Fourty‐one soil samples from the “Eternal Rye” long‐term experiment in Halle, Germany, were used to test the usefulness of near‐infrared spectroscopy (NIRS) to differentiate between C derived from C₃ and C₄ plants by using the isotopic signature (δ¹³C) and to predict the pools considered in the Rothamsted Carbon (RothC) model, i.e., decomposable plant material, resistant plant material, microbial biomass, humified organic matter, and inert organic matter. All samples were scanned in the visible‐light and near‐infrared region (400–2500 nm). Cross‐validation equations were developed using the whole spectrum (first to third derivative) and a modified partial least‐square regression method. δ¹³C values and all pools of the RothC model were successfully predicted by NIRS as reflected by RSC values (ratio between standard deviation of the laboratory results and standard error of cross‐validation) ranging from 3.2 to 3.4. Correlations analysis indicated that organic C can be excluded as basis for the successful predictions by NIRS in most cases, i.e., 11 out of 16.     

A simple approach to soil loss prediction: a revised Morgan–Morgan–Finney model

A revised version of the Morgan–Morgan–Finney model for prediction of annual soil loss by water is presented. Changes have been made to the way soil particle detachment by raindrop impact is simulated, which now takes account of plant canopy height and leaf drainage, and a component has been added for soil particle detachment by flow. When tested against the same data set used to validate the original version at the erosion plot scale, predictions made with the revised model gave slopes of a reduced major-axis regression line closer to 1.0 when compared with measured values. The coefficient of efficiency, for sites with measured runoff and soil loss, increased from 0.54 to 0.65. When applied to a new data set for erosion plots in Denmark, Spain, Greece and Nepal, very high coefficients of efficiency of 0.94 for runoff and 0.84 for soil loss were obtained. The revised version was applied to two small catchments by dividing them into land elements and routing annual runoff and sediment production over the land surface from one element to another. The results indicate that, when used in this way, the model provides useful information on the source areas of sediment, sediment delivery to streams and annual sediment yield.     

Simulating infiltration into stony soils with a dual‐porosity model

Soils containing rock fragments are widely distributed in the world. However, literature on the dynamic simulation of water movement in stony soils is scarce. In this paper, a dual‐porosity model was used to simulate water infiltration into soils containing rock fragments. Sensitivity analysis of the dual‐porosity model parameters demonstrates that the increase of rock fragment content clearly decreased infiltration into stony soils. Big stones hampered infiltration more than small stones. Spherical stones accelerated infiltration compared with solid, cylindrical stones and rectangular, slab‐like stones. Numerical analysis was also performed to test and compare a non‐equilibrium dual‐porosity model (NDPM) with an equilibrium dual‐porosity model (EDPM) and an equilibrium single‐pore model (ESPM). Infiltration experiments on disturbed soils were carried out to verify the ability of the NDPM to simulate infiltration into stony soils. Based on hydraulic parameters of soils without rock fragments and mass transfer coefficients obtained independently, the extrapolated cumulative infiltrations calculated by the NDPM were in good agreement with the observed data. Fitted model parameters of the NDPM indicate that rock fragments not only act as a source or sink to affect infiltration but also change the pore structure of the fine earth, apart from reducing the cross‐sectional area for water flow. Though further studies are required to improve the dual‐porosity model, it already describes more characteristics of infiltration into stony soils and explains more phenomena than does the single‐porosity model.     

