Suchergebnisse

Although modern location theory is now more than 90 years old, the focus of researchers in this area has been mainly problem oriented. However, a common theory, which keeps the essential characteristics of classical location models, is still missing. This monograph addresses this issue. A flexible location problem called the Ordered Median Problem (OMP) is introduced. For all three main subareas of location theory (continuous, network and discrete location) structural properties of the OMP are presented and solution approaches provided. Numerous illustrations and examples help the reader to become familiar with this new location model. By Using OMP classical results of location theory can be reproved in a more general and sometimes even simpler way. Algorithms enable the reader to solve very flexible location models with a single implementation. In addition, the code of some algorithms is available for download. TOC:Location Theory and the Ordered Median Function.- The Continuous Ordered Median Location Problem.- Ordered Median Location Problems on Networks.- The Discrete Ordered Median Location Problem

Main description: Die Steuerung von Krankenhäusern im Zeitalter der Diagnosis Related Groups erfordert eine systematische und wissensbasierte Herangehensweise. Erfahrung, Intuition und Fachkompetenz in Medizin, Pflege oder allgemeiner Verwaltung genügen nicht mehr, um die komplexen und dynamischen Krankenhausbetriebe zu führen. Das vorliegende Lehrbuch entwickelt Instrumente der Krankenhaussteuerung und fügt sie in den Zusammenhang der Krankenhausbetriebslehre ein. Schwerpunkte sind hierbei Management, Controlling, Logistik, Informationswirtschaft und Strategie des Krankenhausbetriebes. Der Leser wird nicht nur schnell umsetzbare Methoden kennenlernen, sondern vor allem eine Denkweise erwerben: eine evidenzbasierte, zielsystemkonforme und nachhaltige Steuerung des Krankenhausbetriebes in einem Gleichgewicht aus Effizienz und Verantwortung.

Abstract

Background
The aim of the study was a statistical evaluation of the statistical relevance of potentially explanatory variables (atmospheric deposition, meteorology, geology, soil, topography, sampling, vegetation structure, land-use density, population density, potential emission sources) correlated with the content of 12 heavy metals and nitrogen in mosses collected from 400 sites across Germany in 2015. Beyond correlation analysis, regression analysis was performed using two methods: random forest regression and multiple linear regression in connection with commonality analysis.


Results
The strongest predictor for the content of Cd, Cu, Ni, Pb, Zn and N in mosses was the sampled species. In 2015, the atmospheric deposition showed a lower predictive power compared to earlier campaigns. The mean precipitation (2013–2015) is a significant factor influencing the content of Cd, Pb and Zn in moss samples. Altitude (Cu, Hg and Ni) and slope (Cd) are the strongest topographical predictors. With regard to 14 vegetation structure measures studied, the distance to adjacent tree stands is the strongest predictor (Cd, Cu, Hg, Zn, N), followed by the tree layer height (Cd, Hg, Pb, N), the leaf area index (Cd, N, Zn), and finally the coverage of the tree layer (Ni, Cd, Hg). For forests, the spatial density in radii 100–300 km predominates as significant predictors for Cu, Hg, Ni and N. For the urban areas, there are element-specific different radii between 25 and 300 km (Cd, Cu, Ni, Pb, N) and for agricultural areas usually radii between 50 and 300 km, in which the respective land use is correlated with the element contents. The population density in the 50 and 100 km radius is a variable with high explanatory power for all elements except Hg and N.


Conclusions
For Europe-wide analyses, the population density and the proportion of different land-use classes up to 300 km around the moss sampling sites are recommended.

Abstract

Background
This article presents statistical analyses of elements concentrations in mosses collected in two monitoring programmes: 1. The German moss monitoring as part of the European Moss Survey conducted in 1990, 1995, 2000, 2005 and 2015 at 592, 1026, 1028, 726 and 400 sites across Germany, respectively, and chemically analysed according to harmonised methods throughout Europe; and 2. The moss surveys additionally performed throughout Bavaria, federal state of Germany. The evaluations of the present study are intended to examine indications whether the element accumulations are specific to moss species and whether, therefore, conversion factors should be used. Such observations and recommendations have so far been limited to spatially confined areas and relatively few moss samples and were derived from different studies without a common methodology. Therefore, the objective of this investigation was to analyse large and long-term datasets from moss surveys for differences in element concentrations in different moss species. This analysis was based on data derived from several moss species collected across Germany and specimens of only one moss species collected in the monitoring programme performed by the environmental authority of Bavaria. So far, the presented investigation is the most comprehensive one in terms of running time, spatial density of the measurement network and method harmonisation.


Results
The present study does neither verify nor falsify the hypothesis of moss species-specific element accumulations in mosses. This, like the other studies, is not possible because of its empirical design, since that would require strictly controlled laboratory experiments. However, this investigation yielded hints, that the differences in element accumulation in several moss species across German surveys between 1990 and 2015 are in the range of the intra- and inter-specific variance reported.


Conclusion
It is, therefore, advisable to continue dispensing with conversion factors so far.

Abstract
Background
Atmospheric deposition of nitrogen and climate change can have impacts on ecological structures and functions, and thus on the integrity of ecosystems and their services. Operationalization of ecosystem integrity is still an important desideratum.

Results
A methodology for classifying the ecosystem integrity of forests in Germany under the influence of climate change and atmospheric nitrogen deposition is presented. The methodology was based on 14 indicators for six ecosystem functions: habitat function, net primary function, carbon sequestration, nutrient and water flux, resilience. It allows assessments of ecosystem integrity changes by comparing current or prospective ecosystem states with ecosystem-type-specific reference states as described by quantitative indicators for 61 forest ecosystem types based on data before 1990.

Conclusion
The method developed enables site-specific classifications of ecosystem integrity as well as classifications with complete coverage and determinations of temporal trends as shown using examples from the Thuringian Forest and the "Kellerwald-Edersee" National Park (Germany).