Presence of erm genes among macrolide-resistant Gram-positive bacteria isolated from Danish farm soil

The presence of erm genes was investigated among macrolide-resistant Gram-positive bacteria isolated from soil samples collected from four Danish farms that had been treated with animal waste. Soil samples were collected before, a few days after spread and 1 1/2 months and 5 months later. In 33% (9/27) of these isolates, an erm gene was detected using PCR. Eight isolates were positive for erm(B) and one isolate was positive for erm(C). No isolates contained erm(A), erm(D) or erm(F). The positive isolates were identified to genus level. Two erm(B) positive isolates were identified as Enterococcus spp., and the erm(C)-positive isolate as a Streptococcus spp., probably indicating survival from animal waste. The remaining six erm(B) positive isolates all belonged to the Bacillus cereus group. The erm(B) gene has not previously been identified in B. cereus but is frequently found among enterococci. This result could indicate horizontal transfer from bacteria of animal origin to indigenous soil bacteria.     

Public Participation and Local Environmental Planning: the collective action problem and the potential of social capital

Expanding the opportunities for public participation in environmental planning is not always the best option. Starting from an institutional public choice analysis of public participation in terms of the collective action problem, this paper emphasises the roots of participatory activities in the incentive structures facing potential participants. It then goes on to consider the strategies that may be adopted for encouraging greater public involvement and looks particularly to the social capital literature for suggestions of how institutional redesign may alter these incentive structures. The paper concludes by distinguishing three different modes of environmental planning, in terms of the rationale for participation, the severity of the collective action problem and the associated participatory strategy that can be adopted.     

Modeling the contribution of speeding and impaired driving to insurance claim counts and costs when contributing factors are unknown

PROBLEM: There are no specific indicators for distinguishing insurance claims related to speeding and impaired driving in the information warehouse at the Insurance Corporation of British Columbia. Contributing factors are only recorded for that part of the claim data that is also reported by the police. Most published statistics on crashes that are related to alcohol or speeding are based on police-reported data, but this represents only a fraction of all incidents. METHOD: This paper proposes surrogate models to estimate the counts and the average costs associated with speeding and impaired driving to insurance claims when contributing factors are unknown. Using police-reported data, classification rules and logistic regression models are developed to form such estimates. One approach applies classification rules to categorize insurance claims into those related to speeding, impaired driving, and other factors. The counts and the costs of insurance claims for each of these strata and overall are then estimated. A second method models the probability that an insurance claim is related to speeding or impaired driving using logistic regression and uses this to estimate the overall counts and the average costs of the claims. The two methods are compared and evaluated using simulation studies. RESULTS: The logistic regression model was found to be superior to the classification model for predicting insurance claim counts by category, but less efficient at predicting average claim costs. IMPACT: Having estimates of counts and costs of insurance claims related to impaired driving or speeding for all reported crash events provides a more accurate basis for policy-makers to plan changes and benefits of road safety programs.     

Estimating the contributions of speeding and impaired driving to insurance claim cost

INTRODUCTION: Logistic regression modelling of crash counts likely associated with speeding and impaired driving was earlier found [Zheng, Y., Cooper, P. J., & Dean, C. B. (2007). Modeling the contribution of speeding and impaired driving to insurance claim counts and costs when contributing factors are unknown. Journal of Safety Research, 38(1)] to successfully predict known outcomes in a series of simulations, but the same types of models did not accurately predict average crash costs. The aim of the study reported here was to develop a means to adjust classification model results that would improve their cost-predicting efficiency. METHOD: A classification modelling process was adjusted at the back-end using non-linear optimization to rationalize the classified proportions with the true proportions when the model was applied to representative subsets of the training data. Corrections were developed to account for cost (severity) differences arising from the classification process that were not due to true variations. The process was then applied to insurance claim test data where crash contributors were unknown. RESULTS: The optimization and severity correction procedure resulted in substantial improvement in average crash cost prediction for both impaired and unsafe speed collision involvements. The error measured against true values in 20 simulations was about half for the adjusted classification model of what it was for either unadjusted classification or logistic regression models. CONCLUSIONS: Non-linear optimization of classification matrices appears to be a workable tool for improving the predictive efficiency of models where desired outcomes represent average characteristics of records as compared to simple counts or proportions. IMPACT ON INDUSTRY: Using the methodology on a full-year of insurance claim data indicated that reliance on police-reported records alone would have underestimated the total cost of unsafe speed and impaired crashes by about 40%. Since most jurisdictions use police data to base policy decisions and set program spending around such safety issues, this finding has important implications.     