Repeated annual drought has minor long‐term influence on δ13C and alkane composition of plant and soil in model grassland and heathland ecosystems

As a result of global climate change the incidence of drought conditions in Europe is predicted to increase in the future, which also influences plant resistance. Lipids are important plant constituents that protect plants against drought stress and contribute to the intermediate stable carbon (C) pool in soil. However, the extent to which drought influences lipid cycling in the plant–soil system is unknown and, therefore, it remains questionable how the ecosystem recovers after drought. We focused on plant and soil samples from two different plant communities (temperate grassland and heathland) that had been exposed to 5 years of 4.5–6.0 weeks repeated annual drought. They were sampled one year after the last drought to check the recovery of the plant–soil system. Samples were analyzed for their bulk C, stable C and nitrogen (N) isotope (δ¹³C, δ¹⁵N) and lipid composition. Contrary to our expectation, no strong influence of five years of repeated annual drought was observed for above‐ground biomass, roots and soils in the model ecosystems with respect to elemental (C and N concentrations, C : N ratio) bulk isotope (δ¹³C, δ¹⁵N) composition and the total extractable lipid concentration. Thus, plants did not sustain a significant change in their C and lipid concentration as well as their composition after five years of repeated annual drought. This might be related to the comparatively short drought period related to the overall growth season and provides evidence for recovery of the C and lipid dynamics in temperate grassland and heathland model ecosystems exposed to annual drought.     

Testing the public–private soil data and information sharing model for sustainable soil management outcomes

Soil data form the basis of soil information systems across the globe. Soil information needs, and the questions posed by users, are likely to evolve in response to advances in technology in this era of Big Data. This poses a challenge to the pedological community which is already experiencing a decline in soil knowledge and expertise. With a decrease in soil data collection by governments, it is timely to reconsider how and what soil information should be provided to future users. A public–private partnership is advocated to deliver timely and accessible soil information to users. Two public–private provisioning programs are presented, and advantages and considerations for sharing soil data and information amongst industry, government, research organizations, service providers and land managers for these are discussed. Interoperable, open‐source and agreed soil community standards are used to present soil data and information through spatial web portals with tools for interpretation of soil data for public and private beneficiaries.     

基于B/S模式的机房实验系统的设计与开发

本文从学校实验教学的实际出发,介绍了基于Browser/Server模式的机房实验系统的主要功能、设计思路及其关键技术。前台使用JSP开发功能页面,后台使用SQL Server 2000管理数据信息。     

The Matérn variogram model: Implications for uncertainty propagation and sampling in geostatistical surveys

The Matérn variogram model has been advocated because it is flexible and can represent varied behaviour at small lags. We show how the constraints on the spherical and exponential variogram at short lags ignore a possible source of uncertainty in the variogram and so in kriging surveys, that the Matérn model can describe. Matérn, spherical and exponential variogram models were fitted by maximum likelihood to a set of log₁₀(K) observations made on a regular grid at Broom's Barn Farm, Suffolk, England. The likelihood profiles of the Matérn parameter estimates were asymmetric. Thus the uncertainty of these estimates could only be adequately assessed by a Bayesian approach. The uncertainty of estimated parameters of the Matérn variogram was larger than for the exponential variogram. This is an indication that the assumption of an exponential model limits the behaviour that may be described by the variogram. Thus uncertainty analyses where an exponential variogram is assumed may underestimate the uncertainty of kriged estimates. Bayesian analysis of the kriged estimates of log₁₀(K) at Broom's Barn Farm using the Matérn variogram revealed an observable component of uncertainty due to variogram uncertainty. When an exponential variogram model was used, the estimate of this component of uncertainty was negligible. The Matérn variogram should therefore be used rather than the exponential model when assessing the adequacy of a variogram estimate. A method of designing sample schemes which is suitable for both estimating a Matérn variogram and interpolation is suggested.     

番茄的结构-功能模型Ⅱ：基于器官水平的功能模型与验证研究

建立了番茄动态生长的功能模型,从个体和器官的角度,研究生物量在植物体内的生产和分配规律、器官的动态生长规则。模型根据蒸腾作用计算物质的生产;根据节间、叶柄、叶片和果实等器官的汇强和扩展规律对物质进行分配;根据与物质量的动态关系计算各器官的几何尺寸;利用试验数据对模型参数进行估计。通过对参数进行比较和分析得出它们对各器官生长的影响程度和器官本身的扩展规律。并对模型输出与测量数据的拟合程度进行了残差分析,验证了模型的合理性和有效性。