Predicting molybdenum toxicity to higher plants: Estimation of toxicity threshold values

Four plant species (oilseed rape, Brassica napus L.; red clover, Trifolium pratense L.; ryegrass, Lolium perenne L.; and tomato, Lycopersicon esculentum L.) were tested on ten soils varying widely in soil properties to assess molybdenum (Mo) toxicity. A larger range (66-fold-609-fold) of added Mo concentrations resulting in 50% inhibition of yield (ED₅₀) was found among soils than among plant species (2-fold-38-fold), which illustrated that the soils differed widely in the expression of Mo toxicity. Toxicity thresholds based on soil solution Mo narrowed the variation among soils compared to thresholds based on added Mo concentrations. We conclude that plant bioavailability of Mo in soil depends on Mo solubility, but this alone did not decrease the variability in observed toxicity enough to be used in risk assessment and that other soil properties influencing Mo toxicity to plants need to be considered.     

BIOAVAILABILITY OF CALCIUM FROM SWEETPOTATO AND SOY FLOUR SUPPLEMENTED DIETS IN HAMSTERS

The bioavailability of calcium from two varieties of sweetpotatoes and supplementation of sweetpotatoes with soy flour was investigated in hamsters using plasma calcium concentration and femur calcium content as indicators. Five different diets were fed to five groups of animals for 28 days. There was no significant difference in plasma calcium concentrations of hamsters in all the diet groups. However, the femur calcium content of hamsters with transgenic sweetpotato flour (TSPF) and parent nontransgenic (from which transgenic was produced) sweetpotato flour (NTSPF) diets was significantly higher than that of the transgenic sweetotato flour supplemented with soy flour (TSPF+SF) and parent nontransgenic sweetpotato flour supplemented with soy flour (NTSPF+SF) diets. The relative bioavailability of calcium from the control (100%), TSPF+SF (30%), NTSPF+SF (23%), TSPF (57%) and NTSPF (46%) indicated that sweetpotatoes could be the better source of calcium, however, supplementation with soy flour might reduce the bioavailability of calcium.     

Priority screening of toxic chemicals and industry sectors in the U.S. toxics release inventory: a comparison of the life cycle impact-based and risk-based assessment tools developed by U.S. EPA

Life Cycle Impact Assessment (LCIA) and Risk Assessment (RA) employ different approaches to evaluate toxic impact potential for their own general applications. LCIA is often used to evaluate toxicity potentials for corporate environmental management and RA is often used to evaluate a risk score for environmental policy in government. This study evaluates the cancer, non-cancer, and ecotoxicity potentials and risk scores of chemicals and industry sectors in the United States on the basis of the LCIA- and RA-based tools developed by U.S. EPA, and compares the priority screening of toxic chemicals and industry sectors identified with each method to examine whether the LCIA- and RA-based results lead to the same prioritization schemes. The Tool for the Reduction and Assessment of Chemical and other environmental Impacts (TRACI) is applied as an LCIA-based screening approach with a focus on air and water emissions, and the Risk-Screening Environmental Indicator (RSEI) is applied in equivalent fashion as an RA-based screening approach. The U.S. Toxic Release Inventory is used as the dataset for this analysis, because of its general applicability to a comprehensive list of chemical substances and industry sectors. Overall, the TRACI and RSEI results do not agree with each other in part due to the unavailability of characterization factors and toxic scores for select substances, but primarily because of their different evaluation approaches. Therefore, TRACI and RSEI should be used together both to support a more comprehensive and robust approach to screening of chemicals for environmental management and policy and to highlight substances that are found to be of concern from both perspectives.     

