Spatial Assessment of Erosion and its Impact on Soil Fertility in the Tajik Foothills

Efficient planning of soil conservation measures requires, first, to understand the impact of soil erosion on soil fertility with regard to local land cover classes; and second, to identify hot spots of soil erosion and bright spots of soil conservation in a spatially explicit manner. Soil organic carbon (SOC) is an important indicator of soil fertility. The aim of this study was to conduct a spatial assessment of erosion and its impact on SOC for specific land cover classes. Input data consisted of extensive ground truth, a digital elevation model and Landsat 7 imagery from two different seasons. Soil spectral reflectance readings were taken from soil samples in the laboratory and calibrated with results of SOC chemical analysis using regression tree modelling. The resulting model statistics for soil degradation assessments are promising (R2=0.71, RMSEV=0.32). Since the area includes rugged terrain and small agricultural plots, the decision tree models allowed mapping of land cover classes, soil erosion incidence and SOC content classes at an acceptable level of accuracy for preliminary studies. The various datasets were linked in the hot-bright spot matrix, which was developed to combine soil erosion incidence information and SOC content levels (for uniform land cover classes) in a scatter plot. The quarters of the plot show different stages of degradation, from well conserved land to hot spots of soil degradation. The approach helps to gain a better understanding of the impact of soil erosion on soil fertility and to identify hot and bright spots in a spatially explicit manner. The results show distinctly lower SOC content levels on large parts of the test areas, where annual crop cultivation was dominant in the 1990s and where cultivation has now been abandoned. On the other hand, there are strong indications that afforestations and fruit orchards established in the 1980s have been successful in conserving soil resources.

Utilizing Gaussian-Schell model beams to mitigate atmospheric turbulence in free space optical communications / by Kyle R. Drexler.

Turbulence affects traditional free space optical communication by causing speckle to appear in the received beam profile. This occurs due to changes in the refractive index of the atmosphere that are caused by fluctuations in temperature and pressure, resulting in an inhomogeneous medium. The Gaussian-Schell model of partial coherence has been suggested as a means of mitigating these atmospheric inhomogeneities on the transmission side. This dissertation analyzed the Gaussian-Schell model of partial coherence by verifying the Gaussian-Schell model in the far-field, investigated the number of independent phase control screens necessary to approach the ideal Gaussian-Schell model, and showed experimentally that the Gaussian-Schell model of partial coherence is achievable in the far-field using a liquid crystal spatial light modulator. A method for optimizing the statistical properties of the Gaussian-Schell model was developed to maximize the coherence of the field while ensuring that it does not exhibit the same statistics as a fully coherent source. Finally a technique to estimate the minimum spatial resolution necessary in a spatial light modulator was developed to effectively propagate the Gaussian-Schell model through a range of atmospheric turbulence strengths. This work showed that regardless of turbulence strength or receiver aperture, transmitting the Gaussian-Schell model of partial coherence instead of a fully coherent source will yield a reduction in the intensity fluctuations of the received field. By measuring the variance of the intensity fluctuations and the received mean, it is shown through the scintillation index that using the Gaussian-Schell model of partial coherence is a simple and straight forward method to mitigate atmospheric turbulence instead of traditional adaptive optics in free space optical communications.

Multivariate modelling of responses to conditional items: New possibilities for latent class analysis

Questionnaire data may contain missing values because certain questions do not apply to all respondents. For instance, questions addressing particular attributes of a symptom, such as frequency, triggers or seasonality, are only applicable to those who have experienced the symptom, while for those who have not, responses to these items will be missing. This missing information does not fall into the category 'missing by design', rather the features of interest do not exist and cannot be measured regardless of survey design. Analysis of responses to such conditional items is therefore typically restricted to the subpopulation in which they apply. This article is concerned with joint multivariate modelling of responses to both unconditional and conditional items without restricting the analysis to this subpopulation. Such an approach is of interest when the distributions of both types of responses are thought to be determined by common parameters affecting the whole population. By integrating the conditional item structure into the model, inference can be based both on unconditional data from the entire population and on conditional data from subjects for whom they exist. This approach opens new possibilities for multivariate analysis of such data. We apply this approach to latent class modelling and provide an example using data on respiratory symptoms (wheeze and cough) in children. Conditional data structures such as that considered here are common in medical research settings and, although our focus is on latent class models, the approach can be applied to other multivariate models.

