Assessing the application of an additive model to estimate toxicity of a complex effluent

A number of industries monitor levels of chemicals in their effluent, but few have undertaken prolonged biological monitoring of this wastewater. The focus of the present study was to determine whether past chemical data for effluent from a lead smelter could be used to estimate its past toxicity. Since the interactive effects of metals in effluents are often assumed to be additive, it was hypothesized that an additive model, 100/[sigma(metal concentration in effluent/EC50 for individual metal)], could be used to generate an EC50 from chemical data (where EC50 is the concentration of test material that affects 50% of the test organisms). To test the approach, a larval development toxicity test with the marine polychaete, Galeolaria caespitosa, was used to test 26 separate samples of effluent from a lead smelter, generating empirical EC50 values. EC50 values for each individual metal in the effluent were also generated using the larval development toxicity test. The concentrations of trace metals in each effluent sample were determined and, using the additive model, EC50 values were calculated. For the majority of effluent samples tested, the additive model underestimated toxicity, suggesting the presence of additional unidentified contaminants in the effluent samples. Additionally, a nonlinear rather than linear regression curve was found to best describe the relationship between the model and empirically derived EC50 values. This relationship was then used to estimate past trends in toxicity of the smelter effluent. Forty-eight percent of the variability in measured toxicity was explained by the model, with the model underestimating toxicity in the majority of samples.     

Risk assessment of antagonistic hazards

This paper considers the risk to major hazard plant from terrorists deliberately causing catastrophic industrial accidents. The United States of America Department of Justice [Assessment of the increased risk of terrorist or other criminal activity associated with posting off-site consequence analysis information on the internet, 2000] reports that “breaching a containment vessel of an industrial facility with an explosive or otherwise causing a chemical release may appear relatively simple to…a terrorist”. They concluded that the risk of such action is “real and credible”.

Analysis of terrorism is often hampered by its being described as ‘irrational’; one corollary would be that it is unpredictable. However, terrorism may usefully be treated as a rational behaviour and in doing so it becomes possible to assess the risks it causes.

We analyse the vulnerability of major hazard plant to terrorist attack and identify nine factors (access, security, visibility, opacity, secondary hazard, robustness, law enforcement response, victim profile, and political value) that might be used as a starting point for more formal risk assessment and management.     

Brood comb as a humidity buffer in honeybee nests

Adverse environmental conditions can be evaded, tolerated or modified in order for an organism to survive. During their development, some insect larvae spin cocoons which, in addition to protecting their occupants against predators, modify microclimatic conditions, thus facilitating thermoregulation or reducing evaporative water loss. Silk cocoons are spun by honeybee (Apis mellifera) larvae and subsequently incorporated into the cell walls of the wax combs in which they develop. The accumulation of this hygroscopic silk in the thousands of cells used for brood rearing may significantly affect nest homeostasis by buffering humidity fluctuations. This study investigates the extent to which the comb may influence homeostasis by quantifying the hygroscopic capacity of the cocoons spun by honeybee larvae. When comb containing cocoons was placed at high humidity, it absorbed 11% of its own mass in water within 4 days. Newly drawn comb composed of hydrophobic wax and devoid of cocoons absorbed only 3% of its own mass. Therefore, the accumulation of cocoons in the comb may increase brood survivorship by maintaining a high and stable humidity in the cells.     

Visualizing different uranium oxidation states during the surface alteration of uraninite and uranium tetrachloride

Low-temperature alteration reactions on uranium phases may lead to the mobilization of uranium and thereby poses a potential threat to humans living close to uranium-contaminated sites. In this study, the surface alteration of uraninite (UO₂) and uranium tetrachloride (UCl₄) in air atmosphere was studied by confocal laser scanning microscopy (CLSM) and laser-induced fluorescence spectroscopy using an excitation wavelength of 408 nm. It was found that within minutes the oxidation state on the surface of the uraninite and the uranium tetrachloride changed. During the surface alteration process U(IV) atoms on the uraninite and uranium tetrachloride surface became stepwise oxidized by a one-electron step at first to U(V) and then further to U(VI). These observed changes in the oxidation states of the uraninite surface were microscopically visualized and spectroscopically identified on the basis of their fluorescence emission signal. A fluorescence signal in the wavelength range of 415–475 nm was indicative for metastable uranium(V), and a fluorescence signal in the range of 480–560 nm was identified as uranium(VI). In addition, the oxidation process of tetravalent uranium in aqueous solution at pH 0.3 was visualized by CLSM and U(V) was fluorescence spectroscopically identified. The combination of microscopy and fluorescence spectroscopy provided a very convincing visualization of the brief presence of U(V) as a metastable reaction intermediate and of the simultaneous coexistence of the three states U(IV), U(V), and U(VI). These results have a significant importance for fundamental uranium redox chemistry and should contribute to a better understanding of the geochemical behavior of uranium in nature. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Manure application technology in reduced tillage and forage systems: a review