Effect of electrokinetic transport on the vulnerability of PAH-degrading bacteria in a model aquifer

There has been increasing interest in employing electro-bioremediation, a hybrid technology of bioremediation and electrokinetics, to overcome the low bioavailability of hydrophobic organic contaminants (HOC) by homogenizing sorption-retarded HOC and immobilised microorganisms. Present electro-remediation approaches mainly aim at macroscale pollutant extraction and tend to neglect possible impacts of direct current (DC) on the physiology of microorganisms. The effect of weak electric fields (X = 1 V cm⁻¹) on the fitness of electrokinetically dispersed fluorene-degrading Sphingomonas sp. LB126 in bench-scale model aquifers was investigated by flow cytometry using propidium iodide (PI) as an indicator that distinguishes between PI-permeable (cells with porous membranes, i.e. dead or vulnerable) and PI-impermeable bacteria. After 15.5 h of DC treatment 56% of all cells recovered were dispersed at the centimetre scale relative to 29% in the absence of DC. There was no overall negative effect of the 15.5-h DC treatment on cell vulnerability, as 7.0% of the DC-treated bacteria exhibited PI-staining compared to 6.5% of the control population. Minor differences were observed in the subpopulation that had been mobilised by electroosmosis with an approximately twofold increase in the percentage of PI-stained cells relative to the control. Enhanced PI staining did not correlate with reduced culturability of the cells on rich-medium agar plates. Relative to the control, DC-treated cells mobilised by electroosmosis were threefold more culturable, confirming earlier data that that PI-cell membrane permeability does not always indicate reduced viability of oligotrophic environmental bacteria. Our findings suggest that electrokinetics is a valuable mechanism to transport viable and culturable polycyclic aromatic hydrocarbon (PAH)-degrading bacteria in soil or sediments.     

Testing the Stochastic Dynamic Methodology (StDM) as a management tool in a shallow temperate estuary of south Europe (Mondego, Portugal)

A long-term monitoring program has been carried out since the early 1990s in the Mondego estuary, on Portugal's west coast, which is presently under heavy human pressure. In this shallow warm-temperate estuary, a significant macroalgal proliferation has been observed, which is a clear sign of nutrient enrichment. As a result of competition with algae, the extension of the seagrass meadows (mainly Zostera noltii) has been reduced. The present paper examined the applicability of a holistic Stochastic Dynamic Methodology (StDM) in predicting the tendencies of trophic key-components (macrophytes, macroalgae, benthic macroinvertebrate and wading birds) as a response to the changes in estuarine environmental conditions. The StDM is a sequential modelling process developed in order to predict the ecological status of changed ecosystems, from which management strategies can be designed. The data used in the dynamic model construction included true gradients of environmental changes and was sampled from January 1993 to September 1995 and from December 1998 to December 2005. The dynamic model developed was preceded by a conventional multivariate statistical procedure performed to discriminate the significant relationships between the selected ecological components. The model validation was based on independent data collected from January 1996 to January 1997 and from February 1999 to April 2000 for all the state variables considered. Overall, the simulation results are encouraging since they seem to demonstrate the StDM reliability in capturing the trophic dynamics of the studied estuary, by predicting the behavioural pattern for the most part of the components selected, with a focus on the Zostera noltii meadows recovery after the implementation of important management measures.     

Bayesian Networks and Adaptive Management of Wildlife Habitat

Abstract: Adaptive management is an iterative process of gathering new knowledge regarding a system's behavior and monitoring the ecological consequences of management actions to improve management decisions. Although the concept originated in the 1970s, it is rarely actively incorporated into ecological restoration. Bayesian networks (BNs) are emerging as efficient ecological decision‐support tools well suited to adaptive management, but examples of their application in this capacity are few. We developed a BN within an adaptive‐management framework that focuses on managing the effects of feral grazing and prescribed burning regimes on avian diversity within woodlands of subtropical eastern Australia. We constructed the BN with baseline data to predict bird abundance as a function of habitat structure, grazing pressure, and prescribed burning. Results of sensitivity analyses suggested that grazing pressure increased the abundance of aggressive honeyeaters, which in turn had a strong negative effect on small passerines. Management interventions to reduce pressure of feral grazing and prescribed burning were then conducted, after which we collected a second set of field data to test the response of small passerines to these measures. We used these data, which incorporated ecological changes that may have resulted from the management interventions, to validate and update the BN. The network predictions of small passerine abundance under the new habitat and management conditions were very accurate. The updated BN concluded the first iteration of adaptive management and will be used in planning the next round of management interventions. The unique belief‐updating feature of BNs provides land managers with the flexibility to predict outcomes and evaluate the effectiveness of management interventions.     

