Subsurface imaging of vegetation, climate, and root-zone moisture interactions

Changes in global climate and land use affect important prolesses from evapotranspiration and groundwater recharge to carbon storage and biochemical cycling. Near surface soil moisture is pivotal to understand the consequences of these changes. However, the dynamic interactions between vegetation and soil moisture remain largely unresolved because it is difficult to monitor and quantify subsurface hydrologic fluxes at relevant scales. Here we use electrical resistivity to monitor the influence of climate and vegetation on root-zone moisture, bridging the gap between remotely-sensed and in-situ point measurements. Our research quantifies large seasonal differences in root-zone moisture dynamics for a forest-grassland ecotone. We found large differences in effective rooting depth and moisture distributions for the two vegetation types. Our results highlight the likely impacts of land transformations on groun ter recharge, streamflow, and land-atmosphere exchanges.

Soil moisture variability in a temperate deciduous forest: insights from electrical resistivity and throughfall data

Hydrogeophysics is a growing discipline that holds significant promise to help elucidate details of dynamic processes in the near surface, built on the ability of geophysical methods to measure properties from which hydrological and geochemical variables can be derived. For example, bulk electrical conductivity is governed by, amongst others, interstitial water content, fluid salinity, and temperature, and can be measured using a range of geophysical methods. In many cases, electrical resistivity tomography (ERT) is well suited to characterize these properties in multiple dimensions and to monitor dynamic processes, such as water infiltration and solute transport. In recent years, ERT has been used increasingly for ecosystem research in a wide range of settings; in particular to characterize vegetation-driven changes in root-zone and near-surface water dynamics. This increased popularity is due to operational factors (e.g., improved equipment, low site impact), data considerations (e.g., excellent repeatability), and the fact that ERT operates at scales significantly larger than traditional point sensors. Current limitations to a more widespread use of the approach include the high equipment costs, and the need for site-specific petrophysical relationships between properties of interest. In this presentation we will discuss recent equipment advances and theoretical and methodological aspects involved in the accurate estimation of soil moisture from ERT results. Examples will be presented from two studies in a temperate climate (Michigan, USA) and one from a humid tropical location (Tapajos, Brazil).

Comparison of three-dimensional profiles over time

In this paper, we describe an analysis for data collected on a three-dimensional spatial lattice with treatments applied at the horizontal lattice points. Spatial correlation is accounted for using a conditional autoregressive model. Observations are defined as neighbours only if they are at the same depth. This allows the corresponding variance components to vary by depth. We use the Markov chain Monte Carlo method with block updating, together with Krylov subspace methods, for efficient estimation of the model. The method is applicable to both regular and irregular horizontal lattices and hence to data collected at any set of horizontal sites for a set of depths or heights, for example, water column or soil profile data. The model for the three-dimensional data is applied to agricultural trial data for five separate days taken roughly six months apart in order to determine possible relationships over time. The purpose of the trial is to determine a form of cropping that leads to less moist soils in the root zone and beyond.We estimate moisture for each date, depth and treatment accounting for spatial correlation and determine relationships of these and other parameters over time.

A Bayesian analysis of an agricultural field trial with three spatial dimensions

Modern technology now has the ability to generate large datasets over space and time. Such data typically exhibit high autocorrelations over all dimensions. The field trial data motivating the methods of this paper were collected to examine the behaviour of traditional cropping and to determine a cropping system which could maximise water use for grain production while minimising leakage below the crop root zone. They consist of moisture measurements made at 15 depths across 3 rows and 18 columns, in the lattice framework of an agricultural field. Bayesian conditional autoregressive (CAR) models are used to account for local site correlations. Conditional autoregressive models have not been widely used in analyses of agricultural data. This paper serves to illustrate the usefulness of these models in this field, along with the ease of implementation in WinBUGS, a freely available software package. The innovation is the fitting of separate conditional autoregressive models for each depth layer, the ‘layered CAR model’, while simultaneously estimating depth profile functions for each site treatment. Modelling interest also lay in how best to model the treatment effect depth profiles, and in the choice of neighbourhood structure for the spatial autocorrelation model. The favoured model fitted the treatment effects as splines over depth, and treated depth, the basis for the regression model, as measured with error, while fitting CAR neighbourhood models by depth layer. It is hierarchical, with separate onditional autoregressive spatial variance components at each depth, and the fixed terms which involve an errors-in-measurement model treat depth errors as interval-censored measurement error. The Bayesian framework permits transparent specification and easy comparison of the various complex models compared.