The cranial bone window model: studying angiogenesis of primary and secondary bone tumors by intravital microscopy

The successful treatment of primary and secondary bone tumors in a huge number of cases remains one of the major unsolved challenges in modern medicine. Malignant primary bone tumor growth predominantly occurs in younger people, whereas older people predominantly suffer from secondary bone tumors since up to 85% of the most frequently occurring malignant solid tumors, such as lung, mammary, and prostate carcinomas, metastasize into the bone. It is well known that a tumor's course may be altered by its surrounding tissue. For this reason, reported here is the protocol for the surgical preparation of a cranial bone window in mice as well as the method to implant tumors in this bone window for further investigations of angiogenesis and other microcirculatory parameters in orthotopically growing primary or secondary bone tumors using intravital microscopy. Intravital microscopy represents an internationally accepted and sophisticated experimental method to study angiogenesis, microcirculation, and many other parameters in a wide variety of neoplastic and nonneoplastic tissues. Since most physiologic and pathophysiologic processes are active and dynamic events, one of the major strengths of chronic animal models using intravital microscopy is the possibility of monitoring the regions of interest in vivo continuously up to several weeks with high spatial and temporal resolution. In addition, after the termination of experiments, tissue samples can be excised easily and further examined by various in vitro methods such as histology, immunohistochemistry, and molecular biology.

Visualization of alveolar recruitment in a porcine model of unilateral lung lavage using 3He-MRI

BACKGROUND: In the acute respiratory distress syndrome potentially recruitable lung volume is currently discussed. (3)He-magnetic resonance imaging ((3)He-MRI) offers the possibility to visualize alveolar recruitment directly. METHODS: With the approval of the state animal care committee, unilateral lung damage was induced in seven anesthetized pigs by saline lavage of the right lungs. The left lung served as an intraindividual control (healthy lung). Unilateral lung damage was confirmed by conventional proton MRI and spiral-CT scanning. The total aerated lung volume was determined both at a positive end-expiratory pressure (PEEP) of 0 and 10 mbar from three-dimensionally reconstructed (3)He images, both for healthy and damaged lungs. The fractional increase of aerated volume in damaged and healthy lungs, followed by a PEEP increase from 0 to 10 mbar, was compared. RESULTS: Aerated gas space was visualized with a high spatial resolution in the three-dimensionally reconstructed (3)He-MR images, and aeration defects in the lavaged lung matched the regional distribution of atelectasis in proton MRI. After recruitment and PEEP increase, the aerated volume increased significantly both in healthy lungs from 415 ml [270-445] (median [min-max]) to 481 ml [347-523] and in lavaged lungs from 264 ml [71-424] to 424 ml [129-520]. The fractional increase in lavaged lungs was significantly larger than that in healthy lungs (healthy: 17% [11-38] vs. lavage: 42% [14-90] (P=0.031). CONCLUSION: The (3)He-MRI signal might offer an experimental approach to discriminate atelectatic vs. poor aerated lung areas in a lung damage animal model. Our results confirm the presence of potential recruitable lung volume by either alveolar collapse or alveolar flooding, in accordance with previous reports by computed tomography.

Assessing the Relevance of Anomie Theory for Explaining Spatial Variation in Lethal Criminal Violence: An Aggregate-Level Analysis of Homicide within the United States