Using the ECLPSS software environment to build a spatially explicit component-based model of ozone effects on forest ecosystems

We have developed a modeling framework to support grid-based simulation of ecosystems at multiple spatial scales, the Ecological Component Library for Parallel Spatial Simulation (ECLPSS). ECLPSS helps ecologists to build robust spatially explicit simulations of ecological processes by providing a growing library of reusable interchangeable components and automating many modeling tasks. To build a model, a user selects components from the library, and then writes new components as needed. Some of these components represent specific ecological processes, such as how environmental factors influence the growth of individual trees. Other components provide simulation support such as reading and writing files in various formats to allow inter-operability with other software. The framework manages components and variables, the order of operations, and spatial interactions. The framework provides only simulation support; it does not include ecological functions or assumptions. This separation allows biologists to build models without becoming computer scientists, while computer scientists can improve the framework without becoming ecologists. The framework is designed to operate on multiple platforms and be used across networks via a World Wide Web-based user interface. ECLPSS is designed for use with both single processor computers for small models, and multiple processors in order to simulate large regions with complex interactions among many individuals or ecological compartments. To test Version 1.0 of ECLPSS, we created a model to evaluate the effect of tropospheric ozone on forest ecosystem dynamics. This model is a reduced-form version of two existing models: , which represents an individual tree, and , which represents forest stand growth and succession. This model demonstrates key features of ECLPSS, such as the ability to examine the effects of cell size and model structure on model predictions.     

Participation for understanding: an interactive method

INTRODUCTION: There are many available models that help evaluate the effectiveness of safety and health measures, but many are complex and require input from many departments within an organization. There is a need to develop a more user-friendly model. METHOD: A participative model was developed that involves face-to-face interviewers with workers, maintenance department, purchasing department and health and safety experts. They were asked about costs, efforts, benefits, and effects of gauging the effects of prevention efforts. RESULTS: Cost effectiveness analyses are essential in all cases and can include whatever the end-user requires, whether it is a small or lasting improvement. Having management participate helps validate the data. CONCLUSIONS: Organizations who collaborate with someone with at least some skill in cost-benefit evaluations will find that they will be able to establish policies and procedures from the data. The end result is a calculation that is understood by all involved.     

The potential-method--an economic evaluation tool

INTRODUCTION: Measuring the effect of safety and health on production is a difficult value to gauge. METHOD: This article introduces the Potential, which is an instrument for economic analysis that incorporates different changes in conditions. RESULTS: While there are a number of problems associated with methods to determine these calculations, this method is a good indicator of the effects of safety and health and produces more than 300 variables with much less input. IMPACT ON INDUSTRY: Organizations can use this method effectively to determine how safety and health measure can improve their bottom line. A positive business case is highlighted.     

Review of water-energy-food Nexus tools to improve the Nexus modelling approach for integrated policy making

The synergies and trade-offs between the water, energy, and food sectors are represented by the Water-Energy-Food Nexus. The Nexus Approach is an integrated decision making practice that can be used by policy makers to optimize these synergies and manage trade-offs. In this paper, the direction of the Nexus Approach regarding the development of modelling tools is explored. The objective of this paper is to review the existing Nexus modelling tools used for integrated policy making to determine and to help policy makers, practitioners, and agencies trying to implement the Nexus Approach to identify a tool that is most suited to their modelling needs. The predominant capabilities of the current tools lie in the understanding of Nexus complexity, consideration of financial elements in the tools, recognition of the importance of multiple Nexus Approach directions, incorporation of different time scales, and enhanced tool accessibility. The main limitations are the extensive data requirements of current tools, and the poor synergy between tools assessing individual Nexus areas. This enhanced overview of the existing tools allows policy makers to maximize the synergies between the Nexus areas, to avoid consumption dilemmas, and to facilitate sustainable development.