A Generic Bio-Economic Farm Model for Environmental and Economic Assessment of Agricultural Systems

Bio-economic farm models are tools to evaluate ex-post or to assess ex-ante the impact of policy and technology change on agriculture, economics and environment. Recently, various BEFMs have been developed, often for one purpose or location, but hardly any of these models are re-used later for other purposes or locations. The Farm System Simulator (FSSIM) provides a generic framework enabling the application of BEFMs under various situations and for different purposes (generating supply response functions and detailed regional or farm type assessments). FSSIM is set up as a component-based framework with components representing farmer objectives, risk, calibration, policies, current activities, alternative activities and different types of activities (e.g., annual and perennial cropping and livestock). The generic nature of FSSIM is evaluated using five criteria by examining its applications. FSSIM has been applied for different climate zones and soil types (criterion 1) and to a range of different farm types (criterion 2) with different specializations, intensities and sizes. In most applications FSSIM has been used to assess the effects of policy changes and in two applications to assess the impact of technological innovations (criterion 3). In the various applications, different data sources, level of detail (e.g., criterion 4) and model configurations have been used. FSSIM has been linked to an economic and several biophysical models (criterion 5). The model is available for applications to other conditions and research issues, and it is open to be further tested and to be extended with new components, indicators or linkages to other models.     

Effects of pH and microbial composition on odour in food waste composting

A major problem for composting plants is odour emission. Slow decomposition during prolonged low-pH conditions is a frequent process problem in food waste composting. The aim was to investigate correlations between low pH, odour and microbial composition during food waste composting. Samples from laboratory composting experiments and two large scale composting plants were analysed for odour by olfactometry, as well as physico-chemical and microbial composition. There was large variation in odour, and samples clustered in two groups, one with low odour and high pH (above 6.5), the other with high odour and low pH (below 6.0). The low-odour samples were significantly drier, had lower nitrate and TVOC concentrations and no detectable organic acids. Samples of both groups were dominated by Bacillales or Actinobacteria, organisms which are often indicative of well-functioning composting processes, but the high-odour group DNA sequences were similar to those of anaerobic or facultatively anaerobic species, not to typical thermophilic composting species. High-odour samples also contained Lactobacteria and Clostridia, known to produce odorous substances. A proposed odour reduction strategy is to rapidly overcome the low pH phase, through high initial aeration rates and the use of additives such as recycled compost.     

The effect of humic acid in chronic deoxynivalenol intoxication

Environmental Science and Pollution Research - The most common mycotoxin found in European foodstuffs, especially unprocessed grains, is deoxynivalenol (DON), which inhibits proteosynthesis and...     

Concentrations of selected trace elements in surface soils near crossroads in the city of Bratislava (the Slovak Republic)

Environmental Science and Pollution Research - It is well known that road transport emits various trace elements into the environment, which are deposited in soils in the vicinity of roads,...     

Ameliorative effects of deferiprone and tetraethylammonium salt of salinomycinic acid on lead-induced toxicity in mouse testes

Environmental Science and Pollution Research - In this study, we compare the effects of deferiprone (Def) and tetraethylammonium salt of salinomycinic acid (Sal) on lead (Pb)-induced toxicity in...     

Metabolomic analysis of the selection response of Drosophila melanogaster to environmental stress: are there links to gene expression and phenotypic traits?

We investigated the global metabolite response to artificial selection for tolerance to stressful conditions such as cold, heat, starvation, and desiccation, and for longevity in Drosophila melanogaster. Our findings were compared to data from other levels of biological organization, including gene expression, physiological traits, and organismal stress tolerance phenotype. Overall, we found that selection for environmental stress tolerance changes the metabolomic ¹H NMR fingerprint largely in a similar manner independent of the trait selected for, indicating that experimental evolution led to a general stress selection response at the metabolomic level. Integrative analyses across data sets showed little similarity when general correlations between selection effects at the level of the metabolome and gene expression were compared. This is likely due to the fact that the changes caused by these selection regimes were rather mild and/or that the dominating determinants for gene expression and metabolite levels were different. However, expression of a number of genes was correlated with the metabolite data. Many of the identified genes were general stress response genes that are down-regulated in response to selection for some of the stresses in this study. Overall, the results illustrate that selection markedly alters the metabolite profile and that the coupling between different levels of biological organization indeed is present though not very strong for stress selection at this level. The results highlight the extreme complexity of environmental stress adaptation and the difficulty of extrapolating and interpreting responses across levels of biological organization.     

Climate change mitigation and international finance: the effectiveness of the Clean Development Mechanism and the Global Environment Facility in India and Brazil

This study analyzes the effectiveness and efficiency of the two principal United Nations (UN) climate change mitigation finance mechanisms, the Clean Development Mechanism (CDM) and the Global Environment Facility (GEF). The realised abatement and costs of the two mechanisms in India and Brazil (using data from 28 GEF and 233 CDM project documents) are compared with theoretical marginal abatement cost curves, based on bottom-up technology studies. We find that both mechanisms have focused on negative and low-cost abatement potential but still leave substantial theoretical potential in this cost range untapped. CDM has more effectively harvested abatement potential of industrial gases and methane emissions, whereas GEF has more successfully targeted demand-side energy efficiency (EE) and transport emission reduction opportunities. CDM has excelled at capturing abatement potential in areas with a limited understanding of abatement, highlighting the shortcomings of theoretical estimates (such as Marginal Abatement Cost Curves) and the benefits of a market mechanism. In some sectors and technologies (particularly renewable energy), the two mechanisms overlapped, which suggests a need for better coordination in the future.     

Power matters in closing the phenotyping gap

Much of our understanding of physiology and metabolism is derived from investigating mouse mutants and transgenic mice, and open-access platforms for standardized mouse phenotyping such as the German Mouse Clinic (GMC) are currently viewed as one powerful tool for identifying novel gene-function relationships. Phenotyping or phenotypic screening involves the comparison of wild-type control mice with their mutant or transgenic littermates. In our study, we explored the extent to which standardized phenotyping will succeed in detecting biologically relevant phenotypic differences in mice generated and provided by different collaborators. We analyzed quantitative metabolic data (body mass, energy intake, and energy metabolized) collected at the GMC under the current workflow, and used them for statistical power considerations. Our results demonstrate that there is substantial variability in these parameters among lines of wild-type C57BL/6 (B6) mice from different sources. Given this variable background noise in mice that serve as controls, subtle phenotypes in mutant or transgenic littermates may be overlooked. Furthermore, a phenotype observed in one cohort of a mutant line may not be reproducible (to the same extent) in mice coming from a different environment or supplier. In the light of these constraints, we encourage researchers to incorporate information on intrastrain variability into future study planning, or to perform advanced hierarchical analyses. Both will ultimately improve the detectability of novel phenotypes by phenotypic screening. Carola W. Meyer and Ralf Elvert contributed equally to this work.     

The Victorian legislative framework for testing drivers for impairment caused by drugs other than alcohol: an evaluation of the characteristics of drivers detected from 2000 to 2005

On December 1, 2000, new legislation came into force in Victoria, Australia, that involved a framework for the procedure to be followed by the police for the detection of drivers impaired by drugs other than alcohol. An integral part of the procedure is the use of performance tests known as the standardized field sobriety tests (SFSTs) and the analysis of blood samples for the presence of drugs other than alcohol. This paper outlines the new legislative framework and the drug impairment detection procedures currently in place in Victoria. This paper also evaluates the data collected using the framework for the first five years since implementation in Victoria.