One of the most influential statements in the anomie theory tradition has been Merton’s argument that the volume of instrumental property crime should be higher where there is a greater imbalance between the degree of commitment to monetary success goals and the degree of commitment to legitimate means of pursing such goals. Contemporary anomie theories stimulated by Merton’s perspective, most notably Messner and Rosenfeld’s institutional anomie theory, have expanded the scope conditions by emphasizing lethal criminal violence as an outcome to which anomie theory is highly relevant, and virtually all contemporary empirical studies have focused on applying the perspective to explaining spatial variation in homicide rates. In the present paper, we argue that current explications of Merton’s theory and IAT have not adequately conveyed the relevance of the core features of the anomie perspective to lethal violence. We propose an expanded anomie model in which an unbalanced pecuniary value system – the core causal variable in Merton’s theory and IAT – translates into higher levels of homicide primarily in indirect ways by increasing levels of firearm prevalence, drug market activity, and property crime, and by enhancing the degree to which these factors stimulate lethal outcomes. Using aggregate-level data collected during the mid-to-late 1970s for a sample of relatively large social aggregates within the U.S., we find a significant effect on homicide rates of an interaction term reflecting high levels of commitment to monetary success goals and low levels of commitment to legitimate means. Virtually all of this effect is accounted for by higher levels of property crime and drug market activity that occur in areas with an unbalanced pecuniary value system. Our analysis also reveals that property crime is more apt to lead to homicide under conditions of high levels of structural disadvantage. These and other findings underscore the potential value of elaborating the anomie perspective to explicitly account for lethal violence.

Reanalysis-driven climate simulation over CORDEX North America domain using the Canadian Regional Climate Model, version 5: model performance evaluation

The performance of reanalysis-driven Canadian Regional Climate Model, version 5 (CRCM5) in reproducing the present climate over the North American COordinated Regional climate Downscaling EXperiment domain for the 1989–2008 period has been assessed in comparison with several observation-based datasets. The model reproduces satisfactorily the near-surface temperature and precipitation characteristics over most part of North America. Coastal and mountainous zones remain problematic: a cold bias (2–6 °C) prevails over Rocky Mountains in summertime and all year-round over Mexico; winter precipitation in mountainous coastal regions is overestimated. The precipitation patterns related to the North American Monsoon are well reproduced, except on its northern limit. The spatial and temporal structure of the Great Plains Low-Level Jet is well reproduced by the model; however, the night-time precipitation maximum in the jet area is underestimated. The performance of CRCM5 was assessed against earlier CRCM versions and other RCMs. CRCM5 is shown to have been substantially improved compared to CRCM3 and CRCM4 in terms of seasonal mean statistics, and to be comparable to other modern RCMs.

The Role of Online Platforms for Media Markets – Two‐Dimensional Spatial Competition in a Two‐Sided Market

We analyze the market for online and offline media in a model of two-dimensional spatial competition where media outlets sell content and advertising space. Consumer preferences are distributed along the style and type of news coverage where the distance costs may vary across dimensions. For integrated provision of online and offline platforms we show that entering the online market reduces average profits and may even constitute a prisoner's dilemma. Specialized provision may yield polarization in the style and type dimensions. This is in contrast to the maximum–minimum differentiation result previously established in the literature on multidimensional horizontal competition. We show that maximal differentiation in both dimensions occurs due to the discrete nature of the type dimension and asymmetric advertising markets.

Evaluation of control and surveillance strategies for classical swine fever using a simulation model

Classical swine fever (CSF) outbreaks can cause enormous losses in naïve pig populations. How to best minimize the economic damage and number of culled animals caused by CSF is therefore an important research area. The baseline CSF control strategy in the European Union and Switzerland consists of culling all animals in infected herds, movement restrictions for animals, material and people within a given distance to the infected herd and epidemiological tracing of transmission contacts. Additional disease control measures such as pre-emptive culling or vaccination have been recommended based on the results from several simulation models; however, these models were parameterized for areas with high animal densities. The objective of this study was to explore whether pre-emptive culling and emergency vaccination should also be recommended in low- to moderate-density areas such as Switzerland. Additionally, we studied the influence of initial outbreak conditions on outbreak severity to improve the efficiency of disease prevention and surveillance. A spatial, stochastic, individual-animal-based simulation model using all registered Swiss pig premises in 2009 (n=9770) was implemented to quantify these relationships. The model simulates within-herd and between-herd transmission (direct and indirect contacts and local area spread). By varying the four parameters (a) control measures, (b) index herd type (breeding, fattening, weaning or mixed herd), (c) detection delay for secondary cases during an outbreak and (d) contact tracing probability, 112 distinct scenarios were simulated. To assess the impact of scenarios on outbreak severity, daily transmission rates were compared between scenarios. Compared with the baseline strategy (stamping out and movement restrictions) vaccination and pre-emptive culling neither reduced outbreak size nor duration. Outbreaks starting in a herd with weaning piglets or fattening pigs caused higher losses regarding to the number of culled premises and were longer lasting than those starting in the two other index herd types. Similarly, larger transmission rates were estimated for these index herd type outbreaks. A longer detection delay resulted in more culled premises and longer duration and better transmission tracing increased the number of short outbreaks. Based on the simulation results, baseline control strategies seem sufficient to control CSF in low-medium animal-dense areas. Early detection of outbreaks is crucial and risk-based surveillance should be focused on weaning piglet and fattening pig premises.

