Assessment of monitoring power for highly mobile vertebrates

Monitoring of population trends is a critical component of conservation management, and development of practical methods remains a priority, particularly for species that challenge more standard approaches. We used field-parameterized simulation models to examine the effects of different errors on monitoring power and compared alternative methods used with two species of threatened pteropodids (flying-foxes), Pteropus conspicillatus and P. poliocephalus, whose mobility violates assumptions of closure on short and long timescales. The influence of three errors on time to 80% statistical power was assessed using a Monte Carlo approach. The errors were: (1) failure to count all animals at a roost, (2) errors associated with enumeration, and (3) variability in the proportion of the population counted due to the movement of individuals between roosts. Even with perfect accuracy and precision for these errors only marginal improvements in power accrued (-1%), with one exception. Improving certainty in the proportion of the population being counted reduced time to detection of a decline by over 6 yr (43%) for fly-out counts and almost 10 yr (71%) for walk-through counts. This error derives from the movement of animals between known and unknown roost sites, violating assumptions of population closure, and because it applies to the entire population, it dominates all other sources of error. Similar errors will accrue in monitoring of a wide variety of highly mobile species and will also result from population redistribution under climate change. The greatest improvements in monitoring performance of highly mobile species accrue through an improved understanding of the proportion of the population being counted, and consequently monitoring of such species must be done at the scale of the species or population range, not at the local level.     

Long-term burning interacts with herbivory to slow decomposition

Fires can generate spatial variation in trophic interactions such as insect herbivory. If trophic interactions mediated by fire influence nutrient cycling, they could feed back on the more immediate consequences of fire on nutrient dynamics. Here we consider herbivore-induced effects on oak litter quality and decomposition within a long-term manipulation of fire frequency in central Minnesota, USA. We focused on bur oak (Quercus macrocarpa) trees, which are common across the fire frequency gradient and are often heavily infested with either lace bugs (Corythuca arcuata) or aphids (Hoplochaithropsus quercicola). We used targeted exclusion to test for herbivore-specific effects on litter chemistry and subsequent decomposition rates. Lace bug exclusion led to lower lignin concentrations in litterfall and subsequently accelerated decomposition. In contrast, aphid exclusion had no effect on litterfall chemistry or on decomposition rate, despite heavy infestation levels. Effects of lace bug herbivory on litterfall chemistry and decomposition were similar in burned and unburned areas. However, lace bug herbivory was much more common in burned than in unburned areas, whereas aphid herbivory was more common in unburned areas. These results suggest that frequent fires promote oak-herbivore interactions that decelerate decomposition. This effect should amplify other influences of fire that slow nitrogen cycling.     

Economic resilience to natural and man-made disasters: Multidisciplinary origins and contextual dimensions

Economic resilience is a major way to reduce losses from disasters. Its effectiveness would be further enhanced if it could be precisely defined and measured. This paper distinguishes static economic resilience—efficient allocation of existing resources—from dynamic economic resilience—speeding recovery through repair and reconstruction of the capital stock. Operational definitions are put forth that incorporate this important distinction. The consistency of the definitions is examined in relation to antecedents from several disciplines. The effectiveness of economic resilience is evaluated on the basis of recent empirical studies. In addition, its potential to be enhanced and eroded is analyzed in various contexts.     

ExSys-LOPA for the chemical process industry

The chemical process industries are characterized by the use, processing, and storage of large amounts of dangerous chemical substances and/or energy. Among different missions of chemical plants there are two very important ones, which: 1. provide a safe work environment, 2. fully protect the environment. These important missions can be achieved only by design of adequate safeguards for identified process hazards. Layer of Protection Analysis (LOPA) can successfully answer this question. This technique is a simplified process of quantitative risk assessment, using the order of magnitude categories for initiating cause frequency, consequence severity, and the likelihood of failure of independent protection layers to analyze and assess the risk of particular accident scenarios. LOPA requires application of qualitative hazard evaluation methods to identify accident scenarios, including initiating causes and appropriate safeguards. This can be well fulfilled, e.g., by HAZOP Studies or What-If Analysis. However, those techniques require extensive experience, efforts by teams of experts as well as significant time commitments, especially for complex chemical process units. In order to simplify that process, this paper presents another strategy that is a combination of an expert system for accident scenario identification with subsequent application of LOPA. The concept is called ExSys-LOPA, which employs, prepared in advance, values from engineering databases for identification of loss events specific to the selected target process and subsequently a accident scenario barrier model developed as an input for LOPA. Such consistent rules for the identification of accident scenarios to be analyzed can facilitate and expedite the analysis and thereby incorporate many more scenarios and analyze those for adequacy of the safeguards. An associated computer program is under development. The proposed technique supports and extends the Layer of Protection Analysis application, especially for safety assurance assessment of risk-based determination for the process industries. A case study concerning HF alkylation plant illustrates the proposed method.     