Some major problems with existing models and terminology associated with kimberlite pipes from a volcanological perspective, and some suggestions

Five significant problems hinder advances in understanding of the volcanology of kimberlites: (1) kimberlite geology is very model driven; (2) a highly genetic terminology drives deposit or facies interpretation; (3) the effects of alteration on preserved depositional textures have been grossly underestimated; (4) the level of understanding of the physical process significance of preserved textures is limited; and, (5) some inferred processes and deposits are not based on actual, modern volcanological processes. These issues need to be addressed in order to advance understanding of kimberlite volcanological pipe forming processes and deposits. The traditional, steep-sided southern African pipe model (Class I) consists of a steep tapering pipe with a deep root zone, a middle diatreme zone and an upper crater zone (if preserved). Each zone is thought to be dominated by distinctive facies, respectively: hypabyssal kimberlite (HK, descriptively called here massive coherent porphyritic kimberlite), tuffisitic kimberlite breccia (TKB, descriptively here called massive, poorly sorted lapilli tuff) and crater zone facies, which include variably bedded pyroclastic kimberlite and resedimented and reworked volcaniclastic kimberlite (RVK). Porphyritic coherent kimberlite may, however, also be emplaced at different levels in the pipe, as later stage intrusions, as well as dykes in the surrounding country rock. The relationship between HK and TKB is not always clear. Sub-terranean fluidisation as an emplacement process is a largely unsubstantiated hypothesis; modern in-vent volcanological processes should initially be considered to explain observed deposits. Crater zone volcaniclastic deposits can occur within the diatreme zone of some pipes, indicating that the pipe was largely empty at the end of the eruption, and subsequently began to fill-in largely through resedimentation and sourcing of pyroclastic deposits from nearby vents. Classes II and III Canadian kimberlite models have a more factual, descriptive basis, but are still inadequately documented given the recency of their discovery. The diversity amongst kimberlite bodies suggests that a three-model classification is an over-simplification. Every kimberlite is altered to varying degrees, which is an intrinsic consequence of the ultrabasic composition of kimberlite and the in-vent context; few preserve original textures. The effects of syn- to post-emplacement alteration on original textures have not been adequately considered to date, and should be back-stripped to identify original textural elements and configurations. Applying sedimentological textural configurations as a guide to emplacement processes would be useful. The traditional terminology has many connotations about spatial position in pipe and of process. Perhaps the traditional terminology can be retained in the industrial situation as a general lithofacies-mining terminological scheme because it is so entrenched. However, for research purposes a more descriptive lithofacies terminology should be adopted to facilitate detailed understanding of deposit characteristics, important variations in these, and the process origins. For example every deposit of TKB is different in componentry, texture, or depositional structure. However, because so many deposits in many different pipes are called TKB, there is an implication that they are all similar and that similar processes were involved, which is far from clear.