Present state of global wetland extent and wetland methane modelling: methodology of a model inter-comparison project (WETCHIMP)

The Wetland and Wetland CH4 Intercomparison of Models Project (WETCHIMP) was created to evaluate our present ability to simulate large-scale wetland characteristics and corresponding methane (CH4) emissions. A multi-model comparison is essential to evaluate the key uncertainties in the mechanisms and parameters leading to methane emissions. Ten modelling groups joined WETCHIMP to run eight global and two regional models with a common experimental protocol using the same climate and atmospheric carbon dioxide (CO2) forcing datasets. We reported the main conclusions from the intercomparison effort in a companion paper (Melton et al., 2013). Here we provide technical details for the six experiments, which included an equilibrium, a transient, and an optimized run plus three sensitivity experiments (temperature, precipitation, and atmospheric CO2 concentration). The diversity of approaches used by the models is summarized through a series of conceptual figures, and is used to evaluate the wide range of wetland extent and CH4 fluxes predicted by the models in the equilibrium run. We discuss relationships among the various approaches and patterns in consistencies of these model predictions. Within this group of models, there are three broad classes of methods used to estimate wetland extent: prescribed based on wetland distribution maps, prognostic relationships between hydrological states based on satellite observations, and explicit hydrological mass balances. A larger variety of approaches was used to estimate the net CH4 fluxes from wetland systems. Even though modelling of wetland extent and CH4 emissions has progressed significantly over recent decades, large uncertainties still exist when estimating CH4 emissions: there is little consensus on model structure or complexity due to knowledge gaps, different aims of the models, and the range of temporal and spatial resolutions of the models.

Present state of global wetland extent and wetland methane modelling: conclusions from a model inter-comparison project (WETCHIMP)

Global wetlands are believed to be climate sensitive, and are the largest natural emitters of methane (CH4). Increased wetland CH4 emissions could act as a positive feedback to future warming. The Wetland and Wetland CH4 Inter-comparison of Models Project (WETCHIMP) investigated our present ability to simulate large-scale wetland characteristics and corresponding CH4 emissions. To ensure inter-comparability, we used a common experimental protocol driving all models with the same climate and carbon dioxide (CO2) forcing datasets. The WETCHIMP experiments were conducted for model equilibrium states as well as transient simulations covering the last century. Sensitivity experiments investigated model response to changes in selected forcing inputs (precipitation, temperature, and atmospheric CO2 concentration). Ten models participated, covering the spectrum from simple to relatively complex, including models tailored either for regional or global simulations. The models also varied in methods to calculate wetland size and location, with some models simulating wetland area prognostically, while other models relied on remotely sensed inundation datasets, or an approach intermediate between the two. Four major conclusions emerged from the project. First, the suite of models demonstrate extensive disagreement in their simulations of wetland areal extent and CH4 emissions, in both space and time. Simple metrics of wetland area, such as the latitudinal gradient, show large variability, principally between models that use inundation dataset information and those that independently determine wetland area. Agreement between the models improves for zonally summed CH4 emissions, but large variation between the models remains. For annual global CH4 emissions, the models vary by ±40% of the all-model mean (190 Tg CH4 yr−1). Second, all models show a strong positive response to increased atmospheric CO2 concentrations (857 ppm) in both CH4 emissions and wetland area. In response to increasing global temperatures (+3.4 °C globally spatially uniform), on average, the models decreased wetland area and CH4 fluxes, primarily in the tropics, but the magnitude and sign of the response varied greatly. Models were least sensitive to increased global precipitation (+3.9 % globally spatially uniform) with a consistent small positive response in CH4 fluxes and wetland area. Results from the 20th century transient simulation show that interactions between climate forcings could have strong non-linear effects. Third, we presently do not have sufficient wetland methane observation datasets adequate to evaluate model fluxes at a spatial scale comparable to model grid cells (commonly 0.5°). This limitation severely restricts our ability to model global wetland CH4 emissions with confidence. Our simulated wetland extents are also difficult to evaluate due to extensive disagreements between wetland mapping and remotely sensed inundation datasets. Fourth, the large range in predicted CH4 emission rates leads to the conclusion that there is both substantial parameter and structural uncertainty in large-scale CH4 emission models, even after uncertainties in wetland areas are accounted for.

