Preparation of consistent soil data sets for modelling purposes: Secondary SOTER data for four case study areas

The common GIS-based approach to regional analyses of soil organic carbon (SOC) stocks and changes is to define geographic layers for which unique sets of driving variables are derived, which include land use, climate, and soils. These GIS layers, with their associated attribute data, can then be fed into a range of empirical and dynamic models. Common methodologies for collating and formatting regional data sets on land use, climate, and soils were adopted for the project Assessment of Soil Organic Carbon Stocks and Changes at National Scale (GEFSOC). This permitted the development of a uniform protocol for handling the various input for the dynamic GEFSOC Modelling System. Consistent soil data sets for Amazon-Brazil, the Indo-Gangetic Plains (IGP) of India, Jordan and Kenya, the case study areas considered in the GEFSOC project, were prepared using methodologies developed for the World Soils and Terrain Database (SOTER). The approach involved three main stages: (1) compiling new soil geographic and attribute data in SOTER format; (2) using expert estimates and common sense to fill selected gaps in the measured or primary data; (3) using a scheme of taxonomy-based pedotransfer rules and expert-rules to derive soil parameter estimates for similar soil units with missing soil analytical data. The most appropriate approach varied from country to country, depending largely on the overall accessibility and quality of the primary soil data available in the case study areas. The secondary SOTER data sets discussed here are appropriate for a wide range of environmental applications at national scale. These include agro-ecological zoning, land evaluation, modelling of soil C stocks and changes, and studies of soil vulnerability to pollution. Estimates of national-scale stocks of SOC, calculated using SOTER methods, are presented as a first example of database application. Independent estimates of SOC stocks are needed to evaluate the outcome of the GEFSOC Modelling System for current conditions of land use and climate. (C) 2007 Elsevier B.V. All rights reserved.

Scale-invariant moving finite elements for nonlinear partial differential equations in two dimensions

A scale-invariant moving finite element method is proposed for the adaptive solution of nonlinear partial differential equations. The mesh movement is based on a finite element discretisation of a scale-invariant conservation principle incorporating a monitor function, while the time discretisation of the resulting system of ordinary differential equations is carried out using a scale-invariant time-stepping which yields uniform local accuracy in time. The accuracy and reliability of the algorithm are successfully tested against exact self-similar solutions where available, and otherwise against a state-of-the-art h-refinement scheme for solutions of a two-dimensional porous medium equation problem with a moving boundary. The monitor functions used are the dependent variable and a monitor related to the surface area of the solution manifold. (c) 2005 IMACS. Published by Elsevier B.V. All rights reserved.

Ecological and life-history traits predict bee species responses to environmental disturbances

The ability to predict the responses of ecological communities and individual species to human-induced environmental change remains a key issue for ecologists and conservation managers alike. Responses are often variable among species within groups making general predictions difficult. One option is to include ecological trait information that might help to disentangle patterns of response and also provide greater understanding of how particular traits link whole clades to their environment. Although this ‘‘trait-guild” approach has been used for single disturbances, the importance of particular traits on general responses to multiple disturbances has not been explored. We used a mixed model analysis of 19 data sets from throughout the world to test the effect of ecological and life-history traits on the responses of bee species to different types of anthropogenic environmental change. These changes included habitat loss, fragmentation, agricultural intensification, pesticides and fire. Individual traits significantly affected bee species responses to different disturbances and several traits were broadly predictive among multiple disturbances. The location of nests – above vs. below ground – significantly affected response to habitat loss, agricultural intensification, tillage regime (within agriculture) and fire. Species that nested above ground were on average more negatively affected by isolation from natural habitat and intensive agricultural land use than were species nesting below ground. In contrast below-ground-nesting species were more negatively affected by tilling than were above-ground nesters. The response of different nesting guilds to fire depended on the time since the burn. Social bee species were more strongly affected by isolation from natural habitat and pesticides than were solitary bee species. Surprisingly, body size did not consistently affect species responses, despite its importance in determining many aspects of individuals’ interaction with their environment. Although synergistic interactions among traits remain to be explored, individual traits can be useful in predicting and understanding responses of related species to global change.

Nitrogen recycling through the gut and the nitrogen economy of ruminants: An asynchronous symbiosis

The extensive development of the ruminant forestomach sets apart their N economy from that of nonruminants in a number of respects. Extensive pregastric fermentation alters the profile of protein reaching the small intestine, largely through the transformation of nitrogenous compounds into microbial protein. This process is fueled primarily by carbohydrate fermentation and includes extensive recycling of N between the body and gut lumen pools. Nitrogen recycling occurs via blood and gut lumen exchanges of urea and NH3, as well as endogenous gut and secretory N entry into the gut lumen, and the subsequent digestion and absorption of microbial and endogenous protein. Factors controlling urea transfer to the gut from blood, including the contributions of urea transporters, remain equivocal. Ammonia produced by microbial degradation of urea and dietary and endogenous AA is utilized by microbial fermentation or absorbed and primarily converted to urea. Therefore, microbial growth and carbohydrate fermentation affect the extent of NH3 absorption and urea N recycling and excretion. The extensive recycling of N to the rumen represents an evolutionary advantage of the ruminant in terms of absorbable protein supply during periods of dietary protein deficiency, or asynchronous carbohydrate and protein supply, but incurs a cost of greater N intakes, especially in terms of excess N excretion. Efforts to improve the efficiency of N utilization in ruminants by synchronizing fermentable energy and N availability have generally met with limited success with regards to production responses. In contrast, imposing asynchrony through oscillating dietary protein concentration, or infrequent supplementation, surprisingly has not negatively affected production responses unless the frequency of supplementation is less than once every 3 d. In some cases, oscillation of dietary protein concentration has improved N retention compared with animals fed an equal amount of dietary protein on a daily basis. This may reflect benefits of Orn cycle adaptations and sustained recycling of urea to the gut. The microbial symbiosis of the ruminant is inherently adaptable to asynchronous N and energy supply. Recycling of urea to the gut buffers the effect of irregular dietary N supply such that intuitive benefits of rumen synchrony in terms of the efficiency of N utilization are typically not observed in practice.