Impacts of sodic soil amelioration on deep drainage

Groundwater tables are rising beneath irrigated fields in some areas of the Lower Burdekin in North Queensland, Australia. The soils where this occurs are predominantly sodic clay soils with low hydraulic conductivities. Many of these soils have been treated by applying gypsum or by increasing the salinity of irrigation water by mixing saline groundwater with fresh river water. While the purpose of these treatments is to increase infiltration into the surface soils and improve productivity of the root zone, it is thought that the treatments may have altered the soil hydraulic properties well below the root zone leading to increased groundwater recharge and rising water tables. In this paper we discuss the use of column experiments and HYDRUS modelling, with major ion reaction and transport and soil water chemistry-dependent hydraulic conductivity, to assess the likely depth, magnitude and timing of the impacts of surface soil amelioration on soil hydraulic properties below the root zone and hence groundwater recharge. In the experiments, columns of sodic clays from the Lower Burdekin were leached for extended periods of time with either gypsum solutions or mixed cation salt solutions and change s in hydraulic conductivity were measured. Leaching with a gypsum solution for an extended time period, until the flow rate stabilised, resulted in an approximately twenty fold increase in the hydraulic conductivity when compared with a low salinity, mixed cation solution. HYDRUS modelling was used to high light the role of those factors which might influence the impacts of soil treatment, particularly at depth, including the large amounts of rain during the relatively short wet season and the presence of thick low permeability clay layers.

The lag effects and vulnerabilities of temperature effects on cardiovascular disease mortality in a subtropical climate zone in China

This research quantifies the lag effects and vulnerabilities of temperature effects on cardiovascular disease in Changsha—a subtropical climate zone of China. A Poisson regression model within a distributed lag nonlinear models framework was used to examine the lag effects of cold- and heat-related CVD mortality. The lag effect for heat-related CVD mortality was just 0–3 days. In contrast, we observed a statistically significant association with 10–25 lag days for cold-related CVD mortality. Low temperatures with 0–2 lag days increased the mortality risk for those ≥65 years and females. For all ages, the cumulative effects of cold-related CVD mortality was 6.6% (95% CI: 5.2%–8.2%) for 30 lag days while that of heat-related CVD mortality was 4.9% (95% CI: 2.0%–7.9%) for 3 lag days. We found that in Changsha city, the lag effect of hot temperatures is short while the lag effect of cold temperatures is long. Females and older people were more sensitive to extreme hot and cold temperatures than males and younger people.

Determination of particle concentration in the breathing zone for four different types of office ventilation systems

Many factors affect the airflow patterns, thermal comfort, contaminant removal efficiency and indoor air quality at individual workstations in office buildings. In this study, four ventilation systems were used in a test chamber designed to represent an area of a typical office building floor and reproduce the real characteristics of a modern office space. Measurements of particle concentration and thermal parameters (temperature and velocity) were carried out for each of the following types of ventilation systems: a) conventional air distribution system with ceiling supply and return; b) conventional air distribution system with ceiling supply and return near the floor; c) underfloor air distribution system; and d) split system. The measurements aimed to analyse the particle removal efficiency in the breathing zone and the impact of particle concentration on an individual at the workstation. The efficiency of the ventilation system was analysed by measuring particle size and concentration, ventilation effectiveness and the Indoor/Outdoor ratio. Each ventilation system showed different airflow patterns and the efficiency of each ventilation system in the removal of the particles in the breathing zone showed no correlation with particle size and the various methods of analyses used.

Gene Silencing in Arabidopsis Spreads from the Root to the Shoot, through a Gating Barrier, by Template-Dependent, Nonvascular, Cell-to-Cell Movement

Upward long-distance mobile silencing has been shown to be phloem mediated in several different solanaceous species. We show that the Arabidopsis (Arabidopsis thaliana) seedling grafting system and a counterpart inducible system generate upwardly spreading long-distance silencing that travels not in the phloem but by template-dependent reiterated short-distance cell-to-cell spread through the cells of the central stele. Examining the movement of the silencing front revealed a largely unrecognized zone of tissue, below the apical meristem, that is resistant to the silencing signal and that may provide a gating or protective barrier against small RNA signals. Using a range of auxin and actin transport inhibitors revealed that, in this zone, alteration of vesicular transport together with cytoskeleton dynamics prevented or retarded the spread of the silencing signal. This suggests that small RNAs are transported from cell to cell via plasmodesmata rather than diffusing from their source in the phloem.