Intra- and interspecific differences of 10 barley and 10 tomato cultivars in response to short-time UV-B radiation: A study analysing thermoluminescence, fluorescence, gas-exchange and biochemical parameters

The impact of UV-B radiation on 10 genotypically different barley and tomato cultivars was tested in a predictive study to screen for potentially UV-tolerant accessions and to analyze underlying mechanisms for UV-B sensitivity. Plant response was analyzed by measuring thermoluminescence, fluorescence, gas exchange and antioxidant status. Generally, barley cultivars proved to be much more sensitive against UV-B radiation than tomato cultivars. Statistical cluster analysis could resolve two barley groups with distinct differences in reaction patterns. The UV-B sensitive group showed a stronger loss in PSII photochemistry and a lower gas-exchange performance and regulation after UV-B radiation compared to the more tolerant group. The results indicate that photosynthetic light and dark reactions have to play optimally in concert to render plants more tolerant against UV-B radiation. Hence, measuring thermoluminescence/fluorescence and gas exchange in parallel will have much higher potential in identifying tolerant cultivars and will help to understand the underlying mechanisms.     

Potential impact model to assess agricultural pressure to landscape ecological functions

Conservation and protection of soil and water resources and visual aspects of landscape, as well as the promotion of biodiversity, are some of the central tasks of environmental policy development and social politics in the future. One of the main questions is: ‘which agricultural systems are able to guarantee sustained resource-conserving land use?’ Based on the ecological risk concepts of the 1970s and 1980s, a potential impact model was developed using a universal assessment algorithm derived from fuzzy logic. The model estimated the potential impact of agricultural land use on ecosystem function using a few resource indicators. Intervention intensities of agricultural land-use are set in relation to site conditions and aggregated for each of several defined potential impact categories. The interpretation with respect to risk and the calculation of potential impact values are explained.     

Organic carbon stratification and size distribution of three typical paddy soils from Taihu Lake region, China

Developing realistic soil carbon (C) sequestration strategies for China’s sustainable agriculture relies on accurate estimates of the amount, retention and turnover rates of C stored in paddy soils. Available C estimates to date are predominantly for the tilled and flood-irrigated surface topsoil (ca. 30 cm). Such estimates cannot be used to extrapolate to soil depths of 100 cm since soil organic carbon (SOC) generally shows a sharp decrease with depth. In this research, composite soil samples were collected at several depths to 100 cm from three representative paddy soils in the Taihu Lake region, China. Soil organic carbon distribution in the profiles and in aggregate-size fractions was determined. Results showed that while SOC decreased exponentially with depth to 100 cm, a substantial proportion of the total SOC (30%–40%) is stored below the 30 cm depth. In the carbon-enriched paddy topsoils, SOC was found to accumulate preferentially in the 2–0.25 and 0.25–0.02 mm aggregate size fractions. σ13C analysis of the coarse micro-aggregate fraction showed that the high degree of C stratification in the paddy topsoil was in agreement with the occurrence of lighter @1313C in the upper 30 cm depth. These results suggest that SOC stratification within profiles varies with di erent pedogenetical types of paddy soils with regards to clay and iron oxyhydrates distributions. Sand-sized fractions of aggregates in paddy soil systems may play a very important role in carbon sequestration and turnover, dissimilar to other studied agricultural systems.     

Regionale Klimatrends mit Hilfe der phänologischen Uhr, dargestellt am Beispiel Rheinland-Pfalz

Aims and Scope

Over recent decades, the climate has changed. Up to now this statement has been made predominantly for the global and/or continental area. What, however, is the situation regarding the climatic trend at the regional scale? Is it already possible to show effects of a climate change in small-scale landscape structures? These questions were addressed looking at the example of the situation in the federal state of Rhineland-Palatinate (Germany).

Methods

Phenological data of plants of the last 50 years from a total of 386 stations of the German Weather Service (DWD) were evaluated. The timing of the different plant phases, beginning of the foliation and plant senescence in autumn, flowering and the first ripening of the fruits had to be registered for different agricultural crops, wild plants, ornamental woods as well as fruit trees. The analysed data material was used to develop the threefold phenological clock (DPU).

Results

Summarising the findings of the DPU for the 15 evaluated nature districts of Rhineland-Palatinate according to individual seasons, which were defined in generic terms as spring, summer, autumn and winter, a tendency of a prematuring of the spring, a prolongation of the autumn as well as a shortening of the winter is evident. From a regional point of view, on the other hand, in individual nature districts such as the ‘Westerwald’ and the ‘Bergisch-Sauerländische Gebirge’, winter seasons are getting longer. Thus the effects of a climate change can differ considerably from region to region.

Outlook

The regionally quite different changes of the climatic situation in Rhineland-Palatinate will not remain without an effect on the ecosystems of this federal state. The currently existing biocoenosis will therefore change. The consequences for forestry, agriculture and nature conservation are of special interest in this context.     

Public Participation and Local Environmental Planning: The collective action problem and the potential of social capital

Expanding the opportunities for public participation in environmental planning is not always the best option. Starting from an institutional public choice analysis of public participation in terms of the collective action problem, this paper emphasises the roots of participatory activities in the incentive structures facing potential participants. It then goes on to consider the strategies that may be adopted for encouraging greater public involvement and looks particularly to the social capital literature for suggestions of how institutional redesign may alter these incentive structures. The paper concludes by distinguishing three different modes of environmental planning, in terms of the rationale for participation, the severity of the collective action problem and the associated participatory strategy that can be adopted.