Managing manure in reduced tillage and forage systems presents challenges, as incorporation by tillage is not compatible. Surface-applied manure that is not quickly incorporated into soil provides inefficient delivery of manure nutrients to crops due to environmental losses through ammonia (NH3) volatilization and nutrient losses in runoff, and serves as a major source of nuisance odors. An array of technologies now exist to facilitate the incorporation of liquid manures into soil with restricted or minor soil disturbance, some of which are new: shallow disk injection; chisel injection; aeration infiltration; pressure injection. Surface banding of manure inforages decreases NH3 emissions relative to surface broadcasting, as the canopy can decrease wind speed over the manure, but greater reductions can be achieved with manure injection. Soilaeration is intended to hasten manure infiltration, but its benefits are not consistent and may be related to factors such as soildrainage characteristics. Work remains to be done on refining its method of use and timing relative to manure application, which may improve its effectiveness. Placing manure under the soil surface efficiency by injection offers much promise to improve N use efficiency through less NH3 volatilization, reduced odors and decreased nutrient losses in runoff, relative to surface application. We identified significant gaps in our knowledge as manyof these technologies are relatively new, and this should help target future research efforts including environmental, agronomic, and economic assessments.     

A novel statistical method for classifying habitat generalists and specialists

We develop a novel statistical approach for classifying generalists and specialists in two distinct habitats. Using a multinomial model based on estimated species relative abundance in two habitats, our method minimizes bias due to differences in sampling intensities between two habitat types as well as bias due to insufficient sampling within each habitat. The method permits a robust statistical classification of habitat specialists and generalists, without excluding rare species a priori. Based on a user-defined specialization threshold, the model classifies species into one of four groups: (1) generalist; (2) habitat A specialist; (3) habitat B specialist; and (4) too rare to classify with confidence. We illustrate our multinomial classification method using two contrasting data sets: (1) bird abundance in woodland and heath habitats in southeastern Australia and (2) tree abundance in second-growth (SG) and old-growth (OG) rain forests in the Caribbean lowlands of northeastern Costa Rica. We evaluate the multinomial model in detail for the tree data set. Our results for birds were highly concordant with a previous nonstatistical classification, but our method classified a higher fraction (57.7%) of bird species with statistical confidence. Based on a conservative specialization threshold and adjustment for multiple comparisons, 64.4% of tree species in the full sample were too rare to classify with confidence. Among the species classified, OG specialists constituted the largest class (40.6%), followed by generalist tree species (36.7%) and SG specialists (22.7%). The multinomial model was more sensitive than indicator value analysis or abundance-based phi coefficient indices in detecting habitat specialists and also detects generalists statistically. Classification of specialists and generalists based on rarefied subsamples was highly consistent with classification based on the full sample, even for sampling percentages as low as 20%. Major advantages of the new method are (1) its ability to distinguish habitat generalists (species with no significant habitat affinity) from species that are simply too rare to classify and (2) applicability to a single representative sample or a single pooled set of representative samples from each of two habitat types. The method as currently developed can be applied to no more than two habitats at a time.     

基于供应链和可拓决策的食品安全预警模型及其应用

为提高食品安全预警能力,改善食品安全状况,以食品原料供应环境质量、生产加工、流通加工、销售食品质量、食品安全管理与监测作为食品安全预警的关键因素,提出一种基于供应链和可拓决策的食品安全预警模型。从供应链的角度建立食品安全预警指标体系,确定食品安全的经典域、节域和预警对象;建立食品安全预警模型并给出食品安全预警的方法和步骤;结合A省2010年的食品安全数据,定量评价A省食品安全预警状态,结合模型评价结果进行单指标和综合安全预警分析,验证该模型的合理性和适用性。研究结果表明:针对食品安全状况与预警特征,运用基于供应链和可拓决策的食品安全预警模型,能够对食品安全状态进行快速判断并有效预警。     

Implementing REDD+ (Reducing Emissions from Deforestation and Degradation): evidence on governance,evaluation and impacts from the REDD-ALERT project

The REDD-ALERT (Reducing Emissions from Deforestation and Degradation from Alternative Land Uses in the Rainforests of the Tropics) project started in 2009 and finished in 2012, and had the aim of evaluating mechanisms that translate international-level agreements into instruments that would help change the behaviour of land users while minimising adverse repercussions on their livelihoods. Findings showed that some developing tropical countries have recently been through a forest transition, thus shifting from declining to expanding forests at a national scale. However, in most of these (e.g. Vietnam), a significant part of the recent increase in national forest cover is associated with an increase in importation of food and timber products from abroad, representing leakage of carbon stocks across international borders. Avoiding deforestation and restoring forests will require a mixture of regulatory approaches, emerging market-based instruments, suasive options, and hybrid management measures. Policy analysis and modelling work showed the high degree of complexity at local levels and highlighted the need to take this heterogeneity into account—it is unlikely that there will be a one size fits all approach to make Reducing Emissions from Deforestation and Degradation (REDD+) work. Significant progress was made in the quantification of carbon and greenhouse gas (GHG) fluxes following land-use change in the tropics, contributing to narrower confidence intervals on peat-based emissions and their reporting standards. There are indications that there is only a short and relatively small window of opportunity of making REDD+ work—these included the fact that forest-related emissions as a fraction of total global GHG emissions have been decreasing over time due to the increase in fossil fuel emissions, and that the cost efficiency of REDD+ may be much less than originally thought due to the need to factor in safeguard costs, transaction costs and monitoring costs. Nevertheless, REDD+ has raised global awareness of the world’s forests and the factors affecting them, and future developments should contribute to the emergence of new landscape-based approaches to protecting a wider range of ecosystem services.