PECAM-1 expression and activity negatively regulate multiple platelet signaling pathways

Platelet endothelial cell adhesion molecule-1 (PECAM-1) inhibits platelet response to collagen and may also inhibit two other major platelet agonists ADP and thrombin although this has been less well explored. We hypothesized that the combined effect of inhibiting these three platelet activating pathways may act to significantly inhibit thrombus formation. We demonstrate a negative relationship between PECAM-1 surface expression and platelet response to cross-linked collagen related peptide (CRP-XL) and ADP, and an inhibitory effect of PECAM-1 clustering on platelet response to CRP-XL, ADP and thrombin. This combined inhibition of multiple signaling pathways results in a marked reduction in thrombus formation. (C) 2009 Federation of European Biochemical Societies. Published by Elsevier B. V. All rights reserved.

Are the spatial patterns of weeds scale-invariant?

In previous empirical and modelling studies of rare species and weeds, evidence of fractal behaviour has been found. We propose that weeds in modern agricultural systems may be managed close to critical population dynamic thresholds, below which their rates of increase will be negative and where scale-invariance may be expected as a consequence. We collected detailed spatial data on five contrasting species over a period of three years in a primarily arable field. Counts in 20×20 cm contiguous quadrats, 225,000 in 1998 and 84,375 thereafter, could be re-structured into a wide range of larger quadrat sizes. These were analysed using three methods based on correlation sum, incidence and conditional incidence. We found non-trivial scale invariance for species occurring at low mean densities and where they were strongly aggregated. The fact that the scale-invariance was not found for widespread species occurring at higher densities suggests that the scaling in agricultural weed populations may, indeed, be related to critical phenomena.

Copper(II) complexes of tetradentate N2S2 donor sets: synthesis, crystal structure characterization and reactivity

Two mononuclear and one dinuclear copper(II) complexes, containing neutral tetradentate NSSN type ligands, of formulation [Cu-II(L-1)Cl]ClO4 (1), [Cu-II(L-2)Cl]ClO4 (2) and [Cu-2(II)(L-3)(2)Cl-2](ClO4)(2) (3) were synthesized and isolated in pure form [where L-1 = 1,2-bis(2-pyridylmethylthio)ethane, L-2 = 1,3-bis(2-pyridylmethylthio)propane and L-3 = 1,4-bis(2-pyridylmethylthio)butane]. All these green colored copper(II) complexes were characterized by physicochemical and spectroscopic methods. The dinuclear copper(II) complex 3 changed to a colorless dinuclear copper(I) species of formula [Cu-2(1)(L-3)(2)](ClO4)(2),0.5H(2)O (4) in dimethylformamide even in the presence of air at ambient temperature, while complexes I and 2 showed no change under similar conditions. The solid-state structures of complexes 1, 2 and 4 were established by X-ray crystallography. The geometry about the copper in complexes 1 and 2 is trigonal bipyramidal whereas the coordination environment about the copper(I) in dinuclear complex 4 is distorted tetrahedral. (C) 2008 Elsevier Ltd. All rights reserved.

A kernel-based two-class classifier for imbalanced data sets

Many kernel classifier construction algorithms adopt classification accuracy as performance metrics in model evaluation. Moreover, equal weighting is often applied to each data sample in parameter estimation. These modeling practices often become problematic if the data sets are imbalanced. We present a kernel classifier construction algorithm using orthogonal forward selection (OFS) in order to optimize the model generalization for imbalanced two-class data sets. This kernel classifier identification algorithm is based on a new regularized orthogonal weighted least squares (ROWLS) estimator and the model selection criterion of maximal leave-one-out area under curve (LOO-AUC) of the receiver operating characteristics (ROCs). It is shown that, owing to the orthogonalization procedure, the LOO-AUC can be calculated via an analytic formula based on the new regularized orthogonal weighted least squares parameter estimator, without actually splitting the estimation data set. The proposed algorithm can achieve minimal computational expense via a set of forward recursive updating formula in searching model terms with maximal incremental LOO-AUC value. Numerical examples are used to demonstrate the efficacy of the algorithm.

Spectrally-invariant behavior of zenith radiance around cloud edges simulated by radiative transfer

In a previous paper, we discovered a surprising spectrally-invariant relationship in shortwave spectrometer observations taken by the Atmospheric Radiation Measurement (ARM) program. The relationship suggests that the shortwave spectrum near cloud edges can be determined by a linear combination of zenith radiance spectra of the cloudy and clear regions. Here, using radiative transfer simulations, we study the sensitivity of this relationship to the properties of aerosols and clouds, to the underlying surface type, and to the finite field-of-view (FOV) of the spectrometer. Overall, the relationship is mostly sensitive to cloud properties and has little sensitivity to other factors. At visible wavelengths, the relationship primarily depends on cloud optical depth regardless of cloud phase function, thermodynamic phase and drop size. At water-absorbing wavelengths, the slope of the relationship depends primarily on cloud optical depth; the intercept, by contrast, depends primarily on cloud absorbing and scattering properties, suggesting a new retrieval method for cloud drop effective radius. These results suggest that the spectrally-invariant relationship can be used to infer cloud properties near cloud edges even with insufficient or no knowledge about spectral surface albedo and aerosol properties.