Langzeitmonitoring möglicher Auswirkungen gentechnisch veränderter Pflanzen auf Pflanzengesellschaften Konzeptentwicklung am Beispiel von Raps (Brassica napus)

Ecological monitoring of genetically engineered plants (GEPs) is being developed in the Bavarian Environmental Protection Agency. Focusing on oilseed rape (Brassica napus, Cruciferae), a method is being established to measure the impact of the commercial release of GEPs on plant communities. Oilseed rape is known to escape from cultures and to establish outside the fields. It also produces hybrid offspring with wild relatives of the European flora. The study site is located in Bavaria (Germany) and comprises an area of 5700 ha. It is characterized by a mosaic of protected natural habitats in close vicinity to intensively cultivated farmland. In this region species composition and population density of Cruciferae is documented prior to a possible commercial release of GEPs. Furthermore Cruciferae of the study site are tested for the presence of transgenes. Therefore, plant material of selected Cruciferae is randomly sampled. We also test oilseed rape honey from the study site and pollen from pollen traps for the presence of hybrid pollen. The molecular method used is the ‘real-time PCR’. In addition, an intensive monitoring program is established in two types of biotopes, which are located in the study site. Multivariate statistics are being used to correlate plant community data with soil parameters.     

A Preliminary Study of Modeling the Air Pollution Effects fromTraffic Engineering Alternatives

Three separate mathematical models were combined to calculate the changes in carbon monoxide (CO) concentrations that might result from traffic engineering changes. The three models used were: (1) The Dynamic Highway Transportation model (DHTM) which relates traffic flow patterns to physical parameters and traffic signal characteristics of a network; (2) an emission model that predicts CO emissions from traffic flow parameters such as number of stops, idling time, etc; and (3) the APRAC-1A urban diffusion model which calculates CO concentrations from source distributions and meteorological factors. The composite model was applied to traffic in downtown Chicago for a specific set of meteorological conditions. Results are compared for two traffic signal control schemes. In those blocks where concentrations were highest, the model indicates a 20% reduction is possible through improved traffic signal controls. The model should be useful for testing other traffic control measures.     

Communicative diagnosis of cost-saving options for reducing nitrogen emission from pig finishing

Reducing nitrogen emission from livestock production is usually perceived as costly. Nevertheless, production process related measures addressing the transformation of input(s) into output(s) may result in a cost-saving reduction of nitrogen emission. This paper explores the separate and combined use of traditional key performance indicators and an environmentally adjusted Data Envelopment Analysis (DEA) to reveal firm-specific cost-saving mechanisms for pig-finishing farms. Traditional key performance indicators are easy to communicate but have shortcomings when assessing benchmarks for comparative farm analysis. The environmentally adjusted DEA decomposes both cost and environmental efficiencies into technical and allocative efficiency components, separating the physical production analysis from price and nutrient content information. DEA makes efficiency benchmarks and improvement paths explicit, but the practical value of such efficiency scores is low. This paper proposes to take advantage of both methods: concrete benchmarks and eligible improvement paths are assessed using frontier methods, while the decision variables that steer farmers towards changes are described in terms of traditional key performance indicators. This leads to an improved diagnosis that is easy to communicate to farmers and may therefore facilitate decision support. Our pig-finishing case study shows that farms can achieve economic-environmental win–win situations through improving technical, cost allocative and cost efficiencies, which are mainly driven by feed conversion. Less technical efficient farms are found to require a lower delivery weight in order to minimize costs, which shows the farm-specificity of economic-environmental improvement advice.     

Dose-response relationships in mutagenicity assays including an appropriate positive control group: a multiple testing approach

The objective of mutagenicity assays in regulatory toxicology is the decision on non-mutagenicity or mutagenicity. An inherent problem of statistical tests is the possibility of false decisions, i.e., a mutagenic substance will be falsely labeled as non-mutagenic or a non-mutagenic substance will be falsely labeled as mutagenic. These probabilities of false negative (consumer's risk=type II error) and/or false positive decision (producer's risk=type I error) can be limited by using suitable testing procedures as well as a design including an appropriate positive control. Using the proof of hazard concept the well-known many-to-one procedures with total order restriction for increasing effect differences are used, while using the proof of safety concept procedures on equivalence with total order restriction are discussed. Both approaches are demonstrated on a real data example.