Application of HS-SPME in the determination of potentially toxic organic compounds emitted from resin-based dental materials

Leaching of volatile substances from resin-based dental materials may have a potential impact on the biocompatibility as well as safety of these materials. Information from manufacturers on ingredients in the materials is very often incomplete. Patients and dentists may be in contact with components emitted from cured dental fillings or from substrates applied in their preparation. Therefore, determination of the components of these materials is necessary for better prevention from possible harmful effects caused by dental fillings. The aim of this work was the isolation and identification of organic compounds evolved from four commercial resin-modified glass-ionomer cements (resin-based dental materials applied in dentistry) by using an alternative method of volatile compounds analysis-HS-SPME (headspace-solid phase microextraction). Dental materials were heated in closed vial at various temperatures and volatile substances released into the headspace phase above the sample were isolated on a thin polymeric fibre placed in SPME syringe. Identification was performed by using the GC-MS (gas chromatography-mass spectrometry) technique. Almost 50 RMGIC (resin-modified glass-ionomer cement) components (monomers and additives) were identified. The main identified leachables were: iodobenzene (DPICls-diphenyliodonium chloride degradation product), camphorquinone (photo-initiator), tert-butyl-p-hydroxyanisole (inhibitor), 4-(dimethylamino)ethyl benzoate (co-initiator), ethylene glycol dimethacrylate (monomer).     

Field Trial of Biosparging with Oxygen for Bioremediation of Volatile Organic Compounds

Xpert Design & Diagnostics, LLC (XDD), & Conestoga‐Rovers and Associates (CRA) conducted a biosparging field trial at a Superfund site in New Jersey. The biosparging field trial proved that biosparging with oxygen was very effective in promoting the biological destruction of benzene. The approximately 265‐day period of oxygen injection successfully reduced benzene concentrations by several orders of magnitude, or even to non‐detect values, at least 40 feet from the point of injection. Through co‐precipitation of arsenic with oxidized iron, biosparging also effectively reduced total concentrations of arsenic and iron in groundwater. Based on the results of the biosparging field trial, the final remedy for the site has been amended to include the use of biosparging technology as an alternative to groundwater pumping and aboveground treatment in select locations. © 2001 John Wiley & Sons,Inc.     

Diffusive wave models for operational forecasting of channel routing at continental scale

Operational forecast models require robust, computationally efficient, and reliable algorithms. We desire accurate forecasts within the limits of the uncertainties in channel geometry and roughness because the output from these algorithms leads to flood warnings and a variety of water management decisions. The current operational Water Model uses the Muskingum-Cunge method, which does not account for key hydraulic conditions such as flow hysteresis and backwater effects, limiting its ability in situations with pronounced backwater effects. This situation most commonly occurs in low-gradient rivers, near confluences and channel constrictions, coastal regions where the combined actions of tides, storm surges, and wind can cause adverse flow. These situations necessitate a more rigorous flow routing approach such as dynamic or diffusive wave approximation to simulate flow hydraulics accurately. Avoiding the dynamic wave routing due to its extreme computational cost, this work presents two diffusive wave approaches to simulate flow routing in a complex river network. This study reports a comparison of two different diffusive wave models that both use a finite difference solution solved using an implicit Crank–Nicolson (CN) scheme with second-order accuracy in both time and space. The first model applies the CN scheme over three spatial nodes and is referred to as Crank–Nicolson over Space (CNS). The second model uses the CN scheme over three temporal nodes and is referred to as Crank–Nicolson over Time (CNT). Both models can properly account for complex cross-section geometry and variable computational points spacing along the channel length. The models were tested in different watersheds representing a mixture of steep and flat topographies. Comparing model outputs against observations of discharges and water levels indicated that the models accurately predict the peak discharge, peak water level, and flooding duration. Both models are accurate and computationally stable over a broad range of hydraulic regimes. The CNS model is dependent on the Courant criteria, making it less computational efficient where short channel segments are present. The CNT model does not suffer from that constraint and is, thus, highly computationally efficient and could be more useful for operational forecast models.     

Calcium amendment improved the performance of fragrant rice and reduced metal uptake under cadmium toxicity

Environmental Science and Pollution Research - Cadmium (Cd) toxicity has detrimental effects on plant metabolism and yield formation. This study examined the effects of Cd stress in rice and the...     

Graphene oxide as a tool for antibiotic-resistant gene removal: a review

Environmental pollutants, including antibiotics (ATBs), have become an increasingly common health hazard in the last several decades. Overdose and abuse of ATBs led to the emergence of antibiotic-resistant genes (ARGs), which represent a serious health threat. Moreover, water bodies and reservoirs are places where a wide range of bacterial species with ARGs originate, owing to the strong selective pressure from presence of ATB residues. In this regard, graphene oxide (GO) has been utilised in several fields including remediation of the environment. In this review, we present a brief overview of resistant genes of frequently used ATBs, their occurrence in the environment and their behaviour. Further, we discussed the factors influencing the binding of nucleic acids and the response of ARGs to GO, including the presence of salts in the water environment or water pH, because of intrinsic properties of GO of not only binding to nucleic acids but also catalysing their decomposition. This would be helpful in designing new types of water treatment facilities.

     

Understanding the source of water for selected springs within Mojave Trails National Monument,California

While water sources that sustain many of the springs in the Mojave Desert have been poorly understood, the desert ecosystem can be highly dependent on such resources. This evaluation updates the water resource forensics of Bonanza Spring, the largest spring in the southeastern Mojave Desert. The source of spring flow at Bonanza Spring was evaluated through an integration of published geologic maps, measured groundwater levels, water quality chemistry, and isotope data compiled from both published sources and new samples collected for water chemistry and isotopic composition. The results indicate that Bonanza Spring has a regional water source, in hydraulic communication with basin fill aquifer systems. Neighboring Lower Bonanza Spring appears to primarily be a downstream manifestation of surfacing water originally discharged from the Bonanza Spring source. Whereas other springs in the area, Hummingbird, Chuckwalla, and Teresa Springs, each appear to be locally sourced as “perched” springs. These conclusions have important implications for managing activities that have the potential to impact the desert ecosystem.