Induction of glutathione reductase enzyme activity by β‐aminobutyric acid in plant leaves

Abstract

Treatment of pea and tobacco leaf discs with the resistance inducer DL‐β‐amino‐n‐butyric acid (BABA) led to a substantial induction of glutathione reductase (GR, E.C. 1.6.4.2.) enzyme activity. After exposure to 1 mM BABA for 96 hrs, the GR activities were 3.2‐fold and 2.9‐fold higher in pea and tobacco leaf discs, respectively, than GR activities in untreated controls. Elevated GR levels may contribute to the antioxidative protection of plants during pathogen attack.     

Data fusion modeling for groundwater systems

Engineering projects involving hydrogeology are faced with uncertainties because the earth is heterogeneous, and typical data sets are fragmented and disparate. In theory, predictions provided by computer simulations using calibrated models constrained by geological boundaries provide answers to support management decisions, and geostatistical methods quantify safety margins. In practice, current methods are limited by the data types and models that can be included, computational demands, or simplifying assumptions. Data Fusion Modeling (DFM) removes many of the limitations and is capable of providing data integration and model calibration with quantified uncertainty for a variety of hydrological, geological, and geophysical data types and models. The benefits of DFM for waste management, water supply, and geotechnical applications are savings in time and cost through the ability to produce visual models that fill in missing data and predictive numerical models to aid management optimization. DFM has the ability to update field-scale models in real time using PC or workstation systems and is ideally suited for parallel processing implementation. DFM is a spatial state estimation and system identification methodology that uses three sources of information: measured data, physical laws, and statistical models for uncertainty in spatial heterogeneities. What is new in DFM is the solution of the causality problem in the data assimilation Kalman filter methods to achieve computational practicality. The Kalman filter is generalized by introducing information filter methods due to Bierman coupled with a Markov random field representation for spatial variation. A Bayesian penalty function is implemented with Gauss–Newton methods. This leads to a computational problem similar to numerical simulation of the partial differential equations (PDEs) of groundwater. In fact, extensions of PDE solver ideas to break down computations over space form the computational heart of DFM. State estimates and uncertainties can be computed for heterogeneous hydraulic conductivity fields in multiple geological layers from the usually sparse hydraulic conductivity data and the often more plentiful head data. Further, a system identification theory has been derived based on statistical likelihood principles. A maximum likelihood theory is provided to estimate statistical parameters such as Markov model parameters that determine the geostatistical variogram. Field-scale application of DFM at the DOE Savannah River Site is presented and compared with manual calibration. DFM calibration runs converge in less than 1 h on a Pentium Pro PC for a 3D model with more than 15,000 nodes. Run time is approximately linear with the number of nodes. Furthermore, conditional simulation is used to quantify the statistical variability in model predictions such as contaminant breakthrough curves.     

Assessment of Several Test Methods for the Determination of the Anaerobic Biodegradability of Polymers

Anaerobic degradation of eight commercially available biodegradable polymers was compared in two anaerobic tests using digestion sludge, according to ISO 11734 and ASTM D.5210-91. Cotton, polyhydroxybutyrate/hydroxyvalerate copolymer (PHB/PHV), starch blend, thermoplastic cellulose acetate, and cellulose acetate fibers proved to be anaerobically degradable, but only a low extent of degradation was found for polylactide, polyvinylalcohol, and polycaprolactone. Both test methods gave the same overall results, but with the ISO medium, longer lag phases and greater ranges of variation in the results were observed. These effects are presumably due to low concentrations of carbon dioxide in the ISO medium. Carbon dioxide has been demonstrated to be essential for the growth of various anaerobic bacteria, notably homoacetogenic and methanogenic bacteria.     

Modeling instability development in layered systems

This study investigates patterns of finger development and propagation in layered porous media. Fingers are created with interfacial perturbations, formed by adding a thin zone of regularly varying hydraulic conductivity along the layer. Simulation results agree qualitatively with those observed in two-dimensional laboratory experiments. In all cases, the formation of instabilities requires seeding of perturbations, even if the system is unstably stratified. A series of simulations show how the shapes of the instabilities differ according to where along the unstable interface the instabilities form and the layer in which they develop. Pathline analyses indicate how the patterns of flow in the domain can be exceedingly complex. Concentration distributions are influenced by movements of water between layers and the formation of a large convection cell in the lowermost layer. These numerical investigations reinforce inferences from the experimental studies that classical stability theory is less useful in determining whether instabilities will form and what their shape will be. Even with the relatively simple layering, patterns of flow and resulting concentrations are complex.     

ESTIMATION OF LONG-TERM DISCHARGE STATISTICS BY REGIONAL ADJUSTMENT1

ABSTRACT: A regional adjustment relationship was developed to estimate long-term (30-year) monthly median discharges from short term (three-year) records. This method differs from traditional approaches in that it is based on site-specific discharge data but does not require correlation of these data with discharges from a single hydrologically similar long-term gage. The method is shown to be statistically robust, and applicable to statistics other than the median.     