A reconstruction of radiocarbon production and total solar irradiance from the Holocene ¹⁴C and CO₂ records: implications of data and model uncertainties

Radiocarbon production, solar activity, total solar irradiance (TSI) and solar-induced climate change are reconstructed for the Holocene (10 to 0 kyr BP), and TSI is predicted for the next centuries. The IntCal09/SHCal04 radiocarbon and ice core CO2 records, reconstructions of the geomagnetic dipole, and instrumental data of solar activity are applied in the Bern3D-LPJ, a fully featured Earth system model of intermediate complexity including a 3-D dynamic ocean, ocean sediments, and a dynamic vegetation model, and in formulations linking radiocarbon production, the solar modulation potential, and TSI. Uncertainties are assessed using Monte Carlo simulations and bounding scenarios. Transient climate simulations span the past 21 thousand years, thereby considering the time lags and uncertainties associated with the last glacial termination. Our carbon-cycle-based modern estimate of radiocarbon production of 1.7 atoms cm−2 s−1 is lower than previously reported for the cosmogenic nuclide production model by Masarik and Beer (2009) and is more in-line with Kovaltsov et al. (2012). In contrast to earlier studies, periods of high solar activity were quite common not only in recent millennia, but throughout the Holocene. Notable deviations compared to earlier reconstructions are also found on decadal to centennial timescales. We show that earlier Holocene reconstructions, not accounting for the interhemispheric gradients in radiocarbon, are biased low. Solar activity is during 28% of the time higher than the modern average (650 MeV), but the absolute values remain weakly constrained due to uncertainties in the normalisation of the solar modulation to instrumental data. A recently published solar activity–TSI relationship yields small changes in Holocene TSI of the order of 1 W m−2 with a Maunder Minimum irradiance reduction of 0.85 ± 0.16 W m−2. Related solar-induced variations in global mean surface air temperature are simulated to be within 0.1 K. Autoregressive modelling suggests a declining trend of solar activity in the 21st century towards average Holocene conditions.

Methane emissions from floodplains in the Amazon Basin: challenges in developing a process-based model for global applications

Tropical wetlands are estimated to represent about 50% of the natural wetland methane (CH4) emissions and explain a large fraction of the observed CH4 variability on timescales ranging from glacial–interglacial cycles to the currently observed year-to-year variability. Despite their importance, however, tropical wetlands are poorly represented in global models aiming to predict global CH4 emissions. This publication documents a first step in the development of a process-based model of CH4 emissions from tropical floodplains for global applications. For this purpose, the LPX-Bern Dynamic Global Vegetation Model (LPX hereafter) was slightly modified to represent floodplain hydrology, vegetation and associated CH4 emissions. The extent of tropical floodplains was prescribed using output from the spatially explicit hydrology model PCR-GLOBWB. We introduced new plant functional types (PFTs) that explicitly represent floodplain vegetation. The PFT parameterizations were evaluated against available remote-sensing data sets (GLC2000 land cover and MODIS Net Primary Productivity). Simulated CH4 flux densities were evaluated against field observations and regional flux inventories. Simulated CH4 emissions at Amazon Basin scale were compared to model simulations performed in the WETCHIMP intercomparison project. We found that LPX reproduces the average magnitude of observed net CH4 flux densities for the Amazon Basin. However, the model does not reproduce the variability between sites or between years within a site. Unfortunately, site information is too limited to attest or disprove some model features. At the Amazon Basin scale, our results underline the large uncertainty in the magnitude of wetland CH4 emissions. Sensitivity analyses gave insights into the main drivers of floodplain CH4 emission and their associated uncertainties. In particular, uncertainties in floodplain extent (i.e., difference between GLC2000 and PCR-GLOBWB output) modulate the simulated emissions by a factor of about 2. Our best estimates, using PCR-GLOBWB in combination with GLC2000, lead to simulated Amazon-integrated emissions of 44.4 ± 4.8 Tg yr−1. Additionally, the LPX emissions are highly sensitive to vegetation distribution. Two simulations with the same mean PFT cover, but different spatial distributions of grasslands within the basin, modulated emissions by about 20%. Correcting the LPX-simulated NPP using MODIS reduces the Amazon emissions by 11.3%. Finally, due to an intrinsic limitation of LPX to account for seasonality in floodplain extent, the model failed to reproduce the full dynamics in CH4 emissions but we proposed solutions to this issue. The interannual variability (IAV) of the emissions increases by 90% if the IAV in floodplain extent is accounted for, but still remains lower than in most of the WETCHIMP models. While our model includes more mechanisms specific to tropical floodplains, we were unable to reduce the uncertainty in the magnitude of wetland CH4 emissions of the Amazon Basin. Our results helped identify and prioritize directions towards more accurate estimates of tropical CH4 emissions, and they stress the need for more research to constrain floodplain CH4 emissions and their temporal variability, even before including other fundamental mechanisms such as floating macrophytes or lateral water fluxes.

