Spatial isolation and genetic differentiation in naturally fragmented plant populations of the Swiss Alps

Aims The effect Of anthropogenic landscape fragmentation on the genetic diversity and adaptive potential of plant populations is a major issue in conservation biology. However, little is known about the partitioning of genetic diversity in alpine species, which occur in naturally fragmented habitats. Here, we, investigate molecular patterns of three alpine plants (Epilobium fleischeri, Geum reptans and Campanula thyrsoides) across Switzerland and ask whether Spatial isolation has led to high levels of populations differentiation, increasing over distance, and a decrease of within-population variability. We further hypothesize that file contrasting potential for long-distance dispersal (LDD) of Seed in these Species will considerably influence and explain diversity partitioning. Methods For each study species, we Sampled 20-23 individuals from each of 20-32 populations across entire Switzerland. We applied Random Amplified Polymorphic Dimorphism markers to assess genetic diversity within (Nei's expected heterozygosity, H-e; percentage of polymorphic hands, P-P) and among (analysis of molecular variance, Phi(st)) populations and correlated population size and altitude with within-populalion diversity. Spatial patterns of genetic relatedness were investigated using Mantel tests and standardized major axis regression as well as unweighted pair group method with arithmetic mean cluster analyses and Monmonier's algorithm. To avoid known biases, We standardized the numbers of populations, individuals and markers using multiple random reductions. We modelled LDD with a high alpine wind data set using the terminal velocity and height of seed release as key parameters. Additionally, we assessed a number of important life-history traits and factors that potentially influence genetic diversity partitioning (e.g. breeding system, longevity and population size). Important findings For all three species, We found a significant isolation-by-distance relationship but only a moderately high differentiation among populations (Phi(st): 22.7, 48 and 16.8%, for E. fleischeri, G. reptans and C. thyrsoides, respectively). Within-population diversity (H-c: 0.19-0.21, P-p: 62-75%) was not reduced in comparison to known results from lowland species and even small populations with < 50 reproductive individuals contained high levels of genetic diversity. We further found no indication that a high long-distance seed dispersal potential enhances genetic connectivity among populations. Gene flow seems to have a strong stochastic component causing large dissimilarity between population pairs irrespective of the spatial distance. Our results suggest that other life-history traits, especially the breeding System, may play an important role in genetic diversity partitioning. We conclude that spatial isolation in the alpine environment has a strong influence on population relatedness but that a number of factors can considerably influence the strength of this relationship.

Is differentiation of frequently encountered foreign bodies in corpses possible by Hounsfield density measurement?

The radiological determination of foreign objects in corpses can be difficult if they are fragmented or deformed. With multislice computed tomography, radiodensities--referred to as Hounsfield units (HU)--can be measured. We examined the possibility of differentiating 21 frequently occurring foreign bodies, such as metals, rocks, and different manmade materials by virtue of their HU values. Gold, steel, and brass showed mean HU values of 30671-30710 (upper measurable limit), mean HU values for steel, silver, copper, and limestone were 20346, 16949, 14033, and 2765, respectively. The group consisting of objects, such as aluminum, tarmac, car front-window glass, and other rocks, displayed mean HU values of 2329-2131 HU. The mean HU value of bottle glass and car side-window glass was 2088, whereas windowpane glass was 493. HU value determination may therefore help in preautopsy differentiation between case-relevant and irrelevant foreign bodies and thus be useful for autopsy planning and extraction of the objects in question.

A Calculus of Evolving Objects

The demands of developing modern, highly dynamic applications have led to an increasing interest in dynamic programming languages and mechanisms. Not only applications must evolve over time, but the object models themselves may need to be adapted to the requirements of different run-time contexts. Class-based models and prototype-based models, for example, may need to co-exist to meet the demands of dynamically evolving applications. Multi-dimensional dispatch, fine-grained and dynamic software composition, and run-time evolution of behaviour are further examples of diverse mechanisms which may need to co-exist in a dynamically evolving run-time environment How can we model the semantics of these highly dynamic features, yet still offer some reasonable safety guarantees? To this end we present an original calculus in which objects can adapt their behaviour at run-time to changing contexts. Both objects and environments are represented by first-class mappings between variables and values. Message sends are dynamically resolved to method calls. Variables may be dynamically bound, making it possible to model a variety of dynamic mechanisms within the same calculus. Despite the highly dynamic nature of the calculus, safety properties are assured by a type assignment system.

A Calculus of Evolving Objects

The demands of developing modern, highly dynamic applications have led to an increasing interest in dynamic programming languages and mechanisms. Not only must applications evolve over time, but the object models themselves may need to be adapted to the requirements of different run-time contexts. Class-based models and prototype-based models, for example, may need to co-exist to meet the demands of dynamically evolving applications. Multi-dimensional dispatch, fine-grained and dynamic software composition, and run-time evolution of behaviour are further examples of diverse mechanisms which may need to co-exist in a dynamically evolving run-time environment. How can we model the semantics of these highly dynamic features, yet still offer some reasonable safety guarantees? To this end we present an original calculus in which objects can adapt their behaviour at run-time. Both objects and environments are represented by first-class mappings between variables and values. Message sends are dynamically resolved to method calls. Variables may be dynamically bound, making it possible to model a variety of dynamic mechanisms within the same calculus. Despite the highly dynamic nature of the calculus, safety properties are assured by a type assignment system.