Nutrient Inputs to the Laurentian Great Lakes by Source and Watershed Estimated Using SPARROW Watershed Models1

Robertson, Dale M. and David A. Saad, 2011. Nutrient Inputs to the Laurentian Great Lakes by Source and Watershed Estimated Using SPARROW Watershed Models. Journal of the American Water Resources Association (JAWRA) 47(5):1011‐1033. DOI: 10.1111/j.1752‐1688.2011.00574.x Abstract: Nutrient input to the Laurentian Great Lakes continues to cause problems with eutrophication. To reduce the extent and severity of these problems, target nutrient loads were established and Total Maximum Daily Loads are being developed for many tributaries. Without detailed loading information it is difficult to determine if the targets are being met and how to prioritize rehabilitation efforts. To help address these issues, SPAtially Referenced Regressions On Watershed attributes (SPARROW) models were developed for estimating loads and sources of phosphorus (P) and nitrogen (N) from the United States (U.S.) portion of the Great Lakes, Upper Mississippi, Ohio, and Red River Basins. Results indicated that recent U.S. loadings to Lakes Michigan and Ontario are similar to those in the 1980s, whereas loadings to Lakes Superior, Huron, and Erie decreased. Highest loads were from tributaries with the largest watersheds, whereas highest yields were from areas with intense agriculture and large point sources of nutrients. Tributaries were ranked based on their relative loads and yields to each lake. Input from agricultural areas was a significant source of nutrients, contributing ～33‐44% of the P and ～33‐58% of the N, except for areas around Superior with little agriculture. Point sources were also significant, contributing ～14‐44% of the P and 13‐34% of the N. Watersheds around Lake Erie contributed nutrients at the highest rate (similar to intensively farmed areas in the Midwest) because they have the largest nutrient inputs and highest delivery ratio.     

Analyzing effective factors on leakage-induced hydrogen fires

Currently, novel energy resources are receiving increasing attention as a response to the limitation in fossil fuels as well as their adverse effects on human health. Hydrogen, one of the most abundant elements on the earth, can be regarded as a new energy source to replace fossil fuels. Therefore, safety assessment of the relating processes is very crucial by increasing use of hydrogen as a fuel source. In this regard, consequence analysis for risk assessment and power reduction is very important. The present study aims at modeling hydrogen dispersion along with consequence analyses for such events as jet fire and flash fire. The model was validated by using the data derived from a study on hydrogen leakage in supply pipelines in the laboratory of the University of Pisa. Modeling results reveal that ambient conditions will impose a milder impact on leakage consequences if internal pressure is high in release source. The safe distance was also estimated to be 14 m. Dispersion consequence modeling was performed, followed by the evaluation of the effect of environmental (i.e., stability, ambient temperature, surface roughness, wind speed, and humidity) and process (i.e., vessel temperature and pressure, leakage diameter, and releasing point height) parameters on maximum size flammable vapor cloud and maximum level jet fire radiation on the ground. The size of flammable vapor cloud (consequence dispersion index) and the maximum flux of radiation were affected by process parameters more than ambient parameters. Leakage diameter and the vessel pressure were found to have the highest impact on the operational parameters.     

Complementarity of No‐Take Marine Reserves and Individual Transferable Catch Quotas for Managing the Line Fishery of the Great Barrier Reef

Abstract: Changes in the management of the fin fish fishery of the Great Barrier Reef motivated us to investigate the combined effects on economic returns and fish biomass of no‐take areas and regulated total allowable catch allocated in the form of individual transferable quotas (such quotas apportion the total allowable catch as fishing rights and permits the buying and selling of these rights among fishers). We built a spatially explicit biological and economic model of the fishery to analyze the trade‐offs between maintaining given levels of fish biomass and the net financial returns from fishing under different management regimes. Results of the scenarios we modeled suggested that a decrease in total allowable catch at high levels of harvest either increased net returns or lowered them only slightly, but increased biomass by up to 10% for a wide range of reserve sizes and an increase in the reserve area from none to 16% did not greatly change net returns at any catch level. Thus, catch shares and no‐take reserves can be complementary and when these methods are used jointly they promote lower total allowable catches when harvest is relatively high and encourage larger no‐take areas when they are small.     

Incorporation of Spatial and Economic Analyses of Human‐Use Data in the Design of Marine Protected Areas

Abstract: Social, economic, and ecological criteria contribute to the successful design, implementation, and management of marine protected areas (MPAs). In the context of California's Marine Life Protection Act Initiative, we developed a set of methods for collecting, compiling, and analyzing data about the spatial extent and relative economic importance of commercial and recreational fishing. We interviewed 174 commercial fishers who represented the major fisheries in the initiative's north‐central coast region, which extends from Point Arena south to Pigeon Point. These fishers provided data that we used to map the extent of each of the fishing grounds, to weight the relative importance of areas within the grounds, to characterize the operating costs of each fishery, and to analyze the potential economic losses associated with proposed marine protected areas. A regional stakeholder group used the maps and impact analyses in conjunction with other data sets to iteratively identify economic and ecological trade‐offs in designations of different areas as MPAs at regional, port, and fishery extents. Their final proposed MPA network designated 20% of state waters as MPAs. Potential net economic loss ranged from 1.7% to 14.2% in the first round of network design and totaled 6.3% in the final round of design. This process is a case study in the application of spatial analysis to validate and integrate local stakeholder knowledge in marine planning.