Detection and sequence analysis of a nickel-induced mutation in a retroviral model system

We have developed a novel way to assess the mutagenicity of environmentally important metal carcinogens, such as nickel, by creating a positive selection system based upon the conditional expression of a retroviral transforming gene. The target gene is the v-mos gene in MuSVts110, a murine retrovirus possessing a growth temperature dependent defect in expression of the transforming gene due to viral RNA splicing. In normal rat kidney cells infected with MuSVts110 (6m2 cells), splicing of the MuSVts110 RNA to form the mRNA from which the transforming protein, p85$\sp{\rm gag-mos}$, is translated is growth-temperature dependent, occurring at 33 C and below but not at 39 C and above. This splicing "defect" is mediated by cis-acting viral sequences. Nickel chloride treatment of 6m2 cells followed by growth at 39 C, allowed the selection of "revertant" cells which constitutively express p85$\sp{\rm gag-mos}$ due to stable changes in the viral RNA splicing phenotype, suggesting that nickel, a carcinogen whose mutagenicity has not been well established, could induce mutations in mammalian genes. We also show by direct sequencing of PCR-amplified integrated MuSVts110 DNA from a 6m2 nickel-revertant cell line that the nickel-induced mutation affecting the splicing phenotype is a cis-acting 70-base duplication of a region of the viral DNA surrounding the 3$\sp\prime$ splice site. These findings provide the first example of the molecular basis for a nickel-induced DNA lesion and establish the mutagenicity of this potent carcinogen. ^

Spatial gradients of temperature, accumulation and delta18O-ice in Greenland over a series of Dansgaard-Oeschger events

Air and water stable isotope measurements from four Greenland deep ice cores (GRIP, GISP2, NGRIP and NEEM) are investigated over a series of Dansgaard–Oeschger events (DO 8, 9 and 10), which are representative of glacial millennial scale variability. Combined with firn modeling, air isotope data allow us to quantify abrupt temperature increases for each drill site (1σ = 0.6 °C for NEEM, GRIP and GISP2, 1.5 °C for NGRIP). Our data show that the magnitude of stadial–interstadial temperature increase is up to 2 °C larger in central and North Greenland than in northwest Greenland: i.e., for DO 8, a magnitude of +8.8 °C is inferred, which is significantly smaller than the +11.1 °C inferred at GISP2. The same spatial pattern is seen for accumulation increases. This pattern is coherent with climate simulations in response to reduced sea-ice extent in the Nordic seas. The temporal water isotope (δ18O)–temperature relationship varies between 0.3 and 0.6 (±0.08) ‰ °C−1 and is systematically larger at NEEM, possibly due to limited changes in precipitation seasonality compared to GISP2, GRIP or NGRIP. The gas age−ice age difference of warming events represented in water and air isotopes can only be modeled when assuming a 26% (NGRIP) to 40% (GRIP) lower accumulation than that derived from a Dansgaard–Johnsen ice flow model.