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.

     

Microbial degradation op tripluralin by aspergillus carneus,fusarium oxysporum and trichoderma viride ∗

Abstract

³H‐Trifluralin was synthesized by condensation of ³H‐4‐chloro‐3,5‐dinitro‐α, α, α‐trifluorotoluene with di‐n‐propylamine.

After incubation of trifluralin with Aspergillus carneus, Fusarium oxysporum and Trichoderma viride for 10 days, a small percentage (less than 10%) of unchanged herbicide was recovered in the extractable fraction. This indicates a fairly rapid degradation of the herbicide by the fungal species. Other than trifluralin, the culture medium contained at least five labelled products: 2, 6‐dinitro‐N‐n‐propyl‐α, α, α‐tri‐fluoro‐p‐toluidine; 2, 6‐dinitro‐α, α, α‐trifluoro‐p‐toluidine; 2‐amino‐6‐nitro‐α, α,‐trifluoro‐p‐toluidine, 2, 6‐dinitro‐4‐trifluoromethyl phenol and a major polar product which constituted more than 50% of the total extractable transformation products. A pathway, which similates that of aerobic degradation of the herbicide in soil, is suggested for the microbiological degradation of trifluralin.     

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.     

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.     

The trophic status of Suwałki Landscape Park lakes based on selected parameters (NE Poland)

This study describes changes in the trophic status of 12 lakes within Suwa?ki Landscape Park (SLP). All of the trophic classifications of the lakes were based on the trophic continuum division. Trophic status was determined by means of multiparameter indices using several diverse criteria. In this study, the assessment of the trophic status of lakes included water quality; abundance and biomass of bacterioplankton, phytoplankton, and zooplankton; and primary production of phytoplankton. The Carlson trophic state index (TSI) describes the level of water fertility and indicated the dominance of moderately eutrophic waters. Lakes Perty, Jeglówek, and Hańcza have a trophic status that indicates mesotrophy (TSI <50). The trophic status of the studied lakes was determined based on the bacterial abundance and clearly showed a lack of oligotrophic lakes in SLP. Based on the number of bacteria, only Lake Szurpi?y can be classified as β-mesotrophic, whereas Lake Linówek can be characterized as hypertrophic with some features typical for humic waters. The greatest value of gross primary production was observed in Lake Linówek (126.4 mg C/m³/h). The phytoplankton trophy index varied from 1.59 to 2.28, and its highest value, which indicated eutrophy, was determined for Lake Udziejek. In the case of Lakes Hańcza, Szurpi?y, Perty, Jeglówek, and Kojle, the index ranged from 1.25 to 1.74, which indicated mesotrophy. The majority of the lakes were classified as mesoeutrophic (1.75–2.24). The highest trophic status was assessed for lakes with a marked dominance of cyanobacteria (Lake Przechodnie, Lake Krajwelek, Lake Udziejek, and Lake Pogorza?ek), which is commonly recognized as an indicator of high trophic status. Considering all of the indices of trophic status, the analysis of rotifer community structure indicates that the studied group of lakes is mesoeutrophic or eutrophic. The values of crustacean zooplankton indices indicated that the trophic status of the studied lakes was close to that determined using a TSI. The parameters of zooplankton abundance and species structure allowed for the observance of changes in the tropic levels of lakes, which are difficult to detect by a chemical assay alone.     

Modeling the dispersion of drilling muds using the bblt model: the effects of settling velocity

The benthic boundary layer transport (bblt) model was widely used in the Atlantic Canadian offshore region to assess the potential impact zones from drilling wastes discharges from offshore oil and gas drilling. The current version of the bblt uses a single-class settling velocity scenario, which may affect its performance, as settling velocity is size, shape, and material dependent. In this study, the effects of settling velocity on bblt predictions were assessed by replacing this single-class settling velocity scenario with a multi-class size-dependent settling velocity scenario. The new scenario was used in a hypothetical study to simulate the dispersion of barite and fine-grained drilling cuttings. The study showed that the effects of settling velocity on bblt predictions are spatial, temporal, and material dependent.     

Integration of Wireless Sensor Networks into Cyberinfrastructure for Monitoring Hawaiian “Mountain-to-Sea” Environments

Monitoring the complex environmental relationships and feedbacks of ecosystems on catchment (or mountain)-to-sea scales is essential for social systems to effectively deal with the escalating impacts of expanding human populations globally on watersheds. However, synthesis of emerging technologies into a robust observing platform for the monitoring of coupled human-natural environments on extended spatial scales has been slow to develop. For this purpose, the authors produced a new cyberinfrastructure for environmental monitoring which successfully merged the use of wireless sensor technologies, grid computing with three-dimensional (3D) geospatial data visualization/exploration, and a secured internet portal user interface, into a working prototype for monitoring mountain-to-sea environments in the high Hawaiian Islands. A use-case example is described in which native Hawaiian residents of Waipa Valley (Kauai) utilized the technology to monitor the effects of regional weather variation on surface water quality/quantity response, to better understand their local hydrologic cycle, monitor agricultural water use, and mitigate the effects of lowland flooding.