Material yielding by both axial and bending spring stiffness at elevated temperature

Material yielding is typically modeled either by plastic zone or plastic hinge methods under the context of geometric and material nonlinear finite element methods. In fire analysis of steel structures, the plastic zone method is widely used, but it requires extensively more computational efforts. The objective of this paper is to develop the nonlinear material model allowing for interaction of both axial force and bending moment, which relies on the plastic hinge method to achieve numerical efficiency and reduce computational effort. The biggest advantage of the plastic-hinge approach is its computational efficiency and easy verification by the design code formulae of the axial force–moment interaction yield criterion for beam–column members. Further, the method is reliable and robust when used in analysis of practical and large structures. In order to allow for the effect of catenary action, axial thermal expansion is considered in the axial restraint equations. The yield function for material yielding incorporated in the stiffness formulation, which allows for both axial force and bending moment effects, is more accurate and rational to predict the behaviour of the frames under fire. In the present fire analysis, the mechanical properties at elevated temperatures follow mainly the Eurocode 3 [Design of steel structures, Part 1.2: Structural fire design. European Committee for Standisation; 2003]. Example of a tension member at a steady state heating condition is modeled to verify the proposed spring formulation and to compare with results by others. The behaviour of a heated member in a highly redundant structure is also studied by the present approach.

An Artificial Neutral Network (ANN) model for predicting biodiesel kinetic viscosity as a function of temperature and chemical compositions

An Artificial Neural Network (ANN) is a computational modeling tool which has found extensive acceptance in many disciplines for modeling complex real world problems. An ANN can model problems through learning by example, rather than by fully understanding the detailed characteristics and physics of the system. In the present study, the accuracy and predictive power of an ANN was evaluated in predicting kinetic viscosity of biodiesels over a wide range of temperatures typically encountered in diesel engine operation. In this model, temperature and chemical composition of biodiesel were used as input variables. In order to obtain the necessary data for model development, the chemical composition and temperature dependent fuel properties of ten different types of biodiesels were measured experimentally using laboratory standard testing equipments following internationally recognized testing procedures. The Neural Networks Toolbox of MatLab R2012a software was used to train, validate and simulate the ANN model on a personal computer. The network architecture was optimised following a trial and error method to obtain the best prediction of the kinematic viscosity. The predictive performance of the model was determined by calculating the absolute fraction of variance (R2), root mean squared (RMS) and maximum average error percentage (MAEP) between predicted and experimental results. This study found that ANN is highly accurate in predicting the viscosity of biodiesel and demonstrates the ability of the ANN model to find a meaningful relationship between biodiesel chemical composition and fuel properties at different temperature levels. Therefore the model developed in this study can be a useful tool in accurately predict biodiesel fuel properties instead of undertaking costly and time consuming experimental tests.

Self-organized ZnO nanodot arrays : effective control using SiNx interlayers and low-temperature plasmas

An advanced inductively coupled plasma (ICP)-assisted rf magnetron sputtering deposition method is developed to synthesize regular arrays of pear-shaped ZnO nanodots on a thin SiNx buffer layer pre-deposited onto a silicon substrate. It is shown that the growth of ZnO nanodots obey the cubic root-law behavior. It is also shown that the synthesized ZnO nanodots are highly-uniform, controllable by the experimental parameters, and also feature good structural and photoluminescent properties. These results suggest that this custom-designed ICP-based technique is very effective and highly-promising for the synthesis of property- and size-controllable highly-uniform ZnO nanodots suitable for next-generation light emitting diodes, energy storage, UV nanolasers, and other applications.

A new low temperature synthesis route of fraipontite (Zn,Al)3(Si,Al)2O5(OH)4

A low temperature synthesis method based on the decomposition of urea at 90°C in water has been developed to synthesise fraipontite. This material is characterised by a basal reflection 001 at 7.44 Å. The trioctahedral nature of the fraipontite is shown by the presence of a 06l band around 1.54 Å, while a minor band around 1.51 Å indicates some cation ordering between Zn and Al resulting in Al-rich areas with a more dioctahedral nature. TEM and IR indicate that no separate kaolinite phase is present. An increase in the Al content however, did result in the formation of some SiO2 in the form of quartz. Minor impurities of carbonate salts were observed during the synthesis caused by to the formation of CO32- during the decomposition of urea.